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      Signatures of cochlear processing in neuronal coding of auditory information

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      Molecular and Cellular Neuroscience
      Elsevier BV

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          Neural correlations, population coding and computation.

          How the brain encodes information in population activity, and how it combines and manipulates that activity as it carries out computations, are questions that lie at the heart of systems neuroscience. During the past decade, with the advent of multi-electrode recording and improved theoretical models, these questions have begun to yield answers. However, a complete understanding of neuronal variability, and, in particular, how it affects population codes, is missing. This is because variability in the brain is typically correlated, and although the exact effects of these correlations are not known, it is known that they can be large. Here, we review studies that address the interaction between neuronal noise and population codes, and discuss their implications for population coding in general.
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            Neuronal population coding of movement direction.

            Although individual neurons in the arm area of the primate motor cortex are only broadly tuned to a particular direction in three-dimensional space, the animal can very precisely control the movement of its arm. The direction of movement was found to be uniquely predicted by the action of a population of motor cortical neurons. When individual cells were represented as vectors that make weighted contributions along the axis of their preferred direction (according to changes in their activity during the movement under consideration) the resulting vector sum of all cell vectors (population vector) was in a direction congruent with the direction of movement. This population vector can be monitored during various tasks, and similar measures in other neuronal populations could be of heuristic value where there is a neural representation of variables with vectorial attributes.
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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
                Molecular and Cellular Neuroscience
                Molecular and Cellular Neuroscience
                Elsevier BV
                10447431
                May 2022
                May 2022
                : 120
                : 103732
                Article
                10.1016/j.mcn.2022.103732
                35489636
                17334b5b-1054-4671-9cbd-34f690c1b970
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://www.elsevier.com/open-access/userlicense/1.0/

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