@article {68786, title = {Distributing task-related neural activity across a cortical network through task-independent connections.}, journal = {Nature Communications}, volume = {14}, year = {2023}, month = {2023 May 18}, pages = {2851}, 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 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. 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.

}, keywords = {Action Potentials, Models, Neurological, Neurons, Synapses}, issn = {2041-1723}, doi = {10.1038/s41467-023-38529-y}, author = {Kim, Christopher M and Finkelstein, Arseny and Chow, Carson C and Svoboda, Karel and Darshan, Ran} } @article {68224, title = {Neural Algorithms and Circuits for Motor Planning.}, journal = {Annual Review Neuroscience}, volume = {45}, year = {2022}, month = {2022 Jul 08}, pages = {249-271}, abstract = {

The brain plans and executes volitional movements. The underlying patterns of neural population activity have been explored in the context of movements of the eyes, limbs, tongue, and head in nonhuman primates and rodents. How do networks of neurons produce the slow neural dynamics that prepare specific movements and the fast dynamics that ultimately initiate these movements? Recent work exploits rapid and calibrated perturbations of neural activity to test specific dynamical systems models that are capable of producing the observed neural activity. These joint experimental and computational studies show that cortical dynamics during motor planning reflect fixed points of neural activity (attractors). Subcortical control signals reshape and move attractors over multiple timescales, causing commitment to specific actions and rapid transitions to movement execution. Experiments in rodents are beginning to reveal how these algorithms are implemented at the level of brain-wide neural circuits.

}, keywords = {Algorithms, Animals, Brain, Motor Cortex, Movement, Neurons}, issn = {1545-4126}, doi = {10.1146/annurev-neuro-092021-121730}, author = {Inagaki, Hidehiko K and Chen, Susu and Daie, Kayvon and Finkelstein, Arseny and Fontolan, Lorenzo and Romani, Sandro and Svoboda, Karel} } @article {67231, title = {Attractor dynamics gate cortical information flow during decision-making.}, journal = {Nature Neuroscience}, volume = {24}, year = {2021}, month = {2021 Jun 1}, pages = {843-50}, abstract = {

Decisions are held in memory until enacted, which makes them potentially vulnerable to distracting sensory input. Gating of information flow from sensory to motor areas could protect memory from interference during decision-making, but the underlying network mechanisms are not understood. Here, we trained mice to detect optogenetic stimulation of the somatosensory cortex, with a delay separating sensation and action. During the delay, distracting stimuli lost influence on behavior over time, even though distractor-evoked neural activity percolated through the cortex without attenuation. Instead, choice-encoding activity in the motor cortex became progressively less sensitive to the impact of distractors. Reverse engineering of neural networks trained to reproduce motor cortex activity revealed that the reduction in sensitivity to distractors was caused by a growing separation in the neural activity space between attractors that encode alternative decisions. Our results show that communication between brain regions can be gated via attractor dynamics, which control the degree of commitment to an action.

}, issn = {1546-1726}, doi = {10.1038/s41593-021-00840-6}, author = {Finkelstein, Arseny and Fontolan, Lorenzo and Economo, Michael N and Li, Nuo and Romani, Sandro and Svoboda, Karel} } @article {49257, title = {Motor control: three-dimensional metric of head movements in the mouse brain.}, journal = {Current Biology : CB}, volume = {28}, year = {2018}, month = {2018 Jun 04}, pages = {R660-R662}, abstract = {

Many forms of human and animal behavior involve head movements. A new study reveals the neural code for three-dimensional head movements in the midbrain of freely moving mice.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2018.04.079}, author = {Finkelstein, Arseny} }