Cognitive control is the ability to modify the behavioral response to a stimulus based on internal representations of goals or rules. We sought to characterize neural mechanisms in prefrontal cortex associated with cognitive control in a context that would maximize the potential for future translational relevance to human neuropsychiatric disease. To that end, we trained monkeys to perform a dot-pattern variant of the AX continuous performance task that is used to measure cognitive control impairment in patients with schizophrenia (MacDonald, 2008; Jones et al., 2010). Here we describe how information processing for cognitive control in this task is related to neural activity patterns in prefrontal cortex of monkeys, to advance our understanding of how behavioral flexibility is implemented by prefrontal neurons in general, and to model neural signals in the healthy brain that may be disrupted to produce cognitive control deficits in schizophrenia. We found that the neural representation of stimuli in prefrontal cortex is strongly biased toward stimuli that inhibit prepotent or automatic responses. We also found that population signals encoding different stimuli were modulated to overlap in time specifically in the case that information from multiple stimuli had to be integrated to select a conditional response. Finally, population signals relating to the motor response were biased toward less frequent and therefore less automatic actions. These data relate neuronal activity patterns in prefrontal cortex to logical information processing operations required for cognitive control, and they characterize neural events that may be disrupted in schizophrenia.
Bibliographical noteFunding Information:
This work was supported by the National Institutes of Health Grants R01MH077779 and R01MH107491, the Department of Veterans Affairs, the American Brain Sciences Chair, the Wilfred Wetzel Graduate Fellowship, and Medical Scientist Training Program at the University of Minnesota Grant T32 GM008244.Wethank C. Dean Evans for excellent technical assistance in surgeries and neural recording as well as animal care; Dale Boeff for computer programming and engineering support; and Dr. Theoden Netoff for consulting on the demixed principal components analysis. The views and opinions expressed in this paper are those of the authors and not those of the United States Federal Government.
© 2016 the authors.
Copyright 2017 Elsevier B.V., All rights reserved.
- Context processing
- Neural activity