Different neurocognitive controls modulate obstacle avoidance through pregnancy.

Understanding why falls during pregnancy occur at over 25% rate over gestation has clinical impacts on the health of pregnant individuals. Attention, proprioception, and perception of the environment are required to prevent trips and falls. This research aimed to understand how the changes to these neurocognitive processes control obstacle avoidance through gestation. Seventeen pregnant participants were tested five times in 6-week intervals. Participants walked an obstacle course (OC), and we analyzed the crossings over obstacles that were set to 10% of participants' body height. Participants also performed an attentional network test (ANT: performance of specific components of attention), an obstacle perception task (OP: ability to visually define an obstacle and translate that to a body posture), and a joint position sense task (JPS: ability to recognize and recreate a joint position from somatosensation). In the OC task, average leading and trailing foot crossing heights significantly reduced by 13% and 23% respectively, with no change in variation, between weeks 13 and 31 of pregnancy, indicating an increased risk of obstacle contact during this time. The variability in minimum leading foot distances from the obstacle was correlated with all three neurocognition tasks (ANT, OP, and JPS). Increased fall rates in the second and third trimesters of pregnancy may be driven by changes in attention, with additional contributions of joint position sense and environmental perception at various stages of gestation. The results imply that a holistic examination on an individual basis may be required to determine individual trip risk and appropriate safety modifications.

Sex-related differences in subjective, but not neural, cue-elicited craving response in heavy cannabis users.

BACKGROUND: Studies indicate that female cannabis users progress through the milestones of cannabis use disorder (CUD) more quickly than male users, likely due to greater subjective craving response in women relative to men. While studies have reported sex-related differences in subjective craving, differences in neural response and the relative contributions of neural and behavioral response remain unclear. METHODS: We examined sex-related differences in neural and behavioral response to cannabis cues and cannabis use measures in 112 heavy cannabis users (54 females). We used principal component analysis to determine the relative contributions of neural and behavioral response and cannabis use measures. RESULTS: We found that principal component (PC) 1, which accounts for the most variance in the dataset, was correlated with neural response to cannabis cues with no differences between male and female users (p = 0.21). PC2, which accounts for the second-most variance, was correlated with subjective craving such that female users exhibited greater subjective craving relative to male users (p = 0.003). We also found that CUD symptoms correlated with both PC1 and PC2, corroborating the relationship between craving and CUD severity. CONCLUSIONS: These results indicate that neural activity primarily underlies response to cannabis cues and that a complex relationship characterizes a convergent neural response and a divergent subjective craving response that differs between the sexes. Accounting for these differences will increase efficacy of treatments through personalized approaches.

Recent tobacco use has widespread associations with adolescent white matter microstructure.

IMPORTANCE: Given the prevalence of alcohol, cannabis, and tobacco use during adolescence, it is important to explore the relative relationship of these three substances with brain structure. OBJECTIVE: To determine associations between recent alcohol, cannabis, and tobacco use and white and gray matter in a large sample of adolescents. DESIGN, SETTING, AND PARTICIPANTS: MRI data were collected in N = 200 adolescents ages 14-18 (M = 15.82 years; 67% male; 61% Hispanic/Latino). On average, during the past month, participants reported consuming 2.05 drinks per 1.01 drinking day, 0.64 g per 6.98 cannabis use days, and 2.49 cigarettes per 12.32 smoking days. MAIN OUTCOMES AND MEASURES: General linear models were utilized to examine past 30-day average quantities of alcohol, cannabis, and tobacco use, age, sex, and sex by substance interactions in skeletonized white matter (fractional anisotropy and axial, radial, and mean diffusivity) and voxel-based morphometry of gray matter (volume/density). RESULTS: Tobacco use was negatively associated with white matter integrity (radial and mean diffusivity) with peak effects in inferior and superior longitudinal fasciculi. Cannabis use was negatively associated with white matter integrity (axial diffusivity) in a small cluster in the left superior longitudinal fasciculus. No associations were observed between recent alcohol use and white or gray matter overall, but interactions showed significant negative associations between alcohol use and white matter in females. CONCLUSIONS AND RELEVANCE: It is important to note that recent tobacco use, particularly given the popularity of e-tobacco/vaping in this age group, had widespread associations with brain structure in this sample of adolescents.

Testing the role of the posterior cingulate cortex in processing salient stimuli in cannabis users: an rTMS study.

The posterior cingulate cortex (PCC) and precuneus are hubs in the default mode network and play a role in processing external salient stimuli. Accordingly, activation in these regions has been associated with response to salient stimuli using drug cue-reactivity paradigms in substance using populations. These studies suggest that the PCC and precuneus may underlie deficits in processing salient stimuli that contribute toward the development of substance use disorders. The goal of this study was to directly test this hypothesis using repetitive transcranial magnetic stimulation (rTMS). Using a double-blind, placebo-controlled design, we used rTMS to target the PCC and precuneus with a double-cone coil at 10 Hz (high frequency) and 1 Hz (low frequency) in 10 adult cannabis users and 10 age- and sex-matched non-using controls. Electroencephalography data were collected before and after rTMS during a modified oddball paradigm with neutral, oddball, self-relevant, and cannabis-related stimuli. Cannabis users exhibited increased amplitude in P3 and faster latencies in the P3, N2, and P2 components in response to self-relevant stimuli compared to controls during baseline that normalized after rTMS. These results suggest that cannabis users exhibited heightened salience to external self-relevant stimuli that were modulated after rTMS. PCC dysfunction in cannabis users may be related to abnormalities in processing salient stimuli, such those during cue-reactivity, and provides a potential target for cannabis use disorder intervention.

Differential associations of combined vs. isolated cannabis and nicotine on brain resting state networks.

Concomitant cannabis and nicotine use is more prevalent than cannabis use alone; however, to date, most of the literature has focused on associations of isolated cannabis and nicotine use limiting the generalizability of existing research. To determine differential associations of concomitant use of cannabis and nicotine, isolated cannabis use and isolated nicotine use on brain network connectivity, we examined systems-level neural functioning via independent components analysis (ICA) on resting state networks (RSNs) in cannabis users (CAN, n = 53), nicotine users (NIC, n = 28), concomitant nicotine and cannabis users (NIC + CAN, n = 26), and non-users (CTRL, n = 30). Our results indicated that the CTRL group and NIC + CAN users had the greatest functional connectivity relative to CAN users and NIC users in 12 RSNs: anterior default mode network (DMN), posterior DMN, left frontal parietal network, lingual gyrus, salience network, right frontal parietal network, higher visual network, insular cortex, cuneus/precuneus, posterior cingulate gyrus/middle temporal gyrus, dorsal attention network, and basal ganglia network. Post hoc tests showed no significant differences between (1) CTRL and NIC + CAN and (2) NIC and CAN users. These findings of differential associations of isolated vs. combined nicotine and cannabis use demonstrate an interaction between cannabis and nicotine use on RSNs. These unique and combined mechanisms through which cannabis and nicotine influence cortical network functional connectivity are important to consider when evaluating the neurobiological pathways associated with cannabis and nicotine use.

Cannabis users exhibit increased cortical activation during resting state compared to non-users.

Studies have shown altered task-based brain functioning as a result of cannabis use. To date, however, whether similar alterations in baseline resting state and functional organization of neural activity are observable in cannabis users remains unknown. We characterized global resting state cortical activations and functional connectivity via electroencephalography (EEG) in cannabis users and related these activations to measures of cannabis use. Resting state EEG in the eyes closed condition was collected from age- and sex-matched cannabis users (N = 17; 6 females; mean age = 30.9 ±â€¯7.4 years) and non-using controls (N = 21; 9 females; mean age = 33.1 ±â€¯11.6 years). Power spectral density and spectral coherence were computed to determine differences in cortical activations and connectivity between the two groups in the delta (1-4Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (13-30 Hz), and gamma (31-50 Hz) frequency bands. Cannabis users exhibited decreased delta and increased theta, beta, and gamma power compared to controls, suggesting increased cortical activation in resting state and a disinhibition of inhibitory functions that may interrupt cognitive processes. Cannabis users also exhibited increased interhemispheric and intrahemispheric coherence relative to controls, reduced mean network degree, and increased clustering coefficient in specific regions and frequencies. This increased cortical activity may indicate a loss of neural refinement and efficiency that may indicate a "noisy" brain. Lastly, measures related to cannabis use were correlated with spectral power and functional connectivity measures, indicating that specific electrophysiological signals are associated with cannabis use. These results suggest that there are differences in cortical activity and connectivity between cannabis users and non-using controls in the resting state that may be related to putative cognitive impairments and can inform effectiveness of intervention programs.

Cross-Cultural Effects of Cannabis Use Disorder: Evidence to Support a Cultural Neuroscience Approach.

PURPOSE OF REVIEW: Cannabis use disorders (CUDs) are prevalent worldwide. Current epidemiological studies underscore differences in behaviors that contribute to cannabis use across cultures that can be leveraged towards prevention and treatment of CUDs. This review proposes a framework for understanding the effects of cross-cultural differences on psychological, neural, and genomic processes underlying CUDs that has the potential to inform global policies and impact global public health. RECENT FINDINGS: We found that cultural factors may influence (1) the willingness to acknowledge CUD-related symptoms among populations of different countries, and (2) neural responses related to the sense of self, perception, emotion, and attention. These findings leverage the potential effects of culture on neural mechanisms underlying CUDs. SUMMARY: As the number of individuals seeking treatment for CUDs increases globally, it is imperative to incorporate cultural considerations to better understand and serve differing populations and develop more targeted treatment strategies and interventions.

Cognitive motor deficits in cannabis users.

Cannabis use affects cortico-striatal networks that are essential for producing movement. In this review, we summarize the literature on motor system dysfunction in cannabis users and provide a rationale for why motor learning should be considered an important area in cannabis research. A majority of studies have addressed cognitive impairments in cannabis users and some have focused on driving performance, motor impulsivity, and motor inhibition. Our review of the literature has found that cannabis use is associated with motor performance impairments; however, there is a gap in the literature regarding impairments in motor learning. The involvement of the cortico-striatal network in both cannabis addiction and movement also suggests potential avenues for treatment and rehabilitation via the motor system.

Probabilistic Motor Sequence Yields Greater Offline and Less Online Learning than Fixed Sequence.

It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the fast learning stage, we asked four groups of young adults to perform the serial reaction time (SRT) task with either a fixed or probabilistic sequence and with or without preliminary knowledge (PK) of the presence of a sequence. The sequence and PK were manipulated to emphasize either procedural (probabilistic sequence; no preliminary knowledge (NPK)) or declarative (fixed sequence; with PK) memory that were found to either facilitate or inhibit offline learning. In the SRT task, there were six learning blocks with a 2 min break between each consecutive block. Throughout the session, stimuli followed the same fixed or probabilistic pattern except in Block 5, in which stimuli appeared in a random order. We found that PK facilitated the learning of a fixed sequence, but not a probabilistic sequence. In addition to overall learning measured by the mean reaction time (RT), we examined the progressive changes in RT within and between blocks (i.e., online and offline learning, respectively). It was found that the two groups who performed the fixed sequence, regardless of PK, showed greater online learning than the other two groups who performed the probabilistic sequence. The groups who performed the probabilistic sequence, regardless of PK, did not display online learning, as indicated by a decline in performance within the learning blocks. However, they did demonstrate remarkably greater offline improvement in RT, which suggests that they are learning the probabilistic sequence offline. These results suggest that in the SRT task, the fast acquisition of a motor sequence is driven by concurrent online and offline learning. In addition, as the acquisition of a probabilistic sequence requires greater procedural memory compared to the acquisition of a fixed sequence, our results suggest that offline learning is more likely to take place in a procedural sequence learning task.