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Koren V, Malerba SB, Schwalger T, Panzeri S. Structure, dynamics, coding and optimal biophysical parameters of efficient excitatory-inhibitory spiking networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.24.590955. [PMID: 38712237 PMCID: PMC11071478 DOI: 10.1101/2024.04.24.590955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
The principle of efficient coding posits that sensory cortical networks are designed to encode maximal sensory information with minimal metabolic cost. Despite the major influence of efficient coding in neuro-science, it has remained unclear whether fundamental empirical properties of neural network activity can be explained solely based on this normative principle. Here, we rigorously derive the structural, coding, biophysical and dynamical properties of excitatory-inhibitory recurrent networks of spiking neurons that emerge directly from imposing that the network minimizes an instantaneous loss function and a time-averaged performance measure enacting efficient coding. The optimal network has biologically-plausible biophysical features, including realistic integrate-and-fire spiking dynamics, spike-triggered adaptation, and a non-stimulus-specific excitatory external input regulating metabolic cost. The efficient network has excitatory-inhibitory recurrent connectivity between neurons with similar stimulus tuning implementing feature-specific competition, similar to that recently found in visual cortex. Networks with unstructured connectivity cannot reach comparable levels of coding efficiency. The optimal biophysical parameters include 4 to 1 ratio of excitatory vs inhibitory neurons and 3 to 1 ratio of mean inhibitory-to-inhibitory vs. excitatory-to-inhibitory connectivity that closely match those of cortical sensory networks. The efficient network has biologically-plausible spiking dynamics, with a tight instantaneous E-I balance that makes them capable to achieve efficient coding of external stimuli varying over multiple time scales. Together, these results explain how efficient coding may be implemented in cortical networks and suggests that key properties of biological neural networks may be accounted for by efficient coding.
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2
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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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3
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Ouelhazi A, Bharmauria V, Molotchnikoff S. Adaptation-induced sharpening of orientation tuning curves in the mouse visual cortex. Neuroreport 2024; 35:291-298. [PMID: 38407865 DOI: 10.1097/wnr.0000000000002012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
OBJECTIVE Orientation selectivity is an emergent property of visual neurons across species with columnar and noncolumnar organization of the visual cortex. The emergence of orientation selectivity is more established in columnar cortical areas than in noncolumnar ones. Thus, how does orientation selectivity emerge in noncolumnar cortical areas after an adaptation protocol? Adaptation refers to the constant presentation of a nonoptimal stimulus (adapter) to a neuron under observation for a specific time. Previously, it had been shown that adaptation has varying effects on the tuning properties of neurons, such as orientation, spatial frequency, motion and so on. BASIC METHODS We recorded the mouse primary visual neurons (V1) at different orientations in the control (preadaptation) condition. This was followed by adapting neurons uninterruptedly for 12 min and then recording the same neurons postadaptation. An orientation selectivity index (OSI) for neurons was computed to compare them pre- and post-adaptation. MAIN RESULTS We show that 12-min adaptation increases the OSI of visual neurons ( n = 113), that is, sharpens their tuning. Moreover, the OSI postadaptation increases linearly as a function of the OSI preadaptation. CONCLUSION The increased OSI postadaptation may result from a specific dendritic neural mechanism, potentially facilitating the rapid learning of novel features.
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Affiliation(s)
- Afef Ouelhazi
- Département de Sciences Biologiques, Neurophysiology of the Visual system, Université de Montréal, Montréal, Québec
| | - Vishal Bharmauria
- Department of Psychology, Centre for Vision Research and Vision: Science to Applications (VISTA) Program, York University, Toronto, Ontario, Canada
| | - Stéphane Molotchnikoff
- Département de Sciences Biologiques, Neurophysiology of the Visual system, Université de Montréal, Montréal, Québec
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4
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Galván Fraile J, Scherr F, Ramasco JJ, Arkhipov A, Maass W, Mirasso CR. Modeling circuit mechanisms of opposing cortical responses to visual flow perturbations. PLoS Comput Biol 2024; 20:e1011921. [PMID: 38452057 PMCID: PMC10950248 DOI: 10.1371/journal.pcbi.1011921] [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: 10/12/2023] [Revised: 03/19/2024] [Accepted: 02/18/2024] [Indexed: 03/09/2024] Open
Abstract
In an ever-changing visual world, animals' survival depends on their ability to perceive and respond to rapidly changing motion cues. The primary visual cortex (V1) is at the forefront of this sensory processing, orchestrating neural responses to perturbations in visual flow. However, the underlying neural mechanisms that lead to distinct cortical responses to such perturbations remain enigmatic. In this study, our objective was to uncover the neural dynamics that govern V1 neurons' responses to visual flow perturbations using a biologically realistic computational model. By subjecting the model to sudden changes in visual input, we observed opposing cortical responses in excitatory layer 2/3 (L2/3) neurons, namely, depolarizing and hyperpolarizing responses. We found that this segregation was primarily driven by the competition between external visual input and recurrent inhibition, particularly within L2/3 and L4. This division was not observed in excitatory L5/6 neurons, suggesting a more prominent role for inhibitory mechanisms in the visual processing of the upper cortical layers. Our findings share similarities with recent experimental studies focusing on the opposing influence of top-down and bottom-up inputs in the mouse primary visual cortex during visual flow perturbations.
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Affiliation(s)
- J. Galván Fraile
- Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC), UIB-CSIC, Palma de Mallorca, Spain
| | - Franz Scherr
- Institute of Theoretical Computer Science, Graz University of Technology, Graz, Austria
| | - José J. Ramasco
- Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC), UIB-CSIC, Palma de Mallorca, Spain
| | - Anton Arkhipov
- Allen Institute, Seattle, Washington, United States of America
| | - Wolfgang Maass
- Institute of Theoretical Computer Science, Graz University of Technology, Graz, Austria
| | - Claudio R. Mirasso
- Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC), UIB-CSIC, Palma de Mallorca, Spain
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5
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Hatsopoulos N, Moore D, MacLean J, Walker J. A dynamic subset of network interactions underlies tuning to natural movements in marmoset sensorimotor cortex. RESEARCH SQUARE 2023:rs.3.rs-3750312. [PMID: 38234779 PMCID: PMC10793486 DOI: 10.21203/rs.3.rs-3750312/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Mechanisms of computation in sensorimotor cortex must be flexible and robust to support skilled motor behavior. Patterns of neuronal coactivity emerge as a result of computational processes. Pairwise spike-time statistical relationships, across the population, can be summarized as a functional network (FN) which retains single-unit properties. We record populations of single-unit neural activity in forelimb sensorimotor cortex during prey-capture and spontaneous behavior and use an encoding model incorporating kinematic trajectories and network features to predict single-unit activity during forelimb movements. The contribution of network features depends on structured connectivity within strongly connected functional groups. We identify a context-specific functional group that is highly tuned to kinematics and reorganizes its connectivity between spontaneous and prey-capture movements. In the remaining context-invariant group, interactions are comparatively stable across behaviors and units are less tuned to kinematics. This suggests different roles in producing natural forelimb movements and contextualizes single-unit tuning properties within population dynamics.
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6
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Zayyad ZA, Maunsell JHR, MacLean JN. Normalization in mouse primary visual cortex. PLoS One 2023; 18:e0295140. [PMID: 38109430 PMCID: PMC10727357 DOI: 10.1371/journal.pone.0295140] [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: 04/25/2023] [Accepted: 11/16/2023] [Indexed: 12/20/2023] Open
Abstract
When multiple stimuli appear together in the receptive field of a visual cortical neuron, the response is typically close to the average of that neuron's response to each individual stimulus. The departure from a linear sum of each individual response is referred to as normalization. In mammals, normalization has been best characterized in the visual cortex of macaques and cats. Here we study visually evoked normalization in the visual cortex of awake mice using imaging of calcium indicators in large populations of layer 2/3 (L2/3) V1 excitatory neurons and electrophysiological recordings across layers in V1. Regardless of recording method, mouse visual cortical neurons exhibit normalization to varying degrees. The distributions of normalization strength are similar to those described in cats and macaques, albeit slightly weaker on average.
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Affiliation(s)
- Zaina A. Zayyad
- Interdisciplinary Scientist Training Program, University of Chicago Pritzker School of Medicine, Chicago, IL, United States of America
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - John H. R. Maunsell
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, United States of America
- Department of Neurobiology, University of Chicago, Chicago, IL, United States of America
- Neuroscience Institute, University of Chicago, Chicago, IL, United States of America
| | - Jason N. MacLean
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, United States of America
- Department of Neurobiology, University of Chicago, Chicago, IL, United States of America
- Neuroscience Institute, University of Chicago, Chicago, IL, United States of America
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7
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Schütz A, Bharmauria V, Yan X, Wang H, Bremmer F, Crawford JD. Integration of landmark and saccade target signals in macaque frontal cortex visual responses. Commun Biol 2023; 6:938. [PMID: 37704829 PMCID: PMC10499799 DOI: 10.1038/s42003-023-05291-2] [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: 04/10/2021] [Accepted: 08/26/2023] [Indexed: 09/15/2023] Open
Abstract
Visual landmarks influence spatial cognition and behavior, but their influence on visual codes for action is poorly understood. Here, we test landmark influence on the visual response to saccade targets recorded from 312 frontal and 256 supplementary eye field neurons in rhesus macaques. Visual response fields are characterized by recording neural responses to various target-landmark combinations, and then we test against several candidate spatial models. Overall, frontal/supplementary eye fields response fields preferentially code either saccade targets (40%/40%) or landmarks (30%/4.5%) in gaze fixation-centered coordinates, but most cells show multiplexed target-landmark coding within intermediate reference frames (between fixation-centered and landmark-centered). Further, these coding schemes interact: neurons with near-equal target and landmark coding show the biggest shift from fixation-centered toward landmark-centered target coding. These data show that landmark information is preserved and influences target coding in prefrontal visual responses, likely to stabilize movement goals in the presence of noisy egocentric signals.
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Affiliation(s)
- Adrian Schütz
- Department of Neurophysics, Phillips Universität Marburg, Marburg, Germany
- Center for Mind, Brain, and Behavior - CMBB, Philipps-Universität Marburg, Marburg, Germany & Justus-Liebig-Universität Giessen, Giessen, Germany
| | - Vishal Bharmauria
- York Centre for Vision Research and Vision: Science to Applications Program, York University, Toronto, Canada
| | - Xiaogang Yan
- York Centre for Vision Research and Vision: Science to Applications Program, York University, Toronto, Canada
| | - Hongying Wang
- York Centre for Vision Research and Vision: Science to Applications Program, York University, Toronto, Canada
| | - Frank Bremmer
- Department of Neurophysics, Phillips Universität Marburg, Marburg, Germany
- Center for Mind, Brain, and Behavior - CMBB, Philipps-Universität Marburg, Marburg, Germany & Justus-Liebig-Universität Giessen, Giessen, Germany
| | - J Douglas Crawford
- York Centre for Vision Research and Vision: Science to Applications Program, York University, Toronto, Canada.
- Departments of Psychology, Biology, Kinesiology & Health Sciences, York University, Toronto, Canada.
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8
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Sundiang M, Hatsopoulos NG, MacLean JN. Dynamic structure of motor cortical neuron coactivity carries behaviorally relevant information. Netw Neurosci 2023; 7:661-678. [PMID: 37397877 PMCID: PMC10312288 DOI: 10.1162/netn_a_00298] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 12/02/2022] [Indexed: 01/28/2024] Open
Abstract
Skillful, voluntary movements are underpinned by computations performed by networks of interconnected neurons in the primary motor cortex (M1). Computations are reflected by patterns of coactivity between neurons. Using pairwise spike time statistics, coactivity can be summarized as a functional network (FN). Here, we show that the structure of FNs constructed from an instructed-delay reach task in nonhuman primates is behaviorally specific: Low-dimensional embedding and graph alignment scores show that FNs constructed from closer target reach directions are also closer in network space. Using short intervals across a trial, we constructed temporal FNs and found that temporal FNs traverse a low-dimensional subspace in a reach-specific trajectory. Alignment scores show that FNs become separable and correspondingly decodable shortly after the Instruction cue. Finally, we observe that reciprocal connections in FNs transiently decrease following the Instruction cue, consistent with the hypothesis that information external to the recorded population temporarily alters the structure of the network at this moment.
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Affiliation(s)
- Marina Sundiang
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, USA
| | - Nicholas G. Hatsopoulos
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, USA
- University of Chicago Neuroscience Institute, Chicago, IL, USA
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Jason N. MacLean
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, USA
- University of Chicago Neuroscience Institute, Chicago, IL, USA
- Department of Neurobiology, University of Chicago, Chicago, IL, USA
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9
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Zayyad ZA, Maunsell JHR, MacLean JN. Normalization in mouse primary visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.18.537260. [PMID: 37131716 PMCID: PMC10153131 DOI: 10.1101/2023.04.18.537260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
When multiple stimuli appear together in the receptive field of a visual cortical neuron, the response is typically close to the average of that neuron's response to each individual stimulus. The departure from a linear sum of each individual response is referred to as normalization. In mammals, normalization has been best characterized in the visual cortex of macaques and cats. Here we study visually evoked normalization in the visual cortex of awake mice using optical imaging of calcium indicators in large populations of layer 2/3 (L2/3) V1 excitatory neurons and electrophysiological recordings across layers in V1. Regardless of recording method, mouse visual cortical neurons exhibit normalization to varying degrees. The distributions of normalization strength are similar to those described in cats and macaques, albeit slightly weaker on average.
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Affiliation(s)
- Zaina A. Zayyad
- Interdisciplinary Scientist Training Program, University of Chicago Pritzker School of Medicine, Chicago, IL, United States of America
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - John H. R. Maunsell
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, United States of America
- Department of Neurobiology, University of Chicago, Chicago, IL, United States of America
- Neuroscience Institute, University of Chicago, Chicago, IL, United States of America
| | - Jason N. MacLean
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, United States of America
- Department of Neurobiology, University of Chicago, Chicago, IL, United States of America
- Neuroscience Institute, University of Chicago, Chicago, IL, United States of America
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10
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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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11
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Wide-Field Calcium Imaging of Neuronal Network Dynamics In Vivo. BIOLOGY 2022; 11:biology11111601. [PMID: 36358302 PMCID: PMC9687960 DOI: 10.3390/biology11111601] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 10/28/2022] [Accepted: 10/31/2022] [Indexed: 11/06/2022]
Abstract
A central tenet of neuroscience is that sensory, motor, and cognitive behaviors are generated by the communications and interactions among neurons, distributed within and across anatomically and functionally distinct brain regions. Therefore, to decipher how the brain plans, learns, and executes behaviors requires characterizing neuronal activity at multiple spatial and temporal scales. This includes simultaneously recording neuronal dynamics at the mesoscale level to understand the interactions among brain regions during different behavioral and brain states. Wide-field Ca2+ imaging, which uses single photon excitation and improved genetically encoded Ca2+ indicators, allows for simultaneous recordings of large brain areas and is proving to be a powerful tool to study neuronal activity at the mesoscopic scale in behaving animals. This review details the techniques used for wide-field Ca2+ imaging and the various approaches employed for the analyses of the rich neuronal-behavioral data sets obtained. Also discussed is how wide-field Ca2+ imaging is providing novel insights into both normal and altered neural processing in disease. Finally, we examine the limitations of the approach and new developments in wide-field Ca2+ imaging that are bringing new capabilities to this important technique for investigating large-scale neuronal dynamics.
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12
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Zhang L, Prince SM, Paulson AL, Singer AC. Goal discrimination in hippocampal nonplace cells when place information is ambiguous. Proc Natl Acad Sci U S A 2022; 119:e2107337119. [PMID: 35254897 PMCID: PMC8931233 DOI: 10.1073/pnas.2107337119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 01/30/2022] [Indexed: 11/18/2022] Open
Abstract
SignificanceGoal-directed spatial navigation has been found to rely on hippocampal neurons that are spatially modulated. We show that "nonplace" cells without significant spatial modulation play a role in discriminating goals when environmental cues for goals are ambiguous. This nonplace cell activity is performance-dependent and is modulated by gamma oscillations. Finally, nonplace cell goal discrimination coding fails in a mouse model of Alzheimer's disease (AD). Together, these results show that nonplace cell firing can signal unique task-relevant information when spatial information is ambiguous; these signals depend on performance and are absent in a mouse model of AD.
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Affiliation(s)
- Lu Zhang
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332
| | - Stephanie M. Prince
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332
- Neuroscience Graduate Program, Graduate Division of Biological and Biomedical Sciences, Emory University, Atlanta, GA 30322
| | - Abigail L. Paulson
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332
| | - Annabelle C. Singer
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332
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13
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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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