Worldwide, cannabis is one of the most widely used psychoactive substances and cannabis use has been implicated in poorer performance in several cognitive domains, including working memory (WM). However, the neural mechanisms underlying these WM decrements are not well understood and the current study investigated the association of cannabis involvement with WM performance and associated neural activation in the Human Connectome Project (N = 1038). Multiple indicators of cannabis involvement were examined in relation to behavioral performance and brain activity in a visual N-back task using functional magnetic resonance imaging. A positive urine drug screen for tetrahydocannabinol (THC+ status), the principal psychoactive constituent in cannabis, was associated with worse WM performance and differential brain response in areas previously linked to WM performance. Furthermore, decreases in blood-activation-level-dependent (BOLD) signal in WM task-positive brain regions and increases in task-negative regions mediated the relationship between THC+ status and WM performance. In contrast, WM performance and BOLD response during the N-back task were not associated with total lifetime cannabis use, age of first use, or other indicators of involvement, suggesting that the effects of cannabis on WM were short-term residual effects, rather than longterm persistent effects. These findings elucidate differential influences of cannabis involvement on neurocognition and have significant potential implications for occupational performance in diverse settings.Neuropsychopharmacology (2019) 44:613-619; https://doi.
The Booklet Category Test (BCT) is a neuropsychological test of cognitive dysfunction that provides only one overall error score indicative of global impairment. It does not, however, delineate specific domains that might be impaired. The aim of this study is to concurrently validate 13 new BCT subscales using legacy instruments in patients with nonpenetrating traumatic brain injury (TBI). Eighty-nine patients with mild, moderate, and severe TBI completed a battery of neuropsychology tests. Partial correlations controlling for age were performed and there were significant correlations between the a priori selected scores from legacy measures of major cognitive domains and both BCT total errors and subscale scores. Additional analysis showed that several subscales were able to differentiate between performance levels on the legacy measures. Overall, our results showed that the subscales measured cognitive skills beyond global impairment, supporting the use of the BCT subscales in a population with TBI.
Objective Cognitive reserve (CR) refers to the brain’s capacity to cope with pathology and preserve functioning. We investigated cognitive performance between individuals with alcohol use disorder (AUD) and healthy controls to examine whether CR, operationalized as education and psychosocial functioning, influences neuropsychological functioning. Method We recruited 45 AUD (DSM-V criteria) who reported drinking levels exceeding NIAAA guidelines (>14/7 drinks/week for men/women) and 30 healthy controls who did not. MANCOVAs controlling for CR were used to investigate between-group differences in neuropsychological performance, as measured by the NIH Toolbox. A series of linear regression analyses were also performed to evaluate effects of AUD and CR on neuropsychological performance. Psychosocial functioning, education, and AUD status were simultaneously entered as predictors of Flanker, Dimensional Change Card Sort, Picture Sequence, List Sort, and Processing Speed scores. Results MANCOVAs revealed a significantly slower processing speed in the AUD group compared to controls when controlling for CR (F = 4.30, p = .042). There were no significant group differences on other tests. Linear regressions showed only processing speed to be predicted by AUD (β = −.255, p = .042), while CR measures were not. Education predicted Picture Sequence (β = .245, p = .041) and Card Sort (β = .291, p = .009) performance, and psychosocial functioning predicted Flanker (β = .296, p = .021) and Card Sort (β = .316, p = .010) performance. Conclusions CR appears to contribute to higher-order cognitive functions, regardless of AUD status. Only processing speed, a domain typically susceptible to brain pathology, was significantly related to AUD. Thus, factors linked to CR may serve as important targets for future research and intervention in AUD to promote favorable cognitive outcomes.
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