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Cocuzza, C. V.

Publications and source records attributed to Cocuzza, C. V..

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Hierarchical and non-hierarchical network flows generate complementary representational dynamics in human visual cortex

Hierarchy is considered a fundamental organizing principle of visual cortex, but its functional implications remain debated given the presence of direct (non-hierarchical) connections. Building on recent advances in measuring direct region-to-region functional connectivity in the human brain, and in using that connectivity (rather than, e.g., visual classification training) to construct deep neural network models, we tested the hypothesis that hierarchical and direct connectivity pathways make distinct contributions to the generation of visual functionality. Detailed measurement of visual functionality, connectivity, and their interaction was achieved using 7T MRI and empirical neural network (ENN) models parameterized by empirical connectivity estimates. The classic V1 to V4 hierarchy was recovered in terms of (i) network distance from V1 along the human brains direct region-to-region resting-state functional connectome and (ii) on-task representational transformation distance (visual representation dissimilarity) from V1. In silico ENN lesion experiments revealed that hierarchical pathways (V1{leftrightarrow}V2{leftrightarrow}V3{leftrightarrow}V4) reduce the dimensionality of neural representations relative to more rapid and high-dimensional representational contributions from direct pathways (e.g., V1{leftrightarrow}V4). These findings reveal distinct but complementary roles of hierarchical and direct pathways in generating cortical functionality. Significance StatementHierarchy is a foundational organizing principle of cortex, yet its functional consequences remain unclear because of direct, non-hierarchical connections. The visual system, often portrayed as the clearest example of cortical hierarchy, provides a testbed for dissociating hierarchical and non-hierarchical contributions. Using high-resolution 7T MRI with recent advances in measuring direct region-to-region functional connectivity, we mapped the classic V1 to V4 hierarchy in the human brain. Using empirical neural network (ENN) models parameterized by these empirical connections, we determined that hierarchical pathways (V1{leftrightarrow}V2{leftrightarrow}V3{leftrightarrow}V4) reduce representational dimensionality relative to more rapid, high-dimensional contributions from direct pathways (e.g., V1{leftrightarrow}V4). These results reveal complementary hierarchical and direct contributions and establish ENN modeling as a general approach for determining pathway-specific functions throughout the brain.

neuroscience↗

Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease

The network organization of the human brain dynamically reconfigures in response to changing environmental demands, an adaptive process that may be disrupted in a symptom-relevant manner across psychiatric illnesses. Here, in a transdiagnostic sample of participants with (n=134) and without (n=85) psychiatric diagnoses, functional connectomes from intrinsic (resting-state) and task-evoked fMRI were decomposed to identify constraints on brain network dynamics across six cognitive states. Hierarchical clustering of 110 clinical, behavioral, and cognitive measures identified participant-specific symptom profiles, revealing four core dimensions of functioning: internalizing, externalizing, cognitive, and social/reward. Brain network dynamics were flattened across cognitive states in individuals with psychiatric illness and could be used to accurately separate dimensional symptom profiles more robustly than both case-control status and primary diagnostic grouping. A key role of inhibitory cognitive control and frontoparietal network interactions was uncovered through systematic model comparison. We provide novel evidence that brain network dynamics can accurately differentiate the extent that psychiatrically-relevant dimensions of functioning are exhibited across health and disease.

neuroscience↗

Shared and unique lifetime stressor characteristics and brain networks predict adolescent anxiety and depression

BackgroundExposure to major life stressors and aberrant brain functioning have been related to anxiety and depression, especially during adolescence. However, whether these associations differ based on the specific characteristics of the stressors experienced, and/or the functional networks engaged, remains unclear. MethodsWe used baseline lifetime stressor exposure and resting-state functional magnetic resonance imaging data from a longitudinal sample of 150 adolescents enriched for anxiety and depressive disorders. We examined the cumulative lifetime stressor frequency and severity of five stressor characteristics: physical danger, interpersonal loss, humiliation, entrapment, and role change/disruption. Anxiety and depression symptoms were assessed at three time points: baseline, 6-month and 12-month follow-ups. Linear mixed-effect models tested if the lifetime frequency and severity of these stressor characteristics and functional connectivity within and between frontoparietal, default, and ventral attention networks at baseline predicted anxiety and depression symptoms at three time points. ResultsLifetime frequency and severity of humiliation and entrapment predicted both anxiety and depression symptoms. Lifetime frequency and severity of entrapment exposures predicted anxiety and depression symptoms after accounting for baseline depression and anxiety symptoms, respectively. Resting-state functional connectivity between default, frontoparietal and ventral attention networks did not predict either anxiety or depression symptoms after correcting for multiple comparisons. ConclusionsOur study highlights lifetime exposures to humiliation and entrapment stressors as central stressor characteristics predictive of prospective anxiety and depression symptoms in adolescence. Our results also suggest that resting-state functional connectivity within and between default, frontoparietal and ventral attention networks may be relatively weak predictors of prospective anxiety and depression symptoms in adolescence.

neuroscience↗

A shared spatial topography links the functional connectome correlates of cocaine use disorder and dopamine D2/3 receptor densities

BackgroundThe biological mechanisms that contribute to cocaine and other substance use disorders involve an array of cortical and subcortical systems. Prior work on the development and maintenance of substance use has largely focused on cortico-striatal circuits, with relatively less attention on alterations within and across large-scale functional brain networks, and associated aspects of the dopamine system. The brain-wide pattern of temporal co-activation between distinct brain regions, referred to as the functional connectome, underpins individual differences in behavior. Critically, the functional connectome correlates of substance use and their specificity to dopamine receptor densities relative to other metabotropic receptors classes remains to be established. MethodsWe comprehensively characterized brain-wide differences in functional connectivity across multiple scales, including individual connections, regions, and networks in participants with cocaine use disorder (CUD; n=69) and healthy matched controls (n=62), Further, we studied the relationship between the observed functional connectivity signatures of CUD and the spatial distribution of a broad range of normative neurotransmitter receptor and transporter bindings as assessed through 18 different normative positron emission tomography (PET) maps. ResultsOur analyses identified a widespread profile of functional connectivity differences between individuals with CUD and matched healthy comparison participants (8.8% of total edges; 8,185 edges; pFWE=0.025). We largely find lower connectivity preferentially linking default network and subcortical regions, and higher within-network connectivity in the default network in participants with CUD. Furthermore, we find consistent and replicable associations between signatures of CUD and normative spatial density of dopamine D2/3 receptors. ConclusionsOur analyses revealed a widespread profile of altered connectivity in individuals with CUD that extends across the functional connectome and implicates multiple circuits. This profile is robustly coupled with normative dopamine D2/3 receptors densities. Underscoring the translational potential of connectomic approaches for the study of in vivo brain functions, CUD- linked aspects of brain function were spatially coupled to disorder relevant neurotransmitter systems. Key PointsO_ST_ABSQuestionC_ST_ABSAre there group differences in whole brain functional connectivity between individuals with and without cocaine use disorder, and to what extent do these connectivity patterns relate to the spatial distribution of dopamine (D2/3) receptor densities? FindingsThe presence of cocaine use disorder is associated with brain-wide functional connectivity alterations that are spatially coupled to the density of dopamine (D2/3) receptors. MeaningA preferential and replicable link exists between the functional connectome correlates of cocaine use disorder and dopamine receptor densities across the brain.

neuroscience↗

Distributed network processes account for the majority of variance in localized visual category selectivity

A central goal of neuroscience is to understand how function-relevant brain activations are generated. Here we test the hypothesis that function-relevant brain activations are generated primarily by distributed network flows. We focused on visual processing in human cortex, given the long-standing literature supporting the functional relevance of brain activations in visual cortex regions exhibiting visual category selectivity. We began by using fMRI data from N=352 human participants to identify category-specific responses in visual cortex for images of faces, places, body parts, and tools. We then systematically tested the hypothesis that distributed network flows can generate these localized visual category selective responses. This was accomplished using a recently developed approach for simulating - in a highly empirically constrained manner - the generation of task-evoked brain activations by modeling activity flowing over intrinsic brain connections. We next tested refinements to our hypothesis, focusing on how stimulus-driven network interactions initialized in V1 generate downstream visual category selectivity. We found evidence that network flows directly from V1 were sufficient for generating visual category selectivity, but that additional, globally distributed (whole-cortex) network flows increased category selectivity further. Using null network architectures we also found that each regions unique intrinsic "connectivity fingerprint" was key to the generation of category selectivity. These results generalized across regions associated with all four visual categories tested (bodies, faces, places, and tools), and provide evidence that the human brains intrinsic network organization plays a prominent role in the generation of functionally relevant, localized responses. Author SummaryA fundamental question in neuroscience has persisted for over a century: to what extent do distributed processes drive brain function? The existence of category-selective regions within visual cortex provides long-standing evidence supporting localized computations, wherein specialized functions (e.g., selective responsiveness to face images) are thought to be primarily generated by within-region processes. This account was recently updated to include category selectivity dispersed across visual cortex, in the absence of category-selective regions. Here we provide groundwork evidence demonstrating that locally-exhibited visual-category-selective responses can be accurately generated via distributed activity flowing over globally connected systems. These processes were simulated via empirically-based computational models initialized by stimulus-evoked activity patterns and empirical connectivity matching each category-selective regions unique intrinsic functional connectivity fingerprint. Results demonstrate that activity flowing over the human brains distributed network architecture can account for the generation of category selectivity in visual cortex regions.

neuroscience↗

Flexible coordinator and switcher hubs for adaptive task control

Functional connectivity studies have identified at least two large-scale neural systems that constitute cognitive control networks - the frontoparietal network (FPN) and cingulo-opercular network (CON). Control networks are thought to support goal-directed cognition and behavior. It was previously shown that the FPN flexibly shifts its global connectivity pattern according to task goal, consistent with a "flexible hub" mechanism for cognitive control. Our aim was to build on this finding to develop a functional cartography (a multi-metric profile) of control networks in terms of dynamic network properties. We quantified network properties in (male and female) humans using a high-control-demand cognitive paradigm involving switching among 64 task sets. We hypothesized that cognitive control is enacted by the FPN and CON via distinct but complementary roles reflected in network dynamics. Consistent with a flexible "coordinator" mechanism, FPN connections were varied across tasks, while maintaining within-network connectivity to aid cross-region coordination. Consistent with a flexible "switcher" mechanism, CON regions switched to other networks in a task-dependent manner, driven primarily by reduced within-network connections to other CON regions. This pattern of results suggests FPN acts as a dynamic, global coordinator of goal-relevant information, while CON transiently disbands to lend processing resources to other goal-relevant networks. This cartography of network dynamics reveals a dissociation between two prominent cognitive control networks, suggesting complementary mechanisms underlying goal-directed cognition. Significance StatementCognitive control supports a variety of behaviors requiring flexible cognition, such as rapidly switching between tasks. Furthermore, cognitive control is negatively impacted in a variety of mental illnesses. We used tools from network science to characterize the implementation of cognitive control by large-scale brain systems. This revealed that two systems - the frontoparietal (FPN) and cingulo-opercular (CON) networks - have distinct but complementary roles in controlling global network reconfigurations. The FPN exhibited properties of a flexible coordinator (orchestrating task changes), while CON acted as a flexible switcher (switching specific regions to other systems to lend processing resources). These findings reveal an underlying distinction in cognitive processes that may be applicable to clinical, educational, and machine learning work targeting cognitive flexibility.

neuroscience↗