@article {69104, title = {Connectivity underlying motor cortex activity during naturalistic goal-directed behavior.}, journal = {bioRxiv}, year = {2023}, month = {2023 Nov 26}, abstract = {

Neural representations of information are shaped by local network interactions. Previous studies linking neural coding and cortical connectivity focused on stimulus selectivity in the sensory cortex\ 1{\textendash}4. Here we study neural activity in the motor cortex during naturalistic behavior in which mice gathered rewards with multidirectional tongue reaching. This behavior does not require training and thus allowed us to probe neural coding and connectivity in motor cortex before its activity is shaped by learning a specific task. Neurons typically responded during and after reaching movements and exhibited conjunctive tuning to target location and reward outcome. We used an all-optical\ 5,4,6,7\ method for large-scale causal functional connectivity mapping\ in vivo. Mapping connectivity between \> 20,000,000 excitatory neuronal pairs revealed fine-scale columnar architecture in layer 2/3 of the motor cortex. Neurons displayed local (\< 100 {\textmu}m) like-to-like connectivity according to target-location tuning, and inhibition over longer spatial scales. Connectivity patterns comprised a continuum, with abundant weakly connected neurons and sparse strongly connected neurons that function as network hubs. Hub neurons were weakly tuned to target-location and reward-outcome but strongly influenced neighboring neurons. This network of neurons, encoding location and outcome of movements to different motor goals, may be a general substrate for rapid learning of complex, goal-directed behaviors.

}, doi = {10.1101/2023.11.25.568673}, url = {https://doi.org/10.1101/2023.11.25.568673}, author = {Arseny Finkelstein and Kayvon Daie and M{\'a}rton R{\'o}zsa and Ran Darshan and Karel Svoboda} } @article {68166, title = {Distributing task-related neural activity across a cortical network through task-independent connections}, journal = {bioRxiv}, year = {2022}, month = {2022 Jun 18}, abstract = {

Task-related neural activity is widespread across populations of neurons during goal-directed behaviors. However, little is known about the synaptic reorganization and circuit mechanisms that lead to broad activity changes. Here we trained a limited subset of neurons in a spiking network with strong synaptic interactions to reproduce the activity of neurons in the motor cortex during a decision-making task. We found that task-related activity, resembling the neural data, emerged across the network, even in the untrained neurons. Analysis of trained networks showed that strong untrained synapses, which were independent of the task and determined the dynamical state of the network, mediated the spread of task-related activity. Optogenetic perturbations suggest that the motor cortex is strongly-coupled, supporting the applicability of the mechanism to cortical networks. Our results reveal a cortical mechanism that facilitates distributed representations of task-variables by spreading the activity from a subset of plastic neurons to the entire network through task-independent strong synapses.

}, doi = {10.1101/2022.06.17.496618}, url = {https://doi.org/10.1101/2022.06.17.496618}, author = {Christopher M. Kim and Arseny Finkelstein and Carson C. Chow and Karel Svoboda and Ran Darshan} }