The Association Between Cannabis Use and Cognitive Function

What's the science?

Recent policies in North America have shifted towards increased acceptance of cannabis use, and perceived harm has decreased. Chronic cannabis use could have effects on cognitive function in developing adolescents, however, this risk is not well understood. This week in JAMA Psychiatry, Scott and colleagues perform a meta-analysis of studies on cannabis use to determine whether there is an association between cannabis use and cognitive function in youth and young adults. 

How did they do it?

They performed a systematic review of the literature. They included all cross-sectional studies where participants were adolescents or young adults, frequent or heavy cannabis use was assessed as a variable of interest (not just acute cannabis use) and cognitive performance on at least one neuropsychological test was measured. They also ensured that each of these studies had sufficient power to calculate effect sizes. 69 studies met their criteria (2152 cannabis users and 6575 control participants with minimal cannabis use). They performed the statistical analysis using a mixed effects multivariate model, which accounts for correlated within-study effects and multiple different effect sizes between studies. Cognitive performance on neuropsychological tests was the measure of interest.

What did they find?

The overall effect size in a model without explanatory variables (i.e. variables that could potentially affect the association between cannabis and cognitive function such as age) was small but significant, showing a lower cognitive performance in cannabis users compared to the comparison group. Cognitive performance in heavy cannabis users was lower in the domains of learning, executive function, information processing speed, delayed memory, inhibition, working memory and attention. When explanatory variables were included, the effects were not explained by age category, age at first cannabis use or alcohol use. Hours of abstinence from cannabis (self-reported) was associated with a lower effect size, suggesting that a longer period of abstinence from cannabis reduced the negative effects on cognitive performance. When looking at studies where a period of greater than 72 hours of abstinence prior to study participation was required, effect size was no longer significant.

What's the impact?

This is the first meta-analysis of the effects of heavy cannabis use specifically in youth and young adults. This study confirms findings from studies in adults, suggesting that in youth, the effects of cannabis use on cognition are small and abstaining from cannabis for at least 3 days, may reduce negative effects on cognitive performance.

A Word of Caution: Studies which take into account the type and amount of cannabis used will be needed to better understand the effects on cognitive performance. Additionally, studies looking at functional outcomes like employment or other health measures (not just cognitive performance) with cannabis use over time may provide more meaningful information. Furthermore, even a small effect on cognitive performance may impact youth differently depending on their genetic makeup or life circumstances.

C. Scott et al., Association of Cannabis with Cognitive Functioning in Adolescents and Young Adults: A Systematic Review and Meta-Analysis. JAMA Psychiatry (2018). Access the original scientific publication here.

Brain Activity Predicts How Much Individuals Like Each Other

What's the science?

Within a group, people tend to like each other over time as they get to know one another. When considering interpersonal factors, if Person A likes Person B, this can lead Person B to like Person A over time (reciprocal liking). Interpersonal reward might affect this process; if a person experiences something rewarding during a social encounter, this can further influence reciprocal liking (a positive feedback loop). Two brain regions, the ventromedial prefrontal cortex and the ventral striatum are known to be involved in processing reward. In some cases, activity in these brain regions can predict an individual’s preferences, and therefore may also be able to predict how much an individual will like someone else. This week in PNAS, Zerubavel and colleagues tested whether interpersonal liking and brain activity in reward-related regions could predict how much people liked each other after a period of time.

How did they do it?

Sixteen healthy young adults, most of whom did not previously know each other, were recruited for the study while volunteering for a summer program that took place over nine weeks. At two timepoints, once at the beginning of the summer program and again 9 weeks later, participants rated how much they liked each other ‘not very’ to ‘very’, 0-100 scale, and also viewed pictures of each other's faces while undergoing functional magnetic resonance imaging (fMRI) scans. The authors employed structural equation modelling (which can account for multiple interrelated variables) to assess liking cross all possible pairs of participants. Each participant was in turn referred to as the ‘actor’ and other participants were referred to as ‘partners.’ The authors assessed: a) the effects of both the actor and the partner’s liking of each other at timepoint 1 on the actor’s liking of the partner at timepoint 2 and b) the effects of both the actor’s and the partner’s neural responses in the ventromedial prefrontal cortex and ventral striatum at timepoint 1 on how much the actor liked the partner at timepoint 2 (i.e. whether either person’s brain activity at timepoint 1 predicted how much the actor liked the partner, controlling for how much they reported liking each other).

What did they find?

The authors found that how much the actor liked the partner, and how much the partner liked the actor at time point 1 predicted how much the actor liked the partner at timepoint 2. Next, after accounting for how much the partner and actor liked each other at timepoint 1 (and other known predictors of future liking) the authors found that neural responses in the ventromedial prefrontal cortex and ventral striatum in both the actor and the partner (brain activity in response to viewing each other's face) at timepoint 1 predicted how much the actor liked the partner at timepoint 2. This indicates that neural processes leading to future liking could be occurring subconsciously.

What's the impact?

This is the first study to demonstrate that fMRI responses (measuring brain activity) in reward-related regions of the brain can predict how much one individual will like another individual months in the future. Specifically, neural responses in both people can affect how much one person likes the other person at a later timepoint. The study furthers our understanding of the neural basis for interpersonal relationships.

N. Zerubavel et al., Neural precursors of future liking and affective reciprocity. PNAS (2018). Access the original scientific publication here.

Mild Traumatic Brain Injury Increases Risk of Parkinson’s Disease

What's the science?

Mild traumatic brain injury, also referred to as a concussion, is defined as a loss of consciousness or confusion due to head injury that lasts less than 30 minutes. Mild traumatic brain injury is especially common among the elderly, athletes and in the military, and is increasingly associated with risk for psychiatric and neurodegenerative diseases. The relationship between mild traumatic brain injury and risk for Parkinson’s disease is not well understood. This week in Neurology, Gardner and colleagues assess the risk of Parkinson’s disease after mild traumatic brain injury in a large sample of patients.

How did they do it?

Participants (18 years or older) from the Veterans Health Association (military veterans) with a diagnosis of traumatic brain injury were included and were age matched to a random sample of participants without brain injury (325,870 total participants). They diagnosed Traumatic brain injury using detailed clinical assessments or criteria from the Department of Defense (IC-9 codes). They also assessed other diseases at baseline and Parkinson’s disease at least one year after baseline in this longitudinal study. They then used a Cox Proportional Hazards model (a standard statistical model for assessing longitudinal risk) to determine risk of developing Parkinson’s disease with and without traumatic brain injury, including assessment of risk specifically after mild traumatic brain injury. They controlled for confounding variables including medical conditions, psychiatric disease and demographics: age, sex, ethnicity, education and level of income.

What did they find?

A total of 1462 participants developed Parkinson’s disease over the course of the study (average 4.6 years follow-up), 65% of whom had previously experienced traumatic brain injury. Participants with previous traumatic brain injury were significantly more likely to develop Parkinson’s disease than those without traumatic brain injury (hazards ratio: 1.71). Even mild traumatic brain injury was associated with increased risk (56%) of developing Parkinson’s disease after adjusting for all confounding variables.

What's the impact?

This is the first large-scale, nationwide study to demonstrate that mild traumatic brain injury is associated with an increased risk of Parkinson’s disease. We now know that focusing on the prevention of mild traumatic brain injury will be important for reducing risk of Parkinson’s disease.

R. Gardner et al., Mild TBI and risk of Parkinson disease: A Chronic Effects of Neurotrauma Consortium Study. Neurology (2018). Access the original scientific publication here.