@article {70248, title = {Connectivity underlying motor cortex activity during goal-directed behaviour.}, journal = {Nature}, volume = {649}, year = {2026}, month = {2026 Jan 01}, pages = {416-422}, abstract = {

Neural representations of information are shaped by long-range input and local network interactions. Previous studies linking neural coding and cortical connectivity have focused on input-driven activity in the sensory cortex. Here we studied neural activity in the motor cortex while mice gathered rewards with multidirectional tongue reaching. This behaviour does not require training, allowing us to probe neural coding and connectivity before activity is shaped by extended learning. Motor cortex neurons were tuned to target location and reward outcome, and typically responded during and after movements. We studied the underlying network interactions in vivo by estimating causal neural connections using an all-optical method. Mapping connectivity between more than 20,000,000 excitatory neuron pairs showed a multi-scale columnar architecture in layer 2/3 of the motor cortex. Neurons displayed local (less than 100 {\textmu}m) like-to-like excitatory connectivity according to target-location tuning, and inhibition over longer spatial scales. Connectivity patterns comprised a continuum, with abundant sparsely connected neurons and rare densely connected neurons that function as network hubs. Hub neurons were weakly tuned to target location and reward outcome but influenced more neighbouring 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 behaviours.

}, keywords = {Animals, Female, Goals, Learning, Male, Mice, Mice, Inbred C57BL, Motor Cortex, Movement, Neural Pathways, Neurons, Reward, Tongue}, issn = {1476-4687}, doi = {10.1038/s41586-025-09758-6}, url = {https://doi.org/10.1038/s41586-025-09758-6}, author = {Finkelstein, Arseny and Daie, Kayvon and Rozsa, Marton and Darshan, Ran and Svoboda, Karel} } @article {70201, title = {Neural dynamics outside task-coding dimensions drive decision trajectories through transient amplification}, journal = {bioRxiv}, year = {2025}, month = {2025 Nov 22}, abstract = {

Most behaviors involve neural dynamics in high-dimensional activity spaces. A common approach is to extract dimensions that capture task-related variability, such as those separating stimuli or choices, yielding low-dimensional, task-aligned neural activity subspaces ({\textquotedblleft}coding dimensions{\textquotedblright}). However, whether these dimensions actively drive decisions or merely reflect underlying computations remains unclear. Moreover, neural activity outside these coding subspaces ({\textquotedblleft}residual dimensions{\textquotedblright}) is often ignored, though it could also causally shape neural dynamics driving behavior. We developed a recurrent neural network model that fits population activity and uncovers the dynamic interactions between coding and residual subspaces on single trials. Applied to electrophysiological recordings from the anterior lateral motor cortex (ALM) and motor thalamus in mice performing a delayed response task, our model demonstrates that perturbations of residual dimensions reliably alter behavioral choices, whereas perturbations of the choice dimension, which strongly encodes the animal{\textquoteright}s upcoming decision, are largely ineffective. These perturbation effects arise because residual dimensions drive transient amplification across an intermediate number of coding and residual dimensions (\~10), before the dynamics collapse into discrete attractor states corresponding to the animal{\textquoteright}s choice. By dissecting the low-dimensional variability underlying error trials, we find that it primarily shifts trajectories along residual dimensions, biasing single decisions. Residual activity in thalamus shapes cortical decision dynamics, implicating weakly selective thalamic populations in the emergence of cortical selectivity. Our findings challenge the conventional focus on low-dimensional coding subspaces as sufficient framework for understanding neural computations, demonstrating that dimensions previously considered task-irrelevant and accounting for little variance can have a critical role in driving behavior.

}, doi = {10.1101/2025.11.20.689599}, url = {https://www.biorxiv.org/content/early/2025/11/22/2025.11.20.689599}, author = {Pereira-Obilinovic, Ulises and Daie, Kayvon and Chen, Susu 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 {67965, title = {Neural Algorithms and Circuits for Motor Planning.}, journal = {Annual Reviews Neuroscience}, year = {2022}, month = {2022 Feb 22}, 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. Expected final online publication date for the , Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

}, issn = {1545-4126}, doi = {10.1146/annurev-neuro-092021-121730}, author = {Inagaki, Hidehiko K and Chen, Susu and Daie, Kayvon and Finklestein, Arseny and Fontolan, Lorenzo and Romani, Sandro and Svoboda, Karel} } @article {66007, title = {Targeted photostimulation uncovers circuit motifs supporting short-term memory.}, journal = {Nature Neuroscience}, volume = {24}, year = {2021}, month = {2021 Jan 25}, pages = {259-265}, abstract = {

Short-term memory is associated with persistent neural activity that is maintained by positive feedback between neurons. To explore the neural circuit motifs that produce memory-related persistent activity, we measured coupling between functionally characterized motor cortex neurons in mice performing a memory-guided response task. Targeted two-photon photostimulation of small (\<10) groups of neurons produced sparse calcium responses in coupled neurons over approximately 100 μm. Neurons with similar task-related selectivity were preferentially coupled. Photostimulation of different groups of neurons modulated activity in different subpopulations of coupled neurons. Responses of stimulated and coupled neurons persisted for seconds, far outlasting the duration of the photostimuli. Photostimuli produced behavioral biases that were predictable based on the selectivity of the perturbed neuronal population, even though photostimulation preceded the behavioral response by seconds. Our results suggest that memory-related neural circuits contain intercalated, recurrently connected modules, which can independently maintain selective persistent activity.

}, issn = {1546-1726}, doi = {10.1038/s41593-020-00776-3}, author = {Daie, Kayvon and Svoboda, Karel and Druckmann, Shaul} } @article {65726, title = {A comparison of neuronal population dynamics measured with calcium imaging and electrophysiology.}, journal = {PLoS Computational Biology}, volume = {16}, year = {2020}, month = {2020 Sep 15}, pages = {e1008198}, abstract = {

Calcium imaging with fluorescent protein sensors is widely used to record activity in neuronal populations. The transform between neural activity and calcium-related fluorescence involves nonlinearities and low-pass filtering, but the effects of the transformation on analyses of neural populations are not well understood. We compared neuronal spikes and fluorescence in matched neural populations in behaving mice. We report multiple discrepancies between analyses performed on the two types of data, including changes in single-neuron selectivity and population decoding. These were only partially resolved by spike inference algorithms applied to fluorescence. To model the relation between spiking and fluorescence we simultaneously recorded spikes and fluorescence from individual neurons. Using these recordings we developed a model transforming spike trains to synthetic-imaging data. The model recapitulated the differences in analyses. Our analysis highlights challenges in relating electrophysiology and imaging data, and suggests forward modeling as an effective way to understand differences between these data.

}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1008198}, author = {Wei, Ziqiang and Lin, Bei-Jung and Chen, Tsai-Wen and Daie, Kayvon and Svoboda, Karel and Druckmann, Shaul} } @article {65254, title = {Two-photon imaging with silicon photomultipliers.}, journal = {Optics Express}, volume = {27}, year = {2019}, month = {2019 Nov 25}, pages = {35830-35841}, abstract = {

We compared performance of recently developed silicon photomultipliers (SiPMs) to GaAsP photomultiplier tubes (PMTs) for two-photon imaging of neural activity. Despite higher dark counts, SiPMs match or exceed the signal-to-noise ratio of PMTs at photon rates encountered in typical calcium imaging experiments due to their low pulse height variability. At higher photon rates encountered during high-speed voltage imaging, SiPMs substantially outperform PMTs.

}, issn = {1094-4087}, doi = {10.1364/OE.27.035830}, author = {Modi, Mehrab N and Daie, Kayvon and Turner, Glenn C and Podgorski, Kaspar} } @article {48459, title = {Maintenance of persistent activity in a frontal thalamocortical loop.}, journal = {Nature}, volume = {545}, year = {2017}, month = {2017 May 03}, pages = {181-6}, abstract = {

Persistent neural activity maintains information that connects past and future events. Models of persistent activity often invoke reverberations within local cortical circuits, but long-range circuits could also contribute. Neurons in the mouse anterior lateral motor cortex (ALM) have been shown to have selective persistent activity that instructs future actions. The ALM is connected bidirectionally with parts of the thalamus, including the ventral medial and ventral anterior-lateral nuclei. We recorded spikes from the ALM and thalamus during tactile discrimination with a delayed directional response. Here we show that, similar to ALM neurons, thalamic neurons exhibited selective persistent delay activity that predicted movement direction. Unilateral photoinhibition of delay activity in the ALM or thalamus produced contralesional neglect. Photoinhibition of the thalamus caused a short-latency and near-complete collapse of ALM activity. Similarly, photoinhibition of the ALM diminished thalamic activity. Our results show that the thalamus is a circuit hub in motor preparation and suggest that persistent activity requires reciprocal excitation across multiple brain areas.

}, issn = {1476-4687}, doi = {10.1038/nature22324}, author = {Guo, Zengcai V and Inagaki, Hidehiko K and Daie, Kayvon and Druckmann, Shaul and Gerfen, Charles R and Svoboda, Karel} } @article {48493, title = {A map of anticipatory activity in mouse motor cortex.}, journal = {Neuron}, volume = {94}, year = {2017}, month = {2017 May 17}, pages = {866-879.e4}, abstract = {

Activity in the mouse anterior lateral motor cortex (ALM) instructs directional movements, often seconds before movement initiation. It is unknown whether this preparatory activity is localized to ALM or widely distributed within motor cortex. Here we imaged activity across motor cortex while mice performed a whisker-based object localization task with a delayed, directional licking response. During tactile sensation and the delay epoch, object location was represented in motor cortex areas that are medial and posterior relative to ALM, including vibrissal motor cortex. Preparatory activity appeared first in deep layers of ALM, seconds before the behavioral response, and remained localized to ALM until the behavioral response. Later, widely distributed neurons represented the outcome of the trial. Cortical area was more predictive of neuronal selectivity than laminar location or axonal projection target. Motor cortex therefore represents sensory, motor, and outcome information in a spatially organized manner.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2017.05.005}, author = {Chen, Tsai-Wen and Li, Nuo and Daie, Kayvon and Svoboda, Karel} } @article {47425, title = {Robust neuronal dynamics in premotor cortex during motor planning.}, journal = {Nature}, year = {2016}, month = {2016 Apr 13}, abstract = {

Neural activity maintains representations that bridge past and future events, often over many seconds. Network models can produce persistent and ramping activity, but the positive feedback that is critical for these slow dynamics can cause sensitivity to perturbations. Here we use electrophysiology and optogenetic perturbations in the mouse premotor cortex to probe the robustness of persistent neural representations during motor planning. We show that preparatory activity is remarkably robust to large-scale unilateral silencing: detailed neural dynamics that drive specific future movements were quickly and selectively restored by the network. Selectivity did not recover after bilateral silencing of the premotor cortex. Perturbations to one hemisphere are thus corrected by information from the other hemisphere. Corpus callosum bisections demonstrated that premotor cortex hemispheres can maintain preparatory activity independently. Redundancy across selectively coupled modules, as we observed in the premotor cortex, is a hallmark of robust control systems. Network models incorporating these principles show robustness that is consistent with data.

}, issn = {1476-4687}, doi = {10.1038/nature17643}, author = {Li, Nuo and Daie, Kayvon and Svoboda, Karel and Druckmann, Shaul} }