Methods for decoding cortical gradients of functional connectivity.

Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques. However, additional methodological development is necessary to fully leverage available meta-analytic methods and resources and quantitatively evaluate their relative performance. Here, we conducted a comprehensive series of analyses to investigate and improve the framework of data-driven, meta-analytic methods, thereby establishing a principled approach for gradient segmentation and functional decoding. We found that a two-segment solution determined by a k-means segmentation approach and an LDA-based meta-analysis combined with the NeuroQuery database was the optimal combination of methods for decoding functional connectivity gradients. Finally, we proposed a method for decoding additional components of the gradient decomposition. The current work aims to provide recommendations on best practices and flexible methods for gradient-based functional decoding of fMRI data.

Extended functional connectivity of convergent structural alterations among individuals with PTSD: a neuroimaging meta-analysis.

BACKGROUND: Post-traumatic stress disorder (PTSD) is a debilitating disorder defined by the onset of intrusive, avoidant, negative cognitive or affective, and/or hyperarousal symptoms after witnessing or experiencing a traumatic event. Previous voxel-based morphometry studies have provided insight into structural brain alterations associated with PTSD with notable heterogeneity across these studies. Furthermore, how structural alterations may be associated with brain function, as measured by task-free and task-based functional connectivity, remains to be elucidated. METHODS: Using emergent meta-analytic techniques, we sought to first identify a consensus of structural alterations in PTSD using the anatomical likelihood estimation (ALE) approach. Next, we generated functional profiles of identified convergent structural regions utilizing resting-state functional connectivity (rsFC) and meta-analytic co-activation modeling (MACM) methods. Finally, we performed functional decoding to examine mental functions associated with our ALE, rsFC, and MACM brain characterizations. RESULTS: We observed convergent structural alterations in a single region located in the medial prefrontal cortex. The resultant rsFC and MACM maps identified functional connectivity across a widespread, whole-brain network that included frontoparietal and limbic regions. Functional decoding revealed overlapping associations with attention, memory, and emotion processes. CONCLUSIONS: Consensus-based functional connectivity was observed in regions of the default mode, salience, and central executive networks, which play a role in the tripartite model of psychopathology. Taken together, these findings have important implications for understanding the neurobiological mechanisms associated with PTSD.

Convergent gray matter alterations across drugs of abuse and network-level implications: A meta-analysis of structural MRI studies.

BACKGROUND: Neuroimaging studies often consider brain alterations linked with substance abuse within the context of individual drugs (e.g., nicotine), while neurobiological theories of addiction emphasize common brain network-level alterations across drug classes. Using emergent meta-analytic techniques, we identified common structural brain alterations across drugs and characterized the functionally-connected networks with which such structurally altered regions interact. METHODS: We identified 82 articles characterizing gray matter (GM) volume differences for substance users vs. controls. Using the anatomical likelihood estimation algorithm, we identified convergent GM reductions across drug classes. Next, we performed resting-state and meta-analytic functional connectivity analyses using each structurally altered region as a seed and computed whole-brain functional connectivity profiles as the union of both maps. We characterized an "extended network" by identifying brain areas demonstrating the highest degree of functional coupling with structurally impacted regions. Finally, hierarchical clustering was performed leveraging extended network nodes' functional connectivity profiles to delineate subnetworks. RESULTS: Across drug classes, we identified medial frontal/ventromedial prefrontal, and multiple regions in anterior cingulate (ACC) and insula as regions displaying convergent GM reductions among users. Overlap of these regions' functional connectivity profiles identified ACC, inferior frontal, PCC, insula, superior temporal, and putamen as regions of an impacted extended network. Hierarchical clustering revealed 3 subnetworks closely corresponding to default mode (PCC, angular), salience (dACC, caudate), and executive control networks (dlPFC and parietal). CONCLUSIONS: These outcomes suggest that substance-related structural brain alterations likely have implications for the functioning of canonical large-scale networks and the perpetuation of substance use and neurocognitive alterations.

The association of amygdala-insula functional connectivity and adolescent e-cigarette use via sleep problems and depressive symptoms.

BACKGROUND: Adolescent electronic cigarette (e-cigarette) use remains high. Elucidating contributing factors may enhance prevention strategies. Neurobiologically, amygdala-insula resting-state functional connectivity (rsFC) has been linked with aspects of sleep, affect, and substance use (SU). As such, we hypothesized that amygdala's rsFC with the insula would be associated with e-cigarette use via sleep problems and/or depression levels. METHODS: An adolescent sample (N = 146) completed a rs-fMRI scan at time 1 and self-reports at time 2 (∼15 months later). Given consistent associations between mental health outcomes and the rsFC of the laterobasal amygdala (lbAMY) with the anterior insula, we utilized a seed region (lbAMY) to region of interest (ROI) analysis approach to characterize brain-behavior relationships. Two serial mediation models tested the interrelations between amygdala's rsFC with distinct anterior insula subregions (i.e., ventral insula [vI], dorsal insula [dI]), sleep problems, depression levels, and days of e-cigarette use. RESULTS: An indirect effect was observed when considering the lbAMY's rsFC with the vI. Greater rsFC predicted more sleep problems, more sleep problems were linked with greater depressive symptoms, and greater depressive symptoms were associated with more e-cigarette use (indirect effect = 0.08, CI [0.01,0.21]). Indicative of a neurobiological dissociation, a similar indirect effect linking these variables was not observed when considering the lbAMY's rsFC with the dI (indirect effect = 0.03, CI [-0.001,0.10]). CONCLUSIONS: These outcomes highlight functional interactions between the amygdala and insula as a neurobiological contributor to sleep problems, depressive symptoms, and ultimately SU thereby suggesting potential intervention points to reduce teen e-cigarette use.

Risky decision-making strategies mediate the relationship between amygdala activity and real-world financial savings among individuals from lower income households: A pilot study.

Lower financial savings among individuals experiencing adverse social determinants of health (SDoH) increases vulnerabilities during times of crisis. SDoH including low socioeconomic status (low-SES) influence cognitive abilities as well as health and life outcomes that may perpetuate poverty and disparities. Despite evidence suggesting a role for financial growth in minimizing SDoH-related disparities and vulnerabilities, neurobiological mechanisms linked with financial behavior remain to be elucidated. As such, we examined the relationships between brain activity during decision-making (DM), laboratory-based task performance, and money savings behavior. Participants (N = 24, 14 females) from low-SES households (income<$20,000/year) underwent fMRI scanning while performing the Balloon Analogue Risk Task (BART), a DM paradigm probing risky- and strategic-DM processes. Participants also completed self-report instruments characterizing relevant personality characteristics and then engaged in a community outreach financial program where amount of money saved was tracked over a 6-month period. Regarding BART-related brain activity, we observed expected activity in regions implicated in reward and emotional processing including the amygdala. Regarding brain-behavior relationships, we found that laboratory-based BART performance mediated the impact of amygdala activity on real-world behavior. That is, elevated amygdala activity was linked with BART strategic-DM which, in turn, was linked with more money saved after 6 months. In exploratory analyses, this mediation was moderated by emotion-related personality characteristics such that, only individuals reporting lower alexithymia demonstrated a relationship between amygdala activity and savings. These outcomes suggest that DM-related amygdala activity and/or emotion-related personality characteristics may provide utility as an endophenotypic marker of individual's financial savings behavior.

Interactive Effects of HIV Infection and Cannabis Use on Insula Subregion Functional Connectivity.

Chronic inflammation in the central nervous system is one mechanism through which human immunodeficiency virus (HIV) may lead to progressive cognitive decline. Given cannabis's (CB's) anti-inflammatory properties, use prevalence among people living with HIV (PLWH), and evidence implicating the insula in both, we examined independent and interactive effects of HIV and CB on insular circuitry, cognition, and immune function. We assessed resting-state functional connectivity (rsFC) of three insula subregions among 106 participants across four groups (co-occurring: HIV+/CB+; HIV-only: HIV+/CB-; CB-only: HIV-/CB+; controls: HIV-/CB-). Participants completed a neurocognitive battery assessing functioning across multiple domains and self-reported somatic complaints. Blood samples quantified immune function (T-cell counts) and inflammation (tumor necrosis factor alpha [TNF-α]). We observed interactive HIV × CB effects on rsFC strength between two anterior insula (aI) subregions and sensorimotor cortices such that, CB appeared to normalize altered rsFC among non-using PLWH. Specifically, compared to controls, HIV-only and CB-only groups displayed decreased dorsal anterior insula (DI) - postcentral gyrus rsFC and increased ventral anterior insula (VI) - supplementary motor area rsFC, whereas the co-occurring group displayed DI and VI rsFC more akin to that of controls. Altered DI - postcentral rsFC correlated with decreased processing speed and somatic complaints, but did not significantly correlate with inflammation (TNF-α). These outcomes implicate insula - sensorimotor neurocircuitries in HIV and CB and are consistent with prior work suggesting that CB use may normalize insula functioning among PLWH.

Altered large-scale brain network interactions associated with HIV infection and error processing.

Altered activity within and between large-scale brain networks has been implicated across various neuropsychiatric conditions. However, patterns of network dysregulation associated with human immunodeficiency virus (HIV), and further impacted by cannabis (CB) use, remain to be delineated. We examined the impact of HIV and CB on resting-state functional connectivity (rsFC) between brain networks and associations with error awareness and error-related network responsivity. Participants (N = 106), stratified into four groups (HIV+/CB+, HIV+/CB-, HIV-/CB+, HIV-/CB-), underwent fMRI scanning while completing a resting-state scan and a modified Go/NoGo paradigm assessing brain responsivity to errors and explicit error awareness. We examined separate and interactive effects of HIV and CB on resource allocation indexes (RAIs), a measure quantifying rsFC strength between the default mode network (DMN), central executive network (CEN), and salience network (SN). We observed reduced RAIs among HIV+ (vs. HIV-) participants, which was driven by increased SN-DMN rsFC. No group differences were detected for SN-CEN rsFC. Increased SN-DMN rsFC correlated with diminished error awareness, but not with error-related network responsivity. These outcomes highlight altered network interactions among participants with HIV and suggest such rsFC dysregulation may persist during task performance, reflecting an inability to disengage irrelevant mental operations, ultimately hindering error processing.

The cue-reactivity paradigm: An ensemble of networks driving attention and cognition when viewing drug and natural reward-related stimuli.

The cue-reactivity paradigm is a widely adopted neuroimaging probe engendering brain activity linked with attentional, affective, and reward processes following presentation of appetitive stimuli. Given the multiple mental operations invoked, we sought to decompose cue-related brain activity into constituent components employing emergent meta-analytic techniques when considering drug and natural reward-related cues. We conducted coordinate-based meta-analyses delineating common and distinct brain activity convergence across cue-reactivity studies (N = 196 articles) involving drug (n = 133) or natural (n = 63) visual stimuli. Across all studies, convergence was observed in limbic, cingulate, insula, and fronto-parieto-occipital regions. Drug-distinct convergence was observed in posterior cingulate, dorsolateral prefrontal, and temporo-parietal regions, whereas distinct-natural convergence was observed in thalamic, insular, orbitofrontal, and occipital regions. We characterized connectivity profiles of identified regions by leveraging task-independent and task-dependent MRI datasets, grouped these profiles into subnetworks, and linked each with putative mental operations. Outcomes suggest multifaceted brain activity during cue-reactivity can be decomposed into elemental processes and indicate that while drugs of abuse usurp the brain's natural-reward-processing system, some regions appear distinct to drug cue-reactivity.

Common and distinct brain activity associated with risky and ambiguous decision-making.

Two often-studied forms of uncertain decision-making (DM) are risky-DM (outcome probabilities known) and ambiguous-DM (outcome probabilities unknown). While DM in general is associated with activation of several brain regions, previous neuroimaging efforts suggest a dissociation between activity linked with risky and ambiguous choices. However, the common and distinct neurobiological correlates associated with risky- and ambiguous-DM, as well as their specificity when compared to perceptual-DM (as a 'control condition'), remains to be clarified. We conducted multiple meta-analyses on neuroimaging results from 151 studies to characterize common and domain-specific brain activity during risky-, ambiguous-, and perceptual-DM. When considering all DM tasks, convergent activity was observed in brain regions considered to be consituents of the canonical salience, valuation, and executive control networks. When considering subgroups of studies, risky-DM (vs. perceptual-DM) was linked with convergent activity in the striatum and anterior cingulate cortex (ACC), regions associated with reward-related processes (determined by objective functional decoding). When considering ambiguous-DM (vs. perceptual-DM), activity convergence was observed in the lateral prefrontal cortex and insula, regions implicated in affectively-neutral mental processes (e.g., cognitive control and behavioral responding; determined by functional decoding). An exploratory meta-analysis comparing brain activity between substance users and non-users during risky-DM identified reduced convergent activity among users in the striatum, cingulate, and thalamus. Taken together, these findings suggest a dissociation of brain regions linked with risky- and ambiguous-DM reflecting possible differential functionality and highlight brain alterations potentially contributing to poor decision-making in the context of substance use disorders.

Meta-analytic clustering dissociates brain activity and behavior profiles across reward processing paradigms.

Reward learning is a ubiquitous cognitive mechanism guiding adaptive choices and behaviors, and when impaired, can lead to considerable mental health consequences. Reward-related functional neuroimaging studies have begun to implicate networks of brain regions essential for processing various peripheral influences (e.g., risk, subjective preference, delay, social context) involved in the multifaceted reward processing construct. To provide a more complete neurocognitive perspective on reward processing that synthesizes findings across the literature while also appreciating these peripheral influences, we used emerging meta-analytic techniques to elucidate brain regions, and in turn networks, consistently engaged in distinct aspects of reward processing. Using a data-driven, meta-analytic, k-means clustering approach, we dissociated seven meta-analytic groupings (MAGs) of neuroimaging results (i.e., brain activity maps) from 749 experimental contrasts across 176 reward processing studies involving 13,358 healthy participants. We then performed an exploratory functional decoding approach to gain insight into the putative functions associated with each MAG. We identified a seven-MAG clustering solution that represented dissociable patterns of convergent brain activity across reward processing tasks. Additionally, our functional decoding analyses revealed that each of these MAGs mapped onto discrete behavior profiles that suggested specialized roles in predicting value (MAG-1 & MAG-2) and processing a variety of emotional (MAG-3), external (MAG-4 & MAG-5), and internal (MAG-6 & MAG-7) influences across reward processing paradigms. These findings support and extend aspects of well-accepted reward learning theories and highlight large-scale brain network activity associated with distinct aspects of reward processing.