Chandra Sekhar Sripada

University of Michigan, Ann Arbor, Michigan, United States

Are you Chandra Sekhar Sripada?

Claim your profile

Publications (41)189.87 Total impact

  • Chandra S Sripada, Daniel Kessler, Mike Angstadt
    [Show abstract] [Hide abstract]
    ABSTRACT: Attention-deficit/hyperactivity disorder (ADHD) is among the most common psychiatric disorders of childhood, and there is great interest in understanding its neurobiological basis. A prominent neurodevelopmental hypothesis proposes that ADHD involves a lag in brain maturation. Previous work has found support for this hypothesis, but examinations have been limited to structural features of the brain (e.g., gray matter volume or cortical thickness). More recently, a growing body of work demonstrates that the brain is functionally organized into a number of large-scale networks, and the connections within and between these networks exhibit characteristic patterns of maturation. In this study, we investigated whether individuals with ADHD (age 7.2-21.8 y) exhibit a lag in maturation of the brain's developing functional architecture. Using connectomic methods applied to a large, multisite dataset of resting state scans, we quantified the effect of maturation and the effect of ADHD at more than 400,000 connections throughout the cortex. We found significant and specific maturational lag in connections within default mode network (DMN) and in DMN interconnections with two task positive networks (TPNs): frontoparietal network and ventral attention network. In particular, lag was observed within the midline core of the DMN, as well as in DMN connections with right lateralized prefrontal regions (in frontoparietal network) and anterior insula (in ventral attention network). Current models of the pathophysiology of attention dysfunction in ADHD emphasize altered DMN-TPN interactions. Our finding of maturational lag specifically in connections within and between these networks suggests a developmental etiology for the deficits proposed in these models.
    Proceedings of the National Academy of Sciences of the United States of America. 09/2014;
  • Chandra Sripada, Daniel Kessler, John Jonides
    [Show abstract] [Hide abstract]
    ABSTRACT: A recent wave of studies-more than 100 conducted over the last decade-has shown that exerting effort at controlling impulses or behavioral tendencies leaves a person depleted and less able to engage in subsequent rounds of regulation. Regulatory depletion is thought to play an important role in everyday problems (e.g., excessive spending, overeating) as well as psychiatric conditions, but its neurophysiological basis is poorly understood. Using a placebo-controlled, double-blind design, we demonstrated that the psychostimulant methylphenidate (commonly known as Ritalin), a catecholamine reuptake blocker that increases dopamine and norepinephrine at the synaptic cleft, fully blocks effort-induced depletion of regulatory control. Spectral analysis of trial-by-trial reaction times revealed specificity of methylphenidate effects on regulatory depletion in the slow-4 frequency band. This band is associated with the operation of resting-state brain networks that produce mind wandering, which raises potential connections between our results and recent brain-network-based models of control over attention.
    Psychological Science 04/2014; · 4.43 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The Selfish Goal model challenges traditional agentic models that place conscious systems at the helm of motivation. We highlight the need for ongoing supervision and intervention of automatic goals by higher-order conscious systems with examples from social cognitive affective neuroscience. We contend that interplay between automatic and supervisory systems is required for adaptive human behavior.
    Behavioral and Brain Sciences 04/2014; 37(2):156-7. · 18.57 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to strong interest in using neuroimaging methods to accurately predict disorder status. In this work, we are specifically interested in a multivariate approach that uses features derived from whole-brain resting state functional connectomes. However, functional connectomes reside in a high dimensional space, which complicates model interpretation and introduces numerous statistical and computational challenges. Traditional feature selection techniques are used to reduce data dimensionality, but are blind to the spatial structure of the connectomes. We propose a regularization framework where the 6-D structure of the functional connectome (defined by pairs of points in 3-D space) is explicitly taken into account via the fused Lasso or the GraphNet regularizer. Our method only restricts the loss function to be convex and margin-based, allowing non-differentiable loss functions such as the hinge-loss to be used. Using the fused Lasso or GraphNet regularizer with the hinge-loss leads to a structured sparse support vector machine (SVM) with embedded feature selection. We introduce a novel efficient optimization algorithm based on the augmented Lagrangian and the classical alternating direction method, which can solve both fused Lasso and GraphNet regularized SVM with very little modification. We also demonstrate that the inner subproblems of the algorithm can be solved efficiently in analytic form by coupling the variable splitting strategy with a data augmentation scheme. Experiments on simulated data and resting state scans from a large schizophrenia dataset show that our proposed approach can identify predictive regions that are spatially contiguous in the 6-D "connectome space," offering an additional layer of interpretability that could provide new insights about various disease processes.
    NeuroImage 04/2014; · 6.25 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent psychiatric disorders of childhood. Neuroimaging investigations of ADHD have traditionally sought to detect localized abnormalities in discrete brain regions. Recent years, however, have seen the emergence of complementary lines of investigation into distributed connectivity disturbances in ADHD. Current models emphasize abnormal relationships between default network-involved in internally directed mentation and lapses of attention-and task positive networks, especially ventral attention network. However, studies that comprehensively investigate interrelationships between large-scale networks in ADHD remain relatively rare. Resting state functional magnetic resonance imaging scans were obtained from 757 participants at seven sites in the ADHD-200 multisite sample. Functional connectomes were generated for each subject, and interrelationships between seven large-scale brain networks were examined with network contingency analysis. ADHD brains exhibited altered resting state connectivity between default network and ventral attention network [P < 0.0001, false discovery rate (FDR)-corrected], including prominent increased connectivity (more specifically, diminished anticorrelation) between posterior cingulate cortex in default network and right anterior insula and supplementary motor area in ventral attention network. There was distributed hypoconnectivity within default network (P = 0.009, FDR-corrected), and this network also exhibited significant alterations in its interconnections with several other large-scale networks. Additionally, there was pronounced right lateralization of aberrant default network connections. Consistent with existing theoretical models, these results provide evidence that default network-ventral attention network interconnections are a key locus of dysfunction in ADHD. Moreover, these findings contribute to growing evidence that distributed dysconnectivity within and between large-scale networks is present in ADHD. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
    Human Brain Mapping 03/2014; · 6.88 Impact Factor
  • Source
    James E Swain, Chandra Sripada, John D Swain
    [Show abstract] [Hide abstract]
    ABSTRACT: The past few years have shown a major rise in network analysis of "big data" sets in the social sciences, revealing non-obvious patterns of organization and dynamic principles. We speculate that the dependency dimension - individuality versus sociality - might offer important insights into the dynamics of neurons and neuronal ensembles. Connectomic neural analyses, informed by social network theory, may be helpful in understanding underlying fundamental principles of brain organization.
    Behavioral and Brain Sciences 02/2014; 37(1):101-2. · 18.57 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we present the results of the construction and validation of a new psychometric tool for measuring beliefs about free will and related concepts: The Free Will Inventory (FWI). In its final form, FWI is a 29-item instrument with two parts. Part 1 consists of three 5-item subscales designed to measure strength of belief in free will, determinism, and dualism. Part 2 consists of a series of fourteen statements designed to further explore the complex network of people’s associated beliefs and attitudes about free will, determinism, choice, the soul, predictability, responsibility, and punishment. Having presented the construction and validation of FWI, we discuss several ways that it could be used in future research, highlight some as yet unanswered questions that are ripe for interdisciplinary investigation, and encourage researchers to join us in our efforts to answer these questions.
    Consciousness and Cognition 01/2014; 25:27–41. · 2.31 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The ability to volitionally regulate emotions is critical to health and well-being. While patterns of neural activation during emotion regulation have been well characterized, patterns of connectivity between regions remain less explored. It is increasingly recognized that the human brain is organized into large-scale intrinsic connectivity networks (ICNs) whose interrelationships are altered in characteristic ways during psychological tasks. In this fMRI study of 54 healthy individuals, we investigated alterations in connectivity within and between ICNs produced by the emotion regulation strategy of reappraisal. In order to gain a comprehensive picture of connectivity changes, we utilized connectomic psychophysiological interactions (PPI), a whole-brain generalization of standard single-seed PPI methods. In particular, we quantified PPI connectivity pair-wise across 837 ROIs placed throughout the cortex. We found that compared to maintaining one's emotional responses, engaging in reappraisal produced robust and distributed alterations in functional connections involving visual, dorsal attention, frontoparietal, and default networks. Visual network in particular increased connectivity with multiple ICNs including dorsal attention and default networks. We interpret these findings in terms of the role of these networks in mediating critical constituent processes in emotion regulation, including visual processing, stimulus salience, attention control, and interpretation and contextualization of stimuli. Our results add a new network perspective to our understanding of the neural underpinnings of emotion regulation, and highlight that connectomic methods can play a valuable role in comprehensively investigating modulation of connectivity across task conditions.
    NeuroImage 11/2013; · 6.25 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: OBJECTIVE: Convergent research demonstrates disrupted attention and heightened threat sensitivity in posttraumatic stress disorder (PTSD). This might be linked to aberrations in large-scale networks subserving the detection of salient stimuli (i.e., the salience network [SN]) and stimulus-independent, internally focused thought (i.e., the default mode network [DMN]). METHODS: Resting-state brain activity was measured in returning veterans with and without PTSD (n = 15 in each group) and in healthy community controls (n = 15). Correlation coefficients were calculated between the time course of seed regions in key SN and DMN regions and all other voxels of the brain. RESULTS: Compared with control groups, participants with PTSD showed reduced functional connectivity within the DMN (between DMN seeds and other DMN regions) including the rostral anterior cingulate cortex/ventromedial prefrontal cortex (z = 3.31; p = .005, corrected) and increased connectivity within the SN (between insula seeds and other SN regions) including the amygdala (z = 3.03; p = .01, corrected). Participants with PTSD also demonstrated increased cross-network connectivity. DMN seeds exhibited elevated connectivity with SN regions including the insula (z = 3.06; p = .03, corrected), and SN seeds exhibited elevated connectivity with DMN regions including the hippocampus (z = 3.10; p = .048, corrected). CONCLUSIONS: During resting-state scanning, participants with PTSD showed reduced coupling within the DMN, greater coupling within the SN, and increased coupling between the DMN and the SN. Our findings suggest a relative dominance of threat-sensitive circuitry in PTSD, even in task-free conditions. Disequilibrium between large-scale networks subserving salience detection versus internally focused thought may be associated with PTSD pathophysiology.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Generalized social anxiety disorder (GSAD) is characterized by excessive fear of public scrutiny and reticence to engage in social interaction. These behaviors are often linked to limbic and limbic-frontal circuits that process social threat, represented by static, non-interactive stimuli (e.g., face photographs). Little is known about the neural systems that implement valuations of social signals in simulated dynamic interactions in GSAD. 28 healthy controls (HC) and 30 individuals meeting DSM-IV criteria for GSAD underwent fMRI while performing iterative exchanges with fictive partners in a behavioral economic game (‘Reputation Trust Game’). Partners were represented by photographs of faces obscured with colored masks which subsequently acquired differential reputations for reciprocity (75%: Fair;
    2013 Society for Neuroscience Meeting, San Diego, CA; 11/2013
  • [Show abstract] [Hide abstract]
    ABSTRACT: Childhood poverty has pervasive negative physical and psychological health sequelae in adulthood. Exposure to chronic stressors may be one underlying mechanism for childhood poverty-health relations by influencing emotion regulatory systems. Animal work and human cross-sectional studies both suggest that chronic stressor exposure is associated with amygdala and prefrontal cortex regions important for emotion regulation. In this longitudinal functional magnetic resonance imaging study of 49 participants, we examined associations between childhood poverty at age 9 and adult neural circuitry activation during emotion regulation at age 24. To test developmental timing, concurrent, adult income was included as a covariate. Adults with lower family income at age 9 exhibited reduced ventrolateral and dorsolateral prefrontal cortex activity and failure to suppress amygdala activation during effortful regulation of negative emotion at age 24. In contrast to childhood income, concurrent adult income was not associated with neural activity during emotion regulation. Furthermore, chronic stressor exposure across childhood (at age 9, 13, and 17) mediated the relations between family income at age 9 and ventrolateral and dorsolateral prefrontal cortex activity at age 24. The findings demonstrate the significance of childhood chronic stress exposures in predicting neural outcomes during emotion regulation in adults who grew up in poverty.
    Proceedings of the National Academy of Sciences 10/2013; · 9.81 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to strong interest in using neuroimaging methods to accurately predict disorder status. In this work, we are specifically interested in a multivariate approach that uses features derived from whole-brain resting state functional connectomes. However, functional connectomes reside in a high dimensional space, which complicates model interpretation and introduces numerous statistical and computational challenges. Traditional feature selection techniques are used to reduce data dimensionality, but are blind to the spatial structure of the connectomes. Here, we propose a regularization framework where the $6$-D structure of the functional connectome (defined by pairs of points in $3$-D space) is explicitly taken into account via the sparse fused Lasso regularizer. Using this regularizer with the hinge-loss function leads to a structured sparse support vector classifier with embedded feature selection. We introduce a novel efficient optimization algorithm based on augmented Lagrangian and the classical alternating direction method, and demonstrate that the inner subproblems of the algorithm can be solved exactly and non-iteratively by coupling the variable splitting strategy with a data augmentation scheme. Experiments on simulated data and resting state scans from a large schizophrenia dataset show that our proposed approach can recover results that are more neuroscientifically informative than previous methods while preserving predictive power.
    10/2013;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Methylphenidate is a psychostimulant medication that produces improvements in functions associated with multiple neurocognitive systems. To investigate the potentially distributed effects of methylphenidate on the brain's intrinsic network architecture, we coupled resting state imaging with multivariate pattern classification. In a within-subject, double-blind, placebo-controlled, randomized, counterbalanced, cross-over design, 32 healthy human volunteers received either methylphenidate or placebo prior to two fMRI resting state scans separated by approximately one week. Resting state connectomes were generated by placing regions of interest at regular intervals throughout the brain, and these connectomes were submitted for support vector machine analysis. We found that methylphenidate produces a distributed, reliably detected, multivariate neural signature. Methylphenidate effects were evident across multiple resting state networks, especially visual, somatomotor, and default networks. Methylphenidate reduced coupling within visual and somatomotor networks. In addition, default network exhibited decoupling with several task positive networks, consistent with methylphenidate modulation of the competitive relationship between these networks. These results suggest that connectivity changes within and between large-scale networks is potentially involved in the mechanisms by which methylphenidate improves attention functioning.
    NeuroImage 05/2013; · 6.25 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Generalized social anxiety disorder (GSAD) is characterized by excessive fear of public scrutiny and reticence in social engagement. Previous studies have probed the neural basis of GSAD often using static, noninteractive stimuli (e.g., face photographs) and have identified dysfunction in fear circuitry. We sought to investigate brain-based dysfunction in GSAD during more real-world, dynamic social interactions, focusing on the role of reward-related regions that are implicated in social decision-making. Thirty-six healthy individuals (healthy control [HC]) and 36 individuals with GSAD underwent functional magnetic resonance imaging (fMRI) scanning while participating in a behavioral economic game ("Trust Game") involving iterative exchanges with fictive partners who acquire differential reputations for reciprocity. We investigated brain responses to reciprocation of trust in one's social partner, and how these brain responses are modulated by partner reputation for repayment. In both HC and GSAD, receipt of reciprocity robustly engaged ventral striatum, a region implicated in reward. In HC, striatal responses to reciprocity were specific to partners who have consistently returned the investment ("cooperative partners"), and were absent for partners who lack a cooperative reputation. In GSAD, modulation of striatal responses by partner reputation was absent. Social anxiety severity predicted diminished responses to cooperative partners. These results suggest abnormalities in GSAD in reward-related striatal mechanisms that may be important for the initiation, valuation, and maintenance of cooperative social relationships. Moreover, this study demonstrates that dynamic, interactive task paradigms derived from economics can help illuminate novel mechanisms of pathology in psychiatric illnesses in which social dysfunction is a cardinal feature.
    Depression and Anxiety 04/2013; 30(4):353-61. · 4.61 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Evidence of prospective processes is increasingly common in psychological research, which suggests the fruitfulness of a theoretical framework for mind and brain built around future orientation. No metaphysics of determinism or indeterminism is presupposed by this framework, nor do considerations of scientific method require determinism—successful scientific theories in the natural sciences all involve probabilistic elements. We speculate that expressive behavior and moral decision making use prospective processes parallel to those used in nonmoral decisions.
    Perspectives on Psychological Science 03/2013; 8(2):151-154. · 4.89 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Prospection (Gilbert & Wilson, 2007), the representation of possible futures, is a ubiquitous feature of the human mind. Much psychological theory and practice, in contrast, has understood human action as determined by the past and viewed any such teleology (selection of action in light of goals) as a violation of natural law because the future cannot act on the present. Prospection involves no backward causation; rather, it is guidance not by the future itself but by present, evaluative representations of possible future states. These representations can be understood minimally as “If X, then Y” conditionals, and the process of prospection can be understood as the generation and evaluation of these conditionals. We review the history of the attempt to cast teleology out of science, culminating in the failures of behaviorism and psychoanalysis to account adequately for action without teleology. A wide range of evidence suggests that prospection is a central organizing feature of perception, cognition, affect, memory, motivation, and action. The authors speculate that prospection casts new light on why subjectivity is part of consciousness, what is “free” and “willing” in “free will,” and on mental disorders and their treatment. Viewing behavior as driven by the past was a powerful framework that helped create scientific psychology, but accumulating evidence in a wide range of areas of research suggests a shift in framework, in which navigation into the future is seen as a core organizing principle of animal and human behavior.
    Perspectives on Psychological Science 03/2013; 8(2):119-141. · 4.89 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The ability to initiate and sustain trust is critical to health and well-being. Willingness to trust is in part determined by the reputation of the putative trustee, gained via direct interactions or indirectly through word of mouth. Few studies have examined how the reputation of others is instantiated in the brain during trust decisions. Here we use an event-related functional MRI (fMRI) design to examine what neural signals correspond to experimentally manipulated reputations acquired in direct interactions during trust decisions. We hypothesized that the caudate (dorsal striatum) and putamen (ventral striatum) and amygdala would signal differential reputations during decision-making. Twenty-nine healthy adults underwent fMRI scanning while completing an iterated Trust Game as trusters with three fictive trustee partners who had different tendencies to reciprocate (i.e., likelihood of rewarding the truster), which were learned over multiple exchanges with real-time feedback. We show that the caudate (both left and right) signals reputation during trust decisions, such that caudate is more active to partners with two types of "bad" reputations, either indifferent partners (who reciprocate 50% of the time) or unfair partners (who reciprocate 25% of the time), than to those with "good" reputations (who reciprocate 75% of the time). Further, individual differences in caudate activity related to biases in trusting behavior in the most uncertain situation, i.e. when facing an indifferent partner. We also report on other areas that were activated by reputation at p < 0.05 whole brain corrected. Our findings suggest that the caudate is involved in signaling and integrating reputations gained through experience into trust decisions, demonstrating a neural basis for this key social process.
    PLoS ONE 01/2013; 8(6):e68884. · 3.53 Impact Factor
  • Biological Psychiatry 01/2013; 73(9):34S. · 9.25 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Objective Convergent research demonstrates disrupted attention and heightened threat sensitivity in posttraumatic stress disorder (PTSD). This might be linked to aberrations in large-scale networks subserving the detection of salient stimuli (i.e., the salience network [SN]) and stimulus-independent, internally focused thought (i.e., the default mode network [DMN]).Methods Resting-state brain activity was measured in returning veterans with and without PTSD (n = 15 in each group) and in healthy community controls (n = 15). Correlation coefficients were calculated between the time course of seed regions in key SN and DMN regions and all other voxels of the brain.ResultsCompared with control groups, participants with PTSD showed reduced functional connectivity within the DMN (between DMN seeds and other DMN regions) including the rostral anterior cingulate cortex/ventromedial prefrontal cortex (z = 3.31; p = .005, corrected) and increased connectivity within the SN (between insula seeds and other SN regions) including the amygdala (z = 3.03; p = .01, corrected). Participants with PTSD also demonstrated increased cross-network connectivity. DMN seeds exhibited elevated connectivity with SN regions including the insula (z = 3.06; p = .03, corrected), and SN seeds exhibited elevated connectivity with DMN regions including the hippocampus (z = 3.10; p = .048, corrected).Conclusions During resting-state scanning, participants with PTSD showed reduced coupling within the DMN, greater coupling within the SN, and increased coupling between the DMN and the SN. Our findings suggest a relative dominance of threat-sensitive circuitry in PTSD, even in task-free conditions. Disequilibrium between large-scale networks subserving salience detection versus internally focused thought may be associated with PTSD pathophysiology.
    Psychosomatic Medicine 10/2012; · 4.08 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: A first-line approach to treat anxiety disorders is exposure-based therapy, which relies on extinction processes such as repeatedly exposing the patient to stimuli (conditioned stimuli; CS) associated with the traumatic, fear-related memory. However, a significant number of patients fail to maintain their gains, partly attributed to the fact that this inhibitory learning and its maintenance is temporary and conditioned fear responses can return. Animal studies have shown that activation of the cannabinoid system during extinction learning enhances fear extinction and its retention. Specifically, CB1 receptor agonists, such as Δ9-tetrahydrocannibinol (THC), can facilitate extinction recall by preventing recovery of extinguished fear in rats. However, this phenomenon has not been investigated in humans. We conducted a study using a randomized, double-blind, placebo-controlled, between-subjects design, coupling a standard Pavlovian fear extinction paradigm and simultaneous skin conductance response (SCR) recording with an acute pharmacological challenge with oral dronabinol (synthetic THC) or placebo (PBO) 2 h prior to extinction learning in 29 healthy adult volunteers (THC = 14; PBO = 15) and tested extinction retention 24 h after extinction learning. Compared to subjects that received PBO, subjects that received THC showed low SCR to a previously extinguished CS when extinction memory recall was tested 24 h after extinction learning, suggesting that THC prevented the recovery of fear. These results provide the first evidence that pharmacological enhancement of extinction learning is feasible in humans using cannabinoid system modulators, which may thus warrant further development and clinical testing. This article is part of a Special Issue entitled 'Cognitive Enhancers'.
    Neuropharmacology 07/2012; 64(1):396-402. · 4.11 Impact Factor

Publication Stats

606 Citations
189.87 Total Impact Points

Institutions

  • 2008–2014
    • University of Michigan
      • • Department of Philosophy
      • • Department of Psychiatry
      Ann Arbor, Michigan, United States
  • 2013
    • University of Denver
      • Department of Psychology
      Denver, Colorado, United States
  • 2011–2013
    • University of Chicago
      • Department of Psychiatry and Behavioral Neuroscience
      Chicago, Illinois, United States
  • 2012
    • Concordia University–Ann Arbor
      Ann Arbor, Michigan, United States
  • 2005
    • Rutgers, The State University of New Jersey
      • Center for Cognitive Science
      Newark, NJ, United States