Department Of Psychology, Royal Holloway, University Of London, Egham Hill, Egham, TW20 0EX, United Kingdom
Abstract
Despite the known risks of recreational substance use, it remains widespread worldwide, with millions of individuals using substances like cannabis, cocaine, and MDMA each year. These substances primarily affect neurotransmitter systems, including the endocannabinoid, serotonergic, and dopaminergic systems, which are integral to cognitive functions. This review examines both the acute and long-term effects of cannabis, cocaine, and MDMA on key cognitive domains, specifically retrospective memory, prospective memory, and executive functions. After briefly reviewing the neurochemical mechanisms underlying their actions in the brain, the review provides an overview of the cognitive impairments linked to these substances. However, the interpretation of these findings is complicated by research challenges such as polydrug use, participant recruitment issues, poor control of confounds, and difficulties in establishing causality.
Keywords
Cannabis; Cocaine; Cognition; Episodic memory; Executive functions; MDMA; Prospective memory; Recreational substance use; Retrospective memory
Introduction
Recreational substances refer to chemical substances used casually and without dependence, primarily for enjoyment rather than for medical purposes. While substances like alcohol, tobacco, and caffeine can also fall under this category, this review focuses specifically on cannabis, MDMA, and cocaine. The recreational use of these substances are illegal in many countries, including the United Kingdom. Despite the risks, illegal recreational substance use remains high worldwide. According to the United Nations Office on Drugs and Crime's World Drug Report 2022, 284 million people aged 15-64 used substances at least once in the previous year, up from 226 million in 2010 (26% increase). This is around 1 in every 18 persons, or 5.6% of the population of the world in that age group. The Report further noted that substance use is much more common among young people [1].
The most commonly used illegal recreational substance is cannabis, followed by cocaine, MDMA [2]. Therefore, this review primarily explores the cognitive effects of cannabis, cocaine, and MDMA on key cognitive domains such as memory and executive functions. These substances are thought to affect cognition by disrupting neurotransmitter systems essential for these cognitive processes [3]. The review begins with an overview of the neurochemical pathways through which these substances influence brain function, followed by a summary of the literature on their cognitive effects. While a comprehensive analysis is beyond the scope of this review, the following overview aims to provide insight into the mechanisms of action of these substances and their potential impact on cognitive functioning.
Effects of Commonly Used Substances on the Brain
Substances affect the brain primarily by interacting with various neurotransmitter systems. While their exact mechanisms are not fully understood, advanced research techniques have provided valuable insights. This section explores how the most commonly used recreational substances (namely cannabis, MDMA, and cocaine) alter neurotransmitter activity and their potential connections to cognitive functions.
Cannabis, typically smoked, releases compounds like Δ9-tetrahydrocannabinol (THC; the primary psychoactive component) and cannabidiol (CBD; a non-psychoactive, medically used compound) into the bloodstream [4,5]. While its exact mechanisms remain unclear, cannabis may impact cognition by interacting with the Endocannabinoid System (ECS), which includes endogenous cannabinoids, receptors (CBs), and enzymes [6]. The ECS regulates neurotransmitter systems, including dopamine [7,8]. THC primarily activates CB receptors [9,10], which are densely located in brain regions like the hippocampus, amygdala, basal ganglia, and prefrontal cortex [11,12]. Disruption of the ECS may affect neurobehavioral processes such as learning, memory, motivation, motor control, reward processing, and executive functions [13-16]. Neuroimaging studies support this, showing reduced Prefrontal Cortex (PFC) size and activity in heavy cannabis users, linked to the disruption of endocannabinoid-mediated synaptic plasticity [17-20]. Animal studies further corroborate these findings [21-23].
MDMA (3,4-Methylenedioxymethamphetamine) is a synthetic stimulant derived from amphetamine, commonly found in crystallized or tablet form. The powder form, typically referred to as MDMA, usually contains pure MDMA, while the tablet form, known as ecstasy or Molly, is often mixed with various other substances. MDMA primarily affects neurotransmitter systems by promoting serotonin (5-HT) release from presynaptic neurons, reversing the serotonin transporter’s which normally recycles serotonin), and subsequently increasing 5-HT availability at postsynaptic receptors [24,25].
Although its precise mechanisms remain unclear, MDMA primarily influences cognition through the serotonergic system, which plays a key role in memory, attention, and perception [26,27]. For example, serotonin depletion, induced through acute tryptophan depletion, has been shown to impair memory [28-31], whereas increasing serotonin levels via selective serotonin reuptake inhibitors is linked to memory improvements [32]. Long-term MDMA use is associated with reduced serotonin signalling, as neuroimaging studies reveal decreased Serotonin Transporter (SERT) binding in the frontal, parietal, and temporal lobes [33-36]. A meta-analysis confirmed widespread reductions in SERT binding in the brain [37,38]. Those findings might explain the observed cognitive impairments in people with a history of MDMA use. Animal studies further support MDMA-induced serotonergic disruption and memory impairments [39,40]. Additionally, MDMA interacts with the glutamatergic and dopaminergic systems [41-44], which may contribute to broader cognitive deficits, particularly in learning and memory.
Cocaine is a stimulant substance derived from the Erythroxylum coca plant, available in forms like powdered cocaine (snorted) and crack cocaine (smoked or injected). Cocaine exerts its effects by blocking or slowing down the monoamine transporters, in particular those for Dopamine (DA). This action primarily increases DA levels, as well as serotonin and Norepinephrine (NE) in the brain [45]. As a result, cognitive deficits related to cocaine use are believed to arise from disruptions in the DA system, which plays a crucial role in memory, executive functions, and attention. For instance, DA neurons increase firing in response to salient stimuli in areas like the hippocampus and Ventral Tegmental Area (VTA), which are involved in encoding new, episodic-like memories [46]. Furthermore, Otmakhova and Lisman found that dopamine receptors (D1 and D5) enhance glutamatergic transmission, facilitating memory encoding [47]. Animal studies support this, with Li et al., showing that DA levels rise when animals encounter new environments, but this improved memory is lost when hippocampal DA receptors are blocked [48]. Additionally, DA is known to regulate executive functions, particularly working memory [49,50].
Cocaine has been shown to reduce DA neuron activity, leading to decreases in DA release and DA receptors’ functions [51]. This suggests that cocaine-induced cognitive impairments may primarily result from disruptions to the dopamine system. It is important to note that several studies have argued that cocaine-related cognitive deficits are driven by long-lasting neuroplastic changes in Prefrontal Cortex (PFC) circuitry, rather than direct cell damage or neurotoxicity [52,53]. Additionally, cocaine use has been associated with significant white matter changes in the brain [54-56].
Challenges in Conduction Studies on the Effects of Substance Use on Cognition
It is important to highlight the challenges involved in conducting studies on the effects of substance use before reviewing the relevant literature, as these challenges must be considered when interpreting the findings.
Polysubstance use, or the combined use of multiple substances, is common among people with a history of substance use [57]. Individuals often combine substances to achieve specific effects, such as the combination of cocaine and ketamine produces intense euphoric highs along with hallucinations [58]. They may also mix substances to counteract negative effects, like using cannabis to help sleep after consuming stimulants like MDMA or cocaine [59]. The widespread availability of various substances further encourages polysubstance use [60]. Polysubstance use complicates studies on substance-related cognitive effects, as different substances interact through distinct neural mechanisms, making it difficult to isolate the impact of one substance [61]. Researchers have attempted to address this by examining ecstasy users with minimal other substance use [62] or comparing MDMA polysubstance users to non-users [63], but these strategies still struggle to fully capture the complex interactions of multiple substances.
- Difficulties to recruiting participants
Another challenge is recruiting substance-using populations who are difficult to reach and may actively conceal their identities due to concerns about legal consequences [64]. The illegal status of many substances and the threat of imprisonment can discourage individuals from participating in research [65]. For instance, in the UK, illicit substances are classified into four categories, each carrying different penalties for possession and distribution. Possessing Class B substances (e.g., cannabis), and Class A substances (e.g., cocaine, MDMA) can result in up to 5, or 7 years in prison, respectively, along with fines. Consequently, many studies suffer from small sample sizes (often averaging around 30 participants; [66]), limiting the ability to generalise findings.
- The causality between substance use and cognitive impairments
Most studies examining the long-term effects of substance use on cognition rely on cross-sectional designs, which collect data from participants at a single point in time. These studies lack prospective or retrospective follow-up, making it challenging to draw causal conclusions between substance use and cognitive impairments. It is possible that cognitive deficits may be present prior to first substance use which can act as a risk factor for substance use initiation [67].
- Poor control for confounding variables
Many studies neglect to account for potential confounding variables such as age, education, depression, sleep quality, and IQ, all of which have been shown to impact cognitive functions [68-76]. In line with this, a comprehensive review highlights that the majority of studies in this area have not properly controlled for these critical confounds [53].
- Issues in defining and measuring levels of illicit substance use
Inconsistent definitions and measurements of illicit substance use, such as frequency, duration, dosage, age at first use, and total lifetime consumption pose a significant challenge to drawing definitive conclusions about their effects. The lack of a standardised framework to classify substance use as heavy, moderate, or light further complicates the interpretation of findings across studies. For example, the same level of ecstasy use (e.g., 400 tablets) may be classified as "heavy" in one study [77] and "moderate" in another [78]. This lack of consistency creates confusion and hinders the ability to make clear, comparable conclusions across research on the effects of illicit substance use.
- Lack of substance-naïve control groups
Many studies on the cognitive effects of illicit substance use lack substance-naïve control groups. Instead, the non-user groups often include individuals who have used other substances, such as cannabis. While statistical methods can control for the influence of these substances, it is impossible to eliminate their effects entirely. This limitation introduces potential confounding factors, making it difficult to attribute observed cognitive deficits solely to the substance under investigation. As a result, findings may be less conclusive, and the true extent of substance-specific effects on cognitive functions remains unclear.
- Generalisability of study findings
Most studies on substance use have been conducted in industrialised nations, such as the United Kingdom and the United States [79], with predominantly white participants. However, substance use prevalence has been reported as higher among individuals from non-white ethnic backgrounds, such as those of mixed race [80]. This may reflect underreporting among non-white individuals, potentially influenced by racial bias within the criminal justice system, where substance-related arrests disproportionately affect minority groups. For instance, Black, Asian, and minority ethnic individuals are 240% more likely to be imprisoned for substance-related offences compared to white offenders [81]. It has been suggested that substance use may have different, potentially more severe, impacts on minority groups [82], though this remains under-researched. Consequently, the findings from these studies may not be fully generalisable beyond white/western populations.
Effects of Commonly Used Substances on Cognitive Functions
Establishing a direct link between recreational substance use and cognitive impairment is complex due to various factors. However, this section aims to clarify substance-induced cognitive changes by reviewing key literature on human participants, providing insights into how these substances may disrupt cognitive processes. While animal studies offer valuable insights, the focus here is on human studies to better understand the real-world impact of substance use on cognition. Evidence on the possible effect of recreational substance use on cognitive functions comes from two lines of research: retrospective studies and placebo-controlled studies. In placebo-controlled studies, participants receive either a dose of the substance or a placebo to measure its acute effects on cognition, providing insights into how substances affect neurocognitive functioning during intoxication. However, it is important to note that these studies often include people with regular or occasional substance use, with substance-naïve controls rarely being included. Retrospective studies, on the other hand, compare current or abstinent substance users with drug-naïve individuals or non-specific substance users (e.g., people with a history of cocaine use vs. those with non-cocaine polysubstance use), offering valuable insights into long-term cognitive deficits that may persist even after acute intoxication has subsided.
Cognitive functioning encompasses a range of mental processes involved in acquiring knowledge, processing information, and reasoning. It includes abilities such as learning, memory, attention, and problem-solving- skills essential for navigating daily life, making decisions, and interacting with the world. The relevant literature will be discussed under three subheadings: retrospective memory, prospective memory, and executive functions.
Retrospective memory
Memory is one of the most crucial cognitive functions in a person’s life for tasks like communication, learning, and developing personality. It involves encoding, storing, and recalling information [83]. Information is encoded through perception and association with prior knowledge, then stored for later retrieval. Memory is often classified under two broad concepts: retrospective and prospective memory. Retrospective memory involves memory of events, people or experimental stimuli that were experienced in the past, such as remembering the detail of a friend’s birthday party or recalling a list of words presented in an experiment. Whereas, prospective memory involves remembering to carry out a planned action or recall a planned intention at some future point in time. When studying explicit forms of retrospective memory, particularly objective episodic memory, participants are typically asked to learn specific materials (e.g., a list of words). After a predefined delay, they are then prompted to intentionally retrieve the learned information through free recall, cued recall, or recognition tasks. Retrospective memory can also be assessed via autobiographical memory tests, which focus on evaluating subjective episodic memory.
The following sections will first review the literature on the acute and long-term effects of commonly used illicit substances on objective episodic memory and then subjective episodic memory.
Objective episodic memory via learning tests
Cannabis has been extensively studied for its acute effects on learning and memory where participants were given a single dose of THC and tested. Numerous studies have consistently demonstrated that THC can impair learning and memory processes [84-90]. Additionally, several review papers further supported the evidence for THC’s negative impact on learning and memory [8,17,91-94]. As aforementioned, cannabis contains two main active compounds: THC, responsible for its psychoactive effects, and CBD, which appears to counteract some of THC’s cognitive impairments. For instance, Englund et al., found that pre-treatment with CBD reduced THC-induced cognitive deficits. In their study, participants who received oral CBD before intravenous THC performed better on verbal learning tasks, compared to those given a placebo [85]. Similarly, Morgan et al., reported that individuals using low-CBD cannabis showed poorer performance on verbal learning tasks compared to those using high-CBD strains [95]. These findings suggest that high-THC/low-CBD cannabis is associated with greater cognitive dysfunction.
A recent report showed that THC potency has increased significantly over recent decades, rising from 4% in 1995 to 9.75% in 2009, and 13.88% in 2019, while CBD content has remained comparatively low, rising only from approximately 0.28% in 2001 to 0.39% in 2009, and 0.56% in 2019 in the USA [96-98]. A United Nations report further shows that cannabis potency has quadrupled in parts of the world over the past 24 years [1]. This trend raises concerns about the potential for more severe cognitive impairments in current cannabis users, especially with high-THC, low-CBD strains.
Although research on the acute effects of MDMA on learning and memory is limited, existing studies consistently suggest a negative impact. For example, Kuypers et al., reported significant impairments in verbal memory performance on the Word Learning Task following MDMA administration [99]. These findings have been consistently replicated, with MDMA-intoxicated individuals performing worse on verbal learning tasks compared to placebo controls [100-104]. Most of these studies were conducted in controlled, daytime laboratory settings, which may limit their ecological validity. However, a few studies have examined the effects of MDMA on verbal learning during real-world nighttime settings, yielding similar results [105,106]. A recent review further confirmed MDMA’s negative impact on memory, with 16 studies reporting acute memory impairments across 23 different tasks [107].
Research on the acute effects of cocaine on learning and memory is limited [108]. Existing studies have found no significant impact on learning following intranasal cocaine administration in recreational users [109-111].
In summary, the acute effects of recreational substances on objective episodic memory differ across substances. Cannabis, particularly due to THC, consistently impairs learning and memory, with higher THC and lower CBD levels linked to greater deficits. MDMA also negatively impacts learning and memory both in controlled laboratory settings and real-world environments. In contrast, acute cocaine use appears to have no effects on learning and memory, though research on this is limited.
Existing literature on the long-term cognitive effects of cannabis use predominantly relies on cross-sectional studies, where cannabis users, after a period of abstinence, are compared to non-users on cognitive performance. These studies consistently report that regular cannabis users who have been abstinent for periods ranging from 12 hours to 21 days demonstrate poorer immediate and delayed recall [112-119]. Multiple reviews suggest that long-term or heavy cannabis use impairs key memory processes, including encoding, storage, manipulation, and retrieval [8,17,91,92,120-122]. These impairments are closely linked to the frequency, duration, quantity, and age of onset of cannabis use [91,118,122,123].
However, not all studies align with these findings. A small number of investigations have reported no significant association between cannabis use and learning deficits [124-126]. Given the limitations of cross-sectional designs, which may reflect individual factors rather than direct effects of cannabis use, the need for longitudinal studies becomes apparent. Longitudinal designs can track cognitive changes over time, offering stronger evidence for causal relationships between cannabis use and cognitive outcomes. For example, a study of chronic daily adolescent-onset cannabis users showed that verbal memory deficits observed at baseline persisted after two years of continued heavy use [127,128]. Another longitudinal study also found that greater cannabis use was associated with poorer episodic memory, especially for immediate recall [129]. In line with these findings, a review of longitudinal studies showed that episodic memory performance was the measure most likely affected by persistent cannabis use [130].
While the evidence points to cannabis-related cognitive impairments, there is growing consensus that these effects may be reversible following extended abstinence. For instance, Medina et al., found that after 30 days of abstinence, cannabis users exhibited only subtle deficits in episodic memory compared to controls [131]. Similarly, Hanson et al., observed significant improvements in verbal learning among adolescent cannabis users after two weeks of abstinence [114]. A meta-analysis by Schreiner and Dunn further supports this notion, reporting no significant cognitive deficits in individuals abstinent from cannabis for at least 25 days across various domains, including learning, and memory [132].
More recent research by Burke et al., examined cognitive performance in heavy cannabis users after periods of abstinence ranging from 3 days to over 90 days. The results indicated that cognitive impairments were detectable during short-term abstinence but largely remitted after 90 days [133]. Similarly, Fried et al., found that learning deficits in young adults who were former heavy cannabis users were no longer apparent three months after cessation of use [134]. These results suggest that the brain may adapt to or compensate for the effects of chronic cannabis use over time. However, the extent of recovery may depend on factors such as lifetime use and dosage, with high lifetime use potentially limiting recovery [135].
Similar to cannabis studies, MDMA studies also primary used cross sectional study design to investigate long-terms effects of MDMA on learning and memory. Multiple studies found the similar results where MDMA users impaired in learning tasks [63,121,124,125,136-140]. Furthermore, it has been well documented that there is a dose-dependent association between ecstasy use and poorer verbal learning and memory abilities where people with moderate to heavy ecstasy/polysubstance use performed significantly worse on learning tasks than those with very mild ecstasy/polysubstance use or drug naïve controls [136,141–144]. Furthermore, a limited number of longitudinal studies have been conducted to assess the relationship between ongoing MDMA use and cognitive performance in novice MDMA users, addressing the methodological limitations of cross-sectional designs. In one such study, the group of incident Ecstasy users showed significantly greater declines in immediate and delayed recall and recognition compared to persistent Ecstasy-naive participants [62]. Such a decline on learning and memory abilities in new MDMA users was evident in other follow-up studies [145]. However, another follow-up study found no significant changes in cognitive performance among MDMA users, controlling for potential confounders such as age, sleep patterns, subjective well-being, recent medical treatments, sports participation, nutrition, and general intelligence [146].
A comprehensive review by Kalechstein et al., assessed the effects of MDMA on learning and memory using two approaches: one with stringent inclusion/exclusion criteria to match participants on key moderator variables and another with more lenient criteria. Analysis of 11 studies using the stricter criteria and 23 studies with more flexible criteria both revealed that MDMA use is associated with impairments in learning and memory [147]. These findings were further supported by a meta-analysis of 21 studies, which found significant negative effects of MDMA use on learning and memory [148].
Several studies have also examined whether cognitive impairments from MDMA use persist after cessation. Reneman et al., found that both recent and former MDMA users (abstinent for over 12 months) performed worse than controls on learning tasks [36]. Similarly, other studies reported poor learning performance in former users [149,150], suggesting that the effects of MDMA may be long-lasting. A follow-up study by Thomasius et al., indicated that memory impairments could persist for over 2.5 years after cessation [151]. These findings align with a review by Klugman and Gruzelier, which concluded that ecstasy-related cognitive impairments, particularly in memory, may endure even after prolonged abstinence [152].
Extensive research has shown that repeated cocaine use is associated with learning and memory impairments [153-164,165]. These deficits appear to be particularly pronounced in individuals with cocaine dependence [154-158,161,162,164,165]. A meta-analysis of 46 studies, including 1,452 chronic cocaine users and 1,411 controls, found moderate cognitive impairments across eight domains, including learning and memory, during intermediate abstinence [166]. Similarly, another review reported moderate deficits in immediate and delayed recall among cocaine users [108].
Some studies suggest that cognitive impairments may be reversible after sustained abstinence. A longitudinal study by Vonmoos et al., found that, following moderate cocaine exposure, cognitive deficits significantly improved within one year of abstinence [167]. Additionally, a meta-analysis reported that long-term abstinence (five months or more) was associated with only small effect sizes for learning and memory deficits, suggesting the potential for cognitive recovery over time [166].
Overall, the evidence suggests that chronic use of cannabis, MDMA, and cocaine is associated with impairments in objective episodic memory. Cross-sectional studies consistently report deficits among long-term users of these substances, with heavy or prolonged use leading to more pronounced impairments. However, findings from longitudinal research indicate that while some cognitive deficits may persist, recovery is possible with sustained abstinence, particularly in cannabis and cocaine users.
Subjective episodic memory via autobiographical memory tests
Autobiographical Memory (AM) is a type of retrospective memory that encompasses recollections of events from an individual's life, combining subjective episodic memory (personal experiences involving specific people, places, and events at particular times) with semantic memory (general knowledge and facts about the world). AM is thought to be a vital part of one’s life since it aids in self-awareness, interpersonal connections, decision-making, and stress management [168]. Despite the importance of AM, research into the effects of recreational substance use on this memory system is very limited, with most studies focusing on cannabis use and occasional investigations into substances like MDMA.
- Acute and Long-term effects
Research on cannabis use and AM has largely focused on its long-term effects. Pillersdorf and Scoboria found that chronic cannabis users (defined as at least 3-4 uses per month for a year) exhibited reduced specificity in AM compared to non-users. This suggests that cannabis may impair the ability to retrieve detailed past experiences [169]. Similarly, Mercuri et al., reported that regular cannabis users (at least three times per week) performed worse on autobiographical interviews than both recreational users and non-users, highlighting the role of frequency in AM deficits [170]. Further evidence of a dose-dependent effect was provided by Sofis et al., who found that more frequent cannabis use was associated with reduced specificity and emotional richness in recent positive autobiographical memories [171]. This aligns with longitudinal findings by Gandolphe and Nandrino, which demonstrated that increasing cannabis use over time correlated with declining specificity in both positive and negative autobiographical recollections [172].
The effects of MDMA on AM have primarily been explored in the context of acute use. In a double-blind, placebo-controlled study, Doss et al., investigated MDMA's impact on emotional memory. Participants viewed emotionally neutral, negative, and positive images paired with descriptive labels before completing memory tests 48 hours later. MDMA administration during encoding or retrieval impaired the recollection of emotional events, while recognition memory remained unaffected [173]. These findings suggest that MDMA specifically disrupts the recollection component of AM, rather than general memory function.
Although less extensively studied, research suggests that substance dependencies, including cocaine dependence, may also impair autobiographical memory. Studies have reported that individuals with cocaine dependence exhibit reduced specificity in AM compared to non-using controls [174,175].
Research on AM is very limited, but the existing literature suggest that cannabis, MDMA, and cocaine use can negatively impact AM. Chronic cannabis use, particularly with higher frequency, is associated with reduced specificity and emotional richness in AM.
Prospective memory
Prospective Memory (PM) refers to the ability to remember to execute future intentions [176,177]. This crucial cognitive function underlies everyday activities, ranging from simple tasks like remembering to buy groceries to more critical ones like remembering taking daily medications. Indeed, individuals who forgot to take their blood pressure medication were found to have a higher likelihood of experiencing a heart attack or dying compared to those who remembered [178].
The existing literature is very limited and mixed. One study with a double-blind, placebo-controlled study found that cannabis impaired performance across various memory tasks, including PM [179]. On the contrary, other two studies found no acute effects of cannabis use on PM [180,181].
A study examining the acute effects of MDMA on PM tested twelve recreational MDMA users who received a single dose of MDMA and a placebo in separate sessions, followed by completion of an objective PM task during functional imaging. The behavioural data revealed that a single dose of MDMA led to an increase in PM failures, with the number of failures positively correlating with MDMA plasma concentrations. This study offers direct evidence of the impact of MDMA on PM performance and the associated brain activity [182].
To date, only one study has explored the immediate effects of cocaine on PM. This placebo-controlled, three-way crossover study involved 15 participants with regular polysubstance use and aimed to determine how oral cocaine and vaporised cannabis influence performance on an event-based PM task. Participants received either cocaine, cannabis, or a placebo in separate sessions and then completed the PM task. The results demonstrated that cocaine administration significantly enhanced PM performance compared to both the placebo and cannabis conditions [181].
Research on acute substance effects on PM is very limited. Findings suggest mixed effects of cannabis, increased PM failures with MDMA, and improved performance with cocaine.
Several studies have reported that cannabis users exhibit impaired performance on various PM tasks [66,180,183-188]. These deficits have been linked to duration of cannabis use, dosage, frequency, cumulative exposure, and early onset of use [66,184,188,189]. A meta-analysis further supports these findings, demonstrating a significant association between cannabis use and impaired PM [94]. Notably, PM deficits appear more pronounced in laboratory-based assessments than in self-reported measures. For instance, Bartholomew et al., found that while cannabis users did not report significant PM difficulties, they performed worse on a video-based PM task, recalling fewer location-action combinations [190]. This suggests that cannabis-related PM impairments may go unnoticed by users. However, some studies have not found significant association between PM impairments and cannabis use [191-194].
Multiple studies found PM impairment in MDMA/ecstasy users [66,193-204]. These deficits have been linked to the level of ecstasy use, with heavier users exhibiting greater impairments [66,194,202]. Some evidence suggests that PM deficits in MDMA users may be more pronounced under specific conditions, particularly when there is a longer delay between forming an intention and executing it. For instance, Weinborn et al., found that while ecstasy users performed comparably to controls on short-delay PM tasks, their performance was significantly impaired on long-delay tasks [205]. Additionally, some studies suggest that PM impairments in MDMA users may be attributable to concurrent cannabis use rather than MDMA alone [66,183,194].
Currently, no research has specifically examined the long-term effects of cocaine on PM. However, some studies investigating MDMA's impact on PM have included cocaine use as part of broader analyses. For instance, Hadjiefthyvoulou et al., studied a group of people with a history of ecstasy/polysubstance use and those with non-ecstasy substance use, which included individuals who used cocaine. Their findings indicated a positive correlation between lifetime cocaine use and PM impairments, suggesting that higher levels of cocaine consumption may contribute to PM deficits [196]. Further evidence comes from a study by Levent and Davelaar, which examined a group of people who primarily used cocaine. The results showed that while people with a history of substance use exhibited impairments on lab-based PM tasks compared to drug-naïve individuals, they did not report significant deficits on self-reported PM measures [206]. A similar discrepancy was highlighted in a comprehensive systematic review, where substance users demonstrated deficits in objective PM tasks but did not perceive impairments in their everyday PM performance [177]. This divergence between self-report and lab-based findings may be explained by impaired metacognition in substance users [207], which refers to an individual's awareness of their own cognitive abilities [208]. Reduced metacognitive awareness may lead people with substance use to underestimate their PM difficulties in real-world settings, despite measurable impairments in controlled experimental conditions.
Overall, the long-term effects of substance use on PM remain complex and varied across substances. Cannabis and MDMA use are both associated with PM impairments, particularly in heavy and long-term users, with deficits more evident in laboratory-based tasks than self-reports. Cocaine’s impact on PM is less studied, though preliminary evidence suggests potential impairments linked to higher lifetime use.
Executive function
Executive Functions (EFs), also known as executive control or cognitive control, are a group of mental processes that help individuals plan, organise, integrate, and manage thoughts and behaviours. Often described as the "CEO" of the brain, EFs are essential for performing everyday tasks such as such as organising, planning, prioritising, paying attention and remembering details, and governing emotional responses [209]. It is generally agreed that three core EFs: working memory, cognitive flexibility, and inhibition [210]. Therefore, this section will review the literature on the acute and long-term effects of cannabis, MDMA, and cocaine use on EFs under three subsections: cognitive inhibition, working memory, and cognitive flexibility.
Cognitive inhibition, also known as inhibitory control, involves a set of processes that regulate thoughts, behaviours, attention, and emotions by suppressing dominant impulses or external distractions in favour of more contextually appropriate action [211]. This ability is crucial for self-regulation and decision-making, particularly in the context of addiction. Deficits in inhibitory control may contribute to the difficulty individuals face in resisting substance-related urges, thereby increasing the risk of relapse [212]. Additionally, poor inhibitory control has been linked to key behavioural characteristics commonly observed in substance use disorders, such as heightened impulsivity [213,214], increased sensation seeking [215], and impaired decision-making [216].
Cannabis use has been widely studied in the context of its acute effects on cognitive inhibition, revealing consistent impairments across different tasks designed to measure this domain [179,182,217-220]. Similarly, Hunault et al., reported that THC decreased response times and increased errors on a cognitive inhibition task in a dose-dependent manner, with the number of errors increasing significantly as the dose increased [221]. Such findings have been corroborated by multiple review studies [14,91,222,223]. Interestingly, the acute effects of THC on cognitive inhibition appears to differ between occasional and heavy cannabis users, potentially reflecting a tolerance effect. Ramaekers et al., observed that THC administration impaired psychomotor control in occasional users but not in heavy users [182]. This suggests that heavy cannabis users might develop a degree of tolerance to some of the impairing behavioural effects of cannabis, as proposed by Crane et al., and Theunissen et al., [224,225].
Research on the acute effects of MDMA on cognitive inhibition has yielded mixed findings, with some studies suggesting no significant impairments while others highlight potential improvements in specific inhibitory processes. For instance, multiple studies have reported that MDMA does not negatively affect cognitive inhibition [226,227]. A review also found that most studies that used measures of inhibition have failed to provide evidence for a relationship between ecstasy use and lower levels of inhibition [228]. Interestingly, one study demonstrated that acute doses of MDMA improved impulse control. Ramaekers and Kuypers found that participants exhibited enhanced cognitive inhibition task performance following MDMA administration [229].
Research examining the effects of acute cocaine doses on cognitive inhibition yielded mixed results. Some studies suggest that cocaine can enhance inhibitory control. For example, Garavan et al., and Fillmore et al., observed improved task performance in cocaine users following cocaine administration, indicating a potential enhancement of inhibitory control [230,231]. However, this enhancement may be dose-dependent. Fillmore et al., found that cocaine reduced the time required to inhibit a response, but only at doses of 100 mg and 200 mg. Higher doses (300 mg) did not produce the same speeding effect [232]. In contrast, other studies have demonstrated that cocaine can impair specific aspects of inhibitory control. For example, Fillmore et al., found that cocaine impaired the ability to inhibit behavioural responses, but did not affect response speed or accuracy, indicating a selective effect on behavioural suppression [233]. Similarly, van Wel et al., observed decreased response times alongside increased errors on impulsivity tasks, highlighting impairments in accuracy despite faster responses [220].
Overall, the acute effects of these substances on cognitive inhibition vary significantly. Cannabis consistently impairs inhibitory control, while MDMA’s effects remain inconclusive. Cocaine shows a complex, dose-dependent pattern, with both improvements and impairments reported.
The evidence regarding deficits in cognitive inhibition among abstinent cannabis users is mixed, with more favour no effect. Some studies suggest chronic cannabis use is associated with impairments in cognitive inhibition, particularly when use begins at an earlier age. For instance, Battisti et al., reported that chronic cannabis users exhibited poorer cognitive inhibition, with earlier age of onset predicting worse performance [112]. This finding implies that deficits may be more pronounced in individuals who initiate cannabis use during adolescence. Supporting this, multiple studies have shown that early-onset users (before age 15) tend to perform worse than both controls and late-onset users [234-236]. Such results align with the notion that cannabis exposure during adolescence (a critical period of neurodevelopment) may disrupt brain development and lead to lasting neuropsychological changes. A dose-dependent relationship has also been observed. For example, Piechatzek et al., found that more frequent cannabis use correlated with higher impulsivity [237].
However, the majority of studies examining long-term effects of cannabis use on cognitive inhibition report no significant deficits. Several studies have failed to find evidence of impairment [113,224,238-243]. Meta-analyses focusing on abstinent users also concluded that past cannabis use does not significantly impact executive functions, including cognitive inhibition [120,132,212]. Interestingly, some studies have revealed nuanced findings. Tapert et al., and Roberts and Garavan found that cannabis users exhibited intact inhibitory control but required greater brain processing effort to achieve comparable task performance to non-users [243,244]. This increased neural activation suggests that cannabis users may compensate for subtle deficits or inefficiencies in their cognitive processes. Tapert et al., proposed that this heightened effort might either predate the onset of regular cannabis use or be a consequence of it [244].
The long-term effects of MDMA on cognitive inhibition present a mixed picture. While most cross-sectional studies comparing MDMA/ecstasy users to non-users found no significant group differences in cognitive inhibition [77,142,143,150,245,246,247], some studies reported poorer performance among ecstasy users [237,248-250]. Piechatzek et al., further demonstrated a dose-dependent relationship, with increased ecstasy consumption associated with poorer performance on cognitive inhibition tests [237]. A limited number of longitudinal studies have addressed the methodological limitations of cross-sectional designs by assessing novice MDMA users over time. After controlling for confounding factors such as age, general intelligence, polysubstance use, and lifestyle variables, these studies found no significant changes in cognitive inhibition over the follow-up period [146,251].
A meta-analysis by Roberts et al., further supports the lack of consistent evidence for impaired cognitive inhibition in ecstasy users. This analysis, which compared 632 sub-stance-using controls to 600 ecstasy polysubstance users across 20 studies, found no significant group differences in inhibitory control performance [37].
Multiple studies have found that cocaine users, particularly those with cocaine dependence, exhibit significantly poorer inhibitory control compared to non-users [165,208,252-260]. Notably, the severity of inhibitory deficits has been positively correlated with lifetime cocaine exposure [253,261] and the dose used [252]. Interestingly, cocaine users performed significantly worse than controls on more demanding cognitive inhibition tasks, while easier tasks show little to no difference [262]. This pattern has been corroborated by studies highlighting performance deficits specifically in complex inhibitory control tasks [208,256].
Conversely, some studies found no behavioural cognitive inhibition impairments [263,264]. However, neuroimaging evidence suggests that cocaine users exhibit distinct patterns of brain activity compared to non-users during inhibition tasks, indicating the engagement of alternative neural pathways. This supports the compensatory mechanism theory, which posits that cocaine users recruit additional neural resources to compensate for deficits in cognitive inhibition [265-267].
A comprehensive meta-analysis of 46 studies identified cognitive inhibition as one of the most impaired domains in cocaine users, with moderate deficits observed [166]. Another meta-analysis further reinforced the presence of response inhibition impairments, reporting moderate effect sizes and suggesting a robust and consistent effect [108]. These findings align with broader reviews on cocaine-related cognitive inhibition impairment [212,268], though it is important to note that most reviews focus specifically on individuals with cocaine dependence.
Relatively few studies have investigated the long-term effects of cocaine use on cognitive inhibition following prolonged abstinence. Bell et al., compared cognitive inhibition performance among current cocaine users, ex-users, and non-users, finding that despite a history of chronic cocaine use (average duration = 8.2 years), ex-users performed just as well as non-users [269]. Neuroimaging data further revealed no significant differences in brain activity between these groups, suggesting that inhibitory control may recover with sustained abstinence. Similarly, Connolly et al., reported that individuals with prolonged abstinence from cocaine (40-102 weeks) exhibited greater recruitment of cognitive control regions compared to those in short-term abstinence (1-5 weeks). These findings suggest that inhibitory control can improve over time with abstinence or, alternatively, that individuals with stronger inhibitory control are more likely to maintain long-term abstinence [269].
Overall, the long-term effects of substance use on cognitive inhibition vary across substances. Chronic cannabis use does not appear to cause lasting deficits in abstinent users, though compensatory neural mechanisms may be involved. MDMA’s impact remains inconclusive, with no consistent evidence of long-term impairments. In contrast, cocaine use, particularly in cases of dependence, is strongly linked to inhibitory control deficits, which worsen with greater exposure but may be reversible with sustained abstinence.
Working Memory (WM) combines the ability to keep information for a very short period of time while allowing the controlling and planning of that information [270]. Working memory serves as a mental workspace, aiding in learning, reasoning, decision-making, and problem-solving [271].
Early investigations of WM have indicated that acute cannabis use is associated with impairments in holding, manipulating and remembering information [272,273]. More recent studies also found that acute intoxication resulted in significant impairment in WM [86,89,179,274-282]. Hunault et al., identified a dose–response relationship, demonstrating that higher THC concentrations in cannabis cigarettes are linearly associated with poorer cognitive performance, including impairments in WM [221]. Additionally, a review by Crean et al., concluded that THC administration has a detrimental effect on executive functions, particularly WM [14].
Research on the acute effects of MDMA on working memory is limited, and the findings are mixed. Some studies have reported that acute MDMA administration impairs performance on WM tasks [283,284], while others have found no significant effects [285]. More recently, Basedow et al., reviewed the literature and concluded that the majority of studies investigating the acute effects of MDMA on WM reported no evidence of impairment [107].
Most research on the acute effects of cocaine on WM has been conducted in animal models, with no studies to date found involving human participants.
Overall, the acute impact of these substances on WM differs. Cannabis consistently impairs WM in a dose-dependent manner, while evidence for MDMA remains inconclusive, with most studies reporting no significant deficits. Research on the acute effects of cocaine on WM is currently lacking.
In studies examining WM, the evidence for cannabis-associated deficits is mixed. Multiple studies showed that cannabis use is significantly associated with WM deficits [115,186,240,286]. These deficits are associated with duration of use [287,288], age of onset of cannabis use [122] or with greater frequency and quantity of use [115,122,289]. However, some other studies reported intact WM among cannabis users [240,290-294], in particular after controlling for confounds [134]. Additionally, in a longitudinal study, WM performance remained intact among recently abstinent current cannabis users, former cannabis users, and controls over a period of eight years [135]. Interestingly, despite comparable task performance with control groups, cannabis users exhibited different brain activity patterns, suggesting the recruitment of additional brain regions not typically engaged during WM tasks [291,294-298]. These findings support the theory of compensatory mechanisms in cannabis users [243,244].
In line with those studies above, multiple reviews examining the long-term effects of cannabis on WM have yielded mixed findings. Some studies report inconsistent evidence for cannabis-induced impairments in WM [8,299], while others found no residual effects of regular cannabis use on overall WM [92]. A longitudinal study found that, while cannabis use acutely impaired WM, users showed significant improvement in WM performance after 3 weeks of abstinence [114], suggesting that the negative effects of cannabis can be reversed with prolonged abstinence. Other studies have also shown no working memory impairments after 25 or more days of abstinence [297,298]. Consistent with these findings, a meta-analysis of 12 studies found no significant impact of past cannabis use on executive functions, including WM, in participants who had been abstinent for at least 25 days [132]. Overall, these findings suggest that the long-term effects of cannabis on brain function may be reversible with sufficient abstinence [291].
Findings on the long term effects of MDMA on WM are mixed [300], but more studies in favour of no effects. For example, some studies found that ecstasy users performed worse than non-user controls on various WM measures [78,247,301-305], with dose relation where increased ecstasy consumption was associated with poorer task performance [78,237,301,306] and which does not improve with abstinence [307,308]. Notably, the impact of MDMA appears to depend on the complexity of the WM task. Less demanding tasks have generally shown no significant differences between ecstasy users and non-users [142,191,309], whereas more cognitively demanding tests have revealed ecstasy-related deficits [302,303]. On the contrary, many studies found no effects [140,142,191,245,309-311]. In multiple follow-up studies, where participants were tested on different occasion to explore the effects on MDMA on WM found no deterioration in continuing MDMA-users was observed in the follow-up periods [62,146,312], potentially related to a low dose of ecstasy use [62,312].
It is worth noting that MDMA users appear to recruit additional cognitive resources to perform WM tasks compared to non-users, suggesting the involvement of compensatory neural mechanisms [310]. This aligns with findings from a comprehensive review of neuroimaging studies on ecstasy users, which also indicates potential compensatory activity in the brain [38].
Numerous studies have found that cocaine users often perform worse than non-users on WM tasks, particularly those with cocaine dependence [313-317]. The age of onset and severity of cocaine use also influence WM impairments, with increased use correlating with greater deficits [318,319]. A follow-up study by Vonmoos et al., provided further support for this relationship, showing that substantial increases in cocaine use over one year (mean +297%) were associated with marked declines in cognitive performance, particularly in WM. Conversely, participants who significantly reduced their cocaine use (-72%) exhibited modest cognitive improvements, while those who achieved sustained abstinence showed complete recovery, performing at levels comparable to non-user controls [167].
However, some studies report no differences in WM performance between cocaine users and controls [320,321]. Despite this, neuroimaging suggests cocaine users may rely on compensatory brain activity to maintain performance [256,322]. A comprehensive review of 46 studies on cognitive dysfunction in individuals with cocaine abuse or dependence found moderate impairments across eight cognitive domains, with WM being one of the most affected, especially during intermediate abstinence [166]. Interestingly, the review also highlighted small effect sizes for cognitive deficits in those with long-term abstinence, suggesting that extended cessation from cocaine use may lead to partial or even full recovery of WM function. These findings align with earlier research by Jovanovski et al., [323].
The long-term effects of cannabis, MDMA, and cocaine on WM remain ambiguous, with conflicting evidence across studies. For cannabis, some research identifies deficits linked to prolonged use, higher frequency, and earlier initiation, whereas other studies have found no such impairments. Notably, emerging evidence proposes that such deficits may diminish with sustained abstinence. Research on MDMA similarly reveals inconsistent results, with some studies reporting dose-dependent impairments, particularly in complex tasks, while others show no significant effects. Cocaine use, especially in heavy users, is generally associated with WM deficits, yet research indicates that reducing use or achieving abstinence can promote cognitive recovery. Neuroimaging findings across all three substances suggest that users may rely on compensatory neural mechanisms to maintain task performance, underscoring the brain’s ability to adapt to substance-related cognitive challenges.
Cognitive flexibility is another component of EFs which is defined as the brain’s ability to switch from thinking about one concept to another [324]. With cognitive flexibility, one is able to adapt his or her thinking and behaviour in response to the environment that constantly changes [325].
The evidence on the acute effects of cannabis intoxication on cognitive flexibility is limited and somewhat mixed. Some studies suggest that acute cannabis use disrupts cognitive flexibility, impairing an individual's ability to adapt to changing rules or switch between tasks [326-328]. However, contrasting findings have also been reported. For instance, Hart et al., found that while THC administration did not affect accuracy on measures of cognitive flexibility, although it significantly increased the number of premature responses and prolonged the time required to complete various tasks [277].
Furthermore, a systematic meta-review of meta-analyses by Dellazizzo et al., reported that cannabis use led to small deficits in cognitive flexibility [92].
Limited number of research with double-blind, randomised, placebo-controlled study design showed that the single administration of MDMA did not affect cognitive flexibility [100,329].
To the authors' knowledge, no studies have been conducted on cognitive flexibility following acute cocaine administration in humans.
In conclusion, the evidence regarding the acute effects of cannabis, MDMA, and cocaine on cognitive flexibility is limited and mixed. Cannabis may impair cognitive flexibility in some studies, while others show no effects. Research on MDMA suggests no impact, and there is a lack of studies on the acute effects of cocaine on cognitive flexibility.
Extensive research has explored the long-term effects of cannabis use on cognitive flexibility, with findings remaining mixed. Several studies have reported no significant differences in cognitive flexibility performance between cannabis users and non-users [330-333]. Conversely, other studies have found clear evidence of cognitive flexibility impairments among cannabis users [234,236,239,334-336]. These deficits have been linked to specific patterns of cannabis use, such as greater consumption in the past 30 days [334], early adolescent exposure [13,234-236], and heavy use [335]. Bolla et al., provided further support for dose-dependent effects, reporting that heavy cannabis users performed worse on cognitive flexibility tasks compared to moderate and occasional users, even after 28 days of abstinence. Their findings demonstrated a positive correlation between the frequency of cannabis consumption and poorer cognitive flexibility performance [337].
Meta-analysis findings also reflect these inconsistencies. An earlier meta-analysis by Grant et al., found no significant non-acute effects of cannabis use on cognitive flexibility [120]. Similarly, Schreiner and Dunn reported no significant impact of past cannabis use on cognitive flexibility [132]. However, a more recent meta-analysis by Figueiredo et al., identified a small but significant association between chronic cannabis use and cognitive impairments across multiple domains, including cognitive flexibility [338].
There is limited number of studies long-term effects of MDMA on cognitive flexibility. The existing literature is mixed. For instance, Dafters reported that chronic MDMA users exhibited impairments in task-switching performance [245]. Additionally, Verdejo-García et al., found a positive correlation between self-reported lifetime MDMA exposure and the number of perseverative errors, lending support to the neurotoxicity hypothesis associated with MDMA use [339].
On the contrary, Several studies have reported no residual cognitive effects in ecstasy users, with performance on cognitive flexibility tasks comparable to that of non-users [78,150,237,302]. Moreover, a longitudinal study conducted over a two-year period found no evidence of cognitive deterioration in individuals who continued using MDMA, suggesting that ongoing use did not exacerbate deficits in cognitive flexibility during the follow-up period [146].
Several studies have examined the long-term effects of cocaine use on cognitive flexibility, with the majority focusing on individuals with cocaine dependence. Consistently, these studies have reported that cocaine-dependent individuals exhibit significant impairments in cognitive flexibility compared to non-users [153,165,238,254,263,314,318,340-347]. Although fewer in number, studies involving recreational cocaine users have also identified deficits in cognitive flexibility, suggesting that impairments may not be exclusive to individuals with clinical dependence [313,317]. Moreover, dose-related neurocognitive research indicates a clear association between the severity of cocaine use (in terms of both quantity and duration) and cognitive flexibility deficits as greater cocaine use has been consistently linked to poorer performance on cognitive flexibility tasks [252,345,348,349].
Conversely, some studies have found no significant differences in cognitive flexibility between cocaine users and non-user controls, particularly in samples of recreational users [158,315,321,350]. Early review papers concluded that chronic cocaine use is generally associated with mild impairments in cognitive flexibility [108,351]. However, more recent reviews have reported inconsistent findings, suggesting that observed deficits may be context-specific and influenced by particular experimental conditions rather than representing broad, generalizable effects [53].
In summary, the long-term effects of cannabis, MDMA, and cocaine on cognitive flexibility are inconsistent. While some studies show no significant differences between cannabis users and non-users, others report impairments linked to patterns of use and dose. Similarly, MDMA's long-term impact is mixed, with some studies reporting deficits and others showing no effects. Cocaine use, particularly in dependent individuals, is generally linked to cognitive flexibility impairments, but findings are more varied in recreational users.
Concluding Remarks
The body of research reviewed reveals that both the acute and long-term effects of cannabis, MDMA, and cocaine on retrospective memory vary. Acute use of cannabis and MDMA consistently impairs objective episodic memory, while acute cocaine use appears to have no effect. However, chronic use of all three substances is associated with deficits in objective episodic memory, with impairment severity increasing with prolonged or heavy use. Longitudinal studies suggest that cognitive recovery is possible, particularly for cannabis and cocaine users, following extended abstinence. Although research on subjective episodic memory remains limited, existing findings indicate that all three substances can negatively affect autobiographical memory. It is well established that impairments in retrospective memory, particularly objective episodic memory (tested via learning tests), are closely associated with poor academic performance [352], which has been found to increase the risk of substance abuse and subsequent addiction [353,354].
Research on the effects of cannabis, MDMA, and cocaine on PM is limited. While the acute administration of cannabis and MDMA impair PM, cocaine appears to enhance PM performance. Long-term use of those substances is linked to PM deficits, especially in heavy users, with stronger effects in laboratory tasks than self-reports. The observed discrepancy between self-reported and laboratory-based PM measures in people with substance use points to metacognitive deficits [177,206], wherein people with substance use exhibit diminished awareness of cognitive impairments potentially stemming from substance use. This accords with previous observations, which showed that people who use substance use are impaired in metacognition [207,208,241,355-360]. This lack of awareness could contribute to continued substance use, as individuals may underestimate the impact of these impairments. Consequently, this may lead to increased consumption, potentially escalating to addiction due to prolonged and excessive use.
The acute effects of cannabis, MDMA and cocaine on executive functions are mixed. Cannabis consistently impairs inhibitory control and working memory and may affect cognitive flexibility. MDMA’s impact remains inconclusive across all domains, with no consistent evidence of impairment. Cocaine’s effects are complex and dose-dependent, with potential improvements or impairments in cognitive inhibition, while research on its effects on working memory and cognitive flexibility remains limited. The long-term effects of these substances on executive functions vary across substances and executive functioning domains. Chronic cannabis use does not appear to cause lasting deficits in inhibitory control, though some studies suggest potential working memory and cognitive flexibility impairments, predominantly with heavier use. MDMA’s long-term impact remains inconclusive, with inconsistent findings across studies. Cocaine, especially in cases of dependence, is strongly linked to inhibitory control and working memory deficits, though some recovery may occur with sustained abstinence.
The existing literature indicates that the observed deficits are associated with the duration of substance use, dosage, frequency, cumulative exposure, and early onset of use. Neuroimaging evidence across various substances suggests that compensatory mechanisms may help mitigate substance-induced cognitive impairments, mainly in executive function domains. People who use substance seem to recruit additional cognitive resources to perform executive function tasks, indicating the involvement of compensatory neural mechanisms [38,243,244,256,265-267,294,297,301,310].
The cognitive impairments observed in people with a history of substance use, including deficits in cognitive inhibition, AM, and WM, may increase the risk for further substance use and contribute to the progression from recreational use to addiction [361-364]. Some studies suggest that recovery from substance-induced cognitive impairments is possible with prolonged abstinence, particularly for cocaine and cannabis use [114,131,132,167,267,269,291,297,298], highlighting the brain's potential for compensatory mechanisms and cognitive restoration over time.
A substantial body of evidence indicates that adolescents, who typically engage in higher levels of illegal recreational substance use compared to other age groups [1], are at a higher risk of suffering potential harmful effects from substance use, particularly cannabis use [118,234-236,290,319,361]. One explanation for these harmful effects is that the adolescent brain undergoes significant development until approximately 25 years of age [365-367] and interference with these processes may manifest as the cognitive impairments ob-served in the existing literature. These substance-induced cognitive impairments may also contribute to the transition from recreational substance use to addiction [353,354,361,363-365,368,369].
It is important to acknowledge the challenges in conducting studies on the effects of substance use on cognition, including polysubstance use, difficulties in participant recruit-ment, and inadequate control of confounding variables, all of which complicate the interpretation of findings.
References
- United Nations (2022) World Drug Report 2022. United Nations, New York, USA.
- Public Health England (2020) United Kingdom drug situation 2019: Summary. Public Health England, England, UK.
- Gould TJ (2010) Addiction and Cognition. Addict Sci Clin Pract 5: 4-14.
- Abood ME, Martin BR (1992) Neurobiology of marijuana abuse. Trends Pharmacol Sci 13: 201-206.
- Chandra S, Radwan MM, Majumdar CG, Church JC, Freeman TP, et al. (2019) New trends in cannabis potency in USA and Europe during the last decade (2008-2017). European Archives of Psychiatry and Clinical Neuroscience 269: 5-15.
- Russo EB (2016) Beyond Cannabis: Plants and the Endocannabinoid System. Trends in Pharmacological Sciences 37: 594-605.
- Covey DP, Mateo Y, Sulzer D, Cheer JF, Lovinger DM (2017) Endocannabinoid modulation of dopamine neurotransmission. Neuropharmacology 124: 52-61.
- Kroon E, Kuhns L, Cousijn J (2021) The short-term and long-term effects of cannabis on cognition: recent advances in the field. Current Opinion in Psychology 38: 49-55.
- Lu HC, Mackie K (2016) An introduction to the endogenous cannabinoid system. Biol Psychiatry 79: 516-525.
- Lu HC, Mackie K (2021) Review of the Endocannabinoid System. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 6: 607-615.
- Mackie K (2005) Distribution of Cannabinoid Receptors in the Central and Peripheral Nervous System. In: Pertwee RG (ed.). Cannabinoids. Springer-Verlag, Berlin, Germany.
- Piomelli D (2003) The molecular logic of endocannabinoid signalling. Nature Reviews Neuroscience 4: 873-884.
- Bourque J, Potvin S (2021) Cannabis and cognitive functioning: from acute to residual effects, from randomized controlled trials to prospective designs. Frontiers in psychiatry 12: 596601.
- Crean RD, Crane NA, Mason BJ (2011) An Evidence Based Review of Acute and Long-Term Effects of Cannabis Use on Executive Cognitive Functions. J Addict Med 5: 1-8.
- Gonzalez R (2007) Acute and non-acute effects of cannabis on brain functioning and neuropsychological performance. Neuropsychol Rev 17: 347-361.
- Solowij N, Pesa N (2010) Cognitive abnormalities and cannabis use. Revista Brasileira de Psiquiatria 32: 31-40.
- Bhattacharyya S, Schoeler T (2013) The effect of cannabis use on memory function: An update. SAR.
- Churchwell JC, Lopez-Larson M, Yurgelun-Todd DA (2010) Altered Frontal Cortical Volume and Decision Making in Adolescent Cannabis Users. Front Psychol 1: 225.
- Lopez-Larson MP, Bogorodzki P, Rogowska J, McGlade E, King JB, et al. (2011) Altered prefrontal and insular cortical thickness in adolescent marijuana users. Behavioural Brain Research 220: 164-172.
- Niloy N, Hediyal TA, Vichitra C, Sonali S, Chidambaram SB, et al. (2023) Effect of Cannabis on Memory Consolidation, Learning and Retrieval and Its Current Legal Status in India: A Review. Biomolecules 13: 162.
- Blest-Hopley G, Giampietro V, Bhattacharyya S (2020) A Systematic Review of Human Neuroimaging Evidence of Memory-Related Functional Alterations Associated with Cannabis Use Complemented with Preclinical and Human Evidence of Memory Performance Alterations. Brain Sciences 10: 102.
- Iyer P, Niknam Y, Campbell M, Moran F, Kaufman F, et al. (2022) Animal evidence considered in determination of cannabis smoke and Δ-tetrahydrocannabinol (Δ-THC) as causing reproductive toxicity (developmental endpoint); Part II. Neurodevelopmental effects. Birth Defects Research 114: 1155-1168.
- Rubino T, Prini P, Piscitelli F, Zamberletti E, Trusel M, et al. (2015) Adolescent exposure to THC in female rats disrupts developmental changes in the prefrontal cortex. Neurobiology of Disease 73: 60-69.
- Gudelsky GA, Yamamoto BK (2008) Actions of 3,4-methylenedioxymethamphetamine (MDMA) on cerebral dopaminergic, serotonergic and cholinergic neurons. Pharmacol Biochem Behav 90: 198-207.
- Liechti ME, Saur MR, Gamma A, Hell D, Vollenweider FX (2000) Psychological and Physiological Effects of MDMA (“Ecstasy”) after Pretreatment with the 5-HT2 Antagonist Ketanserin in Healthy Humans. Neuropsychopharmacol 23: 396-404.
- Bacqué-Cazenave J, Bharatiya R, Barrière G, Delbecque JP, Bouguiyoud N, et al. (2020) Serotonin in Animal Cognition and Behavior. International Journal of Molecular Sciences 21: 1649.
- Coray R, Quednow BB (2022) The role of serotonin in declarative memory: A systematic review of animal and human research. Neuroscience & Biobehavioral Reviews 139: 104729.
- Amin Z, Gueorguieva R, Cappiello A, Czarkowski KA, Stiklus S, et al. (2006) Estradiol and tryptophan depletion interact to modulate cognition in menopausal women. Neuropsychopharmacology 31: 2489-2497.
- Borghans LGJM, Blokland A, Sambeth A (2017) Effects of biperiden and acute tryptophan depletion and their combination on verbal word memory and EEG. Psychopharmacology (Berl) 234: 1135-1143.
- Sambeth A, Riedel WJ, Tillie DE, Blokland A, Postma A, et al. (2009) Memory impairments in humans after acute tryptophan depletion using a novel gelatin-based protein drink. J Psychopharmacol 23: 56-64.
- van Donkelaar EL, Blokland A, Ferrington L, Kelly PT, Steinbusch HWM, et al. (2011) Mechanism of acute tryptophan depletion: is it only serotonin? Mol Psychiatry 16: 695-713.
- Harmer CJ, Bhagwagar Z, Cowen PJ, Goodwin GM (2002) Acute administration of citalopram facilitates memory consolidation in healthy volunteers. Psychopharmacology (Berl) 163: 106-110.
- Buchert R, Thomasius R, Wilke F, Petersen K, Nebeling B, et al. (2004) A Voxel-Based PET Investigation of the Long-Term Effects of “Ecstasy” Consumption on Brain Serotonin Transporters. AJP 161: 1181-1189.
- Kish SJ, Lerch J, Furukawa Y, Tong J, McCluskey T, et al. (2010) Decreased cerebral cortical serotonin transporter binding in ecstasy users: A positron emission tomography/[(11)C]DASB and structural brain imaging study. Brain 133: 1779-1797.
- McCann UD, Szabo Z, Vranesic M, Palermo M, Mathews WB, et al. (2008) Positron emission tomographic studies of brain dopamine and serotonin transporters in abstinent (±)3,4-methylenedioxymethamphetamine (“ecstasy”) users: relationship to cognitive performance. Psychopharmacology 200: 439-450.
- Reneman L, Lavalaye J, Schmand B, de Wolff FA, van den Brink W, et al. (2001) Cortical Serotonin Transporter Density and Verbal Memory in Individuals Who Stopped Using 3,4-Methylenedioxymethamphetamine (MDMA or ‘Ecstasy’): Preliminary Findings. Archives of General Psychiatry 58: 901-906.
- Roberts CA, Jones A, Montgomery C (2016) Meta-analysis of executive functioning in ecstasy/polydrug users. Psychol Med 46: 1581-1596.
- Roberts CA, Quednow BB, Montgomery C, Parrott AC (2018) MDMA and brain activity during neurocognitive performance: An overview of neuroimaging studies with abstinent ‘Ecstasy’ users. Neuroscience & Biobehavioral Reviews 84: 470-482.
- Able JA, Gudelsky GA, Vorhees CV, Williams MT (2006) 3,4-Methylenedioxymethamphetamine in Adult Rats Produces Deficits in Path Integration and Spatial Reference Memory. Biol Psychiatry 59: 1219-1226.
- Molliver ME, Berger UV, Mamounas LA, Molliver DC, O’Hearn E, et al. (1990) Neurotoxicity of MDMA and related compounds: anatomic studies. Ann N Y Acad Sci 600: 649-661.
- Anneken JH, Cunningham JI, Collins SA, Yamamoto BK, Gudelsky GA (2013) MDMA increases glutamate release and reduces parvalbumin-positive GABAergic cells in the dorsal hippocampus of the rat: role of cyclooxygenase. J Neuroimmune Pharmacol 8: 58-65.
- Buhot MC, Martin S, Segu L (2000) Role of serotonin in memory impairment. Annals of Medicine 32: 210-221.
- Sparks GM, Dasari S, Cooper RL (2004) Actions of MDMA at glutamatergic neuromuscular junctions. Neuroscience Research 48: 431-438.
- Colado MI, O’Shea E, Green AR (2004) Acute and long-term effects of MDMA on cerebral dopamine biochemistry and function. Psychopharmacology (Berl) 173: 249-263.
- Woolverton WL, Johnson KM (1992) Neurobiology of cocaine abuse. Trends Pharmacol Sci 13: 193-200.
- Kaminski J, Mamelak AN, Birch K, Mosher CP, Tagliati M, et al. (2018) Novelty-Sensitive Dopaminergic Neurons in the Human Substantia Nigra Predict Success of Declarative Memory Formation. Current Biology 28: 1333-1343.
- Otmakhova NA, Lisman JE (1996) D1/D5 dopamine receptor activation increases the magnitude of early long-term potentiation at CA1 hippocampal synapses. J Neurosci 16: 7478-7486.
- Li S, Cullen WK, Anwyl R, Rowan MJ (2003) Dopamine-dependent facilitation of LTP induction in hippocampal CA1 by exposure to spatial novelty. Nat Neurosci 6: 526-531.
- Goldman-Rakic PS (1995) Cellular basis of working memory. Neuron 14: 477-485.
- Klaus K, Pennington K (2019) Dopamine and Working Memory: Genetic Variation, Stress and Implications for Mental Health. Curr Top Behav Neurosci 41: 369-391.
- Volkow ND, Wang GJ, Fowler JS, Logan J, Gatley SJ, et al. (1997) Decreased striatal dopaminergic responsiveness in detoxified cocaine-dependent subjects. Nature 386: 830-833.
- Briand LA, Flagel SB, Garcia-Fuster MJ, Watson SJ, Akil H, et al. (2008) Persistent Alterations in Cognitive Function and Prefrontal Dopamine D2 Receptors Following Extended, but Not Limited, Access to Self-Administered Cocaine. Neuropsychopharmacol 33: 2969-2980.
- Frazer KM, Richards Q, Keith DR (2018) The long-term effects of cocaine use on cognitive functioning: A systematic critical review. Behavioural Brain Research 348: 241-262.
- Lim KO, Wozniak JR, Mueller BA, Franc DT, Specker SM, et al. (2008) Brain macrostructural and microstructural abnormalities in cocaine dependence. Drug Alcohol Depend 92: 164-172.
- Ma L, Steinberg JL, Moeller FG, Johns SE, Narayana PA (2015) Effect of cocaine dependence on brain connections: Clinical implications. Expert Rev Neurother 15: 1307-1319.
- Moeller FG, Hasan KM, Steinberg JL, Kramer LA, Dougherty DM, et al. (2005) Reduced anterior corpus callosum white matter integrity is related to increased impulsivity and reduced discriminability in cocaine-dependent subjects: diffusion tensor imaging. Neuropsychopharmacology 30: 610-617.
- Grov C, Kelly BC, Parsons JT. Polydrug use among club-going young adults recruited through time-space sampling. Subst Use Misuse. 2009;44(6):848–64.
- Gold MS, Cadet JL, Baron D, Badgaiyan RD, Blum K (2020) Calvin klein (CK) designer cocktail, new “Speedball” is the “grimm reaper”: Brain dopaminergic surge a potential death sentence. J Syst Integr Neurosci 10. 15761
- Gonçalves JR, Nappo SA (2015) Factors that lead to the use of crack cocaine in combination with marijuana in Brazil: A qualitative study. BMC Public Health 15: 706.
- Ives R, Ghelani P (2006) Polydrug use (the use of drugs in combination): A brief review. Drugs: Education, Prevention and Policy 13: 225-232.
- Gouzoulis-Mayfrank E, Daumann J (2006) The confounding problem of polydrug use in recreational ecstasy/MDMA users: A brief overview. J Psychopharmacol 20: 188-193.
- Schilt T, de Win MML, Koeter M, Jager G, Korf DJ, van den Brink W, et al. (2007) Cognition in novice ecstasy users with minimal exposure to other drugs: a prospective cohort study. Arch Gen Psychiatry 64: 728-736.
- McCardle K, Luebbers S, Carter JD, Croft RJ, Stough C (2004) Chronic MDMA (ecstasy) use, cognition and mood. Psychopharmacology (Berl) 173: 434-439.
- Duncan DF, White JB, Nicholson T (2003) Using Internet-based surveys to reach hidden populations: case of nonabusive illicit drug users. Am J Health Behav 27: 208-218.
- Shaghaghi A, Bhopal RS, Sheikh A (2011) Approaches to Recruiting ‘Hard-To-Reach’ Populations into Research: A Review of the Literature. Health Promot Perspect 1: 86-94.
- Rodgers J, Buchanan T, Scholey A, Heffernan T, Ling J, et al. (2001) Differential effects of Ecstasy and cannabis on self-reports of memory ability: A web-based study. Human Psychopharmacology 16: 619-625.
- Boly M, Seth AK, Wilke M, Ingmundson P, Baars B, et al. (2013) Consciousness in humans and non-human animals: recent advances and future directions. Front Psychol 4: 625.
- Ballard ME, Weafer J, Gallo DA, Wit H de (2015) Effects of Acute Methamphetamine on Emotional Memory Formation in Humans: Encoding vs Consolidation. PLOS ONE 10: 0117062.
- Deary IJ, Corley J, Gow AJ, Harris SE, Houlihan LM, et al. (2009) Age-associated cognitive decline. British Medical Bulletin 92: 135-152.
- Glisky EL (2007) Changes in Cognitive Function in Human Aging. In: Riddle DR (ed.). Brain Aging: Models, Methods, and Mechanisms. CRC Press/Taylor & Francis, Boca Raton, Florida, USA.
- Kim S, Kim Y, Park SM (2016) Association between alcohol drinking behaviour and cognitive function: results from a nationwide longitudinal study of South Korea. BMJ Open 6: 010494.
- Mantua J, Simonelli G (2019) Sleep duration and cognition: is there an ideal amount? Sleep 42.
- Mohn C, Sundet K, Rund BR (2014) The relationship between IQ and performance on the MATRICS consensus cognitive battery. Schizophr Res Cogn 1: 96-100.
- Rock PL, Roiser JP, Riedel WJ, Blackwell AD (2014) Cognitive impairment in depression: a systematic review and meta-analysis. Psychol Med 44: 2029-2040.
- Lövdén M, Fratiglioni L, Glymour MM, Lindenberger U, Tucker-Drob EM (2020) Education and Cognitive Functioning Across the Life Span. Psychol Sci Public Interest 21: 6-41.
- Mahoney III JJ (2019) Cognitive dysfunction in individuals with cocaine use disorder: Potential moderating factors and pharmacological treatments. Experimental and Clinical Psychopharmacology 27: 203-214.
- Fisk J, Montgomery C (2009) Evidence for selective executive function deficits in ecstasy/polydrug users. J Psychopharmacol 23: 40-50.
- Fox HC, Parrott AC, Turner JJ (2001) Ecstasy use: Cognitive deficits related to dosage rather than self-reported problematic use of the drug. J Psychopharmacol (Oxford) 15: 273-281.
- Ryan JE, Smeltzer SC, Sharts-Hopko NC (2019) Challenges to Studying Illicit Drug Users. J Nurs Scholarsh 51: 480-488.
- Beddoes D, Sheikh S, Khanna M, Francis R (2010) The Impact Of Drugs on Different Minority Groups: A Review Of The UK Literature. UKDPC, UK.
- Lammy D (2017) Lammy review: Final report. GOV.UK, UK.
- Ritchie H, Roser M (2018) Substance Use. Our World in Data. Our World.
- Alberini C (2022) The Role of Reconsolidation and the Dynamic Process of Long-Term Memory Formation and Storage. Frontiers in Behavioral Neuroscience. Frontiers in Behavioral Neuroscience.
- D’Souza MS (2015) Glutamatergic transmission in drug reward: implications for drug addiction. Front Neurosci 9: 404.
- Englund A, Morrison PD, Nottage J, Hague D, Kane F, et al. (2013) Cannabidiol inhibits THC-elicited paranoid symptoms and hippocampal-dependent memory impairment. Journal of Psychopharmacology 27: 19-27.
- Hindocha C, Freeman TP, Xia JX, Shaban NDC, Curran HV (2017) Acute memory and psychotomimetic effects of cannabis and tobacco both ‘joint’ and individually: A placebo-controlled trial. Psychological Medicine 47: 2708-2719.
- Lawn W, Trinci K, Mokrysz C, Borissova A, Ofori S, et al. (2023) The acute effects of cannabis with and without cannabidiol in adults and adolescents: A randomised, double-blind, placebo-controlled, crossover experiment. Addiction 118: 1282-1294.
- Liem-Moolenaar M, te Beek ET, de Kam ML, Franson KL, Kahn RS, et al. (2010) Central nervous system effects of haloperidol on THC in healthy male volunteers. Journal of Psychopharmacology 24: 1697-1708.
- Morrison PD, Zois V, McKeown DA, Lee TD, Holt DW, et al. (2009) The acute effects of synthetic intravenous Δ9-tetrahydrocannabinol on psychosis, mood and cognitive functioning. Psychological Medicine 39: 1607-1616.
- Ranganathan M, Carbuto M, Braley G, Elander J, Perry E, et al. (2012) Naltrexone does not attenuate the effects of intravenous Δ9-tetrahydrocannabinol in healthy humans. International Journal of Neuropsychopharmacology 15: 1251-1264.
- Broyd SJ, van Hell HH, Beale C, Yücel M, Solowij N (2016) Acute and Chronic Effects of Cannabinoids on Human Cognition—A Systematic Review. Biological Psychiatry 79: 557-567.
- Dellazizzo L, Potvin S, Giguère S, Dumais A (2022) Evidence on the acute and residual neurocognitive effects of cannabis use in adolescents and adults: A systematic meta-review of meta-analyses. Addiction 117: 1857-1870.
- Ranganathan M, D’Souza D (2006) The acute effects of cannabinoids on memory in humans: A review. Psychopharmacology 188: 425-444.
- Schoeler T, Kambeitz J, Behlke I, Murray R, Bhattacharyya S (2016) The effects of cannabis on memory function in users with and without a psychotic disorder: Findings from a combined meta-analysis. Psychological medicine 46: 177-188.
- Morgan CJA, Schafer G, Freeman TP, Curran HV (2010) Impact of cannabidiol on the acute memory and psychotomimetic effects of smoked cannabis: Naturalistic study. The British Journal of Psychiatry 197: 285-290.
- ElSohly MA, Mehmedic Z, Foster S, Gon C, Chandra S, et al. (2016) Changes in cannabis potency over the last 2 decades (1995–2014): analysis of current data in the United States. Biological psychiatry 79: 613-619.
- ElSohly MA, Chandra S, Radwan M, Majumdar CG, Church JC (2021) A comprehensive review of cannabis potency in the United States in the last decade. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 6: 603-606.
- Pennypacker S, Cunnane K, Cash M, Romero-Sandoval E (2022) Potency and Therapeutic THC and CBD Ratios: U.S. Cannabis Markets Overshoot. Frontiers in Pharmacology 13: 921493.
- Kuypers KPC, Theunissen EL, van Wel JHP, de Sousa Fernandes Perna EB, Linssen A, et al. (2016) Verbal Memory Impairment in Polydrug Ecstasy Users: A Clinical Perspective. PLoS One 11: 0149438.
- Dumont GJH, Wezenberg E, Valkenberg MMGJ, de Jong CAJ, Buitelaar JK, et al. (2008) Acute neuropsychological effects of MDMA and ethanol (co-)administration in healthy volunteers. Psychopharmacology (Berl) 197: 465-474.
- Haijen E, Farre M, de la Torre R, Pastor A, Olesti E, et al. (2017) Peripheral endocannabinoid concentrations are not associated with verbal memory impairment during MDMA intoxication. Psychopharmacology 235: 709-717.
- Kuypers KP, Wingen M, Heinecke A, Formisano E, Ramaekers JG (2011) MDMA intoxication and verbal memory performance: a placebo-controlled pharmaco-MRI study. J Psychopharmacol 25: 1053-1061.
- Kuypers KPC, Ramaekers JG (2005) Transient memory impairment after acute dose of 75mg 3.4-Methylene-dioxymethamphetamine. J Psychopharmacol 19: 633-639.
- van Wel JHP, Kuypers KPC, Theunissen EL, Bosker WM, Bakker K, et al. (2011) Blockade of 5-HT2 Receptor Selectively Prevents MDMA-Induced Verbal Memory Impairment. Neuropsychopharmacology 36: 1932-1939.
- Kuypers K, Wingen M, Ramaekers J (2008) Memory and mood during the night and in the morning after repeated evening doses of MDMA. J Psychopharmacol 22: 895-903.
- Parrott AC, Lasky J (1998) Ecstasy (MDMA) effects upon mood and cognition: before, during and after a Saturday night dance. Psychopharmacology 139: 261-268.
- Basedow LA, Majic T, Hafiz NJ, Algharably EAE, Kreutz R, et al. (2024) Cognitive functioning associated with acute and subacute effects of classic psychedelics and MDMA - a systematic review and meta-analysis. Scientific Reports 14: 14782.
- Spronk DB, van Wel JHP, Ramaekers JG, Verkes RJ (2013) Characterizing the cognitive effects of cocaine: A comprehensive review. Neuroscience & Biobehavioral Reviews 37: 1838-1859.
- Higgins ST, Bickel WK, Hughes JR, Lynn M, Capeless MA, et al. (1990) Effects of intranasal cocaine on human learning, performance and physiology. Psychopharmacology 102: 451-458.
- Hopper JW, Karlsgodt KH, Adler CM, Macklin EA, Lukas SE, et al. (2004) Effects of acute cortisol and cocaine administration on attention, recall and recognition task performance in individuals with cocaine dependence. Human Psychopharmacology 19: 511-516.
- Haney M, Hart C, Collins ED, Foltin RW (2005) Smoked cocaine discrimination in humans: effects of gabapentin. Drug Alcohol Depend 80: 53-61.
- Battisti RA, Roodenrys S, Johnstone SJ, Respondek C, Hermens DF, et al. (2010) Chronic use of cannabis and poor neural efficiency in verbal memory ability. Psychopharmacology 209: 319-330.
- Gonzalez R, Schuster RM, Mermelstein RJ, Vassileva J, Martin EM, et al. (2012) Performance of young adult cannabis users on neurocognitive measures of impulsive behavior and their relationship to symptoms of cannabis use disorders. Journal of Clinical and Experimental Neuropsychology 34: 962-976.
- Hanson KL, Winward JL, Schweinsburg AD, Medina KL, Brown SA, et al. (2010) Longitudinal study of cognition among adolescent marijuana users over three weeks of abstinence. Addictive Behaviors 35: 970-976.
- Harvey MA, Sellman JD, Porter RJ, Frampton CM (2007) The relationship between non-acute adolescent cannabis use and cognition. Drug and Alcohol Review 26: 309-319.
- Korver N, Nieman DH, Becker HE, van de Fliert JR, Dingemans PH, et al. (2010) Symptomatology and Neuropsychological Functioning in Cannabis Using Subjects at Ultra-High Risk for Developing Psychosis and Healthy Controls. Aust N Z J Psychiatry 44: 230-236.
- Nestor L, Roberts G, Garavan H, Hester R (2008) Deficits in learning and memory: Parahippocampal hyperactivity and frontocortical hypoactivity in cannabis users. NeuroImage 40: 1328-1339.
- Solowij N, Jones KA, Rozman ME, Davis SM, Ciarrochi J, et al. (2011) Verbal learning and memory in adolescent cannabis users, alcohol users and non-users. Psychopharmacology (Berl) 216: 131-144.
- Yücel M, Solowij N, Respondek C, Whittle S, Fornito A, et al. (2008) Regional Brain Abnormalities Associated With Long-term Heavy Cannabis Use. Archives of General Psychiatry 65: 694-701.
- Grant I, Gonzalez R, Carey C, Natarajan L, Wolfson T (2003) Non-acute (residual) neurocognitive effects of cannabis use: A meta-analytic study. Journal of the International Neuropsychological Society: JINS 9: 679-689.
- Rodgers J (2000) Cognitive performance amongst recreational users of ‘ecstasy’. Psychopharmacology (Berl) 151: 19-24.
- Solowij N, Battisti R (2008) The chronic effects of cannabis on memory in humans: a review. Curr Drug Abuse Rev 1: 81-98.
- Wadsworth EJK, Moss SC, Simpson SA, Smith AP (2006) Cannabis use, cognitive performance and mood in a sample of workers. J Psychopharmacol 2: 14-23.
- Gouzoulis-Mayfrank E, Daumann J, Tuchtenhagen F, Pelz S, Becker S, et al. (2000) Impaired cognitive performance in drug free users of recreational ecstasy (MDMA). J Neurol Neurosurg Psychiatry 68: 719-725.
- Quednow B, Jessen F, Kühn K, Maier W, Daum I, et al. (2006) Memory deficits in abstinent MDMA (ecstasy) users: neuropsychological evidence of frontal dysfunction. Journal of psychopharmacology.
- Reske M, Eidt CA, Delis DC, Paulus MP (2010) Nondependent stimulant users of cocaine and prescription amphetamines show verbal learning and memory deficits. Biol Psychiatry 68: 762-769.
- Becker MP, Collins PF, Luciana M (2014) Neurocognition in college-aged daily marijuana users. Journal of Clinical and Experimental Neuropsychology 36: 379-398.
- Becker MP, Collins PF, Schultz A, Uroševic S, Schmaling B, et al. (2018) Longitudinal changes in cognition in young adult cannabis users. Journal of Clinical and Experimental Neuropsychology 40: 529-543.
- Duperrouzel JC, Hawes SW, Lopez-Quintero C, Pacheco-Colón I, Coxe S, et al. (2019) Adolescent cannabis use and its associations with decision-making and episodic memory: Preliminary results from a longitudinal study. Neuropsychology 33: 701-710.
- Gonzalez R, Pacheco-Colón I, Duperrouzel JC, Hawes SW (2017) Does Cannabis Use Cause Declines in Neuropsychological Functioning?: A Review of Longitudinal Studies. J Int Neuropsychol Soc 23: 893-902.
- Medina KL, Hanson KL, Schweinsburg AD, Cohen-Zion M, Nagel BJ, et al. (2007) Neuropsychological functioning in adolescent marijuana users: Subtle deficits detectable after a month of abstinence. J Int Neuropsychol Soc 13: 807-820.
- Schreiner AM, Dunn ME (2012) Residual effects of cannabis use on neurocognitive performance after prolonged abstinence: A meta-analysis. Experimental and Clinical Psychopharmacology 20: 420-429.
- Burke CO, Boutouis S, Spence JS, Filbey FM (2024) Residual and enduring effects of cannabis use on cognitive and psychomotor function: A study of adults during unrestricted cannabis use, short-term abstinence, and protracted abstinence. Experimental and Clinical Psychopharmacology.
- Fried PA, Watkinson B, Gray R (2005) Neurocognitive consequences of marihuana—a comparison with pre-drug performance. Neurotoxicology and Teratology 27: 231-239.
- Tait RJ, Mackinnon A, Christensen H (2011) Cannabis use and cognitive function: 8-year trajectory in a young adult cohort. Addiction 106: 2195-2203.
- Bolla KI, McCann UD, Ricaurte GA (1998) Memory impairment in abstinent MDMA (‘Ecstasy’) users. Neurology 51: 1532-1537.
- Fox HC, Toplis AS, Turner JJD, Parrott AC (2001) Auditory verbal learning in drug-free Ecstasy polydrug users. Hum Psychopharmacol 16: 613-618.
- Parrott AC, Lees A, Garnham NJ, Jones M, Wesnes K (1998) Cognitive performance in recreational users of MDMA or ‘ecstasy’: evidence for memory deficits. J Psychopharmacol 12: 79-83.
- Rouse E, Bruno R (2011) Impaired Consolidation Processes Underlying Ecstasy-Group Deficits in Verbal Memory. The Open Addiction Journal.
- Yip JTH, Lee TMC (2005) Effect of ecstasy use on neuropsychological function: a study in Hong Kong. Psychopharmacology (Berl) 179: 620-628.
- de Sola Llopis S, Miguelez-Pan M, Peña-Casanova J, Poudevida S, Farré M, et al. (2008) Cognitive performance in recreational ecstasy polydrug users: a two-year follow-up study. J Psychopharmacol 22: 498-510.
- Gouzoulis-Mayfrank E, Thimm B, Rezk M, Hensen G, Daumann J. Memory impairment suggests hippocampal dysfunction in abstinent ecstasy users. Prog Neuropsychopharmacol Biol Psychiatry. 2003 Aug;27(5):819–27.
- Medina K, Shear K, Corcoran K (2005) Ecstasy (MDMA) exposure and neuropsychological functioning: a polydrug perspective. Journal of the International Neuropsychological Society : JINS 11: 753-765.
- Schilt T, Koeter MWJ, Smal JP, Gouwetor MN, van den Brink W, et al. (2009) Long-term neuropsychological effects of ecstasy in middle-aged ecstasy/polydrug users. Psychopharmacology 207: 583-591.
- Zakzanis KK, Young DA (2001) Memory impairment in abstinent MDMA (‘Ecstasy’) users: a longitudinal investigation. Neurology 56: 966-969.
- Wagner D, Tkotz S, Koester P, Becker B, Gouzoulis-Mayfrank E, et al. (2015) Learning, Memory, and Executive Function in New MDMA Users: A 2-Year Follow-Up Study. Frontiers in Neuroscience 9.
- Kalechstein AD, De La Garza R, Mahoney JJ, Fantegrossi WE, et al. (2007) MDMA use and neurocognition: a meta-analytic review. Psychopharmacology (Berl) 189: 531-537.
- Zakzanis KK, Campbell Z, Jovanovski D (2007) The neuropsychology of ecstasy (MDMA) use: a quantitative review. Human Psychopharmacology: Clinical and Experimental 22: 427-435.
- Gouzoulis-Mayfrank E, Fischermann T, Rezk M, Thimm B, Hensen G, et al. (2005) Memory performance in polyvalent MDMA (ecstasy) users who continue or discontinue MDMA use. Drug and Alcohol Dependence 78: 317-323.
- Thomasius R, Petersen K, Buchert R, Andresen B, Zapletalova P, et al. (2003) Mood, cognition and serotonin transporter availability in current and former ecstasy (MDMA) users. Psychopharmacology (Berl) 167: 85-96.
- Thomasius R, Zapletalova P, Petersen K, Buchert R, Andresen B, et al. (2006) Mood, cognition and serotonin transporter availability in current and former ecstasy (MDMA) users: The longitudinal perspective. J Psychopharmacol 20: 211-225.
- Klugman A, Gruzelier J (2003) Chronic cognitive impairment in users of ‘ecstasy’ and cannabis. World psychiatry : official journal of the World Psychiatric Association (WPA) 2: 184-190.
- Beatty WW, Katzung VM, Moreland VJ, Nixon SJ (1995) Neuropsychological performance of recently abstinent alcoholics and cocaine abusers. Drug Alcohol Depend 37: 247-253.
- Berry J, Van Gorp WG, Herzberg DS, Hinkin C, Boone K, et al. (1993) Neuropsychological deficits in abstinent cocaine abusers: Preliminary findings after two weeks of abstinence. Drug and Alcohol Dependence 32: 231-237.
- Cunha PJ, Nicastri S, Gomes LP, Moino RM, Peluso MA (2004) Neuropsychological impairments in crack cocaine-dependent inpatients: Preliminary findings. Revista Brasileira de Psiquiatria 26: 103-106.
- De Oliveira LG, Barroso LP, Silveira CM, Sanchez ZVDM, De Carvalho Ponce J, et al. (2009) Neuropsychological Assessment of Current and Past Crack Cocaine Users. Substance Use & Misuse 44: 1941-1957.
- Fox HC, Jackson ED, Sinha R (2009) Elevated cortisol and learning and memory deficits in cocaine dependent individuals: Relationship to relapse outcomes. Psychoneuroendocrinology 34: 1198-1207.
- Goldstein RZ, Leskovjan AC, Hoff AL, Hitzemann R, Bashan F, et al. (2004) Severity of neuropsychological impairment in cocaine and alcohol addiction: association with metabolism in the prefrontal cortex. Neuropsychologia 42: 1447-1458.
- Kumar DS, Benedict E, Wu O, Rubin E, Gluck MA, et al. (2019) Learning functions in short-term cocaine users. Addictive Behaviors Reports 9: 100169.
- Mittenberg W, Motta S (1993) Effects of chronic cocaine abuse on memory and learning. Archives of Clinical Neuropsychology 8: 477-483.
- O’Malley S, Adamse M, Heaton RK, Gawin FH (1992) Neuropsychological Impairment in Chronic Cocaine Abusers. The American Journal of Drug and Alcohol Abuse 18 131-144.
- Serper MR, Bergman A, Copersino ML, Chou JCY, Richarme D, et al. (2000) Learning and memory impairment in cocaine-dependent and comorbid schizophrenic patients. Psychiatry Research 93: 21-32.
- Vadhan NP, Myers CE, Benedict E, Rubin E, Foltin RW, et al. (2014) A decrement in probabilistic category learning in cocaine users after controlling for marijuana and alcohol use. Experimental and Clinical Psychopharmacology 22: 65-74.
- van Gorp WG, Wilkins JN, Hinkin CH, Moore LH, Hull J, et al. (1999) Declarative and Procedural Memory Functioning in Abstinent Cocaine Abusers. Archives of General Psychiatry 56: 85-89.
- Woicik PA, Moeller SJ, Alia-Klein N, Maloney T, Lukasik TM et al. (2009) The neuropsychology of cocaine addiction: Recent cocaine use masks impairment. Neuropsychopharmacology 34: 1112-1122.
- Potvin S, Stavro K, Rizkallah É, Pelletier J (2014) Cocaine and Cognition: A Systematic Quantitative Review. Journal of Addiction Medicine 8: 368-376.
- Vonmoos M, Hulka LM, Preller KH, Minder F, Baumgartner MR, et al. (2014) Cognitive Impairment in Cocaine Users is Drug-Induced but Partially Reversible: Evidence from a Longitudinal Study. Neuropsychopharmacol 39: 2200-2210.
- Robinson JA, Swanson KL (1990) Autobiographical memory: The next phase. Applied Cognitive Psychology 4: 321-335.
- Pillersdorf D, Scoboria A (2019) Cannabis-associated impairments in the fading affect bias and autobiographical memory specificity. Conscious Cogn 74: 102792.
- Mercuri K, Terrett G, Henry JD, Curran HV, Elliott M, et al. (2018) Episodic foresight deficits in regular, but not recreational, cannabis users. J Psychopharmacol 32: 876-882.
- Sofis MJ, Lemley SM, Budney AJ (2021) The Effects of Cannabis Use Frequency and Episodic Specificity Training on the Recall of Specific and Rewarding Events. Front Psychiatry 12: 643819.
- Gandolphe MC, Nandrino JL (2011) [Overgeneralization of autobiographical memory strategies in cannabis users and multiple psychoactive substance consumers]. Encephale 37: 144-152.
- Doss MK, Weafer J, Gallo DA, Wit H de (2018) MDMA Impairs Both the Encoding and Retrieval of Emotional Recollections. Neuropsychopharmacology 43: 791.
- Gandolphe MC, Nandrino JL, Hancart S, Vosgien V (2013) Autobiographical memory and differentiation of schematic models in substance-dependent patients. Journal of Behavior Therapy and Experimental Psychiatry 44: 114-121.
- Oliveira CCC de, Scheuer CI, Scivoletto S (2007) Autobiographical and semantic memory of adolescent drug users. Archives of Clinical Psychiatry (São Paulo) 34: 260-265.
- Henry JD, MacLeod MS, Phillips LH, Crawford JR (2004) A Meta-Analytic Review of Prospective Memory and Aging. Psychology and Aging 19: 27-39.
- Levent A, Davelaar EJ (2019) Illegal drug use and prospective memory: A systematic review. Drug and Alcohol Dependence 204: 107478.
- Nelson MR, Reid CM, Ryan P, Willson K, Yelland L (2006) Self-reported adherence with medication and cardiovascular disease outcomes in the Second Australian National Blood Pressure Study (ANBP2). Med J Aust 185: 487-489.
- Theunissen EL, Heckman P, de Sousa Fernandes Perna EB, Kuypers KPC, Sambeth A, et al. (2014) Rivastigmine but not vardenafil reverses cannabis-induced impairment of verbal memory in healthy humans. Psychopharmacology 232: 343-353.
- Cuttler C, LaFrance EM, Stueber A (2021) Acute effects of high-potency cannabis flower and cannabis concentrates on everyday life memory and decision making. Sci Rep 11: 13784.
- Hutten NR, Kuypers KP, van Wel JH, Theunissen EL, Toennes SW, et al. (2018) A single dose of cocaine enhances prospective memory performance. J Psychopharmacol 32: 883-892.
- Ramaekers J, Kauert G, Theunissen E, Toennes S, Moeller M (2009) Neurocognitive performance during acute THC intoxication in heavy and occasional cannabis users. J Psychopharmacol 23: 266-277.
- Ciorciari J, Marotte A (2011) Implications of MDMA use for prospective memory function and substance use patterns in an Australian sample: A web-based pilot study. Australian Journal of Psychology 63: 142-149.
- Cuttler C, McLaughlin RJ, Graf P (2012) Mechanisms underlying the link between cannabis use and prospective memory. PLoS ONE 7: 36820.
- Cuttler C, Spradlin A, Nusbaum AT, Whitney P, Hinson JM, et al. (2019) Joint effects of stress and chronic cannabis use on prospective memory. Psychopharmacology 236: 1973-1983.
- Fisk J, Montgomery C (2008) Real-world memory and executive processes in cannabis users and non-users. J Psychopharmacol 22: 727-736.
- McHale S, Hunt N (2008) Executive function deficits in short-term abstinent cannabis users. Hum Psychopharmacol 23: 409-415.
- Montgomery C, Seddon AL, Fisk JE, Murphy PN, Jansari A (2012) Cannabis-related deficits in real-world memory. Hum Psychopharmacol 27: 217-225.
- Arana JM, Blanco C, Meilán JJG, Pérez E, Carro J, et al. (2011) The impact of poly drug use on several prospective memory measures in a sample of university students. Revista Latinoamericana de Psicología. May;43(2):229–40.
- Bartholomew J, Holroyd S, Heffernan TM (2010) Does cannabis use affect prospective memory in young adults? J Psychopharmacol (Oxford) 24: 241-246.
- Bedi G, Redman J (2008) Ecstasy use and higher-level cognitive functions: weak effects of ecstasy after control for potential confounds. Psychol Med 38: 1319-1330.
- Braidwood R, Mansell S, Waldron J, Rendell PG, Kamboj SK, et al. (2018) Non-Dependent and Dependent Daily Cannabis Users Differ in Mental Health but Not Prospective Memory Ability. Front Psychiatry 9: 97.
- Hadjiefthyvoulou F, Fisk JE, Montgomery C, Bridges N (2011) Prospective memory functioning among ecstasy/polydrug users: evidence from the Cambridge Prospective Memory Test (CAMPROMPT). Psychopharmacology 215: 761-774.
- Rodgers J, Buchanan T, Scholey AB, Heffernan TM, Ling J, et al. (2003) Patterns of drug use and the influence of gender on self-reports of memory ability in ecstasy users: A web-based study. J Psychopharmacol (Oxford) 17: 389396.
- Gallagher DT, Hadjiefthyvoulou F, Fisk JE, Montgomery C, Robinson SJ, et al. (2014) Prospective memory deficits in illicit polydrug users are associated with the average long-term typical dose of ecstasy typically consumed in a single session. Neuropsychology 28: 43-54.
- Hadjiefthyvoulou F, Fisk JE, Montgomery C, Bridges N (2011) Everyday and prospective memory deficits in ecstasy/polydrug users. J Psychopharmacol 25: 453-464.
- Heffernan TM, Jarvis H, Rodgers J, Scholey AB, Ling J (2001) Prospective memory, everyday cognitive failure and central executive function in recreational users of Ecstasy. Hum Psychopharmacol 16: 607-612.
- Heffernan TM, Ling J, Scholey AB (2001) Subjective ratings of prospective memory deficits in MDMA ('ecstasy’) users. Hum Psychopharmacol 16: 339-344.
- Montgomery C, Hatton NP, Fisk JE, Ogden RS, Jansari A (2010) Assessing the functional significance of ecstasy-related memory deficits using a virtual paradigm. Hum Psychopharmacol 25: 318-325.
- Montgomery C, Fisk JE (2007) Everyday memory deficits in ecstasy-polydrug users. J Psychopharmacol (Oxford) 21: 709-717.
...
- Rendell PG, Gray TJ, Henry JD, Tolan A (2007) Prospective memory impairment in ‘ecstasy’ (MDMA) users. Psychopharmacology (Berl) 194: 497-504.
- Rodgers J, Buchanan T, Pearson C, Parrott A, Ling J, Heffernan T, et al. Differential experiences of the psychobiological sequelae of ecstasy use: Quantitative and qualitative data from an internet study. Journal of Psychopharmacology. 2006 May;20(3):437–46.
- Rodgers J, Buchanan T, Scholey A, Heffernan T, Ling J, et al. (2011) Prospective Memory: The Influence of Ecstasy, Cannabis and Nicotine Use and the WWW. The Open Addiction Journal 411: 44-45.
- Zakzanis KK, Young DA, Campbell Z (2003) Prospective memory impairment in abstinent MDMA (‘Ecstasy’) users. Cogn Neuropsychiatry 8: 141-53.
- Weinborn M, Woods SP, Nulsen C, Park K (2011) Prospective memory deficits in Ecstasy users: effects of longer ongoing task delay interval. J Clin Exp Neuropsychol 33: 1119-1128.
- Levent A, Davelaar EJ (2022) Recreational drug use and prospective memory. Psychopharmacology (Berl) 239: 909-922.
- Goldstein RZ, Craig AD (Bud), Bechara A, Garavan H, Childress AR, et al. (2009) The Neurocircuitry of Impaired Insight in Drug Addiction. Trends Cogn Sci 13: 372-380.
- Hester R, Simões-Franklin C, Garavan H (2007) Post-error behavior in active cocaine users: poor awareness of errors in the presence of intact performance adjustments. Neuropsychopharmacology 32: 1974-1984.
- Ferguson HJ, Brunsdon VEA, Bradford EEF (2021) The developmental trajectories of executive function from adolescence to old age. Sci Rep 11: 1382.
- Lehto JE, Juujärvi P, Kooistra L, Pulkkinen L (2003) Dimensions of executive functioning: Evidence from children. British Journal of Developmental Psychology 21: 59-80.
- Diamond A (2013) Executive Functions. Annu Rev Psychol 64: 135-168.
- Smith JL, Mattick RP, Jamadar SD, Iredale JM (2014) Deficits in behavioural inhibition in substance abuse and addiction: a meta-analysis. Drug Alcohol Depend 145: 1-33.
- Bornovalova MA, Lejuez CW, Daughters SB, Zachary Rosenthal M, et al. (2005) Impulsivity as a common process across borderline personality and substance use disorders. Clinical Psychology Review 25: 790-812.
- Verdejo-García A, Rivas-Pérez C, Vilar-López R, Pérez-García M (2007) Strategic self-regulation, decision-making and emotion processing in poly-substance abusers in their first year of abstinence. Drug and Alcohol Dependence 86: 139-146.
- Patkar AA, Murray HW, Mannelli P, Gottheil E, Weinstein SP, et al. (2004) Pre—Treatment Measures of Impulsivity, Aggression and Sensation Seeking Are Associated with Treatment Outcome for African—American Cocaine—Dependent Patients. Journal of Addictive Diseases 23: 109-122.
- Bechara A, Dolan S, Denburg N, Hindes A, Anderson SW, et al. (2001) Decision-making deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers. Neuropsychologia 39: 376-389.
- McDonald J, Schleifer L, Richards JB, de Wit H (2003) Effects of THC on Behavioral Measures of Impulsivity in Humans. Neuropsychopharmacology 28: 1356-1365.
- Ramaekers JG, Kauert G, van Ruitenbeek P, Theunissen EL, Schneider E, et al. (2006) High-Potency Marijuana Impairs Executive Function and Inhibitory Motor Control. Neuropsychopharmacol 31: 2296-2303.
- Ramaekers JG, van Wel JH, Spronk DB, Toennes SW, Kuypers KPC, et al. (2016) Cannabis and tolerance: acute drug impairment as a function of cannabis use history. Scientific Reports 6: 26843.
- van Wel JHP, Kuypers KPC, Theunissen EL, Toennes SW, Spronk DB, et al. (2013) Single doses of THC and cocaine decrease proficiency of impulse control in heavy cannabis users. British Journal of Pharmacology 170: 1410-1420.
- Hunault CC, Mensinga TT, Böcker KBE, Schipper CMA, Kruidenier M, et al. (2009) Cognitive and psychomotor effects in males after smoking a combination of tobacco and cannabis containing up to 69 mg delta-9-tetrahydrocannabinol (THC). Psychopharmacology 204: 85-94.
- Morie KP, Potenza MN (2021) A Mini-Review of Relationships Between Cannabis Use and Neural Foundations of Reward Processing, Inhibitory Control and Working Memory. Front Psychiatry 12: 657371.
- Wrege J, Schmidt A, Walter A, Smieskova R, Bendfeldt K, et al. (2014) Effects of Cannabis on Impulsivity: A Systematic Review of Neuroimaging Findings. Curr Pharm Des 20(: 2126-2137.
- Crane NA, Schuster RM, Fusar-Poli P, Gonzalez R (2013) Effects of Cannabis on Neurocognitive Functioning: Recent Advances, Neurodevelopmental Influences, and Sex Differences. Neuropsychol Rev 23: 117-137.
- Theunissen EL, Kauert GF, Toennes SW, Moeller MR, Sambeth A, et al. (2011) Neurophysiological functioning of occasional and heavy cannabis users during THC intoxication. Psychopharmacology 220: 341-350.
- Kuypers KPC, Wingen M, Samyn N, Limbert N, Ramaekers JG (2007) Acute effects of nocturnal doses of MDMA on measures of impulsivity and psychomotor performance throughout the night. Psychopharmacology 192: 111-119.
- Vollenweider FX, Gamma A, Liechti M, Huber T (1998) Psychological and Cardiovascular Effects and Short-Term Sequelae of MDMA (“Ecstasy”) in MDMA-Naive Healthy Volunteers. Neuropsychopharmacology 19: 241-251.
- Guillot CR (2008) MDMA and impulsivity: A review. Current Psychiatry Reviews 4: 63-72.
- Ramaekers JG, Kuypers KPC (2006) Acute Effects of 3,4-Methylenedioxymethamphetamine (MDMA) on Behavioral Measures of Impulsivity: Alone and in Combination with Alcohol. Neuropsychopharmacol 31: 1048-1055.
- Fillmore M, Rush C, Hays L (2005) Cocaine Improves Inhibitory Control in a Human Model of Response Conflict. Experimental and clinical psychopharmacology 13: 327-335.
- Garavan H, Kaufman JN, Hester R (2008) Acute Effects of Cocaine on the Neurobiology of Cognitive Control. Philosophical Transactions: Biological Sciences 363: 3267-3276.
- Fillmore MT, Rush CR, Hays L (2006) Acute effects of cocaine in two models of inhibitory control: implications of non-linear dose effects. Addiction 101: 1323-1332.
- Fillmore MT, Rush CR, Hays L (2002) Acute effects of oral cocaine on inhibitory control of behavior in humans. Drug and Alcohol Dependence 67: 157-167.
- Fontes MA, Bolla KI, Cunha PJ, Almeida PP, Jungerman F, et al. (2011) Cannabis use before age 15 and subsequent executive functioning. The British Journal of Psychiatry 198: 442-447.
- Gorey C, Kuhns L, Smaragdi E, Kroon E, Cousijn J (2019) Age-related differences in the impact of cannabis use on the brain and cognition: a systematic review. Eur Arch Psychiatry Clin Neurosci 269: 37-58.
- Gruber SA, Sagar KA, Dahlgren MK, Racine M, Lukas SE (2012) Age of onset of marijuana use and executive function. Psychology of Addictive Behaviors 26: 496-506.
- Piechatzek M, Indlekofer F, Daamen M, Glasmacher C, Lieb R, et al. (2009) Is moderate substance use associated with altered executive functioning in a population-based sample of young adults? Hum Psychopharmacol 24: 650-665.
- Cunha PJ, Nicastri S, de Andrade AG, Bolla KI (2010) The frontal assessment battery (FAB) reveals neurocognitive dysfunction in substance-dependent individuals in distinct executive domains: Abstract reasoning, motor programming, and cognitive flexibility. Addictive Behaviors 35: 875-881.
- Fontes MA, Bolla KI, Cunha PJ, Almeida PP, Jungerman F, et al. (2011) Frontal Assessment Battery (FAB) is a simple tool for detecting executive deficits in chronic cannabis users. Journal of Clinical and Experimental Neuropsychology 33: 523-531.
- Grant JE, Chamberlain SR, Schreiber L, Odlaug BL (2012) Neuropsychological deficits associated with cannabis use in young adults. Drug and Alcohol Dependence 121: 159-162.
- Hester R, Nestor L, Garavan H (2009) Impaired error awareness and anterior cingulate cortex hypoactivity in chronic cannabis users. Neuropsychopharmacology 34: 2450-2458.
- Lyons MJ, Bar JL, Panizzon MS, Toomey R, Eisen S, et al. (2004) Neuropsychological consequences of regular marijuana use: a twin study. Psychological Medicine 34: 1239-1250.
- Roberts GMP, Garavan H (2010) Evidence of increased activation underlying cognitive control in ecstasy and cannabis users. Neuroimage 52: 429-435.
- Tapert SF, Schweinsburg AD, Drummond SPA, Paulus MP, Brown SA, et al. (2007) Functional MRI of inhibitory processing in abstinent adolescent marijuana users. Psychopharmacology 194: 173-183.
- Dafters RI (2006) Chronic ecstasy (MDMA) use is associated with deficits in task-switching but not inhibition or memory updating executive functions. Drug Alcohol Depend 83: 181-184.
- Fox HC, McLean A, Turner JJD, Parrott AC, Rogers R, et al. (2002) Neuropsychological evidence of a relatively selective profile of temporal dysfunction in drug-free MDMA (‘ecstasy’) polydrug users. Psychopharmacology 162: 203-214.
- Morgan M, McFie L, Fleetwood L, Robinson J (2001) Ecstasy (MDMA): are the psychological problems associated with its use reversed by prolonged abstinence? Psychopharmacology 159: 294-303.
- Butler GKL, Montgomery AMJ (2004) Impulsivity, risk taking and recreational ‘ecstasy’ (MDMA) use. Drug and Alcohol Dependence 76: 55-62.
- Croft RJ, Mackay AJ, Mills AT, Gruzelier JG (2001) The relative contributions of ecstasy and cannabis to cognitive impairment. Psychopharmacology (Berl) 153: 373-379.
- Quednow BB, Kühn KU, Hoppe C, Westheide J, Maier W, et al. (2007) Elevated impulsivity and impaired decision-making cognition in heavy users of MDMA (‘Ecstasy’). Psychopharmacology (Berl) 189: 517-530.
- Wagner D, Becker B, Koester P, Gouzoulis-Mayfrank E, Daumann J (2013) A prospective study of learning, memory, and executive function in new MDMA users. Addiction 108: 136-145.
- Bolla KI, Rothman R, Cadet JL (1999) Dose-related neurobehavioral effects of chronic cocaine use. J Neuropsychiatry Clin Neurosci 11: 361-369.
- Colzato LS, van den Wildenberg WPM, Hommel B (2007) Impaired Inhibitory Control in Recreational Cocaine Users. García AV, editor. PLoS ONE 2: 1143.
- Fernández-Serrano MJ, Perales JC, Moreno-López L, Pérez-García M, Verdejo-García A (2012) Neuropsychological profiling of impulsivity and compulsivity in cocaine dependent individuals. Psychopharmacology (Berl) 219: 673-683.
- Fillmore MT, Rush CR (2012) Impaired inhibitory control of behavior in chronic cocaine users. Drug and Alcohol Dependence 66: 265-273.
- Hester R, Garavan H (2004) Executive dysfunction in cocaine addiction: evidence for discordant frontal, cingulate, and cerebellar activity. J Neurosci 24: 11017-11022.
- Kjome KL, Lane SD, Schmitz JM, Green C, Ma L, et al. (2010) Relationship between impulsivity and decision-making in cocaine dependence. Psychiatry Res 178: 299-304.
- Li C shan R, Milivojevic V, Kemp K, Hong K, Sinha R (2006) Performance monitoring and stop signal inhibition in abstinent patients with cocaine dependence. Drug and Alcohol Dependence 85: 205-212.
- Li C shan R, Huang C, Yan P, Bhagwagar Z, Milivojevic V, et al. (2008) Neural Correlates of Impulse Control During Stop Signal Inhibition in Cocaine-Dependent Men. Neuropsychopharmacol 33: 1798-1806.
- Liu S, Lane SD, Schmitz JM, Waters AJ, Cunningham KA, et al. (2011) Relationship between attentional bias to cocaine-related stimuli and impulsivity in cocaine-dependent subjects. The American Journal of Drug and Alcohol Abuse 37: 117-122.
- Abdulaal A, El Tantawy A, Ibrahim O, Elbadry H, Hassan H (2023) Cognitive dysfunction in adolescents with substance use disorder. Middle East Current Psychiatry 30: 13.
- Lane SD, Moeller FG, Steinberg JL, Buzby M, Kosten TR (2007) Performance of Cocaine Dependent Individuals and Controls on a Response Inhibition Task with Varying Levels of Difficulty. The American Journal of Drug and Alcohol Abuse 33: 717-726.
- van der Plas EAA, Crone EA, van den Wildenberg WPM, Tranel D, Bechara A (2009) Executive control deficits in substance-dependent individuals: A comparison of alcohol, cocaine, and methamphetamine and of men and women. Journal of Clinical and Experimental Neuropsychology 31: 706-719.
- Li G, Zhang Z, Zhang Y, Tang X, Li CSR (2023) The effects of cocaine use severity and abstinence on behavioral performance and neural processes of response inhibition. Psychiatry Research: Neuroimaging 336: 111734.
- Barrós-Loscertales A, Bustamante JC, Ventura-Campos N, Llopis JJ, Parcet MA, et al. (2011) Lower activation in the right frontoparietal network during a counting Stroop task in a cocaine-dependent group. Psychiatry Research: Neuroimaging 194: 111-118.
- Castelluccio BC, Meda SA, Muska CE, Stevens MC, Pearlson GD (2014) Error processing in current and former cocaine users. Brain Imaging Behav 8: 87-96.
- Connolly CG, Foxe JJ, Nierenberg J, Shpaner M, Garavan H (2012) The neurobiology of cognitive control in successful cocaine abstinence. Drug and Alcohol Dependence 121: 45-53.
- Czermainski FR, Willhelm AR, Santos ÁZ, Pachado MP, De Almeida RMM (2017) Assessment of inhibitory control in crack and/or cocaine users: a systematic review. Trends Psychiatry Psychother 39: 216-225.
- Bell RP, Foxe JJ, Ross LA, Garavan H (2014) Intact inhibitory control processes in abstinent drug abusers (I): A functional neuroimaging study in former cocaine addicts. Neuropharmacology 82: 143-150.
- Chai WJ, Abd Hamid AI, Abdullah JM (2018) Working Memory From the Psychological and Neurosciences Perspectives: A Review. Frontiers in Psychology 9.
- Cowan N (2014) Working Memory Underpins Cognitive Development, Learning, and Education. Educ Psychol Rev 26: 197-1223.
- Miller LL, McFarland DJ, Cornett TL, Brightwell DR, Wikler A (1977) Marijuana: effects on free recall and subjective organization of pictures and words. Psychopharmacology (Berl) 55: 257-262.
- Tinklenberg JR, Melges FT, Hollister LE, Gillespie HK (1970) Marijuana and immediate memory. Nature 226: 1171-112.
- Adam KCS, Doss MK, Pabon E, Vogel EK, de Wit H (2020) Δ9-Tetrahydrocannabinol (THC) impairs visual working memory performance: A randomized crossover trial. Neuropsychopharmacology 45: 1807-1816.
- Bossong MG, Jager G, van Hell HH, Zuurman L, Jansma JM, et al. (2012) Effects of Δ9-tetrahydrocannabinol administration on human encoding and recall memory function: a pharmacological FMRI study. J Cogn Neurosci 24: 588-599.
- D’Souza DC, Braley G, Blaise R, Vendetti M, Oliver S, et al. (2008) Effects of haloperidol on the behavioral, subjective, cognitive, motor, and neuroendocrine effects of Δ-9-tetrahydrocannabinol in humans. Psychopharmacology (Berl) 198: 587-603.
- Hart CL, van Gorp W, Haney M, Foltin RW, Fischman MW (2001) Effects of acute smoked marijuana on complex cognitive performance. Neuropsychopharmacology 25: 757-765.
- Hart CL, Ilan AB, Gevins A, Gunderson EW, Role K, et al. (2010) Neurophysiological and cognitive effects of smoked marijuana in frequent users. Pharmacology Biochemistry and Behavior 96: 333-341.
- Ilan AB, Smith ME, Gevins A (2004) Effects of marijuana on neurophysiological signals of working and episodic memory. Psychopharmacology (Berl) 176: 214-222.
- Ilan AB, Gevins A, Coleman M, ElSohly MA, de Wit H (2005) Neurophysiological and subjective profile of marijuana with varying concentrations of cannabinoids. Behav Pharmacol 16: 487-496.
- Owens MM, McNally S, Petker T, Amlung MT, Balodis IM, et al. (2019) Urinary tetrahydrocannabinol is associated with poorer working memory performance and alterations in associated brain activity. Neuropsychopharmacol 44: 613-619.
- Wesnes K, Annas P, Edgar C, Deeprose C, Karlsten R, et al. (2010) Nabilone produces marked impairments to cognitive function and changes in subjective state in healthy volunteers. J Psychopharmacol 24: 1659-1669.
- Curran HV, Travill RA (1997) Mood and cognitive effects of ± 3,4-methylenedioxymethamphetamine (MDMA, ‘ecstasy’): week-end ‘high’ followed by mid-week low. Addiction 92: 821-831.
- Stough C, King R, Papafotiou K, Swann P, Ogden E, et al. (2012) The acute effects of 3,4-methylenedioxymethamphetamine and d-methamphetamine on human cognitive functioning. Psychopharmacology (Berl) 220: 799-807.
- Dumont G, Van Hasselt J, De Kam M, Van Gerven J, Touw D, et al. (2010) Acute psychomotor, memory and subjective effects of MDMA and THC (co-) administration over time in healthy volunteers. European Neuropsychopharmacology 20: 235-236.
- Eriksson J, Vogel EK, Lansner A, Bergström F, Nyberg L (2015) Neurocognitive architecture of working memory. Neuron 88: 33-46.
- Solowij N, Michie PT, Fox AM (1995) Differential impairments of selective attention due to frequency and duration of cannabis use. Biol Psychiatry 37: 731-739.
- Solowij N, Stephens RS, Roffman RA, Babor T, Kadden R, et al. (2002) Cognitive functioning of long-term heavy cannabis users seeking treatment. JAMA 287: 1123-1131.
- Thames AD, Arbid N, Sayegh P (2014) Cannabis use and neurocognitive functioning in a non-clinical sample of users. Addictive Behaviors 39: 994-999.
- Becker B, Wagner D, Gouzoulis-Mayfrank E, Spuentrup E, Daumann J (2010) The impact of early-onset cannabis use on functional brain correlates of working memory. Prog Neuropsychopharmacol Biol Psychiatry 34: 837-845.
- Chang L, Yakupov R, Cloak C, Ernst T (2006) Marijuana use is associated with a reorganized visual-attention network and cerebellar hypoactivation. Brain 129: 1096-1112.
- Jager G, Kahn R, van den Brink W, Ree J, Ramsey N (2006) Long-term effects of frequent cannabis use on working memory and attention: An fMRI study. Psychopharmacology 185: 358-368.
- Jager G, Block RI, Luijten M, Ramsey NF (2010) Cannabis use and memory brain function in adolescent boys: a cross-sectional multicenter fMRI study. J Am Acad Child Adolesc Psychiatry 49: 561-572.
- Kanayama G, Rogowska J, Pope HG, Gruber SA, Yurgelun-Todd DA (2004) Spatial working memory in heavy cannabis users: a functional magnetic resonance imaging study. Psychopharmacology (Berl) 176: 239-247.
- Jacobsen LK, Mencl WE, Westerveld M, Pugh KR (2004) Impact of cannabis use on brain function in adolescents. Ann N Y Acad Sci 1021: 384-390.
- Lorenzetti V, Alonso-Lana S, Youssef GJ, Verdejo-Garcia A, Suo C, et al. (2016) Adolescent Cannabis Use: What is the Evidence for Functional Brain Alteration? Curr Pharm Des 22: 6353-6365.
- Padula CB, Schweinsburg AD, Tapert SF (2007) Spatial Working Memory Performance and fMRI Activation Interactions in Abstinent Adolescent Marijuana Users. Psychol Addict Behav 21: 478-487.
- Schweinsburg AD, Schweinsburg BC, Medina KL, McQueeny T, Brown SA, et al. (2010) The Influence of Recency of Use on fMRI Response During Spatial Working Memory in Adolescent Marijuana Users. J Psychoactive Drugs 42: 401-412.
- Lovell ME, Akhurst J, Padgett C, Garry MI, Matthews A (2020) Cognitive outcomes associated with long-term, regular, recreational cannabis use in adults: A meta-analysis. Exp Clin Psychopharmacol 28: 471-494.
- Murphy PN, Ryland I, Wolohan F, Bartholomew J (2021) ‘Ecstasy’ (MDMA) and visuospatial processing: A follow-up systematic review. Psychobiological issues in substance use and misuse. Routledge/Taylor & Francis Group, New York, USA.
- Jacobsen LK, Mencl WE, Pugh KR, Skudlarski P, Krystal JH (2004) Preliminary evidence of hippocampal dysfunction in adolescent MDMA (“ecstasy”) users: possible relationship to neurotoxic effects. Psychopharmacology 173: 383-390.
- Montgomery C, Fisk JE, Newcombe R, Murphy PN (2005) The differential effects of ecstasy/polydrug use on executive components: shifting, inhibition, updating and access to semantic memory. Psychopharmacology (Berl) 182: 262-276.
- Montgomery C, Fisk JE (2008) Ecstasy-related deficits in the updating component of executive processes. Hum Psychopharmacol 23: 495-511.
- Reay JL, Hamilton C, Kennedy DO, Scholey AB (2006) MDMA polydrug users show process-specific central executive impairments coupled with impaired social and emotional judgement processes. J Psychopharmacol 20: 385-388.
- Wareing M, Fisk JE, Murphy PN (2000) Working memory deficits in current and previous users of MDMA ('ecstasy’). Br J Psychol 91: 181-188.
- Hanson KL, Luciana M (2010) Neurocognitive impairments in MDMA and other drug users: MDMA alone may not be a cognitive risk factor. Journal of Clinical and Experimental Neuropsychology 32: 337-349.
- Wareing M, Fisk JE, Murphy P, Montgomery C (2004) Verbal working memory deficits in current and previous users of MDMA. Hum Psychopharmacol 19: 225-234.
- Wareing M, Fisk JE, Murphy P, Montgomery C (2005) Visuo-spatial working memory deficits in current and former users of MDMA ('ecstasy’). Hum Psychopharmacol 20: 115-123.
- Bhattachary S, Powell JH (2001) Recreational use of 3,4-methylenedioxymethamphetamine (MDMA) or ‘ecstasy’: Evidence for cognitive impairment. Psychological Medicine 31: 647-658.
- Daumann J, Fimm B, Willmes K, Thron A, Gouzoulis-Mayfrank E (2003) Cerebral activation in abstinent ecstasy (MDMA) users during a working memory task: a functional magnetic resonance imaging (fMRI) study. Brain Res Cogn Brain Res 16: 479-487.
- Jager G, de Win MML, van der Tweel I, Schilt T, Kahn RS, et al. (2008) Assessment of Cognitive Brain Function in Ecstasy Users and Contributions of Other Drugs of Abuse: Results from an fMRI Study. Neuropsychopharmacology 33: 247-258.
- Jager G, de Win MM, Vervaeke HK, Schilt T, Kahn RS, et al. (2007) Incidental use of ecstasy: no evidence for harmful effects on cognitive brain function in a prospective fMRI study. Psychopharmacology 193: 403-414.
- Colzato LS, Huizinga M, Hommel B (2009) Recreational cocaine polydrug use impairs cognitive flexibility but not working memory. Psychopharmacology 207: 225-234.
- Kübler A, Murphy K, Garavan H (2005) Cocaine dependence and attention switching within and between verbal and visuospatial working memory. European Journal of Neuroscience 21: 1984-1992.
- Rahman Q, Clarke CD (2005) Sex differences in neurocognitive functioning among abstinent recreational cocaine users. Psychopharmacology 181: 374-380.
- Sanvicente-Vieira B, Kommers-Molina J, Nardi TD, Francke I, Grassi-Oliveira R (2016) Crack-cocaine dependence and aging: effects on working memory. Brazilian Journal of Psychiatry 38: 58-60.
- Soar K, Mason C, Potton A, Dawkins L (2012) Neuropsychological effects associated with recreational cocaine use. Psychopharmacology (Berl) 222: 633-643.
- Madoz-Gúrpide A, Blasco-Fontecilla H, Baca-García E, Ochoa-Mangado E (2011) Executive dysfunction in chronic cocaine users: An exploratory study. Drug Alcohol Depend 117: 55-58.
- Vonmoos M, Hulka LM, Preller KH, Baumgartner MR, Stohler R, et al. (2013) Cognitive dysfunctions in recreational and dependent cocaine users: role of attention-deficit hyperactivity disorder, craving and early age at onset. British Journal of Psychiatry 203: 35-43.
- Bustamante JC, Barrós-Loscertales A, Ventura-Campos N, Sanjuán A, Llopis JJ, et al. (2011) Right parietal hypoactivation in a cocaine-dependent group during a verbal working memory task. Brain Res 1375: 111-119.
- Frazer KM, Manly JJ, Downey G, Hart CL (2017) Assessing cognitive functioning in individuals with cocaine use disorder. Journal of Clinical and Experimental Neuropsychology 40: 619-632.
- Tomasi D, Goldstein RZ, Telang F, Maloney T, Alia-Klein N, et al. (2007) Widespread disruption in brain activation patterns to a working memory task during cocaine abstinence. Brain Research 1171: 83-92.
- Jovanovski D, Erb S, Zakzanis KK (2005) Neurocognitive Deficits in Cocaine Users: A Quantitative Review of the Evidence. Journal of Clinical and Experimental Neuropsychology 27: 189-204.
- Gonzalez CA, Figueroa IJ, Bellows BG, Rhodes D, Youmans RJ (2013) A New Behavioral Measure of Cognitive Flexibility. Engineering Psychology and Cognitive Ergonomics Understanding Human Cognition. Springer, Berlin, Berlin.
- Cools R (2015) Neuropsychopharmacology of Cognitive Flexibility. In: Toga AW (ed.). Brain Mapping.: Academic Press, Waltham, USA.
- Anderson BM, Rizzo M, Block RI, Pearlson GD, O’Leary DS (2010) Sex, Drugs, and Cognition: Effects of Marijuana. Journal of Psychoactive Drugs 42: 413-424.
- Curran HV, Brignell C, Fletcher S, Middleton P, Henry J (2002) Cognitive and subjective dose-response effects of acute oral Delta 9-tetrahydrocannabinol (THC) in infrequent cannabis users. Psychopharmacology (Berl) 164: 61-70.
- Weinstein A, Brickner O, Lerman H, Greemland M, Bloch M, et al. (2008) A study investigating the acute dose-response effects of 13 mg and 17 mg Delta 9- tetrahydrocannabinol on cognitive-motor skills, subjective and autonomic measures in regular users of marijuana. J Psychopharmacol 22: 441-451.
- Hasler F, Studerus E, Lindner K, Ludewig S, Vollenweider F (2009) Investigation of serotonin-1A receptor function in the human psychopharmacology of MDMA. J Psychopharmacol 23: 923-935.
- Burke CO, Boutouis S, Spence JS, Filbey FM (2025) Residual and enduring effects of cannabis use on cognitive and psychomotor function: A study of adults during unrestricted cannabis use, short-term abstinence, and protracted abstinence. Exp Clin Psychopharmacol 33: 53-61.
- Pope HG, Gruber AJ, Hudson JI, Huestis MA, Yurgelun-Todd D (2001) Neuropsychological performance in long-term cannabis users. Arch Gen Psychiatry 58: 909-915.
- Scholes KE, Martin-Iverson MT (2010) Cannabis use and neuropsychological performance in healthy individuals and patients with schizophrenia. Psychol Med 40: 1635-1646.
- Selamoglu A, Langley C, Crean R, Savulich G, Cormack F, et al. (2021) Neuropsychological performance in young adults with cannabis use disorder. J Psychopharmacol 35: 1349-1355.
- Lahanas S, Cservenka A (2019) Frequent marijuana use and cognitive flexibility in young adult college students. Journal of Drug and Alcohol Research.
- Lane SD, Cherek DR, Tcheremissine OV, Steinberg JL, Sharon JL (2007) Response perseveration and adaptation in heavy marijuana-smoking adolescents. Addict Behav 32: 977-990.
- Pope HG, Yurgelun-Todd D (1996) The residual cognitive effects of heavy marijuana use in college students. JAMA 275: 521-527.
- Bolla KI, Brown K, Eldreth D, Tate K, Cadet JL (2002) Dose-related neurocognitive effects of marijuana use. Neurology 59: 1337-1343.
- Figueiredo PR, Tolomeo S, Steele JD, Baldacchino A (2020) Neurocognitive consequences of chronic cannabis use: a systematic review and meta-analysis. Neuroscience & Biobehavioral Reviews 108: 358-369.
- Verdejo-García AJ, López-Torrecillas F, Aguilar de Arcos F, Pérez-García M (2005) Differential effects of MDMA, cocaine, and cannabis use severity on distinctive components of the executive functions in polysubstance users: a multiple regression analysis. Addict Behav 30: 89-101.
- Alonso-Matias L, Reyes-Zamorano E, Gonzalez-Olvera JJ (2019) Cognitive functions of subjects with cocaine and crack dependency disorder during early abstinence. Rev Neurol 68: 271-280.
- Ersche KD, Roiser JP, Robbins TW, Sahakian BJ (2008) Chronic cocaine but not chronic amphetamine use is associated with perseverative responding in humans. Psychopharmacology (Berl) 197: 421-431.
- Hanlon CA, Dufault DL, Wesley MJ, Porrino LJ (2011) Elevated gray and white matter densities in cocaine abstainers compared to current users. Psychopharmacology 218: 681-692.
- Kelley BJ, Yeager KR, Pepper TH, Beversdorf DQ (2005) Cognitive Impairment in Acute Cocaine Withdrawal. Cogn Behav Neurol 18: 108-112.
- Simon SL, Domier CP, Sim T, Richardson K, Rawson RA, et al. (2001) Cognitive Performance of Current Methamphetamine and Cocaine Abusers. Journal of Addictive Diseases 21: 61-74.
- Verdejo-Garcia A, Clark L, Verdejo-Román J, Albein-Urios N, Martinez-Gonzalez JM, et al. (2015) Neural substrates of cognitive flexibility in cocaine and gambling addictions. The British Journal of Psychiatry 207: 158-164.
- Verdejo-García AJ, Perales JC, Pérez-García M (2007) Cognitive impulsivity in cocaine and heroin polysubstance abusers. Addict Behav 32: 950-966.
- Woicik PA, Urban C, Alia-Klein N, Henry A, Maloney T, et al. (2011) A pattern of perseveration in cocaine addiction may reveal neurocognitive processes implicit in the Wisconsin Card Sorting Test. Neuropsychologia 49: 1660-1669.
- Fernández-Serrano MJ, Pérez-García M, Schmidt Río-Valle J, Verdejo-García A (2010) Neuropsychological consequences of alcohol and drug abuse on different components of executive functions. J Psychopharmacol (Oxford) 24: 1317-1332.
- Fernández-Serrano MJ, Pérez-García M, Verdejo-García A (2011) What are the specific vs. generalized effects of drugs of abuse on neuropsychological performance? Neurosci Biobehav Rev 35: 377-406.
- Cunha PJ, Bechara A, de Andrade AG, Nicastri S (2011) Decision-Making Deficits Linked to Real-life Social Dysfunction in Crack Cocaine-Dependent Individuals. Am J Addict 20: 78-86.
- Lundqvist T (2005) Cognitive consequences of cannabis use: Comparison with abuse of stimulants and heroin with regard to attention, memory and executive functions. Pharmacology Biochemistry and Behavior 81: 319-330.
- Kastner JW, May W, Hildman L (2001) Relationship between language skills and academic achievement in first grade. Percept Mot Skills 92: 381-390.
- Kendler KS, Ohlsson H, Fagan AA, Lichtenstein P, Sundquist J, et al. (2018) Academic Achievement and Drug Abuse Risk Assessed Using Instrumental Variable Analysis and Co-relative Designs. JAMA Psychiatry 7: 1182-1188.
- King KM, Meehan BT, Trim RS, Chassin L (2006) Substance use and academic outcomes: Synthesizing findings and future directions. Addiction 101: 1688-1689.
- Balconi M, Finocchiaro R, Campanella S (2014) Reward Sensitivity, Decisional Bias, and Metacognitive Deficits in Cocaine Drug Addiction. Journal of Addiction Medicine 8: 399-406.
- Moeller SJ, Fleming SM, Gan G, Zilverstand A, Malaker P, et al. (2016) Metacognitive impairment in active cocaine use disorder is associated with individual differences in brain structure. Eur Neuropsychopharmacol 2: 653-662.
- Moeller SJ, Kundu P, Bachi K, Maloney T, Malaker P, et al. (2020) Self-awareness of problematic drug use: Preliminary validation of a new fMRI task to assess underlying neurocircuitry. Drug Alcohol Depend 209: 107930.
- Verdejo-García A, Pérez-García M (2008) Substance abusers’ self-awareness of the neurobehavioral consequences of addiction. Psychiatry Research 158: 172-180.
- Lysaker P, Bell M, Bryson G, Kaplan E (1998) Neurocognitive function and insight in schizophrenia: support for an association with impairments in executive function but not with impairments in global function. Acta psychiatrica Scandinavica.
- Buckley RF, Laming G, Chen LPE, Crole A, Hester R (2016) Assessing Error Awareness as a Mediator of the Relationship between Subjective Concerns and Cognitive Performance in Older Adults. PLoS ONE 11.
- Khurana A, Romer D, Betancourt LM, Hurt H (2017) Working Memory Ability and Early Drug Use Progression as Predictors of Adolescent Substance Use Disorders. Addiction 112: 1220-1228.
- Müller CP (2013) Episodic Memories and Their Relevance for Psychoactive Drug Use and Addiction. Front Behav Neurosci 7: 34.
- Zilverstand A, Huang AS, Alia-Klein N, Goldstein RZ (2018) Neuroimaging Impaired Response Inhibition and Salience Attribution in Human Drug Addiction: A Systematic Review. Neuron 98: 886-903.
- Noël X, Brevers D, Bechara A (2013) A neurocognitive approach to understanding the neurobiology of addiction. Curr Opin Neurobiol 23: 632-638.
- Jordan CJ, Andersen SL (2017) Sensitive periods of substance abuse: Early risk for the transition to dependence. Developmental Cognitive Neuroscience 25: 29-44.
- Paus T (2005) Mapping brain maturation and cognitive development during adolescence. Trends Cogn Sci 9: 60-68.
- Schneider M (2008) Puberty as a highly vulnerable developmental period for the consequences of cannabis exposure. Addict Biol 13: 253-263.
- Winters KC, Arria A (2011) Adolescent Brain Development and Drugs. Prev Res 18: 21-24.
- Salmanzadeh H, Ahmadi-Soleimani SM, Pachenari N, Azadi M, Halliwell RF, et al. (2020) Adolescent drug exposure: A review of evidence for the development of persistent changes in brain function. Brain Res Bull 156: 105-117.