eLifeNeurosciencePeer-reviewed journal article
Orexin population activity precisely reflects net body movement across behavioral and metabolic states
Alexander Lee TesmeriD, Paulius ViskaitisiD, Dane DoneganiD, Edward F. BraceyiD, Nikola GrujiciD, Tommaso PatriarchiiD, Daria Peleg‐RaibsteiniD, Denis BurdakoviD
Abstract
Tracking net body movement in real time may enable the brain to estimate ongoing demands and thus better orchestrate muscle tone, energy balance, and arousal. To identify neural populations specializing in tracking net body movement, here we compared self-initiated movement-related activity across genetically-defined subcortical neurons in the mouse brain, including dopaminergic, glutamatergic, noradrenergic, and key peptidergic neurons. We show that hypothalamic orexin/hypocretin-producing neurons (HONs) are exceptionally precise movement-trackers, encoding net body movement across multiple classified behaviors with a high degree of precision, independent of head acceleration. This tracking was so precise, that video analysis of the mouse body movement reliably served as a low-cost biometric for HON population activity. The movement tracking was independent of internal nutritional states, and occurred in a communication bandwidth distinct from HON encoding of blood glucose. At key projection targets, orexin/hypocretin peptide outputs correlated with self-initiated movement in a projection-specific manner, indicating functional heterogeneity in HON outputs. Finally, we found that body movement was not encoded to the same extent in other key neural populations related to arousal or energy. These findings indicate that subcortical orchestrators of arousal and metabolism are finely tuned to encode net body movement, constituting a bridge multiplexing ongoing motor activity with internal energy resources.
- organism: mouse
- assay: electronic health records
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 1
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