Identification of Common Neural Circuit Disruptions in Cognitive Control Across Psychiatric Disorders.

OBJECTIVE Cognitive deficits are a common feature of psychiatric disorders. The authors investigated the nature of disruptions in neural circuitry underlying cognitive control capacities across psychiatric disorders through a transdiagnostic neuroimaging meta-analysis. METHOD A PubMed search was conducted for whole-brain functional neuroimaging articles published through June 2015 that compared activation in patients with axis I disorders and matched healthy control participants during cognitive control tasks. Tasks that probed performance or conflict monitoring, response inhibition or selection, set shifting, verbal fluency, and recognition or working memory were included. Activation likelihood estimation meta-analyses were conducted on peak voxel coordinates. RESULTS The 283 experiments submitted to meta-analysis included 5,728 control participants and 5,493 patients with various disorders (schizophrenia, bipolar or unipolar depression, anxiety disorders, and substance use disorders). Transdiagnostically abnormal activation was evident in the left prefrontal cortex as well as the anterior insula, the right ventrolateral prefrontal cortex, the right intraparietal sulcus, and the midcingulate/presupplementary motor area. Disruption was also observed in a more anterior cluster in the dorsal cingulate cortex, which overlapped with a network of structural perturbation that the authors previously reported in a transdiagnostic meta-analysis of gray matter volume. CONCLUSIONS These findings demonstrate a common pattern of disruption across major psychiatric disorders that parallels the "multiple-demand network" observed in intact cognition. This network interfaces with the anterior-cingulo-insular or "salience network" demonstrated to be transdiagnostically vulnerable to gray matter reduction. Thus, networks intrinsic to adaptive, flexible cognition are vulnerable to broad-spectrum psychopathology. Dysfunction in these networks may reflect an intermediate transdiagnostic phenotype, which could be leveraged to advance therapeutics.

[1]  V. Menon,et al.  Saliency, switching, attention and control: a network model of insula function , 2010, Brain Structure and Function.

[2]  C. Li,et al.  Causal Interactions Within a Frontal-Cingulate-Parietal Network During Cognitive Control: Convergent Evidence from a Multisite-Multitask Investigation. , 2016, Cerebral cortex.

[3]  Lars Michels,et al.  Role of the anterior insular cortex in integrative causal signaling during multisensory auditory–visual attention , 2015, The European journal of neuroscience.

[4]  N. Eaton,et al.  The hierarchical structure of common mental disorders: Connecting multiple levels of comorbidity, bifactor models, and predictive validity. , 2015, Journal of abnormal psychology.

[5]  S. Eickhoff,et al.  Interindividual differences in cognitive flexibility: influence of gray matter volume, functional connectivity and trait impulsivity , 2014, Brain Structure and Function.

[6]  C. Gualtieri,et al.  The frequency of cognitive impairment in patients with anxiety, depression, and bipolar disorder: an unaccounted source of variance in clinical trials. , 2008, The Journal of clinical psychiatry.

[7]  M. D’Esposito,et al.  Functional Characterization of the Cingulo-Opercular Network in the Maintenance of Tonic Alertness. , 2015, Cerebral cortex.

[8]  Kristina M. Visscher,et al.  A Core System for the Implementation of Task Sets , 2006, Neuron.

[9]  Peter Stiers,et al.  Distributed task coding throughout the multiple demand network of the human frontal–insular cortex , 2010, NeuroImage.

[10]  N. Carragher,et al.  The structure of adolescent psychopathology: a symptom-level analysis , 2015, Psychological Medicine.

[11]  G. Glover,et al.  Dissociable Intrinsic Connectivity Networks for Salience Processing and Executive Control , 2007, The Journal of Neuroscience.

[12]  Kimberly L. Ray,et al.  Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions , 2012, Cognitive, affective & behavioral neuroscience.

[13]  K. Miller.  Executive functions. , 2005, Pediatric annals.

[14]  Daniel J Mitchell,et al.  Task Encoding across the Multiple Demand Cortex Is Consistent with a Frontoparietal and Cingulo-Opercular Dual Networks Distinction , 2016, The Journal of Neuroscience.

[15]  Angela R. Laird,et al.  Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation , 2016, NeuroImage.

[16]  J. Duncan,et al.  Common regions of the human frontal lobe recruited by diverse cognitive demands , 2000, Trends in Neurosciences.

[17]  Walter Schneider,et al.  The cognitive control network: Integrated cortical regions with dissociable functions , 2007, NeuroImage.

[18]  A. Miyake,et al.  The Nature and Organization of Individual Differences in Executive Functions , 2012, Current directions in psychological science.

[19]  P. Fox,et al.  Identification of a common neurobiological substrate for mental illness. , 2015, JAMA psychiatry.

[20]  Niall W. Duncan,et al.  A comparison of neural responses to appetitive and aversive stimuli in humans and other mammals , 2014, Neuroscience & Biobehavioral Reviews.

[21]  S. Petersen,et al.  A dual-networks architecture of top-down control , 2008, Trends in Cognitive Sciences.

[22]  C. Kennard,et al.  Functional role of the supplementary and pre-supplementary motor areas , 2008, Nature Reviews Neuroscience.

[23]  Simon B Eickhoff,et al.  Minimizing within‐experiment and within‐group effects in activation likelihood estimation meta‐analyses , 2012, Human brain mapping.

[24]  Michael J. Martinez,et al.  Bias between MNI and Talairach coordinates analyzed using the ICBM‐152 brain template , 2007, Human brain mapping.

[25]  S. Nolen-Hoeksema,et al.  A Heuristic for Developing Transdiagnostic Models of Psychopathology , 2011, Perspectives on psychological science : a journal of the Association for Psychological Science.

[26]  Bruce N Cuthbert,et al.  The NIMH Research Domain Criteria Initiative: Background, Issues, and Pragmatics. , 2016, Psychophysiology.

[27]  Angela R. Laird,et al.  ANIMA: A data-sharing initiative for neuroimaging meta-analyses , 2016, NeuroImage.

[28]  J. Duncan.  The Structure of Cognition: Attentional Episodes in Mind and Brain , 2013, Neuron.

[29]  Bradford C. Dickerson,et al.  Dissociable large-scale networks anchored in the right anterior insula subserve affective experience and attention , 2012, NeuroImage.

[30]  S. Petersen,et al.  Role of the anterior insula in task-level control and focal attention , 2010, Brain Structure and Function.

[31]  Tobias Egner,et al.  An insula-frontostriatal network mediates flexible cognitive control by adaptively predicting changing control demands , 2015, Nature Communications.

[32]  A. Miyake,et al.  Individual differences in executive functions are almost entirely genetic in origin. , 2008, Journal of experimental psychology. General.

[33]  V. Menon,et al.  A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks , 2008, Proceedings of the National Academy of Sciences.

[34]  J. Duncan.  The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour , 2010, Trends in Cognitive Sciences.

[35]  M. Greicius,et al.  Decoding subject-driven cognitive states with whole-brain connectivity patterns. , 2012, Cerebral cortex.

[36]  A. Etkin,et al.  Functional neuroimaging of anxiety: a meta-analysis of emotional processing in PTSD, social anxiety disorder, and specific phobia. , 2007, The American journal of psychiatry.

[37]  T. Braver.  The variable nature of cognitive control: a dual mechanisms framework , 2012, Trends in Cognitive Sciences.

[38]  Timothy O. Laumann,et al.  Functional Network Organization of the Human Brain , 2011, Neuron.

[39]  A. Meyer-Lindenberg,et al.  Psychopathology and the Human Connectome: Toward a Transdiagnostic Model of Risk For Mental Illness , 2012, Neuron.

[40]  Nancy Kanwisher,et al.  Broad domain generality in focal regions of frontal and parietal cortex , 2013, Proceedings of the National Academy of Sciences.

[41]  Sandhya Ramrakha,et al.  The p Factor , 2014, Clinical psychological science : a journal of the Association for Psychological Science.

[42]  R. Kotov,et al.  Schizophrenia in the internalizing-externalizing framework: a third dimension? , 2011, Schizophrenia bulletin.

[43]  Angela R. Laird,et al.  Is There “One” DLPFC in Cognitive Action Control? Evidence for Heterogeneity From Co-Activation-Based Parcellation , 2012, Cerebral cortex.

[44]  K. Zilles,et al.  Coordinate‐based activation likelihood estimation meta‐analysis of neuroimaging data: A random‐effects approach based on empirical estimates of spatial uncertainty , 2009, Human brain mapping.

[45]  Kaustubh Supekar,et al.  Distinct Global Brain Dynamics and Spatiotemporal Organization of the Salience Network , 2016, PLoS biology.

[46]  Angela R. Laird,et al.  Activation likelihood estimation meta-analysis revisited , 2012, NeuroImage.

[47]  Jan Derrfuss,et al.  Co-Activation-Based Parcellation of the Lateral Prefrontal Cortex Delineates the Inferior Frontal Junction Area. , 2016, Cerebral cortex.