@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 {68665, title = {Fast and sensitive GCaMP calcium indicators for imaging neural populations.}, journal = {Nature}, year = {2023}, month = {2023 Mar 15}, abstract = {

Calcium imaging with protein-based indicators is widely used to follow neural activity in intact nervous systems, but current protein sensors report neural activity at timescales much slower than electrical signalling and are limited by trade-offs between sensitivity and kinetics. Here we used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators. The resulting {\textquoteright}jGCaMP8{\textquoteright} sensors, based on the calcium-binding protein calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (half-rise times of 2 ms) and the highest sensitivity for neural activity reported for a protein-based calcium sensor. jGCaMP8 sensors will allow tracking of large populations of neurons on timescales relevant to neural computation.

}, issn = {1476-4687}, doi = {10.1038/s41586-023-05828-9}, author = {Zhang, Yan and Rozsa, Marton and Liang, Yajie and Bushey, Daniel and Wei, Ziqiang and Zheng, Jihong and Reep, Daniel and Broussard, Gerard Joey and Tsang, Arthur and Tsegaye, Getahun and Narayan, Sujatha and Obara, Christopher J and Lim, Jing-Xuan and Patel, Ronak and Zhang, Rongwei and Ahrens, Misha B and Turner, Glenn C and Wang, Samuel S-H and Korff, Wyatt L and Schreiter, Eric R and Svoboda, Karel and Hasseman, Jeremy P and Kolb, Ilya and Looger, Loren L} } @article {68973, title = {FIOLA: an accelerated pipeline for fluorescence imaging online analysis.}, journal = {Nature Methods}, volume = {20}, year = {2023}, month = {2023 Sep 01}, pages = {1417-1425}, abstract = {

Optical microscopy methods such as calcium and voltage imaging enable fast activity readout of large neuronal populations using light. However, the lack of corresponding advances in online algorithms has slowed progress in retrieving information about neural activity during or shortly after an experiment. This gap not only prevents the execution of real-time closed-loop experiments, but also hampers fast experiment-analysis-theory turnover for high-throughput imaging modalities. Reliable extraction of neural activity from fluorescence imaging frames at speeds compatible with indicator dynamics and imaging modalities poses a challenge. We therefore developed FIOLA, a framework for fluorescence imaging online analysis that extracts neuronal activity from calcium and voltage imaging movies at speeds one order of magnitude faster than state-of-the-art methods. FIOLA exploits algorithms optimized for parallel processing on GPUs and CPUs. We demonstrate reliable and scalable performance of FIOLA on both simulated and real calcium and voltage imaging datasets. Finally, we present an online experimental scenario to provide guidance in setting FIOLA parameters and to highlight the trade-offs of our approach.

}, keywords = {Algorithms, Calcium, Microscopy, Optical Imaging}, issn = {1548-7105}, doi = {10.1038/s41592-023-01964-2}, author = {Cai, Changjia and Dong, Cynthia and Friedrich, Johannes and Rozsa, Marton and Pnevmatikakis, Eftychios A and Giovannucci, Andrea} } @article {67211, title = {High-fidelity estimates of spikes and subthreshold waveforms from 1-photon voltage imaging in~vivo.}, journal = {Cell Reports}, volume = {35}, year = {2021}, month = {2021 Apr 06}, pages = {108954}, abstract = {

The ability to probe the membrane potential of multiple genetically defined neurons simultaneously would have a profound impact on neuroscience research. Genetically encoded voltage indicators are a promising tool for this purpose, and recent developments have achieved a high signal-to-noise ratio in\ vivo with 1-photon fluorescence imaging. However, these recordings exhibit several sources of noise and signal extraction remains a challenge. We present an improved signal extraction pipeline, spike-guided penalized matrix decomposition-nonnegative matrix factorization (SGPMD-NMF), which resolves supra- and subthreshold voltages in\ vivo. The method incorporates biophysical and optical constraints. We validate the pipeline with simultaneous patch-clamp and optical recordings from mouse layer 1 in\ vivo and with simulated and composite datasets with realistic noise. We demonstrate applications to mouse hippocampus expressing paQuasAr3-s or SomArchon1, mouse cortex expressing SomArchon1 or Voltron, and zebrafish spines expressing zArchon1.

}, issn = {2211-1247}, doi = {10.1016/j.celrep.2021.108954}, author = {Xie, Michael E and Adam, Yoav and Fan, Linlin Z and B{\"o}hm, Urs L and Kinsella, Ian and Zhou, Ding and Rozsa, Marton and Singh, Amrita and Svoboda, Karel and Paninski, Liam and Cohen, Adam E} }