Resting-State Directional Connectivity and Anxiety and Depression Symptoms in Adult Cannabis Users

The role of sex in the association between cannabis use disorder and resting-state functional connectivity

While Cannabis use disorder (CUD) is twice as prevalent in males, females transition more quickly from heavy use to CUD and experience more severe withdrawal. These clinically relevant sex differences contrast the lack of knowledge about the underlying brain mechanisms. This study investigated the relationship between CUD and resting-state functional brain connectivity (RSFC), assessing potential sex differences herein. RSFC of the Salience Network (SN), Basal Ganglia Network (BGN), Executive Control Network (ECN), and Default Mode Network (DMN) was compared between 152 individuals (76 males) with CUD and 114 matched controls (47 males). Within the CUD group, relationships between RSFC and heaviness of cannabis use, age of onset, and CUD symptom severity, along with their associations with sex, were investigated. CUD and control groups showed similar RSFC across all networks, regardless of sex. In the CUD group, heavier cannabis use correlated with higher RSFC across all networks and earlier age of onset was related to higher RSFC in the anterior SN, BGN, left ECN, and dorsal DMN. These associations were similar for males and females. CUD severity was related to higher RSFC in the anterior SN, which was moderated by sex, with a positive association seen only in males. In conclusion, CUD may not necessarily be associated with altered RSFC. Individual use characteristics such age of onset and severity of use may determine the potential impact of cannabis use on RSFC in a largely similar way in males and females.

Effective connectivity of default mode network subsystems and automatic smoking behaviour among males

BACKGROUND

The default mode network (DMN) is not a single system, but rather is composed of smaller and distinct functional subsystems that interact with each other. The functional relevance of these subsystems in tobacco use disorder (TUD) and the neurobiological features associated with smoking motivation are still unclear; thus, we sought to assess causal or direct connectivity alterations within 3 subsystems of the DMN among people with TUD.

METHODS

We recruited male smokers and nonsmokers. We conducted resting-state functional magnetic resonance imaging (rs-fMRI) and collected ratings on smoking-related clinical scales. We applied dynamic causal modelling (DCM) to rs-fMRI to characterize changes of effective connectivity in TUD from 3 DMN subsystems, including the midline core network (i.e., the posterior cingulate cortex and the anterior medial prefrontal cortex [PCC-aMPFC] core DMN), the medial temporal subsystem (MTL-DMN), and the dorsal medial prefrontal cortex subsystem (dMPFC-DMN). We used leave-one-out cross-validation to investigate whether the neural response could predict smoking reasons, evaluated using the Russell Reason for Smoking Questionnaire).

RESULTS

We recruited 88 smokers and 54 nonsmokers. Among people with TUD, the parahippocampal cortex (PHC) region showed enhanced self-connection, which was associated with the severity of TUD after nighttime withdrawal. Compared with nonsmokers, people with TUD displayed significant increased effective connectivity within the dMPFC-DMN, and decreased effective connectivity from the dMPFC-DMN to the PCC-aMPFC core DMN. Moreover, decreased effective connectivity from the lateral temporal cortex to the dMPFC could predict the smoking reason related to automatic behaviour.

LIMITATIONS

Although we found aberrance in causal connections in DMN subsystems among people with TUD, our cross-sectional study could not be used to investigate changes in effective connectivity over time and their relationship with clinical features.

CONCLUSION

This study emphasized the aberrant causal connections of different functional subsystems of the DMN in TUD and revealed the neural correlates of automatic smoking behaviours. These findings suggested DMN subsystem-derived indicators could be a potential biomarker for TUD and could be used to identify the heterogeneity in motivation for smoking behaviour.

Abnormal resting-state effective connectivity in large-scale networks among obsessive-compulsive disorder

BACKGROUND

Obsessive-compulsive disorder (OCD) is a chronic mental illness characterized by abnormal functional connectivity among distributed brain regions. Previous studies have primarily focused on undirected functional connectivity and rarely reported from network perspective.

METHODS

To better understand between or within-network connectivities of OCD, effective connectivity (EC) of a large-scale network is assessed by spectral dynamic causal modeling with eight key regions of interests from default mode (DMN), salience (SN), frontoparietal (FPN) and cerebellum networks, based on large sample size including 100 OCD patients and 120 healthy controls (HCs). Parametric empirical Bayes (PEB) framework was used to identify the difference between the two groups. We further analyzed the relationship between connections and Yale-Brown Obsessive Compulsive Scale (Y-BOCS).

RESULTS

OCD and HCs shared some similarities of inter- and intra-network patterns in the resting state. Relative to HCs, patients showed increased ECs from left anterior insula (LAI) to medial prefrontal cortex, right anterior insula (RAI) to left dorsolateral prefrontal cortex (L-DLPFC), right dorsolateral prefrontal cortex (R-DLPFC) to cerebellum anterior lobe (CA), CA to posterior cingulate cortex (PCC) and to anterior cingulate cortex (ACC). Moreover, weaker from LAI to L-DLPFC, RAI to ACC, and the self-connection of R-DLPFC. Connections from ACC to CA and from L-DLPFC to PCC were positively correlated with compulsion and obsession scores (r = 0.209, p = 0.037; r = 0.199, p = 0.047, uncorrected).

CONCLUSIONS

Our study revealed dysregulation among DMN, SN, FPN, and cerebellum in OCD, emphasizing the role of these four networks in achieving top-down control for goal-directed behavior. There existed a top-down disruption among these networks, constituting the pathophysiological and clinical basis.

Executive control network resting state fMRI functional and effective connectivity and delay discounting in cocaine dependent subjects compared to healthy controls

Resting state functional magnetic resonance imaging (fMRI) has been used to study functional connectivity of brain networks in addictions. However, most studies to-date have focused on the default mode network (DMN) with fewer studies assessing the executive control network (ECN) and salience network (SN), despite well-documented cognitive executive behavioral deficits in addictions. The present study assessed the functional and effective connectivity of the ECN, DMN, and SN in cocaine dependent subjects (CD) (n = 22) compared to healthy control subjects (HC) (n = 22) matched on age and education. This study also investigated the relationship between impulsivity measured by delay discounting and functional and effective connectivity of the ECN, DMN, and SN. The Left ECN (LECN), Right ECN (RECN), DMN, and SN functional networks were identified using FSL MELODIC independent component analysis. Functional connectivity differences between CD and HC were assessed using FSL Dual Regression analysis and FSLNets. Effective connectivity differences between CD and HC were measured using the Parametric Empirical Bayes module of Dynamic Causal Modeling. The relationship between delay discounting and functional and effective connectivity were examined using regression analyses. Dynamic causal modeling (DCM) analysis showed strong evidence (posterior probability > 0.95) for CD to have greater effective connectivity than HC in the RECN to LECN pathway when tobacco use was included as a factor in the model. DCM analysis showed strong evidence for a positive association between delay discounting and effective connectivity for the RECN to LECN pathway and for the DMN to DMN self-connection. There was strong evidence for a negative association between delay discounting and effective connectivity for the DMN to RECN pathway and for the SN to DMN pathway. Results also showed strong evidence for a negative association between delay discounting and effective connectivity for the RECN to SN pathway in CD but a positive association in HC. These novel findings provide preliminary support that RECN effective connectivity may differ between CD and HC after controlling for tobacco use. RECN effective connectivity may also relate to tobacco use and impulsivity as measured by delay discounting.

Associations between cannabis use, cannabis use disorder, and mood disorders: longitudinal, genetic, and neurocognitive evidence

RATIONALE

Cannabis use among people with mood disorders increased in recent years. While comorbidity between cannabis use, cannabis use disorder (CUD), and mood disorders is high, the underlying mechanisms remain unclear.

OBJECTIVES

We aimed to evaluate (1) the epidemiological evidence for an association between cannabis use, CUD, and mood disorders; (2) prospective longitudinal, genetic, and neurocognitive evidence of underlying mechanisms; and (3) prognosis and treatment options for individuals with CUD and mood disorders.

METHODS

Narrative review of existing literature is identified through PubMed searches, reviews, and meta-analyses. Evidence was reviewed separately for depression, bipolar disorder, and suicide.

RESULTS

Current evidence is limited and mixed but suggestive of a bidirectional relationship between cannabis use, CUD, and the onset of depression. The evidence more consistently points to cannabis use preceding onset of bipolar disorder. Shared neurocognitive mechanisms and underlying genetic and environmental risk factors appear to explain part of the association. However, cannabis use itself may also influence the development of mood disorders, while others may initiate cannabis use to self-medicate symptoms. Comorbid cannabis use and CUD are associated with worse prognosis for depression and bipolar disorder including increased suicidal behaviors. Evidence for targeted treatments is limited.

CONCLUSIONS

The current evidence base is limited by the lack of well-controlled prospective longitudinal studies and clinical studies including comorbid individuals. Future studies in humans examining the causal pathways and potential mechanisms of the association between cannabis use, CUD, and mood disorder comorbidity are crucial for optimizing harm reduction and treatment strategies.

Sleep-Dependent Anomalous Cortical Information Interaction in Patients With Depression

Depression is a prevalent mental illness with high morbidity and is considered the main cause of disability worldwide. Brain activity while sleeping is reported to be affected by such mental illness. To explore the change of cortical information flow during sleep in depressed patients, a delay symbolic phase transfer entropy of scalp electroencephalography signals was used to measure effective connectivity between cortical regions in various frequency bands and sleep stages. The patient group and the control group shared similar patterns of information flow between channels during sleep. Obvious information flows to the left hemisphere and to the anterior cortex were found. Moreover, the occiput tended to be the information driver, whereas the frontal regions played the role of the receiver, and the right hemispheric regions showed a stronger information drive than the left ones. Compared with healthy controls, such directional tendencies in information flow and the definiteness of role division in cortical regions were both weakened in patients in most frequency bands and sleep stages, but the beta band during the N1 stage was an exception. The computable sleep-dependent cortical interaction may provide clues to characterize cortical abnormalities in depressed patients and should be helpful for the diagnosis of depression.

Altered effective connectivity of the reward network during an incentive-processing task in adults with alcohol use disorder

BACKGROUND

Abnormalities of reward sensitivity and impulsivity are known to be correlated with each other and alcohol use disorder (AUD) risk, but the underlying aberrant neural circuitry involved is not clearly defined. We sought to extend the current knowledge of AUD pathophysiology by studying incentive processing in persons with AUD using functional neuroimaging data.

METHODS

We utilized functional MRI data from the Human Connectome Project Database obtained during performance of a number-guessing incentive-processing task with win, loss, and neutral feedback conditions in 78 participants with either DSM-IV alcohol abuse or dependence (combined as the AUD group) and 78 age- and sex-matched control (CON) participants. Within a network consisting of anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), insula, ventral striatum, and dorsal striatum (DS) in the right hemisphere, we performed dynamic causal modeling analysis to test group-level differences (AUD vs. CON) in effective directional connectivity (EC) as modulated by "win" and "loss" conditions. We used linear regression analyses to characterize the relations between each EC outcome and measures of cumulative alcohol exposure and impulsivity.

RESULTS

During wins, AUD participants had lower ECs from ACC to the other four nodes, greater ECs from insula to the other four nodes, greater ECs from DLPFC to the other four nodes, and greater DS to DS self-connection EC than CON participants. In the total sample, EC from the insula to the DLPFC (insula → DLPFC) during wins was positively correlated with both impulsivity (as measured by the delay-discounting task) and cumulative alcohol exposure. The DS to DS self-connection EC during wins was positively correlated with impulsivity. Many of the altered ECs from the ACC and insula to other nodes were correlated with cumulative alcohol exposure.

CONCLUSIONS

Individuals with AUD have disrupted EC in both instrumentally driven and automatized corticostriatal reward circuits during non-alcohol reward feedback. These results point to disrupted corticostriatal EC in both "top-down" and "bottom-up" pathways among individuals with AUD.

Cannabis and synaptic reprogramming of the developing brain

Recent years have been transformational in regard to the perception of the health risks and benefits of cannabis with increased acceptance of use. This has unintended neurodevelopmental implications given the increased use of cannabis and the potent levels of Δ⁹-tetrahydrocannabinol today being consumed by pregnant women, young mothers and teens. In this Review, we provide an overview of the neurobiological effects of cannabinoid exposure during prenatal/perinatal and adolescent periods, in which the endogenous cannabinoid system plays a fundamental role in neurodevelopmental processes. We highlight impaired synaptic plasticity as characteristic of developmental exposure and the important contribution of epigenetic reprogramming that maintains the long-term impact into adulthood and across generations. Such epigenetic influence by its very nature being highly responsive to the environment also provides the potential to diminish neural perturbations associated with developmental cannabis exposure.

Distinct Activity of Endocannabinoid-Hydrolyzing Enzymes MAGL and FAAH in Key Regions of Peripheral and Central Nervous System Implicated in Migraine

In migraine pain, cannabis has a promising analgesic action, which, however, is associated with side psychotropic effects. To overcome these adverse effects of exogenous cannabinoids, we propose migraine pain relief via activation of the endogenous cannabinoid system (ECS) by inhibiting enzymes degrading endocannabinoids. To provide a functional platform for such purpose in the peripheral and central parts of the rat nociceptive system relevant to migraine, we measured by activity-based protein profiling (ABPP) the activity of the main endocannabinoid-hydrolases, monoacylglycerol lipase (MAGL) and fatty acid amide hydrolase (FAAH). We found that in trigeminal ganglia, the MAGL activity was nine-fold higher than that of FAAH. MAGL activity exceeded FAAH activity also in DRG, spinal cord and brainstem. However, activities of MAGL and FAAH were comparably high in the cerebellum and cerebral cortex implicated in migraine aura. MAGL and FAAH activities were identified and blocked by the selective and potent inhibitors JJKK-048/KML29 and JZP327A, respectively. The high MAGL activity in trigeminal ganglia implicated in the generation of nociceptive signals suggests this part of ECS as a priority target for blocking peripheral mechanisms of migraine pain. In the CNS, both MAGL and FAAH represent potential targets for attenuation of migraine-related enhanced cortical excitability and pain transmission.