1
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Dong LL, Fiete IR. Grid Cells in Cognition: Mechanisms and Function. Annu Rev Neurosci 2024; 47:345-368. [PMID: 38684081 DOI: 10.1146/annurev-neuro-101323-112047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
The activity patterns of grid cells form distinctively regular triangular lattices over the explored spatial environment and are largely invariant to visual stimuli, animal movement, and environment geometry. These neurons present numerous fascinating challenges to the curious (neuro)scientist: What are the circuit mechanisms responsible for creating spatially periodic activity patterns from the monotonic input-output responses of single neurons? How and why does the brain encode a local, nonperiodic variable-the allocentric position of the animal-with a periodic, nonlocal code? And, are grid cells truly specialized for spatial computations? Otherwise, what is their role in general cognition more broadly? We review efforts in uncovering the mechanisms and functional properties of grid cells, highlighting recent progress in the experimental validation of mechanistic grid cell models, and discuss the coding properties and functional advantages of the grid code as suggested by continuous attractor network models of grid cells.
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Affiliation(s)
- Ling L Dong
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;
| | - Ila R Fiete
- McGovern Institute and K. Lisa Yang Integrative Computational Neuroscience Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;
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2
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Dubanet O, Higley MJ. Retrosplenial inputs drive visual representations in the medial entorhinal cortex. Cell Rep 2024; 43:114470. [PMID: 38985682 PMCID: PMC11300029 DOI: 10.1016/j.celrep.2024.114470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 05/21/2024] [Accepted: 06/24/2024] [Indexed: 07/12/2024] Open
Abstract
The importance of visual cues for navigation and goal-directed behavior is well established, although the neural mechanisms supporting sensory representations in navigational circuits are largely unknown. Navigation is fundamentally dependent on the medial entorhinal cortex (MEC), which receives direct projections from neocortical visual areas, including the retrosplenial cortex (RSC). Here, we perform high-density recordings of MEC neurons in awake, head-fixed mice presented with simple visual stimuli and assess the dynamics of sensory-evoked activity. We find that a large fraction of neurons exhibit robust responses to visual input. Visually responsive cells are located primarily in layer 3 of the dorsal MEC and can be separated into subgroups based on functional and molecular properties. Furthermore, optogenetic suppression of RSC afferents within the MEC strongly reduces visual responses. Overall, our results demonstrate that the MEC can encode simple visual cues in the environment that may contribute to neural representations of location necessary for accurate navigation.
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Affiliation(s)
- Olivier Dubanet
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University, New Haven, CT 06510, USA
| | - Michael J Higley
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University, New Haven, CT 06510, USA.
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3
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Neupane S, Fiete I, Jazayeri M. Mental navigation in the primate entorhinal cortex. Nature 2024; 630:704-711. [PMID: 38867051 PMCID: PMC11224022 DOI: 10.1038/s41586-024-07557-z] [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: 12/13/2022] [Accepted: 05/10/2024] [Indexed: 06/14/2024]
Abstract
A cognitive map is a suitably structured representation that enables novel computations using previous experience; for example, planning a new route in a familiar space1. Work in mammals has found direct evidence for such representations in the presence of exogenous sensory inputs in both spatial2,3 and non-spatial domains4-10. Here we tested a foundational postulate of the original cognitive map theory1,11: that cognitive maps support endogenous computations without external input. We recorded from the entorhinal cortex of monkeys in a mental navigation task that required the monkeys to use a joystick to produce one-dimensional vectors between pairs of visual landmarks without seeing the intermediate landmarks. The ability of the monkeys to perform the task and generalize to new pairs indicated that they relied on a structured representation of the landmarks. Task-modulated neurons exhibited periodicity and ramping that matched the temporal structure of the landmarks and showed signatures of continuous attractor networks12,13. A continuous attractor network model of path integration14 augmented with a Hebbian-like learning mechanism provided an explanation of how the system could endogenously recall landmarks. The model also made an unexpected prediction that endogenous landmarks transiently slow path integration, reset the dynamics and thereby reduce variability. This prediction was borne out in a reanalysis of firing rate variability and behaviour. Our findings link the structured patterns of activity in the entorhinal cortex to the endogenous recruitment of a cognitive map during mental navigation.
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Affiliation(s)
- Sujaya Neupane
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ila Fiete
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Mehrdad Jazayeri
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
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4
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Clark H, Nolan MF. Task-anchored grid cell firing is selectively associated with successful path integration-dependent behaviour. eLife 2024; 12:RP89356. [PMID: 38546203 PMCID: PMC10977970 DOI: 10.7554/elife.89356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/01/2024] Open
Abstract
Grid firing fields have been proposed as a neural substrate for spatial localisation in general or for path integration in particular. To distinguish these possibilities, we investigate firing of grid and non-grid cells in the mouse medial entorhinal cortex during a location memory task. We find that grid firing can either be anchored to the task environment, or can encode distance travelled independently of the task reference frame. Anchoring varied between and within sessions, while spatial firing of non-grid cells was either coherent with the grid population, or was stably anchored to the task environment. We took advantage of the variability in task-anchoring to evaluate whether and when encoding of location by grid cells might contribute to behaviour. We find that when reward location is indicated by a visual cue, performance is similar regardless of whether grid cells are task-anchored or not, arguing against a role for grid representations when location cues are available. By contrast, in the absence of the visual cue, performance was enhanced when grid cells were anchored to the task environment. Our results suggest that anchoring of grid cells to task reference frames selectively enhances performance when path integration is required.
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Affiliation(s)
- Harry Clark
- Centre for Discovery Brain Sciences, Simons Initiative for the Developing Brain, Hugh Robson Building, University of EdinburghEdinburghUnited Kingdom
| | - Matthew F Nolan
- Centre for Discovery Brain Sciences, Simons Initiative for the Developing Brain, Hugh Robson Building, University of EdinburghEdinburghUnited Kingdom
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5
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Cheng N, Dong Q, Zhang Z, Wang L, Chen X, Wang C. Egocentric processing of items in spines, dendrites, and somas in the retrosplenial cortex. Neuron 2024; 112:646-660.e8. [PMID: 38101396 DOI: 10.1016/j.neuron.2023.11.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 08/31/2023] [Accepted: 11/15/2023] [Indexed: 12/17/2023]
Abstract
Egocentric representations of external items are essential for spatial navigation and memory. Here, we explored the neural mechanisms underlying egocentric processing in the retrosplenial cortex (RSC), a pivotal area for memory and navigation. Using one-photon and two-photon calcium imaging, we identified egocentric tuning for environment boundaries in dendrites, spines, and somas of RSC neurons (egocentric boundary cells) in the open-field task. Dendrites with egocentric tuning tended to have similarly tuned spines. We further identified egocentric neurons representing landmarks in a virtual navigation task or remembered cue location in a goal-oriented task, respectively. These neurons formed an independent population with egocentric boundary cells, suggesting that dedicated neurons with microscopic clustering of functional inputs shaped egocentric boundary processing in RSC and that RSC adopted a labeled line code with distinct classes of egocentric neurons responsible for representing different items in specific behavioral contexts, which could lead to efficient and flexible computation.
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Affiliation(s)
- Ning Cheng
- Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Qiqi Dong
- Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Zhen Zhang
- CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Li Wang
- Brain Research Centre, Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xiaojing Chen
- Brain Research Centre, Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
| | - Cheng Wang
- Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; CAS Centre for Excellence in Brain Science and Intelligent Technology, Shanghai, China.
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6
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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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7
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Reinshagen A. Grid cells: the missing link in understanding Parkinson's disease? Front Neurosci 2024; 18:1276714. [PMID: 38389787 PMCID: PMC10881698 DOI: 10.3389/fnins.2024.1276714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 01/24/2024] [Indexed: 02/24/2024] Open
Abstract
The mechanisms underlying Parkinson's disease (PD) are complex and not fully understood, and the box-and-arrow model among other current models present significant challenges. This paper explores the potential role of the allocentric brain and especially its grid cells in several PD motor symptoms, including bradykinesia, kinesia paradoxa, freezing of gait, the bottleneck phenomenon, and their dependency on cueing. It is argued that central hubs, like the locus coeruleus and the pedunculopontine nucleus, often narrowly interpreted in the context of PD, play an equally important role in governing the allocentric brain as the basal ganglia. Consequently, the motor and secondary motor (e.g., spatially related) symptoms of PD linked with dopamine depletion may be more closely tied to erroneous computation by grid cells than to the basal ganglia alone. Because grid cells and their associated central hubs introduce both spatial and temporal information to the brain influencing velocity perception they may cause bradykinesia or hyperkinesia as well. In summary, PD motor symptoms may primarily be an allocentric disturbance resulting from virtual faulty computation by grid cells revealed by dopamine depletion in PD.
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8
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Nguyen D, Wang G, Gu Y. The medial entorhinal cortex encodes multisensory spatial information. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.09.574924. [PMID: 38313299 PMCID: PMC10836072 DOI: 10.1101/2024.01.09.574924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Animals employ spatial information in multisensory modalities to navigate their natural environments. However, it is unclear whether the brain encodes such information in separate cognitive maps or integrates all into a single, universal map. We addressed this question in the microcircuit of the medial entorhinal cortex (MEC), a cognitive map of space. Using cellular-resolution calcium imaging, we examined the MEC of mice navigating virtual reality tracks, where visual and auditory cues provided comparable spatial information. We uncovered two cell types: "unimodality cells" and "multimodality cells". The unimodality cells specifically represent either auditory or visual spatial information. They are anatomically intermingled and maintain sensory preferences across multiple tracks and behavioral states. The multimodality cells respond to both sensory modalities with their responses shaped differentially by auditory and visual information. Thus, the MEC enables accurate spatial encoding during multisensory navigation by computing spatial information in different sensory modalities and generating distinct maps.
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Affiliation(s)
- 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
| | - Garret Wang
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, 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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9
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Dubanet O, Higley MJ. Retrosplenial inputs drive diverse visual representations in the medial entorhinal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.03.560642. [PMID: 37873152 PMCID: PMC10592898 DOI: 10.1101/2023.10.03.560642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The ability of rodents to use visual cues for successful navigation and goal-directed behavior has been long appreciated, although the neural mechanisms supporting sensory representations in navigational circuits are largely unknown. Navigation is fundamentally dependent on the hippocampus and closely connected entorhinal cortex, whose neurons exhibit characteristic firing patterns corresponding to the animal's location. The medial entorhinal cortex (MEC) receives direct projections from sensory areas in the neocortex, suggesting the ability to encode sensory information. To examine this possibility, we performed high-density recordings of MEC neurons in awake, head-fixed mice presented with simple visual stimuli and assessed the dynamics of sensory-evoked activity. We found a large fraction of neurons exhibited robust responses to visual input that shaped activity relative to ongoing network dynamics. Visually responsive cells could be separated into subgroups based on functional and molecular properties within deep layers of the dorsal MEC, suggesting diverse populations within the MEC contribute to sensory encoding. We then showed that optogenetic suppression of retrosplenial cortex afferents within the MEC strongly reduced visual responses. Overall, our results demonstrate the the MEC can encode simple visual cues in the environment that can contribute to neural representations of location necessary for accurate navigation.
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Affiliation(s)
- Olivier Dubanet
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University, New Haven, CT, 06510, USA
| | - Michael J Higley
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University, New Haven, CT, 06510, USA
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10
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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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11
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Saleem AB, Busse L. Interactions between rodent visual and spatial systems during navigation. Nat Rev Neurosci 2023:10.1038/s41583-023-00716-7. [PMID: 37380885 DOI: 10.1038/s41583-023-00716-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/31/2023] [Indexed: 06/30/2023]
Abstract
Many behaviours that are critical for animals to survive and thrive rely on spatial navigation. Spatial navigation, in turn, relies on internal representations about one's spatial location, one's orientation or heading direction and the distance to objects in the environment. Although the importance of vision in guiding such internal representations has long been recognized, emerging evidence suggests that spatial signals can also modulate neural responses in the central visual pathway. Here, we review the bidirectional influences between visual and navigational signals in the rodent brain. Specifically, we discuss reciprocal interactions between vision and the internal representations of spatial position, explore the effects of vision on representations of an animal's heading direction and vice versa, and examine how the visual and navigational systems work together to assess the relative distances of objects and other features. Throughout, we consider how technological advances and novel ethological paradigms that probe rodent visuo-spatial behaviours allow us to advance our understanding of how brain areas of the central visual pathway and the spatial systems interact and enable complex behaviours.
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Affiliation(s)
- Aman B Saleem
- UCL Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London, UK.
| | - Laura Busse
- Division of Neuroscience, Faculty of Biology, LMU Munich, Munich, Germany.
- Bernstein Centre for Computational Neuroscience Munich, Munich, Germany.
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12
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Applegate MC, Gutnichenko KS, Mackevicius EL, Aronov D. An entorhinal-like region in food-caching birds. Curr Biol 2023; 33:2465-2477.e7. [PMID: 37295426 PMCID: PMC10329498 DOI: 10.1016/j.cub.2023.05.031] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 04/14/2023] [Accepted: 05/15/2023] [Indexed: 06/12/2023]
Abstract
The mammalian entorhinal cortex routes inputs from diverse sources into the hippocampus. This information is mixed and expressed in the activity of many specialized entorhinal cell types, which are considered indispensable for hippocampal function. However, functionally similar hippocampi exist even in non-mammals that lack an obvious entorhinal cortex or, generally, any layered cortex. To address this dilemma, we mapped extrinsic hippocampal connections in chickadees, whose hippocampi are used for remembering numerous food caches. We found a well-delineated structure in these birds that is topologically similar to the entorhinal cortex and interfaces between the hippocampus and other pallial regions. Recordings of this structure revealed entorhinal-like activity, including border and multi-field grid-like cells. These cells were localized to the subregion predicted by anatomical mapping to match the dorsomedial entorhinal cortex. Our findings uncover an anatomical and physiological equivalence of vastly different brains, suggesting a fundamental nature of entorhinal-like computations for hippocampal function.
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Affiliation(s)
- Marissa C Applegate
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, 3227 Broadway, New York, NY 10027, USA
| | - Konstantin S Gutnichenko
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, 3227 Broadway, New York, NY 10027, USA
| | - Emily L Mackevicius
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, 3227 Broadway, New York, NY 10027, USA
| | - Dmitriy Aronov
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, 3227 Broadway, New York, NY 10027, USA.
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13
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Yu F, Wu Y, Ma S, Xu M, Li H, Qu H, Song C, Wang T, Zhao R, Shi L. Brain-inspired multimodal hybrid neural network for robot place recognition. Sci Robot 2023; 8:eabm6996. [PMID: 37163608 DOI: 10.1126/scirobotics.abm6996] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Place recognition is an essential spatial intelligence capability for robots to understand and navigate the world. However, recognizing places in natural environments remains a challenging task for robots because of resource limitations and changing environments. In contrast, humans and animals can robustly and efficiently recognize hundreds of thousands of places in different conditions. Here, we report a brain-inspired general place recognition system, dubbed NeuroGPR, that enables robots to recognize places by mimicking the neural mechanism of multimodal sensing, encoding, and computing through a continuum of space and time. Our system consists of a multimodal hybrid neural network (MHNN) that encodes and integrates multimodal cues from both conventional and neuromorphic sensors. Specifically, to encode different sensory cues, we built various neural networks of spatial view cells, place cells, head direction cells, and time cells. To integrate these cues, we designed a multiscale liquid state machine that can process and fuse multimodal information effectively and asynchronously using diverse neuronal dynamics and bioinspired inhibitory circuits. We deployed the MHNN on Tianjic, a hybrid neuromorphic chip, and integrated it into a quadruped robot. Our results show that NeuroGPR achieves better performance compared with conventional and existing biologically inspired approaches, exhibiting robustness to diverse environmental uncertainty, including perceptual aliasing, motion blur, light, or weather changes. Running NeuroGPR as an overall multi-neural network workload on Tianjic showcases its advantages with 10.5 times lower latency and 43.6% lower power consumption than the commonly used mobile robot processor Jetson Xavier NX.
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Affiliation(s)
- Fangwen Yu
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Yujie Wu
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
- Institute of Theoretical Computer Science, Graz University of Technology, Graz, Austria
| | - Songchen Ma
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Mingkun Xu
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Hongyi Li
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Huanyu Qu
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Chenhang Song
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Taoyi Wang
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Rong Zhao
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Luping Shi
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
- THU-CET HIK Joint Research Center for Brain-Inspired Computing, Tsinghua University, Beijing 100084, China
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14
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Effects of neuromodulation-inspired mechanisms on the performance of deep neural networks in a spatial learning task. iScience 2023; 26:106026. [PMID: 36818295 PMCID: PMC9929609 DOI: 10.1016/j.isci.2023.106026] [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: 09/09/2022] [Revised: 11/18/2022] [Accepted: 01/19/2023] [Indexed: 01/25/2023] Open
Abstract
In recent years, the biological underpinnings of adaptive learning have been modeled, leading to faster model convergence and various behavioral benefits in tasks including spatial navigation and cue-reward association. Furthermore, studies have investigated how the neuromodulatory system, a major driver of synaptic plasticity and state-dependent changes in the brain neuronal activities, plays a role in training deep neural networks (DNNs). In this study, we extended previous studies on neuromodulation-inspired DNNs and explored the effects of neuromodulatory components on learning and single unit activities in a spatial learning task. Under the multiscale neuromodulatory framework, plastic components, dropout probability modulation, and learning rate decay were added to the single unit, layer, and whole network levels of DNN models, respectively. We observed behavioral benefits including faster learning and smaller error of ambulation. We then concluded that neuromodulatory components can affect learning trajectories, outcomes, and single unit activities, in a component- and hyperparameter-dependent manner.
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15
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Applegate MC, Gutnichenko KS, Mackevicius EL, Aronov D. An entorhinal-like region in food-caching birds. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.05.522940. [PMID: 36711539 PMCID: PMC9881956 DOI: 10.1101/2023.01.05.522940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The mammalian entorhinal cortex routes inputs from diverse sources into the hippocampus. This information is mixed and expressed in the activity of many specialized entorhinal cell types, which are considered indispensable for hippocampal function. However, functionally similar hippocampi exist even in non-mammals that lack an obvious entorhinal cortex, or generally any layered cortex. To address this dilemma, we mapped extrinsic hippocampal connections in chickadees, whose hippocampi are used for remembering numerous food caches. We found a well-delineated structure in these birds that is topologically similar to the entorhinal cortex and interfaces between the hippocampus and other pallial regions. Recordings of this structure revealed entorhinal-like activity, including border and multi-field grid-like cells. These cells were localized to the subregion predicted by anatomical mapping to match the dorsomedial entorhinal cortex. Our findings uncover an anatomical and physiological equivalence of vastly different brains, suggesting a fundamental nature of entorhinal-like computations for hippocampal function.
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Affiliation(s)
| | | | | | - Dmitriy Aronov
- Zuckerman Mind Brain Behavior Institute, Columbia University,Corresponding author:
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16
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Tennant SA, Clark H, Hawes I, Tam WK, Hua J, Yang W, Gerlei KZ, Wood ER, Nolan MF. Spatial representation by ramping activity of neurons in the retrohippocampal cortex. Curr Biol 2022; 32:4451-4464.e7. [PMID: 36099915 DOI: 10.1016/j.cub.2022.08.050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 07/05/2022] [Accepted: 08/17/2022] [Indexed: 11/18/2022]
Abstract
Neurons in the retrohippocampal cortices play crucial roles in spatial memory. Many retrohippocampal neurons have firing fields that are selectively active at specific locations, with memory for rewarded locations associated with reorganization of these firing fields. Whether this is the sole strategy for representing spatial memories is unclear. Here, we demonstrate that during a spatial memory task retrohippocampal neurons encode location through ramping activity that extends across segments of a linear track approaching and following a reward, with the rewarded location represented by offsets or switches in the slope of the ramping activity. Ramping representations could be maintained independently of trial outcome and cues marking the reward location, indicating that they result from recall of the track structure. When recorded in an open arena, neurons that generated ramping activity during the spatial memory task were more numerous than grid or border cells, with a majority showing spatial firing that did not meet criteria for classification as grid or border representations. Encoding of rewarded locations through offsets and switches in the slope of ramping activity also emerged in recurrent neural network models trained to solve a similar spatial memory task. Impaired performance of model networks following disruption of outputs from ramping neurons is consistent with this coding strategy supporting navigation to recalled locations of behavioral significance. Our results suggest that encoding of learned spaces by retrohippocampal networks employs both discrete firing fields and continuous ramping representations. We hypothesize that retrohippocampal ramping activity mediates readout of learned models for goal-directed navigation.
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Affiliation(s)
- Sarah A Tennant
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Harry Clark
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Ian Hawes
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Wing Kin Tam
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK; Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
| | - Junji Hua
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Wannan Yang
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Klara Z Gerlei
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Emma R Wood
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK; Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
| | - Matthew F Nolan
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK; Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK; Centre for Statistics, University of Edinburgh, Edinburgh, UK.
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17
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LaChance PA, Graham J, Shapiro BL, Morris AJ, Taube JS. Landmark-modulated directional coding in postrhinal cortex. SCIENCE ADVANCES 2022; 8:eabg8404. [PMID: 35089792 PMCID: PMC8797796 DOI: 10.1126/sciadv.abg8404] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 12/07/2021] [Indexed: 06/14/2023]
Abstract
Visual landmarks can anchor an animal's internal sense of orientation to the external world. The rodent postrhinal cortex (POR) may facilitate this processing. Here, we demonstrate that, in contrast to classic head direction (HD) cells, which have a single preferred orientation, POR HD cells develop a second preferred orientation when an established landmark cue is duplicated along another environmental wall. We therefore refer to these cells as landmark-modulated-HD (LM-HD) cells. LM-HD cells discriminate between landmarks in familiar and novel locations, discriminate between visually disparate landmarks, and continue to respond to the previous location of a familiar landmark following its removal. Rats initially exposed to different stable landmark configurations show LM-HD tuning that may reflect the integration of visual landmark information into an allocentric HD signal. These results provide insight into how visual landmarks are integrated into a framework that supports the neural encoding of landmark-based orientation.
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Affiliation(s)
- Patrick A. LaChance
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Jalina Graham
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Benjamin L. Shapiro
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Ashlyn J. Morris
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
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18
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Vandrey B, Armstrong J, Brown CM, Garden DLF, Nolan MF. Fan cells in lateral entorhinal cortex directly influence medial entorhinal cortex through synaptic connections in layer 1. eLife 2022; 11:83008. [PMID: 36562467 PMCID: PMC9822265 DOI: 10.7554/elife.83008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022] Open
Abstract
Standard models for spatial and episodic memory suggest that the lateral entorhinal cortex (LEC) and medial entorhinal cortex (MEC) send parallel independent inputs to the hippocampus, each carrying different types of information. Here, we evaluate the possibility that information is integrated between divisions of the entorhinal cortex prior to reaching the hippocampus. We demonstrate that, in mice, fan cells in layer 2 (L2) of LEC that receive neocortical inputs, and that project to the hippocampal dentate gyrus, also send axon collaterals to layer 1 (L1) of the MEC. Activation of inputs from fan cells evokes monosynaptic glutamatergic excitation of stellate and pyramidal cells in L2 of the MEC, typically followed by inhibition that contains fast and slow components mediated by GABAA and GABAB receptors, respectively. Inputs from fan cells also directly activate interneurons in L1 and L2 of MEC, with synaptic connections from L1 interneurons accounting for slow feedforward inhibition of L2 principal cell populations. The relative strength of excitation and inhibition following fan cell activation differs substantially between neurons and is largely independent of anatomical location. Our results demonstrate that the LEC, in addition to directly influencing the hippocampus, can activate or inhibit major hippocampal inputs arising from the MEC. Thus, local circuits in the superficial MEC may combine spatial information with sensory and higher order signals from the LEC, providing a substrate for integration of 'what' and 'where' components of episodic memories.
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Affiliation(s)
- Brianna Vandrey
- Centre for Discovery Brain Sciences, University of EdinburghEdinburghUnited Kingdom
| | - Jack Armstrong
- Centre for Discovery Brain Sciences, University of EdinburghEdinburghUnited Kingdom
| | - Christina M Brown
- Centre for Discovery Brain Sciences, University of EdinburghEdinburghUnited Kingdom
| | - Derek LF Garden
- Centre for Discovery Brain Sciences, University of EdinburghEdinburghUnited Kingdom
| | - Matthew F Nolan
- Centre for Discovery Brain Sciences, University of EdinburghEdinburghUnited Kingdom,Simons Initiative for the Developing Brain, University of EdinburghEdinburghUnited Kingdom,Centre for Statistics, University of EdinburghEdinburghUnited Kingdom
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19
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Campbell MG, Attinger A, Ocko SA, Ganguli S, Giocomo LM. Distance-tuned neurons drive specialized path integration calculations in medial entorhinal cortex. Cell Rep 2021; 36:109669. [PMID: 34496249 PMCID: PMC8437084 DOI: 10.1016/j.celrep.2021.109669] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 05/25/2021] [Accepted: 08/13/2021] [Indexed: 12/01/2022] Open
Abstract
During navigation, animals estimate their position using path integration and landmarks, engaging many brain areas. Whether these areas follow specialized or universal cue integration principles remains incompletely understood. We combine electrophysiology with virtual reality to quantify cue integration across thousands of neurons in three navigation-relevant areas: primary visual cortex (V1), retrosplenial cortex (RSC), and medial entorhinal cortex (MEC). Compared with V1 and RSC, path integration influences position estimates more in MEC, and conflicts between path integration and landmarks trigger remapping more readily. Whereas MEC codes position prospectively, V1 codes position retrospectively, and RSC is intermediate between the two. Lowered visual contrast increases the influence of path integration on position estimates only in MEC. These properties are most pronounced in a population of MEC neurons, overlapping with grid cells, tuned to distance run in darkness. These results demonstrate the specialized role that path integration plays in MEC compared with other navigation-relevant cortical areas.
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Affiliation(s)
- Malcolm G Campbell
- Department of Neurobiology, Stanford University, Stanford, CA 94305, USA
| | - Alexander Attinger
- Department of Neurobiology, Stanford University, Stanford, CA 94305, USA
| | - Samuel A Ocko
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Surya Ganguli
- Department of Neurobiology, Stanford University, Stanford, CA 94305, USA; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Lisa M Giocomo
- Department of Neurobiology, Stanford University, Stanford, CA 94305, USA.
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20
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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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21
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Lee SM, Jin SW, Park SB, Park EH, Lee CH, Lee HW, Lim HY, Yoo SW, Ahn JR, Shin J, Lee SA, Lee I. Goal-directed interaction of stimulus and task demand in the parahippocampal region. Hippocampus 2021; 31:717-736. [PMID: 33394547 PMCID: PMC8359334 DOI: 10.1002/hipo.23295] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 12/05/2020] [Accepted: 12/12/2020] [Indexed: 11/10/2022]
Abstract
The hippocampus and parahippocampal region are essential for representing episodic memories involving various spatial locations and objects, and for using those memories for future adaptive behavior. The “dual‐stream model” was initially formulated based on anatomical characteristics of the medial temporal lobe, dividing the parahippocampal region into two streams that separately process and relay spatial and nonspatial information to the hippocampus. Despite its significance, the dual‐stream model in its original form cannot explain recent experimental results, and many researchers have recognized the need for a modification of the model. Here, we argue that dividing the parahippocampal region into spatial and nonspatial streams a priori may be too simplistic, particularly in light of ambiguous situations in which a sensory cue alone (e.g., visual scene) may not allow such a definitive categorization. Upon reviewing evidence, including our own, that reveals the importance of goal‐directed behavioral responses in determining the relative involvement of the parahippocampal processing streams, we propose the Goal‐directed Interaction of Stimulus and Task‐demand (GIST) model. In the GIST model, input stimuli such as visual scenes and objects are first processed by both the postrhinal and perirhinal cortices—the postrhinal cortex more heavily involved with visual scenes and perirhinal cortex with objects—with relatively little dependence on behavioral task demand. However, once perceptual ambiguities are resolved and the scenes and objects are identified and recognized, the information is then processed through the medial or lateral entorhinal cortex, depending on whether it is used to fulfill navigational or non‐navigational goals, respectively. As complex sensory stimuli are utilized for both navigational and non‐navigational purposes in an intermixed fashion in naturalistic settings, the hippocampus may be required to then put together these experiences into a coherent map to allow flexible cognitive operations for adaptive behavior to occur.
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Affiliation(s)
- Su-Min Lee
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, South Korea
| | - Seung-Woo Jin
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, South Korea
| | - Seong-Beom Park
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, South Korea
| | - Eun-Hye Park
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, South Korea
| | - Choong-Hee Lee
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, South Korea
| | - Hyun-Woo Lee
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, South Korea
| | - Heung-Yeol Lim
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, South Korea
| | - Seung-Woo Yoo
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Brain Institute, Florida Atlantic University, Jupiter, Florida, USA
| | - Jae Rong Ahn
- Department of Biology, Tufts University, Medford, Massachusetts, USA
| | - Jhoseph Shin
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, South Korea
| | - Sang Ah Lee
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
| | - Inah Lee
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, South Korea
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