@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 {69774, title = {Neuropixels Opto: Combining high-resolution electrophysiology and optogenetics}, journal = {bioRxiv}, year = {2025}, month = {2025 Feb 06}, abstract = {

High-resolution extracellular electrophysiology is the gold standard for recording spikes from distributed neural populations, and is especially powerful when combined with optogenetics for manipulation of specific cell types with high temporal resolution. We integrated these approaches into prototype Neuropixels Opto probes, which combine electronic and photonic circuits. These devices pack 960 electrical recording sites and two sets of 14 light emitters onto a 1 cm shank, allowing spatially addressable optogenetic stimulation with blue and red light. In mouse cortex, Neuropixels Opto probes delivered high-quality recordings together with spatially addressable optogenetics, differentially activating or silencing neurons at distinct cortical depths. In mouse striatum and other deep structures, Neuropixels Opto probes delivered efficient optotagging, facilitating the identification of two cell types in parallel. Neuropixels Opto probes represent an unprecedented tool for recording, identifying, and manipulating neuronal populations.

}, doi = {10.1101/2025.02.04.636286}, url = {https://www.biorxiv.org/content/early/2025/02/06/2025.02.04.636286}, author = {Lakunina, Anna and Socha, Karolina Z and Ladd, Alexander and Bowen, Anna J and Chen, Susu and Colonell, Jennifer and Doshi, Anjal and Karsh, Bill and Krumin, Michael and Kulik, Pavel and Li, Anna and Neutens, Pieter and O{\textquoteright}Callaghan, John and Olsen, Meghan and Putzeys, Jan and Tilmans, Harrie AC and Ye, Zhiwen and Welkenhuysen, Marleen and H{\"a}usser, Michael and Koch, Christof and Ting, Jonathan T. and Neuropixels Opto Consortium and Dutta, Barun and Harris, Timothy D and Steinmetz, Nicholas A and Svoboda, Karel and Siegle, Joshua H and Carandini, Matteo} } @article {70133, title = {Ultra-high-density Neuropixels probes improve detection and identification in neuronal recordings.}, journal = {Neuron}, volume = {113}, year = {2025}, month = {2025 Dec 3}, abstract = {

To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single-neuron and single-spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). Using NP Ultra, neuronal yield in mouse visual cortex recordings increased by more than 2-fold. With ultra-high spatial resolution, we discovered that a feature of extracellular waveforms, the spatial extent or "footprint," distinguished axonal from somatic recordings. In addition, three genetically identified cortical cell types could be discriminated from one another with \~{}80\% accuracy and from other neurons with \~{}85\% accuracy. NP Ultra improves yield, detection of subcellular compartments, and cell type identification to enable a more powerful dissection of neural circuit activity during behavior.

bioRxiv preprint: doi.org/10.1101/2023.08.23.554527

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2025.08.030}, url = {https://doi.org/10.1016/j.neuron.2025.08.030}, author = {Ye, Zhiwen and Shelton, Andrew M and Shaker, Jordan R and Boussard, Julien and Colonell, Jennifer and Birman, Daniel and Manavi, Sahar and Chen, Susu and Windolf, Charlie and Hurwitz, Cole and Yu, Han and Namima, Tomoyuki and Pedraja, Federico and Weiss, Shahaf and Raducanu, Bogdan C and Ness, Torbj{\o}rn V and Jia, Xiaoxuan and Mastroberardino, Giulia and Rossi, L Federico and Carandini, Matteo and H{\"a}usser, Michael and Einevoll, Gaute T and Laurent, Gilles and Sawtell, Nathaniel B and Bair, Wyeth and Pasupathy, Anitha and Mora Lopez, Carolina and Dutta, Barundeb and Paninski, Liam and Siegle, Joshua H and Koch, Christof and Olsen, Shawn R and Harris, Timothy D and Steinmetz, Nicholas A} } @article {69185, title = {Brain-wide neural activity underlying memory-guided movement.}, journal = {Cell}, volume = {187}, year = {2024}, month = {2024 Feb 01}, pages = {676-691.e16}, abstract = {

Behavior relies on activity in structured neural circuits that are distributed across the brain, but most experiments probe neurons in a single area at a time. Using multiple Neuropixels probes, we recorded from multi-regional loops connected to the anterior lateral motor cortex (ALM), a circuit node mediating memory-guided directional licking. Neurons encoding sensory stimuli, choices, and actions were distributed across the brain. However, choice coding was concentrated in the ALM and subcortical areas receiving input from the ALM in an ALM-dependent manner. Diverse orofacial movements were encoded in the hindbrain; midbrain; and, to a lesser extent, forebrain. Choice signals were first detected in the ALM and the midbrain, followed by the thalamus and other brain areas. At movement initiation, choice-selective activity collapsed across the brain, followed by new activity patterns driving specific actions. Our experiments provide the foundation for neural circuit models of decision-making and movement initiation.

}, keywords = {Brain, Memory, Movement, Neurons, Thalamus}, issn = {1097-4172}, doi = {10.1016/j.cell.2023.12.035}, author = {Chen, Susu and Liu, Yi and Wang, Ziyue Aiden and Colonell, Jennifer and Liu, Liu D and Hou, Han and Tien, Nai-Wen and Wang, Tim and Harris, Timothy and Druckmann, Shaul and Li, Nuo and Svoboda, Karel} } @article {68968, title = {Ultra-high density electrodes improve detection, yield, and cell type specificity of brain recordings.}, journal = {bioRxiv}, year = {2023}, month = {2023 Aug 25}, abstract = {

To study the neural basis of behavior, we require methods to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology is a principal method for achieving this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To overcome these limitations, we developed a silicon probe with significantly smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device measures neuronal activity at ultra-high densities (\>1300 sites per mm, 10 times higher than previous probes), with 6 {\textmu}m center-to-center spacing and low noise. This device effectively comprises an implantable voltage-sensing camera that captures a planar image of a neuron{\textquoteright}s electrical field. We introduce a new spike sorting algorithm optimized for these probes and use it to find that the yield of visually-responsive neurons in recordings from mouse visual cortex improves \~{}3-fold. Recordings across multiple brain regions and four species revealed a subset of unexpectedly small extracellular action potentials not previously reported. Further experiments determined that, in visual cortex, these do not correspond to major subclasses of interneurons and instead likely reflect recordings from axons. Finally, using ground-truth identification of cortical inhibitory cell types with optotagging, we found that cell type was discriminable with approximately 75\% success among three types, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, sampling bias, and cell type classification.

}, doi = {10.1101/2023.08.23.554527}, author = {Ye, Zhiwen and Shelton, Andrew M and Shaker, Jordan R and Boussard, Julien and Colonell, Jennifer and Manavi, Sahar and Chen, Susu and Windolf, Charlie and Hurwitz, Cole and Namima, Tomoyuki and Pedraja, Federico and Weiss, Shahaf and Raducanu, Bogdan and Ness, Torbj{\o}rn V and Einevoll, Gaute T and Laurent, Gilles and Sawtell, Nathaniel B and Bair, Wyeth and Pasupathy, Anitha and Mora Lopez, Carolina and Dutta, Barun and Paninski, Liam and Siegle, Joshua H and Koch, Christof and Olsen, Shawn R and Harris, Timothy D and Steinmetz, Nicholas A} } @article {67951, title = {A midbrain-thalamus-cortex circuit reorganizes cortical dynamics to initiate movement.}, journal = {Cell}, volume = {185}, year = {2022}, month = {2022 Mar 17}, pages = {1065}, abstract = {

Motor behaviors are often planned long before execution but only released after specific sensory events. Planning and execution are each associated with distinct patterns of motor cortex activity. Key questions are how these dynamic activity patterns are generated and how they relate to behavior. Here, we investigate the multi-regional neural circuits that link an auditory "Go cue" and the transition from planning to execution of directional licking. Ascending glutamatergic neurons in the midbrain reticular and pedunculopontine nuclei show short latency and phasic changes in spike rate that are selective for the Go cue. This signal is transmitted via the thalamus to the motor cortex, where it triggers a rapid reorganization of motor cortex state from planning-related activity to a motor command, which in turn drives appropriate movement. Our studies show how midbrain can control cortical dynamics via the thalamus for rapid and precise motor behavior.

}, issn = {1097-4172}, doi = {10.1016/j.cell.2022.02.006}, author = {Inagaki, Hidehiko K and Chen, Susu and Ridder, Margreet C and Sah, Pankaj and Li, Nuo and Yang, Zidan and Hasanbegovic, Hana and Gao, Zhenyu and Gerfen, Charles R 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 {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 {65319, title = {Accurate localization of linear probe electrodes across multiple brains.}, journal = {eNeuro}, volume = {8}, year = {2021}, month = {2021 Nov 12}, pages = {ENEURO.0241-21.2021}, author = {Liu, Liu D. and Chen, Susu and Economo, Michael N. and Li, Nuo and Svoboda, Karel} } @article {67263, title = {Hunger or thirst state uncertainty is resolved by outcome evaluation in medial prefrontal cortex to guide decision-making.}, journal = {Nature Neuroscience}, volume = {24}, year = {2021}, month = {2021 Jul 01}, pages = {907-912}, abstract = {

Physiological need states direct decision-making toward re-establishing homeostasis. Using a two-alternative forced choice task for mice that models elements of human decisions, we found that varying hunger and thirst states caused need-inappropriate choices, such as food seeking when thirsty. These results show limits on interoceptive knowledge of hunger and thirst states to guide decision-making. Instead, need states were identified after food and water consumption by outcome evaluation, which depended on the medial prefrontal cortex.

}, issn = {1546-1726}, doi = {10.1038/s41593-021-00850-4}, author = {Eiselt, Anne-Kathrin and Chen, Susu and Chen, Jim and Arnold, Jon and Kim, Tahnbee and Pachitariu, Marius and Sternson, Scott M} } @article {67232, title = {Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings.}, journal = {Science}, volume = {372}, year = {2021}, month = {2021 Apr 16}, abstract = {

Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.

}, issn = {1095-9203}, doi = {10.1126/science.abf4588}, author = {Steinmetz, Nicholas A and Ayd{\i}n, {\c C}a{\u g}atay and Lebedeva, Anna and Okun, Michael and Pachitariu, Marius and Bauza, Marius and Beau, Maxime and Bhagat, Jai and B{\"o}hm, Claudia and Broux, Martijn and Chen, Susu and Colonell, Jennifer and Gardner, Richard J and Karsh, Bill and Kloosterman, Fabian and Kostadinov, Dimitar and Mora-Lopez, Carolina and O{\textquoteright}Callaghan, John and Park, Junchol and Putzeys, Jan and Sauerbrei, Britton and van Daal, Rik J J and Vollan, Abraham Z and Wang, Shiwei and Welkenhuysen, Marleen and Ye, Zhiwen and Dudman, Joshua T and Dutta, Barundeb and Hantman, Adam W and Harris, Kenneth D and Lee, Albert K and Moser, Edvard I and O{\textquoteright}Keefe, John and Renart, Alfonso and Svoboda, Karel and H{\"a}usser, Michael and Haesler, Sebastian and Carandini, Matteo and Harris, Timothy D} } @article {65226, title = {Spatiotemporal constraints on optogenetic inactivation in cortical circuits.}, journal = {eLife}, volume = {8}, year = {2019}, month = {2019 Nov 18}, abstract = {

Optogenetics allows manipulations of genetically and spatially defined neuronal populations with excellent temporal control. However, neurons are coupled with other neurons over multiple length scales, and the effects of localized manipulations thus spread beyond the targeted neurons. We benchmarked several optogenetic methods to inactivate small regions of neocortex. Optogenetic excitation of GABAergic neurons produced more effective inactivation than light-gated ion pumps. Transgenic mice expressing the light-dependent chloride channel GtACR1 produced the most potent inactivation. Generally, inactivation spread substantially beyond the photostimulation light, caused by strong coupling between cortical neurons. Over some range of light intensity, optogenetic excitation of inhibitory neurons reduced activity in these neurons, together with pyramidal neurons, a signature of inhibition-stabilized neural networks ({\textquoteright}paradoxical effect{\textquoteright}). The offset of optogenetic inactivation was followed by rebound excitation in a light dose-dependent manner, limiting temporal resolution. Our data offer guidance for the design of optogenetics experiments.

}, issn = {2050-084X}, doi = {10.7554/eLife.48622}, author = {Li, Nuo and Chen, Susu and Guo, Zengcai V and Chen, Han and Huo, Yan and Inagaki, Hidehiko K and Chen, Guang and Davis, Courtney and Hansel, David and Guo, Caiying and Svoboda, Karel} }