ABSTRACT
Complex, learned motor behaviors involve the coordination of large-scale neural activity across multiple brain regions, but our understanding of the population-level dynamics within different regions tied to the same behavior remains limited. Here, we investigate the neural population dynamics underlying learned vocal production in awake-singing songbirds. We use Neuropixels probes to record the simultaneous extracellular activity of populations of neurons in two regions of the vocal motor pathway. In line with observations made in non-human primates during limb-based motor tasks, we show that the population-level activity in both the premotor nucleus HVC and the motor nucleus RA is organized on low-dimensional neural manifolds upon which coordinated neural activity is well described by temporally structured trajectories during singing behavior. Both the HVC and RA latent trajectories provide relevant information to predict vocal sequence transitions between song syllables. However, the dynamics of these latent trajectories differ between regions. Our state-space models suggest a unique and continuous-over-time correspondence between the latent space of RA and vocal output, whereas the corresponding relationship for HVC exhibits a higher degree of neural variability. We then demonstrate that comparable high-fidelity reconstruction of continuous vocal outputs can be achieved from HVC and RA neural latents and spiking activity. Unlike those that use spiking activity, however, decoding models using neural latents generalize to novel sub-populations in each region, consistent with the existence of preserved manifolds that confine vocal-motor activity in HVC and RA.
ABSTRACT
Self-injurious behavior (SIB) is a pathology observed in both humans and animals. In humans, SIB has been linked to various mental health conditions that are also associated with significant sleep disruption. In rhesus macaques, SIB consists of self-directed biting which can range from mild skin abrasions to wounds requiring veterinary care. However, only one study suggests possible sleep disruption in macaques with SIB. We evaluated sleep disruption using a noninvasive system (infra-red camera and a video surveillance program) which created videos for every movement over the nighttime hours. Nighttime activity was examined in 13 macaques (three females) of which six were classified as having SIB (one female). Each monkey was studied for a total of 6 nights spanning a period of 4 months. Measures included total movement time (TMT), time moving in the first hour (HR1), time moving in the last hour (HR11), and number of videos <10 secs, ≥10 secs, and ≥30 secs in length. Overall, SIB monkeys had higher TMT (p < 0.01), higher HR1 (p<0.001), and generated more videos ≥10 secs (p < 0.01) and ≥30 secs (p < 0.01). Thus, SIB monkeys showed significant sleep disruption. A four-fold difference between SIB and control monkeys in the ≥30 secs videos revealed many more significant awakenings in the SIB group. Overall higher nighttime activity, in the first hour but not in the last hour, is consistent with sleep-onset insomnia in humans. Whether increased nighttime activity contributes to the SIB condition during the day or, conversely, SIB causes higher nighttime activity remains undetermined.
