This article extends research in other states by investigating the landscape of licensed and unlicensed cannabis retailers in California as of October 2018, providing a descriptive snapshot of California’s cannabis retail landscape at one point in time. We hypothesized that neighborhoods with cannabis retailers—particularly unlicensed retailers—would show more socioeconomic disadvantage  than communities without cannabis retailers. We also tested the hypotheses that unlicensed facilities would be more likely than licensed facilities to be in unincorporated areas .We also analyzed the locations of licensed and unlicensed facilities relative to whether medicinal, adult-use, or both types of cannabis retail businesses are allowed or not allowed in all unincorporated and incorporated jurisdictions throughout California. We obtained data on local cannabis ordinances as of October 2018 from local news stories and the websites of local jurisdictions. We took state data on population by jurisdiction  and calculated the proportion of the state population living in incorporated areas versus unincorporated areas and the proportion living in localities that allow  versus localities do not allow adult-use retail .We estimated the expected values of facility locations by apportioning the total number of licensed or unlicensed facilities according to the population, and then used chi-square statistics to test whether facility locations varied significantly from the expected values.Licensed retailers can benefit public health by ensuring that cannabis products are uncontaminated, accurately labeled, and sold only to adults . Our findings show that neighborhoods with only licensed retailers contain a disproportionately high proportion of non-Hispanic whites, compared to neighborhoods with unlicensed retailers or a mix of licensed and unlicensed retailers.

Unlicensed dispensaries are problematic because they have been reported to engage in illegal business practices that can compromise public health and encourage underage use, including selling products that exceed the legal THC limit, selling counterfeit products that contain pesticides, allowing consumption of cannabis in retail stores, not imposing daily limits on purchases, staying open late at night, and selling products that are attractive to youth and lack child-resistant packaging . From a social justice perspective, it is important that African American communities now benefit from the safety precautions, employment opportunities, and revenue afforded by the retailer licensing process. For this to occur, it is important to prevent unlicensed retailers from competing with licensed retailers in African American and Hispanic neighborhoods. Retailers in unincorporated areas were more likely to be unlicensed, relative to retailers in incorporated areas. Enforcement could be difficult in unincorporated areas because these areas lack the representation of a centralized local government, which can provide local control over community services such as law enforcement and regulatory oversight for cannabis retail stores. Increased county-level enforcement resources are needed to eliminate unlicensed cannabis retailers in areas that are outside the jurisdictions of city governments. California currently has more unlicensed cannabis grow tray retailers than it can control with existing enforcement resources . Enforcement by the state has been hampered by a lack of resources and a decision to give new businesses time to comply with complex regulations. At the same time, lack of enforcement has created an environment for a thriving unregulated ‘underground market.’ Major depressive disorder  is a potentially debilitating psychiatric disorder with an estimated worldwide prevalence in emerging adults of 16–18% . Cannabis is the most commonly used recreational drug after alcohol and the highest prevalence of use is in teens and young adults . A recent study of Canadian middle school age youth showed that cannabis use was strongly associated with internalizing mental health problems  with an odds ratio of approximately 6.5 . There is some overlap in symptomatology between MDD and heavy cannabis use including anhedonia, changes in weight, sleep disturbance and psychomotor problems . A recent meta-analysis also found that adolescent cannabis use predicted depression and suicidal behaviour later in life . The link between mood disorders and cannabis use is complex, especially with respect to directionality; cannabis use is predictive of the onset of mood disorders in youth , even while some individuals use cannabis in an attempt to regulate the symptoms of depression .

The likelihood of developing MDD in heavy cannabis users who began at a young age has been estimated to be up to 8.3 times higher than in individuals who do not use cannabis . Emotion regulation, or the ability to modify one’s emotional experience to produce an appropriate response, has been shown to be maladaptive in teenagers and young adults with MDD and who use cannabis . For example, suppression is a maladaptive regulation style in which an individual inhibits expressing emotions, and is correlated with greater depressive symptoms in youth and adults . In contrast, reappraisal is an adaptive regulation style in which an individual changes their interpretation of a situation to alter the emotional impact, and is underutilized in emerging adults with MDD  and in those who are cannabis users . In the context of MDD, studies have shown lower activity in brain areas involved in emotional processing when compared to healthy controls in the dorsolateral prefrontal cortex , ventrolateral prefrontal cortex , anterior cingulate cortex, as well as the basal ganglia . These findings fit well with models of emotion regulation and of MDD. Emotion regulation is thought to occur through a network of regions, beginning with affective arousal in the amygdala and basal ganglia, then projecting to frontal regions including the vlPFC and the insula, as well as other regions such as the superior temporal gyrus and angular gyrus . The vlPDC then begins the process of emotional appraisal, indicating the need for regulation to the dlPFC. From there, the dlPFC regulates the emotion and feeds forward to the angular gyrus, STG, and back to the amygdala and basal ganglia, all of which create a regulated emotional state . Disruption of the communication among these areas in individuals with MDD has been observed both in measures of resting state connectivity  and in the suppression of activity within these frontal regions in association with over-activation of temporal regions such as the insula and hippocampus . The prevalence of depressive symptoms in frequent cannabis users suggests that brain regions involved in emotion regulation may overlap with those affected by cannabis use. A study showing emotion regulation deficits in young, regular recreational cannabis users compared to nonusers bolsters this hypothesis . Indeed, a meta-analysis showed that cannabis use was linked to brain activity abnormalities in the vlPFC, dlPFC, and dmPFC, orbital frontal cortex, ventral striatum, and thalamus . A recent review of the imaging literature indicated that adolescent cannabis users showed differences in frontal-parietal networks that mediate cognitive control .

Further, emotion regulation deficits in frequent cannabis users were associated with abnormal neural activity in bilateral frontal networks as well as decreased amygdala-dorsolateral prefrontal cortex functional connectivity . Suppressed inferior frontal and medial PFC activation has been found in cannabis users during positive and negative emotional evaluation , as has suppressed activity levels in the amygdala . The overlap in these brain regions, combined with weakened emotional regulation in people with both MDD and cannabis use, suggests that there may be an interaction between MDD and cannabis use on human brain function in the context of emotion regulation. The aim of the present study was to examine the combined effect of MDD and cannabis use on the brain during emotion regulation in emerging adults, as well as how specific characteristics, such as degree of depressive symptoms and age of cannabis use onset, affect emotion processing. To address these questions, we employed an emotion regulation task while participants underwent functional magnetic resonance imaging . We recruited individuals either with or without MDD, who either did or did not use cannabis frequently, and used a mixed effects approach to identify the unique contributions of each factor on emotion processing. Because both MDD and cannabis use have been shown to suppress activation within frontal regions during emotion regulation, we predicted that combined MDD and cannabis use would interact with emotion regulation within the vlPFC, dlPFC, and dmPFC, above and beyond the contribution of each factor alone. In contrast, we predicted that we would see a dissociation between MDD and cannabis use in temporal regions, with MDD showing increased activity levels and cannabis use showing suppression of activity during emotion processing. Finally, we predicted that severity of depressive symptoms, emotion regulation style, and age of cannabis use onset would each uniquely interact with emotion regulation, further elucidating the relationship between MDD, cannabis use, and the brain. The emotion regulation fMRI task, adopted from Greening et al. , was designed to have participants actively alter their feelings elicited by sad  and happy  emotional scenes. Twenty negative and 20 positive emotional scenes were taken from the International Affective Picture System for this study. The task involved viewing both negative and positive emotional scenes while being instructed to either simply view the scene or actively alter their feelings while viewing the scene . The four task conditions were therefore attend negative, reduce-negative, attend-positive, and enhance-positive. During the reduce-negative task condition participants were instructed to ‘acknowledge that the scene is negative. However, it does not affect you, things do not stay this bad, and the scene does not reflect the whole world’ and during the enhance-positive task condition participants were instructed to ‘acknowledge that the scene is positive. Further, that it does affect you, things can and do get even better and the scene does reflect the real world’ . This paradigm attempts to target and modify the negative thought tendencies about self, the world, and the future that are typical for depressed patients . Participants were trained and practiced the paradigm before being scanned. During 4 imaging runs each participant completed 20 trials of each task condition . The 20 negative and 20 positive emotional scenes were displayed twice, once during the attend condition and again during the regulate condition. Participants never saw the same picture twice in the same run. To help mitigate any order affects,vertical grow systems for sale the trial order in each run was set as 4 independent runs and these were counterbalanced across subjects. The functional data were also preprocessed according to the fMRIPrep pipeline. For each of the BOLD runs per subject, the following preprocessing was performed. First, a reference volume and its skull stripped version were generated using a custom methodology of fMRIPrep. The BOLD reference was then co-registered to the T1w reference using bb register which implements boundary-based registration .

Co-registration was configured with nine degrees of freedom to account for distortions remaining in the BOLD reference. Head-motion parameters with respect to the BOLD reference  are estimated before any spatiotemporal filtering using mcflirt. BOLD runs were slice-time corrected using 3dTshift from AFNI v16.2.07. The BOLD time-series, were resampled to surfaces on the following spaces: fsaverage5. The BOLD time series  were resampled onto their original, native space by applying a single, composite transform to correct for head-motion and susceptibility distortions. These resampled BOLD time-series will be referred to as preprocessed BOLD in original space, or just preprocessed BOLD. The BOLD time series were resampled to MNI152NLin2009cAsym standard space, generating a preprocessed BOLD run in MNI152NLin2009cAsym space. First, a reference volume and its skull-stripped version were generated using a custom methodology of fMRIP rep. Several confounding time series were calculated based on the preprocessed BOLD: frame wise displacement , DVARS and three region-wise global signals. FD and DVARS are calculated for each functional run, both using their implementations in Nipype . The three global signals are extracted within the CSF, the WM, and the whole-brain masks. Additionally, a set of physiological regressors were extracted to allow for component-based noise correction. Principal components are estimated after high pass filtering the preprocessed BOLD time-series  for the two CompCor variants: temporal  and anatomical . Six tCompCor components are then calculated from the top 5% variable voxels within a mask covering the sub-cortical regions. This sub-cortical mask is obtained by heavily eroding the brain mask, which ensures it does not include cortical GM regions. For aCompCor, six components are calculated within the intersection of the aforementioned mask and the union of CSF and WM masks calculated in T1w space, after their projection to the native space of each functional run .