Connectome-based Brain Marker Moderates the Relationship between Childhood Adversity and Transdiagnostic Psychopathology during Early Adolescence.

Importance: Identifying brain-based markers of resiliency that reliably predict who is and is not at elevated risk for developing psychopathology among children who experience adverse childhood experiences (ACEs) is important for improving our mechanistic understanding of these etiological links between child adversity and psychopathology and guiding precision medicine and prevention efforts for reducing psychiatric impact of ACEs. Objective: To examine associations between ACEs and transdiagnostic psychopathology during the transition from preadolescence to early adolescence and test whether these associations are moderated by a hypothesized resilience factor, a previously identified connectome variate (CV) that is associated with higher cognitive function and lower psychopathology. Design Setting and Participants: This study was conducted in a longitudinal design based on multicenter data from a community cohort of U.S. youth aged of 9-11 at baseline, who participated in the Adolescent Brain Cognitive Development (ABCD) study (N=7,382 at baseline and 6,813 at 2-year follow-up). Linear regression models and moderation analyses were used to characterize concurrent and prospective associations between lifetime ACEs and number of DSM-5 psychiatric disorders (indexing transdiagnostic psychopathology) and to determine if individual variations in these associations were moderated by the CV derived from resting-state fMRI at baseline. Main Outcomes and Measures: Cumulative number of current DSM-5 psychiatric disorders assessed using the computerized self-admin version Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-5) and lifetime ACEs assessed from child and parent reports at baseline (9-10 years) and 2-year-follow-up (11-12 years). Results: ACE total scores correlated positively with the cumulative number of current DSM-5 psychiatric disorders at both baseline (r =.258, p < .001) and 2-year follow-up (r =.257, p < .001). The baseline CV score moderated the ACE-disorder associations at baseline (B = -0.021, p < .001) and at 2-year follow-up (B = -0.018, p = .008), as well as the association between the changes in ACE and in the number of disorders from baseline to year 2 (B = -0.012, p = .045). Post-hoc analyses further showed that the moderation effect of CV on ACE-psychopathology associations was specific to the threat-related ACEs and to female youth. Conclusions and Relevance: These findings provide preliminary evidence for a connectome-based resiliency marker and suggest that functional connectivity strength in a broad system including frontal-parietal cortices and subcortical nuclei relevant to cognitive control may protect preadolescents who have experienced lifetime ACEs--especially females and those experiencing threat-related ACEs--from developing transdiagnostic psychopathology.

In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI.

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, ω $$ \omega $$ , in addition to the diffusion tensor, D $$ \mathbf{D} $$ , and relaxation, R 1 $$ {R}_1 $$ , R 2 $$ {R}_2 $$ , correlations. A D ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their D ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

Sex-difference in the association between social drinking, structural brain aging and cognitive function in older individuals free of cognitive impairment.

Background: We investigated a potential sex difference in the relationship between alcohol consumption, brain age gap and cognitive function in older adults without cognitive impairment from the population-based Mayo Clinic Study of Aging. Methods: Self-reported alcohol consumption was collected using the food-frequency questionnaire. A battery of cognitive testing assessed performance in four different domains: attention, memory, language, and visuospatial. Brain magnetic resonance imaging (MRI) was conducted using 3-T scanners (Signa; GE Healthcare). Brain age was estimated using the Brain-Age Regression Analysis and Computational Utility Software (BARACUS). We calculated the brain age gap as the difference between predicted brain age and chronological age. Results: The sample consisted of 269 participants [55% men (n=148) and 45% women (n=121) with a mean age of 79.2 ± 4.6 and 79.5 ± 4.7 years respectively]. Women had significantly better performance compared to men in memory, (1.12 ± 0.87 vs 0.57 ± 0.89, P<0.0001) language (0.66 ± 0.8 vs 0.33 ± 0.72, P=0.0006) and attention (0.79 ± 0.87 vs 0.39 ± 0.83, P=0.0002) z-scores. Men scored higher in visuospatial skills (0.71 ± 0.91 vs 0.44 ± 0.90, P=0.016). Compared to participants who reported zero alcohol drinking (n=121), those who reported alcohol consumption over the year prior to study enrollment (n=148) scored significantly higher in all four cognitive domains [memory: F3,268 = 5.257, P=0.002, Language: F3,258 = 12.047, P<0.001, Attention: F3,260 = 22.036, P<0.001, and Visuospatial: F3,261 = 9.326, P<0.001] after correcting for age and years of education. In addition, we found a significant positive correlation between alcohol consumption and the brain age gap (P=0.03). Post hoc regression analysis for each sex with language z-score revealed a significant negative correlation between brain age gap and language z-scores in women only (P=0.008). Conclusion: Among older adults who report alcohol drinking, there is a positive association between higher average daily alcohol consumption and accelerated brain aging despite the fact that drinkers had better cognitive performance compared to zero drinkers. In women only, accelerated brain aging is associated with worse performance in language cognitive domain. Older adult women seem to be vulnerable to the negative effects of alcohol on brain structure and on certain cognitive functions.

Childhood Trauma, Emotional Awareness, and Neural Correlates of Long-Term Nicotine Smoking.

Importance: Temporal dynamic measures provide insight into the neurobiological properties of nicotine use. It is critical to determine whether brain-based measures are associated with substance use risk factors, such as childhood trauma-related emotion dysregulation. Objective: To assess temporal dynamic differences based on smoking status and examine the associations between childhood trauma, alexithymia, nicotine smoking, and default mode network (DMN) states. Design, Setting, and Participants: This cross-sectional study was conducted in the Baltimore, Maryland, area at the National Institute on Drug Abuse. Participants included individuals aged 18 to 65 years who smoked nicotine long term and matched controls with no co-occurring substance use or psychiatric disorders. Participants were enrolled from August 8, 2013, to August 9, 2022. Analysis was conducted from August 2022 to July 2023. Exposure: Long-term nicotine smoking. Main Outcomes and Measures: The main outcome was temporal dynamic differences based on smoking status. Coactivation pattern analysis was conducted based on 16-minute resting-state functional magnetic resonance imaging; total time in, persistence of, and frequency of transitions into states were evaluated. The associations between childhood trauma (Childhood Trauma Questionnaire), alexithymia (20-item Toronto Alexithymia Scale), and DMN temporal dynamics were assessed. Results: The sample included 204 participants (102 individuals who smoked nicotine and 102 control individuals) with a mean (SD) age of 37.53 (10.64) years (109 [53.4%] male). Compared with controls, individuals who smoked nicotine spent more time in the frontoinsular DMN (FI-DMN) state (mean difference, 25.63 seconds; 95% CI, 8.05-43.20 seconds; η2p = 0.04; P = .004 after Bonferroni correction). In those who smoked nicotine, greater alexithymia was associated with less time spent in the FI-DMN state (r, -0.26; 95% CI, -0.44 to -0.07; P = .007). In a moderated mediation analysis, alexithymia mediated the association between childhood trauma and time spent in the FI-DMN state only in individuals who smoked nicotine (c' = -0.24; 95% CI, -0.58 to -0.03; P = .02). Conclusions and Relevance: Compared with controls, individuals who smoked nicotine spent more time in the FI-DMN state. Among those who smoked nicotine, childhood trauma-related alexithymia was associated with less time spent in the FI-DMN state, indicating that considering trauma-related factors may reveal alternative neurobiological underpinnings of substance use. These data may aid in reconciling contradictory findings in prior literature regarding the role of FI-DMN regions in substance use.

In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI.

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, ω, in addition to the diffusion tensor, D, and relaxation, R1, R2, correlations. A D(ω)-R1-R2 clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their D(ω)-R1-R2 distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

Brain Functional Connectome Defines a Transdiagnostic Dimension Shared by Cognitive Function and Psychopathology in Preadolescents.

BACKGROUND: Cognitive function and general psychopathology are two important classes of human behavior dimensions that are individually related to mental disorders across diagnostic categories. However, whether these two transdiagnostic dimensions are linked to common or distinct brain networks that convey resilience or risk for the development of psychiatric disorders remains unclear. METHODS: The current study is a longitudinal investigation with 11,875 youths from the Adolescent Brain Cognitive Development (ABCD) Study at ages 9 to 10 years at the onset of the study. A machine learning approach based on canonical correlation analysis was used to identify latent dimensional associations of the resting-state functional connectome with multidomain behavioral assessments including cognitive functions and psychopathological measures. For the latent resting-state functional connectivity factor showing a robust behavioral association, its ability to predict psychiatric disorders was assessed using 2-year follow-up data, and its genetic association was evaluated using twin data from the same cohort. RESULTS: A latent functional connectome pattern was identified that showed a strong and generalizable association with the multidomain behavioral assessments (5-fold cross-validation: ρ = 0.68-0.73 for the training set [n = 5096]; ρ = 0.56-0.58 for the test set [n = 1476]). This functional connectome pattern was highly heritable (h2 = 74.42%, 95% CI: 56.76%-85.42%), exhibited a dose-response relationship with the cumulative number of psychiatric disorders assessed concurrently and at 2 years post-magnetic resonance imaging scan, and predicted the transition of diagnosis across disorders over the 2-year follow-up period. CONCLUSIONS: These findings provide preliminary evidence for a transdiagnostic connectome-based measure that underlies individual differences in the development of psychiatric disorders during early adolescence.

Misconfigured striatal connectivity profiles in smokers.

Dysregulation of frontal cortical inputs to the striatum is foundational in the neural basis of substance use disorder (SUD). Neuroanatomical and electrophysiological data increasingly show that striatal nodes receive appreciable input from numerous cortical areas, and that the combinational properties of these multivariate "connectivity profiles" play a predominant role in shaping striatal activity and function. Yet, how abnormal configuration of striatal connectivity profiles might contribute to SUD is unknown. Here, we implemented a novel "connectivity profile analysis" (CPA) approach using resting-state functional connectivity data to facilitate detection of different types of connectivity profile "misconfiguration" that may reflect distinct forms of aberrant circuit plasticity in SUD. We examined 46 nicotine-dependent smokers and 33 non-smokers and showed that both dorsal striatum (DS) and ventral striatum (VS) connectivity profiles with frontal cortex were misconfigured in smokers-but in doubly distinct fashions. DS misconfigurations were stable across sated and acute abstinent states (indicative of a "trait" circuit adaptation) whereas VS misconfigurations emerged only during acute abstinence (indicative of a "state" circuit adaptation). Moreover, DS misconfigurations involved abnormal connection strength rank order arrangement, whereas VS misconfigurations involved abnormal aggregate strength. We found that caudal ventral putamen in smokers uniquely displayed multiple types of connectivity profile misconfiguration, whose interactive magnitude was linked to dependence severity, and that VS misconfiguration magnitude correlated positively with withdrawal severity during acute abstinence. Findings underscore the potential for approaches that more aptly model the neurobiological composition of corticostriatal circuits to yield deeper insights into the neural basis of SUD.

Brain lesions disrupting addiction map to a common human brain circuit.

Drug addiction is a public health crisis for which new treatments are urgently needed. In rare cases, regional brain damage can lead to addiction remission. These cases may be used to identify therapeutic targets for neuromodulation. We analyzed two cohorts of patients addicted to smoking at the time of focal brain damage (cohort 1 n = 67; cohort 2 n = 62). Lesion locations were mapped to a brain atlas and the brain network functionally connected to each lesion location was computed using human connectome data (n = 1,000). Associations with addiction remission were identified. Generalizability was assessed using an independent cohort of patients with focal brain damage and alcohol addiction risk scores (n = 186). Specificity was assessed through comparison to 37 other neuropsychological variables. Lesions disrupting smoking addiction occurred in many different brain locations but were characterized by a specific pattern of brain connectivity. This pattern involved positive connectivity to the dorsal cingulate, lateral prefrontal cortex, and insula and negative connectivity to the medial prefrontal and temporal cortex. This circuit was reproducible across independent lesion cohorts, associated with reduced alcohol addiction risk, and specific to addiction metrics. Hubs that best matched the connectivity profile for addiction remission were the paracingulate gyrus, left frontal operculum, and medial fronto-polar cortex. We conclude that brain lesions disrupting addiction map to a specific human brain circuit and that hubs in this circuit provide testable targets for therapeutic neuromodulation.

Not all smokers are alike: the hidden cost of sustained attention during nicotine abstinence.

Nicotine Withdrawal Syndrome (NWS)-associated cognitive deficits are notably heterogeneous, suggesting underlying endophenotypic variance. However, parsing this variance in smokers has remained challenging. In this study, we identified smoker subgroups based on response accuracy during a Parametric Flanker Task (PFT) and then characterized distinct neuroimaging endophenotypes using a nicotine state manipulation. Smokers completed the PFT in two fMRI sessions (nicotine sated, abstinent). Based on response accuracy in the stressful, high cognitive demand PFT condition, smokers split into high (HTP, n = 21) and low task performer (LTP, n = 24) subgroups. Behaviorally, HTPs showed greater response accuracy (88.68% ± 5.19 SD) vs. LTPs (51.04% ± 4.72 SD), independent of nicotine state, and greater vulnerability to abstinence-induced errors of omission (EOm, p = 0.01). Neurobiologically, HTPs showed greater BOLD responses in attentional control brain regions, including bilateral insula, dorsal ACC, and frontoparietal Cx for the [correct responses (-) errors of commission] PFT contrast in both states. A whole-brain functional connectivity (FC) analysis with these subgroup-derived regions as seeds identified two circuits: Precentral Cx↔Insula and Insula↔Occipital Cx, with abstinence-induced FC strength increases seen only in HTPs. Finally, abstinence-induced FC and behavior (EOm) differences were positively correlated for HTPs in a Precentral Cx↔Orbitofrontal cortical circuit. In sum, only the HTP subgroup demonstrated sustained attention deficits following 48-hr nicotine abstinence, a stressor in dependent smokers. Unpacking underlying smoker heterogeneity with this 'dual (task and abstinence) stressor' approach revealed discrete smoker subgroups with differential attentional deficits to withdrawal that could be novel pharmacological/behavioral targets for therapeutic interventions to improve cessation outcomes.

Dose-dependent relationship between social drinking and brain aging.

Low-level alcohol consumption is commonly perceived as being inconsequential or even beneficial for overall health, with some reports suggesting that it may protect against dementia or cardiovascular risks. However, these potential benefits do not preclude the concurrent possibility of negative health outcomes related to alcohol consumption. To examine whether casual, non-heavy drinking is associated with premature brain aging, we utilized the Brain-Age Regression Analysis and Computational Utility Software package to predict brain age in a community sample of adults [n = 240, mean age 35.1 (±10.7) years, 48% male, 49% African American]. Accelerated brain aging was operationalized as the difference between predicted and chronological age ("brain age gap"). Multiple regression analysis revealed a significant association between previous 90-day alcohol consumption and brain age gap (ß = 0.014, p = 0.023). We replicated these results in an independent cohort [n = 231 adults, mean age 34.3 (±11.1) years, 55% male, 28% African American: ß = 0.014, p = 0.002]. Our results suggest that even low-level alcohol consumption is associated with premature brain aging. The clinical significance of these findings remains to be investigated.

Laterality Hotspots in the Striatum.

Striatal loci are connected to both the ipsilateral and contralateral frontal cortex. Normative quantitation of the dissimilarity between striatal loci's hemispheric connection profiles and its spatial variance across the striatum, and assessment of how interindividual differences relate to function, stands to further the understanding of the role of corticostriatal circuits in lateralized functions and the role of abnormal corticostriatal laterality in neurodevelopmental and other neuropsychiatric disorders. A resting-state functional connectivity fingerprinting approach (n = 261) identified "laterality hotspots"-loci whose profiles of connectivity with ipsilateral and contralateral frontal cortex were disproportionately dissimilar-in the right rostral ventral putamen, left rostral central caudate, and bilateral caudal ventral caudate. Findings were replicated in an independent sample and were robust to both preprocessing choices and the choice of cortical atlas used for parcellation definitions. Across subjects, greater rightward connectional laterality at the right ventral putamen hotspot and greater leftward connectional laterality at the left rostral caudate hotspot were associated with higher performance on tasks engaging lateralized functions (i.e., response inhibition and language, respectively). In sum, we find robust and reproducible evidence for striatal loci with disproportionately lateralized connectivity profiles where interindividual differences in laterality magnitude are associated with behavioral capacities on lateralized functions.

Schizophrenia Patients Show Largely Similar Salience Signaling Compared to Healthy Controls in an Observational Task Environment.

Recent evidence suggests that the aberrant signaling of salience is associated with psychotic illness. Salience, however, can take many forms in task environments. For example, salience may refer to any of the following: (1) the valence of an outcome, (2) outcomes that are unexpected, called reward prediction errors (PEs), or (3) cues associated with uncertain outcomes. Here, we measure brain responses to different forms of salience in the context of a passive PE-signaling task, testing whether patients with schizophrenia (SZ) showed aberrant signaling of particular types of salience. We acquired event-related MRI data from 29 SZ patients and 23 controls during the performance of a passive outcome prediction task. Across groups, we found that the anterior insula and posterior parietal cortices were activated to multiple different types of salience, including PE magnitude and heightened levels of uncertainty. However, BOLD activation to salient events was not significantly different between patients and controls in many regions, including the insula, posterior parietal cortices, and default mode network nodes. Such results suggest that deficiencies in salience processing in SZ may not result from an impaired ability to signal salience per se, but instead the ability to use such signals to guide future actions. Notably, no between-group differences were observed in BOLD signal changes associated with PE-signaling in the striatum. However, positive symptom severity was found to significantly correlate with the magnitudes of salience contrasts in default mode network nodes. Our results suggest that, in an observational environment, SZ patients may show an intact ability to activate striatal and cortical regions to rewarding and non-rewarding salient events. Furthermore, reduced deactivation of a hypothesized default mode network node for SZ participants with high levels of positive symptoms, following salient events, point to abnormalities in interactions of the salience network with other brain networks, and their potential importance to positive symptoms.

Time-Varying Functional Connectivity Decreases as a Function of Acute Nicotine Abstinence.

BACKGROUND: The nicotine withdrawal syndrome (NWS) includes affective and cognitive disruptions whose incidence and severity vary across time during acute abstinence. However, most network-level neuroimaging uses static measures of resting-state functional connectivity and assumes time-invariance and is thus unable to capture dynamic brain-behavior relationships. Recent advances in resting-state functional connectivity signal processing allow characterization of time-varying functional connectivity (TVFC), which characterizes network communication between networks that reconfigure over the course of data collection. Therefore, TVFC may more fully describe network dysfunction related to the NWS. METHODS: To isolate alterations in the frequency and diversity of communication across network boundaries during acute nicotine abstinence, we scanned 25 cigarette smokers in the nicotine-sated and abstinent states and applied a previously validated method to characterize TVFC at a network and a nodal level within the brain. RESULTS: During abstinence, we found brain-wide decreases in the frequency of interactions between network nodes in different modular communities (i.e., temporal flexibility). In addition, within a subset of the networks examined, the variability of these interactions across community boundaries (i.e., spatiotemporal diversity) also decreased. Finally, within 2 of these networks, the decrease in spatiotemporal diversity was significantly related to NWS clinical symptoms. CONCLUSIONS: Using multiple measures of TVFC in a within-subjects design, we characterized a novel set of changes in network communication and linked these changes to specific behavioral symptoms of the NWS. These reductions in TVFC provide a meso-scale network description of the relative inflexibility of specific large-scale brain networks during acute abstinence.

Nicotinic receptor modulation of the default mode network.

RATIONALE: Previous neuroimaging studies of cognition involving nicotinic acetylcholine receptor (nAChR) agonist administration have repeatedly found enhanced task-induced deactivation of regions of the default mode network (DMN), a group of brain systems that is more active at rest and mediates task-independent thought processes. This effect may be related to pro-cognitive nAChR agonist effects OBJECTIVES: The present study sought to test whether nAChR modulation of the DMN is bi-directional, i.e., whether a nAChR antagonist would reduce task-induced deactivation. METHODS: Eighteen healthy non-smokers underwent functional magnetic resonance imaging while performing a letter N-back task. Scans were performed after nicotine administration (7 mg/24 h, transdermally), after administration of the nAChR antagonist mecamylamine (7.5 mg, p.o.), and after double placebo, in counterbalanced sequence. Blood-oxygen-level-dependent (BOLD) signal was analyzed within ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC) regions of interest-central hubs of the DMN in which consistent nAChR agonist-induced changes had previously been identified. RESULTS: Nicotine enhanced hit rate in both the 0-back and 2-back condition, while mecamylamine slowed reaction time in the 2-back condition. Mecamylamine reduced task-induced deactivation of vmPFC and PCC. Nicotine had no significant effects on the BOLD signal. CONCLUSIONS: The finding that nAChR tone reduction by mecamylamine weakened task-induced DMN deactivation indicates that a constant tone of nAChR activation helps regulate DMN activity in healthy individuals. This suggests that low nAChR tone may play a causal role in DMN dysregulation seen in conditions such as mild cognitive impairment or Alzheimer's disease.

Short-term nicotine deprivation alters dorsal anterior cingulate glutamate concentration and concomitant cingulate-cortical functional connectivity.

Most cigarette smokers who wish to quit too often relapse within the first few days of abstinence, primarily due to the aversive aspects of the nicotine withdrawal syndrome (NWS), which remains poorly understood. Considerable research has suggested that the dorsal anterior cingulate cortex (dACC) plays a key role in nicotine dependence, with its functional connections between other brain regions altered as a function of trait addiction and state withdrawal. The flow of information between dACC and fronto-striatal regions is secured through different pathways, the vast majority of which are glutamatergic. As such, we investigated dACC activity using resting state functional connectivity (rsFC) with functional magnetic resonance imaging (fMRI) and glutamate (Glu) concentration with magnetic resonance spectroscopy (MRS). We also investigated the changes in adenosine levels in plasma during withdrawal as a surrogate for brain adenosine, which plays a role in fine-tuning synaptic glutamate transmission. Using a double-blind, placebo-controlled, randomized crossover design, nontreatment seeking smoking participants (N = 30) completed two imaging sessions, one while nicotine sated and another after 36 h nicotine abstinence. We observed reduced dACC Glu (P = 0.029) along with a significant reduction in plasma adenosine (P = 0.03) and adenosine monophosphate (AMP; P < 0.0001) concentrations during nicotine withdrawal in comparison with nicotine sated state. This withdrawal state manipulation also led to an increase in rsFC strength (P < 0.05) between dACC and several frontal cortical regions, including left superior frontal gyrus (LSFG), and right middle frontal gyrus (RMFG). Moreover, the state-trait changes in dACC Glu and rsFC strength between the dACC and both SFG and MFG were positively correlated (P = 0.012, and P = 0.007, respectively). Finally, the change in circuit strength between dACC and LSFG was negatively correlated with the change in withdrawal symptom manifestations as measured by the Wisconsin Smoking Withdrawal Scale (P = 0.04) and Tobacco Craving Questionnaire (P = 0.014). These multimodal imaging-behavioral findings reveal the complex cascade of changes induced by acute nicotine deprivation and call for further investigation into the potential utility of adenosine- and glutamate-signaling as novel therapeutic targets to treat the NWS.

Transcranial Direct Current Stimulation Applied to the Dorsolateral and Ventromedial Prefrontal Cortices in Smokers Modifies Cognitive Circuits Implicated in the Nicotine Withdrawal Syndrome.

BACKGROUND: The nicotine withdrawal syndrome remains a major impediment to smoking cessation. Cognitive and affective disturbances are associated with altered connectivity within and between the executive control network, default mode network (DMN), and salience network. We hypothesized that functional activity in cognitive control networks, and downstream amygdala circuits, would be modified by application of transcranial direct current stimulation (tDCS) to the left (L) dorsolateral prefrontal cortex (dlPFC, executive control network) and right (R) ventromedial prefrontal cortex (vmPFC, DMN). METHODS: A total of 15 smokers (7 women) and 28 matched nonsmokers (14 women) participated in a randomized, sham-controlled, double-blind, exploratory crossover study of 3 tDCS conditions: anodal-(L)dlPFC/cathodal-(R)vmPFC, reversed polarity, and sham. Cognitive tasks probed withdrawal-related constructs (error monitoring, working memory, amygdalar reactivity), while simultaneous functional magnetic resonance imaging measured brain activity. We assessed tDCS impact on trait (nonsmokers vs. sated smokers) and state (sated vs. abstinent) smoking aspects. RESULTS: Single-session, anodal-(L)dlPFC/cathodal-(R)vmPFC tDCS enhanced deactivation of DMN nodes during the working memory task and strengthened anterior cingulate cortex activity during the error-monitoring task. Smokers were more responsive to tDCS-induced DMN deactivation when sated (vs. withdrawn) and displayed greater cingulate activity during error monitoring than nonsmokers. Nicotine withdrawal reduced task engagement and attention and reduced suppression of DMN nodes. CONCLUSIONS: Cognitive circuit dysregulation associated with nicotine withdrawal may be modifiable by anodal tDCS applied to L-dlPFC and cathodal tDCS applied to R-vmPFC. tDCS may have stronger effects as a complement to existing therapies, such as nicotine replacement, owing to possible enhanced plasticity in the sated state.

Triple Network Resting State Connectivity Predicts Distress Tolerance and Is Associated with Cocaine Use.

Distress tolerance (DT), a predictor of substance use treatment retention and post-treatment relapse, is associated with task based neural activation in regions located within the salience (SN), default mode (DMN), and executive control networks (ECN). The impact of network connectivity on DT has yet to be investigated. The aim of the present study was to test within and between network resting-state functional connectivity (rsFC) associations with DT, and the impact of cocaine use on this relationship. Twenty-nine adults reporting regular cocaine use (CU) and 28 matched healthy control individuals (HC), underwent resting-state functional magnetic resonance imaging followed by the completion of two counterbalanced, computerized DT tasks. Dual-regression analysis was used to derive within and between network rsFC of the SN, DMN, and lateralized (left and right) ECN. Cox proportional-hazards survival models were used to test the interactive effect of rsFC and group on DT. The association between cocaine use severity, rsFC, and DT was tested within the CU group. Lower LECN and higher DMN-SN rsFC were associated with DT impairment. Greater amount of cocaine use per using day was associated with greater DMN-SN rsFC. The findings emphasize the role of neural resource allocation within the ECN and between DMN-SN on distress tolerance.

Accelerated Intermittent Theta-Burst Stimulation as a Treatment for Cocaine Use Disorder: A Proof-of-Concept Study.

There are no effective treatments for cocaine use disorder (CUD), a chronic, relapsing brain disease characterized by dysregulated circuits related to cue reactivity, reward processing, response inhibition, and executive control. Transcranial magnetic stimulation (TMS) has the potential to modulate circuits and networks implicated in neuropsychiatric disorders, including addiction. Although acute applications of TMS have reduced craving in urine-negative cocaine users, the tolerability and safety of administering accelerated TMS to cocaine-positive individuals is unknown. As such, we performed a proof-of-concept study employing an intermittent theta-burst stimulation (iTBS) protocol in an actively cocaine-using sample. Although our main goal was to assess the tolerability and safety of administering three iTBS sessions daily, we also hypothesized that iTBS would reduce cocaine use in this non-treatment seeking cohort. We recruited 19 individuals with CUD to receive three open-label iTBS sessions per day, with approximately a 60-min interval between sessions, for 10 days over a 2-week period (30 total iTBS sessions). iTBS was delivered to left dorsolateral prefrontal cortex (dlPFC) with neuronavigation guidance. Compliance and safety were assessed throughout the trial. Cocaine use behavior was assessed before, during, and after the intervention and at 1- and 4-week follow-up visits. Of the 335 iTBS sessions applied, 73% were performed on participants with cocaine-positive urine tests. Nine of the 14 participants who initiated treatment received at least 26 of 30 iTBS sessions and returned for the 4-week follow-up visit. These individuals reduced their weekly cocaine consumption by 78% in amount of dollars spent and 70% in days of use relative to pre-iTBS cocaine use patterns. Similarly, individuals reduced their weekly consumption of nicotine, alcohol, and THC, suggesting iTBS modulated a common circuit across drugs of abuse. iTBS was well-tolerated, despite the expected occasional headaches. A single participant developed a transient neurological event of uncertain etiology on iTBS day 9 and cocaine-induced psychosis 2 weeks after discontinuation. It thus appears that accelerated iTBS to left dlPFC administered in active, chronic cocaine users is both feasible and tolerable in actively using cocaine participants with preliminary indications of efficacy in reducing both the amount and frequency of cocaine (and other off target drug) use. The neural underpinnings of these behavioral changes could help in the future development of effective treatment of CUD.

Habenular and striatal activity during performance feedback are differentially linked with state-like and trait-like aspects of tobacco use disorder.

The habenula, an epithalamic nucleus involved in reward and aversive processing, may contribute to negative reinforcement mechanisms maintaining nicotine use. We used a performance feedback task that differentially activates the striatum and habenula and administered nicotine and varenicline (versus placebos) to overnight-abstinent smokers and nonsmokers to delineate feedback-related functional brain alterations both as a function of smoking trait (smokers versus nonsmokers) and drug administration state (drug versus placebo). Smokers showed less striatal responsivity to positive feedback, an alteration not mitigated by drug administration, but rather correlated with trait-level addiction severity. Conversely, nicotine administration reduced habenula activity following both positive and negative feedback among abstinent smokers, but not nonsmokers, and increased habenula activity among smokers correlated with elevated state-level tobacco cravings. These outcomes highlight a dissociation between neurobiological processes linked with the dependence severity trait and the nicotine withdrawal state. Interventions simultaneously targeting both aspects may improve currently poor cessation outcomes.

Factors Affecting Detection Power of Blood Oxygen-Level Dependent Signal in Resting-State Functional Magnetic Resonance Imaging Using High-Resolution Echo-Planar Imaging.

Latest developments in magnetic resonance imaging (MRI) hardware and software have significantly improved image acquisition for functional MRI (fMRI) techniques, including resting-state fMRI (rsfMRI). Specifically, with improvements in gradient and radiofrequency coils and advances in pulse sequence designs, functional images with higher spatiotemporal resolution can be achieved. However, while smaller voxel size has the benefit of resolving finer brain structures, it also decreases voxel-wise signal-to-noise ratio (SNR) and, subsequently, temporal SNR (tSNR), which is critical for the sensitivity of fMRI. Although the improved temporal resolution allows more image frames to be collected per unit time, the ability to detect brain activity by using the high spatiotemporal fMRI has not been fully characterized. Here, we aimed to evaluate the effects of spatial smoothing, scan length, sample size, seed size, and location on resting-state functional connectivity (rsFC) and tSNR by using data from the human connectome project. Results from this analysis show an important effect of smoothing on the rsFC strength (correlation values between the seed and the target) as well as on the tSNR. In contrast, while rsFC strength is not affected by sample size, the standard error decreases with the increasing number of participants, therefore improving the detection power for larger samples. Scan length and seed size seem to have a moderate effect on rsFC strength. Finally, seed location has an important impact on rsFC maps, as rsFC strength from cortical seeds seems higher than from sub-cortical seeds. In summary, our findings show that the choice of parameters can be critical for an rsfMRI study.