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Journal of Computational Neuroscience

Erschienen in:

01.06.2014

On parsing the neural code in the prefrontal cortex of primates using principal dynamic modes

verfasst von: V. Z. Marmarelis, D. C. Shin, D. Song, R. E. Hampson, S. A. Deadwyler, T. W. Berger

Erschienen in: Journal of Computational Neuroscience | Ausgabe 3/2014

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Abstract

Nonlinear modeling of multi-input multi-output (MIMO) neuronal systems using Principal Dynamic Modes (PDMs) provides a novel method for analyzing the functional connectivity between neuronal groups. This paper presents the PDM-based modeling methodology and initial results from actual multi-unit recordings in the prefrontal cortex of non-human primates. We used the PDMs to analyze the dynamic transformations of spike train activity from Layer 2 (input) to Layer 5 (output) of the prefrontal cortex in primates performing a Delayed-Match-to-Sample task. The PDM-based models reduce the complexity of representing large-scale neural MIMO systems that involve large numbers of neurons, and also offer the prospect of improved biological/physiological interpretation of the obtained models. PDM analysis of neuronal connectivity in this system revealed “input–output channels of communication” corresponding to specific bands of neural rhythms that quantify the relative importance of these frequency-specific PDMs across a variety of different tasks. We found that behavioral performance during the Delayed-Match-to-Sample task (correct vs. incorrect outcome) was associated with differential activation of frequency-specific PDMs in the prefrontal cortex.

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Titel: On parsing the neural code in the prefrontal cortex of primates using principal dynamic modes
verfasst von: V. Z. Marmarelis
D. C. Shin
D. Song
R. E. Hampson
S. A. Deadwyler
T. W. Berger
Publikationsdatum: 01.06.2014
Verlag: Springer US
Erschienen in: Journal of Computational Neuroscience / Ausgabe 3/2014
Print ISSN: 0929-5313
Elektronische ISSN: 1573-6873
DOI: https://doi.org/10.1007/s10827-013-0475-3

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