1
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Savelli F. Spontaneous Dynamics of Hippocampal Place Fields in a Model of Combinatorial Competition among Stable Inputs. J Neurosci 2024; 44:e1663232024. [PMID: 38316560 PMCID: PMC10977031 DOI: 10.1523/jneurosci.1663-23.2024] [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: 09/03/2023] [Revised: 01/16/2024] [Accepted: 01/21/2024] [Indexed: 02/07/2024] Open
Abstract
We present computer simulations illustrating how the plastic integration of spatially stable inputs could contribute to the dynamic character of hippocampal spatial representations. In novel environments of slightly larger size than typical apparatus, the emergence of well-defined place fields in real place cells seems to rely on inputs from normally functioning grid cells. Theoretically, the grid-to-place transformation is possible if a place cell is able to respond selectively to a combination of suitably aligned grids. We previously identified the functional characteristics that allow a synaptic plasticity rule to accomplish this selection by synaptic competition during rat foraging behavior. Here, we show that the synaptic competition can outlast the formation of place fields, contributing to their spatial reorganization over time, when the model is run in larger environments and the topographical/modular organization of grid inputs is taken into account. Co-simulated cells that differ only by their randomly assigned grid inputs display different degrees and kinds of spatial reorganization-ranging from place-field remapping to more subtle in-field changes or lapses in firing. The model predicts a greater number of place fields and propensity for remapping in place cells recorded from more septal regions of the hippocampus and/or in larger environments, motivating future experimental standardization across studies and animal models. In sum, spontaneous remapping could arise from rapid synaptic learning involving inputs that are functionally homogeneous, spatially stable, and minimally stochastic.
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Affiliation(s)
- Francesco Savelli
- Department of Neuroscience, Developmental and Regenerative Biology, The University of Texas at San Antonio, San Antonio, Texas 78249
- Neurosciences Institute, The University of Texas at San Antonio, San Antonio, Texas 78249
- Brain Health Consortium, The University of Texas at San Antonio, San Antonio, Texas 78249
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2
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Malone TJ, Tien NW, Ma Y, Cui L, Lyu S, Wang G, Nguyen D, Zhang K, Myroshnychenko MV, Tyan J, Gordon JA, Kupferschmidt DA, Gu Y. A consistent map in the medial entorhinal cortex supports spatial memory. Nat Commun 2024; 15:1457. [PMID: 38368457 PMCID: PMC10874432 DOI: 10.1038/s41467-024-45853-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 02/05/2024] [Indexed: 02/19/2024] Open
Abstract
The medial entorhinal cortex (MEC) is hypothesized to function as a cognitive map for memory-guided navigation. How this map develops during learning and influences memory remains unclear. By imaging MEC calcium dynamics while mice successfully learned a novel virtual environment over ten days, we discovered that the dynamics gradually became more spatially consistent and then stabilized. Additionally, grid cells in the MEC not only exhibited improved spatial tuning consistency, but also maintained stable phase relationships, suggesting a network mechanism involving synaptic plasticity and rigid recurrent connectivity to shape grid cell activity during learning. Increased c-Fos expression in the MEC in novel environments further supports the induction of synaptic plasticity. Unsuccessful learning lacked these activity features, indicating that a consistent map is specific for effective spatial memory. Finally, optogenetically disrupting spatial consistency of the map impaired memory-guided navigation in a well-learned environment. Thus, we demonstrate that the establishment of a spatially consistent MEC map across learning both correlates with, and is necessary for, successful spatial memory.
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Affiliation(s)
- Taylor J Malone
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Nai-Wen Tien
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
- Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Yan Ma
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Lian Cui
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Shangru Lyu
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Garret Wang
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Duc Nguyen
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
- Center of Neural Science, New York University, New York, NY, USA
| | - Kai Zhang
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
- Department of Anesthesiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Maxym V Myroshnychenko
- Integrative Neuroscience Section, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Jean Tyan
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Joshua A Gordon
- Integrative Neuroscience Section, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
- Office of the Director, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
| | - David A Kupferschmidt
- Integrative Neuroscience Section, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Yi Gu
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA.
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3
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Malone TJ, Tien NW, Ma Y, Cui L, Lyu S, Wang G, Nguyen D, Zhang K, Myroshnychenko MV, Tyan J, Gordon JA, Kupferschmidt DA, Gu Y. A consistent map in the medial entorhinal cortex supports spatial memory. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.30.560254. [PMID: 37986767 PMCID: PMC10659391 DOI: 10.1101/2023.09.30.560254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The medial entorhinal cortex (MEC) is hypothesized to function as a cognitive map for memory-guided navigation. How this map develops during learning and influences memory remains unclear. By imaging MEC calcium dynamics while mice successfully learned a novel virtual environment over ten days, we discovered that the dynamics gradually became more spatially consistent and then stabilized. Additionally, grid cells in the MEC not only exhibited improved spatial tuning consistency, but also maintained stable phase relationships, suggesting a network mechanism involving synaptic plasticity and rigid recurrent connectivity to shape grid cell activity during learning. Increased c-Fos expression in the MEC in novel environments further supports the induction of synaptic plasticity. Unsuccessful learning lacked these activity features, indicating that a consistent map is specific for effective spatial memory. Finally, optogenetically disrupting spatial consistency of the map impaired memory-guided navigation in a well-learned environment. Thus, we demonstrate that the establishment of a spatially consistent MEC map across learning both correlates with, and is necessary for, successful spatial memory.
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Affiliation(s)
- Taylor J. Malone
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- These authors contributed equally to this work
| | - Nai-Wen Tien
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- Current address: Washington University School of Medicine in St. Louis, St. Louis, MO, USA
- These authors contributed equally to this work
| | - Yan Ma
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- These authors contributed equally to this work
| | - Lian Cui
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Shangru Lyu
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Garret Wang
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Duc Nguyen
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- Current address: Center of Neural Science, New York University, New York, NY, USA
| | - Kai Zhang
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- Department of Anesthesiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Maxym V. Myroshnychenko
- Integrative Neuroscience Section, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jean Tyan
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Joshua A. Gordon
- Integrative Neuroscience Section, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
- Office of the Director, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - David A. Kupferschmidt
- Integrative Neuroscience Section, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Yi Gu
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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4
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Savelli F. Spontaneous dynamics of hippocampal place fields in a model of combinatorial competition among stable inputs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.04.556254. [PMID: 37732194 PMCID: PMC10508775 DOI: 10.1101/2023.09.04.556254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
We present computer simulations illustrating how the plastic integration of spatially stable inputs could contribute to the dynamic character of hippocampal spatial representations. In novel environments of slightly larger size than typical apparatus, the emergence of well-defined place fields in real place cells seems to rely on inputs from normally functioning grid cells. Theoretically, the grid-to-place transformation is possible if a place cell is able to respond selectively to a combination of suitably aligned grids. We previously identified the functional characteristics that allow a synaptic plasticity rule to accomplish this selection by synaptic competition during rat foraging behavior. Here, we show that the synaptic competition can outlast the formation of place fields, contributing to their spatial reorganization over time, when the model is run in larger environments and the topographical/modular organization of grid inputs is taken into account. Co-simulated cells that differ only by their randomly assigned grid inputs display different degrees and kinds of spatial reorganization-ranging from place-field remapping to more subtle in-field changes or lapses in firing. The model predicts a greater number of place fields and propensity for remapping in place cells recorded from more septal regions of the hippocampus and/or in larger environments, motivating future experimental standardization across studies and animal models. In sum, spontaneous remapping could arise from rapid synaptic learning involving inputs that are functionally homogeneous, spatially stable, and minimally stochastic. Significance Statement In both AI and theoretical neuroscience, learning systems often rely on the asymptotic convergence of slow-acting learning rules applied to input spaces that are presumed to be sampled repeatedly, for example over developmental timescales. Place cells of the hippocampus testify to a neural system capable of rapidly encoding cognitive variables-such as the animal's position in space-from limited experience. These internal representations undergo "spontaneous" changes over time, spurring much interest in their cognitive significance and underlying mechanisms. We investigate a model suggesting that some of these changes could be a tradeoff of rapid learning.
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5
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Moore JJ, Rashid SK, Johnson CD, Codrington N, Chklovskii DB, Basu J. Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3. RESEARCH SQUARE 2023:rs.3.rs-2733660. [PMID: 37131789 PMCID: PMC10153397 DOI: 10.21203/rs.3.rs-2733660/v1] [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
Anatomically segregated apical and basal dendrites of pyramidal neurons receive functionally distinct inputs, but it is unknown if this results in compartment-level functional diversity during behavior. Here we imaged calcium signals from apical dendrites, soma, and basal dendrites of pyramidal neurons in area CA3 of mouse hippocampus during head-fixed navigation. To examine dendritic population activity, we developed computational tools to identify dendritic regions of interest and extract accurate fluorescence traces. We identified robust spatial tuning in apical and basal dendrites, similar to soma, though basal dendrites had reduced activity rates and place field widths. Across days, apical dendrites were more stable than soma or basal dendrites, resulting in better decoding of the animal's position. These population-level dendritic differences may reflect functionally distinct input streams leading to different dendritic computations in CA3. These tools will facilitate future studies of signal transformations between cellular compartments and their relation to behavior.
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Affiliation(s)
- Jason J Moore
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Center for Computational Neuroscience, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
| | - Shannon K Rashid
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Cara D. Johnson
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Naomi Codrington
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Dmitri B Chklovskii
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Center for Computational Neuroscience, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
| | - Jayeeta Basu
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Neural Science, New York University, New York, NY 10003, USA
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Tsao A, Yousefzadeh SA, Meck WH, Moser MB, Moser EI. The neural bases for timing of durations. Nat Rev Neurosci 2022; 23:646-665. [PMID: 36097049 DOI: 10.1038/s41583-022-00623-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2022] [Indexed: 11/10/2022]
Abstract
Durations are defined by a beginning and an end, and a major distinction is drawn between durations that start in the present and end in the future ('prospective timing') and durations that start in the past and end either in the past or the present ('retrospective timing'). Different psychological processes are thought to be engaged in each of these cases. The former is thought to engage a clock-like mechanism that accurately tracks the continuing passage of time, whereas the latter is thought to engage a reconstructive process that utilizes both temporal and non-temporal information from the memory of past events. We propose that, from a biological perspective, these two forms of duration 'estimation' are supported by computational processes that are both reliant on population state dynamics but are nevertheless distinct. Prospective timing is effectively carried out in a single step where the ongoing dynamics of population activity directly serve as the computation of duration, whereas retrospective timing is carried out in two steps: the initial generation of population state dynamics through the process of event segmentation and the subsequent computation of duration utilizing the memory of those dynamics.
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Affiliation(s)
- Albert Tsao
- Department of Biology, Stanford University, Stanford, CA, USA.
| | | | - Warren H Meck
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - May-Britt Moser
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Edvard I Moser
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway.
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Low IIC, Williams AH, Campbell MG, Linderman SW, Giocomo LM. Dynamic and reversible remapping of network representations in an unchanging environment. Neuron 2021; 109:2967-2980.e11. [PMID: 34363753 DOI: 10.1016/j.neuron.2021.07.005] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 02/26/2021] [Accepted: 07/06/2021] [Indexed: 12/14/2022]
Abstract
Neurons in the medial entorhinal cortex alter their firing properties in response to environmental changes. This flexibility in neural coding is hypothesized to support navigation and memory by dividing sensory experience into unique episodes. However, it is unknown how the entorhinal circuit as a whole transitions between different representations when sensory information is not delineated into discrete contexts. Here we describe rapid and reversible transitions between multiple spatial maps of an unchanging task and environment. These remapping events were synchronized across hundreds of neurons, differentially affected navigational cell types, and correlated with changes in running speed. Despite widespread changes in spatial coding, remapping comprised a translation along a single dimension in population-level activity space, enabling simple decoding strategies. These findings provoke reconsideration of how the medial entorhinal cortex dynamically represents space and suggest a remarkable capacity of cortical circuits to rapidly and substantially reorganize their neural representations.
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Affiliation(s)
- Isabel I C Low
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
| | - Alex H Williams
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA; Department of Statistics, Stanford University, Stanford, CA, USA
| | - Malcolm G Campbell
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Scott W Linderman
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA; Department of Statistics, Stanford University, Stanford, CA, USA
| | - Lisa M Giocomo
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
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Irregular distribution of grid cell firing fields in rats exploring a 3D volumetric space. Nat Neurosci 2021; 24:1567-1573. [PMID: 34381241 PMCID: PMC8553607 DOI: 10.1038/s41593-021-00907-4] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 07/09/2021] [Indexed: 11/25/2022]
Abstract
We investigated how entorhinal grid cells encode volumetric space. On a horizontal surface, grid cells usually produce multiple, spatially focal, approximately circular firing fields that are evenly sized and spaced to form a regular, close-packed, hexagonal array. This spatial regularity has been suggested to underlie navigational computations. In three dimensions, theoretically the equivalent firing pattern would be a regular, hexagonal close packing of evenly sized spherical fields. In the present study, we report that, in rats foraging in a cubic lattice, grid cells maintained normal temporal firing characteristics and produced spatially stable firing fields. However, although most grid fields were ellipsoid, they were sparser, larger, more variably sized and irregularly arranged, even when only fields abutting the lower surface (equivalent to the floor) were considered. Thus, grid self-organization is shaped by the environment's structure and/or movement affordances, and grids may not need to be regular to support spatial computations.
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9
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Prefrontal Neural Ensembles Develop Selective Code for Stimulus Associations within Minutes of Novel Experiences. J Neurosci 2020; 40:8355-8366. [PMID: 32989098 DOI: 10.1523/jneurosci.1503-20.2020] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Revised: 08/25/2020] [Accepted: 09/20/2020] [Indexed: 12/14/2022] Open
Abstract
Prevailing theories posit that the hippocampus rapidly learns stimulus conjunctions during novel experiences, whereas the neocortex learns slowly through subsequent, off-line interaction with the hippocampus. Parallel evidence, however, shows that the medial prefrontal cortex (mPFC; a critical node of the neocortical network supporting long-term memory storage) undergoes rapid modifications of gene expression, synaptic structure, and physiology at the time of encoding. These observations, along with impaired learning with disrupted mPFC, suggest that mPFC neurons may exhibit rapid neural plasticity during novel experiences; however, direct empirical evidence is lacking. We extracellularly recorded action potentials of cells in the prelimbic region of the mPFC, while male rats received a sequence of stimulus presentations for the first time in life. Moment-to-moment tracking of neural ensemble firing patterns revealed that the prelimbic network activity exhibited an abrupt transition within 1 min after the first encounter of an aversive but not neutral stimulus. This network-level change was driven by ∼15% of neurons that immediately elevated their spontaneous firing rates (FRs) and developed firing responses to a neutral stimulus preceding the aversive stimulus within a few instances of their pairings. When a new sensory stimulus was paired with the same aversive stimulus, about half of these neurons generalized firing responses to the new stimulus association. Thus, prelimbic neurons are capable of rapidly forming ensemble codes for novel stimulus associations within minutes. This circuit property may enable the mPFC to rapidly detect and selectively encode the central content of novel experiences.SIGNIFICANCE STATEMENT During a new experience, a region of the brain, called the hippocampus, rapidly forms its memory and later instructs another region, called the neocortex, that stores its content. Consistent with this dominant view, cells in the neocortex gradually strengthen the selectivity for the memory content over weeks after novel experiences. However, we still do not know precisely when these cells begin to develop the selectivity. We found that neocortical cells were capable of forming the selectivity for ongoing events within a few minutes of new experiences. This finding provides support for an alternative view that the neocortex works with, but not follows, the hippocampus to form new memories.
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10
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Dentate gyrus circuits for encoding, retrieval and discrimination of episodic memories. Nat Rev Neurosci 2020; 21:153-168. [PMID: 32042144 DOI: 10.1038/s41583-019-0260-z] [Citation(s) in RCA: 203] [Impact Index Per Article: 50.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/18/2019] [Indexed: 12/19/2022]
Abstract
The dentate gyrus (DG) has a key role in hippocampal memory formation. Intriguingly, DG lesions impair many, but not all, hippocampus-dependent mnemonic functions, indicating that the rest of the hippocampus (CA1-CA3) can operate autonomously under certain conditions. An extensive body of theoretical work has proposed how the architectural elements and various cell types of the DG may underlie its function in cognition. Recent studies recorded and manipulated the activity of different neuron types in the DG during memory tasks and have provided exciting new insights into the mechanisms of DG computational processes, particularly for the encoding, retrieval and discrimination of similar memories. Here, we review these DG-dependent mnemonic functions in light of the new findings and explore mechanistic links between the cellular and network properties of, and the computations performed by, the DG.
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11
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Kang L, DeWeese MR. Replay as wavefronts and theta sequences as bump oscillations in a grid cell attractor network. eLife 2019; 8:46351. [PMID: 31736462 PMCID: PMC6901334 DOI: 10.7554/elife.46351] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 11/15/2019] [Indexed: 11/17/2022] Open
Abstract
Grid cells fire in sequences that represent rapid trajectories in space. During locomotion, theta sequences encode sweeps in position starting slightly behind the animal and ending ahead of it. During quiescence and slow wave sleep, bouts of synchronized activity represent long trajectories called replays, which are well-established in place cells and have been recently reported in grid cells. Theta sequences and replay are hypothesized to facilitate many cognitive functions, but their underlying mechanisms are unknown. One mechanism proposed for grid cell formation is the continuous attractor network. We demonstrate that this established architecture naturally produces theta sequences and replay as distinct consequences of modulating external input. Driving inhibitory interneurons at the theta frequency causes attractor bumps to oscillate in speed and size, which gives rise to theta sequences and phase precession, respectively. Decreasing input drive to all neurons produces traveling wavefronts of activity that are decoded as replays.
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Affiliation(s)
- Louis Kang
- Redwood Center for Theoretical Neuroscience, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States.,Department of Physics, University of California, Berkeley, Berkeley, United States
| | - Michael R DeWeese
- Redwood Center for Theoretical Neuroscience, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States.,Department of Physics, University of California, Berkeley, Berkeley, United States
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12
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Sugar J, Moser MB. Episodic memory: Neuronal codes for what, where, and when. Hippocampus 2019; 29:1190-1205. [PMID: 31334573 DOI: 10.1002/hipo.23132] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 06/06/2019] [Accepted: 06/12/2019] [Indexed: 11/07/2022]
Abstract
Episodic memory is defined as the ability to recall events in a spatiotemporal context. Formation of such memories is critically dependent on the hippocampal formation and its inputs from the entorhinal cortex. To be able to support the formation of episodic memories, entorhinal cortex and hippocampal formation should contain a neuronal code that follows several requirements. First, the code should include information about position of the agent ("where"), sequence of events ("when"), and the content of the experience itself ("what"). Second, the code should arise instantly thereby being able to support memory formation of one-shot experiences. For successful encoding and to avoid interference between memories during recall, variations in location, time, or in content of experience should result in unique ensemble activity. Finally, the code should capture several different resolutions of experience so that the necessary details relevant for future memory-based predictions will be stored. We review how neuronal codes in entorhinal cortex and hippocampus follow these requirements and argue that during formation of episodic memories entorhinal cortex provides hippocampus with instant information about ongoing experience. Such information originates from (a) spatially modulated neurons in medial entorhinal cortex, including grid cells, which provide a stable and universal positional metric of the environment; (b) a continuously varying signal in lateral entorhinal cortex providing a code for the temporal progression of events; and (c) entorhinal neurons coding the content of experiences exemplified by object-coding and odor-selective neurons. During formation of episodic memories, information from these systems are thought to be encoded as unique sequential ensemble activity in hippocampus, thereby encoding associations between the content of an event and its spatial and temporal contexts. Upon exposure to parts of the encoded stimuli, activity in these ensembles can be reinstated, leading to reactivation of the encoded activity pattern and memory recollection.
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Affiliation(s)
- Jørgen Sugar
- Centre for Neural Computation, Egil and Pauline Braathen and Fred Kavli Center for Cortical Microcircuits, Kavli Institute for Systems Neuroscience, Norwegian University for Science and Technology (NTNU), Trondheim, Norway
| | - May-Britt Moser
- Centre for Neural Computation, Egil and Pauline Braathen and Fred Kavli Center for Cortical Microcircuits, Kavli Institute for Systems Neuroscience, Norwegian University for Science and Technology (NTNU), Trondheim, Norway
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