|
|
||||||||
1The Weizmann Institute of Science, Department of Neurobiology, Rehovot, 76100 Israel; 2Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, Center for Biological and Computational Learning, McGovern Institute for Brain Research, and Artificial Intelligence Laboratory, Cambridge, Massachusetts 02142; 3Northwestern University, Department of Neurobiology and Physiology, Evanston, Illinois 60208; and 4Georgetown University Medical Center, Department of Neuroscience, Washington, DC 20007
Submitted 20 January 2004; accepted in final form 30 June 2004
We have examined the spatial integration properties of complex cells to determine whether some of their responses can be described by a maximum operation (MAX)-like computation, as suggested by Riesenhuber and Poggio's model of object recognition. Membrane potential was recorded from anesthetized cats while optimally oriented bars were presented, either alone or in pairs, in different parts of the cells' receptive field. In most cells, the membrane potential response to two bars presented simultaneously could not be predicted by the sum of the responses to individual bars. In many cells, however, the responses closely approximated a MAX-like model. That is, the response of the cell to two bars was similar to the larger of the two individual responses ("soft-MAX"). The degree of nonlinear summation varied from cell to cell and varied within single cells from one stimulus configuration to another but on average fit most closely to the MAX model. The firing response of the cells was also well predicted by the MAX-like model. The MAX-like behavior was independent of the distance between the bars (orthogonal to the preferred orientation), independent of the relative amplitude of the responses, and slightly less pronounced at low levels of contrast. This MAX-like behavior of a subset of complex cells may play an important role in invariant object recognition in clutter.
This article has been cited by other articles:
![]() |
M. Kouh and T. Poggio A Canonical Neural Circuit for Cortical Nonlinear Operations Neural Comput., June 1, 2008; 20(6): 1427 - 1451. [Abstract] [Full Text] [PDF] |
||||
![]() |
I. M. Finn and D. Ferster Computational Diversity in Complex Cells of Cat Primary Visual Cortex J. Neurosci., September 5, 2007; 27(36): 9638 - 9648. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. Kiani, H. Esteky, K. Mirpour, and K. Tanaka Object Category Structure in Response Patterns of Neuronal Population in Monkey Inferior Temporal Cortex J Neurophysiol, June 1, 2007; 97(6): 4296 - 4309. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. C. Alvarado, J. W. Vaughan, T. R. Stanford, and B. E. Stein Multisensory Versus Unisensory Integration: Contrasting Modes in the Superior Colliculus J Neurophysiol, May 1, 2007; 97(5): 3193 - 3205. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. Serre, A. Oliva, and T. Poggio A feedforward architecture accounts for rapid categorization PNAS, April 10, 2007; 104(15): 6424 - 6429. [Abstract] [Full Text] [PDF] |
||||
![]() |
D. Zoccolan, D. D. Cox, and J. J. DiCarlo Multiple Object Response Normalization in Monkey Inferotemporal Cortex J. Neurosci., September 7, 2005; 25(36): 8150 - 8164. [Abstract] [Full Text] [PDF] |
||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Visit Other APS Journals Online |