1
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Franco LM, Goard MJ. Differential stability of task variable representations in retrosplenial cortex. Nat Commun 2024; 15:6872. [PMID: 39127731 PMCID: PMC11316801 DOI: 10.1038/s41467-024-51227-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 08/02/2024] [Indexed: 08/12/2024] Open
Abstract
Cortical neurons store information across different timescales, from seconds to years. Although information stability is variable across regions, it can vary within a region as well. Association areas are known to multiplex behaviorally relevant variables, but the stability of their representations is not well understood. Here, we longitudinally recorded the activity of neuronal populations in the mouse retrosplenial cortex (RSC) during the performance of a context-choice association task. We found that the activity of neurons exhibits different levels of stability across days. Using linear classifiers, we quantified the stability of three task-relevant variables. We find that RSC representations of context and trial outcome display higher stability than motor choice, both at the single cell and population levels. Together, our findings show an important characteristic of association areas, where diverse streams of information are stored with varying levels of stability, which may balance representational reliability and flexibility according to behavioral demands.
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Affiliation(s)
- Luis M Franco
- Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA.
- Institute of Neuroscience, University of Oregon, Eugene, OR, USA.
| | - Michael J Goard
- Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA.
- Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA.
- Department of Psychological & Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, USA.
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2
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Jurewicz K, Sleezer BJ, Mehta PS, Hayden BY, Ebitz RB. Irrational choices via a curvilinear representational geometry for value. Nat Commun 2024; 15:6424. [PMID: 39080250 PMCID: PMC11289086 DOI: 10.1038/s41467-024-49568-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 06/06/2024] [Indexed: 08/02/2024] Open
Abstract
We make decisions by comparing values, but it is not yet clear how value is represented in the brain. Many models assume, if only implicitly, that the representational geometry of value is linear. However, in part due to a historical focus on noisy single neurons, rather than neuronal populations, this hypothesis has not been rigorously tested. Here, we examine the representational geometry of value in the ventromedial prefrontal cortex (vmPFC), a part of the brain linked to economic decision-making, in two male rhesus macaques. We find that values are encoded along a curved manifold in vmPFC. This curvilinear geometry predicts a specific pattern of irrational decision-making: that decision-makers will make worse choices when an irrelevant, decoy option is worse in value, compared to when it is better. We observe this type of irrational choices in behavior. Together, these results not only suggest that the representational geometry of value is nonlinear, but that this nonlinearity could impose bounds on rational decision-making.
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Affiliation(s)
- Katarzyna Jurewicz
- Department of Neurosciences, Faculté de médecine, and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage, Université de Montréal, Montréal, QC, Canada
- Department of Physiology, Faculty of Medicine and Health Sciences, McGill University, Montréal, QC, Canada
| | - Brianna J Sleezer
- Department of Neuroscience, Center for Magnetic Resonance Research, and Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA
| | - Priyanka S Mehta
- Department of Neuroscience, Center for Magnetic Resonance Research, and Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA
- Psychology Program, Department of Human Behavior, Justice, and Diversity, University of Wisconsin, Superior, Superior, WI, USA
| | - Benjamin Y Hayden
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - R Becket Ebitz
- Department of Neurosciences, Faculté de médecine, and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage, Université de Montréal, Montréal, QC, Canada.
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3
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Manley J, Lu S, Barber K, Demas J, Kim H, Meyer D, Traub FM, Vaziri A. Simultaneous, cortex-wide dynamics of up to 1 million neurons reveal unbounded scaling of dimensionality with neuron number. Neuron 2024; 112:1694-1709.e5. [PMID: 38452763 PMCID: PMC11098699 DOI: 10.1016/j.neuron.2024.02.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 05/18/2023] [Accepted: 02/14/2024] [Indexed: 03/09/2024]
Abstract
The brain's remarkable properties arise from the collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, can such low-dimensional representations truly explain the vast range of brain activity, and if not, what is the appropriate resolution and scale of recording to capture them? Imaging neural activity at cellular resolution and near-simultaneously across the mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number in populations up to 1 million neurons. Although half of the neural variance is contained within sixteen dimensions correlated with behavior, our discovered scaling of dimensionality corresponds to an ever-increasing number of neuronal ensembles without immediate behavioral or sensory correlates. The activity patterns underlying these higher dimensions are fine grained and cortex wide, highlighting that large-scale, cellular-resolution recording is required to uncover the full substrates of neuronal computations.
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Affiliation(s)
- Jason Manley
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Sihao Lu
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Kevin Barber
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Jeffrey Demas
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Hyewon Kim
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - David Meyer
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Francisca Martínez Traub
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA.
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4
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Pérez-Ortega J, Akrouh A, Yuste R. Stimulus encoding by specific inactivation of cortical neurons. Nat Commun 2024; 15:3192. [PMID: 38609354 PMCID: PMC11015011 DOI: 10.1038/s41467-024-47515-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 04/02/2024] [Indexed: 04/14/2024] Open
Abstract
Neuronal ensembles are groups of neurons with correlated activity associated with sensory, motor, and behavioral functions. To explore how ensembles encode information, we investigated responses of visual cortical neurons in awake mice using volumetric two-photon calcium imaging during visual stimulation. We identified neuronal ensembles employing an unsupervised model-free algorithm and, besides neurons activated by the visual stimulus (termed "onsemble"), we also find neurons that are specifically inactivated (termed "offsemble"). Offsemble neurons showed faster calcium decay during stimuli, suggesting selective inhibition. In response to visual stimuli, each ensemble (onsemble+offsemble) exhibited small trial-to-trial variability, high orientation selectivity, and superior predictive accuracy for visual stimulus orientation, surpassing the sum of individual neuron activity. Thus, the combined selective activation and inactivation of cortical neurons enhances visual encoding as an emergent and distributed neural code.
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Affiliation(s)
- Jesús Pérez-Ortega
- Neurotechnology Center, Dept. Biological Sciences, Columbia University, New York, NY, 10027, USA.
| | - Alejandro Akrouh
- Neurotechnology Center, Dept. Biological Sciences, Columbia University, New York, NY, 10027, USA
| | - Rafael Yuste
- Neurotechnology Center, Dept. Biological Sciences, Columbia University, New York, NY, 10027, USA
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5
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Tlaie A, Shapcott K, van der Plas TL, Rowland J, Lees R, Keeling J, Packer A, Tiesinga P, Schölvinck ML, Havenith MN. What does the mean mean? A simple test for neuroscience. PLoS Comput Biol 2024; 20:e1012000. [PMID: 38640119 PMCID: PMC11062559 DOI: 10.1371/journal.pcbi.1012000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 05/01/2024] [Accepted: 03/12/2024] [Indexed: 04/21/2024] Open
Abstract
Trial-averaged metrics, e.g. tuning curves or population response vectors, are a ubiquitous way of characterizing neuronal activity. But how relevant are such trial-averaged responses to neuronal computation itself? Here we present a simple test to estimate whether average responses reflect aspects of neuronal activity that contribute to neuronal processing. The test probes two assumptions implicitly made whenever average metrics are treated as meaningful representations of neuronal activity: Reliability: Neuronal responses repeat consistently enough across trials that they convey a recognizable reflection of the average response to downstream regions.Behavioural relevance: If a single-trial response is more similar to the average template, it is more likely to evoke correct behavioural responses. We apply this test to two data sets: (1) Two-photon recordings in primary somatosensory cortices (S1 and S2) of mice trained to detect optogenetic stimulation in S1; and (2) Electrophysiological recordings from 71 brain areas in mice performing a contrast discrimination task. Under the highly controlled settings of Data set 1, both assumptions were largely fulfilled. In contrast, the less restrictive paradigm of Data set 2 met neither assumption. Simulations predict that the larger diversity of neuronal response preferences, rather than higher cross-trial reliability, drives the better performance of Data set 1. We conclude that when behaviour is less tightly restricted, average responses do not seem particularly relevant to neuronal computation, potentially because information is encoded more dynamically. Most importantly, we encourage researchers to apply this simple test of computational relevance whenever using trial-averaged neuronal metrics, in order to gauge how representative cross-trial averages are in a given context.
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Affiliation(s)
- Alejandro Tlaie
- Ernst Strüngmann Institute for Neuroscience, Frankfurt am Main, Germany
- Laboratory for Clinical Neuroscience, Centre for Biomedical Technology, Technical University of Madrid, Madrid, Spain
| | | | - Thijs L. van der Plas
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom
| | - James Rowland
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom
| | - Robert Lees
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom
| | - Joshua Keeling
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom
| | - Adam Packer
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom
| | - Paul Tiesinga
- Department of Neuroinformatics, Donders Institute, Radboud University, Nijmegen, The Netherlands
| | | | - Martha N. Havenith
- Ernst Strüngmann Institute for Neuroscience, Frankfurt am Main, Germany
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom
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6
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Oude Lohuis MN, Marchesi P, Olcese U, Pennartz CMA. Triple dissociation of visual, auditory and motor processing in mouse primary visual cortex. Nat Neurosci 2024; 27:758-771. [PMID: 38307971 DOI: 10.1038/s41593-023-01564-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 12/19/2023] [Indexed: 02/04/2024]
Abstract
Primary sensory cortices respond to crossmodal stimuli-for example, auditory responses are found in primary visual cortex (V1). However, it remains unclear whether these responses reflect sensory inputs or behavioral modulation through sound-evoked body movement. We address this controversy by showing that sound-evoked activity in V1 of awake mice can be dissociated into auditory and behavioral components with distinct spatiotemporal profiles. The auditory component began at approximately 27 ms, was found in superficial and deep layers and originated from auditory cortex. Sound-evoked orofacial movements correlated with V1 neural activity starting at approximately 80-100 ms and explained auditory frequency tuning. Visual, auditory and motor activity were expressed by different laminar profiles and largely segregated subsets of neuronal populations. During simultaneous audiovisual stimulation, visual representations remained dissociable from auditory-related and motor-related activity. This three-fold dissociability of auditory, motor and visual processing is central to understanding how distinct inputs to visual cortex interact to support vision.
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Affiliation(s)
- Matthijs N Oude Lohuis
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Pietro Marchesi
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands.
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands.
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7
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Manley J, Vaziri A. Whole-brain neural substrates of behavioral variability in the larval zebrafish. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.03.583208. [PMID: 38496592 PMCID: PMC10942351 DOI: 10.1101/2024.03.03.583208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Animals engaged in naturalistic behavior can exhibit a large degree of behavioral variability even under sensory invariant conditions. Such behavioral variability can include not only variations of the same behavior, but also variability across qualitatively different behaviors driven by divergent cognitive states, such as fight-or-flight decisions. However, the neural circuit mechanisms that generate such divergent behaviors across trials are not well understood. To investigate this question, here we studied the visual-evoked responses of larval zebrafish to moving objects of various sizes, which we found exhibited highly variable and divergent responses across repetitions of the same stimulus. Given that the neuronal circuits underlying such behaviors span sensory, motor, and other brain areas, we built a novel Fourier light field microscope which enables high-resolution, whole-brain imaging of larval zebrafish during behavior. This enabled us to screen for neural loci which exhibited activity patterns correlated with behavioral variability. We found that despite the highly variable activity of single neurons, visual stimuli were robustly encoded at the population level, and the visual-encoding dimensions of neural activity did not explain behavioral variability. This robustness despite apparent single neuron variability was due to the multi-dimensional geometry of the neuronal population dynamics: almost all neural dimensions that were variable across individual trials, i.e. the "noise" modes, were orthogonal to those encoding for sensory information. Investigating this neuronal variability further, we identified two sparsely-distributed, brain-wide neuronal populations whose pre-motor activity predicted whether the larva would respond to a stimulus and, if so, which direction it would turn on a single-trial level. These populations predicted single-trial behavior seconds before stimulus onset, indicating they encoded time-varying internal modulating behavior, perhaps organizing behavior over longer timescales or enabling flexible behavior routines dependent on the animal's internal state. Our results provide the first whole-brain confirmation that sensory, motor, and internal variables are encoded in a highly mixed fashion throughout the brain and demonstrate that de-mixing each of these components at the neuronal population level is critical to understanding the mechanisms underlying the brain's remarkable flexibility and robustness.
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Affiliation(s)
- Jason Manley
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
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8
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Gillon CJ, Pina JE, Lecoq JA, Ahmed R, Billeh YN, Caldejon S, Groblewski P, Henley TM, Kato I, Lee E, Luviano J, Mace K, Nayan C, Nguyen TV, North K, Perkins J, Seid S, Valley MT, Williford A, Bengio Y, Lillicrap TP, Richards BA, Zylberberg J. Responses to Pattern-Violating Visual Stimuli Evolve Differently Over Days in Somata and Distal Apical Dendrites. J Neurosci 2024; 44:e1009232023. [PMID: 37989593 PMCID: PMC10860604 DOI: 10.1523/jneurosci.1009-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/14/2023] [Accepted: 09/16/2023] [Indexed: 11/23/2023] Open
Abstract
Scientists have long conjectured that the neocortex learns patterns in sensory data to generate top-down predictions of upcoming stimuli. In line with this conjecture, different responses to pattern-matching vs pattern-violating visual stimuli have been observed in both spiking and somatic calcium imaging data. However, it remains unknown whether these pattern-violation signals are different between the distal apical dendrites, which are heavily targeted by top-down signals, and the somata, where bottom-up information is primarily integrated. Furthermore, it is unknown how responses to pattern-violating stimuli evolve over time as an animal gains more experience with them. Here, we address these unanswered questions by analyzing responses of individual somata and dendritic branches of layer 2/3 and layer 5 pyramidal neurons tracked over multiple days in primary visual cortex of awake, behaving female and male mice. We use sequences of Gabor patches with patterns in their orientations to create pattern-matching and pattern-violating stimuli, and two-photon calcium imaging to record neuronal responses. Many neurons in both layers show large differences between their responses to pattern-matching and pattern-violating stimuli. Interestingly, these responses evolve in opposite directions in the somata and distal apical dendrites, with somata becoming less sensitive to pattern-violating stimuli and distal apical dendrites more sensitive. These differences between the somata and distal apical dendrites may be important for hierarchical computation of sensory predictions and learning, since these two compartments tend to receive bottom-up and top-down information, respectively.
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Affiliation(s)
- Colleen J Gillon
- Department of Biological Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada
- Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada
- Mila, Montréal, Québec, Canada
| | - Jason E Pina
- Department of Physics and Astronomy, York University, Toronto, Ontario, Canada
- Centre for Vision Research, York University, Toronto, Ontario, Canada
| | | | | | | | | | | | - Timothy M Henley
- Department of Physics and Astronomy, York University, Toronto, Ontario, Canada
- Centre for Vision Research, York University, Toronto, Ontario, Canada
| | | | - Eric Lee
- Allen Institute, Seattle, Washington
| | | | - Kyla Mace
- Allen Institute, Seattle, Washington
| | | | | | - Kat North
- Allen Institute, Seattle, Washington
| | | | - Sam Seid
- Allen Institute, Seattle, Washington
| | | | | | - Yoshua Bengio
- Mila, Montréal, Québec, Canada
- Département d'informatique et de recherche opérationnelle, Université de Montréal, Montréal, Québec, Canada
- Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada
| | - Timothy P Lillicrap
- DeepMind, Inc., London, United Kingdom
- Centre for Computation, Mathematics and Physics in the Life Sciences and Experimental Biology, University College London, London, United Kingdom
| | - Blake A Richards
- Mila, Montréal, Québec, Canada
- Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada
- School of Computer Science, McGill University, Montréal, Québec, Canada
- Department of Neurology & Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Joel Zylberberg
- Department of Physics and Astronomy, York University, Toronto, Ontario, Canada
- Centre for Vision Research, York University, Toronto, Ontario, Canada
- Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada
- Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada
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9
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Manley J, Demas J, Kim H, Traub FM, Vaziri A. Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.15.575721. [PMID: 38293036 PMCID: PMC10827059 DOI: 10.1101/2024.01.15.575721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
The brain's remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.
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Affiliation(s)
- Jason Manley
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Jeffrey Demas
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Hyewon Kim
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Francisca Martínez Traub
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
- Lead Contact
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10
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Yang H, Huang P, Li R, Tang N, Zhang Y, Zhou Z, Liu L, Liu X, Kang J. Flash-based content addressable memory with L2 distance for memory-augmented neural network. iScience 2023; 26:108371. [PMID: 38025791 PMCID: PMC10663817 DOI: 10.1016/j.isci.2023.108371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 10/07/2023] [Accepted: 10/26/2023] [Indexed: 12/01/2023] Open
Abstract
Memory-augmented neural network (MANN) has received increasing attention as a promising approach to achieve lifelong on-device learning, of which implementation of the explicit memory is vital. Content addressable memory (CAM) has been designed to accelerate the explicit memory by harnessing the in-memory-computing capability. In this work, a CAM cell with quadratic code is proposed, and a 1Mb Flash-based multi-bit CAM chip capable of computing Euclidean (L2) distance is fabricated. Compared with ternary CAM, the latency and energy are significantly reduced by 5.3- and 46.6-fold, respectively, for the MANN on Omniglot dataset. Besides, the recognition accuracy has slight degradation (<1%) even after baking for 105 s at 200°C, demonstrating the robustness to environmental disturbance. Performance evaluation indicates a reduction of 471-fold in latency and 1267-fold in energy compared with GPU for search operation. The proposed robust and energy-efficient CAM provides a promising solution to implement lifelong on-device machine intelligence.
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Affiliation(s)
- Haozhang Yang
- School of Integrated Circuits, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China
| | - Peng Huang
- School of Integrated Circuits, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China
| | - Ruiyi Li
- School of Integrated Circuits, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China
| | - Nan Tang
- School of Integrated Circuits, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China
| | - Yizhou Zhang
- School of Integrated Circuits, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China
| | - Zheng Zhou
- School of Integrated Circuits, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China
| | - Lifeng Liu
- School of Integrated Circuits, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China
| | - Xiaoyan Liu
- School of Integrated Circuits, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China
| | - Jinfeng Kang
- School of Integrated Circuits, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China
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11
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Alisha A, Bettina V, Simon P. Representational drift in barrel cortex is receptive field dependent. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.20.563381. [PMID: 37961727 PMCID: PMC10634719 DOI: 10.1101/2023.10.20.563381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Cortical populations often exhibit changes in activity even when behavior is stable. How behavioral stability is maintained in the face of such 'representational drift' remains unclear. One possibility is that some neurons are stable despite broader instability. We examine whisker touch responses in superficial layers of primary vibrissal somatosensory cortex (vS1) over several weeks in mice stably performing an object detection task with two whiskers. While the number of touch neurons remained constant, individual neurons changed with time. Touch-responsive neurons with broad receptive fields were more stable than narrowly tuned neurons. Transitions between functional types were non-random: before becoming broadly tuned neurons, unresponsive neurons first pass through a period of narrower tuning. Broadly tuned neurons with higher pairwise correlations to other touch neurons were more stable than neurons with lower correlations. Thus, a small population of broadly tuned and synchronously active touch neurons exhibit elevated stability and may be particularly important for downstream readout.
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Affiliation(s)
- Ahmed Alisha
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| | - Voelcker Bettina
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| | - Peron Simon
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
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12
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Kimura R. Flexible information representation to stabilize sensory perception despite minor external input variations. Neurosci Res 2023; 195:1-8. [PMID: 37236268 DOI: 10.1016/j.neures.2023.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 05/14/2023] [Accepted: 05/18/2023] [Indexed: 05/28/2023]
Abstract
Sensory information about the environment constantly changes or varies depending on circumstances. However, once we repeatedly experience objects, our brain can perceive and recognize them as identical, even if they are slightly altered or include some diversity. We can stably perceive things without interference from minor external changes or variety. Our recent study focusing on visual perception showed that repeatedly viewing the same oriented grating stimuli enables information representation for low-contrast (or weak-intensity) orientations in the primary visual cortex. We observed low contrast-preferring neurons, whose firing rates increased by reducing the luminance contrast. The number of such neurons increased after the experience, and the neuronal population, including such neurons, can represent even low-contrast orientations. This study indicated that experience leads to flexible information representations that continuously respond to inputs of various strengths at the neuronal population level in the primary sensory cortex. In this perspective article, in addition to the above mechanism, I would discuss alternative mechanisms for perceptual stabilization. The primary sensory cortex represents external information faithfully without alterations, as well as in a state distorted by experience. Both sensory representations may cooperatively and dynamically affect hierarchical downstream, resulting in stable perception.
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Affiliation(s)
- Rie Kimura
- International Research Center for Neurointelligence, The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan.
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13
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Pennartz CMA, Oude Lohuis MN, Olcese U. How 'visual' is the visual cortex? The interactions between the visual cortex and other sensory, motivational and motor systems as enabling factors for visual perception. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220336. [PMID: 37545313 PMCID: PMC10404929 DOI: 10.1098/rstb.2022.0336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 06/13/2023] [Indexed: 08/08/2023] Open
Abstract
The definition of the visual cortex is primarily based on the evidence that lesions of this area impair visual perception. However, this does not exclude that the visual cortex may process more information than of retinal origin alone, or that other brain structures contribute to vision. Indeed, research across the past decades has shown that non-visual information, such as neural activity related to reward expectation and value, locomotion, working memory and other sensory modalities, can modulate primary visual cortical responses to retinal inputs. Nevertheless, the function of this non-visual information is poorly understood. Here we review recent evidence, coming primarily from studies in rodents, arguing that non-visual and motor effects in visual cortex play a role in visual processing itself, for instance disentangling direct auditory effects on visual cortex from effects of sound-evoked orofacial movement. These findings are placed in a broader framework casting vision in terms of predictive processing under control of frontal, reward- and motor-related systems. In contrast to the prevalent notion that vision is exclusively constructed by the visual cortical system, we propose that visual percepts are generated by a larger network-the extended visual system-spanning other sensory cortices, supramodal areas and frontal systems. This article is part of the theme issue 'Decision and control processes in multisensory perception'.
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Affiliation(s)
- Cyriel M. A. Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
| | - Matthijs N. Oude Lohuis
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
- Champalimaud Research, Champalimaud Foundation, 1400-038 Lisbon, Portugal
| | - Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
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14
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Safaai H, Wang AY, Kira S, Malerba SB, Panzeri S, Harvey CD. Specialized structure of neural population codes in parietal cortex outputs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.24.554635. [PMID: 37662297 PMCID: PMC10473762 DOI: 10.1101/2023.08.24.554635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Do cortical neurons that send axonal projections to the same target area form specialized population codes for transmitting information? We used calcium imaging in mouse posterior parietal cortex (PPC), retrograde labeling, and statistical multivariate models to address this question during a delayed match-to-sample task. We found that PPC broadcasts sensory, choice, and locomotion signals widely, but sensory information is enriched in the output to anterior cingulate cortex. Neurons projecting to the same area have elevated pairwise activity correlations. These correlations are structured as information-limiting and information-enhancing interaction networks that collectively enhance information levels. This network structure is unique to sub-populations projecting to the same target and strikingly absent in surrounding neural populations with unidentified projections. Furthermore, this structure is only present when mice make correct, but not incorrect, behavioral choices. Therefore, cortical neurons comprising an output pathway form uniquely structured population codes that enhance information transmission to guide accurate behavior.
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Affiliation(s)
- Houman Safaai
- Department of Neurobiology, Harvard Medical School, Boston, USA
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
| | - Alice Y. Wang
- Department of Neurobiology, Harvard Medical School, Boston, USA
| | - Shinichiro Kira
- Department of Neurobiology, Harvard Medical School, Boston, USA
| | - Simone Blanco Malerba
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Stefano Panzeri
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
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15
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Montijn JS, Riguccini V, Levelt CN, Heimel JA. Impaired Direction Selectivity in the Nucleus of the Optic Tract of Albino Mice. Invest Ophthalmol Vis Sci 2023; 64:9. [PMID: 37548962 PMCID: PMC10411648 DOI: 10.1167/iovs.64.11.9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 07/17/2023] [Indexed: 08/08/2023] Open
Abstract
Purpose Human albinos have a low visual acuity. This is partially due to the presence of spontaneous erroneous eye movements called pendular nystagmus. This nystagmus is present in other albino vertebrates and has been hypothesized to be caused by aberrant wiring of retinal ganglion axons to the nucleus of the optic tract (NOT), a part of the accessory optic system involved in the optokinetic response to visual motion. The NOT in pigmented rodents is preferentially responsive to ipsiversive motion (i.e., motion in the contralateral visual field in the temporonasal direction). We compared the response to visual motion in the NOT of albino and pigmented mice to understand if motion coding and preference are impaired in the NOT of albino mice. Methods We recorded neuronal spiking activity with Neuropixels probes in the visual cortex and NOT in C57BL/6JRj mice (pigmented) and DBA/1JRj mice with oculocutaneous albinism (albino). Results We found that in pigmented mice, NOT is retinotopically organized, and neurons are direction tuned, whereas in albino mice, neuronal tuning is severely impaired. Neurons in the NOT of albino mice do not have a preference for ipsiversive movement. In contrast, neuronal tuning in visual cortex was preserved in albino mice and did not differ significantly from the tuning in pigmented mice. Conclusions We propose that excessive interhemispheric crossing of retinal projections in albinos may cause the disrupted left/right direction encoding we found in NOT. This, in turn, impairs the normal horizontal optokinetic reflex and leads to pendular albino nystagmus.
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Affiliation(s)
- Jorrit S. Montijn
- Department of Circuits, Structure & Function, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Valentina Riguccini
- Department of Molecular Visual Plasticity, Netherlands Institute for Neuroscience, Amsterdam, the Netherlands
| | - Christiaan N. Levelt
- Department of Molecular Visual Plasticity, Netherlands Institute for Neuroscience, Amsterdam, the Netherlands
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, Amsterdam, the Netherlands
| | - J. Alexander Heimel
- Department of Circuits, Structure & Function, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
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16
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Pancholi R, Ryan L, Peron S. Learning in a sensory cortical microstimulation task is associated with elevated representational stability. Nat Commun 2023; 14:3860. [PMID: 37385989 PMCID: PMC10310840 DOI: 10.1038/s41467-023-39542-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 06/16/2023] [Indexed: 07/01/2023] Open
Abstract
Sensory cortical representations can be highly dynamic, raising the question of how representational stability impacts learning. We train mice to discriminate the number of photostimulation pulses delivered to opsin-expressing pyramidal neurons in layer 2/3 of primary vibrissal somatosensory cortex. We simultaneously track evoked neural activity across learning using volumetric two-photon calcium imaging. In well-trained animals, trial-to-trial fluctuations in the amount of photostimulus-evoked activity predicted animal choice. Population activity levels declined rapidly across training, with the most active neurons showing the largest declines in responsiveness. Mice learned at varied rates, with some failing to learn the task in the time provided. The photoresponsive population showed greater instability both within and across behavioral sessions among animals that failed to learn. Animals that failed to learn also exhibited a faster deterioration in stimulus decoding. Thus, greater stability in the stimulus response is associated with learning in a sensory cortical microstimulation task.
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Affiliation(s)
- Ravi Pancholi
- Center for Neural Science, New York University, 4 Washington Place Rm. 621, New York, NY, 10003, USA
| | - Lauren Ryan
- Center for Neural Science, New York University, 4 Washington Place Rm. 621, New York, NY, 10003, USA
| | - Simon Peron
- Center for Neural Science, New York University, 4 Washington Place Rm. 621, New York, NY, 10003, USA.
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17
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Klaver LMF, Brinkhof LP, Sikkens T, Casado-Román L, Williams AG, van Mourik-Donga L, Mejías JF, Pennartz CMA, Bosman CA. Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness. Cereb Cortex 2023; 33:7564-7581. [PMID: 36935096 PMCID: PMC10267643 DOI: 10.1093/cercor/bhad061] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 02/11/2023] [Accepted: 02/14/2023] [Indexed: 03/21/2023] Open
Abstract
Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12 Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80 Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18 Hz) and high-frequency (>80 Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.
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Affiliation(s)
- Lianne M F Klaver
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Lotte P Brinkhof
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Tom Sikkens
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Lorena Casado-Román
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Alex G Williams
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Laura van Mourik-Donga
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Jorge F Mejías
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Conrado A Bosman
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
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18
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Jacob M, Ford J, Deacon T. Cognition is entangled with metabolism: relevance for resting-state EEG-fMRI. Front Hum Neurosci 2023; 17:976036. [PMID: 37113322 PMCID: PMC10126302 DOI: 10.3389/fnhum.2023.976036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 03/02/2023] [Indexed: 04/29/2023] Open
Abstract
The brain is a living organ with distinct metabolic constraints. However, these constraints are typically considered as secondary or supportive of information processing which is primarily performed by neurons. The default operational definition of neural information processing is that (1) it is ultimately encoded as a change in individual neuronal firing rate as this correlates with the presentation of a peripheral stimulus, motor action or cognitive task. Two additional assumptions are associated with this default interpretation: (2) that the incessant background firing activity against which changes in activity are measured plays no role in assigning significance to the extrinsically evoked change in neural firing, and (3) that the metabolic energy that sustains this background activity and which correlates with differences in neuronal firing rate is merely a response to an evoked change in neuronal activity. These assumptions underlie the design, implementation, and interpretation of neuroimaging studies, particularly fMRI, which relies on changes in blood oxygen as an indirect measure of neural activity. In this article we reconsider all three of these assumptions in light of recent evidence. We suggest that by combining EEG with fMRI, new experimental work can reconcile emerging controversies in neurovascular coupling and the significance of ongoing, background activity during resting-state paradigms. A new conceptual framework for neuroimaging paradigms is developed to investigate how ongoing neural activity is "entangled" with metabolism. That is, in addition to being recruited to support locally evoked neuronal activity (the traditional hemodynamic response), changes in metabolic support may be independently "invoked" by non-local brain regions, yielding flexible neurovascular coupling dynamics that inform the cognitive context. This framework demonstrates how multimodal neuroimaging is necessary to probe the neurometabolic foundations of cognition, with implications for the study of neuropsychiatric disorders.
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Affiliation(s)
- Michael Jacob
- Mental Health Service, San Francisco VA Healthcare System, San Francisco, CA, United States
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Judith Ford
- Mental Health Service, San Francisco VA Healthcare System, San Francisco, CA, United States
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Terrence Deacon
- Department of Anthropology, University of California, Berkeley, Berkeley, CA, United States
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19
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Chambers AR, Aschauer DF, Eppler JB, Kaschube M, Rumpel S. A stable sensory map emerges from a dynamic equilibrium of neurons with unstable tuning properties. Cereb Cortex 2022; 33:5597-5612. [PMID: 36418925 PMCID: PMC10152095 DOI: 10.1093/cercor/bhac445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 10/17/2022] [Accepted: 10/21/2022] [Indexed: 11/25/2022] Open
Abstract
Abstract
Recent long-term measurements of neuronal activity have revealed that, despite stability in large-scale topographic maps, the tuning properties of individual cortical neurons can undergo substantial reformatting over days. To shed light on this apparent contradiction, we captured the sound response dynamics of auditory cortical neurons using repeated 2-photon calcium imaging in awake mice. We measured sound-evoked responses to a set of pure tone and complex sound stimuli in more than 20,000 auditory cortex neurons over several days. We found that a substantial fraction of neurons dropped in and out of the population response. We modeled these dynamics as a simple discrete-time Markov chain, capturing the continuous changes in responsiveness observed during stable behavioral and environmental conditions. Although only a minority of neurons were driven by the sound stimuli at a given time point, the model predicts that most cells would at least transiently become responsive within 100 days. We observe that, despite single-neuron volatility, the population-level representation of sound frequency was stably maintained, demonstrating the dynamic equilibrium underlying the tonotopic map. Our results show that sensory maps are maintained by shifting subpopulations of neurons “sharing” the job of creating a sensory representation.
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Affiliation(s)
- Anna R Chambers
- Institute of Physiology, Focus Program Translational Neurosciences, University Medical Center, Johannes Gutenberg University Mainz , Duesbergweg 6, Mainz 55128 , Germany
| | - Dominik F Aschauer
- Institute of Physiology, Focus Program Translational Neurosciences, University Medical Center, Johannes Gutenberg University Mainz , Duesbergweg 6, Mainz 55128 , Germany
| | - Jens-Bastian Eppler
- Frankfurt Institute for Advanced Studies and Department of Computer Science, Goethe University Frankfurt , Ruth-Moufang-Straße 1, Frankfurt am Main 60438 , Germany
| | - Matthias Kaschube
- Frankfurt Institute for Advanced Studies and Department of Computer Science, Goethe University Frankfurt , Ruth-Moufang-Straße 1, Frankfurt am Main 60438 , Germany
| | - Simon Rumpel
- Institute of Physiology, Focus Program Translational Neurosciences, University Medical Center, Johannes Gutenberg University Mainz , Duesbergweg 6, Mainz 55128 , Germany
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20
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Tuning instability of non-columnar neurons in the salt-and-pepper whisker map in somatosensory cortex. Nat Commun 2022; 13:6611. [PMID: 36329010 PMCID: PMC9633707 DOI: 10.1038/s41467-022-34261-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 10/19/2022] [Indexed: 11/06/2022] Open
Abstract
Rodent sensory cortex contains salt-and-pepper maps of sensory features, whose structure is not fully known. Here we investigated the structure of the salt-and-pepper whisker somatotopic map among L2/3 pyramidal neurons in somatosensory cortex, in awake mice performing one-vs-all whisker discrimination. Neurons tuned for columnar (CW) and non-columnar (non-CW) whiskers were spatially intermixed, with co-tuned neurons forming local (20 µm) clusters. Whisker tuning was markedly unstable in expert mice, with 35-46% of pyramidal cells significantly shifting tuning over 5-18 days. Tuning instability was highly concentrated in non-CW tuned neurons, and thus was structured in the map. Instability of non-CW neurons was unchanged during chronic whisker paralysis and when mice discriminated individual whiskers, suggesting it is an inherent feature. Thus, L2/3 combines two distinct components: a stable columnar framework of CW-tuned cells that may promote spatial perceptual stability, plus an intermixed, non-columnar surround with highly unstable tuning.
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21
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Jeon BB, Fuchs T, Chase SM, Kuhlman SJ. Visual experience has opposing influences on the quality of stimulus representation in adult primary visual cortex. eLife 2022; 11:80361. [PMID: 36321876 PMCID: PMC9629826 DOI: 10.7554/elife.80361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 10/21/2022] [Indexed: 11/07/2022] Open
Abstract
Transient dark exposure, typically 7–10 days in duration, followed by light reintroduction is an emerging treatment for improving the restoration of vision in amblyopic subjects whose occlusion is removed in adulthood. Dark exposure initiates homeostatic mechanisms that together with light-induced changes in cellular signaling pathways result in the re-engagement of juvenile-like plasticity in the adult such that previously deprived inputs can gain cortical territory. It is possible that dark exposure itself degrades visual responses, and this could place constraints on the optimal duration of dark exposure treatment. To determine whether eight days of dark exposure has a lasting negative impact on responses to classic grating stimuli, neural activity was recorded before and after dark exposure in awake head-fixed mice using two-photon calcium imaging. Neural discriminability, assessed using classifiers, was transiently reduced following dark exposure; a decrease in response reliability across a broad range of spatial frequencies likely contributed to the disruption. Both discriminability and reliability recovered. Fixed classifiers were used to demonstrate that stimulus representation rebounded to the original, pre-deprivation state, thus dark exposure did not appear to have a lasting negative impact on visual processing. Unexpectedly, we found that dark exposure significantly stabilized orientation preference and signal correlation. Our results reveal that natural vision exerts a disrupting influence on the stability of stimulus preference for classic grating stimuli and, at the same time, improves neural discriminability for both low and high-spatial frequency stimuli.
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Affiliation(s)
- Brian B Jeon
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, United States.,Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, United States
| | - Thomas Fuchs
- Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, United States.,Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, United States
| | - Steven M Chase
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, United States.,Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, United States
| | - Sandra J Kuhlman
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, United States.,Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, United States.,Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, United States
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22
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Sadeh S, Clopath C. Contribution of behavioural variability to representational drift. eLife 2022; 11:e77907. [PMID: 36040010 PMCID: PMC9481246 DOI: 10.7554/elife.77907] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 08/24/2022] [Indexed: 11/25/2022] Open
Abstract
Neuronal responses to similar stimuli change dynamically over time, raising the question of how internal representations can provide a stable substrate for neural coding. Recent work has suggested a large degree of drift in neural representations even in sensory cortices, which are believed to store stable representations of the external world. While the drift of these representations is mostly characterized in relation to external stimuli, the behavioural state of the animal (for instance, the level of arousal) is also known to strongly modulate the neural activity. We therefore asked how the variability of such modulatory mechanisms can contribute to representational changes. We analysed large-scale recording of neural activity from the Allen Brain Observatory, which was used before to document representational drift in the mouse visual cortex. We found that, within these datasets, behavioural variability significantly contributes to representational changes. This effect was broadcasted across various cortical areas in the mouse, including the primary visual cortex, higher order visual areas, and even regions not primarily linked to vision like hippocampus. Our computational modelling suggests that these results are consistent with independent modulation of neural activity by behaviour over slower timescales. Importantly, our analysis suggests that reliable but variable modulation of neural representations by behaviour can be misinterpreted as representational drift if neuronal representations are only characterized in the stimulus space and marginalized over behavioural parameters.
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Affiliation(s)
- Sadra Sadeh
- Department of Bioengineering, Imperial College LondonLondonUnited Kingdom
| | - Claudia Clopath
- Department of Bioengineering, Imperial College LondonLondonUnited Kingdom
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23
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Avitan L, Stringer C. Not so spontaneous: Multi-dimensional representations of behaviors and context in sensory areas. Neuron 2022; 110:3064-3075. [PMID: 35863344 DOI: 10.1016/j.neuron.2022.06.019] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 06/20/2022] [Accepted: 06/22/2022] [Indexed: 11/27/2022]
Abstract
Sensory areas are spontaneously active in the absence of sensory stimuli. This spontaneous activity has long been studied; however, its functional role remains largely unknown. Recent advances in technology, allowing large-scale neural recordings in the awake and behaving animal, have transformed our understanding of spontaneous activity. Studies using these recordings have discovered high-dimensional spontaneous activity patterns, correlation between spontaneous activity and behavior, and dissimilarity between spontaneous and sensory-driven activity patterns. These findings are supported by evidence from developing animals, where a transition toward these characteristics is observed as the circuit matures, as well as by evidence from mature animals across species. These newly revealed characteristics call for the formulation of a new role for spontaneous activity in neural sensory computation.
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Affiliation(s)
- Lilach Avitan
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
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24
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Existing function in primary visual cortex is not perturbed by new skill acquisition of a non-matched sensory task. Nat Commun 2022; 13:3638. [PMID: 35752622 PMCID: PMC9233699 DOI: 10.1038/s41467-022-31440-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 06/16/2022] [Indexed: 02/07/2023] Open
Abstract
Acquisition of new skills has the potential to disturb existing network function. To directly assess whether previously acquired cortical function is altered during learning, mice were trained in an abstract task in which selected activity patterns were rewarded using an optical brain-computer interface device coupled to primary visual cortex (V1) neurons. Excitatory neurons were longitudinally recorded using 2-photon calcium imaging. Despite significant changes in local neural activity during task performance, tuning properties and stimulus encoding assessed outside of the trained context were not perturbed. Similarly, stimulus tuning was stable in neurons that remained responsive following a different, visual discrimination training task. However, visual discrimination training increased the rate of representational drift. Our results indicate that while some forms of perceptual learning may modify the contribution of individual neurons to stimulus encoding, new skill learning is not inherently disruptive to the quality of stimulus representation in adult V1.
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25
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Oude Lohuis MN, Pie JL, Marchesi P, Montijn JS, de Kock CPJ, Pennartz CMA, Olcese U. Multisensory task demands temporally extend the causal requirement for visual cortex in perception. Nat Commun 2022; 13:2864. [PMID: 35606448 PMCID: PMC9126973 DOI: 10.1038/s41467-022-30600-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 05/09/2022] [Indexed: 01/02/2023] Open
Abstract
Primary sensory areas constitute crucial nodes during perceptual decision making. However, it remains unclear to what extent they mainly constitute a feedforward processing step, or rather are continuously involved in a recurrent network together with higher-order areas. We found that the temporal window in which primary visual cortex is required for the detection of identical visual stimuli was extended when task demands were increased via an additional sensory modality that had to be monitored. Late-onset optogenetic inactivation preserved bottom-up, early-onset responses which faithfully encoded stimulus features, and was effective in impairing detection only if it preceded a late, report-related phase of the cortical response. Increasing task demands were marked by longer reaction times and the effect of late optogenetic inactivation scaled with reaction time. Thus, independently of visual stimulus complexity, multisensory task demands determine the temporal requirement for ongoing sensory-related activity in V1, which overlaps with report-related activity. How primary sensory cortices contribute to decision making remains poorly understood. Here the authors report that increasing task demands extend the temporal window in which the primary visual cortex is required for detecting identical stimuli.
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26
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Ebrahimi S, Lecoq J, Rumyantsev O, Tasci T, Zhang Y, Irimia C, Li J, Ganguli S, Schnitzer MJ. Emergent reliability in sensory cortical coding and inter-area communication. Nature 2022; 605:713-721. [PMID: 35589841 PMCID: PMC10985415 DOI: 10.1038/s41586-022-04724-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 04/04/2022] [Indexed: 12/16/2022]
Abstract
Reliable sensory discrimination must arise from high-fidelity neural representations and communication between brain areas. However, how neocortical sensory processing overcomes the substantial variability of neuronal sensory responses remains undetermined1-6. Here we imaged neuronal activity in eight neocortical areas concurrently and over five days in mice performing a visual discrimination task, yielding longitudinal recordings of more than 21,000 neurons. Analyses revealed a sequence of events across the neocortex starting from a resting state, to early stages of perception, and through the formation of a task response. At rest, the neocortex had one pattern of functional connections, identified through sets of areas that shared activity cofluctuations7,8. Within about 200 ms after the onset of the sensory stimulus, such connections rearranged, with different areas sharing cofluctuations and task-related information. During this short-lived state (approximately 300 ms duration), both inter-area sensory data transmission and the redundancy of sensory encoding peaked, reflecting a transient increase in correlated fluctuations among task-related neurons. By around 0.5 s after stimulus onset, the visual representation reached a more stable form, the structure of which was robust to the prominent, day-to-day variations in the responses of individual cells. About 1 s into stimulus presentation, a global fluctuation mode conveyed the upcoming response of the mouse to every area examined and was orthogonal to modes carrying sensory data. Overall, the neocortex supports sensory performance through brief elevations in sensory coding redundancy near the start of perception, neural population codes that are robust to cellular variability, and widespread inter-area fluctuation modes that transmit sensory data and task responses in non-interfering channels.
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Affiliation(s)
- Sadegh Ebrahimi
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA.
- CNC Program, Stanford University, Stanford, CA, USA.
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
- Department of Biology, Stanford University, Stanford, CA, USA.
| | - Jérôme Lecoq
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | - Oleg Rumyantsev
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Tugce Tasci
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Yanping Zhang
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Cristina Irimia
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- CNC Program, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Jane Li
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Surya Ganguli
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Mark J Schnitzer
- James Clark Center for Biomedical Engineering, Stanford University, Stanford, CA, USA.
- CNC Program, Stanford University, Stanford, CA, USA.
- Department of Biology, Stanford University, Stanford, CA, USA.
- Department of Applied Physics, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
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27
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Bauer J, Rose T. Mouse vision: Variability and stability across the visual processing hierarchy. Curr Biol 2021; 31:R1129-R1132. [PMID: 34637715 DOI: 10.1016/j.cub.2021.08.071] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The response of individual neurons to stable sensory input or behavioral output can change over time. A new study provides evidence from the mouse visual system that such drift does not follow the hierarchy of information flow across the brain.
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Affiliation(s)
- Joel Bauer
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Tobias Rose
- Institute for Experimental Epileptology and Cognition Research, University of Bonn, Venusberg-Campus 1, 53127 Bonn, Germany.
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28
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Deitch D, Rubin A, Ziv Y. Representational drift in the mouse visual cortex. Curr Biol 2021; 31:4327-4339.e6. [PMID: 34433077 DOI: 10.1016/j.cub.2021.07.062] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 07/02/2021] [Accepted: 07/26/2021] [Indexed: 10/20/2022]
Abstract
Recent studies have shown that neuronal representations gradually change over time despite no changes in the stimulus, environment, or behavior. However, such representational drift has been assumed to be a property of high-level brain structures, whereas earlier circuits, such as sensory cortices, have been assumed to stably encode information over time. Here, we analyzed large-scale optical and electrophysiological recordings from six visual cortical areas in behaving mice that were repeatedly presented with the same natural movies. Contrary to the prevailing notion, we found representational drift over timescales spanning minutes to days across multiple visual areas, cortical layers, and cell types. Notably, neural-code stability did not reflect the hierarchy of information flow across areas. Although individual neurons showed time-dependent changes in their coding properties, the structure of the relationships between population activity patterns remained stable and stereotypic. Such population-level organization may underlie stable visual perception despite continuous changes in neuronal responses.
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Affiliation(s)
- Daniel Deitch
- Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Alon Rubin
- Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Yaniv Ziv
- Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel.
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29
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Montijn JS, Seignette K, Howlett MH, Cazemier JL, Kamermans M, Levelt CN, Heimel JA. A parameter-free statistical test for neuronal responsiveness. eLife 2021; 10:71969. [PMID: 34570697 PMCID: PMC8626082 DOI: 10.7554/elife.71969] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 09/22/2021] [Indexed: 01/13/2023] Open
Abstract
Neurophysiological studies depend on a reliable quantification of whether and when a neuron responds to stimulation. Simple methods to determine responsiveness require arbitrary parameter choices, such as binning size, while more advanced model-based methods require fitting and hyperparameter tuning. These parameter choices can change the results, which invites bad statistical practice and reduces the replicability. New recording techniques that yield increasingly large numbers of cells would benefit from a test for cell-inclusion that requires no manual curation. Here, we present the parameter-free ZETA-test, which outperforms t-tests, ANOVAs, and renewal-process-based methods by including more cells at a similar false-positive rate. We show that our procedure works across brain regions and recording techniques, including calcium imaging and Neuropixels data. Furthermore, in illustration of the method, we show in mouse visual cortex that (1) visuomotor-mismatch and spatial location are encoded by different neuronal subpopulations and (2) optogenetic stimulation of VIP cells leads to early inhibition and subsequent disinhibition.
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Affiliation(s)
- Jorrit Steven Montijn
- Netherlands Institute for Neuroscience, Royal Dutch Academy for Arts and Sciences, Amsterdam, Netherlands
| | - Koen Seignette
- Netherlands Institute for Neuroscience, Royal Dutch Academy for Arts and Sciences, Amsterdam, Netherlands
| | - Marcus H Howlett
- Netherlands Institute for Neuroscience, Royal Dutch Academy for Arts and Sciences, Amsterdam, Netherlands
| | - J Leonie Cazemier
- Netherlands Institute for Neuroscience, Royal Dutch Academy for Arts and Sciences, Amsterdam, Netherlands
| | - Maarten Kamermans
- Retinal Signal Processing, Netherlands Institute for Neuroscience, Amsterdam, Netherlands
| | | | - J Alexander Heimel
- Netherlands Institute for Neuroscience, Royal Dutch Academy for Arts and Sciences, Amsterdam, Netherlands
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30
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Marks TD, Goard MJ. Stimulus-dependent representational drift in primary visual cortex. Nat Commun 2021; 12:5169. [PMID: 34453051 PMCID: PMC8397766 DOI: 10.1038/s41467-021-25436-3] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 08/11/2021] [Indexed: 02/07/2023] Open
Abstract
To produce consistent sensory perception, neurons must maintain stable representations of sensory input. However, neurons in many regions exhibit progressive drift across days. Longitudinal studies have found stable responses to artificial stimuli across sessions in visual areas, but it is unclear whether this stability extends to naturalistic stimuli. We performed chronic 2-photon imaging of mouse V1 populations to directly compare the representational stability of artificial versus naturalistic visual stimuli over weeks. Responses to gratings were highly stable across sessions. However, neural responses to naturalistic movies exhibited progressive representational drift across sessions. Differential drift was present across cortical layers, in inhibitory interneurons, and could not be explained by differential response strength or higher order stimulus statistics. However, representational drift was accompanied by similar differential changes in local population correlation structure. These results suggest representational stability in V1 is stimulus-dependent and may relate to differences in preexisting circuit architecture of co-tuned neurons.
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Affiliation(s)
- Tyler D Marks
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
| | - Michael J Goard
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA.
- Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA.
- Department of Psychological & Brain Sciences, University of California, Santa Barbara, CA, USA.
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31
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Xia J, Marks TD, Goard MJ, Wessel R. Stable representation of a naturalistic movie emerges from episodic activity with gain variability. Nat Commun 2021; 12:5170. [PMID: 34453045 PMCID: PMC8397750 DOI: 10.1038/s41467-021-25437-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 08/11/2021] [Indexed: 01/08/2023] Open
Abstract
Visual cortical responses are known to be highly variable across trials within an experimental session. However, the long-term stability of visual cortical responses is poorly understood. Here using chronic imaging of V1 in mice we show that neural responses to repeated natural movie clips are unstable across weeks. Individual neuronal responses consist of sparse episodic activity which are stable in time but unstable in gain across weeks. Further, we find that the individual episode, instead of neuron, serves as the basic unit of the week-to-week fluctuation. To investigate how population activity encodes the stimulus, we extract a stable one-dimensional representation of the time in the natural movie, using an unsupervised method. Most week-to-week fluctuation is perpendicular to the stimulus encoding direction, thus leaving the stimulus representation largely unaffected. We propose that precise episodic activity with coordinated gain changes are keys to maintain a stable stimulus representation in V1.
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Affiliation(s)
- Ji Xia
- Department of Physics, Washington University in St. Louis, St. Louis, MO, USA.
| | - Tyler D Marks
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
| | - Michael J Goard
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
- Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA
- Department of Psychological & Brain Sciences, University of California, Santa Barbara, CA, USA
| | - Ralf Wessel
- Department of Physics, Washington University in St. Louis, St. Louis, MO, USA
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32
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Pérez-Ortega J, Alejandre-García T, Yuste R. Long-term stability of cortical ensembles. eLife 2021; 10:e64449. [PMID: 34328414 PMCID: PMC8376248 DOI: 10.7554/elife.64449] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 07/29/2021] [Indexed: 12/25/2022] Open
Abstract
Neuronal ensembles, coactive groups of neurons found in spontaneous and evoked cortical activity, are causally related to memories and perception, but it is still unknown how stable or flexible they are over time. We used two-photon multiplane calcium imaging to track over weeks the activity of the same pyramidal neurons in layer 2/3 of the visual cortex from awake mice and recorded their spontaneous and visually evoked responses. Less than half of the neurons remained active across any two imaging sessions. These stable neurons formed ensembles that lasted weeks, but some ensembles were also transient and appeared only in one single session. Stable ensembles preserved most of their neurons for up to 46 days, our longest imaged period, and these 'core' cells had stronger functional connectivity. Our results demonstrate that neuronal ensembles can last for weeks and could, in principle, serve as a substrate for long-lasting representation of perceptual states or memories.
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Affiliation(s)
- Jesús Pérez-Ortega
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
| | | | - Rafael Yuste
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
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33
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Contribution of non-sensory neurons in visual cortical areas to visually guided decisions in the rat. Curr Biol 2021; 31:2757-2769.e6. [DOI: 10.1016/j.cub.2021.03.099] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 03/15/2021] [Accepted: 03/31/2021] [Indexed: 01/18/2023]
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34
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Meijer GT, Marchesi P, Mejias JF, Montijn JS, Lansink CS, Pennartz CMA. Neural Correlates of Multisensory Detection Behavior: Comparison of Primary and Higher-Order Visual Cortex. Cell Rep 2021; 31:107636. [PMID: 32402272 DOI: 10.1016/j.celrep.2020.107636] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 01/10/2020] [Accepted: 04/21/2020] [Indexed: 01/16/2023] Open
Abstract
We act upon stimuli in our surrounding environment by gathering the multisensory information they convey and by integrating this information to decide on a behavioral action. We hypothesized that the anterolateral secondary visual cortex (area AL) of the mouse brain may serve as a hub for sensorimotor transformation of audiovisual information. We imaged neuronal activity in primary visual cortex (V1) and AL of the mouse during a detection task using visual, auditory, and audiovisual stimuli. We found that AL neurons were more sensitive to weak uni- and multisensory stimuli compared to V1. Depending on contrast, different subsets of AL and V1 neurons showed cross-modal modulation of visual responses. During audiovisual stimulation, AL neurons showed stronger differentiation of behaviorally reported versus unreported stimuli compared to V1, whereas V1 showed this distinction during unisensory visual stimulation. Thus, neural population activity in area AL correlates more closely with multisensory detection behavior than V1.
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Affiliation(s)
- Guido T Meijer
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Pietro Marchesi
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Jorge F Mejias
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Jorrit S Montijn
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Carien S Lansink
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, 1098 XH Amsterdam, the Netherlands.
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, 1098 XH Amsterdam, the Netherlands.
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35
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Azeredo da Silveira R, Rieke F. The Geometry of Information Coding in Correlated Neural Populations. Annu Rev Neurosci 2021; 44:403-424. [PMID: 33863252 DOI: 10.1146/annurev-neuro-120320-082744] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Neurons in the brain represent information in their collective activity. The fidelity of this neural population code depends on whether and how variability in the response of one neuron is shared with other neurons. Two decades of studies have investigated the influence of these noise correlations on the properties of neural coding. We provide an overview of the theoretical developments on the topic. Using simple, qualitative, and general arguments, we discuss, categorize, and relate the various published results. We emphasize the relevance of the fine structure of noise correlation, and we present a new approach to the issue. Throughout this review, we emphasize a geometrical picture of how noise correlations impact the neural code.
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Affiliation(s)
| | - Fred Rieke
- Department of Physics, Ecole Normale Supérieure, 75005 Paris, France;
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36
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Stringer C, Michaelos M, Tsyboulski D, Lindo SE, Pachitariu M. High-precision coding in visual cortex. Cell 2021; 184:2767-2778.e15. [PMID: 33857423 DOI: 10.1016/j.cell.2021.03.042] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 03/04/2021] [Accepted: 03/19/2021] [Indexed: 01/18/2023]
Abstract
Individual neurons in visual cortex provide the brain with unreliable estimates of visual features. It is not known whether the single-neuron variability is correlated across large neural populations, thus impairing the global encoding of stimuli. We recorded simultaneously from up to 50,000 neurons in mouse primary visual cortex (V1) and in higher order visual areas and measured stimulus discrimination thresholds of 0.35° and 0.37°, respectively, in an orientation decoding task. These neural thresholds were almost 100 times smaller than the behavioral discrimination thresholds reported in mice. This discrepancy could not be explained by stimulus properties or arousal states. Furthermore, behavioral variability during a sensory discrimination task could not be explained by neural variability in V1. Instead, behavior-related neural activity arose dynamically across a network of non-sensory brain areas. These results imply that perceptual discrimination in mice is limited by downstream decoders, not by neural noise in sensory representations.
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Affiliation(s)
| | | | | | - Sarah E Lindo
- HHMI Janelia Research Campus, Ashburn, VA 20147, USA
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37
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Zeldenrust F, Gutkin B, Denéve S. Efficient and robust coding in heterogeneous recurrent networks. PLoS Comput Biol 2021; 17:e1008673. [PMID: 33930016 PMCID: PMC8115785 DOI: 10.1371/journal.pcbi.1008673] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 05/12/2021] [Accepted: 04/07/2021] [Indexed: 11/19/2022] Open
Abstract
Cortical networks show a large heterogeneity of neuronal properties. However, traditional coding models have focused on homogeneous populations of excitatory and inhibitory neurons. Here, we analytically derive a class of recurrent networks of spiking neurons that close to optimally track a continuously varying input online, based on two assumptions: 1) every spike is decoded linearly and 2) the network aims to reduce the mean-squared error between the input and the estimate. From this we derive a class of predictive coding networks, that unifies encoding and decoding and in which we can investigate the difference between homogeneous networks and heterogeneous networks, in which each neurons represents different features and has different spike-generating properties. We find that in this framework, 'type 1' and 'type 2' neurons arise naturally and networks consisting of a heterogeneous population of different neuron types are both more efficient and more robust against correlated noise. We make two experimental predictions: 1) we predict that integrators show strong correlations with other integrators and resonators are correlated with resonators, whereas the correlations are much weaker between neurons with different coding properties and 2) that 'type 2' neurons are more coherent with the overall network activity than 'type 1' neurons.
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Affiliation(s)
- Fleur Zeldenrust
- Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Boris Gutkin
- Group for Neural Theory, INSERM U960, Département d’Études Cognitives, École Normal Supérieure PSL University, Paris, France
- Center for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, Russia
| | - Sophie Denéve
- Group for Neural Theory, INSERM U960, Département d’Études Cognitives, École Normal Supérieure PSL University, Paris, France
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38
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Lu J, Zuo Y. Shedding light on learning and memory: optical interrogation of the synaptic circuitry. Curr Opin Neurobiol 2020; 67:138-144. [PMID: 33279804 DOI: 10.1016/j.conb.2020.10.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 10/16/2020] [Accepted: 10/18/2020] [Indexed: 01/02/2023]
Abstract
In the quest for the physical substrate of learning and memory, a consensus gradually emerges that memory traces are stored in specific neuronal populations and the synaptic circuits that connect them. In this review, we discuss recent progresses in understanding the reorganization of synaptic circuits and neuronal assemblies associated with learning and memory, with an emphasis on optical techniques for in vivo interrogations. We also highlight some open questions on the missing link between synaptic modifications and neuronal coding, and how stable memory persists despite synaptic and neuronal fluctuations.
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Affiliation(s)
- Ju Lu
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA
| | - Yi Zuo
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.
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39
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Kowalewski NN, Kauttonen J, Stan PL, Jeon BB, Fuchs T, Chase SM, Lee TS, Kuhlman SJ. Development of Natural Scene Representation in Primary Visual Cortex Requires Early Postnatal Experience. Curr Biol 2020; 31:369-380.e5. [PMID: 33220181 DOI: 10.1016/j.cub.2020.10.046] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 09/10/2020] [Accepted: 10/15/2020] [Indexed: 02/07/2023]
Abstract
The development of the visual system is known to be shaped by early-life experience. To identify response properties that contribute to enhanced natural scene representation, we performed calcium imaging of excitatory neurons in the primary visual cortex (V1) of awake mice raised in three different conditions (standard-reared, dark-reared, and delayed-visual experience) and compared neuronal responses to natural scene features in relation to simpler grating stimuli that varied in orientation and spatial frequency. We assessed population selectivity in the V1 by using decoding methods and found that natural scene discriminability increased by 75% between the ages of 4 and 6 weeks. Both natural scene and grating discriminability were higher in standard-reared animals than in those raised in the dark. This increase in discriminability was accompanied by a reduction in the number of neurons that responded to low-spatial-frequency gratings. At the same time, there was an increase in neuronal preference for natural scenes. Light exposure restricted to a 2- to 4-week window during adulthood did not induce improvements in natural scene or in grating stimulus discriminability. Our results demonstrate that experience reduces the number of neurons needed to effectively encode grating stimuli and that early visual experience enhances natural scene discriminability by directly increasing responsiveness to natural scene features.
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Affiliation(s)
- Nina N Kowalewski
- Department of Biological Sciences, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Janne Kauttonen
- Department of Biological Sciences, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA; Center for the Neural Basis of Cognition, 1400 Locust Street, Pittsburgh, PA 15219, USA
| | - Patricia L Stan
- Center for the Neural Basis of Cognition, 1400 Locust Street, Pittsburgh, PA 15219, USA; University of Pittsburgh Center for Neuroscience, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Brian B Jeon
- Department of Biomedical Engineering, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Thomas Fuchs
- Department of Biological Sciences, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA; Center for the Neural Basis of Cognition, 1400 Locust Street, Pittsburgh, PA 15219, USA; Neuroscience Institute, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Steven M Chase
- Center for the Neural Basis of Cognition, 1400 Locust Street, Pittsburgh, PA 15219, USA; Department of Biomedical Engineering, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Tai Sing Lee
- Center for the Neural Basis of Cognition, 1400 Locust Street, Pittsburgh, PA 15219, USA; Neuroscience Institute, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA; Department of Computer Science, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Sandra J Kuhlman
- Department of Biological Sciences, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA; Center for the Neural Basis of Cognition, 1400 Locust Street, Pittsburgh, PA 15219, USA; University of Pittsburgh Center for Neuroscience, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA; Department of Biomedical Engineering, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA.
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40
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Abstract
Neural oscillations play an important role in the integration and segregation of brain regions that are important for brain functions, including pain. Disturbances in oscillatory activity are associated with several disease states, including chronic pain. Studies of neural oscillations related to pain have identified several functional bands, especially alpha, beta, and gamma bands, implicated in nociceptive processing. In this review, we introduce several properties of neural oscillations that are important to understand the role of brain oscillations in nociceptive processing. We also discuss the role of neural oscillations in the maintenance of efficient communication in the brain. Finally, we discuss the role of neural oscillations in healthy and chronic pain nociceptive processing. These data and concepts illustrate the key role of regional and interregional neural oscillations in nociceptive processing underlying acute and chronic pains.
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Affiliation(s)
- Junseok A. Kim
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Karen D. Davis
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Surgery, University of Toronto, Toronto, Ontario, Canada
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41
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Rule ME, Loback AR, Raman DV, Driscoll LN, Harvey CD, O'Leary T. Stable task information from an unstable neural population. eLife 2020; 9:51121. [PMID: 32660692 PMCID: PMC7392606 DOI: 10.7554/elife.51121] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 06/17/2020] [Indexed: 02/06/2023] Open
Abstract
Over days and weeks, neural activity representing an animal's position and movement in sensorimotor cortex has been found to continually reconfigure or 'drift' during repeated trials of learned tasks, with no obvious change in behavior. This challenges classical theories, which assume stable engrams underlie stable behavior. However, it is not known whether this drift occurs systematically, allowing downstream circuits to extract consistent information. Analyzing long-term calcium imaging recordings from posterior parietal cortex in mice (Mus musculus), we show that drift is systematically constrained far above chance, facilitating a linear weighted readout of behavioral variables. However, a significant component of drift continually degrades a fixed readout, implying that drift is not confined to a null coding space. We calculate the amount of plasticity required to compensate drift independently of any learning rule, and find that this is within physiologically achievable bounds. We demonstrate that a simple, biologically plausible local learning rule can achieve these bounds, accurately decoding behavior over many days.
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Affiliation(s)
- Michael E Rule
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
| | - Adrianna R Loback
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
| | - Dhruva V Raman
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
| | - Laura N Driscoll
- Department of Electrical Engineering, Stanford University, Stanford, United States
| | | | - Timothy O'Leary
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
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42
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Sachdeva PS, Livezey JA, DeWeese MR. Heterogeneous Synaptic Weighting Improves Neural Coding in the Presence of Common Noise. Neural Comput 2020; 32:1239-1276. [PMID: 32433901 DOI: 10.1162/neco_a_01287] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Simultaneous recordings from the cortex have revealed that neural activity is highly variable and that some variability is shared across neurons in a population. Further experimental work has demonstrated that the shared component of a neuronal population's variability is typically comparable to or larger than its private component. Meanwhile, an abundance of theoretical work has assessed the impact that shared variability has on a population code. For example, shared input noise is understood to have a detrimental impact on a neural population's coding fidelity. However, other contributions to variability, such as common noise, can also play a role in shaping correlated variability. We present a network of linear-nonlinear neurons in which we introduce a common noise input to model-for instance, variability resulting from upstream action potentials that are irrelevant to the task at hand. We show that by applying a heterogeneous set of synaptic weights to the neural inputs carrying the common noise, the network can improve its coding ability as measured by both Fisher information and Shannon mutual information, even in cases where this results in amplification of the common noise. With a broad and heterogeneous distribution of synaptic weights, a population of neurons can remove the harmful effects imposed by afferents that are uninformative about a stimulus. We demonstrate that some nonlinear networks benefit from weight diversification up to a certain population size, above which the drawbacks from amplified noise dominate over the benefits of diversification. We further characterize these benefits in terms of the relative strength of shared and private variability sources. Finally, we studied the asymptotic behavior of the mutual information and Fisher information analytically in our various networks as a function of population size. We find some surprising qualitative changes in the asymptotic behavior as we make seemingly minor changes in the synaptic weight distributions.
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Affiliation(s)
- Pratik S Sachdeva
- Redwood Center for Theoretical Neuroscience and Department of Physics, University of California, Berkeley, Berkeley, CA 94720 U.S.A., and Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, U.S.A.
| | - Jesse A Livezey
- Redwood Center for Theoretical Neuroscience, University of California, Berkeley, Berkeley, CA 94720, U.S.A., and Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, U.S.A.
| | - Michael R DeWeese
- Redwood Center for Theoretical Neuroscience, Department of Physics, and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720 U.S.A.
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43
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Reimann HM, Niendorf T. The (Un)Conscious Mouse as a Model for Human Brain Functions: Key Principles of Anesthesia and Their Impact on Translational Neuroimaging. Front Syst Neurosci 2020; 14:8. [PMID: 32508601 PMCID: PMC7248373 DOI: 10.3389/fnsys.2020.00008] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 01/27/2020] [Indexed: 12/11/2022] Open
Abstract
In recent years, technical and procedural advances have brought functional magnetic resonance imaging (fMRI) to the field of murine neuroscience. Due to its unique capacity to measure functional activity non-invasively, across the entire brain, fMRI allows for the direct comparison of large-scale murine and human brain functions. This opens an avenue for bidirectional translational strategies to address fundamental questions ranging from neurological disorders to the nature of consciousness. The key challenges of murine fMRI are: (1) to generate and maintain functional brain states that approximate those of calm and relaxed human volunteers, while (2) preserving neurovascular coupling and physiological baseline conditions. Low-dose anesthetic protocols are commonly applied in murine functional brain studies to prevent stress and facilitate a calm and relaxed condition among animals. Yet, current mono-anesthesia has been shown to impair neural transmission and hemodynamic integrity. By linking the current state of murine electrophysiology, Ca2+ imaging and fMRI of anesthetic effects to findings from human studies, this systematic review proposes general principles to design, apply and monitor anesthetic protocols in a more sophisticated way. The further development of balanced multimodal anesthesia, combining two or more drugs with complementary modes of action helps to shape and maintain specific brain states and relevant aspects of murine physiology. Functional connectivity and its dynamic repertoire as assessed by fMRI can be used to make inferences about cortical states and provide additional information about whole-brain functional dynamics. Based on this, a simple and comprehensive functional neurosignature pattern can be determined for use in defining brain states and anesthetic depth in rest and in response to stimuli. Such a signature can be evaluated and shared between labs to indicate the brain state of a mouse during experiments, an important step toward translating findings across species.
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Affiliation(s)
- Henning M. Reimann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine, Helmholtz Association of German Research Centers (HZ), Berlin, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine, Helmholtz Association of German Research Centers (HZ), Berlin, Germany
- Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Berlin, Germany
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44
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Information-Limiting Correlations in Large Neural Populations. J Neurosci 2020; 40:1668-1678. [PMID: 31941667 DOI: 10.1523/jneurosci.2072-19.2019] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 11/22/2019] [Accepted: 12/22/2019] [Indexed: 11/21/2022] Open
Abstract
Understanding the neural code requires understanding how populations of neurons code information. Theoretical models predict that information may be limited by correlated noise in large neural populations. Nevertheless, analyses based on tens of neurons have failed to find evidence of saturation. Moreover, some studies have shown that noise correlations can be very small, and therefore may not affect information coding. To determine whether information-limiting correlations exist, we implanted eight Utah arrays in prefrontal cortex (PFC; area 46) of two male macaque monkeys, recording >500 neurons simultaneously. We estimated information in PFC about saccades as a function of ensemble size. Noise correlations were, on average, small (∼10-3). However, information scaled strongly sublinearly with ensemble size. After shuffling trials, destroying noise correlations, information was a linear function of ensemble size. Thus, we provide evidence for the existence of information-limiting noise correlations in large populations of PFC neurons.SIGNIFICANCE STATEMENT Recent theoretical work has shown that even small correlations can limit information if they are "differential correlations," which are difficult to measure directly. However, they can be detected through decoding analyses on recordings from a large number of neurons over a large number of trials. We have achieved both by collecting neural activity in dorsal-lateral prefrontal cortex of macaques using eight microelectrode arrays (768 electrodes), from which we were able to compute accurate information estimates. We show, for the first time, strong evidence for information-limiting correlations. Despite pairwise correlations being small (on the order of 10-3), they affect information coding in populations on the order of 100 s of neurons.
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45
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Betzel RF, Wood KC, Angeloni C, Neimark Geffen M, Bassett DS. Stability of spontaneous, correlated activity in mouse auditory cortex. PLoS Comput Biol 2019; 15:e1007360. [PMID: 31815941 PMCID: PMC6968873 DOI: 10.1371/journal.pcbi.1007360] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 01/17/2020] [Accepted: 08/24/2019] [Indexed: 12/31/2022] Open
Abstract
Neural systems can be modeled as complex networks in which neural elements are represented as nodes linked to one another through structural or functional connections. The resulting network can be analyzed using mathematical tools from network science and graph theory to quantify the system’s topological organization and to better understand its function. Here, we used two-photon calcium imaging to record spontaneous activity from the same set of cells in mouse auditory cortex over the course of several weeks. We reconstruct functional networks in which cells are linked to one another by edges weighted according to the correlation of their fluorescence traces. We show that the networks exhibit modular structure across multiple topological scales and that these multi-scale modules unfold as part of a hierarchy. We also show that, on average, network architecture becomes increasingly dissimilar over time, with similarity decaying monotonically with the distance (in time) between sessions. Finally, we show that a small fraction of cells maintain strongly-correlated activity over multiple days, forming a stable temporal core surrounded by a fluctuating and variable periphery. Our work indicates a framework for studying spontaneous activity measured by two-photon calcium imaging using computational methods and graphical models from network science. The methods are flexible and easily extended to additional datasets, opening the possibility of studying cellular level network organization of neural systems and how that organization is modulated by stimuli or altered in models of disease. Neurons coordinate their activity with one another, forming networks that help support adaptive, flexible behavior. Still, little is known about the organization of these networks at the cellular scale and their stability over time. Here, we reconstruct networks from calcium imaging data recorded in mouse primary auditory cortex. We show that these networks exhibit spatially constrained, hierarchical modular structure, which may facilitate specialized information processing. However, we show that connection weights and modular structure are also variable over time, changing on a timescale of days and adopting novel network configurations. Despite this, a small subset of neurons maintain their connections to one another and preserve their modular organization across time, forming a stable temporal core surrounded by a flexible periphery. These findings represent a conceptual bridge linking network analyses of macroscale and cellular-level neuroimaging data. They also represent a complementary approach to existing circuits- and systems-based interrogation of nervous system function, opening the door for deeper and more targeted analysis in the future.
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Affiliation(s)
- Richard F Betzel
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.,Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.,Cognitive Science Program, Indiana University, Bloomington, Indiana, United States of America.,Program in Neuroscience, Indiana University, Bloomington, Indiana, United States of America.,Network Science Institute, Indiana University, Bloomington, Indiana, United States of America
| | - Katherine C Wood
- Department of Otorhinolaryngology: HNS, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Christopher Angeloni
- Department of Otorhinolaryngology: HNS, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Maria Neimark Geffen
- Department of Otorhinolaryngology: HNS, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Danielle S Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.,Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.,Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.,Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.,Santa Fe Institute, Santa Fa, New Mexico, United States of America
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46
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Abstract
The normalization model provides an elegant account of contextual modulation in individual neurons of primary visual cortex. Understanding the implications of normalization at the population level is hindered by the heterogeneity of cortical neurons, which differ in the composition of their normalization pools and semi-saturation constants. Here we introduce a geometric approach to investigate contextual modulation in neural populations and study how the representation of stimulus orientation is transformed by the presence of a mask. We find that population responses can be embedded in a low-dimensional space and that an affine transform can account for the effects of masking. The geometric analysis further reveals a link between changes in discriminability and bias induced by the mask. We propose the geometric approach can yield new insights into the image processing computations taking place in early visual cortex at the population level while coping with the heterogeneity of single cell behavior.
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Affiliation(s)
- Dario L Ringach
- Departments of Neurobiology and Psychology, UCLA, Los Angeles, CA, 90095, USA.
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47
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Rule ME, O'Leary T, Harvey CD. Causes and consequences of representational drift. Curr Opin Neurobiol 2019; 58:141-147. [PMID: 31569062 PMCID: PMC7385530 DOI: 10.1016/j.conb.2019.08.005] [Citation(s) in RCA: 99] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 08/13/2019] [Accepted: 08/27/2019] [Indexed: 01/27/2023]
Abstract
The nervous system learns new associations while maintaining memories over long periods, exhibiting a balance between flexibility and stability. Recent experiments reveal that neuronal representations of learned sensorimotor tasks continually change over days and weeks, even after animals have achieved expert behavioral performance. How is learned information stored to allow consistent behavior despite ongoing changes in neuronal activity? What functions could ongoing reconfiguration serve? We highlight recent experimental evidence for such representational drift in sensorimotor systems, and discuss how this fits into a framework of distributed population codes. We identify recent theoretical work that suggests computational roles for drift and argue that the recurrent and distributed nature of sensorimotor representations permits drift while limiting disruptive effects. We propose that representational drift may create error signals between interconnected brain regions that can be used to keep neural codes consistent in the presence of continual change. These concepts suggest experimental and theoretical approaches to studying both learning and maintenance of distributed and adaptive population codes.
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Affiliation(s)
- Michael E Rule
- Department of Engineering, University of Cambridge, Cambridge CB21PZ, United Kingdom
| | - Timothy O'Leary
- Department of Engineering, University of Cambridge, Cambridge CB21PZ, United Kingdom.
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48
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LeMessurier AM, Laboy-Juárez KJ, McClain K, Chen S, Nguyen T, Feldman DE. Enrichment drives emergence of functional columns and improves sensory coding in the whisker map in L2/3 of mouse S1. eLife 2019; 8:46321. [PMID: 31418693 PMCID: PMC6697414 DOI: 10.7554/elife.46321] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 08/01/2019] [Indexed: 12/02/2022] Open
Abstract
Sensory maps in layer (L) 2/3 of rodent cortex lack precise functional column boundaries, and instead exhibit locally heterogeneous (salt-and-pepper) tuning superimposed on smooth global topography. Could this organization be a byproduct of impoverished experience in laboratory housing? We compared whisker map somatotopy in L2/3 and L4 excitatory cells of somatosensory (S1) cortex in normally housed vs. tactile-enriched mice, using GCaMP6s imaging. Normally housed mice had a dispersed, salt-and-pepper whisker map in L2/3, but L4 was more topographically precise. Enrichment (P21 to P46-71) sharpened whisker tuning and decreased, but did not abolish, local tuning heterogeneity. In L2/3, enrichment strengthened and sharpened whisker point representations, and created functional boundaries of tuning similarity and noise correlations at column edges. Thus, enrichment drives emergence of functional columnar topography in S1, and reduces local tuning heterogeneity. These changes predict better touch detection by neural populations within each column.
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Affiliation(s)
- Amy M LeMessurier
- Department of Molecular and Cellular Biology, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
| | - Keven J Laboy-Juárez
- Department of Molecular and Cellular Biology, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
| | - Kathryn McClain
- Department of Molecular and Cellular Biology, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
| | - Shilin Chen
- Department of Molecular and Cellular Biology, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
| | - Theresa Nguyen
- Department of Molecular and Cellular Biology, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
| | - Daniel E Feldman
- Department of Molecular and Cellular Biology, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
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49
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Stringer C, Pachitariu M, Steinmetz N, Reddy CB, Carandini M, Harris KD. Spontaneous behaviors drive multidimensional, brainwide activity. Science 2019; 364:255. [PMID: 31000656 PMCID: PMC6525101 DOI: 10.1126/science.aav7893] [Citation(s) in RCA: 698] [Impact Index Per Article: 139.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 02/26/2019] [Indexed: 12/13/2022]
Abstract
Neuronal populations in sensory cortex produce variable responses to sensory stimuli and exhibit intricate spontaneous activity even without external sensory input. Cortical variability and spontaneous activity have been variously proposed to represent random noise, recall of prior experience, or encoding of ongoing behavioral and cognitive variables. Recording more than 10,000 neurons in mouse visual cortex, we observed that spontaneous activity reliably encoded a high-dimensional latent state, which was partially related to the mouse's ongoing behavior and was represented not just in visual cortex but also across the forebrain. Sensory inputs did not interrupt this ongoing signal but added onto it a representation of external stimuli in orthogonal dimensions. Thus, visual cortical population activity, despite its apparently noisy structure, reliably encodes an orthogonal fusion of sensory and multidimensional behavioral information.
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Affiliation(s)
- Carsen Stringer
- HHMI Janelia Research Campus, Ashburn, VA 20147, USA.
- Gatsby Computational Neuroscience Unit, UCL, London W1T 4JG, UK
| | - Marius Pachitariu
- HHMI Janelia Research Campus, Ashburn, VA 20147, USA.
- UCL Institute of Neurology, London WC1E 6DE, UK
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50
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Kobak D, Pardo-Vazquez JL, Valente M, Machens CK, Renart A. State-dependent geometry of population activity in rat auditory cortex. eLife 2019; 8:e44526. [PMID: 30969167 PMCID: PMC6491041 DOI: 10.7554/elife.44526] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 04/07/2019] [Indexed: 12/02/2022] Open
Abstract
The accuracy of the neural code depends on the relative embedding of signal and noise in the activity of neural populations. Despite a wealth of theoretical work on population codes, there are few empirical characterizations of the high-dimensional signal and noise subspaces. We studied the geometry of population codes in the rat auditory cortex across brain states along the activation-inactivation continuum, using sounds varying in difference and mean level across the ears. As the cortex becomes more activated, single-hemisphere populations go from preferring contralateral loud sounds to a symmetric preference across lateralizations and intensities, gain-modulation effectively disappears, and the signal and noise subspaces become approximately orthogonal to each other and to the direction corresponding to global activity modulations. Level-invariant decoding of sound lateralization also becomes possible in the active state. Our results provide an empirical foundation for the geometry and state-dependence of cortical population codes.
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Affiliation(s)
- Dmitry Kobak
- Champalimaud Center for the UnknownLisbonPortugal
- Institute for Ophthalmic ResearchUniversity of TübingenTübingenGermany
| | - Jose L Pardo-Vazquez
- Champalimaud Center for the UnknownLisbonPortugal
- Neuroscience and Motor Control GroupUniversity of A CoruñaCoruñaSpain
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