Main Menu (Mobile)- Block

Main Menu - Block

custom | custom

Search Results

filters_region_cap | custom

Filter

facetapi-Q2b17qCsTdECvJIqZJgYMaGsr8vANl1n | block
facetapi-W9JlIB1X0bjs93n1Alu3wHJQTTgDCBGe | block
facetapi-61yz1V0li8B1bixrCWxdAe2aYiEXdhd0 | block
facetapi-PV5lg7xuz68EAY8eakJzrcmwtdGEnxR0 | block
general_search_page-panel_pane_1 | views_panes

126 Janelia Publications

Showing 1-10 of 126 results
Your Criteria:
    11/13/22 | Brain-wide measurement of protein turnover with high spatial and temporal resolution
    Boaz Mohar , Jonathan B. Grimm , Ronak Patel , Timothy A. Brown , Paul Tillberg , Luke D. Lavis , Nelson Spruston , Karel Svoboda
    bioRxiv. 2022 Nov 13:. doi: 10.1101/2022.11.12.516226

    Cells regulate function by synthesizing and degrading proteins. This turnover ranges from minutes to weeks, as it varies across proteins, cellular compartments, cell types, and tissues. Current methods for tracking protein turnover lack the spatial and temporal resolution needed to investigate these processes, especially in the intact brain, which presents unique challenges. We describe a pulse-chase method (DELTA) for measuring protein turnover with high spatial and temporal resolution throughout the body, including the brain. DELTA relies on rapid covalent capture by HaloTag of fluorophores that were optimized for bioavailability in vivo. The nuclear protein MeCP2 showed brain region- and cell type-specific turnover. The synaptic protein PSD95 was destabilized in specific brain regions by behavioral enrichment. A novel variant of expansion microscopy further facilitated turnover measurements at individual synapses. DELTA enables studies of adaptive and maladaptive plasticity in brain-wide neural circuits.

    View Publication Page
    Svoboda Lab
    10/04/22 | The Neurodata Without Borders ecosystem for neurophysiological data science.
    Rubel O, Tritt A, Ly R, Dichter BK, Ghosh S, Niu L, Baker P, Soltesz I, Ng L, Svoboda K, Frank L, Bouchard KE
    eLife. 2022 Oct 04;11:. doi: 10.7554/eLife.78362

    The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB's impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

    View Publication Page
    Romani LabSvoboda Lab
    07/08/22 | Neural Algorithms and Circuits for Motor Planning.
    Inagaki HK, Chen S, Daie K, Finkelstein A, Fontolan L, Romani S, Svoboda K
    Annual Review Neuroscience. 2022 Jul 08;45:249-271. doi: 10.1146/annurev-neuro-092021-121730

    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.

    View Publication Page
    Svoboda LabDarshan Lab
    06/18/22 | Distributing task-related neural activity across a cortical network through task-independent connections
    Christopher M. Kim , Arseny Finkelstein , Carson C. Chow , Karel Svoboda , Ran Darshan
    bioRxiv. 2022 Jun 18:. doi: 10.1101/2022.06.17.496618

    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.

    View Publication Page
    Svoboda Lab
    03/17/22 | A midbrain-thalamus-cortex circuit reorganizes cortical dynamics to initiate movement.
    Inagaki HK, Chen S, Ridder MC, Sah P, Li N, Yang Z, Hasanbegovic H, Gao Z, Gerfen CR, Svoboda K
    Cell. 2022 Mar 17;185(8):1065. doi: 10.1016/j.cell.2022.02.006

    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.

    View Publication Page
    Romani LabSvoboda Lab
    02/22/22 | Neural Algorithms and Circuits for Motor Planning.
    Inagaki HK, Chen S, Daie K, Finklestein A, Fontolan L, Romani S, Svoboda K
    Annual Reviews Neuroscience. 2022 Feb 22:. doi: 10.1146/annurev-neuro-092021-121730

    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.

    View Publication Page
    Svoboda LabSaalfeld LabSternson LabTillberg Lab
    12/01/21 | EASI-FISH for thick tissue defines lateral hypothalamus spatio-molecular organization.
    Wang Y, Eddison M, Fleishman G, Weigert M, Xu S, Wang T, Rokicki K, Goina C, Henry FE, Lemire AL, Schmidt U, Yang H, Svoboda K, Myers EW, Saalfeld S, Korff W, Sternson SM, Tillberg PW
    Cell. 2021 Dec 01;184(26):6361. doi: 10.1016/j.cell.2021.11.024

    Determining the spatial organization and morphological characteristics of molecularly defined cell types is a major bottleneck for characterizing the architecture underpinning brain function. We developed Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH) to survey gene expression in brain tissue, as well as a turnkey computational pipeline to rapidly process large EASI-FISH image datasets. EASI-FISH was optimized for thick brain sections (300 μm) to facilitate reconstruction of spatio-molecular domains that generalize across brains. Using the EASI-FISH pipeline, we investigated the spatial distribution of dozens of molecularly defined cell types in the lateral hypothalamic area (LHA), a brain region with poorly defined anatomical organization. Mapping cell types in the LHA revealed nine spatially and molecularly defined subregions. EASI-FISH also facilitates iterative reanalysis of scRNA-seq datasets to determine marker-genes that further dissociated spatial and morphological heterogeneity. The EASI-FISH pipeline democratizes mapping molecularly defined cell types, enabling discoveries about brain organization.

    View Publication Page
    Svoboda LabMouseLight
    11/12/21 | Accurate localization of linear probe electrodes across multiple brains.
    Liu LD, Chen S, Economo MN, Li N, Svoboda K
    eNeuro. 2021 Nov 12;8(6):ENEURO.0241-21.2021
    Romani LabSvoboda Lab
    06/01/21 | Attractor dynamics gate cortical information flow during decision-making.
    Finkelstein A, Fontolan L, Economo MN, Li N, Romani S, Svoboda K
    Nature Neuroscience. 2021 Jun 1;24(6):843-50. doi: 10.1038/s41593-021-00840-6

    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.

    View Publication Page
    04/16/21 | Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings.
    Steinmetz NA, Aydın Ç, Lebedeva A, Okun M, Pachitariu M, Bauza M, Beau M, Bhagat J, Böhm C, Broux M, Chen S, Colonell J, Gardner RJ, Karsh B, Kloosterman F, Kostadinov D, Mora-Lopez C, O'Callaghan J, Park J, Putzeys J, Sauerbrei B, van Daal RJ, Vollan AZ, Wang S, Welkenhuysen M, Ye Z, Dudman JT, Dutta B, Hantman AW, Harris KD, Lee AK, Moser EI, O'Keefe J, Renart A, Svoboda K, Häusser M, Haesler S, Carandini M, Harris TD
    Science. 2021 Apr 16;372(6539):. doi: 10.1126/science.abf4588

    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.

    View Publication Page