Inference and Decoding of Motor Cortex Low-Dimensional Dynamics via Latent State-Space Models

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
Mehdi Aghagolzadeh, Wilson Truccolo

Abstract

Motor cortex neuronal ensemble spiking activity exhibits strong low-dimensional collective dynamics (i.e., coordinated modes of activity) during behavior. Here, we demonstrate that these low-dimensional dynamics, revealed by unsupervised latent state-space models, can provide as accurate or better reconstruction of movement kinematics as direct decoding from the entire recorded ensemble. Ensembles of single neurons were recorded with triple microelectrode arrays (MEAs) implanted in ventral and dorsal premotor (PMv, PMd) and primary motor (M1) cortices while nonhuman primates performed 3-D reach-to-grasp actions. Low-dimensional dynamics were estimated via various types of latent state-space models including, for example, Poisson linear dynamic system (PLDS) models. Decoding from low-dimensional dynamics was implemented via point process and Kalman filters coupled in series. We also examined decoding based on a predictive subsampling of the recorded population. In this case, a supervised greedy procedure selected neuronal subsets that optimized decoding performance. When comparing decoding based on predictive subsampling and latent state-space models, the size of the neuronal subset was set to the same number of latent state dim...Continue Reading

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Citations

Jul 26, 2016·Frontiers in Neuroscience·Karen E Schroeder, Cynthia A Chestek
Nov 11, 2017·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Stefan L SumskySabato Santaniello
Feb 6, 2019·Journal of Neural Engineering·Shizhao LiuZhe Chen
May 17, 2019·Journal of Neural Engineering·Yuxiao YangMaryam M Shanechi
Nov 5, 2019·PLoS Computational Biology·Michael E RuleGuido Sanguinetti
Dec 2, 2017·Journal of Neural Engineering·Joseph G MakinPhilip N Sabes
Jan 29, 2021·Nature Communications·Hamidreza AbbaspourazadMaryam M Shanechi
Dec 1, 2020·Journal of Neural Engineering·Yuxiao YangMaryam M Shanechi
Sep 21, 2021·Physiological Reviews·Chethan Pandarinath, Sliman J Bensmaia

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