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A Distributed Neural Code in the Dentate Gyrus and in CA1

NEURON 2020年第4期107卷 703-+页

作者： Stefanini, Fabio Kushnir, Lyudmila Jimenez, Jessica C. Jennings, Joshua H. Woods, Nicholas, I Stuber, Garret D. Kheirbek, Mazen A. Hen, Rene Fusi, Stefano Columbia Univ Coll Phys & Surg Ctr Theoret Neurosci New York NY 10027 USA Columbia Univ Mortimer B Zuckerman Mind Brain Behav Inst New York NY 10027 USA PSL Res Univ Dept Etud Cognitives INSERM GNT LNCEcole Normale Super F-75005 Paris France Columbia Univ Dept Neurosci New York NY 10027 USA Columbia Univ Dept Psychiat New York NY 10027 USA Columbia Univ Dept Pharmacol New York NY 10027 USA New York State Psychiat Inst & Hosp Dept Psychiat Div Integrat Neurosci New York NY 10032 USA Stanford Univ Dept Bioengn Stanford CA 94305 USA Univ Calif San Francisco Neurosci Grad Program San Francisco CA 94143 USA Univ Calif San Francisco Med Scientist Training Program San Francisco CA 94143 USA Univ Washington Dept Pharmacol Ctr Neurobiol Addict Pain & Emot Dept Anesthesiol & Pain Med Seattle WA 98195 USA Univ Calif San Francisco Dept Psychiat San Francisco CA 94143 USA Univ Calif San Francisco Weill Inst Neurosci San Francisco CA 94143 USA Univ Calif San Francisco Kavli Inst Fundamental Neurosci San Francisco CA 94143 USA Columbia Univ Kavli Inst Brain Sci New York NY 10027 USA

Neurons are often considered specialized functional units that encode a single variable. However, many neurons are observed to respond to a mix of disparate sensory, cognitive, and behavioral variables. For such representations, information is distributed across multiple neurons. Here we find this distributed code in the dentate gyrus and CA1 subregions of the hippocampus. Using calcium imaging in freely moving mice, we decoded an animal's position, direction of motion, and speed from the activity of hundreds of cells. The response properties of individual neurons were only partially predictive of their importance for encoding position. Non-place cells encoded position and contributed to position encoding when combined with other cells. Indeed, disrupting the correlations between neural activities decreased decoding performance, mostly in CA1. Our analysis indicates that population methods rather than classical analyses based on single-cell response properties may more accurately characterize the neural code in the hippocampus.

关键词： hippocampus dentate gyrus calcium imaging decoding population coding distributed representations correlated activity mixed selectivity place cells

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Dynamic and reversible remapping of network representations in an unchanging environment

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NEURON 2021年第18期109卷 2967-+页

作者： Low, Isabel I. C. Williams, Alex H. Campbell, Malcolm G. Linderman, Scott W. Giocomo, Lisa M. Stanford Univ Dept Neurobiol Sch Med Stanford CA 94305 USA Stanford Univ Wu Tsai Neurosci Inst Stanford CA 94305 USA Stanford Univ Dept Stat Stanford CA 94305 USA Harvard Univ Dept Mol & Cellular Biol Cambridge MA 02138 USA

Neurons in the medial entorhinal cortex alter their firing properties in response to environmental changes. This flexibility in neural coding is hypothesized to support navigation and memory by dividing sensory experience into unique episodes. However, it is unknown how the entorhinal circuit as a whole transitions between different representations when sensory information is not delineated into discrete contexts. Here we describe rapid and reversible transitions between multiple spatial maps of an unchanging task and environment. These remapping events were synchronized across hundreds of neurons, differentially affected navigational cell types, and correlated with changes in running speed. Despite widespread changes in spatial coding, re mapping comprised a translation along a single dimension in population-level activity space, enabling simple decoding strategies. These findings provoke reconsideration of how the medial entorhinal cortex dynamically represents space and suggest a remarkable capacity of cortical circuits to rapidly and substantially reorganize their neural representations.

关键词： medial entorhinal cortex dynamic coding behavioral state population coding attractor manifolds

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Mixing novel and familiar cues modifies representations of familiar visual images and affects behavior

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CELL REPORTS 2024年第8期43卷 114521页

作者： Nitzan, Noam Bennett, Corbett Movshon, J. Anthony Olsen, Shawn R. Buzsaki, Gyorgy NYU Neurosci Inst New York NY 10016 USA NYU Ctr Neural Sci New York NY 10003 USA Allen Inst Neural Dynam Seattle WA 98109 USA

While visual responses to familiar and novel stimuli have been extensively studied, it is unknown how neuronal representations of familiar stimuli are affected when they are interleaved with novel images. We examined a large-scale dataset from mice performing a visual go/no-go change detection task. After training with eight images, six novel images were interleaved with two familiar ones. Unexpectedly, we found that the behavioral performance in response to familiar images was impaired when they were mixed with novel images. When familiar images were interleaved with novel ones, the dimensionality of their representation increased, indicating a perturbation of their neuronal responses. Furthermore, responses to familiar images in the primary visual cortex were less predictive of responses in higher-order areas, indicating less efficient communication. Spontaneous correlations between neurons were predictive of responses to novel images, but less so to familiar ones. Our study demonstrates the modification of representations of familiar images by novelty.

关键词： visual system novelty change-detection population coding

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Hippocampal Network Reorganization Underlies the Formation of a Temporal Association Memory

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NEURON 2020年第2期107卷 283-+页

作者： Ahmed, Mohsin S. Priestley, James B. Castro, Angel Stefanini, Fabio Canales, Ana Sofia Solis Balough, Elizabeth M. Lavoie, Erin Mazzucato, Luca Fusi, Stefano Losonczy, Attila Columbia Univ Dept Psychiat New York NY 10032 USA Columbia Univ Dept Neurosci New York NY 10027 USA Columbia Univ Doctoral Program Neurobiol & Behav New York NY 10027 USA Columbia Univ Ctr Theoret Neurosci New York NY 10027 USA Columbia Univ Kavli Inst Brain Sci New York NY 10027 USA Columbia Univ Mortimer B Zuckerman Mind Brain Behav Inst New York NY 10027 USA New York State Psychiat Inst & Hosp Div Mol Therapeut New York NY 10032 USA Univ Oregon Dept Math Eugene OR 97403 USA Univ Oregon Dept Biol Eugene OR 97403 USA

Episodic memory requires linking events in time, a function dependent on the hippocampus. In "trace'' fear conditioning, animals learn to associate a neutral cue with an aversive stimulus despite their separation in time by a delay period on the order of tens of seconds. But how this temporal association forms remains unclear. Here we use two-photon calcium imaging of neural population dynamics throughout the course of learning and show that, in contrast to previous theories, hippocampal CA1 does not generate persistent activity to bridge the delay. Instead, learning is concomitant with broad changes in the active neural population. Although neural responses were stochastic in time, cue identity could be read out from population activity over longer timescales after learning. These results question the ubiquity of seconds-long neural sequences during temporal association learning and suggest that trace fear conditioning relies on mechanisms that differ from persistent activity accounts of working memory.

关键词： hippocampus memory learning trace fear conditioning calcium imaging population coding

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Neural Trajectories in the Supplementary Motor Area and Motor Cortex Exhibit Distinct Geometries, Compatible with Different Classes of Computation

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NEURON 2020年第4期107卷 745-+页

作者： Russo, Abigail A. Khajeh, Ramin Bittner, Sean R. Perkins, Sean M. Cunningham, John P. Abbott, L. F. Churchland, Mark M. Columbia Univ Dept Neurosci New York NY 10027 USA Columbia Univ Zuckerman Mind Brain Behav Inst New York NY 10027 USA Columbia Univ Dept Biomed Engn New York NY 10027 USA Columbia Univ Grossman Ctr Stat Mind New York NY 10027 USA Columbia Univ Ctr Theoret Neurosci New York NY 10027 USA Columbia Univ Dept Stat New York NY 10027 USA Columbia Univ Dept Physiol & Cellular Biophys Med Ctr New York NY 10032 USA Columbia Univ Kavli Inst Brain Sci New York NY 10027 USA

The supplementary motor area (SMA) is believed to contribute to higher order aspects of motor control. We considered a key higher order role: tracking progress throughout an action. We propose that doing so requires population activity to display low "trajectory divergence": situations with different future motor outputs should be distinct, even when present motor output is identical. We examined neural activity in SMA and primary motor cortex (M1) as monkeys cycled various distances through a virtual environment. SMA exhibited multiple response features that were absent in M1. At the single-neuron level, these included ramping firing rates and cycle-specific responses. At the population level, they included a helical population-trajectory geometry with shifts in the occupied subspace as movement unfolded. These diverse features all served to reduce trajectory divergence, which was much lower in SMA versus M1. Analogous population-trajectory geometry, also with low divergence, naturally arose in networks trained to internally guide multi-cycle movement.

关键词： supplementary motor area motor control motor cortex population coding recurrent neural network neural dynamics neural computation population geometry

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Coarse-to-fine processing drives the efficient coding of natural scenes in mouse visual cortex

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CELL REPORTS 2022年第13期38卷 110606-110606页

作者： Skyberg, Rolf Tanabe, Seiji Chen, Hui Cang, Jianhua Univ Virginia Dept Biol Charlottesville VA 22904 USA Univ Virginia Dept Psychol Charlottesville VA 22904 USA

The visual system processes sensory inputs sequentially, perceiving coarse information before fine details. Here we study the neural basis of coarse-to-fine processing and its computational benefits in natural vision. We find that primary visual cortical neurons in awake mice respond to natural scenes in a coarse-to-fine manner, primarily driven by individual neurons rapidly shifting their spatial frequency preference from low to high over a brief response period. This shift transforms the population response in a way that counteracts the statistical regularities of natural scenes, thereby reducing redundancy and generating a more efficient neural representation. The increase in representational efficiency does not occur in either dark-reared or anesthetized mice, which show significantly attenuated coarse-to-fine spatial processing. Collectively, these results illustrate that coarse-to-fine processing is state dependent, develops postnatally via visual experience, and provides a computational advantage by generating more efficient representations of the complex spatial statistics of ethologically relevant natural scenes.

关键词： visual neuroscience population coding temporal dynamics spatial frequency tuning single-unit recording experience-dependent development natural scene statistics

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Organization of hippocampal CA3 into correlated cell assemblies supports a stable spatial code

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CELL REPORTS 2023年第2期42卷 112119页

作者： Sheintuch, Liron Geva, Nitzan Deitch, Daniel Rubin, Alon Ziv, Yaniv Weizmann Inst Sci Dept Brain Sci Rehovot Israel

Hippocampal subfield CA3 is thought to stably store memories in assemblies of recurrently connected cells functioning as a collective. However, the collective hippocampal coding properties that are unique to CA3 and how such properties facilitate the stability or precision of the neural code remain unclear. Here, we per-formed large-scale Ca2+ imaging in hippocampal CA1 and CA3 of freely behaving mice that repeatedly explored the same, initially novel environments over weeks. CA3 place cells have more precise and more stable tuning and show a higher statistical dependence with their peers compared with CA1 place cells, uncovering a cell assembly organization in CA3. Surprisingly, although tuning precision and long-term stability are correlated, cells with stronger peer dependence exhibit higher stability but not higher precision. Overall, our results expose the three-way relationship between tuning precision, long-term stability, and peer dependence, suggesting that a cell assembly organization underlies long-term storage of information in the hippocampus.

关键词： hippocampus place cells memory population coding CA3 CA1 calcium imaging optical imaging attractor dynamics representational drift Research topic(s)CP: Neuroscience

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Detecting neural assemblies in calcium imaging data

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BMC BIOLOGY 2018年第1期16卷 143-143页

作者： Molter, Jan Avitan, Lilach Goodhill, Geoffrey J. Univ Queensland Queensland Brian Inst Brisbane Qld 4072 Australia Univ Queensland Sch Math & Phys Brisbane Qld 4072 Australia

Background: Activity in populations of neurons often takes the form of assemblies, where specific groups of neurons tend to activate at the same time. However, in calcium imaging data, reliably identifying these assemblies is a challenging problem, and the relative performance of different assembly-detection algorithms is unknown. Results: To test the performance of several recently proposed assembly-detection algorithms, we first generated large surrogate datasets of calcium imaging data with predefined assembly structures and characterised the ability of the algorithms to recover known assemblies. The algorithms we tested are based on independent component analysis (ICA), principal component analysis (Promax), similarity analysis (CORE), singular value decomposition (SVD), graph theory (SGC), and frequent item set mining (FIM-X). When applied to the simulated data and tested against parameters such as array size, number of assemblies, assembly size and overlap, and signal strength, the SGC and ICA algorithms and a modified form of the Promax algorithm performed well, while PCA-Promax and FIM-X did less well, for instance, showing a strong dependence on the size of the neural array. Notably, we identified additional analyses that can improve their importance. Next, we applied the same algorithms to a dataset of activity in the zebrafish optic tectum evoked by simple visual stimuli, and found that the SGC algorithm recovered assemblies closest to the averaged responses. Conclusions: Our findings suggest that the neural assemblies recovered from calcium imaging data can vary considerably with the choice of algorithm, but that some algorithms reliably perform better than others. This suggests that previous results using these algorithms may need to be reevaluated in this light.

关键词： Spontaneous activity population coding Clustering

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Cortical neural populations can guide behavior by integrating inputs linearly, independent of synchrony

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2014年第1期111卷 E178-E187页

作者： Histed, Mark H. Maunsell, John H. R. Harvard Univ Sch Med Dept Neurobiol Boston MA 02115 USA

Neurons are sensitive to the relative timing of inputs, both because several inputs must coincide to reach spike threshold and because active dendritic mechanisms can amplify synchronous inputs. To determine if input synchrony can influence behavior, we trained mice to report activation of excitatory neurons in visual cortex using channelrhodopsin-2. We used light pulses that varied in duration from a few milliseconds to 100 ms and measured neuronal responses and animals' detection ability. We found detection performance was well predicted by the total amount of light delivered. Short pulses provided no behavioral advantage, even when they concentrated evoked spikes into an interval a few milliseconds long. Arranging pulses into trains of varying frequency from beta to gamma also produced no behavioral advantage. Light intensities required to drive behavior were low ( at low intensities, channelrhodopsin- 2 conductance varies linearly with intensity), and the accompanying changes in firing rate were small ( over 100 ms, average change: 1.1 spikes per s). Firing rate changes varied linearly with pulse intensity and duration, and behavior was predicted by total spike count independent of temporal arrangement. Thus, animals' detection performance reflected the linear integration of total input over 100 ms. This behavioral linearity despite neurons' nonlinearities can be explained by a population code using noisy neurons. Ongoing background activity creates probabilistic spiking, allowing weak inputs to change spike probability linearly, with little amplification of coincident input. Summing across a population then yields a total spike count that weights inputs equally, regardless of their arrival time.

关键词： neuronal circuits population coding optogenetics mouse

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Distinct hippocampal-prefrontal neural assemblies coordinate memory encoding, maintenance, and recall

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CURRENT BIOLOGY 2023年第7期33卷 1220-+页

作者： Domanski, Aleksander P. F. Kucewicz, Michal T. Russo, Eleonora Tricklebank, Mark D. Robinson, Emma S. J. Durstewitz, Daniel Jones, Matt W. Univ Bristol Fac Life Sci Sch Physiol Pharmacol & Neurosci Univ Walk Bristol BS8 1TD England Gdansk Univ Technol Fac Elect BioTechMed Ctr Multimedia Syst DeptBrain & Mind Electrophysiol L PL-80233 Gdansk Poland Heidelberg Univ Cent Inst Mental Hlth Med Fac Mannheim Dept Theoret Neurosci D-68159 Mannheim Germany Johannes Gutenberg Univ Mainz Univ Med Ctr Dept Psychiat & Psychotherapy D-55131 Mainz Germany Kings Coll London Ctr Neuroimaging Sci Denmark Hill London SE5 8AF England Alan Turing Inst British Lib 96 Euston Rd London England Francis Crick Inst 1 Midland Rd London England

Short-term memory enables incorporation of recent experience into subsequent decision-making. This pro-cessing recruits both the prefrontal cortex and hippocampus, where neurons encode task cues, rules, and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC populations lead in maintaining sample information across delays of an operant non-match to sample task, despite individual neurons firing only transiently. During sample encoding, distinct mPFC subpopulations joined distributed CA1-mPFC cell assemblies hallmarked by 4-5 Hz rhythmic modulation;CA1-mPFC assemblies re-emerged during choice episodes but were not 4-5 Hz modulated. Delay-dependent errors arose when attenuated rhythmic assembly activity heralded collapse of sustained mPFC encoding. Our results map component processes of memory-guided decisions onto heterogeneous CA1-mPFC subpopulations and the dynamics of physiologically distinct, distributed cell assemblies.

关键词： working memory neural ensembles population coding synchrony network oscillations theta rhythm prelimbic cognition operant task tetrode electrophysiology

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