Publications by authors named "Sidhant Chopra"

Behavioral change studies mostly focus on external reinforcements to modify preferences. Cue-approach training (CAT) is a paradigm that influences preferences by the mere association of stimuli, sensory cues, and a rapid motor response, without external reinforcements. The behavioral effect has been shown to last for months after less than one hour of training.

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Resting-state functional connectivity (RSFC) is widely used to predict phenotypic traits in individuals. Large sample sizes can significantly improve prediction accuracies. However, for studies of certain clinical populations or focused neuroscience inquiries, small-scale datasets often remain a necessity.

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A pervasive dilemma in brain-wide association studies (BWAS) is whether to prioritize functional magnetic resonance imaging (fMRI) scan time or sample size. We derive a theoretical model showing that individual-level phenotypic prediction accuracy increases with sample size and total scan duration (sample size × scan time per participant). The model explains empirical prediction accuracies well across 76 phenotypes from nine resting-fMRI and task-fMRI datasets (R = 0.

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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.

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An important aim in psychiatry is to establish valid and reliable associations linking profiles of brain functioning to clinically relevant symptoms and behaviors across patient populations. To advance progress in this area, we introduce an open dataset containing behavioral and neuroimaging data from 241 individuals aged 18 to 70, comprising 148 individuals meeting diagnostic criteria for a broad range of psychiatric illnesses and a healthy comparison group of 93 individuals. These data include high-resolution anatomical scans, multiple resting-state, and task-based functional MRI runs.

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Background: Interindividual variability in the neurobiological and clinical characteristics of mental illnesses are often overlooked by classical group-mean case-control studies. Studies using normative modeling to infer person-specific deviations of gray matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear.

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Converging neuroimaging, genetic, and post-mortem evidence show a fundamental role of synaptic deficits in schizophrenia pathogenesis. However, the underlying molecular and cellular mechanisms that drive the onset and progression of synaptic pathology remain to be established. Here, we used synaptic density positron emission tomography (PET) imaging using the [C]UCB-J radiotracer to reveal a prominent widespread pattern ( < 0.

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The experience of human parenthood is near ubiquitous and can profoundly alter one's body, mind, and environment. However, we know very little about the long-term neural effects of parenthood for parents themselves, or the implications of pregnancy and caregiving experience on the aging adult brain. Here, we investigate the link between the number of children parented and age on brain function in 19,964 females and 17,607 males from the UK Biobank.

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The past decade witnessed substantial discoveries related to the psychosis spectrum. Many of these discoveries resulted from pursuits of objective and quantifiable biomarkers in tandem with the application of analytical tools such as machine learning. These approaches provided exciting new insights that significantly helped improve precision in diagnosis, prognosis, and treatment.

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The functional properties of the human brain arise, in part, from the vast assortment of cell types that pattern the cerebral cortex. The cortical sheet can be broadly divided into distinct networks, which are embedded into processing streams, or gradients, that extend from unimodal systems through higher-order association territories. Here using microarray data from the Allen Human Brain Atlas and single-nucleus RNA-sequencing data from multiple cortical territories, we demonstrate that cell-type distributions are spatially coupled to the functional organization of cortex, as estimated through functional magnetic resonance imaging.

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Article Synopsis
  • The goal of computational psychiatry is to create models that connect differences in brain function to cognitive impairments and symptoms, which are often resistant to treatment.* -
  • Research shows that to predict cognitive functioning accurately, large participant samples are needed, highlighting limitations in smaller patient studies.* -
  • Using a transfer learning approach on neuroimaging data from the UK Biobank, the study found that predictions of cognitive functioning improved significantly, even with smaller sample sizes, validating the effectiveness of training models on larger datasets.*
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Background: Exposure to major life stressors and aberrant functional connectivity have been linked to anxiety and depression, especially during adolescence. However, whether specific characteristics of life stressors and functional network connectivity act together to differentially predict anxiety and depression symptoms remains unclear.

Methods: We utilized baseline lifetime stressor exposure and resting-state functional magnetic resonance imaging data in a longitudinal sample of 107 adolescents enriched for anxiety and depressive disorders.

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Background: Aging is a multilevel process of gradual decline that predicts morbidity and mortality. Independent investigations have implicated senescence of brain and peripheral physiology in psychiatric risk, but it is unclear whether these effects stem from unique or shared mechanisms.

Methods: To address this question, we analyzed clinical, blood chemistry, and resting-state functional neuroimaging data in a healthy aging cohort (n = 427; ages 36-100 years) and 2 disorder-specific samples including patients with early psychosis (100 patients, 16-35 years) and major depressive disorder (MDD) (104 patients, 20-76 years).

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Article Synopsis
  • - The study investigates how brain mechanisms related to cocaine use disorder involve both cortical and subcortical systems, emphasizing the importance of large-scale functional brain networks and the dopamine system.
  • - Previous research predominantly focused on cortico-striatal circuits, but this study shifts attention to how functional connectivity patterns are associated with neurotransmitter receptor densities in cocaine users.
  • - Findings reveal that specific patterns of connectivity in the brains of individuals with cocaine use disorder correspond with the spatial densities of dopamine D receptors, suggesting that these receptor distributions may influence brain connectivity associated with substance use.
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Background: Inter-individual variability in neurobiological and clinical characteristics in mental illness is often overlooked by classical group-mean case-control studies. Studies using normative modelling to infer person-specific deviations of grey matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear.

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Background: Disruptions of axonal connectivity are thought to be a core pathophysiological feature of psychotic illness, but whether they are present early in the illness, prior to antipsychotic exposure, and whether they can predict clinical outcome remain unknown.

Methods: We acquired diffusion-weighted magnetic resonance images to map structural connectivity between each pair of 319 parcellated brain regions in 61 antipsychotic-naïve individuals with first-episode psychosis (15-25 years, 46% female) and a demographically matched sample of 27 control participants. Clinical follow-up data were also acquired in patients 3 and 12 months after the scan.

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Article Synopsis
  • The study aims to connect brain functioning profiles with symptoms and behaviors in psychiatric patients by introducing a new dataset.
  • This dataset includes brain imaging and behavioral data from 241 individuals, with a mix of 148 people diagnosed with psychiatric illnesses and a healthy group of 93.
  • It provides a comprehensive resource including high-resolution scans, fMRI data, and over 50 psychological assessments to facilitate research in neuroscience.
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The experience of parenthood can profoundly alter one's body, mind, and environment, yet we know little about the long-term associations between parenthood and brain function and aging in adulthood. Here, we investigate the link between number of children parented (parity) and age on brain function in 19,964 females and 17,607 males from the UK Biobank. In both females and males, increased parity was positively associated with functional connectivity, particularly within the somato/motor network.

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Psychotic-like experiences (PLEs) include a range of sub-threshold symptoms that resemble aspects of psychosis but do not necessarily indicate the presence of psychiatric illness. These experiences are highly prevalent in youth and are associated with developmental disruptions across social, academic, and emotional domains. While not all youth who report PLEs develop psychosis, many develop other psychiatric illnesses during adolescence and adulthood.

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Article Synopsis
  • - The study examines the balance between sample size and scan time in neuroimaging, particularly in brain-wide association studies (BWAS) using fMRI, and finds that total scan duration significantly affects prediction accuracy, suggesting they can be interchangeable up to 20-30 minutes.
  • - As scan time increases, its relative benefits diminish compared to sample size, indicating that longer scan times should be considered, especially when accounting for participant-related costs like recruitment and non-imaging measures.
  • - The research highlights that conventional methods prioritize sample size over scan time, potentially leading to poorer prediction accuracies; thus, it provides recommendations for optimizing future study designs to make better resource use.
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Psychosis has often been linked to abnormal cortical asymmetry, but prior results have been inconsistent. Here, we applied a novel spectral shape analysis to characterize cortical shape asymmetries in patients with early psychosis across different spatial scales. We used the Human Connectome Project for Early Psychosis dataset (aged 16-35), comprising 56 healthy controls (37 males, 19 females) and 112 patients with early psychosis (68 males, 44 females).

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Functional magnetic resonance imaging (fMRI) is widely used to investigate functional coupling (FC) disturbances in a range of clinical disorders. Most analyses performed to date have used group-based parcellations for defining regions of interest (ROIs), in which a single parcellation is applied to each brain. This approach neglects individual differences in brain functional organization and may inaccurately delineate the true borders of functional regions.

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Resting-state functional connectivity (RSFC) is widely used to predict phenotypic traits in individuals. Large sample sizes can significantly improve prediction accuracies. However, for studies of certain clinical populations or focused neuroscience inquiries, small-scale datasets often remain a necessity.

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