TY - JOUR
T1 - Working memory and decision-making in a frontoparietal circuit model
AU - Murray, John D.
AU - Jaramillo, Jorge
AU - Wang, Xiao Jing
N1 - Funding Information:
Received Feb. 1, 2017; revised Aug. 24, 2017; accepted Sept. 19, 2017. Author contributions: J.D.M., J.J., and X.-J.W. designed research; J.D.M. and J.J. performed research; J.D.M., J.J., and X.-J.W. wrote the paper. This work was supported by National Institutes Health Grant R01-MH-062349, Naval Research Grant N00014-17-1-2041,aSimonsFoundationCollaborationontheGlobalBrainGrant,andScienceandTechnologyCommission of Shanghai Municipality Grants 14JC1404900 and 15JC1400104 (to X.-J.W.). We thank Dr. Braden Purcell and Robert Yang for careful reading of an earlier version of the manuscript. *J.D.M. and J.J. contributed equally to this work. The authors declare no competing financial interests. Correspondence should be addressed to Xiao-Jing Wang, Center for Neural Science, 4 Washington Place, New York University, New York, NY 10003. E-mail: [email protected].
Funding Information:
This work was supported by National Institutes Health Grant R01-MH-062349, Naval Research Grant N00014-17-1-2041, a Simons Foundation Collaboration on the Global Brain Grant, and Science and Technology Commission of Shanghai Municipality Grants 14JC1404900 and 15JC1400104 (to X.-J.W.). We thank Dr. Braden Purcell and Robert Yang for careful reading of an earlier version of the manuscript.
Publisher Copyright:
© 2017 the authors.
PY - 2017/12/13
Y1 - 2017/12/13
N2 - Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models.
SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental "building blocks" of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks.
AB - Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models.
SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental "building blocks" of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks.
KW - Attractor network
KW - Decision-making
KW - NMDA receptor
KW - Parietal cortex
KW - Prefrontal cortex
KW - Working memory
KW - Neural Networks, Computer
KW - Parietal Lobe/physiology
KW - Humans
KW - Memory, Short-Term/physiology
KW - Connectome
KW - Synaptic Transmission
KW - Action Potentials
KW - Computer Simulation
KW - Decision Making/physiology
KW - Models, Neurological
KW - Prefrontal Cortex/physiology
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UR - http://www.scopus.com/inward/citedby.url?scp=85038259889&partnerID=8YFLogxK
U2 - 10.1523/JNEUROSCI.0343-17.2017
DO - 10.1523/JNEUROSCI.0343-17.2017
M3 - Article
C2 - 29114071
AN - SCOPUS:85038259889
SN - 0270-6474
VL - 37
SP - 12167
EP - 12186
JO - Journal of Neuroscience
JF - Journal of Neuroscience
IS - 50
ER -