Behavior-dLDS: A decomposed linear dynamical systems model for neural activity partially constrained by behavior
Brain-wide recordings of large-scale networks of neurons now provide an unprecedented view into how the brain drives behavior. However, brain activity contains both information directly related to behavior as well as the potential for many internal computations. Moreover, observable behavior is executed not only by the brain, but also by the spinal cord and peripheral nervous system. Behavior is a coarse-grained product of neural activity, and we thus take the view that it can be best represented by lower-dimensional latent neural dynamics. Capturing this indirect relationship while disambiguating behavior-generating networks from internal computations running in parallel requires new mod...
| Authors | Eva Yezerets, En Yang, Misha B. Ahrens et al. |
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| Primary category | q-bio.NC |
| Published | 5 March 2026 |
| Last updated at source | 4 May 2026 |
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