Direct neural perturbations reveal a dynamical mechanism for robust computation

Abstract

The rich repertoire of skilled mammalian behavior is the product of neural circuits that generate robust and flexible patterns of activity distributed across populations of neurons. Decades of associative studies have linked many behaviors to specific patterns of population activity, but association alone cannot reveal the dynamical mechanisms that shape those patterns. Are local neural circuits high- dimensional dynamical reservoirs able to generate arbitrary superpositions of patterns with appropriate excitation? Or might circuit dynamics be shaped in response to behavioral context so as to generate only the low-dimensional patterns needed for the task at hand? Here, we address these questions within primate motor cortex by delivering optogenetic and electrical microstimulation perturbations during reaching behavior. We develop a novel analytic approach that relates measured activity to theoretically tractable, dynamical models of excitatory and inhibitory neurons. This computational model captures the dynamical effects of these perturbations and demonstrates that motor cortical activity during reaching is shaped by a self-contained, low-dimensional dynamical system. The subspace containing task-relevant dynamics proves to be oriented so as to be robust to strong non-normal amplification within cortical circuits. This task dynamics space exhibits a privileged causal relationship with behavior, in that stimulation in motor cortex perturb reach kinematics only to the extent that it alters neural states within this subspace. Our results resolve long-standing questions about the dynamical structure of cortical activity associated with movement, and illuminate the dynamical perturbation experiments needed to understand how neural circuits throughout the brain generate complex behavior.

Large-scale high-density brain-wide neural recording in nonhuman primates

“…Second, in contrast with many passive electrodes, it is not currently possible to use the Neuropixels probe to deliver intracortical microstimulation (ICMS), though future versions of the probe may add this functionality. The Neuropixels technology is, however, capable of recording while stimulating through external electrodes, as recently demonstrated by O’Shea, Duncker, et al 13 . Third, the Neuropixels 1.0-NHP design is not explicitly optimized for chronic implantation.…”

“…The capabilities provided by these approaches have led to important new discoveries, such as a continuous attractor network of grid cells in the rat hippocampus 9 , establishing a causal topographical mapping between activity in the cortex and striatum in mice 4 , and revealing how thirst modulates brain-wide neural population dynamics in mice 7 . The Neuropixels 1.0 probe has also been used to record neurons acutely in nonhuman primates (NHPs) like macaques [10][11][12][13] and in humans 14,15 , but their short length (10 mm) restricts access to all but the most superficial targets, and the thinness of the shanks (24 µm) renders them fragile and difficult to insert through primate dura mater.…”

Inferring context-dependent computations through linear approximations of prefrontal cortex dynamics

“…In addition to this role in inputs selection, our analysis revealed that non-normal dynamics might additionally result in the transient amplification of relevant inputs in PFC. Non-normal transient amplification had previously been proposed to play a role in the processing of external inputs [21][22][23] , as well as computations as varied as maintaining inputs in working-memory 24 , generating the transient neural activations required for generating movements 25 and mediating robustness to perturbations 26 . Our observation of two distinct stages in PFC dynamics during decision formation is evocative of a recently proposed mechanisms relying on transient amplification to optimally load information onto an attractor 22 .…”

“…While here we fitted activity from only a relatively short time window from each trial (the 750ms of random dots presentation), recent findings suggests that linear models may not be outperformed by non-linear models in capturing cortical dynamics even over longer time-windows 45 . Nonetheless, analyses based on non-linear models are becoming increasingly common, given their flexibility in capturing very complex neural data 35 and the interest in modeling biological constraints that cannot be captured by linear models 46 (but see 26 ).…”

“…Apart from this role in inputs selection, our analysis revealed how non-normal dynamics might additionally result in the transient amplification of relevant inputs in PFC. Non-normal transient amplification was previously proposed to be involved in the processing of external inputs 17,[25][26][27][28] and their maintenance in working-memory 29 , in producing transient activations during movement generation 30 and in mediating robustness to perturbations 31 .…”