Some Psychobiological Implications of Cannabis Use

(i) Cannabis use: an important topic

Evidence from a number of countries indicates that cannabis, or marijuana as it is

sometimes called, is the most commonly used of drugs for which possession and

use have traditionally been prohibited by law. For example, in the United Kingdom

the 2015-16 Crime Survey for England and Wales (Lader, 2016) estimated that over

9.6 million people aged 16 to 59 years in those countries had used cannabis at some

time in their lives. The corresponding estimates for use in the last year and last

month, respectively, were approximately 2.1 million and 1.1 million people. In each

case these were the largest estimates of consumption for any prohibited drug. In the

United States, 8.3% of the population aged 12 years or older were estimated to have

used cannabis in the past month in 2015. Cannabis was not only the most commonly

used prohibited drug, but was also the drug most commonly associated with major

depressive episodes in the previous year within the 12 to 17 years age range

(Center for Behavioral Health Statistics and Quality, 2016). The importance of

cannabis use as a topic for research may be seen to lie in the combination of its

relative popularity as a drug, and reviews of scientific evidence indicating that its use

may be associated with impairments in neurocognitive performance (Broyd et al.,

2016; Ganzer et al., 2016; Volkow et al., 2016), changes in brain structures

(Lorenzetti et al., 2013, 2016; Malchow et al., 2013; Rochetti et al., 2013), and

changes in neurotransmission (Colizzi et al., 2016; Sami et al., 2015; Szabo, 2014).

This evidence suggests that the relationship of cannabis use to such impairments

has potential implications for the health of a large number of people Furthermore,

public debates concerning the removal of legal prohibitions concerning cannabis

use, and the media coverage of these debates, add further to the importance and

public relevance of research into the psychobiological implications of cannabis use.

The objective of this chapter is to provide an overview of evidence which highlights

the interrelatedness of effects upon neurotransmission, brain structures, and

neurocognitive performance, and provides a foundation for future research.

(ii) What is cannabis?

Three main varieties of plant have been identified within the genus ‘cannabis’, these

being cannabis sativa, cannabis indica, and cannabis ruderalis. Disagreement exists

regarding whether or not these varieties constitute different taxonomic categories or

a single species (de Meijer, 2014; Gloss, 2015; Hilig & Mahlberg, 2004). ‘Cannabis’

is the name given to the recreationally used drug derived from the buds and leaves

of the cannabis plant. In some countries, notably the United States, the name

‘marijuana’ is often used for this drug, rather than cannabis (NIDA, 2016).

Recreational self-administration principally takes the form of smoke inhalation,

although oral administration in the form of ‘cakes’ or ‘tea’ is also known (Hazekamp

& Pappas, 2014; Heustis & Smith, 2014). If the grass like substance harvested from

the plant is sieved into a powder and then compressed and heated, a solid block is

formed which is referred to as cannabis resin, which is then self-administered

through smoke inhalation (Advisory Council on the Misuse of Drugs, 2008; NIDA,

2016). The inhalation of vapour from the heating of an oil extract from the leaves of

the cannabis plant, sometimes referred to as dabbing, has developed as a means of

self-administration in recent years, partly because the process of producing the oil

leads to a relatively potent form of cannabis (Krauss et al, 2015; Loflin & Earleywine,

2014). The commonly self-reported desired effects of cannabis consumption include

increased feelings of relaxation, an elevated mood level, and enhancements in

sensory perception (Grinspoon et al., 2005; Winstock et al., 2010). The clinical

administration of cannabis based medications may include oral ingestion, sublingual,

rectal, dermal, eye drops, and intravenous routes (Heustis & Smith, 2014; Scuderi et

al., 2009).

The number of separately identified compounds isolated from the cannabis sativa

plant has grown steadily since the 1980s, with 545 identified compounds being

reported by Elsohly and Gul (2014). This total of 545 included 104 identified as being

cannabinoids by their structure. This group of cannabinoids includes those

compounds considered to be psychoactive, most notably (-)-Δ9-

tetrahydrocannabinol (Δ9-THC) (Pertwee, 1988). As this cannabinoid is seen to be

chiefly responsible for the psychoactive effects of cannabis, descriptions of the

potency of cannabis are generally related to the Δ9-THC concentration of a given

supply (Freeman et al., 2014; Hardwick & King, 2008). It is the high Δ9-THC

concentration of the oil extracted from cannabis plant products for vapour inhalation

which makes it a potent form of the drug (Mahmedic et al., 2010; Loflin & Earleywine,

2014). The intensive and selective breeding of cannabis plants, together with the use

of cuttings from the flowering tops of the plant, have led to the production of

cannabis with elevated levels of Δ9-THC, sometimes referred to as sinsemilla, or

colloquially by users as ‘skunk’ which has become increasingly prevalent for

consumption by smoking since the 1990s in the United Kingdom (Freeman et al.,

2014; Hardwick & King, 2008), the United States (ElSohley et al., 2016), and

Australia (Swift et al., 2013). Importantly, It has been demonstrated that Δ9-THC

activates dopaminergic activity in the ventral tegmental and substantia nigra, which

are both implicated in neural substrates relevant to substance addiction generally

(French et al., 1997). The bioavailability level of THC consumed through cannabis

smoking has been reported to be approximately 25%, although much variability in

this measure can be found both within and between individuals (Heustis & Smith,

2014).

Another cannabinoid, cannabidiol (CBD), is not generally considered psychoactive

because of its minimal affinity for endogenous cannabinoid receptors (see below),

but has well documented beneficial effects which for the treatment of anxiety and

psychosis, respectively (Blessing et al., 2015; Fakhoury, 2015; Scuderi et al., 2009).

From a psychological perspective, therefore, the description of CBD as non-

psychoactive in psychopharmacological literature does not mean that it is without

effect upon psychological processes and related behaviour. As most of the research

on cannabinoids relevant to psychological functioning has focussed particularly upon

THC, this chapter will also adopt this focus. Cannabinoids originating from plant

extract in their production are referred to collectively as phytocannabinoids.

However, synthetic cannabinoids have been produced for clinical purposes (e.g.

dronabinol and nabilone; see Wright & Guy, 2014), and have more recently also

been produced for illegal distribution for recreational purposes (Thomas et al., 2014).

(iii) Cannabis and neurotransmission

One way in which cannabis exerts effects upon psychological functioning and related

behaviour is through acting upon the processes of neurotransmission. This raises

the distinction between exogenous cannabinoids taken into the body, predominantly

by smoking, and endogenous cannabinoids (generally referred to as

endocannabinoids) which are naturally occurring compounds within the central

nervous system (CNS) known to modulate several important aspects of CNS

monoamine functioning (Van Bockstaele, 2013). Exogenous cannabinoids have an

affinity for the neuronal receptors normally acted upon by endocannabinoids,

although they can also act upon cells outside the endocannabinoid system (Pertwee

& Cascio, 2014).

Two major G-protein coupled receptors within the endocannabinoid system (ECS)

have been discovered, and are referred to as CB1 and CB2 respectively, with Δ9-

THC predominantly exerting its psychoactive effects through the CB1 receptor which

is most frequently found presynaptically on axon terminals, where its activation has

been shown to mediate synaptic inhibition. However, the functional role of CB2

receptors is less well understood than that of CB1 receptors (Pertwee & Cascio,

2014). Whilst research concerning cannabinoid related activity has focussed

predominantly upon the CB1 and CB2 receptors, which may be distinguished by

their respective protein structures and different pattern of bodily distribution (Cabrel

& Griffin-Thomas, 2009; Szabo, 2014), it should be noted that other receptor

structures exist which may be also be regarded as cannabinoid receptors (Marcu et

al., 2013).

In reviewing the affinity of Δ9-THC for both CB1 and CB2 receptors, Pertwee and

Cascio (2014) concluded that the effect sizes demonstrated by its activation of both

receptor types was consistent with it being classified as a partial agonist for both,

with more effective agonistic effects being demonstrated by the synthetic Δ9-THC

analogue nabilone used in the treatment of multiple sclerosis (see Wright & Guy,

2014), and by two synthetic cannabinoids known to be used recreationally. The

larger agonistic effects of recreationally used synthetic cannabinoids, manufactured

and disseminated through unregulated criminal channels, represents one source of

increasing concern regarding the effects of their use (Thomas et al., 2014), and

poses important questions to be addressed by future research.

CB1 receptors have been identified in many parts of the brain including the prefrontal

cortex, amygdala, hippocampus, nucleus accumbens, ventral tegmental area,

cerebellum and basal ganglia (Herkenham et al., 1991; LÓpez-Moreno et al, 2008).

CB2 receptors are also present within the cerebral cortex, hippocampus, globus

pallidus, cerebellum, and other brain areas, and are also to be found in the

peripheral immune system (Pertwee et al., 2010; Szabo, 2014). Rodent studies of

CB1 receptors within the prefrontal cortex have demonstrated that they play a role in

modulating the secretion of glutamate (Polissidis et al., 2013), gamma-aminobutyric

acid (GABA) (Cass et al., 2014), serotonin (Sartim et al., 2016), dopamine (Draycott

et al., 2014), and acetylcholine (Davis & Nomikos, 2008). Similarly, within the

hippocampus they have been demonstrated to modulate the secretion of glutamate

(Talani et al., 2016), GABA (Laaris et al., 2010), serotonin (Nasehi et al., 2017),

dopamine (Loureiro et al., 2015), and acetylcholine (Navakkode & Korte, 2014).

Finally, within the amygdala CB1 receptors have been demonstrated to modulate the

secretion of glutamate (Schmidt et al., 2011), GABA (Varodayan et al., 2015), and

dopamine (Zarrindast et al., 2011). The range of neurotransmitter systems

modulated by CB1 receptors in brain areas contributing to the support of many

important psychological and behavioural functions, highlights the potential for impact

upon these functions arising from the consumption of exogenous opiates with an

affinity with these receptors. However, the reliance upon rodent studies for the

development of our knowledge regarding the role of CB1 receptors in the brain

needs to be noted as a limiting factor in the conclusions which can be made

regarding human brain functioning.

Two processes which support the efficient acquisition and retention of memories in

learning are the long-term potentiation (LTP) and long-term depression (LTD) of

synaptic transmission (Bliss & Collingridge, 1993). The ECS has been demonstrated

to have a role in supporting both LTP and LTD through the retrograde signalling of

an endocannabinoid neurotransmitter secreted from postsynaptic membranes (Xu &

Chen, 2015). By acting upon presynaptic CB1 receptors, excitatory glutamatergic

transmission may be potentiated whilst inhibitory GABAergic transmission may be

depressed, with these processes being seen to enhance the effectiveness of brain

functioning. Exogenously administered CB1 agonists have been shown to disturb the

induction of LTP and LTD in rat studies (Abush & Akirav, 2010; Goodman &

Packard, 2015; Hoffman et al., 2007) with complex molecular processes being

implicated in this disruption (Chen et al., 2013; Navakkode & Korte, 2014). These

studies have particularly highlighted the potential for cannabinoid induced disruption

of LTP in the hippocampus, with consequent possible implications for the impairment

of learning and memory performance. The importance of LTP in the dorsolateral

prefrontal cortex (DLPFC) for learning and memory in healthy drug free human

participants has also been demonstrated (Rajji et al., 2013), raising the possibility

that exogenous cannabinoid induced LTP disruption involving cortical CB1 receptors

would be another potential source for learning and memory performance

impairments. The DLPFC has been implicated in a number of aspects of human

executive functioning (Enriquez-Geppert et al., 2013; Suhr & Hammers, 2010, Yuan

& Raz, 2014), including visusopatial working memory (Zimmer, 2008), so that a wide

range of psychological functions would potentially be vulnerable cannabinoid

induced LTP disruption in this brain area.

The effects of an early onset age for recreational cannabis use constitute one area of

particular concern in the literature, with early onset having been shown to be related

to the enhanced impairment of cognitive performance reported by some studies

(Broyd et al., 2016; Schweinsburg et al., 2008). Rodent studies have indicated that

adolescent exposure to CB1 agonists can be associated with the impairment of

hippocampal neurogenesis and increased stress reactivity in male rats (Lee et al.,

2014), and the impaired development of inhibitory GABA functioning in the prefrontal

cortex (Cass et al. 2014). Adolescent (i.e. at 28 days of age) administration of Δ9-

THC has been shown to produce a persistent neuroinflammatory state in the

prefrontal cortex of rats (Zamberletti et al., 2015), although the administration of an

ultralow dose to older rats (8 weeks) has been found to be neuroprotective

(Fishbein-Kaminietsky et al., 2014). Whilst findings such as these may have potential

implications for our understanding of the effects of early cannabis exposure on

human psychological functioning, these implications are limited by the differences

between rodent and human anatomy and functioning. A review of rodent studies

concerning the effects of adolescent cannabis exposure is provided by Renard et al

(2016).

In considering the effects of cannabinoids upon neurotransmission, it is important to

note the growth in the use of potent forms of cannabis with high Δ9-THC

concentrations for smoking or inhalation (ElSohly et al., 2016; Loflin & Earleywine,

2014), and also the use of synthetic cannabinoids with stronger affinities for CB1

receptors than Δ-9THC (Centres for Disease Control and Prevention, 2013; Thomas

et al., 2014). Both of these trends in consumption raise the possibility that alterations

to neurotransmission may be potentiated, with consequent effects for cognitive and

behavioural functioning.

The potential effects of Δ9-THC upon neurotransmission described above should be

seen as occurring within a pharmacokinetic context of this compound being highly

lipophilic, and therefore readily stored in human adipose tissue for subsequent slow

release into blood circulation (Ashton, 2001). Although 80 to 90% of consumed Δ9-

THC is excreted from the body within 5 days (Heustis, 2005), its presence in the

urine of chronic cannabis users has been detected up to 24 days since consumption

(Lowe et al., 2009). Consequently, the effects of Δ9-THC upon neurotransmission

may be expected mainly within the first 5 days since consumption, although the

possibility of effects over a more extended period in the month since consumption

cannot be ruled out.

(iv) Cannabis and structural changes to the brain.

Studies performed in vitro have demonstrated that Δ9-THC and other CB1 agonists

can be neurotoxic with regard to cell death and reduced synaptic connections

(Bologov et al., 2011; Chan et al., 1998; Kim & Thayer, 2001). Rodent studies have

demonstrated structural changes in the hippocampus related to Δ9-THC exposure

(Landfield et al., 1988) and to administration of the CB1 agonist WIN,55,212-2

(Lawston et al., 2000). Structural changes in the medial prefrontal cortex and

nucleus accumbens related to Δ9-THC administration have also been reported (Kolb

et al., 2006). Such findings demonstrate one mechanism whereby structural changes

in the brain could occur. However, rodent studies have also demonstrated

neuroprotective properties for ultralow doses of Δ9-THC (Assaf et al., 2011;

Fishbein-Kaminietsky et al., 2014). Mechanisms reflecting the internal state of the

cell and its viability have been proposed as a possible basis for these differential

effects of Δ9-THC, with poorer initial viability enhancing vulnerability to neurotoxicity

(Bologov et al. 2011). Similar to the concern noted above in relation to effects upon

neurotransmission, the increasing popularity of both potent forms of cannabis with

high Δ9-THC concentrations for smoking or inhalation (ElSohly et al., 2016; Loflin &

Earleywine, 2014), and of synthetic cannabinoids with stronger affinities for CB1

receptors than Δ-9THC (Centres for Disease Control and Prevention, 2013; Thomas

et al., 2014), raises the possibility of exacerbating the effects any neurotoxic

properties of this cannabinoid.

Reviews by Lorrenzetti et al. (2016) and Rocchetti et al. (2013) of brain imaging

studies which have compared cannabis users with nonusers both reported lower

levels of hippocampal grey matter volume in the cannabis users. Both reviews

excluded studies which had recruited participants with diagnoses of psychoses in

order to remove structural brain changes arising from these conditions as a potential

confound (Fusar-Poli, et al., 2012; Malchow et al., 2013). Rocchetti et al. conducted

meta-analyses on data from six primary studies concerning the hippocampus, and

found this difference between users and nonusers to statistically significant for the

hippocampus as a whole, and to be independent of publication biases. When the left

and right hippocampus were analysed independently the inter-group difference was

not significant. The role of the hippocampus is heavily implicated in human memory

performance (Fastenrath et al., 2014; Voogd et al., 2017) so that structural changes

to this area related to cannabis use have potential implications for memory

performance. Structural development within the hippocampus has been shown to

continue throughout adolescence (Benes et al., 1994), which raises the question of

the relationship between the onset age for cannabis use and the potential effects

which may occur upon hippocampal development. Unfortunately Rocchetti et al.

(2013) were unable to retrieve sufficient data from the primary studies to conduct a

meta-regression with onset age as a moderator for hippocampal volume. However,

Battistella et al. (2014) subsequently reported that an onset for cannabis use below

the age of 18 years amongst recreational users (defined as the mean consumption

of less than 1 joint per week in the 3 months prior to testing) was associated with

significantly lower grey matter volume in the left parahippocampal gyrus when

measured between the ages of 19 and 29 years, compared to an onset age of 18

years or older amongst recreational users. Regular cannabis use (defined as a

minimum of 10 joints consumed per month in the 3 months prior to testing) was

associated significantly lower grey matter volumes in this region compared to

recreational use with early and late onset participants combined. With regard to

duration of cannabis use, Rocchetti et al. (2013) reported no significant effect for this

variable as a moderator for hippocampal changes, but emphasised that this variable

may not have been adequately sensitive to actual cannabis consumption by

participants. Whilst insufficient data on actual consumption was available for use a

moderator in meta-regression, there was conflicting evidence from some of the

primary studies in their sample, with Ashtari et al. (2011) reporting a negative

correlation between right hippocampal volume and the estimated number of joints

smoked, whilst Tzilos et al. (2005) reported no relationship between hippocampal

volume and the number of episodes of cannabis consumption.

Functional connections between the hippocampus and the amygdala in the

modulation of memory and emotion are noted in the literature (de Voogd et al., 2017;

Fastenrath et al., 2014; Mandell et al., 2014). Rocchetti et al (2013) reported the

presence of conflicting results concerning volumetric differences in the amygdala in

their systematic review sample of 14 primary studies comparing cannabis users and

nonusers. Unfortunately, results from the meta-analysed sub-sample were not valid

after testing for publication biases. The review by Lorenzetti et al. (2016) reported

two studies finding reduced amygdala volume in cannabis users compared to

nonusers, and a third study which reported higher grey matter density and an altered

shape in the amygdala. With regard to the prefrontal cortex, evidence for changes in

cortical thickness being related to the onset age for cannabis included the findings of

Lopez-Larson et al. (2011), with a negative correlation between onset age and the

thickness of the right superior frontal lobe. Levels of cannabis consumption obtained

from urinalysis were negatively correlated with thickness in the region of the caudal

middle of the right frontal lobe, right lingual, and left superior frontal gyrus. Lorenzetti

et al. (2016) concluded that a relationship seemed to exist between brain regions

showing structural differences between the cannabis users and nonusers, and their

density of cannabinoid receptors, and that connectivity between these regions

potentially played a role in the development of structural changes related to cannabis

consumption.

(v) What is the relationship between cannabis consumption and changes in

human performance?

Overview. The effects of cannabinoid consumption discussed so far, with regard to

changes in neurotransmission and structural aspects of the brain, provide a basis for

exploring potential impacts upon human performance with regard to cognition and

behaviour. Reviews of primary studies which have compared the task performance

of groups of cannabis users to nonusing controls have previously been provided by

various teams of researchers (Broyd et al., 2016; Ranganathan & D’Souza, 2006;

Schweinsburg et al., 2008; Solowij and Battisti, 2008; Volkow et al., 2016). Rather

than duplicating the work of these reviews, this present review will aim to highlight

some of the areas of methodology and interpretation which recur in this area, and

some of the domains of cognitive functioning where cannabis related performance

impairments have consistently been reported.

Issues of methodology and interpretation. One distinction which needs to be borne in

mind with this literature is that between studies examining performance differences

attributable to the administration of a cannabinoid to participants with the specific

purpose of observing its effects upon performance, and studies where participants

are required to have been abstinent from the drug at the time of testing for a

specified period. These two types of study essentially address different questions.

For example, the demonstration of acute impairments in time perception (Sewell et

al., 2013) and on-the-road driving performance (Bosker et al., 2012), respectively,

related to researcher administered doses of Δ9-THC, constitute findings which

address the short term effects on specific areas of performance in response to the

administration of a cannabinoid. Although ethical considerations will limit the

dosages researchers may administer, there is an implication of addressing the effect

on performance of cannabinoid induced intoxication. This is a state described in the

Diagnostic and Statistical Manual (DSM-5) of the American Psychiatric Association

as possibly including impairments in motor control and judgement abilities, and mood

changes such as the onset of anxiety or euphoria (APA, 2013). By contrast, studies

which investigate the possibility of performance impairments in abstinent users

address a longer term issue regarding the relationships between cannabis

consumption, neurobiological functioning, and brain structure, and effects upon one

or more domain of functioning. There is an implication here of considering the

duration and reversibility (or otherwise) of any effects observed, beyond the short

term effects following consumption and, consequently, the findings have some

degree of relevance to everyone who has consumed cannabis at some time as

opposed to just current users. The distinction between the acute effects following

cannabinoid administration and long term effects in abstinence is highlighted by the

evidence for impairments in the ability to sustain attention, reviewed by Broyd et al.,

2016), which show impaired attention to have an acute onset following consumption,

and which may persist for several weeks, but which disappears as an effect with

sustained abstinence.

The recruitment of a relevant participant sample generally requires that some

minimal level of cannabis consumption has been achieved which may, for example

be defined as a minimum number of episodes of lifetime use, or within some other

specified time frame. However, recruiting participants who may be described as

current or recent cannabis users, for example in the past 6 or 12 months, may lead

to difficulty in attempting to operationalize a suitable ‘washout’ period for

cannabinoids due to the action of Δ9-THC on brain reward areas implicated in

addiction (French et al., 1997) and the experience of withdrawal symptoms in

potential participants (Budney & Hughes, 2006; Budney et al., 2004) making

abstinence difficult to maintain. Furthermore, where some of the recorded withdrawal

symptoms such as disturbances in sleep and mood occur, there is the danger of

introducing a confounding variable into a study which may influence performance

upon a task. With Δ9-THC having been detected in the urine of chronic users for up

to 23 days since last use (Lowe et al., 2009), it may be argued that testing with

anything less than a one month washout period carries the risk of task performance,

and also any neurobiological correlates of performance, being affected by a currently

present exogenous cannabinoid, rather than representing any long term legacy

effects on performance of cannabis use. In practice, the pragmatic response of

researchers is generally to apply and report a specific minimum washout period, for

example 24 hours, augmented by a reported mean abstinence period for the sample,

so that reported findings may be interpreted within this context.

The use of the word ‘relationship’ is very important in stating the question to be

examined regarding cannabis consumption and cognitive performance. Across the

range of scientific disciplines which study some aspect of human research

participants, it is the convention that cause and effect relationships are regarded as

only being established through experiments involving the random allocation of

participants to respective conditions, across which an independent variable is

systematically manipulated (Laake et al., 2007). Consequently, such an experiment

into the effects of cannabis consumption upon human cognitive performance would

require the random allocation of participants to a cannabis consumption group, and a

cannabis free control group. The legal, ethical, and practical (in terms of securing

agreement and compliance) barriers to conducting such an experiment with human

participants will be considered self-evident at this point. The inability to impose

conventional experimental controls on research has the consequence that the

potentially confounding influence upon cognitive performance of variables other than

cannabis use has to be considered in the design of studies, the analytic strategy

utilised with the data, and in the interpretation of results. The point here is that

variables need to be identified for which there are empirical and logical grounds to

assume that they may influence the measurable cognitive performance between a

group of cannabis users and nonusers if not balanced or controlled in some way.

Such potential confounds may include participants’ age (Beitz et al., 2014; Bowles &

Salthouse, 2008), measurable intelligence (van Aken, 2016), years of education (Wu

et al., 2015), and the use of other drugs with the potential to act upon cognitive

performance (Murphy et al., 2011; Valls-Serrano et al., 2016). Differences in

exposure to cannabis, such as age at onset of use, lifetime consumption, and period

since last used, also have the potential to influence the demonstrable relationship

between cannabis consumption and cognitive performance (Montgomery et al.,

2012; Schweinsburg et al, 2008; Solowij & Battisti, 2008; Thames et al., 2014).

In summary, the inability to conduct a true experiment regarding the effects of

cannabis consumption on cognitive performance in human participants means that

the evidence available is essentially correlational nature. A relationship between

cannabis consumption and cognitive performance may be demonstrated when a

significantly different level of performance is shown by a group of cannabis users

compared to nonusing controls, but the nature of this relationship with regard to the

causal role of cannabis consumption remains an open question. This may be seen to

raise the question of what importance and relevance should be placed upon the

findings of studies examining the relationship of cannabis consumption to cognitive

performance, and this question will be addressed at the end of the chapter.

Verbal learning and memory. Verbal learning and memory is a domain of cognitive

functioning where reviews highlight the prevalence of primary studies reporting

impaired functioning in cannabis users compared to controls, or the finding of a

correlation between estimates of cannabis consumption and task performance

(Broyd et al., 2016; Volkow et al., 2016). Sollowij et al. (2011) reported a sample of

adolescent cannabis users to show poorer performance than nonusing controls on

measures of word recall verbal learning, retention, and retrieval from the Rey

Auditory-Verbal Learning Test (RAVLT). There was evidence of poorer performance

by the cannabs users on 8 of the 11 performance measures analysed. Furthermore,

poorer performance amongst the users was related to longer durations of cannabis

use, higher quantities and frequency of use, and to earlier onset ages for cannabis

use. A minimum washout period of 12 hours was applied for all substance use, with

the median abstinence period from cannabis being reported as 20.3hours.

Importantly, urinary measures of cannabinoid metabolites and salivary measures of

Δ9-THC were both negatively correlated with performance for the total number of

words recalled and on a delayed recall task, but were not related to four other

performance measures. Becker et al. (2014) also employed a 12 hour minimum

washout period and reported impaired performance on three RAVLT measures of

the six analysed. However, no toxicological measures were utilised. In a study which

did not include control group comparisons, Bolla et al (2002) reported a negative

correlation between cannabis consumption and performance on the RAVLT delayed

recall measure following a mean cannabis abstinence period of 28 days, but not for

other RAVLT measures. Medina et al (2007) administered a battery of

neuropsychological tests to adolescent cannabis users with a minimum abstinence

period of 23 days monitored through urinalysis, although self-reports indicated a

minimum of 30 days of abstinence. Performance scores on individual scales were

composited to form eight functional domains, and the performance of users was

significantly worse than that of controls in the domain of verbal story memory utilising

measures from the Weschler Memory Scale (WMS-III), but not in the domain of

verbal list learning utilising measures from the California Verbal Learning Test

(CVLT). The users also performed worse than the controls in the domain of complex

attention which incorporated some CVLT measures alongside some nonverbal tasks.

Poorer performance in the verbal story memory and complex attention domains was

associated with higher estimates of lifetime cannabis use.

Working memory.

The psychological construct of working memory involves elements of short term

storage, combined with additional cognitive processing which may include elements

of executive control in the form of decision making (Baddeley, 2000; Shah & Miyake,

1999; Miyake et al., 2000). Latent variable analysis has demonstrated that

visuospatial memory draws upon executive working memory processes regardless of

the level of the level of additional processing required beyond the acquisition and

retention of visuospatial information (Miyake et al., 2001). Working memory covers

the range of stimulus domains (i.e. visual, auditory, etc.), so that with the range of

executive processes which may be performed on this variety of stimuli, a wide range

of tasks may be used to examine working memory functioning (Fisk & Sharp, 2004;

Miyake et al., 2000). Broyd et al. (2016) point out that the range of tasks used by

different researchers to investigate working memory functioning in cannabis users

which have been associated with contrasting results, is partly responsible for a lack

of clarity regarding whether or not cannabis use is associated with working memory

impairments, except for those studies utilising acute administration of Δ9-THC,

dronabinol, or nabilone where impairments were consistently reported.

The n-back task requires participants to indicate if the stimulus presented on one trial

is identical or not to the stimulus presented on the previous trial (i.e. 1-back) or two

trials previously (i.e. 2-back), and is a commonly used test of working memory.

Stimuli may be either verbal or nonverbal. Two neuroimaging studies have shown

that cannabis users and controls did not differ regarding performance or brain

activation patterns on this task with letters as stimuli, although there was some

evidence for an increase in activity in relevant brain regions being associated with

increased cannabis consumption, with task performance not showing any

impairment (Cousijn et al., 2013, 2014). Significantly poorer performance by

cannabis users compared to controls on a verbal 2-back test was reported by Herzig

et al. (2014), although the required minimum cannabis abstinence period was only 2

hours in this study. A mean abstinence period of in excess of 24 hours was in fact

reported, although four participants had used cannabis between 2 hours and 6 hours

prior to testing. Verdejo-Garcia et al. (2013) reported no performance impairments in

cannabis users on an n-back task incorporating 1-back, 2-back, and 3-back

procedures employing circles as target stimuli with spatial position as the

determinant of a ‘same/different’ response. The washout period in this study was 72

hours, with medication given for the control of any withdrawal symptoms. Using a

different test of spatial memory, Harvey et al. (2007) reported spatial working

memory deficits (as measured by the Cambridge Neuropsychological Test

Automated Battery: CANTAB) in regular adolescent cannabis users aged between

13 and 18 years, compared to occasional users in the same age range, with a

minimum requested abstinence period of 12 hours. The age range in this study was

markedly younger than that of 18 to 30 years used by Verdejo-Garcia et al. (2013),

but the difference in task employed makes it difficult to comment further on the

possible contribution of age to the different results reported for spatial memory.

Furthermore, neither of these studies explored the potentially confounding effects of

other lifetime drug use in detail. Cannabis use has been shown to have no

relationship to spatial memory performance on computer generated grid tasks in

studies of young adults (over 18 years of age) using both ecstasy (MDMA) and

cannabis (Montgomery & Fisk, 2008; Wareing et al., 2004). Both studies reported

spatial memory performance impairments to be related to ecstasy use.

There are few studies as yet which have examined the relationship of synthetic

cannabinoid use to cognitive performance. However, Cohen et al. (2017) report that

synthetic cannabinoid users performed worse on a 2-back task using digits as stimuli

for recognition, and upon the Stroop task, than either conventional phytocannabinoid

users, or nonusing controls. The Stroop task has been shown to yield measures of

executive inhibitory processes in working memory (Miyake et al., 2000). The potent

agonistic effects of these synthetic compounds for CB1 receptors make the further

investigation of their relationship to cognitive performance an important area for

future research in their context of their increasing use (Centres for Disease Control

and Prevention, 2013; Thomas et al., 2014).

Executive functioning

Terms such ‘executive functioning’ and ‘executive processes’ may sometimes refer

to an executive construct in working memory (Baddeley, 2000; Miyake et al., 2000),

or to a broader set of functions around planning, decision making and problem

solving (Lezak et al., 2012; Yuen & Raz, 2014). Broyd et al. (2016) report that acute

Δ9-THC administration produced mixed results on tests of such abilities, with the

differences in results possibly being related to such things as prior exposure to

cannabinoids, route of administration, dosage, and cannabinoid levels in blood

following dose administration.

The Iowa Gambling task (IGT: Bechara et al., 1994) has been used in a number of

studies to measure the quality of decision making in cannabis users. The task

simulates a gambling situation where participants are instructed to win as much

money as possible by making successive choices of cards from four decks, where

two decks offer relatively fast gains but higher risks of loss, and two decks which

offer smaller gains but relative security with regard to losses. Cannabis users have

been reported to show worse performance on this task than nonusing controls

(Fernández-Serano et al., 2010; Moreno et al., 2012) with reported abstinence

periods of 15 days and 3 days, respectively. In studies where cannabis users did not

perform worse than controls on this task, there was evidence that within the sample

of users, poorer performance was related to a significantly greater number of

cannabis dependence symptoms (Gonzalez et al., 2012) and a broader range of life

experience problems arising from cannabis use (Gonzalez et al., 2015).

Cannabis users abstinent for approximately 2 weeks were reported to perform worse

than nonusing controls in the domains of abstract reasoning, motor programming,

and cognitive flexibility measured by the Frontal Assessment Battery (FAB) of

neuropsychological tests (Cunha et al., 2010). However, no differences were

reported for environmental autonomy, sensitivity to interference, and inhibitory

control. The number of joints smoked in the 30 days before testing was negatively

correlated with inhibitory control performance but not any of the other domains. The

tests comprising this battery have been shown to correlate with aspects of frontal

lobe activity (Sarazin et al, 1998). Verdejo-Garcia et al (2005) measured cognitive

flexibility in a sample of detoxified cannabis users using a test requiring the

manipulation of geometric figures. Composite scores representing lifetime cannabis

use were inversely related to cognitive flexibility performance, but not to inhibitory

control measured by the Stroop task. Montgomery et al. (2012) tried to address

issues of ecological validity which can arise in the use of laboratory based tests by

using a non-immersive virtual reality task which simulated an office based daily work

routine. Whilst cannabis users (who had been asked to abstain for 5 days prior to

testing) performed worse than nonusing controls on a measure of planning

performance, there were no performance differences on measures of creative

thinking and adaptive thinking, respectively.

In summary, the relatively wide range of abilities which may come under the heading

of executive functioning, and the different ways in which these may be measured,

does make it difficult to make definitive conclusions about the relationship between

cannabis use and executive functioning. However, it is worth noting the observation

of Broyd et al. (2016) that impairments in executive functioning tended to be found in

studies using samples of older cannabis users rather than younger users. Whilst

older users may have experienced greater exposure to exogenous cannabinoids and

their effects, the additional and possibly interactive effects with age related declines

in cognitive ability (Salthouse & Babcock, 1991) need to be considered in the design

of studies and the interpretation of their results.

(vi) Dependence and addiction

The DSM-5 (APA, 2013) recognises five diagnostic categories associated with

cannabis use, these being, cannabis use disorder, cannabis intoxication, cannabis

withdrawal, other cannabis-induced disorders, and unspecified cannabis-related

disorder. The cannabis induced disorders are listed as psychotic disorders (onset

during intoxication may be noted for this category), anxiety disorders (onset during

intoxication may be noted for this category), delirium (onset during intoxication may

be noted for this category), and sleep disorders (either onset during intoxication or

onset during withdrawal may be noted for this category). Specialised reviews

relevant to psychosis have been conducted by Kraan et al.(2016), Schoeler et al.

(2016), and Volkow et al. (2016); for anxiety by Karila et al. (2014); and for sleep

disorders by Angarita et al. (2016) and Gates et al. (2016).

French et al. (1997) demonstrated that Δ9-THC administration activated

dopaminergic activity in the ventral tegmental area (VTA) and substantia nigra. Both

of these areas are implicated in brain reward pathways relevant to substance

addiction generally. In particular, the VTA has strong neural connections with the

nucleus accumbens which has been implicated in the reinforcement of substance

using behaviour generally, including the use of cannabis (Filbey et al., 2009; Nutt,

1996; Wenger et al., 2003), and in turn serving as an important neurobiological

foundation for the development of addictive drug use. Whilst cannabis consumption

may be incentivised by positive reinforcement mediated by these brain reward

pathways, the existence of withdrawal symptoms when regular consumption is

ceased provide a basis for the negative reinforcement of continued consumption in

order to avoid these symptoms, or where there has been a pause in consumption,

for its resumption in order to escape symptoms (Baker et al., 2004). The diagnostic

criteria for cannabis withdrawal in DSM-5 stipulate that three or more of the following

seven signs or symptoms (which in some cases may be more clearly understood as

symptom groups) are required to appear after the cessation of heavy and prolonged

use, for this diagnosis to be made: irritability, anger, or aggression; nervousness or

anxiety; sleep difficulty such as insomnia or disturbing dreams; decreased appetite

or weight loss; restlessness; depressed mood (APA, 2013). The seventh symptom

group lists significant discomfort from abdominal pain, shakiness and/or tremors,

sweating, fever, chills, or headache, with at least one of these being present for this

group to count as one of the three groups required for a diagnosis of cannabis

withdrawal to be made. The occurrence of significant distress or functional

impairment from the signs and symptoms listed is required for this diagnosis to be

made, and there should be no other medical condition present to which they may be

attributed more appropriately. These diagnostic criteria closely reflect the findings of

research on what is described by Budney et al. (2004) as the cannabis withdrawal

syndrome, with symptoms typically appearing within 2 days of the cessation of

cannabis use, with most symptoms lasting no longer than 2 weeks if cannabis use is

not resumed. However, the evidence reviewed by Budney et al. indicated that sleep

problems could persist for beyond 45 days of abstinence, and that irritability could

persist for between 28 and 45 days. The modulation of cannabis withdrawal

symptoms has been shown to involve CB1 receptors with this being demonstrated,

for example, in rodent studies using CB1 receptor antagonists or knockout

procedures (Ledent et al., 1999; Lichtman & Martin, 2002). The elevation of extra-

cellular levels of corticotropin releasing factor (CRF: de Fonseca et al., 1997) and a

decline in limbic system dopaminergic activity (Diana et al., 1997), similar to

withdrawal responses to other drugs, have also been reported.

The DSM-5 (APA, 2013) is the first version of the DSM series to include cannabis

withdrawal as a diagnosable condition, which is indicative of the acknowledgement

of a withdrawal syndrome being associated with cannabis as having only developed

gradually since the 1990s. The increase in potency of some black market supplies of

cannabis which have become available since the 1990s with regard to elevated Δ9-

THC levels (ElSohly et al., 2016; Hardwick & King, 2008; Loflin & Earleywine, 2014),

and the relatively high prevalence of cannabis use by comparison to other drugs

(Center for Behavioral Health Statistics and Quality, 2016; Lader, 2016) indicate that

problems of addictive cannabis use constitute an important health issue for society.

Furthermore, the growth in the use of synthetic cannabinoids with stronger affinities

for CB1 receptors than Δ9-THC (Centres for Disease Control and Prevention, 2013;

Thomas et al., 2014) may be exacerbating this problem. A detailed review of the

addictive nature of cannabinoids is provided by Gardner (2014).

(vii) Conclusions

It is clear that much of what is known about the effects of cannabis consumption has

been learned from animal studies, most notably using rodents, so that limitations

exist with regard to extent to which their findings can be taken to represent the

effects of human cannabis consumption. Additionally, ethical and methodological

limitations with human research generally preclude valid cause and effect

conclusions regarding cannabis consumption. However, the evidence which does

exist provides an empirical basis for concern regarding the effects of cannabis

consumption upon neurotransmission processes, brain anatomy, and neurocognitive

functioning, which may extend beyond the immediate period of consumption, despite

the best evidence available being subject to considerations around the potentially

confounding effects of other drug use, pre-existing differences between users and

nonusers on relevant variables such as IQ, and other influences. Whilst it may not be

possible to attain the highest level of scientific evidence regarding cause and effect

in human consumers, the potential impact of the cannabis related effects reviewed

above, alongside the prevalence of this drugs consumption, indicate that this is an

important area for ongoing research. Developments concerning the consumption of

potent forms of cannabis with high Δ9-THC concentrations, and also the increasing

consumption of synthetic cannabinoids from black market sources, add to the

relevance of such research for addressing important issues of health and well-being

in society.

The question of the appropriate legal status for cannabis inevitably stretches beyond

the scientific domain into issues of value judgements, and the balance between

personal liberties and responsible social restraints. Science can only inform such a

debate from the basis of its own domain of knowledge. However, where properly

manufactured and prescribed cannabinoid based medicines can contribute to

diminishing human suffering, in the context of appropriate clinical management, it is

important that the development and implementation of such interventions is not

impeded by being conflated with issues around the desirability of cannabis being

available for personal recreational use.

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