QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

HOME  |   SEARCH  |   ARCHIVE  |   SUBSCRIBE  |   CONTACT  |   HELP

This Article Full Text Full Text (PDF) Submit an eLetter Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (35) Citing Articles via Google Scholar Google Scholar Articles by Moody, S. L. Articles by Zipser, D. Search for Related Content PubMed PubMed Citation Articles by Moody, S. L. Articles by Zipser, D.

 Previous Article  |  Next Article 

The Journal of Neuroscience, January 1, 1998, 18(1):399-410

A Model That Accounts for Activity in Primate Frontal Cortex during a Delayed Matching-to-Sample Task

Sohie Lee Moody^{1, 2}, Steven P. Wise², Giuseppe di Pellegrino², and David Zipser¹

¹ Cognitive Science Department, University of California, San Diego, La Jolla, California 92093-0515, and ² Laboratory of Systems Neuroscience, National Institute of Mental Health, Poolesville, Maryland 20837

A fully recurrent neural network model was optimized to perform a spatial delayed matching-to-sample task (DMS). In DMS, a stimulus is presented at a sample location, and a match is reported when a subsequent stimulus appears at that location. Stimuli elsewhere are ignored. Computationally, a DMS system could consist of memory and comparison components. The model, although not constrained to do so, worked by using two corresponding classes of neurons in the hidden layer: storage and comparator units. Storage units form a dynamical system with one fixed point attractor for each sample location. Comparator units constitute a system receiving input from these storage units as well as from current input stimuli. Both unit types were tuned directionally. These two sources of information combine to create unique patterns of activity that determine whether a match has occurred. In networks with abundant hidden units, the storage and comparator functions were distributed so that individual units took part in both. We compared the model with single-neuron recordings from premotor (PM) and prefrontal (PF) cortex. As shown previously, many PM and PF neurons behaved like storage units. In addition, both regions contain neurons that behave like the comparator units of the model and appear to have dual functionality similar to that observed in the model units. No neuron in either area had properties identical to those of the match output neuron of the model. However, four PF neurons and one PM neuron resembled the output signal more closely than any of the hidden units of the model.

Key words: model; attractor; prefrontal; premotor; neural network; matching-to-sample; comparator

---

Copyright © 1998 Society for Neuroscience  0270-6474/98/181399-12$05.00/0

This article has been cited by other articles:

				M. Maniadakis and P. Trahanias Hierarchical Co-evolution of Cooperating Agents Acting in the Brain-Arena Adaptive Behavior, August 1, 2008; 16(4): 221 - 245. [Abstract] [PDF]

				R. E. B. Mruczek and D. L. Sheinberg Activity of Inferior Temporal Cortical Neurons Predicts Recognition Choice Behavior and Recognition Time during Visual Search J. Neurosci., March 14, 2007; 27(11): 2825 - 2836. [Abstract] [Full Text] [PDF]

				W. A SUZUKI Making New Memories: The Role of the Hippocampus in New Associative Learning Ann. N.Y. Acad. Sci., February 1, 2007; 1097(1): 1 - 11. [Abstract] [Full Text] [PDF]

				S. Tsujimoto and T. Sawaguchi Context-dependent Representation of Response-outcome in Monkey Prefrontal Neurons Cereb Cortex, July 1, 2005; 15(7): 888 - 898. [Abstract] [Full Text] [PDF]

				T. Gisiger, M. Kerszberg, and J.-P. Changeux Acquisition and Performance of Delayed-response Tasks: a Neural Network Model Cereb Cortex, May 1, 2005; 15(5): 489 - 506. [Abstract] [Full Text] [PDF]

				C. K. Machens, R. Romo, and C. D. Brody Flexible Control of Mutual Inhibition: A Neural Model of Two-Interval Discrimination Science, February 18, 2005; 307(5712): 1121 - 1124. [Abstract] [Full Text] [PDF]

				S. Wirth, M. Yanike, L. M. Frank, A. C. Smith, E. N. Brown, and W. A. Suzuki Single Neurons in the Monkey Hippocampus and Learning of New Associations Science, June 6, 2003; 300(5625): 1578 - 1581. [Abstract] [Full Text] [PDF]

				A. Compte, N. Brunel, P. S. Goldman-Rakic, and X.-J. Wang Synaptic Mechanisms and Network Dynamics Underlying Spatial Working Memory in a Cortical Network Model Cereb Cortex, September 1, 2000; 10(9): 910 - 923. [Abstract] [Full Text] [PDF]

				A. D. Lawrence, L. H. A. Watkins, B. J. Sahakian, J. R. Hodges, and T. W. Robbins Visual object and visuospatial cognition in Huntington's disease: implications for information processing in corticostriatal circuits Brain, July 1, 2000; 123(7): 1349 - 1364. [Abstract] [Full Text] [PDF]

				S. L. Moody and S. P. Wise A Model that Accounts for Activity Prior to Sensory Inputs and Responses During Matching-to-Sample Tasks J. Cogn. Neurosci., May 1, 2000; 12(3): 429 - 448. [Abstract] [Full Text]

				X.-J. Wang Synaptic Basis of Cortical Persistent Activity: the Importance of NMDA Receptors to Working Memory J. Neurosci., November 1, 1999; 19(21): 9587 - 9603. [Abstract] [Full Text] [PDF]

				K. Zhang and T. J. Sejnowski A Theory of Geometric Constraints on Neural Activity for Natural Three-Dimensional Movement J. Neurosci., April 15, 1999; 19(8): 3122 - 3145. [Abstract] [Full Text] [PDF]

Home  |   Search  |   Archive  |   Subscribe  |   Contact  |   Help