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

• DOI: 10.1007/s10827-013-0475-3
• Publication Date: 2013-08-08T09:36:49Z
• Authors: V. Z. Marmarelis; D. C. Shin; D. Song; R. E. Hampson; S. A. Deadwyler; T. W. Berger
• Keywords: Male; Neurons; 0301 basic medicine; 03 medical and health sciences; Nonlinear Dynamics; Models, Neurological; Action Potentials; Animals; Prefrontal Cortex; Nerve Net; Macaca mulatta

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.