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      Information processing with population codes

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      Nature Reviews Neuroscience
      Springer Science and Business Media LLC

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          Abstract

          Information is encoded in the brain by populations or clusters of cells, rather than by single cells. This encoding strategy is known as population coding. Here we review the standard use of population codes for encoding and decoding information, and consider how population codes can be used to support neural computations such as noise removal and nonlinear mapping. More radical ideas about how population codes may directly represent information about stimulus uncertainty are also discussed.

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          Theoretical Statistics

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            Information theory and neural coding.

            Information theory quantifies how much information a neural response carries about the stimulus. This can be compared to the information transferred in particular models of the stimulus-response function and to maximum possible information transfer. Such comparisons are crucial because they validate assumptions present in any neurophysiological analysis. Here we review information-theory basics before demonstrating its use in neural coding. We show how to use information theory to validate simple stimulus-response models of neural coding of dynamic stimuli. Because these models require specification of spike timing precision, they can reveal which time scales contain information in neural coding. This approach shows that dynamic stimuli can be encoded efficiently by single neurons and that each spike contributes to information transmission. We argue, however, that the data obtained so far do not suggest a temporal code, in which the placement of spikes relative to each other yields additional information.
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              On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex.

              The activity of single cells in the motor cortex was recorded while monkeys made arm movements in eight directions (at 45 degrees intervals) in a two-dimensional apparatus. These movements started from the same point and were of the same amplitude. The activity of 606 cells related to proximal arm movements was examined in the task; 323 of the 606 cells were active in that task and were studied in detail. The frequency of discharge of 241 of the 323 cells (74.6%) varied in an orderly fashion with the direction of movement. Discharge was most intense with movements in a preferred direction and was reduced gradually when movements were made in directions farther and farther away from the preferred one. This resulted in a bell-shaped directional tuning curve. These relations were observed for cell discharge during the reaction time, the movement time, and the period that preceded the earliest changes in the electromyographic activity (approximately 80 msec before movement onset). In about 75% of the 241 directionally tuned cells, the frequency of discharge, D, was a sinusoidal function of the direction of movement, theta: D = b0 + b1 sin theta + b2cos theta, or, in terms of the preferred direction, theta 0: D = b0 + c1cos (theta - theta0), where b0, b1, b2, and c1 are regression coefficients. Preferred directions differed for different cells so that the tuning curves partially overlapped. The orderly variation of cell discharge with the direction of movement and the fact that cells related to only one of the eight directions of movement tested were rarely observed indicate that movements in a particular direction are not subserved by motor cortical cells uniquely related to that movement. It is suggested, instead, that a movement trajectory in a desired direction might be generated by the cooperation of cells with overlapping tuning curves. The nature of this hypothetical population code for movement direction remains to be elucidated.
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                Author and article information

                Journal
                Nature Reviews Neuroscience
                Nat Rev Neurosci
                Springer Science and Business Media LLC
                1471-003X
                1471-0048
                November 2000
                November 2000
                : 1
                : 2
                : 125-132
                Article
                10.1038/35039062
                11252775
                d9b33f1b-c7b8-4ec6-b356-58e3fa89f6e7
                © 2000

                http://www.springer.com/tdm


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