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Despite advances in suicide risk assessment and intervention, evidence-based suicide prevention training for university health service providers is still lacking. This study evaluated the core comp...

Objective Smoking cue-(SC) elicited craving can lead to relapse in SC-vulnerable individuals. Thus, identifying treatments that target SC-elicited craving is a top research priority. Reduced drug cue neural activity is associated with recovery and is marked by a profile of greater tonic (resting) activation in executive control regions, and increased connectivity between executive and salience regions. Evidence suggests the GABA-B agonist baclofen can reduce drug cue-elicited neural activity, potentially through its actions on the resting brain. Based on the literature, we hypothesize that baclofen's effects in the resting brain can predict its effects during SC exposure. Methods In this longitudinal, double blind, placebo-controlled neuropharmacological study 43 non-abstinent, sated treatment-seeking cigarette smokers (63% male) participated in an fMRI resting-state scan and a SC-reactivity task prior to (T1) and 3 weeks following randomization (T2; baclofen: 80 mg/day; n = 21). Subjective craving reports were acquired before and after SC exposure to explicitly examine SC-induced craving. Results Whole-brain full-factorial analysis revealed a group-by-time interaction with greater resting brain activation of the right dorsolateral prefrontal cortex (dlPFC) at T2 in the baclofen group (BAC) (pFWEcorr = 0.02), which was associated with reduced neural responses to SCs in key cue-reactive brain regions; the anterior ventral insula and ventromedial prefrontal cortex (pFWEcorr ＜ 0.01). BAC, but not the placebo group reported decreased SC-elicited craving (p = 0.02). Conclusion Results suggest that baclofen mitigates the reward response to SCs through an increase in tonic activation of the dlPFC, an executive control region. Through these mechanisms, baclofen may offer SC-vulnerable smokers protection from SC-induced relapse.

BACKGROUND: Intolerance of uncertainty (IU), perceived attentional control (AC), and poor cognitive control abilities are risk factors for anxiety; however, few studies have examined their interactive effects in relation to anxiety. A more complete understanding of interplay between IU, perceived AC, and cognitive control could inform intervention efforts. METHODS: The current study examined the direct and interactive effects of IU and AC on anxiety in a sample of 280 community outpatients (M age = 36.01 years, SD = 16.17). Perceived AC was measured using self-report and cognitive control abilities were measured using a Go/No-Go task. RESULTS: Findings indicated a significant IU by perceived AC interaction predicting worry and GAD diagnoses. There was a positive relation between IU and worry/GAD diagnoses that was strongest among those with high perceived AC. Perceived AC was unrelated to cognitive control abilities, and cognitive control abilities did not interact significantly with IU. Cognitive control abilities were related to worry symptoms but not to GAD diagnoses. CONCLUSIONS: These results indicate that at high levels of perceived AC, individuals with elevated IU report higher levels of worry, potentially due to the conscious use of worry as an emotion regulation strategy. Clinical implications and future directions are discussed.

The reward positivity (RewP) is a putative biomarker of depression. Careful control of stimulus properties and manipulation of both stimulus valence and salience could facilitate interpretation of the RewP. RewP interpretation could further be improved by investigating functional outcomes of a blunted RewP in depression, such as reduced memory for rewarding outcomes. This study sought to advance RewP interpretation first by advancing task design through use of neutral (i.e., draw) control trials and counterbalanced feedback stimuli. Second, we examined the RewP's association with memory and the impact of depression. Undergraduates completed self-report measures of depression and anhedonia prior to a modified doors task in which words were displayed in colored fonts that indicated win, loss, or draw feedback. Memory of the feedback associated with each word (i.e., source memory) was tested. Results showed that RewP response to wins was more positive than to losses, which was more positive than to draws. The RewP was not associated with depression or anhedonia. The low depression group showed a source memory advantage for win words, but the high depression group did not. Source memory showed small relations to the RewP, but these did not survive Bonferroni correction. Results suggest the RewP is sensitive to salience and highlight challenges in detecting an association between the RewP and depression in modified doors tasks. Findings indicate that depression is related to dysfunctional source memory for reward but not loss and that future research should probe the possible associations between the RewP and memory in depression.

Anxiety sensitivity (AS), the fear of fear, has been proposed as a transdiagnostic feature of anxiety disorders. AS social concerns is a dimension of AS that involves worry about the social consequences of anxiety symptoms. Although AS social concerns has been linked to social anxiety both theoretically and empirically, few studies have considered processes that may explain this association. AS social concerns may be associated with avoidance of eye contact (gaze avoidance), which in turn may be associated with greater social anxiety. This hypothesis was tested using a sample of 190 undergraduate students. Self-reported gaze avoidance partially explained the association between AS social concerns and social anxiety. The model remained significant when controlling for other AS dimensions, general anxiety, and depression symptoms. The model was not moderated by race (Black, White), a finding which partially addresses the need to test how well theories apply to diverse populations. The findings advance cognitive frameworks of social anxiety by suggesting that gaze avoidance may explain associations between risk factors and symptoms. Additional research is needed to examine whether interventions that increase eye contact may weaken the association between AS social concerns and social anxiety.

Prior studies suggest that the Attentional Control Scale (ACS) consists of two correlated factors. These models do not include a general factor, though this is assumed often in theory and practice. Using an adult North American sample collected through Amazon Mechanical Turk (N = 419), we examined a revised version of the ACS with positive keying of all items (Straightforward Attentional Control Scale; ACS-S) to avoid the potential of a factor produced by mixing positively and negatively keyed items. Exploratory factor analysis using a bifactor approach was used to examine the structure of the ACS-S, which consisted of a general factor and a nuisance variance factor. There was mixed evidence of good fit for the full 20-item version of the ACS, but fit was good for a reduced 12-item version of the ACS-S. The full and reduced version were highly correlated (r = .98). Exploratory structural equation modeling suggested that the general factor of the ACS-S was negatively related to depression and both anxious arousal, as reflected by panic symptoms, and anxious apprehension, as reflected by worry. The findings suggest that perceived attentional control is uniquely related to depression and both dimensions of anxiety. ACS-S Short scores were tested as a moderator of the association between anxious apprehension and anxious arousal. The association between these anxiety dimensions was weaker at higher levels of perceived attentional control. Our findings suggest that the ACS-S is best represented as a single dimension of beliefs about attentional control which can be scored by totaling the items and that the ACS-S uniquely related to the internalizing symptoms we assessed. The findings also contribute to the understanding of how anxiety dimensions are influenced by perceived attentional control.

The COVID-19 pandemic triggered increased rates of depression, especially among college students. Due to social distancing guidelines, loneliness has been suspected as a prominent factor in depression during the pandemic. Research is needed to identify possible mechanisms through which loneliness conveys risk for pandemic-era depression. Two potential mechanisms are boredom and repetitive negative thinking (RNT). This study examined cross-sectional associations between depression, loneliness, boredom, and RNT in a sample of college students (N =199) in April 2020 immediately following campus closure. Results showed a serial indirect effect of loneliness on depression through boredom then RNT. Moreover, specific indirect effects of loneliness on depression were found through boredom and RNT, individually. Though limited by the cross-sectional design, these data align with cognitive-behavioral theory and identify boredom and RNT as possible mechanisms of the association between loneliness and depression in college students during the COVID-19 pandemic.

The COVID-19 pandemic triggered increased rates of depression, especially among college students. Due to social distancing guidelines, loneliness has been suspected as a prominent factor in depression during the pandemic. Research is needed to identify possible mechanisms through which loneliness conveys risk for pandemic-era depression. Two potential mechanisms are boredom and repetitive negative thinking (RNT). This study examined cross-sectional associations between depression, loneliness, boredom, and RNT in a sample of college students (N =199) in April 2020 immediately following campus closure. Results showed a serial indirect effect of loneliness on depression through boredom then RNT. Moreover, specific indirect effects of loneliness on depression were found through boredom and RNT, individually. These data align with cognitive-behavioral theory and identify boredom and RNT as possible mechanisms of the association between loneliness and depression in college students. As such, boredom and RNT might be suitable treatment targets for depression during the COVID-19 pandemic.

Suicide-related behavior (SRB) is a growing mental health concern on college campuses. We argue that causes of this rising trend go beyond student stress, to include outdated campus policies, overburdened counseling center staffing, and untapped targets for prevention efforts. We outline the social-ecological model applied to suicide and related public health problems. Such a viewpoint provides an example road map to redress suicide and related risk factors (e.g., violence, substance abuse) through multiple levels of prevention-focused programing. Using our SAMHSA-funded campus suicide prevention programmatic approach as a case illustration, we proffer lessons and guidelines for the implementation of a social-ecological suicide prevention program (SESPP). Emphasis is placed on review of evidence-informed prevention programs, utilization of interdisciplinary prevention teams, need for rigorous program evaluation, and consideration of the unique demography of each campus.

Past research suggests that social anxiety is associated with increased processing of cardiac activity. Cognitive theories propose that this is one aspect of self-focus, which is driven by concerns that features of the self, such as anxiety symptoms, will elicit evaluation from others. We investigated the relationship of social anxiety to the cortical processing of heartbeats as reflected in the heartbeat evoked potential (HEP) during false feedback of accelerated heart rate. Thirty-eight participants with high social anxiety (HSA; n = 19) and non-elevated social anxiety (NSA; n = 19) completed a cognitive task during which false feedback of accelerated heart rate was randomly provided on 50% of trials. HEP amplitude was larger in HSAs, but not NSAs, during false heartbeat acceleration cues compared to standard cues. HEP amplitude also was larger in HSAs compared to NSAs during acceleration cues. HEP amplitude during acceleration cues, but not standard cues correlated with social anxiety. Within the first second after the R-peak, social anxiety correlated with voltage at Fz from 223 to 305 ms. Social concerns about the consequences of anxiety symptoms accounted for an indirect relationship between social anxiety and the HEP. These data extend prior evidence of increased processing of cardiac activity in socially anxious individuals, providing support for cognitive theories.

Introduction Research indicates that overnight nicotine abstinence disrupts neural activity in the mesocorticolimbic reward network; however, less is known about the time course of abstinence-induced brain changes. To examine the potential neural effects of early abstinence, we used arterial spin labeling perfusion fMRI, to measure regional cerebral blood flow (rCBF) changes in the resting brain induced by 4 h of nicotine abstinence. Methods In a repeated measures design, 5 min of resting perfusion fMRI data were acquired in awake nicotine-dependent individuals (eyes open) during ‘smoking as usual’ (SMK) and following 4 h of monitored nicotine abstinence (ABS) conditions (N = 20). Conditions were compared using a paired t test in SPM8. Craving was assessed prior to each condition. Results Compared to SMK, ABS significantly increased craving and reduced rCBF in select regions, including the hippocampus and ventral striatum (cluster corr, α = 0.01, 943 contiguous voxels). The magnitude of the abstinence-induced change in rCBF correlated with the magnitude of the change in craving across conditions in select regions, including the medial and lateral orbitofrontal cortices and the anterior ventral insula (r values ranging from 0.59–0.74). Conclusions Results show that as few as 4 h of abstinence can reduce resting rCBF in multiple nodes of the brain’s mesocorticolimbic network, disrupting neural processing. Identifying early withdrawal treatment targets has far-reaching implications, which include thwarting relapse proclivities. Results parallel those of the extant human literature and are in agreement with an extensive preclinical literature showing compromised mesolimbic dopaminergic function and impairments in reward function during nicotine withdrawal.

Background Biological sex influences cigarette smoking behavior. More men than women smoke, but women have a harder time quitting. Sex differences in smoking cue (SC) reactivity may underlie such behavioral differences. However, the influence of sex on brain reactivity to SCs has yielded inconsistent findings suggesting the need for continued study. Here, we investigated the effect of sex on SC reactivity across two sites using different imaging modalities and SC stimulus types. Methods Pseudo-continuous arterial spin-labeled (pCASL) perfusion functional magnetic resonance imaging (fMRI) was used to assess brain responses to SC versus non-SC videos in 40 smokers (23 females) at the University of Pennsylvania. BOLD fMRI was used to assess brain responses to SC versus non-SC still images in 32 smokers (18 females) at McLean Hospital. Brain reactivity to SCs was compared between men and women and was correlated with SC-induced craving. Results In both cohorts, males showed higher SC versus non-SC reactivity compared to females in reward-related brain regions (i.e., ventral striatum/ventral pallidum, ventral medial prefrontal cortex). Brain activation during SC versus non-SC exposure correlated positively with SC-induced subjective craving in males, but not females. Conclusions The current work provides much needed replication and validation of sex differences in SC-reactivity. These findings also add to a body of literature showing that men have greater reward-related brain activation to drug cues across drug classes. Such sex differences confirm the need to consider sex not only when evaluating SC-reactivity but when examining nicotine dependence etiology and treatment.

Addiction theories posit that addiction is the result of a progressive transition from voluntary to habitual, compulsive drug use—changes that have been linked, in animals, to a shift from ventral to dorsal striatal control over drug-seeking behavior. Thus, we hypothesized that early-onset (EOs) cannabis users versus late-onset (LOs) cannabis users might exhibit, respectively, greater dorsal versus ventral striatal response to drug cues. We used functional magnetic resonance imaging and an event-related blood oxygen level-dependent backward-masking task to evaluate striatal responses to backward-masked cannabis cues (vs. neutral cues) in EOs (50 voxels). Within-group analyses revealed that EOs showed greater neural response to cannabis cues in the dorsal striatum, whereas LOs exhibited greater neural response to cannabis cues in the ventral striatum. Although cross-sectional, these findings are consistent with recent addiction theories suggesting a progressive shift from ventral to dorsal striatal control over drug-seeking behavior and highlight the importance of age of onset of cannabis use on the brain and cognition.

Obesity and cigarette smoking are two of the leading preventable causes of death in the United States. Research suggests that overlapping pathophysiology may contribute to obesity and nicotine use disorder (NUD), yet no studies have investigated the effect of obesity on neural response to reward stimuli in NUD. This study used arterial spin-labeled perfusion functional magnetic resonance imaging (fMRI) to examine neural responses during exposure to smoking versus nonsmoking cues in 79 treatment-seeking participants with NUD, 26 with normal weight, 28 with overweight, and 25 with obesity. Given that deficits in behavioral inhibitory control have been associated with both obesity and NUD, participants completed an affect-congruent Go/NoGo task to assess the effect of body mass index (BMI) on this construct in NUD. Analyses revealed that BMI was negatively associated with activation in the right dorsolateral prefrontal cortex (dlPFC) in response to smoking cues, with significantly reduced response in smokers with overweight and smokers with obesity compared with normal-weight smokers. In addition, greater commission errors on the Go/NoGo task were correlated with reduced neural response to smoking cues in the right dlPFC only among those with obesity. Together, these findings provide evidence that obesity in treatment-seeking NUDs is related to neurobiological alterations in inhibitory control over cue-potentiated behaviors, suggesting that smoking cessation may be more difficult in individuals with comorbid NUD and obesity than in those without, requiring treatment strategies tailored to meet their unique needs.

Cigarette smoking continues to be a leading cause of preventable morbidity and mortality. Although the majority of smokers report making a quit attempt in the past year, smoking cessation rates remain modest. Thus, developing accurate, data-driven methods that can classify and characterize the neural features of nicotine use disorder (NUD) would be a powerful clinical tool that could aid in optimizing treatment development and guide treatment modifications. This investigation applied support vector machine-based classification to resting-state functional connectivity (rsFC) data from individuals diagnosed with NUD (n = 108; 63 male) and matched nonsmoking controls (n = 108; 63 male) and multi-dimensional scaling to visualize the heterogeneity of NUD in individual smokers based on rsFC measures. Machine-based learning models identified five resting-state networks that played a role in distinguishing smokers from controls: the posterior and anterior default mode networks, the sensorimotor network, the salience network and the right executive control network. The classification method constructed classifiers with an average correct classification rate of 88.1 percent and an average area under the curve of 0.93. Compared with controls, individuals with NUD had weaker functional connectivity measures within these networks (P

Cigarette smoking is a chronic relapsing brain disorder, and remains a premier cause of morbidity and mortality. Functional neuroimaging has been used to assess differences in the mean strength of brain activity in smokers’ brains, however less is known about the temporal dynamics within smokers’ brains. Temporal dynamics is a key feature of a dynamic system such as the brain, and may carry information critical to understanding the brain mechanisms underlying cigarette smoking. We measured the temporal dynamics of brain activity using brain entropy (BEN) mapping and compared BEN between chronic non-deprived smokers and non-smoking controls. Because of the known sex differences in neural and behavioral smoking characteristics, comparisons were also made between males and females. Associations between BEN and smoking related clinical measures were assessed in smokers. Our data showed globally higher BEN in chronic smokers compared to controls. The escalated BEN was associated with more years of smoking in the right limbic area and frontal region. Female nonsmokers showed higher BEN than male nonsmokers in prefrontal cortex, insula, and precuneus, but the BEN sex difference in smokers was less pronounced. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to smoking.

Preclinical and clinical research indicates that there are sex differences in how men and women initiate, progress, respond to, and withdraw from cannabis use; however, neurophysiological differences, such as neural responses to cannabis cues, are not well understood. Using functional MRI and an event-related blood oxygen level-dependent backward-masking task, we compared neural responses to backward-masked cannabis cues to neutral cues in treatment-seeking, cannabis-dependent adults (N = 44; 27 males) and examined whether sex differences exist. In addition, functional MRI findings were correlated with cannabis craving. Backward-masked cannabis cues elicited greater neural responses than neutral cues in reward-related brain regions, including the striatum, hippocampus/amygdala, insula, anterior cingulate cortex, and lateral orbitofrontal cortex, p.01, k121 voxels. Although no significant sex differences in neural responses to cannabis cues emerged, women showed a positive correlation between neural responses to cannabis cues in the bilateral insula and cannabis craving and an inverse correlation between neural responses to cannabis cues in the left lateral orbitofrontal cortex and cannabis craving. Men, however, showed a positive correlation between neural responses to cannabis cues in the striatum and cannabis craving. Given that cues and craving are important triggers and the focus on many behavioral treatment approaches, these findings suggest that treatment-seeking, cannabis-dependent men and women may benefit from sex-specific and tailored cannabis use disorder treatments.

The magnetization-prepared rapid gradient-echo (MP-RAGE) T1-weighted high resolution structural MRI is a mainstay tool used to identify morphometric biomarkers of disease conditions, progression and treatment effects despite a critical limitation: the relaxation signal on which inferences are based is nearly indistinguishable for gray matter vs. blood flow (Lu et al., 2004; Wright et al., 2008). Thus, apparent reported morphometric findings might be at least partially related to transient changes in blood flow or other physiological signals. Consistent with this technical limitation, using a standard analysis technique, voxel based morphometry (VBM), we recently reported that a single dose of a medication had “apparent” effects on T1-weighted MRIs (Franklin et al., 2013). Specifically, we observed medication-induced decreases in gray matter volume in the anterior cingulate and other regions that overlapped with changes in brain blood flow (perfusion). Similarly, others have shown effects of medication on T1-weighted scans that are likely transient. For example, acute levodopa administration altered gray matter indices on T1-weighted images in the midbrain (Salgado-Pineda et al., 2006). Further, in a well-controlled longitudinal VBM study of patients with attention deficit hyperactivity disorder (ADHD), Hoekzema et al. (2014) showed that stimulant drugs trigger transient volumetric changes in the ventral striatum, challenging previous VBM studies suggesting that these changes were an intrinsic feature of the disorder (Hoekzema et al., 2014). These examples highlight the importance of employing appropriate experimental conditions to ensure that morphometric findings are actually revealing long-term changes that are unrelated to transient states. Specifically, longitudinal investigations into the effects of a medication on neural structure using VBM may want to include a group that is administered an acute dose of the medication. The findings of altered gray matter induced by acute pharmacological manipulations highlighted above led us to hypothesize that cigarette smoking, which delivers the psychostimulant, nicotine, to the brain may transiently alter the MP-RAGE, based on the T1-weighted images. Thus, we examined T1-weighted structural MRIs acquired in a within-subjects design in 39 otherwise healthy nicotine-dependent individuals. Subjects meeting our standard MRI-specific inclusion/exclusion criteria (Franklin et al., 2013, 2014) provided written informed consent to participate in the study, which adhered to the Declaration of Helsinki and was approved by the University of Pennsylvania Institutional Review Board. Screening procedures included a medical history, physical examination, and a psychological assessment. Subjects participated in two counterbalanced scanning sessions that occurred on separate days. For condition “Smoke” subjects smoked a cigarette to satiety approximately 45 min prior to obtaining structural MRI data. For condition “No smoke,” subjects smoked a cigarette and then remained abstinent for approximately 5 h prior to data acquisition. To obtain quantitative cerebral blood flow (CBF) maps, 5 min resting baseline pseudo-continuous arterial spin labeled perfusion fMRI scans were also acquired under both conditions. Nicotine's terminal half-life is approximately 2 h; thus, conservative estimates might place the onset of withdrawal symptomatology within the first 2 h after last smoking (Benowitz et al., 1982). Thus, 5 h of deprivation was chosen to ensure that the subjects would be experiencing withdrawal from nicotine. During the “No smoke” condition, carbon monoxide (CO) levels were acquired after the baseline cigarette and prior to scanning. Abstinence was confirmed by monitoring the subjects and was biochemically confirmed by observing reductions in CO from baseline to time of scan acquisition. Structural data were analyzed using statistical mapping software (SPM8) and its available VBM tool with diffeomorphic anatomical registration using exponentiated lie algebra (DARTEL). Statistical parametric maps were generated to perform between-condition comparisons (paired t-test) using the gray matter tissue segmentation output by DARTEL. To obtain measures of brain blood flow mean CBF maps were calculated for each condition and between-condition comparisons (paired t-test) were performed. Image acquisition, data processing and analysis methods have been previously published (Franklin et al., 2013, 2014). Once again, we report that transient state impacts gray matter indices. Compared to not smoking for several hours, recent smoking altered the T-1 weighted MP-RAGE, bilaterally in the striatum (see Figure ​Figure11 and http://www.franklinbrainimaging.com/LimitationsofMPRAGE/, which provides all images from all 3 planes). Differences were not observed in any other brain regions. Additionally, as in our previous study, the effects overlapped with changes in blood flow (Figure S1 shows the results from the MP-RAGE and blood flow overlain on the same template. These results unambiguously demonstrate that the use of VBM to identify morphometric biomarkers of disease conditions, progression and treatment effects must employ appropriate experimental conditions to ensure that morphometric findings are not related to acute states that may be introduced by drug or medication, but are indeed revealing long-term change. Importantly, the use of medications or substances (e.g., alcohol, cigarettes, concomitant medications) that affect the brain should be controlled (either through matching or statistical co-variation) across groups that are being compared. Third, these results show that the MP-RAGE should be acquired at the initiation of a scanning session, given the potential for it to be altered by subsequent activities (tasks, pharmacological manipulations) that occur over the course of scanning. These findings also underscore the crucial and immediate need to develop neuroimaging tools that can uniquely capture changes in neuronal structure dissociable from those related to blood flow or other physiological signals. Figure 1 Illustration of the effects of physiological state on VBM results. T1-weighted MPRAGE structural MRI scans were acquired in nicotine-dependent individuals after recently smoking (Smoke condition) or maintaining 5 h of monitored abstinence (No Smoke condition) ...

Aims: Attentional biases (AB) interfere with decision making processes and AB to drug cues is a cardinal feature of addiction that may contribute to relapse. Thus it is critical to identify the neural correlates of AB for improving interventions. Cue responsivity and AB differ between males and females suggesting the neural correlates of AB to drug cues may also be sex-specific. Methods: We explored associations between AB for cannabis cues (CCs) and neural responses to CCs among males (n=24) and females (n=14) seeking treatment for cannabis use disorder (CUD). CUDs were exposed to CCs and comparison cues (500ms duration; 48 images of each cue type) presented in a quasi-random order in a BOLD fMRI fast event-related paradigm. Males and females did not differ in demographic or drug use characteristics. Male and female CUDs also completed a visual dot-probe AB task, which contained pictures of CCs and nondrug cues to examine whether sex influences AB and to investigate relationships between AB and neural responses to CCs. Results: CUDs showed an AB to CCs (22.8±4.7ms), which was not significantly different between males and females. Neural responses to CCs were strongest in the ventral striatum in females and the amygdala inmales.Males showed positive correlations between AB and increased CC-induced brain activity in visual cortex and bilateral parahippocampus whereas females showed positive correlations (all bilateral) in the insula, lateral orbitofrontal cortex, dorsolateral prefrontal cortex and middle temporal cortex. (T values range from 3 to 6, p=0.01). Conclusions: Results suggest that AB to CCs has different brain correlates for men and women. Thus, strategies to address AB may need to target sex-specific brain vulnerabilities for maximum impact on relapse. Financial support: PA DOH CURE.

Background Structural magnetic resonance imaging techniques are powerful tools for examining the effects of drug use on the brain. The nicotine and cannabis literature has demonstrated differences between nicotine cigarette smokers and cannabis users compared to controls in brain structure; however, less is known about the effects of co-occurring cannabis and tobacco use. Methods We used voxel-based morphometry to examine gray matter volume differences between four groups: (1) cannabis-dependent individuals who do not smoke tobacco (Cs); (2) cannabis-dependent individuals who smoke tobacco (CTs); (3) cannabis-naive, nicotine-dependent individuals who smoke tobacco (Ts); and (4) healthy controls (HCs). We also explored associations between gray matter volume and measures of cannabis and tobacco use. Results A significant group effect was observed in the left putamen, thalamus, right precentral gyrus, and left cerebellum. Compared to HCs, the Cs, CTs, and Ts exhibited larger gray matter volumes in the left putamen. Cs also had larger gray matter volume than HCs in the right precentral gyrus. Cs and CTs exhibited smaller gray matter volume than HCs in the thalamus, and CTs and Ts had smaller left cerebellar gray matter volume than HCs. Conclusions This study extends previous research that independently examined the effects of cannabis or tobacco use on brain structure by including an examination of co-occurring cannabis and tobacco use, and provides evidence that cannabis and tobacco exposure are associated with alterations in brain regions associated with addiction.

Cigarette smoke contains nicotine and toxic chemicals and may cause significant neurochemical and anatomical brain changes. Voxel-based morphometry studies have examined the effects of smoking on the brain by comparing gray matter volume (GMV) in nicotine dependent individuals (NDs) to nonsmoking individuals with inconsistent results. Although sex differences in neural and behavioral features of nicotine dependence are reported, sex differences in regional GMV remain unknown. The current study examined sex differences in GMV in a large sample of 80 NDs (41 males) and 80 healthy controls (41 males) using voxel-based morphometry. Within NDs, we explored whether GMV was correlated with measures of cigarette use and nicotine dependence. High-resolution T1 structural scans were obtained from all participants. Segmentation and registration were performed in SPM8 using the optimized DARTEL approach. Covariates included age and an estimate of total global GMV. Differences were considered significant at p≤0.001, with a whole brain FWE-corrected cluster probability of p

Background Sex differences in tobacco-related morbidity and mortality exist, with women experiencing more severe health consequences and greater difficulty with smoking cessation than men. One factor that likely contributes to these sex differences is menstrual cycle phase and associated neural and cognitive changes associated with ovarian hormone fluctuations across the menstrual cycle. Previously, we showed that naturally cycling, cigarette-dependent women in the follicular phase of their menstrual cycle showed greater reward-related neural activity and greater craving during smoking cue exposure. To better understand our results and the observed sex differences in smoking behavior and relapse, we explored potential menstrual cycle phase differences in resting-state functional connectivity (rsFC) in naturally cycling, cigarette-dependent women. Understanding how menstrual cycle phase affects neural processes, cognition, and behavior is a critical step in developing more efficacious treatments and in selecting the best treatment option based on a patient’s needs. Methods Resting-state functional connectivity analyses were used to examine connectivity strength differences between naturally cycling, premenopausal, cigarette-dependent women who were in the follicular phase (FPs; n = 22) and those in the luteal phase (LPs, n = 16) of their menstrual cycle. We also explored associations between connectivity strength and attentional bias to smoking cues. Results Compared with LPs, FPs showed decreased rsFC between the dorsal anterior cingulate cortex (dACC) and the subgenual anterior cingulate cortex, medial orbitofrontal cortex (mOFC), and ventral striatum. Among FPs, rsFC strength between the dACC and the bilateral dorsolateral prefrontal cortex (DLPFC), the bilateral dorsal striatum, and the left temporal gyrus was inversely correlated with attentional bias to smoking cues. Conclusions This is the first study to explore menstrual cycle phase differences in rsFC among cigarette-dependent women, and results suggest that FPs show differences in rsFC underlying cognitive control, which could place them at greater risk for continued smoking and relapse. These findings provide new insights toward individualized treatment strategies. Electronic supplementary material The online version of this article (doi:10.1186/s13293-016-0078-6) contains supplementary material, which is available to authorized users.