Mapping Neural Architectures Onto Acoustic Features of Birdsong

Abstract

The motor pathway responsible for the complex vocalizations of songbirds has been extensively characterized, both in terms of intrinsic and synaptic physiology in vitro and in terms of the spatiotemporal patterns of neural activity in vivo. However, the relationship between the neural architecture of the song motor pathway and the acoustic features of birdsong is not well understood. Using a computational model of the song motor pathway and the songbird vocal organ, we investigate the relationship between song production and the neural connectivity of nucleus HVc (used as a proper name) and the robust nucleus of the archistriatum (RA). Drawing on recent experimental observations, our neural model contains a population of sequentially bursting HVc neurons driving the activity of a population of RA neurons. An important focus of our investigations is the contribution of intrinsic circuitry within RA to the acoustic output of the model. We find that the inclusion of inhibitory interneurons in the model can substantially influence the features of song syllables, and we illustrate the potential for subharmonic behavior in RA in response to forcing by HVc neurons. Our results demonstrate the association of specific acoustic features with specific neural connectivities and support the view that intrinsic circuitry within RA may play a critical role in generating the features of birdsong.

Dynamical model of birdsong maintenance and control

“…It will initiate, in a manner not addressed here, sparse bursts of high frequency ͑613± 210 Hz͒ spikes projecting to the RA and area X. The RA processes these sparse bursts in a fashion we have explored elsewhere [11], while the AFP relays these sparse bursts to the RA producing a time delay ⌬T whose biophysical origin we will explore.…”

“…2 where we have two PNs and one IN to represent the nucleus. A larger model with order of 100 PNs projecting to muscle control and 100 PNs projecting to respiration control along with 3-5 PNs in each population would be required to represent the way the RA nucleus distributes command signals from many HVc RA projecting neurons and determines details of syllables in each motif of a song [11]. Our focus here is in the mechanisms which control the synaptic plasticity at the HVc→ RA junctions, and what we reveal in our calculations will be operating at each such junction in a larger model.…”

“…Our goal is to understand the dynamics of the synaptic plasticity which can provide stable connections for the fully developed matrix of connections in adult songbirds. Our exploration of the song production through stabilized, and thus fixed over the short-term of song production, HVc→ RA connections is in [11].…”

“…It is not clear yet whether this would provide an interesting representation of the already simplified biological physics of this network. In connecting the dynamics explored here of the coupled premotor and AFP pathways with the mechanisms for the generation of song [11] we may need a much larger network for each nucleus, and then the issue of simplification of the nodes may become essential.…”

Stable propagation of a burst through a one-dimensional homogeneous excitatory chain model of songbird nucleus HVC

“…experimentalists [6,27] and assumed in several theoretical studies [28,29,30]. In a recent experiment [26], calcium imaging and timing studies of intracellular recordings have suggested the existence of synfire chains in the visual cortices of mice and cats but no similar imaging study has yet been carried out for songbirds.…”