Title |
Distributed representations of action sequences in anterior cingulate cortex: A recurrent neural network approach
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Published in |
Psychonomic Bulletin & Review, April 2017
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DOI | 10.3758/s13423-017-1280-1 |
Pubmed ID | |
Authors |
Danesh Shahnazian, Clay B. Holroyd |
Abstract |
Anterior cingulate cortex (ACC) has been the subject of intense debate over the past 2 decades, but its specific computational function remains controversial. Here we present a simple computational model of ACC that incorporates distributed representations across a network of interconnected processing units. Based on the proposal that ACC is concerned with the execution of extended, goal-directed action sequences, we trained a recurrent neural network to predict each successive step of several sequences associated with multiple tasks. In keeping with neurophysiological observations from nonhuman animals, the network yields distributed patterns of activity across ACC neurons that track the progression of each sequence, and in keeping with human neuroimaging data, the network produces discrepancy signals when any step of the sequence deviates from the predicted step. These simulations illustrate a novel approach for investigating ACC function. |
X Demographics
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 93 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 17 | 18% |
Student > Master | 13 | 14% |
Student > Bachelor | 12 | 13% |
Researcher | 12 | 13% |
Other | 8 | 9% |
Other | 10 | 11% |
Unknown | 21 | 23% |
Readers by discipline | Count | As % |
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Psychology | 22 | 24% |
Neuroscience | 12 | 13% |
Agricultural and Biological Sciences | 6 | 6% |
Engineering | 5 | 5% |
Medicine and Dentistry | 5 | 5% |
Other | 13 | 14% |
Unknown | 30 | 32% |