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Gandit B, Posani L, Zhang CL, Saha S, Ortiz C, Allegra M, Schmidt-Hieber C. Transformation of spatial representations along hippocampal circuits. iScience 2024; 27:110361. [PMID: 39071886 PMCID: PMC11277690 DOI: 10.1016/j.isci.2024.110361] [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: 08/18/2023] [Revised: 03/01/2024] [Accepted: 06/21/2024] [Indexed: 07/30/2024] Open
Abstract
The hippocampus is thought to provide the brain with a cognitive map of the external world by processing various types of spatial information. To understand how essential spatial variables such as direction, position, and distance are transformed along its circuits to construct this global map, we perform single-photon widefield microendoscope calcium imaging in the dentate gyrus and CA3 of mice freely navigating along a narrow corridor. We find that spatial activity maps in the dentate gyrus, but not in CA3, are correlated after aligning them to the running directions, suggesting that they represent the distance traveled along the track in egocentric coordinates. Together with population activity decoding, our data suggest that while spatial representations in the dentate gyrus and CA3 are anchored in both egocentric and allocentric coordinates, egocentric distance coding is more prevalent in the dentate gyrus than in CA3, providing insights into the assembly of the cognitive map.
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Affiliation(s)
- Bérénice Gandit
- Institut Pasteur, Université Paris Cité, Neural Circuits for Spatial Navigation and Memory, Department of Neuroscience, F-75015 Paris, France
- Sorbonne Université, Collège Doctoral, F-75005 Paris, France
| | - Lorenzo Posani
- Center for Theoretical Neuroscience, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Chun-Lei Zhang
- Institut Pasteur, Université Paris Cité, Neural Circuits for Spatial Navigation and Memory, Department of Neuroscience, F-75015 Paris, France
| | - Soham Saha
- Institut Pasteur, Université Paris Cité, Neural Circuits for Spatial Navigation and Memory, Department of Neuroscience, F-75015 Paris, France
| | - Cantin Ortiz
- Institut Pasteur, Université Paris Cité, Neural Circuits for Spatial Navigation and Memory, Department of Neuroscience, F-75015 Paris, France
- Sorbonne Université, Collège Doctoral, F-75005 Paris, France
| | - Manuela Allegra
- Institut Pasteur, Université Paris Cité, Neural Circuits for Spatial Navigation and Memory, Department of Neuroscience, F-75015 Paris, France
| | - Christoph Schmidt-Hieber
- Institut Pasteur, Université Paris Cité, Neural Circuits for Spatial Navigation and Memory, Department of Neuroscience, F-75015 Paris, France
- Institute for Physiology I, Jena University Hospital, 07743 Jena, Germany
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2
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Ostojic S, Fusi S. Computational role of structure in neural activity and connectivity. Trends Cogn Sci 2024; 28:677-690. [PMID: 38553340 DOI: 10.1016/j.tics.2024.03.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 02/29/2024] [Accepted: 03/07/2024] [Indexed: 07/05/2024]
Abstract
One major challenge of neuroscience is identifying structure in seemingly disorganized neural activity. Different types of structure have different computational implications that can help neuroscientists understand the functional role of a particular brain area. Here, we outline a unified approach to characterize structure by inspecting the representational geometry and the modularity properties of the recorded activity and show that a similar approach can also reveal structure in connectivity. We start by setting up a general framework for determining geometry and modularity in activity and connectivity and relating these properties with computations performed by the network. We then use this framework to review the types of structure found in recent studies of model networks performing three classes of computations.
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Affiliation(s)
- Srdjan Ostojic
- Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, Ecole Normale Superieure - PSL Research University, 75005 Paris, France.
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA; Department of Neuroscience, Columbia University, New York, NY, USA; Kavli Institute for Brain Science, Columbia University, New York, NY, USA
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3
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Gonzalez A, Giocomo LM. Parahippocampal neurons encode task-relevant information for goal-directed navigation. eLife 2024; 12:RP85646. [PMID: 38363198 PMCID: PMC10942598 DOI: 10.7554/elife.85646] [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] [Indexed: 02/17/2024] Open
Abstract
A behavioral strategy crucial to survival is directed navigation to a goal, such as a food or home location. One potential neural substrate for supporting goal-directed navigation is the parahippocampus, which contains neurons that represent an animal's position, orientation, and movement through the world, and that change their firing activity to encode behaviorally relevant variables such as reward. However, little prior work on the parahippocampus has considered how neurons encode variables during goal-directed navigation in environments that dynamically change. Here, we recorded single units from rat parahippocampal cortex while subjects performed a goal-directed task. The maze dynamically changed goal-locations via a visual cue on a trial-to-trial basis, requiring subjects to use cue-location associations to receive reward. We observed a mismatch-like signal, with elevated neural activity on incorrect trials, leading to rate-remapping. The strength of this remapping correlated with task performance. Recordings during open-field foraging allowed us to functionally define navigational coding for a subset of the neurons recorded in the maze. This approach revealed that head-direction coding units remapped more than other functional-defined units. Taken together, this work thus raises the possibility that during goal-directed navigation, parahippocampal neurons encode error information reflective of an animal's behavioral performance.
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Affiliation(s)
- Alexander Gonzalez
- Department of Neurobiology, Stanford University School of MedicineStanfordUnited States
| | - Lisa M Giocomo
- Department of Neurobiology, Stanford University School of MedicineStanfordUnited States
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4
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Vorhees CV, Williams MT. Tests for learning and memory in rodent regulatory studies. Curr Res Toxicol 2024; 6:100151. [PMID: 38304257 PMCID: PMC10832385 DOI: 10.1016/j.crtox.2024.100151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 01/11/2024] [Accepted: 01/16/2024] [Indexed: 02/03/2024] Open
Abstract
For decades, regulatory guidelines for safety assessment in rodents for drugs, chemicals, pesticides, and food additives with developmental neurotoxic potential have recommended a single test of learning and memory (L&M). In recent years some agencies have requested two such tests. Given the importance of higher cognitive function to health, and the fact that different types of L&M are mediated by different brain regions assessing higher functions represents a step forward in providing better evidence-based protection against adverse brain effects. Given the myriad of tests available for assessing L&M in rodents this leads to the question of which tests best fit regulatory guidelines. To address this question, we begin by describing the central role of two types of L&M essential to all mammalian species and the regions/networks that mediate them. We suggest that the tests recommended possess characteristics that make them well suited to the needs in regulatory safety studies. By brain region, these are (1) the hippocampus and entorhinal cortex for spatial navigation, which assesses explicit L&M for reference and episodic memory and (2) the striatum and related structures for egocentric navigation, which assesses implicit or procedural memory and path integration. Of the tests available, we suggest that in this context, the evidence supports the use of water mazes, specifically, the Morris water maze (MWM) for spatial L&M and the Cincinnati water maze (CWM) for egocentric/procedural L&M. We review the evidentiary basis for these tests, describe their use, and explain procedures that optimize their sensitivity.
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Affiliation(s)
- Charles V. Vorhees
- Corresponding author at: Div. of Neurology, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Ave., Cincinnati, OH 45229, USA.
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5
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Aoun A, Shetler O, Raghuraman R, Rodriguez GA, Hussaini SA. Beyond correlation: optimal transport metrics for characterizing representational stability and remapping in neurons encoding spatial memory. Front Cell Neurosci 2024; 17:1273283. [PMID: 38303974 PMCID: PMC10831886 DOI: 10.3389/fncel.2023.1273283] [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: 08/05/2023] [Accepted: 12/05/2023] [Indexed: 02/03/2024] Open
Abstract
Introduction Spatial representations in the entorhinal cortex (EC) and hippocampus (HPC) are fundamental to cognitive functions like navigation and memory. These representations, embodied in spatial field maps, dynamically remap in response to environmental changes. However, current methods, such as Pearson's correlation coefficient, struggle to capture the complexity of these remapping events, especially when fields do not overlap, or transformations are non-linear. This limitation hinders our understanding and quantification of remapping, a key aspect of spatial memory function. Methods We propose a family of metrics based on the Earth Mover's Distance (EMD) as a versatile framework for characterizing remapping. Results The EMD provides a granular, noise-resistant, and rate-robust description of remapping. This approach enables the identification of specific cell types and the characterization of remapping in various scenarios, including disease models. Furthermore, the EMD's properties can be manipulated to identify spatially tuned cell types and to explore remapping as it relates to alternate information forms such as spatiotemporal coding. Discussion We present a feasible, lightweight approach that complements traditional methods. Our findings underscore the potential of the EMD as a powerful tool for enhancing our understanding of remapping in the brain and its implications for spatial navigation, memory studies and beyond.
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Affiliation(s)
- Andrew Aoun
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, United States
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, United States
| | - Oliver Shetler
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, United States
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, United States
| | - Radha Raghuraman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, United States
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, United States
| | - Gustavo A. Rodriguez
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, United States
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, United States
| | - S. Abid Hussaini
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, United States
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, United States
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6
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Aoun A, Shetler O, Raghuraman R, Rodriguez GA, Hussaini SA. Beyond Correlation: Optimal Transport Metrics For Characterizing Representational Stability and Remapping in Neurons Encoding Spatial Memory. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.11.548592. [PMID: 37503011 PMCID: PMC10369988 DOI: 10.1101/2023.07.11.548592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Spatial representations in the entorhinal cortex (EC) and hippocampus (HPC) are fundamental to cognitive functions like navigation and memory. These representations, embodied in spatial field maps, dynamically remap in response to environmental changes. However, current methods, such as Pearson's correlation coefficient, struggle to capture the complexity of these remapping events, especially when fields do not overlap, or transformations are non-linear. This limitation hinders our understanding and quantification of remapping, a key aspect of spatial memory function. To address this, we propose a family of metrics based on the Earth Mover's Distance (EMD) as a versatile framework for characterizing remapping. Applied to both normalized and unnormalized distributions, the EMD provides a granular, noise-resistant, and rate-robust description of remapping. This approach enables the identification of specific cell types and the characterization of remapping in various scenarios, including disease models. Furthermore, the EMD's properties can be manipulated to identify spatially tuned cell types and to explore remapping as it relates to alternate information forms such as spatiotemporal coding. By employing approximations of the EMD, we present a feasible, lightweight approach that complements traditional methods. Our findings underscore the potential of the EMD as a powerful tool for enhancing our understanding of remapping in the brain and its implications for spatial navigation, memory studies and beyond.
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Affiliation(s)
- Andrew Aoun
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Medical Center, New York, NY 10032, USA
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032, USA
- Co-first author
| | - Oliver Shetler
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Medical Center, New York, NY 10032, USA
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032, USA
- Co-first author
| | - Radha Raghuraman
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Medical Center, New York, NY 10032, USA
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032, USA
| | - Gustavo A. Rodriguez
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Medical Center, New York, NY 10032, USA
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032, USA
| | - S. Abid Hussaini
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Medical Center, New York, NY 10032, USA
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032, USA
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7
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Low IIC, Giocomo LM, Williams AH. Remapping in a recurrent neural network model of navigation and context inference. eLife 2023; 12:RP86943. [PMID: 37410093 PMCID: PMC10328512 DOI: 10.7554/elife.86943] [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] [Indexed: 07/07/2023] Open
Abstract
Neurons in navigational brain regions provide information about position, orientation, and speed relative to environmental landmarks. These cells also change their firing patterns ('remap') in response to changing contextual factors such as environmental cues, task conditions, and behavioral states, which influence neural activity throughout the brain. How can navigational circuits preserve their local computations while responding to global context changes? To investigate this question, we trained recurrent neural network models to track position in simple environments while at the same time reporting transiently-cued context changes. We show that these combined task constraints (navigation and context inference) produce activity patterns that are qualitatively similar to population-wide remapping in the entorhinal cortex, a navigational brain region. Furthermore, the models identify a solution that generalizes to more complex navigation and inference tasks. We thus provide a simple, general, and experimentally-grounded model of remapping as one neural circuit performing both navigation and context inference.
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Affiliation(s)
- Isabel IC Low
- Zuckerman Mind Brain Behavior Institute, Columbia UniversityNew YorkUnited States
| | - Lisa M Giocomo
- Department of Neurobiology, Stanford UniversityStanfordUnited States
| | - Alex H Williams
- Center for Computational Neuroscience, Flatiron InstituteNew YorkUnited States
- Center for Neural Science, New York UniversityNew YorkUnited States
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8
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Low II, Giocomo LM, Williams AH. Remapping in a recurrent neural network model of navigation and context inference. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.25.525596. [PMID: 36747825 PMCID: PMC9900889 DOI: 10.1101/2023.01.25.525596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Neurons in navigational brain regions provide information about position, orientation, and speed relative to environmental landmarks. These cells also change their firing patterns ("remap") in response to changing contextual factors such as environmental cues, task conditions, and behavioral state, which influence neural activity throughout the brain. How can navigational circuits preserve their local computations while responding to global context changes? To investigate this question, we trained recurrent neural network models to track position in simple environments while at the same time reporting transiently-cued context changes. We show that these combined task constraints (navigation and context inference) produce activity patterns that are qualitatively similar to population-wide remapping in the entorhinal cortex, a navigational brain region. Furthermore, the models identify a solution that generalizes to more complex navigation and inference tasks. We thus provide a simple, general, and experimentally-grounded model of remapping as one neural circuit performing both navigation and context inference.
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Affiliation(s)
- Isabel I.C. Low
- Zuckerman Mind Brain Behavior Institute, Columbia University,Center for Computational Neuroscience, Flatiron Institute,Correspondence to: ,
| | | | - Alex H. Williams
- Center for Computational Neuroscience, Flatiron Institute,Center for Neural Science, New York University,Correspondence to: ,
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9
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Chen ZS, Zhang X, Long X, Zhang SJ. Are Grid-Like Representations a Component of All Perception and Cognition? Front Neural Circuits 2022; 16:924016. [PMID: 35911570 PMCID: PMC9329517 DOI: 10.3389/fncir.2022.924016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 06/14/2022] [Indexed: 11/24/2022] Open
Abstract
Grid cells or grid-like responses have been reported in the rodent, bat and human brains during various spatial and non-spatial tasks. However, the functions of grid-like representations beyond the classical hippocampal formation remain elusive. Based on accumulating evidence from recent rodent recordings and human fMRI data, we make speculative accounts regarding the mechanisms and functional significance of the sensory cortical grid cells and further make theory-driven predictions. We argue and reason the rationale why grid responses may be universal in the brain for a wide range of perceptual and cognitive tasks that involve locomotion and mental navigation. Computational modeling may provide an alternative and complementary means to investigate the grid code or grid-like map. We hope that the new discussion will lead to experimentally testable hypotheses and drive future experimental data collection.
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Affiliation(s)
- Zhe Sage Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, Neuroscience Institute, New York University School of Medicine, New York, NY, United States
- *Correspondence: Zhe Sage Chen
| | - Xiaohan Zhang
- Department of Psychiatry, Department of Neuroscience and Physiology, Neuroscience Institute, New York University School of Medicine, New York, NY, United States
| | - Xiaoyang Long
- Department of Neurosurgery, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Sheng-Jia Zhang
- Department of Neurosurgery, Xinqiao Hospital, Army Medical University, Chongqing, China
- Sheng-Jia Zhang
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10
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Roux K, van den Heever D. Orientation Invariant Sensorimotor Object Recognition Using Cortical Grid Cells. Front Neural Circuits 2022; 15:738137. [PMID: 35153678 PMCID: PMC8825787 DOI: 10.3389/fncir.2021.738137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 12/31/2021] [Indexed: 12/01/2022] Open
Abstract
Grid cells enable efficient modeling of locations and movement through path integration. Recent work suggests that the brain might use similar mechanisms to learn the structure of objects and environments through sensorimotor processing. This work is extended in our network to support sensor orientations relative to learned allocentric object representations. The proposed mechanism enables object representations to be learned through sensorimotor sequences, and inference of these learned object representations from novel sensorimotor sequences produced by rotated objects through path integration. The model proposes that orientation-selective cells are present in each column in the neocortex, and provides a biologically plausible implementation that echoes experimental measurements and fits in with theoretical predictions of previous studies.
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Affiliation(s)
- Kalvyn Roux
- BERG, Department of Mechanical and Mechatronic Engineering, Stellenbosch University, Stellenbosch, South Africa
- *Correspondence: Kalvyn Roux
| | - David van den Heever
- BERG, Department of Mechanical and Mechatronic Engineering, Stellenbosch University, Stellenbosch, South Africa
- Department of Agricultural and Biological Engineering, Mississippi State University, Starkville, MS, United States
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11
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Benna MK, Fusi S. Place cells may simply be memory cells: Memory compression leads to spatial tuning and history dependence. Proc Natl Acad Sci U S A 2021; 118:e2018422118. [PMID: 34916282 PMCID: PMC8713479 DOI: 10.1073/pnas.2018422118] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/02/2021] [Indexed: 11/18/2022] Open
Abstract
The observation of place cells has suggested that the hippocampus plays a special role in encoding spatial information. However, place cell responses are modulated by several nonspatial variables and reported to be rather unstable. Here, we propose a memory model of the hippocampus that provides an interpretation of place cells consistent with these observations. We hypothesize that the hippocampus is a memory device that takes advantage of the correlations between sensory experiences to generate compressed representations of the episodes that are stored in memory. A simple neural network model that can efficiently compress information naturally produces place cells that are similar to those observed in experiments. It predicts that the activity of these cells is variable and that the fluctuations of the place fields encode information about the recent history of sensory experiences. Place cells may simply be a consequence of a memory compression process implemented in the hippocampus.
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Affiliation(s)
- Marcus K Benna
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027;
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027
- Neurobiology Section, Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027;
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027
- Kavli Institute for Brain Sciences, Columbia University, New York, NY 10027
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12
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Tukker JJ, Beed P, Brecht M, Kempter R, Moser EI, Schmitz D. Microcircuits for spatial coding in the medial entorhinal cortex. Physiol Rev 2021; 102:653-688. [PMID: 34254836 PMCID: PMC8759973 DOI: 10.1152/physrev.00042.2020] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
The hippocampal formation is critically involved in learning and memory and contains a large proportion of neurons encoding aspects of the organism’s spatial surroundings. In the medial entorhinal cortex (MEC), this includes grid cells with their distinctive hexagonal firing fields as well as a host of other functionally defined cell types including head direction cells, speed cells, border cells, and object-vector cells. Such spatial coding emerges from the processing of external inputs by local microcircuits. However, it remains unclear exactly how local microcircuits and their dynamics within the MEC contribute to spatial discharge patterns. In this review we focus on recent investigations of intrinsic MEC connectivity, which have started to describe and quantify both excitatory and inhibitory wiring in the superficial layers of the MEC. Although the picture is far from complete, it appears that these layers contain robust recurrent connectivity that could sustain the attractor dynamics posited to underlie grid pattern formation. These findings pave the way to a deeper understanding of the mechanisms underlying spatial navigation and memory.
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Affiliation(s)
- John J Tukker
- Network Dysfunction, German Center for Neurodegenerative Diseases, Berlin, Germany
| | - Prateep Beed
- NeuroScientific Research Center, Charite Berlin, Germany
| | - Michael Brecht
- Systems Neuroscience, Humboldt University of Berlin, Berlin, Germany
| | - Richard Kempter
- Department of Biology, Institute for Theoretical Biology, Humbolt-Universität zu Berlin, Berlin, Germany
| | - Edvard I Moser
- Kavli Institute for Systems Neuroscience and Centre for the Biology of Memory, Norwegian University of Science and Technology
| | - Dietmar Schmitz
- Neuroscience Research Center, Charité Universitätsmedizin Berlin, Berlin, Germany
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13
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Delaux A, de Saint Aubert JB, Ramanoël S, Bécu M, Gehrke L, Klug M, Chavarriaga R, Sahel JA, Gramann K, Arleo A. Mobile brain/body imaging of landmark-based navigation with high-density EEG. Eur J Neurosci 2021; 54:8256-8282. [PMID: 33738880 PMCID: PMC9291975 DOI: 10.1111/ejn.15190] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 03/05/2021] [Accepted: 03/14/2021] [Indexed: 01/07/2023]
Abstract
Coupling behavioral measures and brain imaging in naturalistic, ecological conditions is key to comprehend the neural bases of spatial navigation. This highly integrative function encompasses sensorimotor, cognitive, and executive processes that jointly mediate active exploration and spatial learning. However, most neuroimaging approaches in humans are based on static, motion‐constrained paradigms and they do not account for all these processes, in particular multisensory integration. Following the Mobile Brain/Body Imaging approach, we aimed to explore the cortical correlates of landmark‐based navigation in actively behaving young adults, solving a Y‐maze task in immersive virtual reality. EEG analysis identified a set of brain areas matching state‐of‐the‐art brain imaging literature of landmark‐based navigation. Spatial behavior in mobile conditions additionally involved sensorimotor areas related to motor execution and proprioception usually overlooked in static fMRI paradigms. Expectedly, we located a cortical source in or near the posterior cingulate, in line with the engagement of the retrosplenial complex in spatial reorientation. Consistent with its role in visuo‐spatial processing and coding, we observed an alpha‐power desynchronization while participants gathered visual information. We also hypothesized behavior‐dependent modulations of the cortical signal during navigation. Despite finding few differences between the encoding and retrieval phases of the task, we identified transient time–frequency patterns attributed, for instance, to attentional demand, as reflected in the alpha/gamma range, or memory workload in the delta/theta range. We confirmed that combining mobile high‐density EEG and biometric measures can help unravel the brain structures and the neural modulations subtending ecological landmark‐based navigation.
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Affiliation(s)
- Alexandre Delaux
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | | | - Stephen Ramanoël
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Marcia Bécu
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Lukas Gehrke
- Institute of Psychology and Ergonomics, Technische Universität Berlin, Berlin, Germany
| | - Marius Klug
- Institute of Psychology and Ergonomics, Technische Universität Berlin, Berlin, Germany
| | - Ricardo Chavarriaga
- Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland.,Zurich University of Applied Sciences, ZHAW Datalab, Winterthur, Switzerland
| | - José-Alain Sahel
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France.,CHNO des Quinze-Vingts, INSERM-DGOS CIC 1423, Paris, France.,Fondation Ophtalmologique Rothschild, Paris, France.,Department of Ophthalmology, The University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Klaus Gramann
- Institute of Psychology and Ergonomics, Technische Universität Berlin, Berlin, Germany
| | - Angelo Arleo
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
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14
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Bant JS, Hardcastle K, Ocko SA, Giocomo LM. Topography in the Bursting Dynamics of Entorhinal Neurons. Cell Rep 2021; 30:2349-2359.e7. [PMID: 32075768 DOI: 10.1016/j.celrep.2020.01.057] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 11/28/2019] [Accepted: 01/17/2020] [Indexed: 12/18/2022] Open
Abstract
Medial entorhinal cortex contains neural substrates for representing space. These substrates include grid cells that fire in repeating locations and increase in scale progressively along the dorsal-to-ventral entorhinal axis, with the physical distance between grid firing nodes increasing from tens of centimeters to several meters in rodents. Whether the temporal scale of grid cell spiking dynamics shows a similar dorsal-to-ventral organization remains unknown. Here, we report the presence of a dorsal-to-ventral gradient in the temporal spiking dynamics of grid cells in behaving mice. This gradient in bursting supports the emergence of a dorsal grid cell population with a high signal-to-noise ratio. In vitro recordings combined with a computational model point to a role for gradients in non-inactivating sodium conductances in supporting the bursting gradient in vivo. Taken together, these results reveal a complementary organization in the temporal and intrinsic properties of entorhinal cells.
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Affiliation(s)
- Jason S Bant
- Department of Neurobiology, Stanford University School of Medicine, Stanford CA 94305, USA
| | - Kiah Hardcastle
- Department of Neurobiology, Stanford University School of Medicine, Stanford CA 94305, USA
| | - Samuel A Ocko
- Department of Applied Physics, Stanford University, Stanford CA 94305, USA
| | - Lisa M Giocomo
- Department of Neurobiology, Stanford University School of Medicine, Stanford CA 94305, USA.
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15
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Xu S, Yang H, Menon V, Lemire AL, Wang L, Henry FE, Turaga SC, Sternson SM. Behavioral state coding by molecularly defined paraventricular
hypothalamic cell type ensembles. Science 2020; 370:370/6514/eabb2494. [DOI: 10.1126/science.abb2494] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Accepted: 08/18/2020] [Indexed: 12/11/2022]
Abstract
Brains encode behaviors using neurons amenable to systematic
classification by gene expression. The contribution of molecular identity to
neural coding is not understood because of the challenges involved with
measuring neural dynamics and molecular information from the same cells. We
developed CaRMA (calcium and RNA multiplexed activity) imaging based on
recording in vivo single-neuron calcium dynamics followed by gene expression
analysis. We simultaneously monitored activity in hundreds of neurons in
mouse paraventricular hypothalamus (PVH). Combinations of cell-type marker
genes had predictive power for neuronal responses across 11 behavioral
states. The PVH uses combinatorial assemblies of molecularly defined neuron
populations for grouped-ensemble coding of survival behaviors. The
neuropeptide receptor neuropeptide Y receptor type 1 (Npy1r) amalgamated
multiple cell types with similar responses. Our results show that
molecularly defined neurons are important processing units for brain
function.
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Affiliation(s)
- Shengjin Xu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Hui Yang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Vilas Menon
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Andrew L. Lemire
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Lihua Wang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Fredrick E. Henry
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Srinivas C. Turaga
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Scott M. Sternson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
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16
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Munn RGK, Giocomo LM. Multiple head direction signals within entorhinal cortex: origin and function. Curr Opin Neurobiol 2020; 64:32-40. [DOI: 10.1016/j.conb.2020.01.015] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 01/23/2020] [Accepted: 01/26/2020] [Indexed: 12/24/2022]
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17
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Gerlei K, Passlack J, Hawes I, Vandrey B, Stevens H, Papastathopoulos I, Nolan MF. Grid cells are modulated by local head direction. Nat Commun 2020; 11:4228. [PMID: 32839445 PMCID: PMC7445272 DOI: 10.1038/s41467-020-17500-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 07/02/2020] [Indexed: 01/11/2023] Open
Abstract
Grid and head direction codes represent cognitive spaces for navigation and memory. Pure grid cells generate grid codes that have been assumed to be independent of head direction, whereas conjunctive cells generate grid representations that are tuned to a single head direction. Here, we demonstrate that pure grid cells also encode head direction, but through distinct mechanisms. We show that individual firing fields of pure grid cells are tuned to multiple head directions, with the preferred sets of directions differing between fields. This local directional modulation is not predicted by previous continuous attractor or oscillatory interference models of grid firing but is accounted for by models in which pure grid cells integrate inputs from co-aligned conjunctive cells with firing rates that differ between their fields. We suggest that local directional signals from grid cells may contribute to downstream computations by decorrelating different points of view from the same location.
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Affiliation(s)
- Klara Gerlei
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD, UK
| | - Jessica Passlack
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD, UK
| | - Ian Hawes
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD, UK
| | - Brianna Vandrey
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD, UK
| | - Holly Stevens
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD, UK
| | - Ioannis Papastathopoulos
- School of Mathematics, Maxwell Institute and Centre for Statistics, University of Edinburgh, Edinburgh, EH9 3FD, UK
- The Alan Turing Institute, 96 Euston Road, London, NW1 2DB, UK
| | - Matthew F Nolan
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD, UK.
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9XD, UK.
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18
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Harvey RE, Berkowitz LE, Hamilton DA, Clark BJ. The effects of developmental alcohol exposure on the neurobiology of spatial processing. Neurosci Biobehav Rev 2019; 107:775-794. [PMID: 31526818 PMCID: PMC6876993 DOI: 10.1016/j.neubiorev.2019.09.018] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 08/02/2019] [Accepted: 09/11/2019] [Indexed: 01/20/2023]
Abstract
The consumption of alcohol during gestation is detrimental to the developing central nervous system. One functional outcome of this exposure is impaired spatial processing, defined as sensing and integrating information pertaining to spatial navigation and spatial memory. The hippocampus, entorhinal cortex, and anterior thalamus are brain regions implicated in spatial processing and are highly susceptible to the effects of developmental alcohol exposure. Some of the observed effects of alcohol on spatial processing may be attributed to changes at the synaptic to circuit level. In this review, we first describe the impact of developmental alcohol exposure on spatial behavior followed by a summary of the development of brain areas involved in spatial processing. We then provide an examination of the consequences of prenatal and early postnatal alcohol exposure in rodents on hippocampal, anterior thalamus, and entorhinal cortex-dependent spatial processing from the cellular to behavioral level. We conclude by highlighting several unanswered questions which may provide a framework for future investigation.
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Affiliation(s)
- Ryan E Harvey
- Department of Psychology, University of New Mexico, Albuquerque, NM, United States
| | - Laura E Berkowitz
- Department of Psychology, University of New Mexico, Albuquerque, NM, United States
| | - Derek A Hamilton
- Department of Psychology, University of New Mexico, Albuquerque, NM, United States
| | - Benjamin J Clark
- Department of Psychology, University of New Mexico, Albuquerque, NM, United States.
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19
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Hardcastle K, Giocomo LM. The Shifting Sands of Cortical Divisions. Neuron 2019; 102:8-11. [PMID: 30946829 DOI: 10.1016/j.neuron.2019.03.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
In this issue of Neuron, a new study by Minderer et al. (2019) examines the activity of thousands of cortical neurons during a navigation task and reveals that features of the task encoded by neurons vary smoothly across cortex rather than falling into functionally discrete cortical regions.
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Affiliation(s)
- Kiah Hardcastle
- Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Lisa M Giocomo
- Stanford University School of Medicine, Stanford, CA 94305, USA.
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20
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Hippocampal Global Remapping Can Occur without Input from the Medial Entorhinal Cortex. Cell Rep 2019; 22:3152-3159. [PMID: 29562172 PMCID: PMC5929481 DOI: 10.1016/j.celrep.2018.02.082] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Revised: 12/26/2017] [Accepted: 02/21/2018] [Indexed: 12/11/2022] Open
Abstract
The high storage capacity of the episodic memory system relies on distinct representations for events that are separated in time and space. The spatial component of these computations includes the formation of independent maps by hippocampal place cells across environments, referred to as global re-mapping. Such remapping is thought to emerge by the switching of input patterns from specialized spatially selective cells in medial entorhinal cortex (mEC), such as grid and border cells. Although it has been shown that acute manipulations of mEC firing patterns are sufficient for inducing hippocampal remapping, it remains unknown whether specialized spatial mEC inputs are necessary for the reorganization of hippocampal spatial representations. Here, we examined remapping in rats without mEC input to the hippocampus and found that highly distinct spatial maps emerged rapidly in every individual rat. Our data suggest that hippocampal spatial computations do not depend on inputs from specialized cell types in mEC.
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21
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Abstract
Most biological and artificial neural systems are capable of completing multiple tasks. However, the neural mechanism by which multiple tasks are accomplished within the same system is largely unclear. We start by discussing how different tasks can be related, and methods to generate large sets of inter-related tasks to study how neural networks and animals perform multiple tasks. We then argue that there are mechanisms that emphasize either specialization or flexibility. We will review two such neural mechanisms underlying multiple tasks at the neuronal level (modularity and mixed selectivity), and discuss how different mechanisms can emerge depending on training methods in neural networks.
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22
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Huang ZJ, Paul A. The diversity of GABAergic neurons and neural communication elements. Nat Rev Neurosci 2019; 20:563-572. [PMID: 31222186 PMCID: PMC8796706 DOI: 10.1038/s41583-019-0195-4] [Citation(s) in RCA: 119] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/20/2019] [Indexed: 12/18/2022]
Abstract
The phenotypic diversity of cortical GABAergic neurons is probably necessary for their functional versatility in shaping the spatiotemporal dynamics of neural circuit operations underlying cognition. Deciphering the logic of this diversity requires comprehensive analysis of multi-modal cell features and a framework of neuronal identity that reflects biological mechanisms and principles. Recent high-throughput single-cell analyses have generated unprecedented data sets characterizing the transcriptomes, morphology and electrophysiology of interneurons. We posit that cardinal interneuron types can be defined by their synaptic communication properties, which are encoded in key transcriptional signatures. This conceptual framework integrates multi-modal cell features, captures neuronal input-output properties fundamental to circuit operation and may advance understanding of the appropriate granularity of neuron types, towards a biologically grounded and operationally useful interneuron taxonomy.
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Affiliation(s)
- Z Josh Huang
- Cold Spring Harbor Laboratory, New York, NY, USA.
| | - Anirban Paul
- Cold Spring Harbor Laboratory, New York, NY, USA
- Department of Neural & Behavioral Sciences, Penn State University College of Medicine, Hershey, PA, USA
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23
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Trautmann EM, Stavisky SD, Lahiri S, Ames KC, Kaufman MT, O'Shea DJ, Vyas S, Sun X, Ryu SI, Ganguli S, Shenoy KV. Accurate Estimation of Neural Population Dynamics without Spike Sorting. Neuron 2019; 103:292-308.e4. [PMID: 31171448 DOI: 10.1016/j.neuron.2019.05.003] [Citation(s) in RCA: 121] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 02/06/2019] [Accepted: 04/30/2019] [Indexed: 11/25/2022]
Abstract
A central goal of systems neuroscience is to relate an organism's neural activity to behavior. Neural population analyses often reduce the data dimensionality to focus on relevant activity patterns. A major hurdle to data analysis is spike sorting, and this problem is growing as the number of recorded neurons increases. Here, we investigate whether spike sorting is necessary to estimate neural population dynamics. The theory of random projections suggests that we can accurately estimate the geometry of low-dimensional manifolds from a small number of linear projections of the data. We recorded data using Neuropixels probes in motor cortex of nonhuman primates and reanalyzed data from three previous studies and found that neural dynamics and scientific conclusions are quite similar using multiunit threshold crossings rather than sorted neurons. This finding unlocks existing data for new analyses and informs the design and use of new electrode arrays for laboratory and clinical use.
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Affiliation(s)
- Eric M Trautmann
- Neurosciences Program, Stanford University, Stanford, CA, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
| | - Sergey D Stavisky
- Neurosciences Program, Stanford University, Stanford, CA, USA; Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Subhaneil Lahiri
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Katherine C Ames
- Neurosciences Program, Stanford University, Stanford, CA, USA; Department of Neuroscience, Columbia University, New York, NY, USA
| | - Matthew T Kaufman
- Neurosciences Program, Stanford University, Stanford, CA, USA; Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Daniel J O'Shea
- Neurosciences Program, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Saurabh Vyas
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Xulu Sun
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Stephen I Ryu
- Palo Alto Medical Foundation, Palo Alto, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Surya Ganguli
- Department of Applied Physics, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA; Department of Neurobiology, Stanford University, Stanford, CA, USA; Stanford Neurosciences Institute, Stanford, CA, USA; Bio-X Program, Stanford University, Stanford, CA, USA
| | - Krishna V Shenoy
- Neurosciences Program, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA; Department of Neurobiology, Stanford University, Stanford, CA, USA; Stanford Neurosciences Institute, Stanford, CA, USA; Bio-X Program, Stanford University, Stanford, CA, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
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24
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Abstract
Neural recording electrode technologies have contributed considerably to neuroscience by enabling the extracellular detection of low-frequency local field potential oscillations and high-frequency action potentials of single units. Nevertheless, several long-standing limitations exist, including low multiplexity, deleterious chronic immune responses and long-term recording instability. Driven by initiatives encouraging the generation of novel neurotechnologies and the maturation of technologies to fabricate high-density electronics, novel electrode technologies are emerging. Here, we provide an overview of recently developed neural recording electrode technologies with high spatial integration, long-term stability and multiple functionalities. We describe how these emergent neurotechnologies can approach the ultimate goal of illuminating chronic brain activity with minimal disruption of the neural environment, thereby providing unprecedented opportunities for neuroscience research in the future.
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Affiliation(s)
- Guosong Hong
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Charles M Lieber
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Center for Brain Science, Harvard University, Cambridge, MA, USA.
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
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25
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Hawkins J, Lewis M, Klukas M, Purdy S, Ahmad S. A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex. Front Neural Circuits 2019; 12:121. [PMID: 30687022 PMCID: PMC6336927 DOI: 10.3389/fncir.2018.00121] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2018] [Accepted: 12/24/2018] [Indexed: 11/17/2022] Open
Abstract
How the neocortex works is a mystery. In this paper we propose a novel framework for understanding its function. Grid cells are neurons in the entorhinal cortex that represent the location of an animal in its environment. Recent evidence suggests that grid cell-like neurons may also be present in the neocortex. We propose that grid cells exist throughout the neocortex, in every region and in every cortical column. They define a location-based framework for how the neocortex functions. Whereas grid cells in the entorhinal cortex represent the location of one thing, the body relative to its environment, we propose that cortical grid cells simultaneously represent the location of many things. Cortical columns in somatosensory cortex track the location of tactile features relative to the object being touched and cortical columns in visual cortex track the location of visual features relative to the object being viewed. We propose that mechanisms in the entorhinal cortex and hippocampus that evolved for learning the structure of environments are now used by the neocortex to learn the structure of objects. Having a representation of location in each cortical column suggests mechanisms for how the neocortex represents object compositionality and object behaviors. It leads to the hypothesis that every part of the neocortex learns complete models of objects and that there are many models of each object distributed throughout the neocortex. The similarity of circuitry observed in all cortical regions is strong evidence that even high-level cognitive tasks are learned and represented in a location-based framework.
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26
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Diehl GW, Hon OJ, Leutgeb S, Leutgeb JK. Stability of medial entorhinal cortex representations over time. Hippocampus 2018; 29:284-302. [PMID: 30175425 DOI: 10.1002/hipo.23017] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 07/02/2018] [Accepted: 07/19/2018] [Indexed: 02/02/2023]
Abstract
Distinct functional cell types in the medial entorhinal cortex (mEC) have been shown to represent different aspects of experiences. To further characterize mEC cell populations, we examined whether spatial representations of neurons in mEC superficial layers depended on the scale of the environment and changed over extended time periods. Accordingly, mEC cells were recorded while rats repeatedly foraged in a small or a large environment in sessions that were separated by time intervals from minutes to hours. Comparing between large and small environments, we found that the overall precision of grid and non-grid cell spatial maps was higher in smaller environments. When examining the stability of spatial firing patterns over time, differences and similarities were observed across cell types. Within-session stability was higher for grid cells than for non-grid cell populations. Despite differences in baseline stability between cell types, stability levels remained consistent over time between sessions, up to 1 hr. Even for sessions separated by 6 hrs, activity patterns of grid cells and of most non-grid cells lacked any systematic decrease in spatial similarity over time. However, a subset of ~15% of mEC non-grid cells recorded preferentially from layer III exhibited dramatic, time dependent changes in firing patterns across 6 hrs, reminiscent of previous characterizations of the hippocampal CA2 subregion. Collectively, our data suggest that mEC grid cell input to hippocampus in conjunction with many time invariant non-grid cells may aid in stabilizing hippocampal spatial maps, while a subset of time varying non-grid cells could provide complementary temporal information.
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Affiliation(s)
- Geoffrey W Diehl
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, La Jolla, California
| | - Olivia J Hon
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, La Jolla, California
| | - Stefan Leutgeb
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, La Jolla, California.,Kavli Institute for Brain and Mind, University of California, La Jolla, California
| | - Jill K Leutgeb
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, La Jolla, California
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27
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Souza BC, Pavão R, Belchior H, Tort ABL. On Information Metrics for Spatial Coding. Neuroscience 2018; 375:62-73. [PMID: 29432886 DOI: 10.1016/j.neuroscience.2018.01.066] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Revised: 01/28/2018] [Accepted: 01/31/2018] [Indexed: 01/03/2023]
Abstract
The hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon's mutual information (Shannon, 1948), and convey information rate in bits/s or bits/spike (Skaggs et al., 1993, 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice.
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Affiliation(s)
- Bryan C Souza
- Brain Institute, Federal University of Rio Grande do Norte, RN, Brazil.
| | - Rodrigo Pavão
- Brain Institute, Federal University of Rio Grande do Norte, RN, Brazil
| | - Hindiael Belchior
- Faculty of Health Sciences of Trairi, Federal University of Rio Grande do Norte, RN, Brazil
| | - Adriano B L Tort
- Brain Institute, Federal University of Rio Grande do Norte, RN, Brazil
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28
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Lisman J, Buzsáki G, Eichenbaum H, Nadel L, Ranganath C, Redish AD. Viewpoints: how the hippocampus contributes to memory, navigation and cognition. Nat Neurosci 2017; 20:1434-1447. [PMID: 29073641 PMCID: PMC5943637 DOI: 10.1038/nn.4661] [Citation(s) in RCA: 387] [Impact Index Per Article: 55.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The hippocampus serves a critical function in memory, navigation, and cognition. Nature Neuroscience asked John Lisman to lead a group of researchers in a dialog on shared and distinct viewpoints on the hippocampus. There has been a long history of studying the hippocampus, but recent work has made it possible to study the cellular and network basis of defined operations—operations that include cognitive processes that have been otherwise difficult to study (see Box 1 for useful terminology). These operations deal with the context-dependent representation of complex memories, the role of mental exploration based on imagined rather than real movements, and the use of recalled information for navigation and decision-making. The progress that has been made in understanding the hippocampus has motivated the study of other brain regions that provide hippocampal input or receive hippocampal output; the hippocampus is thus serving as a nucleating point for the larger goal of understanding the neural codes that allow inter-regional communication and more generally, understanding how memory-guided behavior is achieved by large scale integration of brain regions. In generating a discussion among experts in the study of the cognitive processes of the hippocampus, the editors and I have posed questions that probe important principles of hippocampal function. We hope that the resulting discussion will make clear to readers the progress that has been made, while also identifying issues where consensus has not yet been achieved and that should be pursued in future research. – John Lisman
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Affiliation(s)
- John Lisman
- Department of Biology at Brandeis University, Waltham, Massachusetts, USA
| | - György Buzsáki
- NYU Neuroscience Institute at New York University, New York, New York, USA
| | - Howard Eichenbaum
- Center for Memory and Brain at Boston University, Boston, Massachusetts, USA
| | - Lynn Nadel
- Department of Psychology and Cognitive Science Program at University of Arizona, Tucson, Arizona, USA
| | - Charan Ranganath
- Center for Neuroscience and Department of Psychology at the University of California, Davis, California, USA
| | - A David Redish
- Department of Neuroscience at the University of Minnesota, Minneapolis, Minnesota, USA
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