Cocaine Use Prediction With Tensor-Based Machine Learning on Multimodal MRI Connectome Data.

This letter considers the use of machine learning algorithms for predicting cocaine use based on magnetic resonance imaging (MRI) connectomic data. The study used functional MRI (fMRI) and diffusion MRI (dMRI) data collected from 275 individuals, which was then parcellated into 246 regions of interest (ROIs) using the Brainnetome atlas. After data preprocessing, the data sets were transformed into tensor form. We developed a tensor-based unsupervised machine learning algorithm to reduce the size of the data tensor from 275 (individuals) × 2 (fMRI and dMRI) × 246 (ROIs) × 246 (ROIs) to 275 (individuals) × 2 (fMRI and dMRI) × 6 (clusters) × 6 (clusters). This was achieved by applying the high-order Lloyd algorithm to group the ROI data into six clusters. Features were extracted from the reduced tensor and combined with demographic features (age, gender, race, and HIV status). The resulting data set was used to train a Catboost model using subsampling and nested cross-validation techniques, which achieved a prediction accuracy of 0.857 for identifying cocaine users. The model was also compared with other models, and the feature importance of the model was presented. Overall, this study highlights the potential for using tensor-based machine learning algorithms to predict cocaine use based on MRI connectomic data and presents a promising approach for identifying individuals at risk of substance abuse.

Cocaine use is associated with cerebral white matter hyperintensities in HIV disease.

BACKGROUND: White matter hyperintensities (WMH), a marker of cerebral small vessel disease and predictor of cognitive decline, are observed at higher rates in persons with HIV (PWH). The use of cocaine, a potent central nervous system stimulant, is disproportionately common in PWH and may contribute to WMH. METHODS: The sample included of 110 PWH on antiretroviral therapy. Fluid-attenuated inversion recovery (FLAIR) and T1-weighted anatomical MRI scans were collected, along with neuropsychological testing. FLAIR images were processed using the Lesion Segmentation Toolbox. A hierarchical regression model was run to investigate predictors of WMH burden [block 1: demographics; block 2: cerebrovascular disease (CVD) risk; block 3: lesion burden]. RESULTS: The sample was 20% female and 79% African American with a mean age of 45.37. All participants had persistent HIV viral suppression, and the median CD4+ T-cell count was 750. Nearly a third (29%) currently used cocaine regularly, with an average of 23.75 (SD = 20.95) days in the past 90. In the hierarchical linear regression model, cocaine use was a significant predictor of WMH burden (ß = .28). WMH burden was significantly correlated with poorer cognitive function (r = -0.27). Finally, higher WMH burden was significantly associated with increased serum concentrations of interferon-γ-inducible protein 10 (IP-10) but lower concentrations of myeloperoxidase (MPO); however, these markers did not differ by COC status. CONCLUSIONS: WMH burden is associated with poorer cognitive performance in PWH. Cocaine use and CVD risk independently contribute to WMH, and addressing these conditions as part of HIV care may mitigate brain injury underlying neurocognitive impairment.

The Individualized Prediction of Neurocognitive Function in People Living with HIV Based on Clinical and Multimodal Connectome Data.

Neurocognitive impairment continues to be common comorbidity for people living with HIV (PLWH). Given the chronic nature of HIV disease, identifying reliable biomarkers of these impairments is essential to advance our understanding of the underlying neural foundation and facilitate screening and diagnosis in clinical care. While neuroimaging provides immense potential for such biomarkers, to date, investigations in PLWH have been mostly limited to either univariate mass techniques or a single neuroimaging modality. In the present study, connectome-based predictive modeling (CPM) was proposed to predict individual differences of cognitive functioning in PLWH, using resting-state functional connectivity (FC), white matter structural connectivity (SC), and clinical relevant measures. We also adopted an efficient feature selection approach to identify the most predictive features, which achieved an optimal prediction accuracy of r = 0.61 in the discovery dataset (n = 102) and r = 0.45 in an independent validation HIV cohort (n = 88). Two brain templates and nine distinct prediction models were also tested for better modeling generalizability. Results show that combining multimodal FC and SC features enabled higher prediction accuracy of cognitive scores in PLWH, while adding clinical and demographic metrics may further improve the prediction by introducing complementary information, which may help better evaluate the individual-level cognitive performance in PLWH.

Cortico-striatal networking deficits associated with advanced HIV disease and cocaine use.

Cocaine use is disproportionately prevalent in people with HIV (PWH) and is known to potentiate HIV neuropathogenesis. As both HIV and cocaine have well-documented cortico-striatal effects, PWH who use cocaine and have a history of immunosuppression may exhibit greater FC deficits compared to PWH without these conditions. However, research investigating the legacy effects of HIV immunosuppression (i.e., a history of AIDS) on cortico-striatal functional connectivity (FC) in adults with and without cocaine use is sparse. Resting-state functional magnetic resonance imaging (fMRI) and neuropsychological assessment data from 273 adults were analyzed to examine FC in relation to HIV disease: HIV-negative (n = 104), HIV-positive with nadir CD4 ≥ 200 (n = 96), HIV-positive with nadir CD4 < 200 (AIDS; n = 73), and cocaine use (83 COC and 190 NON). Using independent component analysis/dual regression, FC was assessed between the basal ganglia network (BGN) and five cortical networks: dorsal attention network (DAN), default mode network, left executive network, right executive network, and salience network. There were significant interaction effects such that AIDS-related BGN-DAN FC deficits emerged in COC but not in NON participants. Independent of HIV, cocaine effects emerged in FC between the BGN and executive networks. Disruption of BGN-DAN FC in AIDS/COC participants is consistent with cocaine potentiation of neuro-inflammation and may be indicative of legacy HIV immunosuppressive effects. The current study bolsters previous findings linking HIV and cocaine use with cortico-striatal networking deficits. Future research should consider the effects of the duration of HIV immunosuppression and early treatment initiation.

Additive cortical gray matter deficits in people living with HIV who use cocaine.

Cocaine use, which is disproportionately common in people living with HIV (PWH), is known to have neurotoxic effects that may exacerbate HIV neuropathogenesis. While both cocaine use and HIV disease are independently associated with deficits in gray matter (GM) volume, the additive effect of cocaine use to HIV disease on GM volume has not been explored. Here, we investigated subcortical and cortical brain volume differences between four groups of individuals with and without HIV disease and/or cocaine use. Participants also completed a comprehensive neuropsychological testing battery, and HIV disease characteristics were recorded. Within subcortical regions, cocaine use was independently associated with higher volume in the dorsal striatum and pallidum, while HIV disease was associated with lower volume in the nucleus accumbens and thalamus. For cortical regions, there was an additive effect of cocaine use on HIV disease in parietal and occipital lobe volume with PWH who used cocaine displaying the lowest GM volume. Within regions that differed between groups, higher neurocognitive function was positively associated with thalamic, nucleus accumbens, dorsal striatum, and occipital lobe volume. For regions that showed a significant main effect of HIV disease, lower nadir CD4 + T cell count was associated with lower nucleus accumbens and occipital lobe volume. Lower current CD4 + T cell count was associated with lower occipital lobe volume. These results suggest that PWH who use cocaine are at greater risk for cortical atrophy than cocaine use or HIV disease alone.

Neuroimaging and immunological features of neurocognitive function related to substance use in people with HIV.

This study sought to identify neuroimaging and immunological factors associated with substance use and that contribute to neurocognitive impairment (NCI) in people with HIV (PWH). We performed cross-sectional immunological phenotyping, neuroimaging, and neurocognitive testing on virally suppressed PWH in four substance groups: cocaine only users (COC), marijuana only users (MJ), dual users (Dual), and Non-users. Participants completed substance use assessments, multimodal MRI brain scan, neuropsychological testing, and blood and CSF sampling. We employed a two-stage analysis of 305 possible biomarkers of cognitive function associated with substance use. Feature reduction (Kruskal Wallis p-value < 0.05) identified 53 biomarkers associated with substance use (22 MRI and 31 immunological) for model inclusion along with clinical and demographic variables. We employed eXtreme Gradient Boosting (XGBoost) with these markers to predict cognitive function (global T-score). SHapley Additive exPlanations (SHAP) values were calculated to rank features for impact on model output and NCI. Participants were 110 PWH with sustained HIV viral suppression (33 MJ, 12 COC, 22 Dual, and 43 Non-users). The ten highest ranking biomarkers for predicting global T-score were 4 neuroimaging biomarkers including functional connectivity, gray matter volume, and white matter integrity; 5 soluble biomarkers (plasma glycine, alanine, lyso-phosphatidylcholine (lysoPC) aC17.0, hydroxy-sphingomyelin (SM.OH) C14.1, and phosphatidylcholinediacyl (PC aa) C28.1); and 1 clinical variable (nadir CD4 count). The results of our machine learning model suggest that substance use may indirectly contribute to NCI in PWH through both metabolomic and neuropathological mechanisms.

Strengthened and posterior-shifted structural rich-club organization in people who use cocaine.

BACKGROUND: People with cocaine use disorder (CUD) often have abnormal cognitive function and brain structure. Cognition is supported by brain networks that typically have characteristics like rich-club organization, which is a group of regions that are highly connected across the brain and to each other, and small worldness, which is a balance between local and long-distance connections. However, it is unknown whether there are abnormalities in structural brain network connectivity of CUD. METHODS: Using diffusion-weighted imaging, we measured structural connectivity in 37 people with CUD and 38 age-matched controls. We identified differences in rich-club organization and whether such differences related to small worldness and behavior. We also tested whether rich-club reorganization was associated with caudate and putamen structural connectivity due to the relevance of the dopamine system to cocaine use. RESULTS: People with CUD had a higher normalized rich-club coefficient than controls, more edges connecting rich-club nodes to each other and to non-rich-club nodes, and fewer edges connecting non-rich-club nodes. Rich-club nodes were shifted posterior and lateral. Rich-club reorganization was related to lower clustered connectivity around individual nodes found in CUD, to increased impulsivity, and to a decrease in caudate connectivity. CONCLUSIONS: These findings are consistent with previous work showing increased rich-club connectivity in conditions associated with a hypofunctional dopamine system. The posterior shift in rich-club nodes in CUD suggests that the structural connectivity of posterior regions may be more impacted than previously recognized in models based on brain function and morphology.

Principal component analysis denoising improves sensitivity of MR diffusion to detect white matter injury in neuroHIV.

BACKGROUND AND PURPOSE: Diffusion-weighted imaging is able to capture important information about cerebral white matter (WM) structure. However, diffusion data can suffer from MRI and biological noise that degrades the quality of the images and makes finding important features difficult. We investigated how effectively local and nonlocal denoising increased the sensitivity to detect differences in cerebral WM in neuroHIV. METHODS: We utilized principal component analysis (PCA) denoising to detect WM differences using fractional anisotropy. Local and nonlocal PCA denoising paradigms were implemented that varied in search area and number of components. We examined different-sized WM tracts that consistently show differences between people living with Human Immunodeficiency Virus (HIV) (PWH) and HIV-negative individuals (corpus callosum, forceps minor, and right uncinate fasciculus), and size-matched tracts not typically associated with HIV-related differences (spinothalamic, right medial lemniscus, and left occipitopontine). We first conducted a full sample comparison of WM differences between groups, and then randomly reduced the sample to the point where we still found differences in WM. RESULTS: Nonlocal PCA denoising allowed us to detect differences after a sample reduction of 35% in the forceps minor, 17% in the right uncinate fasciculus, and 6% in the corpus callosum. CONCLUSIONS: PCA denoising had a beneficial effect on detecting significant differences in PWH after sample size reduction. The smaller forceps minor tract and right uncinate fasciculus showed greater sensitivity to PCA denoising than the larger corpus callosum. These results show the importance of identifying the most effective PCA denoising strategy when investigating WM in PWH.

Brain multimodal co-alterations related to delay discounting: a multimodal MRI fusion analysis in persons with and without cocaine use disorder.

BACKGROUND: Delay discounting has been proposed as a behavioral marker of substance use disorders. Innovative analytic approaches that integrate information from multiple neuroimaging modalities can provide new insights into the complex effects of drug use on the brain. This study implemented a supervised multimodal fusion approach to reveal neural networks associated with delay discounting that distinguish persons with and without cocaine use disorder (CUD). METHODS: Adults with (n = 35) and without (n = 37) CUD completed a magnetic resonance imaging (MRI) scan to acquire high-resolution anatomical, resting-state functional, and diffusion-weighted images. Pre-computed features from each data modality included whole-brain voxel-wise maps for gray matter volume, fractional anisotropy, and regional homogeneity, respectively. With delay discounting as the reference, multimodal canonical component analysis plus joint independent component analysis was used to identify co-alterations in brain structure and function. RESULTS: The sample was 58% male and 78% African-American. As expected, participants with CUD had higher delay discounting compared to those without CUD. One joint component was identified that correlated with delay discounting across all modalities, involving regions in the thalamus, dorsal striatum, frontopolar cortex, occipital lobe, and corpus callosum. The components were negatively correlated with delay discounting, such that weaker loadings were associated with higher discounting. The component loadings were lower in persons with CUD, meaning the component was expressed less strongly. CONCLUSIONS: Our findings reveal structural and functional co-alterations linked to delay discounting, particularly in brain regions involved in reward salience, executive control, and visual attention and connecting white matter tracts. Importantly, these multimodal networks were weaker in persons with CUD, indicating less cognitive control that may contribute to impulsive behaviors.

Human immunodeficiency virus-related decreases in corpus callosal integrity and corresponding increases in functional connectivity.

People living with human immunodeficiency virus (PLWH) often have neurocognitive impairment. However, findings on HIV-related differences in brain network function underlying these impairments are inconsistent. One principle frequently absent from these reports is that brain function is largely emergent from brain structure. PLWH commonly have degraded white matter; we hypothesized that functional communities connected by degraded white matter tracts would show abnormal functional connectivity. We measured white matter integrity in 69 PLWH and 67 controls using fractional anisotropy (FA) in 24 intracerebral white matter tracts. Then, among tracts with degraded FA, we identified gray matter regions connected to these tracts and measured their functional connectivity during rest. Finally, we identified cognitive impairment related to these structural and functional connectivity systems. We found HIV-related decreased FA in the corpus callosum body (CCb), which coordinates activity between the left and right hemispheres, and corresponding increases in functional connectivity. Finally, we found that individuals with impaired cognitive functioning have lower CCb FA and higher CCb functional connectivity. This result clarifies the functional relevance of the corpus callosum in HIV and provides a framework in which abnormal brain function can be understood in the context of abnormal brain structure, which may both contribute to cognitive impairment.

The Acute Effects of Time-Varying Caloric Vestibular Stimulation as Assessed With fMRI.

We describe preliminary results from the application of time-varying caloric vestibular stimulation (tvCVS) to volunteers during a continuous blood oxygen level dependent (BOLD) functional MRI (fMRI) acquisition, recording baseline, during-tvCVS and post-tvCVS epochs. The modifications necessary to enable the use of this novel device in a 3-Tesla magnetic field are discussed. Independent component analysis (ICA) was used as a model-free method to highlight spatially and temporally coherent brain networks. The ICA results are consistent with tvCVS induction being mediated principally by thermoconvection in the vestibular labyrinth and not by direct thermal effects. The activation of hub networks identified by ICA is consistent with the concept of sensory neuromodulation, which posits that a modulatory signal introduced to a sensory organ is able to traverse the regions innervated (directly and indirectly) by that organ, while being transformed so as to be "matched" to regional neuronal dynamics. The data suggest that regional neurovascular coupling and a systemic cerebral blood flow component account for the BOLD contrast observed. The ability to modulate cerebral hemodynamics is of significant interest. The implications of these initial findings for the use of tvCVS therapeutically are discussed.

On the down-sampling of diffusion MRI data along the angular dimension.

BACKGROUND: It has been established that the diffusion gradient directions in diffusion MRI should be uniformly distributed in 3D spherical space, so that orientation-dependent diffusion properties (e.g., fractional anisotropy or FA) can be properly quantified. Sometimes the acquired data need to be down-sampled along the angular dimension before computing diffusion properties (e.g., to exclude data points corrupted by motion artifact; to harmonize data obtained with different protocols). It is important to quantitatively assess the impact of data down-sampling on measurement of diffusion properties. MATERIALS AND METHODS: Here we report 1) a numerical procedure for down-sampling diffusion MRI (e.g., for data harmonization), and 2) a spatial uniformity index of diffusion directions, aiming to predict the quality of the chosen down-sampling schemes (e.g., from data harmonization; or rejection of motion corrupted data points). We quantitatively evaluated human diffusion MRI data, which were down-sampled from 64 or 60 diffusion gradient directions to 30 directions, in terms of their 1) FA value accuracy (using fully-sampled data as the ground truth), 2) FA fitting residuals, and 3) spatial uniformity indices. RESULTS: Our experimental data show that the proposed spatial uniformity index is correlated with errors in FA obtained from down-sampled diffusion MRI data. The FA fitting residuals that are typically used to assess diffusion MRI quality are not correlated with either FA errors or spatial uniformity index. CONCLUSIONS: These results suggest that the spatial uniformity index could be more valuable in assessing quality of down-sampled diffusion MRI data, as compared with FA fitting residual measures. We expect that our implemented software procedure should prove valuable for 1) guiding data harmonization for multi-site diffusion MRI studies, and 2) assessing the impact of rejecting motion corrupted data points on the accuracy of diffusion measures.

Machine learning prediction of neurocognitive impairment among people with HIV using clinical and multimodal magnetic resonance imaging data.

Diagnosis of HIV-associated neurocognitive impairment (NCI) continues to be a clinical challenge. The purpose of this study was to develop a prediction model for NCI among people with HIV using clinical- and magnetic resonance imaging (MRI)-derived features. The sample included 101 adults with chronic HIV disease. NCI was determined using a standardized neuropsychological testing battery comprised of seven domains. MRI features included gray matter volume from high-resolution anatomical scans and white matter integrity from diffusion-weighted imaging. Clinical features included demographics, substance use, and routine laboratory tests. Least Absolute Shrinkage and Selection Operator Logistic regression was used to perform variable selection on MRI features. These features were subsequently used to train a support vector machine (SVM) to predict NCI. Three different classification tasks were performed: one used only clinical features; a second used only selected MRI features; a third used both clinical and selected MRI features. Model performance was evaluated by area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity with a tenfold cross-validation. The SVM classifier that combined selected MRI with clinical features outperformed the model using clinical features or MRI features alone (AUC: 0.83 vs. 0.62 vs. 0.79; accuracy: 0.80 vs. 0.65 vs. 0.72; sensitivity: 0.86 vs. 0.85 vs. 0.86; specificity: 0.71 vs. 0.37 vs. 0.52). Our results provide preliminary evidence that combining clinical and MRI features can increase accuracy in predicting NCI and could be developed as a potential tool for NCI diagnosis in HIV clinical practice.

Structural and Functional Brain Abnormalities in Human Immunodeficiency Virus Disease Revealed by Multimodal Magnetic Resonance Imaging Fusion: Association With Cognitive Function.

BACKGROUND: Human immunodeficiency virus (HIV)-associated neurocognitive impairment remains a prevalent comorbidity that impacts daily functioning and increases morbidity. While HIV infection is known to cause widespread disruptions in the brain, different magnetic resonance imaging (MRI) modalities have not been effectively integrated. In this study, we applied 3-way supervised fusion to investigate how structural and functional coalterations affect cognitive function. METHODS: Participants (59 people living with HIV and 58 without HIV) completed comprehensive neuropsychological testing and multimodal MRI scanning to acquire high-resolution anatomical, diffusion-weighted, and resting-state functional images. Preprocessed data were reduced using voxel-based morphometry, probabilistic tractography, and regional homogeneity, respectively. We applied multimodal canonical correlation analysis with reference plus joint independent component analysis using global cognitive functioning as the reference. RESULTS: Compared with controls, participants living with HIV had lower global cognitive functioning. One joint component was both group discriminating and correlated with cognitive function. This component included the following covarying regions: fractional anisotropy in the corpus callosum, short and long association fiber tracts, and corticopontine fibers; gray matter volume in the thalamus, prefrontal cortex, precuneus, posterior parietal regions, and occipital lobe; and functional connectivity in frontoparietal and visual processing regions. Component loadings for fractional anisotropy also correlated with immunosuppression. CONCLUSIONS: These results suggest that coalterations in brain structure and function can distinguish people with and without HIV and may drive cognitive impairment. As MRI becomes more commonplace in HIV care, multimodal fusion may provide neural biomarkers to support diagnosis and treatment of cognitive impairment.

Synergistic effects of HIV and marijuana use on functional brain network organization.

HIV is associated with disruptions in cognition and brain function. Marijuana use is highly prevalent in HIV but its effects on resting brain function in HIV are unknown. Brain function can be characterized by brain activity that is correlated between regions over time, called functional connectivity. Neuropsychiatric disorders are increasingly being characterized by disruptions in such connectivity. We examined the synergistic effects of HIV and marijuana use on functional whole-brain network organization during resting state. Our sample included 78 adults who differed on HIV and marijuana status (19 with co-occurring HIV and marijuana use, 20 HIV-only, 17 marijuana-only, and 22 controls). We examined differences in local and long-range brain network organization using eight graph theoretical metrics: transitivity, local efficiency, within-module degree, modularity, global efficiency, strength, betweenness, and participation coefficient. Local and long-range connectivity were similar between the co-occurring HIV and marijuana use and control groups. In contrast, the HIV-only and marijuana-only groups were both associated with disruptions in brain network organization. These results suggest that marijuana use in HIV may normalize disruptions in brain network organization observed in persons with HIV. However, future work is needed to determine whether this normalization is suggestive of a beneficial or detrimental effect of marijuana on cognitive functioning in HIV.

Neural sensitivity to risk in adults with co-occurring HIV infection and cocaine use disorder.

Persons with co-occurring HIV infection and cocaine use disorder tend to engage in riskier decision-making. However, the neural correlates of sensitivity to risk are not well-characterized in this population. The purpose of this study was to examine the neural interaction effects of HIV infection and cocaine use disorder to sensitivity to risk. The sample included 79 adults who differed on HIV status and cocaine use disorder. During functional magnetic resonance imaging (fMRI), participants completed a Wheel of Fortune (WoF) task that assessed neural activation in response to variations of monetary risk (i.e., lower probability of winning a larger reward). Across groups, neural activation to increasing risk was in cortical and subcortical regions similar to previous investigations using the WoF in nondrug-using populations. Our analyses showed that there was a synergistic effect between HIV infection and cocaine use in the left precuneus/posterior cingulate cortex and hippocampus, and right postcentral gyrus, lateral occipital cortex, cerebellum, and posterior parietal cortex. HIV+ individuals with cocaine use disorder displayed neural hyperactivation to increasing risk that was not observed in the other groups. These results support a synergistic effect of co-occurring HIV infection and cocaine dependence in neural processing of risk probability that may reflect compensation. Future studies can further investigate and validate how neural activation to increasing risk is associated with risk-taking behavior.

Reciprocal Influences of HIV and Cannabinoids on the Brain and Cognitive Function.

Globally, cannabis is the most commonly used illicit drug, with disproportionately high use among persons with HIV. Despite advances in HIV care, nearly half of persons living with HIV continue to experience neurocognitive deficits or impairments that may have negative impacts on their daily function. Chronic cannabis use may play a role in the development or exacerbation of these impairments. Here we present a review summarizing existing research detailing the effect of cannabis use associated with the neuropathogenesis of HIV. We examine evidence for possible additive or synergistic effects of HIV infection and cannabis use on neuroHIV in both the preclinical and adult human literatures, including in vitro studies, animal models, clinical neuroimaging research, and studies examining the cognitive effects of cannabis. We discuss the limitations of existing research, including methodological challenges involved with clinical research with human subjects. We identify gaps in the field and propose critical research questions to advance our understanding of how cannabis use affects neuroHIV. Graphical Abstract.

Cocaine-related alterations in fronto-parietal gray matter volume correlate with trait and behavioral impulsivity.

BACKGROUND: Chronic cocaine use is associated with structural brain abnormalities within prefrontal regions implicated in impulsivity. Despite high levels of impulsivity among persons who use cocaine, it is not known how reductions in gray matter volume (GMV) may relate to trait and behavioral measures of impulsivity. METHODS: The sample included 39 active cocaine users (COC+) and 40 controls with no history of cocaine use (COC-). Participants had a brain scan on a 3 T MRI machine and completed out-of-scanner measures of trait impulsivity and delayed reward discounting. Whole-brain voxel-based morphometry was used to compare GMV between COC+ and COC-. Within regions that differed between groups, voxelwise correlations were conducted to examine the relationship between GMV and impulsivity. RESULTS: In a whole-brain analysis, COC+ had broad reductions in GMV compared to COC- in bilateral frontal, parietal, occipital, and cerebellar regions. Lower GMV correlated with trait impulsivity in lateral prefrontal regions and with delayed reward discounting in medial prefrontal regions, while lower GMV correlated with both measures in the posterior parietal cortex. COC+ demonstrated significantly higher impulsivity than COC- on all measures, but the nature of the correlation with GMV was similar in both groups. CONCLUSIONS: Reflecting the multi-faceted nature of impulsivity, these results show that trait and behavioral measures of impulsivity map differentially onto altered brain morphology. While the brain-behavior patterns were similar in COC+ and COC-, suggesting that impulsivity varies on a continuous spectrum, cocaine-related abnormalities in frontal-parietal brain systems may contribute to heightened impulsivity.

Neural reward response to substance-free activity images in opiate use disorder patients with depressive symptoms.

BACKGROUND: Deficits in the ability to experience reward from natural, substance-free activities and stimuli is a common mechanism contributing to both opiate use disorder and depressive symptoms, and is a target of behavioral-focused treatments for substance use and depression. Although the neural response to monetary, positive affect-eliciting and social images has been investigated, the neural response to images representing substance-free activity engagement remains untested. The current study tested the neural response to anticipation and receipt of substance-free activity engagement images and monetary reward in opiate use disorder patients with elevated depressive symptoms compared to healthy controls. METHODS: Sixteen male opiate use disorder detoxification patients with elevated depressive symptoms (Beck Depression Inventory (BDI-II) ≥ 14) (OUDD Mage = 32.19 years, SD = 8.17 years) and seventeen male healthy controls (BDI-II < 14) (HC: Mage = 26.82 years, SD = 5.29 years) completed the Monetary Incentive Delay (MID) and newly developed Activity Incentive Delay (AID) tasks. Within- and between-group whole-brain contrasts tested activation during anticipation ([reward]-[non-reward]) and receipt ([win]-[non-win]) of substance-free activity image, monetary, and substance-free activity relative to monetary (AID-MID), reward. RESULTS: OUDD demonstrated significantly lower activation in reward regions during anticipation and significantly greater activation during receipt of substance-free activity image reward compared to HC. OUDD demonstrated significantly lower activation during anticipation of substance-free activity reward relative to monetary reward, compared to HC. CONCLUSIONS: The observed reduction in frontostriatal response to reward anticipation of substance-free activity engagement images in OUDD, yet increased neural response to reward receipt, supports theory linking reductions in reward processing with deficits in motivation for substance-free activity engagement.

Synergistic effects of marijuana abuse and HIV infection on neural activation during a cognitive interference task.

Marijuana use, which is disproportionately prevalent among human immunodeficiency virus (HIV)-infected persons, can alter activity in fronto-parietal regions during cognitively demanding tasks. While HIV is also associated with altered neural activation, it is not known how marijuana may further affect brain function in this population. Our study examined the independent and additive effects of HIV infection and regular marijuana use on neural activation during a cognitive interference task. The sample included 93 adults who differed on marijuana (MJ) and HIV statuses (20 MJ+/HIV+, 19 MJ+/HIV-, 29 MJ-/HIV+, 25 MJ-/HIV-). Participants completed a counting Stroop task during a functional magnetic resonance imaging scan. Main and interactive effects on neural activation during interference versus neutral blocks were examined using a mixed-effects analysis. The sample showed the expected Stroop effect for both speed and accuracy. There were main effects of MJ in the right and left inferior parietal lobules, with the left cluster extending into the posterior middle temporal gyrus and a main effect of HIV in the dorsal anterior cingulate cortex. There was an interaction in the left fronto-insular cortex, such that the MJ+/HIV+ group had the largest increase in activation compared with other groups. Among MJ+, signal change in this cluster correlated positively with cumulative years of regular marijuana use. These results suggest that comorbid HIV and marijuana use is associated with complex neural alterations in multiple brain regions during cognitive interference. Follow-up research is needed to determine how marijuana-related characteristics may moderate HIV neurologic disease and impact real-world functioning.