Model of the Songbird Nucleus HVC as a Network of Central Pattern Generators

TL;DR

This paper presents a computational model of the songbird HVC nucleus as a network of functional syllable units, explaining how inhibitory and excitatory neurons produce song patterns and how mode switching may be neuromodulation-driven.

Contribution

It introduces a novel biophysically based network model of HVC with functional syllable units that elucidate song production mechanisms and mode switching.

Findings

Model explains various HVC activity observations

Identifies testable predictions for experimental validation

Suggests neuromodulation controls mode transitions

Abstract

We propose a functional architecture of the adult songbird nucleus HVC in which the core element is a "functional syllable unit" (FSU). In this model, HVC is organized into FSUs, each of which provides the basis for the production of one syllable in vocalization. Within each FSU, the inhibitory neuron population takes one of two operational states: (A) simultaneous firing wherein all inhibitory neurons fire simultaneously, and (B) competitive firing of the inhibitory neurons. Switching between these basic modes of activity is accomplished via changes in the synaptic strengths among the inhibitory neurons. The inhibitory neurons connect to excitatory projection neurons such that during state (A) the activity of projection neurons is suppressed, while during state (B) patterns of sequential firing of projection neurons can occur. The latter state is stabilized by feedback from the projection to the inhibitory neurons. Song composition for specific species is distinguished by the manner in which different FSUs are functionally connected to each other. Ours is a computational model built with biophysically based neurons. We illustrate that many observations of HVC activity are explained by the dynamics of the proposed population of FSUs, and we identify aspects of the model that are currently testable experimentally. In addition, and standing apart from the core features of an FSU, we propose that the transition between modes may be governed by the biophysical mechanism of neuromodulation.