Thalamocortical dynamics in a complex learned behavior
Performing learned behaviors requires animals to produce precisely timed motor sequences. The underlying neuronal circuits must convert incoming spike trains into precisely timed firing to indicate the onset of crucial sensory cues or to carry out well-coordinated muscle movements. Birdsong is a remarkable example of a complex, learned and precisely timed natural behavior which is controlled by a brainstem-thalamocortical feedback loop. Projection neurons within the zebra finch cortical nucleus HVC (used as a proper name), produce precisely timed, highly reliable and ultra-sparse neural sequences that are thought to underlie song dynamics. However, the origin of short timescale dynamics of the song is debated. One model posits that these dynamics reside in HVC and are mediated through a synaptic chain mechanism. Alternatively, the upstream motor thalamic nucleus Uveaformis (Uva), could drive HVC bursts as part of a brainstem-thalamocortical distributed network. Using focal temperature manipulation we found that the song dynamics reside chiefly in HVC. We then characterized the activity of thalamic nucleus Uva, which provides input to HVC. We developed a lightweight (~1 g) microdrive for juxtacellular recordings and with it performed the very first extracellular single unit recordings in Uva during song. Recordings revealed HVC-projecting Uva neurons contain timing information during the song, but compared to HVC neurons, fire densely in time and are much less reliable. Computational models of Uva-driven HVC neurons estimated that a high degree of synaptic convergence is needed from Uva to HVC to overcome the inconsistency of Uva firing patterns. However, axon terminals of single Uva neurons exhibit low convergence within HVC such that each HVC neuron receives input from 2-7 Uva neurons. These results suggest that thalamus maintains sequential cortical activity during song but does not provide unambiguous timing information. Our observations are consistent with a model in which the brainstem-thalamocortical feedback loop acts at the syllable timescale (~100 ms) and does not support a model in which the brainstem-thalamocortical feedback loop acts at fast timescale (~10 ms) to generate sequences within cortex. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2024-02-14. Recording duration: 00:39:45.
Neural control of vocal interactions in songbirds
During conversations we rapidly switch between listening and speaking which often requires withholding or delaying our speech in order to hear others and avoid overlapping. This capacity for vocal turn-taking is exhibited by non-linguistic species as well, however the neural circuit mechanisms that enable us to regulate the precise timing of our vocalizations during interactions are unknown. We aim to identify the neural mechanisms underlying the coordination of vocal interactions. Therefore, we paired zebra finches with a vocal robot (1Hz call playback) and measured the bird’s call response times. We found that individual birds called with a stereotyped delay in respect to the robot call. Pharmacological inactivation of the premotor nucleus HVC revealed its necessity for the temporal coordination of calls. We further investigated the contributing neural activity within HVC by performing intracellular recordings from premotor neurons and inhibitory interneurons in calling zebra finches. We found that inhibition is preceding excitation before and during call onset. To test whether inhibition guides call timing we pharmacologically limited the impact of inhibition on premotor neurons. As a result zebra finches converged on a similar delay time i.e. birds called more rapidly after the vocal robot call suggesting that HVC inhibitory interneurons regulate the coordination of social contact calls. In addition, we aim to investigate the vocal turn-taking capabilities of the common nightingale. Male nightingales learn over 100 different song motifs which are being used in order to attract mates or defend territories. Previously, it has been shown that nightingales counter-sing with each other following a similar temporal structure to human vocal turn-taking. These animals are also able to spontaneously imitate a motif of another nightingale. The neural mechanisms underlying this behaviour are not yet understood. In my lab, we further probe the capabilities of these animals in order to access the dynamic range of their vocal turn taking flexibility.