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Behavioral/Systems/Cognitive Proactive Inhibitory Control and Attractor Dynamics in
 

Summary: Behavioral/Systems/Cognitive
Proactive Inhibitory Control and Attractor Dynamics in
Countermanding Action: A Spiking Neural Circuit Model
Chung-Chuan Lo,1,2 Leanne Boucher,3 Martin Pare,4 Jeffrey D. Schall,3 and Xiao-Jing Wang1
1Department of Neurobiology and Kavli Institute for Neuroscience, Yale University, New Haven, Connecticut 06510, 2Institute of Bioinformatics and
Structural Biology, National Tsing Hua University, Hsinchu 30013, Taiwan, 3Center for Integrative & Cognitive Neuroscience, Vanderbilt Vision Research
Center, Department of Psychology, Vanderbilt University, Nashville, Tennessee 37240, and 4Centre for Neuroscience Studies and Departments of
Physiology and Psychology, Queen's University, Kingston, Ontario K7L 3N6, Canada
Flexiblebehaviordependsonthebrain'sabilitytosuppressahabitualresponseortocancelaplannedmovementwheneverneeded.Such
inhibitory control has been studied using the countermanding paradigm in which subjects are required to withhold an imminent
movement when a stop signal appears infrequently in a fraction of trials. To elucidate the circuit mechanism of inhibitory control of
action, we developed a recurrent network model consisting of spiking movement (GO) neurons and fixation (STOP) neurons, based on
neurophysiologicalobservationsinthefrontaleyefieldandsuperiorcolliculusofbehavingmonkeys.Themodelplacesapremiumonthe
network dynamics before the onset of a stop signal, especially the experimentally observed high baseline activity of fixation neurons,
which is assumed to be modulated by a persistent top-down control signal, and their synaptic interaction with movement neurons. The
model simulated observed neural activity and fit behavioral performance quantitatively. In contrast to a race model in which the STOP
processisinitiatedattheonsetofastopsignal,inourmodelwhetheramovementwilleventuallybecanceledisdeterminedlargelybythe
proactive top-down control and the stochastic network dynamics, even before the appearance of the stop signal. A prediction about the
correlation between the fixation neural activity and the behavioral outcome was verified in the neurophysiological data recorded from
behaving monkeys. The proposed mechanism for adjusting control through tonically active neurons that inhibit movement-producing

  

Source: Andrzejak, Ralph Gregor - Departament de Tecnologia, Universitat Pompeu Fabra
Lo, Chung-Chuan - Department of Life Science, National Tsing Hua University
Palmeri, Thomas - Department of Psychology, Vanderbilt University
Wang, Xiao-Jing - Kavli Institute for Neuroscience & Department of Neurobiology, Yale University

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences; Physics