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bioRxiv · 10.64898/2026.11.09.765426

Interpreting computational mechanism from multi-area neural recordings

Versteeg, C.·Michaels, J. A.·Kashefi, M.·Vermani, A.·Le, T.·Pruszynski, J. A.·Pandarinath, C.
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Abstract

Distilling computational mechanisms from neural recordings requires disambiguating intrinsic dynamics from external inputs. Here, we introduce Dynamically Interacting Systems (DynISys), a multi-compartment dynamical-systems model that infers per-area dynamics and structured inter-area communication from multi-area spiking activity. DynISys combines neural ordinary differential equation (ODE) latent dynamics with injective latent-to-neural mappings to achieve expressive and trustworthy dynamical inference. When applied to simultaneous dorsal premotor (PMd) and primary motor (M1) recordings from a continuous reaching task, DynISys accurately reconstructs neuronal responses without inventing spurious latent features. Analyzing the model's dynamics reveals putative mechanisms for motor planning and execution, with PMd-to-M1 inputs positioning a stable fixed point in M1 that encodes execution dynamics for the upcoming movement, subsequently evoked by external (non-PMd) inputs. Finally, multi-session DynISys achieves consistent latents when fit to neural recordings spanning multiple days. In summary, DynISys allows distillation of multi-area recordings into an interpretable account of distributed neural computation.

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Versteeg, C., Michaels, J. A., Kashefi, M., Vermani, A., Le, T., Pruszynski, J. A., Pandarinath, C.. 2026-11-11. Interpreting computational mechanism from multi-area neural recordings. https://doi.org/10.64898/2026.11.09.765426

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