1
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Basu J, Nagel K. Neural circuits for goal-directed navigation across species. Trends Neurosci 2024:S0166-2236(24)00177-2. [PMID: 39393938 DOI: 10.1016/j.tins.2024.09.005] [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: 05/07/2024] [Revised: 08/26/2024] [Accepted: 09/17/2024] [Indexed: 10/13/2024]
Abstract
Across species, navigation is crucial for finding both resources and shelter. In vertebrates, the hippocampus supports memory-guided goal-directed navigation, whereas in arthropods the central complex supports similar functions. A growing literature is revealing similarities and differences in the organization and function of these brain regions. We review current knowledge about how each structure supports goal-directed navigation by building internal representations of the position or orientation of an animal in space, and of the location or direction of potential goals. We describe input pathways to each structure - medial and lateral entorhinal cortex in vertebrates, and columnar and tangential neurons in insects - that primarily encode spatial and non-spatial information, respectively. Finally, we highlight similarities and differences in spatial encoding across clades and suggest experimental approaches to compare coding principles and behavioral capabilities across species. Such a comparative approach can provide new insights into the neural basis of spatial navigation and neural computation.
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Affiliation(s)
- 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.
| | - Katherine Nagel
- 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; Center for Neural Science, New York University, New York, NY 10003, USA.
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2
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Urbaniak R, Xie M, Mackevicius E. Linking cognitive strategy, neural mechanism, and movement statistics in group foraging behaviors. Sci Rep 2024; 14:21770. [PMID: 39294261 PMCID: PMC11411083 DOI: 10.1038/s41598-024-71931-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 09/02/2024] [Indexed: 09/20/2024] Open
Abstract
Foraging for food is a rich and ubiquitous animal behavior that involves complex cognitive decisions, and interactions between different individuals and species. There has been exciting recent progress in understanding multi-agent foraging behavior from cognitive, neuroscience, and statistical perspectives, but integrating these perspectives can be elusive. This paper seeks to unify these perspectives, allowing statistical analysis of observational animal movement data to shed light on the viability of cognitive models of foraging strategies. We start with cognitive agents with internal preferences expressed as value functions, and implement this in a biologically plausible neural network, and an equivalent statistical model, where statistical predictors of agents' movements correspond to the components of the value functions. We test this framework by simulating foraging agents and using Bayesian statistical modeling to correctly identify the factors that best predict the agents' behavior. As further validation, we use this framework to analyze an open-source locust foraging dataset. Finally, we collect new multi-agent real-world bird foraging data, and apply this method to analyze the preferences of different species. Together, this work provides an initial roadmap to integrate cognitive, neuroscience, and statistical approaches for reasoning about animal foraging in complex multi-agent environments.
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Affiliation(s)
| | - Marjorie Xie
- Basis Research Institute, New York, 10026, USA
- Arizona State University, School for the Future of Innovation in Society, Tempe, 85287, USA
- New York Academy of Sciences, New York, 10006, USA
- Columbia University, New York, 10027, USA
| | - Emily Mackevicius
- Basis Research Institute, New York, 10026, USA.
- Columbia University, New York, 10027, USA.
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3
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Cao R, Bright IM, Howard MW. Ramping cells in the rodent medial prefrontal cortex encode time to past and future events via real Laplace transform. Proc Natl Acad Sci U S A 2024; 121:e2404169121. [PMID: 39254998 PMCID: PMC11420195 DOI: 10.1073/pnas.2404169121] [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: 02/28/2024] [Accepted: 08/05/2024] [Indexed: 09/11/2024] Open
Abstract
In interval reproduction tasks, animals must remember the event starting the interval and anticipate the time of the planned response to terminate the interval. The interval reproduction task thus allows for studying both memory for the past and anticipation of the future. We analyzed previously published recordings from the rodent medial prefrontal cortex [J. Henke et al., eLife10, e71612 (2021)] during an interval reproduction task and identified two cell groups by modeling their temporal receptive fields using hierarchical Bayesian models. The firing in the "past cells" group peaked at the start of the interval and relaxed exponentially back to baseline. The firing in the "future cells" group increased exponentially and peaked right before the planned action at the end of the interval. Contrary to the previous assumption that timing information in the brain has one or two time scales for a given interval, we found strong evidence for a continuous distribution of the exponential rate constants for both past and future cell populations. The real Laplace transformation of time predicts exponential firing with a continuous distribution of rate constants across the population. Therefore, the firing pattern of the past cells can be identified with the Laplace transform of time since the past event while the firing pattern of the future cells can be identified with the Laplace transform of time until the planned future event.
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Affiliation(s)
- Rui Cao
- Department of Psychological and Brain Sciences, Boston University, Boston, MA02215
| | - Ian M. Bright
- Department of Psychological and Brain Sciences, Boston University, Boston, MA02215
| | - Marc W. Howard
- Department of Psychological and Brain Sciences, Boston University, Boston, MA02215
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4
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Park K, Yeo Y, Shin K, Kwag J. Egocentric neural representation of geometric vertex in the retrosplenial cortex. Nat Commun 2024; 15:7156. [PMID: 39169030 PMCID: PMC11339352 DOI: 10.1038/s41467-024-51391-w] [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: 07/12/2023] [Accepted: 08/07/2024] [Indexed: 08/23/2024] Open
Abstract
Egocentric neural representations of environmental features, such as edges and vertices, are important for constructing a geometrically detailed egocentric cognitive map for goal-directed navigation and episodic memory. While egocentric neural representations of edges like egocentric boundary/border cells exist, those that selectively represent vertices egocentrically are yet unknown. Here we report that granular retrosplenial cortex (RSC) neurons in male mice generate spatial receptive fields exclusively near the vertices of environmental geometries during free exploration, termed vertex cells. Their spatial receptive fields occurred at a specific orientation and distance relative to the heading direction of mice, indicating egocentric vector coding of vertex. Removing physical boundaries defining the environmental geometry abolished the egocentric vector coding of vertex, and goal-directed navigation strengthened the egocentric vector coding at the goal-located vertex. Our findings suggest that egocentric vector coding of vertex by granular RSC neurons helps construct an egocentric cognitive map that guides goal-directed navigation.
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Affiliation(s)
- Kyerl Park
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, 08826, Republic of Korea
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Yoonsoo Yeo
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, 08826, Republic of Korea
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Kisung Shin
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Jeehyun Kwag
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, 08826, Republic of Korea.
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5
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Raju RV, Guntupalli JS, Zhou G, Wendelken C, Lázaro-Gredilla M, George D. Space is a latent sequence: A theory of the hippocampus. SCIENCE ADVANCES 2024; 10:eadm8470. [PMID: 39083616 PMCID: PMC11290523 DOI: 10.1126/sciadv.adm8470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 06/26/2024] [Indexed: 08/02/2024]
Abstract
Fascinating phenomena such as landmark vector cells and splitter cells are frequently discovered in the hippocampus. Without a unifying principle, each experiment seemingly uncovers new anomalies or coding types. Here, we provide a unifying principle that the mental representation of space is an emergent property of latent higher-order sequence learning. Treating space as a sequence resolves numerous phenomena and suggests that the place field mapping methodology that interprets sequential neuronal responses in Euclidean terms might itself be a source of anomalies. Our model, clone-structured causal graph (CSCG), employs higher-order graph scaffolding to learn latent representations by mapping aliased egocentric sensory inputs to unique contexts. Learning to compress sequential and episodic experiences using CSCGs yields allocentric cognitive maps that are suitable for planning, introspection, consolidation, and abstraction. By explicating the role of Euclidean place field mapping and demonstrating how latent sequential representations unify myriad observed phenomena, our work positions the hippocampus in a sequence-centric paradigm, challenging the prevailing space-centric view.
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6
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Regele-Blasco E, Palmer LM. The plasticity of pyramidal neurons in the behaving brain. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230231. [PMID: 38853566 PMCID: PMC11407500 DOI: 10.1098/rstb.2023.0231] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 03/17/2024] [Accepted: 04/23/2024] [Indexed: 06/11/2024] Open
Abstract
Neurons are plastic. That is, they change their activity according to different behavioural conditions. This endows pyramidal neurons with an incredible computational power for the integration and processing of synaptic inputs. Plasticity can be investigated at different levels of investigation within a single neuron, from spines to dendrites, to synaptic input. Although most of our knowledge stems from the in vitro brain slice preparation, plasticity plays a vital role during behaviour by providing a flexible substrate for the execution of appropriate actions in our ever-changing environment. Owing to advances in recording techniques, the plasticity of neurons and the neural networks in which they are embedded is now beginning to be realized in the in vivo intact brain. This review focuses on the structural and functional synaptic plasticity of pyramidal neurons, with a specific focus on the latest developments from in vivo studies. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.
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Affiliation(s)
- Elena Regele-Blasco
- The Florey Institute of Neuroscience and Mental Health, The Florey Department of Neuroscience and Mental Health, University of Melbourne , Victoria 3052, Australia
| | - Lucy M Palmer
- The Florey Institute of Neuroscience and Mental Health, The Florey Department of Neuroscience and Mental Health, University of Melbourne , Victoria 3052, Australia
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7
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Lee JY, Jung D, Royer S. Stochastic characterization of navigation strategies in an automated variant of the Barnes maze. eLife 2024; 12:RP88648. [PMID: 38899521 PMCID: PMC11189626 DOI: 10.7554/elife.88648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2024] Open
Abstract
Animals can use a repertoire of strategies to navigate in an environment, and it remains an intriguing question how these strategies are selected based on the nature and familiarity of environments. To investigate this question, we developed a fully automated variant of the Barnes maze, characterized by 24 vestibules distributed along the periphery of a circular arena, and monitored the trajectories of mice over 15 days as they learned to navigate towards a goal vestibule from a random start vestibule. We show that the patterns of vestibule visits can be reproduced by the combination of three stochastic processes reminiscent of random, serial, and spatial strategies. The processes randomly selected vestibules based on either uniform (random) or biased (serial and spatial) probability distributions. They closely matched experimental data across a range of statistical distributions characterizing the length, distribution, step size, direction, and stereotypy of vestibule sequences, revealing a shift from random to spatial and serial strategies over time, with a strategy switch occurring approximately every six vestibule visits. Our study provides a novel apparatus and analysis toolset for tracking the repertoire of navigation strategies and demonstrates that a set of stochastic processes can largely account for exploration patterns in the Barnes maze.
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Affiliation(s)
- Ju-Young Lee
- Center for Functional Connectomics, Brain Science Institute, Korea Institute of Science and Technology (KIST)SeoulRepublic of Korea
- Division of Bio-Medical Science and Technology, KIST School, Korea University of Science and Technology (UST)SeoulRepublic of Korea
| | - Dahee Jung
- Center for Functional Connectomics, Brain Science Institute, Korea Institute of Science and Technology (KIST)SeoulRepublic of Korea
| | - Sebastien Royer
- Center for Functional Connectomics, Brain Science Institute, Korea Institute of Science and Technology (KIST)SeoulRepublic of Korea
- Division of Bio-Medical Science and Technology, KIST School, Korea University of Science and Technology (UST)SeoulRepublic of Korea
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8
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Sulpizio V, Teghil A, Pitzalis S, Boccia M. Common and specific activations supporting optic flow processing and navigation as revealed by a meta-analysis of neuroimaging studies. Brain Struct Funct 2024; 229:1021-1045. [PMID: 38592557 PMCID: PMC11147901 DOI: 10.1007/s00429-024-02790-8] [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: 11/27/2023] [Accepted: 03/12/2024] [Indexed: 04/10/2024]
Abstract
Optic flow provides useful information in service of spatial navigation. However, whether brain networks supporting these two functions overlap is still unclear. Here we used Activation Likelihood Estimation (ALE) to assess the correspondence between brain correlates of optic flow processing and spatial navigation and their specific neural activations. Since computational and connectivity evidence suggests that visual input from optic flow provides information mainly during egocentric navigation, we further tested the correspondence between brain correlates of optic flow processing and that of both egocentric and allocentric navigation. Optic flow processing shared activation with egocentric (but not allocentric) navigation in the anterior precuneus, suggesting its role in providing information about self-motion, as derived from the analysis of optic flow, in service of egocentric navigation. We further documented that optic flow perception and navigation are partially segregated into two functional and anatomical networks, i.e., the dorsal and the ventromedial networks. Present results point to a dynamic interplay between the dorsal and ventral visual pathways aimed at coordinating visually guided navigation in the environment.
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Affiliation(s)
- Valentina Sulpizio
- Department of Psychology, Sapienza University, Rome, Italy
- Department of Humanities, Education and Social Sciences, University of Molise, Campobasso, Italy
| | - Alice Teghil
- Department of Psychology, Sapienza University, Rome, Italy
- Department of Cognitive and Motor Rehabilitation and Neuroimaging, Santa Lucia Foundation (IRCCS Fondazione Santa Lucia), Rome, Italy
| | - Sabrina Pitzalis
- Department of Cognitive and Motor Rehabilitation and Neuroimaging, Santa Lucia Foundation (IRCCS Fondazione Santa Lucia), Rome, Italy
- Department of Movement, Human and Health Sciences, University of Rome ''Foro Italico'', Rome, Italy
| | - Maddalena Boccia
- Department of Psychology, Sapienza University, Rome, Italy.
- Department of Cognitive and Motor Rehabilitation and Neuroimaging, Santa Lucia Foundation (IRCCS Fondazione Santa Lucia), Rome, Italy.
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9
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Yang X, Cacucci F, Burgess N, Wills TJ, Chen G. Visual boundary cues suffice to anchor place and grid cells in virtual reality. Curr Biol 2024; 34:2256-2264.e3. [PMID: 38701787 DOI: 10.1016/j.cub.2024.04.026] [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: 10/17/2023] [Revised: 03/01/2024] [Accepted: 04/10/2024] [Indexed: 05/05/2024]
Abstract
The hippocampal formation contains neurons responsive to an animal's current location and orientation, which together provide the organism with a neural map of space.1,2,3 Spatially tuned neurons rely on external landmark cues and internally generated movement information to estimate position.4,5 An important class of landmark cue are the boundaries delimiting an environment, which can define place cell field position6,7 and stabilize grid cell firing.8 However, the precise nature of the sensory information used to detect boundaries remains unknown. We used 2-dimensional virtual reality (VR)9 to show that visual cues from elevated walls surrounding the environment are both sufficient and necessary to stabilize place and grid cell responses in VR, when only visual and self-motion cues are available. By contrast, flat boundaries formed by the edges of a textured floor did not stabilize place and grid cells, indicating only specific forms of visual boundary stabilize hippocampal spatial firing. Unstable grid cells retain internally coherent, hexagonally arranged firing fields, but these fields "drift" with respect to the virtual environment over periods >5 s. Optic flow from a virtual floor does not slow drift dynamics, emphasizing the importance of boundary-related visual information. Surprisingly, place fields are more stable close to boundaries even with floor and wall cues removed, suggesting invisible boundaries are inferred using the motion of a discrete, separate cue (a beacon signaling reward location). Subsets of place cells show allocentric directional tuning toward the beacon, with strength of tuning correlating with place field stability when boundaries are removed.
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Affiliation(s)
- Xiuting Yang
- School of Biological and Behavioural Sciences, Queen Mary University of London, 327 Mile End Road, London E1 4NS, UK
| | - Francesca Cacucci
- Department of Neuroscience, Physiology, and Pharmacology, University College London, Gower Street, London WC1E 6BT, UK
| | - Neil Burgess
- Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK; Queen Square Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK
| | - Thomas Joseph Wills
- Department of Cell and Developmental Biology, University College London, Gower Street, London WC1E 6BT, UK.
| | - Guifen Chen
- School of Biological and Behavioural Sciences, Queen Mary University of London, 327 Mile End Road, London E1 4NS, UK.
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10
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Zhang X, Cao Q, Gao K, Chen C, Cheng S, Li A, Zhou Y, Liu R, Hao J, Kropff E, Miao C. Multiplexed representation of others in the hippocampal CA1 subfield of female mice. Nat Commun 2024; 15:3702. [PMID: 38697969 PMCID: PMC11065873 DOI: 10.1038/s41467-024-47453-8] [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: 06/24/2023] [Accepted: 04/02/2024] [Indexed: 05/05/2024] Open
Abstract
Hippocampal place cells represent the position of a rodent within an environment. In addition, recent experiments show that the CA1 subfield of a passive observer also represents the position of a conspecific performing a spatial task. However, whether this representation is allocentric, egocentric or mixed is less clear. In this study we investigated the representation of others during free behavior and in a task where female mice learned to follow a conspecific for a reward. We found that most cells represent the position of others relative to self-position (social-vector cells) rather than to the environment, with a prevalence of purely egocentric coding modulated by context and mouse identity. Learning of a pursuit task improved the tuning of social-vector cells, but their number remained invariant. Collectively, our results suggest that the hippocampus flexibly codes the position of others in multiple coordinate systems, albeit favoring the self as a reference point.
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Affiliation(s)
- Xiang Zhang
- State key laboratory of Membrane biology, School of Life Sciences, Peking university, Beijing, 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Peking university, Beijing, 100871, China
| | - Qichen Cao
- State key laboratory of Membrane biology, School of Life Sciences, Peking university, Beijing, 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Peking university, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China
| | - Kai Gao
- State key laboratory of Membrane biology, School of Life Sciences, Peking university, Beijing, 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Peking university, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China
| | - Cong Chen
- State key laboratory of Membrane biology, School of Life Sciences, Peking university, Beijing, 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Peking university, Beijing, 100871, China
| | - Sihui Cheng
- State key laboratory of Membrane biology, School of Life Sciences, Peking university, Beijing, 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Peking university, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China
| | - Ang Li
- State key laboratory of Membrane biology, School of Life Sciences, Peking university, Beijing, 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Peking university, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China
| | - Yuqian Zhou
- State key laboratory of Membrane biology, School of Life Sciences, Peking university, Beijing, 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Peking university, Beijing, 100871, China
| | - Ruojin Liu
- State key laboratory of Membrane biology, School of Life Sciences, Peking university, Beijing, 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Peking university, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China
| | - Jun Hao
- State key laboratory of Membrane biology, School of Life Sciences, Peking university, Beijing, 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Peking university, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China
| | - Emilio Kropff
- Leloir Institute/IIBBA-CONICET, Buenos Aires, Argentina.
| | - Chenglin Miao
- State key laboratory of Membrane biology, School of Life Sciences, Peking university, Beijing, 100871, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking university, Beijing, 100871, China.
- Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China.
- Chinese Institute for Brain Research (CIBR), Beijing, China.
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11
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Herber CS, Pratt KJ, Shea JM, Villeda SA, Giocomo LM. Spatial Coding Dysfunction and Network Instability in the Aging Medial Entorhinal Cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.12.588890. [PMID: 38659809 PMCID: PMC11042240 DOI: 10.1101/2024.04.12.588890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Across species, spatial memory declines with age, possibly reflecting altered hippocampal and medial entorhinal cortex (MEC) function. However, the integrity of cellular and network-level spatial coding in aged MEC is unknown. Here, we leveraged in vivo electrophysiology to assess MEC function in young, middle-aged, and aged mice navigating virtual environments. In aged grid cells, we observed impaired stabilization of context-specific spatial firing, correlated with spatial memory deficits. Additionally, aged grid networks shifted firing patterns often but with poor alignment to context changes. Aged spatial firing was also unstable in an unchanging environment. In these same mice, we identified 458 genes differentially expressed with age in MEC, 61 of which had expression correlated with spatial firing stability. These genes were enriched among interneurons and related to synaptic transmission. Together, these findings identify coordinated transcriptomic, cellular, and network changes in MEC implicated in impaired spatial memory in aging.
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Affiliation(s)
- Charlotte S. Herber
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, 94305, USA
| | - Karishma J.B. Pratt
- Department of Anatomy, University of California San Francisco, 513 Parnassus Avenue, Box 0452, San Francisco, CA, 94143, USA
- These authors contributed equally
| | - Jeremy M. Shea
- Department of Anatomy, University of California San Francisco, 513 Parnassus Avenue, Box 0452, San Francisco, CA, 94143, USA
- These authors contributed equally
| | - Saul A. Villeda
- Department of Anatomy, University of California San Francisco, 513 Parnassus Avenue, Box 0452, San Francisco, CA, 94143, USA
- Bakar Aging Research Institute, San Francisco, CA, 94143, USA
| | - Lisa M. Giocomo
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, 94305, USA
- Lead contact
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12
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Zeng YF, Yang KX, Cui Y, Zhu XN, Li R, Zhang H, Wu DC, Stevens RC, Hu J, Zhou N. Conjunctive encoding of exploratory intentions and spatial information in the hippocampus. Nat Commun 2024; 15:3221. [PMID: 38622129 PMCID: PMC11018604 DOI: 10.1038/s41467-024-47570-4] [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: 05/02/2023] [Accepted: 04/02/2024] [Indexed: 04/17/2024] Open
Abstract
The hippocampus creates a cognitive map of the external environment by encoding spatial and self-motion-related information. However, it is unclear whether hippocampal neurons could also incorporate internal cognitive states reflecting an animal's exploratory intention, which is not driven by rewards or unexpected sensory stimuli. In this study, a subgroup of CA1 neurons was found to encode both spatial information and animals' investigatory intentions in male mice. These neurons became active before the initiation of exploration behaviors at specific locations and were nearly silent when the same fields were traversed without exploration. Interestingly, this neuronal activity could not be explained by object features, rewards, or mismatches in environmental cues. Inhibition of the lateral entorhinal cortex decreased the activity of these cells during exploration. Our findings demonstrate that hippocampal neurons may bridge external and internal signals, indicating a potential connection between spatial representation and intentional states in the construction of internal navigation systems.
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Affiliation(s)
- Yi-Fan Zeng
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Ke-Xin Yang
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Yilong Cui
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Xiao-Na Zhu
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Rui Li
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Hanqing Zhang
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
| | - Dong Chuan Wu
- Neuroscience and Brain Disease Center, Graduate Institute of Biomedical Sciences, China Medical University, Taichung City, 404333, Taiwan
- Translational Medicine Research Center, China Medical University Hospital, Taichung City, 404333, Taiwan
| | - Raymond C Stevens
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Ji Hu
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Ning Zhou
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China.
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13
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Waschke L, Kamp F, van den Elzen E, Krishna S, Lindenberger U, Rutishauser U, Garrett DD. Single-neuron spiking variability in hippocampus dynamically tracks sensory content during memory formation in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.02.23.529684. [PMID: 36865320 PMCID: PMC9980052 DOI: 10.1101/2023.02.23.529684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/03/2023]
Abstract
During memory formation, the hippocampus is presumed to represent the content of stimuli, but how it does so is unknown. Using computational modelling and human single-neuron recordings, we show that the more precisely hippocampal spiking variability tracks the composite features of each individual stimulus, the better those stimuli are later remembered. We propose that moment-to-moment spiking variability may provide a new window into how the hippocampus constructs memories from the building blocks of our sensory world.
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14
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Cao R, Bright IM, Howard MW. Ramping cells in rodent mPFC encode time to past and future events via real Laplace transform. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.13.580170. [PMID: 38405896 PMCID: PMC10888827 DOI: 10.1101/2024.02.13.580170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
In interval reproduction tasks, animals must remember the event starting the interval and anticipate the time of the planned response to terminate the interval. The interval reproduction task thus allows for studying both memory for the past and anticipation of the future. We analyzed previously published recordings from rodent mPFC (Henke et al., 2021) during an interval reproduction task and identified two cell groups by modeling their temporal receptive fields using hierarchical Bayesian models. The firing in the "past cells" group peaked at the start of the interval and relaxed exponentially back to baseline. The firing in the "future cells" group increased exponentially and peaked right before the planned action at the end of the interval. Contrary to the previous assumption that timing information in the brain has one or two time scales for a given interval, we found strong evidence for a continuous distribution of the exponential rate constants for both past and future cell populations. The real Laplace transformation of time predicts exponential firing with a continuous distribution of rate constants across the population. Therefore, the firing pattern of the past cells can be identified with the Laplace transform of time since the past event while the firing pattern of the future cells can be identified with the Laplace transform of time until the planned future event.
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Affiliation(s)
- Rui Cao
- Department of Psychological and Brain Sciences, Boston University
| | - Ian M Bright
- Department of Psychological and Brain Sciences, Boston University
| | - Marc W Howard
- Department of Psychological and Brain Sciences, Boston University
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15
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Grella SL, Donaldson TN. Contextual memory engrams, and the neuromodulatory influence of the locus coeruleus. Front Mol Neurosci 2024; 17:1342622. [PMID: 38375501 PMCID: PMC10875109 DOI: 10.3389/fnmol.2024.1342622] [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: 11/22/2023] [Accepted: 01/19/2024] [Indexed: 02/21/2024] Open
Abstract
Here, we review the basis of contextual memory at a conceptual and cellular level. We begin with an overview of the philosophical foundations of traversing space, followed by theories covering the material bases of contextual representations in the hippocampus (engrams), exploring functional characteristics of the cells and subfields within. Next, we explore various methodological approaches for investigating contextual memory engrams, emphasizing plasticity mechanisms. This leads us to discuss the role of neuromodulatory inputs in governing these dynamic changes. We then outline a recent hypothesis involving noradrenergic and dopaminergic projections from the locus coeruleus (LC) to different subregions of the hippocampus, in sculpting contextual representations, giving a brief description of the neuroanatomical and physiological properties of the LC. Finally, we examine how activity in the LC influences contextual memory processes through synaptic plasticity mechanisms to alter hippocampal engrams. Overall, we find that phasic activation of the LC plays an important role in promoting new learning and altering mnemonic processes at the behavioral and cellular level through the neuromodulatory influence of NE/DA in the hippocampus. These findings may provide insight into mechanisms of hippocampal remapping and memory updating, memory processes that are potentially dysregulated in certain psychiatric and neurodegenerative disorders.
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Affiliation(s)
- Stephanie L. Grella
- MNEME Lab, Department of Psychology, Program in Neuroscience, Loyola University Chicago, Chicago, IL, United States
| | - Tia N. Donaldson
- Systems Neuroscience and Behavior Lab, Department of Psychology, The University of New Mexico, Albuquerque, NM, United States
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16
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Sosa M, Plitt MH, Giocomo LM. Hippocampal sequences span experience relative to rewards. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.27.573490. [PMID: 38234842 PMCID: PMC10793396 DOI: 10.1101/2023.12.27.573490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Hippocampal place cells fire in sequences that span spatial environments and non-spatial modalities, suggesting that hippocampal activity can anchor to the most behaviorally salient aspects of experience. As reward is a highly salient event, we hypothesized that sequences of hippocampal activity can anchor to rewards. To test this, we performed two-photon imaging of hippocampal CA1 neurons as mice navigated virtual environments with changing hidden reward locations. When the reward moved, the firing fields of a subpopulation of cells moved to the same relative position with respect to reward, constructing a sequence of reward-relative cells that spanned the entire task structure. The density of these reward-relative sequences increased with task experience as additional neurons were recruited to the reward-relative population. Conversely, a largely separate subpopulation maintained a spatially-based place code. These findings thus reveal separate hippocampal ensembles can flexibly encode multiple behaviorally salient reference frames, reflecting the structure of the experience.
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Affiliation(s)
- Marielena Sosa
- Department of Neurobiology, Stanford University School of Medicine; Stanford, CA, USA
| | - Mark H. Plitt
- Department of Neurobiology, Stanford University School of Medicine; Stanford, CA, USA
- Present address: Department of Molecular and Cell Biology, University of California Berkeley; Berkeley, CA, USA
| | - Lisa M. Giocomo
- Department of Neurobiology, Stanford University School of Medicine; Stanford, CA, USA
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17
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Mussells Pires P, Zhang L, Parache V, Abbott LF, Maimon G. Converting an allocentric goal into an egocentric steering signal. Nature 2024; 626:808-818. [PMID: 38326612 PMCID: PMC10881393 DOI: 10.1038/s41586-023-07006-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 12/19/2023] [Indexed: 02/09/2024]
Abstract
Neuronal signals that are relevant for spatial navigation have been described in many species1-10. However, a circuit-level understanding of how such signals interact to guide navigational behaviour is lacking. Here we characterize a neuronal circuit in the Drosophila central complex that compares internally generated estimates of the heading and goal angles of the fly-both of which are encoded in world-centred (allocentric) coordinates-to generate a body-centred (egocentric) steering signal. Past work has suggested that the activity of EPG neurons represents the fly's moment-to-moment angular orientation, or heading angle, during navigation2,11. An animal's moment-to-moment heading angle, however, is not always aligned with its goal angle-that is, the allocentric direction in which it wishes to progress forward. We describe FC2 cells12, a second set of neurons in the Drosophila brain with activity that correlates with the fly's goal angle. Focal optogenetic activation of FC2 neurons induces flies to orient along experimenter-defined directions as they walk forward. EPG and FC2 neurons connect monosynaptically to a third neuronal class, PFL3 cells12,13. We found that individual PFL3 cells show conjunctive, spike-rate tuning to both the heading angle and the goal angle during goal-directed navigation. Informed by the anatomy and physiology of these three cell classes, we develop a model that explains how this circuit compares allocentric heading and goal angles to build an egocentric steering signal in the PFL3 output terminals. Quantitative analyses and optogenetic manipulations of PFL3 activity support the model. Finally, using a new navigational memory task, we show that flies expressing disruptors of synaptic transmission in subsets of PFL3 cells have a reduced ability to orient along arbitrary goal directions, with an effect size in quantitative accordance with the prediction of our model. The biological circuit described here reveals how two population-level allocentric signals are compared in the brain to produce an egocentric output signal that is appropriate for motor control.
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Affiliation(s)
- Peter Mussells Pires
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
| | - Lingwei Zhang
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
| | - Victoria Parache
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
| | - L F Abbott
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY, USA
| | - Gaby Maimon
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA.
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18
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Nagel K. A neural circuit for navigation keeps flies on target. Nature 2024; 626:718-720. [PMID: 38326416 DOI: 10.1038/d41586-024-00230-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
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19
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Bowler JC, Losonczy A. Direct cortical inputs to hippocampal area CA1 transmit complementary signals for goal-directed navigation. Neuron 2023; 111:4071-4085.e6. [PMID: 37816349 PMCID: PMC11490304 DOI: 10.1016/j.neuron.2023.09.013] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 07/14/2023] [Accepted: 09/13/2023] [Indexed: 10/12/2023]
Abstract
The subregions of the entorhinal cortex (EC) are conventionally thought to compute dichotomous representations for spatial processing, with the medial EC (MEC) providing a global spatial map and the lateral EC (LEC) encoding specific sensory details of experience. Yet, little is known about the specific types of information EC transmits downstream to the hippocampus. Here, we exploit in vivo sub-cellular imaging to record from EC axons in CA1 while mice perform navigational tasks in virtual reality (VR). We uncover distinct yet overlapping representations of task, location, and context in both MEC and LEC axons. MEC transmitted highly location- and context-specific codes; LEC inputs were biased by ongoing navigational goals. However, during tasks with reliable reward locations, the animals' position could be accurately decoded from either subregion. Our results revise the prevailing dogma about EC information processing, revealing novel ways spatial and non-spatial information is routed and combined upstream of the hippocampus.
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Affiliation(s)
- John C Bowler
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Doctoral Program in Neurobiology and Behavior, Columbia University, New York, NY 10027, USA.
| | - Attila Losonczy
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA.
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20
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Ohki T, Kunii N, Chao ZC. Efficient, continual, and generalized learning in the brain - neural mechanism of Mental Schema 2.0. Rev Neurosci 2023; 34:839-868. [PMID: 36960579 DOI: 10.1515/revneuro-2022-0137] [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: 11/15/2022] [Accepted: 02/26/2023] [Indexed: 03/25/2023]
Abstract
There has been tremendous progress in artificial neural networks (ANNs) over the past decade; however, the gap between ANNs and the biological brain as a learning device remains large. With the goal of closing this gap, this paper reviews learning mechanisms in the brain by focusing on three important issues in ANN research: efficiency, continuity, and generalization. We first discuss the method by which the brain utilizes a variety of self-organizing mechanisms to maximize learning efficiency, with a focus on the role of spontaneous activity of the brain in shaping synaptic connections to facilitate spatiotemporal learning and numerical processing. Then, we examined the neuronal mechanisms that enable lifelong continual learning, with a focus on memory replay during sleep and its implementation in brain-inspired ANNs. Finally, we explored the method by which the brain generalizes learned knowledge in new situations, particularly from the mathematical generalization perspective of topology. Besides a systematic comparison in learning mechanisms between the brain and ANNs, we propose "Mental Schema 2.0," a new computational property underlying the brain's unique learning ability that can be implemented in ANNs.
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Affiliation(s)
- Takefumi Ohki
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Tokyo 113-0033, Japan
| | - Naoto Kunii
- Department of Neurosurgery, The University of Tokyo, Tokyo 113-0033, Japan
| | - Zenas C Chao
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Tokyo 113-0033, Japan
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21
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Beetz MJ, El Jundi B. The neurobiology of the Monarch butterfly compass. CURRENT OPINION IN INSECT SCIENCE 2023; 60:101109. [PMID: 37660836 DOI: 10.1016/j.cois.2023.101109] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/17/2023] [Accepted: 08/28/2023] [Indexed: 09/05/2023]
Abstract
Monarch butterflies (Danaus plexippus) have become a superb model system to unravel how the tiny insect brain controls an impressive navigation behavior, such as long-distance migration. Moreover, the ability to compare the neural substrate between migratory and nonmigratory Monarch butterflies provides us with an attractive model to specifically study how the insect brain is adapted for migration. We here review our current progress on the neural substrate of spatial orientation in Monarch butterflies and how their spectacular annual migration might be controlled by their brain. We also discuss open research questions, the answers to which will provide important missing pieces to obtain a full picture of insect migration - from the perception of orientation cues to the neural control of migration.
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Affiliation(s)
- M Jerome Beetz
- Zoology II, Biocenter, University of Würzburg, Würzburg, Germany
| | - Basil El Jundi
- Animal Physiology, Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway.
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22
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Abstract
Knowing where you are and where you go is a prerequisite for planning a goal-directed journey. The discovery of spatially tuned neurons in the hippocampus and parahippocampal cortices provides a mechanism by which the brain pinpoints an animal’s own position in an environment. By contrast, how the brain encodes a remote navigational goal remained largely obscure until recently. In this review, we discuss algorithmic challenges and requirements for the brain to form a representation of a remote navigational goal at which an animal is not present. We then highlight a line of evidence that neurons in the orbitofrontal cortex (OFC) represent a goal location persistently while an animal navigates to this destination. Finally, we propose a new perspective of navigation research opened by this recently reported brain’s goal map.
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Affiliation(s)
- Raunak Basu
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Hiroshi T. Ito
- Max Planck Institute for Brain Research, Frankfurt am Main 60438, Germany
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23
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Williams HJ, Sridhar VH, Hurme E, Gall GE, Borrego N, Finerty GE, Couzin ID, Galizia CG, Dominy NJ, Rowland HM, Hauber ME, Higham JP, Strandburg-Peshkin A, Melin AD. Sensory collectives in natural systems. eLife 2023; 12:e88028. [PMID: 38019274 PMCID: PMC10686622 DOI: 10.7554/elife.88028] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 11/10/2023] [Indexed: 11/30/2023] Open
Abstract
Groups of animals inhabit vastly different sensory worlds, or umwelten, which shape fundamental aspects of their behaviour. Yet the sensory ecology of species is rarely incorporated into the emerging field of collective behaviour, which studies the movements, population-level behaviours, and emergent properties of animal groups. Here, we review the contributions of sensory ecology and collective behaviour to understanding how animals move and interact within the context of their social and physical environments. Our goal is to advance and bridge these two areas of inquiry and highlight the potential for their creative integration. To achieve this goal, we organise our review around the following themes: (1) identifying the promise of integrating collective behaviour and sensory ecology; (2) defining and exploring the concept of a 'sensory collective'; (3) considering the potential for sensory collectives to shape the evolution of sensory systems; (4) exploring examples from diverse taxa to illustrate neural circuits involved in sensing and collective behaviour; and (5) suggesting the need for creative conceptual and methodological advances to quantify 'sensescapes'. In the final section, (6) applications to biological conservation, we argue that these topics are timely, given the ongoing anthropogenic changes to sensory stimuli (e.g. via light, sound, and chemical pollution) which are anticipated to impact animal collectives and group-level behaviour and, in turn, ecosystem composition and function. Our synthesis seeks to provide a forward-looking perspective on how sensory ecologists and collective behaviourists can both learn from and inspire one another to advance our understanding of animal behaviour, ecology, adaptation, and evolution.
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Affiliation(s)
- Hannah J Williams
- Max Planck Institute of Animal BehaviorKonstanzGermany
- Centre for the Advanced Study of Collective Behaviour, University of KonstanzKonstanzGermany
- Biology Department, University of KonstanzKonstanzGermany
| | - Vivek H Sridhar
- Max Planck Institute of Animal BehaviorKonstanzGermany
- Centre for the Advanced Study of Collective Behaviour, University of KonstanzKonstanzGermany
- Biology Department, University of KonstanzKonstanzGermany
| | - Edward Hurme
- Max Planck Institute of Animal BehaviorKonstanzGermany
- Centre for the Advanced Study of Collective Behaviour, University of KonstanzKonstanzGermany
- Biology Department, University of KonstanzKonstanzGermany
| | - Gabriella E Gall
- Max Planck Institute of Animal BehaviorKonstanzGermany
- Centre for the Advanced Study of Collective Behaviour, University of KonstanzKonstanzGermany
- Biology Department, University of KonstanzKonstanzGermany
- Zukunftskolleg, University of KonstanzKonstanzGermany
| | | | | | - Iain D Couzin
- Max Planck Institute of Animal BehaviorKonstanzGermany
- Centre for the Advanced Study of Collective Behaviour, University of KonstanzKonstanzGermany
- Biology Department, University of KonstanzKonstanzGermany
| | - C Giovanni Galizia
- Biology Department, University of KonstanzKonstanzGermany
- Zukunftskolleg, University of KonstanzKonstanzGermany
| | - Nathaniel J Dominy
- Zukunftskolleg, University of KonstanzKonstanzGermany
- Department of Anthropology, Dartmouth CollegeHanoverUnited States
| | - Hannah M Rowland
- Max Planck Research Group Predators and Toxic Prey, Max Planck Institute for Chemical EcologyJenaGermany
| | - Mark E Hauber
- Department of Evolution, Ecology, and Behavior, School of Integrative Biology, University of Illinois at Urbana-ChampaignUrbana-ChampaignUnited States
| | - James P Higham
- Zukunftskolleg, University of KonstanzKonstanzGermany
- Department of Anthropology, New York UniversityNew YorkUnited States
| | - Ariana Strandburg-Peshkin
- Max Planck Institute of Animal BehaviorKonstanzGermany
- Centre for the Advanced Study of Collective Behaviour, University of KonstanzKonstanzGermany
- Biology Department, University of KonstanzKonstanzGermany
| | - Amanda D Melin
- Zukunftskolleg, University of KonstanzKonstanzGermany
- Department of Anthropology and Archaeology, University of CalgaryCalgaryCanada
- Alberta Children’s Hospital Research Institute, University of CalgaryCalgaryCanada
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24
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Lai C, Tanaka S, Harris TD, Lee AK. Volitional activation of remote place representations with a hippocampal brain-machine interface. Science 2023; 382:566-573. [PMID: 37917713 PMCID: PMC10683874 DOI: 10.1126/science.adh5206] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 09/22/2023] [Indexed: 11/04/2023]
Abstract
The hippocampus is critical for recollecting and imagining experiences. This is believed to involve voluntarily drawing from hippocampal memory representations of people, events, and places, including maplike representations of familiar environments. However, whether representations in such "cognitive maps" can be volitionally accessed is unknown. We developed a brain-machine interface to test whether rats can do so by controlling their hippocampal activity in a flexible, goal-directed, and model-based manner. We found that rats can efficiently navigate or direct objects to arbitrary goal locations within a virtual reality arena solely by activating and sustaining appropriate hippocampal representations of remote places. This provides insight into the mechanisms underlying episodic memory recall, mental simulation and planning, and imagination and opens up possibilities for high-level neural prosthetics that use hippocampal representations.
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Affiliation(s)
- Chongxi Lai
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Shinsuke Tanaka
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Timothy D. Harris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Albert K. Lee
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
- Howard Hughes Medical Institute and Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
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25
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Levy ERJ, Carrillo-Segura S, Park EH, Redman WT, Hurtado JR, Chung S, Fenton AA. A manifold neural population code for space in hippocampal coactivity dynamics independent of place fields. Cell Rep 2023; 42:113142. [PMID: 37742193 PMCID: PMC10842170 DOI: 10.1016/j.celrep.2023.113142] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 06/14/2023] [Accepted: 08/30/2023] [Indexed: 09/26/2023] Open
Abstract
Hippocampus place cell discharge is temporally unreliable across seconds and days, and place fields are multimodal, suggesting an "ensemble cofiring" spatial coding hypothesis with manifold dynamics that does not require reliable spatial tuning, in contrast to hypotheses based on place field (spatial tuning) stability. We imaged mouse CA1 (cornu ammonis 1) ensembles in two environments across three weeks to evaluate these coding hypotheses. While place fields "remap," being more distinct between than within environments, coactivity relationships generally change less. Decoding location and environment from 1-s ensemble location-specific activity is effective and improves with experience. Decoding environment from cell-pair coactivity relationships is also effective and improves with experience, even after removing place tuning. Discriminating environments from 1-s ensemble coactivity relies crucially on the cells with the most anti-coactive cell-pair relationships because activity is internally organized on a low-dimensional manifold of non-linear coactivity relationships that intermittently reregisters to environments according to the anti-cofiring subpopulation activity.
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Affiliation(s)
| | - Simón Carrillo-Segura
- Center for Neural Science, New York University, New York, NY 10003, USA; Graduate Program in Mechanical and Aerospace Engineering, Tandon School of Engineering, New York University, Brooklyn, NY 11201, USA
| | - Eun Hye Park
- Center for Neural Science, New York University, New York, NY 10003, USA
| | - William Thomas Redman
- Interdepartmental Graduate Program in Dynamical Neuroscience, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | | | - SueYeon Chung
- Center for Neural Science, New York University, New York, NY 10003, USA; Flatiron Institute Center for Computational Neuroscience, New York, NY 10010, USA
| | - André Antonio Fenton
- Center for Neural Science, New York University, New York, NY 10003, USA; Neuroscience Institute at the NYU Langone Medical Center, New York, NY 10016, USA.
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26
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Yuan M. Multiple Representations in geospatial databases, the brain's spatial cells, and deep learning algorithms. CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE 2023; 51:687-701. [PMID: 39429547 PMCID: PMC11486309 DOI: 10.1080/15230406.2023.2264758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 09/04/2023] [Indexed: 10/22/2024]
Abstract
Buttenfield (1988) pioneered research on multiple representations in the dawn of GIScience. Her efforts evoked inquiries into fundamental issues arising from the selective abstractions of infinite geographic complexity in spatial databases, cartography and application needs for varied geographic details. These fundamental issues posed ontological challenges (e.g., entity classification) and implementational complications (e.g., duplication and inconsistency) in geographic information systems (GIS). Expanding upon Buttenfield's line of research over the last three decades, this study reviewed multiple representations in spatial databases, spatial cognition, and deep learning. Initially perceived as a hindrance in GIS, multiple representations were found to offer new perspectives to encode and decipher geographic complexity. This paper commenced by acknowledging Buttenfield's pivotal contributions to multiple representations in GIScience. Subsequent discussions synthesized the literature to outline cognitive representations of space in the brain's hippocampal formation and feature representations in deep learning. By cross-referencing related concepts of multiple representations in GIScience, the brain's spatial cells, and machine learning algorithms, this review concluded that multiple representations facilitate learning geography for both humans and machines.
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Affiliation(s)
- May Yuan
- Geospatial Information Sciences, School of Economic, Political and Policy Sciences, The University of Texas at Dallas, Richardson, TX USA
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27
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Li CJ, Hui YQ, Zhang R, Zhou HY, Cai X, Lu L. A comparison of behavioral paradigms assessing spatial memory in tree shrews. Cereb Cortex 2023; 33:10303-10321. [PMID: 37642602 DOI: 10.1093/cercor/bhad283] [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: 06/04/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 08/31/2023] Open
Abstract
Impairments in spatial navigation in humans can be preclinical signs of Alzheimer's disease. Therefore, cognitive tests that monitor deficits in spatial memory play a crucial role in evaluating animal models with early stage Alzheimer's disease. While Chinese tree shrews (Tupaia belangeri) possess many features suitable for Alzheimer's disease modeling, behavioral tests for assessing spatial cognition in this species are lacking. Here, we established reward-based paradigms using the radial-arm maze and cheeseboard maze for tree shrews, and tested spatial memory in a group of 12 adult males in both tasks, along with a control water maze test, before and after bilateral lesions to the hippocampus, the brain region essential for spatial navigation. Tree shrews memorized target positions during training, and task performance improved gradually until reaching a plateau in all 3 mazes. However, spatial learning was compromised post-lesion in the 2 newly developed tasks, whereas memory retrieval was impaired in the water maze task. These results indicate that the cheeseboard task effectively detects impairments in spatial memory and holds potential for monitoring progressive cognitive decline in aged or genetically modified tree shrews that develop Alzheimer's disease-like symptoms. This study may facilitate the utilization of tree shrew models in Alzheimer's disease research.
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Affiliation(s)
- Cheng-Ji Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
| | - Yi-Qing Hui
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
| | - Rong Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
| | - Hai-Yang Zhou
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
| | - Xing Cai
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
| | - Li Lu
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
- National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
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28
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Beetz MJ, Kraus C, El Jundi B. Neural representation of goal direction in the monarch butterfly brain. Nat Commun 2023; 14:5859. [PMID: 37730704 PMCID: PMC10511513 DOI: 10.1038/s41467-023-41526-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 09/04/2023] [Indexed: 09/22/2023] Open
Abstract
Neural processing of a desired moving direction requires the continuous comparison between the current heading and the goal direction. While the neural basis underlying the current heading is well-studied, the coding of the goal direction remains unclear in insects. Here, we used tetrode recordings in tethered flying monarch butterflies to unravel how a goal direction is represented in the insect brain. While recording, the butterflies maintained robust goal directions relative to a virtual sun. By resetting their goal directions, we found neurons whose spatial tuning was tightly linked to the goal directions. Importantly, their tuning was unaffected when the butterflies changed their heading after compass perturbations, showing that these neurons specifically encode the goal direction. Overall, we here discovered invertebrate goal-direction neurons that share functional similarities to goal-direction cells reported in mammals. Our results give insights into the evolutionarily conserved principles of goal-directed spatial orientation in animals.
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Affiliation(s)
- M Jerome Beetz
- Zoology II, Biocenter, University of Würzburg, Würzburg, Germany.
| | - Christian Kraus
- Zoology II, Biocenter, University of Würzburg, Würzburg, Germany
- Animal Physiology, Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Basil El Jundi
- Zoology II, Biocenter, University of Würzburg, Würzburg, Germany
- Animal Physiology, Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway
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29
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Mehrotra D, Dubé L. Accounting for multiscale processing in adaptive real-world decision-making via the hippocampus. Front Neurosci 2023; 17:1200842. [PMID: 37732307 PMCID: PMC10508350 DOI: 10.3389/fnins.2023.1200842] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 08/25/2023] [Indexed: 09/22/2023] Open
Abstract
For adaptive real-time behavior in real-world contexts, the brain needs to allow past information over multiple timescales to influence current processing for making choices that create the best outcome as a person goes about making choices in their everyday life. The neuroeconomics literature on value-based decision-making has formalized such choice through reinforcement learning models for two extreme strategies. These strategies are model-free (MF), which is an automatic, stimulus-response type of action, and model-based (MB), which bases choice on cognitive representations of the world and causal inference on environment-behavior structure. The emphasis of examining the neural substrates of value-based decision making has been on the striatum and prefrontal regions, especially with regards to the "here and now" decision-making. Yet, such a dichotomy does not embrace all the dynamic complexity involved. In addition, despite robust research on the role of the hippocampus in memory and spatial learning, its contribution to value-based decision making is just starting to be explored. This paper aims to better appreciate the role of the hippocampus in decision-making and advance the successor representation (SR) as a candidate mechanism for encoding state representations in the hippocampus, separate from reward representations. To this end, we review research that relates hippocampal sequences to SR models showing that the implementation of such sequences in reinforcement learning agents improves their performance. This also enables the agents to perform multiscale temporal processing in a biologically plausible manner. Altogether, we articulate a framework to advance current striatal and prefrontal-focused decision making to better account for multiscale mechanisms underlying various real-world time-related concepts such as the self that cumulates over a person's life course.
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Affiliation(s)
- Dhruv Mehrotra
- Integrated Program in Neuroscience, McGill University, Montréal, QC, Canada
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Laurette Dubé
- Desautels Faculty of Management, McGill University, Montréal, QC, Canada
- McGill Center for the Convergence of Health and Economics, McGill University, Montréal, QC, Canada
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30
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Parra-Barrero E, Vijayabaskaran S, Seabrook E, Wiskott L, Cheng S. A map of spatial navigation for neuroscience. Neurosci Biobehav Rev 2023; 152:105200. [PMID: 37178943 DOI: 10.1016/j.neubiorev.2023.105200] [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: 01/25/2023] [Revised: 04/13/2023] [Accepted: 04/24/2023] [Indexed: 05/15/2023]
Abstract
Spatial navigation has received much attention from neuroscientists, leading to the identification of key brain areas and the discovery of numerous spatially selective cells. Despite this progress, our understanding of how the pieces fit together to drive behavior is generally lacking. We argue that this is partly caused by insufficient communication between behavioral and neuroscientific researchers. This has led the latter to under-appreciate the relevance and complexity of spatial behavior, and to focus too narrowly on characterizing neural representations of space-disconnected from the computations these representations are meant to enable. We therefore propose a taxonomy of navigation processes in mammals that can serve as a common framework for structuring and facilitating interdisciplinary research in the field. Using the taxonomy as a guide, we review behavioral and neural studies of spatial navigation. In doing so, we validate the taxonomy and showcase its usefulness in identifying potential issues with common experimental approaches, designing experiments that adequately target particular behaviors, correctly interpreting neural activity, and pointing to new avenues of research.
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Affiliation(s)
- Eloy Parra-Barrero
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany; International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Sandhiya Vijayabaskaran
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany
| | - Eddie Seabrook
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany
| | - Laurenz Wiskott
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany; International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Sen Cheng
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany; International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany.
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31
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Keshavarzi S, Velez-Fort M, Margrie TW. Cortical Integration of Vestibular and Visual Cues for Navigation, Visual Processing, and Perception. Annu Rev Neurosci 2023; 46:301-320. [PMID: 37428601 PMCID: PMC7616138 DOI: 10.1146/annurev-neuro-120722-100503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2023]
Abstract
Despite increasing evidence of its involvement in several key functions of the cerebral cortex, the vestibular sense rarely enters our consciousness. Indeed, the extent to which these internal signals are incorporated within cortical sensory representation and how they might be relied upon for sensory-driven decision-making, during, for example, spatial navigation, is yet to be understood. Recent novel experimental approaches in rodents have probed both the physiological and behavioral significance of vestibular signals and indicate that their widespread integration with vision improves both the cortical representation and perceptual accuracy of self-motion and orientation. Here, we summarize these recent findings with a focus on cortical circuits involved in visual perception and spatial navigation and highlight the major remaining knowledge gaps. We suggest that vestibulo-visual integration reflects a process of constant updating regarding the status of self-motion, and access to such information by the cortex is used for sensory perception and predictions that may be implemented for rapid, navigation-related decision-making.
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Affiliation(s)
- Sepiedeh Keshavarzi
- The Sainsbury Wellcome Centre for Neural Circuits and Behavior, University College London, London, United Kingdom;
| | - Mateo Velez-Fort
- The Sainsbury Wellcome Centre for Neural Circuits and Behavior, University College London, London, United Kingdom;
| | - Troy W Margrie
- The Sainsbury Wellcome Centre for Neural Circuits and Behavior, University College London, London, United Kingdom;
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32
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Duszkiewicz AJ, Rossato JI, Moreno A, Takeuchi T, Yamasaki M, Genzel L, Spooner P, Canals S, Morris RGM. Execution of new trajectories toward a stable goal without a functional hippocampus. Hippocampus 2023; 33:769-786. [PMID: 36798045 PMCID: PMC10946713 DOI: 10.1002/hipo.23497] [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: 06/19/2022] [Revised: 12/06/2022] [Accepted: 12/14/2022] [Indexed: 02/18/2023]
Abstract
The hippocampus is a critical component of a mammalian spatial navigation system, with the firing sequences of hippocampal place cells during sleep or immobility constituting a "replay" of an animal's past trajectories. A novel spatial navigation task recently revealed that such "replay" sequences of place fields can also prospectively map onto imminent new paths to a goal that occupies a stable location during each session. It was hypothesized that such "prospective replay" sequences may play a causal role in goal-directed navigation. In the present study, we query this putative causal role in finding only minimal effects of muscimol-induced inactivation of the dorsal and intermediate hippocampus on the same spatial navigation task. The concentration of muscimol used demonstrably inhibited hippocampal cell firing in vivo and caused a severe deficit in a hippocampal-dependent "episodic-like" spatial memory task in a watermaze. These findings call into question whether "prospective replay" of an imminent and direct path is actually necessary for its execution in certain navigational tasks.
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Affiliation(s)
- Adrian J. Duszkiewicz
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Department of PsychologyUniversity of StirlingStirlingScotlandUK
| | - Janine I. Rossato
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Department of PhysiologyUniversidade Federal do Rio Grande do NorteRio Grande do NorteBrazil
| | - Andrea Moreno
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Instituto de Neurociencias, CSIC‐UMHSan Juan de AlicanteSpain
- Department of Biomedicine, Danish Research Institute of Translational Neuroscience (DANDRITE)Aarhus UniversityAarhus CDenmark
| | - Tomonori Takeuchi
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Department of Biomedicine, Danish Research Institute of Translational Neuroscience (DANDRITE)Aarhus UniversityAarhus CDenmark
| | - Miwako Yamasaki
- Department of Anatomy, Graduate School of MedicineHokkaido UniversitySapporoJapan
| | - Lisa Genzel
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Donders Institute for Brain, Cognition, and BehaviourRadboud University and RadboudumcNijmegenThe Netherlands
| | - Patrick Spooner
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
| | - Santiago Canals
- Instituto de Neurociencias, CSIC‐UMHSan Juan de AlicanteSpain
| | - Richard G. M. Morris
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Instituto de Neurociencias, CSIC‐UMHSan Juan de AlicanteSpain
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33
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Han CZ, Donoghue T, Cao R, Kunz L, Wang S, Jacobs J. Using multi-task experiments to test principles of hippocampal function. Hippocampus 2023; 33:646-657. [PMID: 37042212 PMCID: PMC10249632 DOI: 10.1002/hipo.23540] [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: 03/23/2023] [Revised: 03/30/2023] [Accepted: 03/31/2023] [Indexed: 04/13/2023]
Abstract
Investigations of hippocampal functions have revealed a dizzying array of findings, from lesion-based behavioral deficits, to a diverse range of characterized neural activations, to computational models of putative functionality. Across these findings, there remains an ongoing debate about the core function of the hippocampus and the generality of its representation. Researchers have debated whether the hippocampus's primary role relates to the representation of space, the neural basis of (episodic) memory, or some more general computation that generalizes across various cognitive domains. Within these different perspectives, there is much debate about the nature of feature encodings. Here, we suggest that in order to evaluate hippocampal responses-investigating, for example, whether neuronal representations are narrowly targeted to particular tasks or if they subserve domain-general purposes-a promising research strategy may be the use of multi-task experiments, or more generally switching between multiple task contexts while recording from the same neurons in a given session. We argue that this strategy-when combined with explicitly defined theoretical motivations that guide experiment design-could be a fruitful approach to better understand how hippocampal representations support different behaviors. In doing so, we briefly review key open questions in the field, as exemplified by articles in this special issue, as well as previous work using multi-task experiments, and extrapolate to consider how this strategy could be further applied to probe fundamental questions about hippocampal function.
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Affiliation(s)
- Claire Z. Han
- Department of Biomedical Engineering, Columbia University
| | | | - Runnan Cao
- Department of Radiology, Washington University in St. Louis
| | - Lukas Kunz
- Department of Epileptology, University of Bonn Medical Center, Bonn, Germany
| | - Shuo Wang
- Department of Radiology, Washington University in St. Louis
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University
- Department of Neurological Surgery, Columbia University
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34
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Liu J, Chen D, Xiao X, Zhang H, Zhou W, Liang S, Kunz L, Schulze-Bonhage A, Axmacher N, Wang L. Multi-scale goal distance representations in human hippocampus during virtual spatial navigation. Curr Biol 2023; 33:2024-2033.e3. [PMID: 37148875 DOI: 10.1016/j.cub.2023.04.033] [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: 12/29/2022] [Revised: 03/17/2023] [Accepted: 04/14/2023] [Indexed: 05/08/2023]
Abstract
Goal-directed navigation relies on both coarse and fine-grained coding of spatial distance between the current position of a navigating subject and a goal destination. However, the neural signatures underlying goal distance coding remain poorly understood. Using intracranial EEG recordings from the hippocampus of drug-resistant epilepsy patients who performed a virtual spatial navigation task, we found that the right hippocampal theta power was significantly modulated by goal distance and decreased with goal proximity. This modulation varied along the hippocampal longitudinal axis such that theta power in the posterior hippocampus decreased more strongly with goal proximity. Similarly, neural timescale, reflecting the duration across which information can be maintained, increased gradually from the posterior to anterior hippocampus. Taken together, this study provides empirical evidence for multi-scale spatial representations of goal distance in the human hippocampus and links the hippocampal processing of spatial information to its intrinsic temporal dynamics.
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Affiliation(s)
- Jiali Liu
- CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Rd, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, 1 Yanqihu East Rd, Beijing 101408, China
| | - Dong Chen
- CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Rd, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, 1 Yanqihu East Rd, Beijing 101408, China
| | - Xue Xiao
- CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Rd, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, 1 Yanqihu East Rd, Beijing 101408, China
| | - Hui Zhang
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, Bochum 44801, Germany
| | - Wenjing Zhou
- Department of Epilepsy Center, Tsinghua University Yuquan Hospital, 5 Shijingshan Rd, Beijing 100040, China
| | - Shuli Liang
- Functional Neurosurgery Department, Beijing Children's Hospital, Capital Medical University, 56 Nanlishi Rd, Beijing 100045, China
| | - Lukas Kunz
- Department of Biomedical Engineering, Columbia University, 1210 Amsterdam Ave, New York, NY 10027, USA
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Str. 64, Freiburg im Breisgau 79106, Germany
| | - Nikolai Axmacher
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, Bochum 44801, Germany
| | - Liang Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Rd, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, 1 Yanqihu East Rd, Beijing 101408, China.
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35
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Omer DB, Las L, Ulanovsky N. Contextual and pure time coding for self and other in the hippocampus. Nat Neurosci 2023; 26:285-294. [PMID: 36585486 DOI: 10.1038/s41593-022-01226-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 10/31/2022] [Indexed: 12/31/2022]
Abstract
Navigation and episodic memory depend critically on representing temporal sequences. Hippocampal 'time cells' form temporal sequences, but it is unknown whether they represent context-dependent experience or time per se. Here we report on time cells in bat hippocampal area CA1, which, surprisingly, formed two distinct populations. One population of time cells generated different temporal sequences when the bat hung at different locations, thus conjunctively encoding spatial context and time-'contextual time cells'. A second population exhibited similar preferred times across different spatial contexts, thus purely encoding elapsed time. When examining neural responses after the landing moment of another bat, in a social imitation task, we found time cells that encoded temporal sequences aligned to the other's landing. We propose that these diverse time codes may support the perception of interval timing, episodic memory and temporal coordination between self and others.
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Affiliation(s)
- David B Omer
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel.
- Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Liora Las
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Nachum Ulanovsky
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel.
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36
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Linton P, Morgan MJ, Read JCA, Vishwanath D, Creem-Regehr SH, Domini F. New Approaches to 3D Vision. Philos Trans R Soc Lond B Biol Sci 2023; 378:20210443. [PMID: 36511413 PMCID: PMC9745878 DOI: 10.1098/rstb.2021.0443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/25/2022] [Indexed: 12/15/2022] Open
Abstract
New approaches to 3D vision are enabling new advances in artificial intelligence and autonomous vehicles, a better understanding of how animals navigate the 3D world, and new insights into human perception in virtual and augmented reality. Whilst traditional approaches to 3D vision in computer vision (SLAM: simultaneous localization and mapping), animal navigation (cognitive maps), and human vision (optimal cue integration) start from the assumption that the aim of 3D vision is to provide an accurate 3D model of the world, the new approaches to 3D vision explored in this issue challenge this assumption. Instead, they investigate the possibility that computer vision, animal navigation, and human vision can rely on partial or distorted models or no model at all. This issue also highlights the implications for artificial intelligence, autonomous vehicles, human perception in virtual and augmented reality, and the treatment of visual disorders, all of which are explored by individual articles. This article is part of a discussion meeting issue 'New approaches to 3D vision'.
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Affiliation(s)
- Paul Linton
- Presidential Scholars in Society and Neuroscience, Center for Science and Society, Columbia University, New York, NY 10027, USA
- Italian Academy for Advanced Studies in America, Columbia University, New York, NY 10027, USA
- Visual Inference Lab, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Michael J. Morgan
- Department of Optometry and Visual Sciences, City, University of London, Northampton Square, London EC1V 0HB, UK
| | - Jenny C. A. Read
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, Tyne & Wear NE2 4HH, UK
| | - Dhanraj Vishwanath
- School of Psychology and Neuroscience, University of St Andrews, St Andrews, Fife KY16 9JP, UK
| | | | - Fulvio Domini
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI 02912-9067, USA
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37
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Alexander AS, Place R, Starrett MJ, Chrastil ER, Nitz DA. Rethinking retrosplenial cortex: Perspectives and predictions. Neuron 2023; 111:150-175. [PMID: 36460006 DOI: 10.1016/j.neuron.2022.11.006] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 08/09/2022] [Accepted: 11/06/2022] [Indexed: 12/03/2022]
Abstract
The last decade has produced exciting new ideas about retrosplenial cortex (RSC) and its role in integrating diverse inputs. Here, we review the diversity in forms of spatial and directional tuning of RSC activity, temporal organization of RSC activity, and features of RSC interconnectivity with other brain structures. We find that RSC anatomy and dynamics are more consistent with roles in multiple sensorimotor and cognitive processes than with any isolated function. However, two more generalized categories of function may best characterize roles for RSC in complex cognitive processes: (1) shifting and relating perspectives for spatial cognition and (2) prediction and error correction for current sensory states with internal representations of the environment. Both functions likely take advantage of RSC's capacity to encode conjunctions among sensory, motor, and spatial mapping information streams. Together, these functions provide the scaffold for intelligent actions, such as navigation, perspective taking, interaction with others, and error detection.
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Affiliation(s)
- Andrew S Alexander
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Ryan Place
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA
| | - Michael J Starrett
- Department of Neurobiology & Behavior, University of California, Irvine, Irvine, CA 92697, USA
| | - Elizabeth R Chrastil
- Department of Neurobiology & Behavior, University of California, Irvine, Irvine, CA 92697, USA; Department of Cognitive Sciences, University of California, Irvine, Irvine, CA 92697, USA.
| | - Douglas A Nitz
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA.
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38
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Campagner D, Vale R, Tan YL, Iordanidou P, Pavón Arocas O, Claudi F, Stempel AV, Keshavarzi S, Petersen RS, Margrie TW, Branco T. A cortico-collicular circuit for orienting to shelter during escape. Nature 2023; 613:111-119. [PMID: 36544025 PMCID: PMC7614651 DOI: 10.1038/s41586-022-05553-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 11/10/2022] [Indexed: 12/24/2022]
Abstract
When faced with predatory threats, escape towards shelter is an adaptive action that offers long-term protection against the attacker. Animals rely on knowledge of safe locations in the environment to instinctively execute rapid shelter-directed escape actions1,2. Although previous work has identified neural mechanisms of escape initiation3,4, it is not known how the escape circuit incorporates spatial information to execute rapid flights along the most efficient route to shelter. Here we show that the mouse retrosplenial cortex (RSP) and superior colliculus (SC) form a circuit that encodes the shelter-direction vector and is specifically required for accurately orienting to shelter during escape. Shelter direction is encoded in RSP and SC neurons in egocentric coordinates and SC shelter-direction tuning depends on RSP activity. Inactivation of the RSP-SC pathway disrupts the orientation to shelter and causes escapes away from the optimal shelter-directed route, but does not lead to generic deficits in orientation or spatial navigation. We find that the RSP and SC are monosynaptically connected and form a feedforward lateral inhibition microcircuit that strongly drives the inhibitory collicular network because of higher RSP input convergence and synaptic integration efficiency in inhibitory SC neurons. This results in broad shelter-direction tuning in inhibitory SC neurons and sharply tuned excitatory SC neurons. These findings are recapitulated by a biologically constrained spiking network model in which RSP input to the local SC recurrent ring architecture generates a circular shelter-direction map. We propose that this RSP-SC circuit might be specialized for generating collicular representations of memorized spatial goals that are readily accessible to the motor system during escape, or more broadly, during navigation when the goal must be reached as fast as possible.
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Affiliation(s)
- Dario Campagner
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
- UCL Gatsby Computational Neuroscience Unit, London, UK
| | - Ruben Vale
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Yu Lin Tan
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
| | | | - Oriol Pavón Arocas
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
| | - Federico Claudi
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
| | - A Vanessa Stempel
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
| | | | | | - Troy W Margrie
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
| | - Tiago Branco
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK.
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39
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Scleidorovich P, Fellous JM, Weitzenfeld A. Adapting hippocampus multi-scale place field distributions in cluttered environments optimizes spatial navigation and learning. Front Comput Neurosci 2022; 16:1039822. [PMID: 36578316 PMCID: PMC9792172 DOI: 10.3389/fncom.2022.1039822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 11/21/2022] [Indexed: 12/14/2022] Open
Abstract
Extensive studies in rodents show that place cells in the hippocampus have firing patterns that are highly correlated with the animal's location in the environment and are organized in layers of increasing field sizes or scales along its dorsoventral axis. In this study, we use a spatial cognition model to show that different field sizes could be exploited to adapt the place cell representation to different environments according to their size and complexity. Specifically, we provide an in-depth analysis of how to distribute place cell fields according to the obstacles in cluttered environments to optimize learning time and path optimality during goal-oriented spatial navigation tasks. The analysis uses a reinforcement learning (RL) model that assumes that place cells allow encoding the state. While previous studies have suggested exploiting different field sizes to represent areas requiring different spatial resolutions, our work analyzes specific distributions that adapt the representation to the environment, activating larger fields in open areas and smaller fields near goals and subgoals (e.g., obstacle corners). In addition to assessing how the multi-scale representation may be exploited in spatial navigation tasks, our analysis and results suggest place cell representations that can impact the robotics field by reducing the total number of cells for path planning without compromising the quality of the paths learned.
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Affiliation(s)
- Pablo Scleidorovich
- Department of Computer Science and Engineering, University of South Florida, Tampa, FL, United States
| | - Jean-Marc Fellous
- Department of Psychology and Biomedical Engineering, University of Arizona, Tucson, AZ, United States
| | - Alfredo Weitzenfeld
- Department of Computer Science and Engineering, University of South Florida, Tampa, FL, United States
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40
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An artificial neural network explains how bats might use vision for navigation. Commun Biol 2022; 5:1325. [PMID: 36463311 PMCID: PMC9719490 DOI: 10.1038/s42003-022-04260-5] [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: 03/03/2022] [Accepted: 11/15/2022] [Indexed: 12/04/2022] Open
Abstract
Animals navigate using various sensory information to guide their movement. Miniature tracking devices now allow documenting animals' routes with high accuracy. Despite this detailed description of animal movement, how animals translate sensory information to movement is poorly understood. Recent machine learning advances now allow addressing this question with unprecedented statistical learning tools. We harnessed this power to address visual-based navigation in fruit bats. We used machine learning and trained a convolutional neural network to navigate along a bat's route using visual information that would have been available to the real bat, which we collected using a drone. We show that a simple feed-forward network can learn to guide the agent towards a goal based on sensory input, and can generalize its learning both in time and in space. Our analysis suggests how animals could potentially use visual input for navigation and which features might be useful for this purpose.
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41
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Gobbo F, Mitchell-Heggs R, Tse D, Al Omrani M, Spooner PA, Schultz SR, Morris RGM. Neuronal signature of spatial decision-making during navigation by freely moving rats by using calcium imaging. Proc Natl Acad Sci U S A 2022; 119:e2212152119. [PMID: 36279456 PMCID: PMC9636941 DOI: 10.1073/pnas.2212152119] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 09/20/2022] [Indexed: 11/22/2022] Open
Abstract
A challenge in spatial memory is understanding how place cell firing contributes to decision-making in navigation. A spatial recency task was created in which freely moving rats first became familiar with a spatial context over several days and thereafter were required to encode and then selectively recall one of three specific locations within it that was chosen to be rewarded that day. Calcium imaging was used to record from more than 1,000 cells in area CA1 of the hippocampus of five rats during the exploration, sample, and choice phases of the daily task. The key finding was that neural activity in the startbox rose steadily in the short period prior to entry to the arena and that this selective population cell firing was predictive of the daily changing goal on correct trials but not on trials in which the animals made errors. Single-cell and population activity measures converged on the idea that prospective coding of neural activity can be involved in navigational decision-making.
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Affiliation(s)
- Francesco Gobbo
- Centre for Discovery Brain Sciences, Edinburgh Neuroscience, The University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Rufus Mitchell-Heggs
- Centre for Discovery Brain Sciences, Edinburgh Neuroscience, The University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Department of Bioengineering and Centre for Neurotechnology, Imperial College London, London, SW7 2AZ, UK
| | - Dorothy Tse
- Centre for Discovery Brain Sciences, Edinburgh Neuroscience, The University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Department of Psychology, Edge Hill University, Ormskirk, L39 4QP, UK
| | - Meera Al Omrani
- MSc Program in Integrative Neuroscience, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Patrick A. Spooner
- Centre for Discovery Brain Sciences, Edinburgh Neuroscience, The University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Simon R. Schultz
- Department of Bioengineering and Centre for Neurotechnology, Imperial College London, London, SW7 2AZ, UK
| | - Richard G. M. Morris
- Centre for Discovery Brain Sciences, Edinburgh Neuroscience, The University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
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42
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Vijayabaskaran S, Cheng S. Navigation task and action space drive the emergence of egocentric and allocentric spatial representations. PLoS Comput Biol 2022; 18:e1010320. [PMID: 36315587 PMCID: PMC9648855 DOI: 10.1371/journal.pcbi.1010320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 11/10/2022] [Accepted: 10/18/2022] [Indexed: 11/12/2022] Open
Abstract
In general, strategies for spatial navigation could employ one of two spatial reference frames: egocentric or allocentric. Notwithstanding intuitive explanations, it remains unclear however under what circumstances one strategy is chosen over another, and how neural representations should be related to the chosen strategy. Here, we first use a deep reinforcement learning model to investigate whether a particular type of navigation strategy arises spontaneously during spatial learning without imposing a bias onto the model. We then examine the spatial representations that emerge in the network to support navigation. To this end, we study two tasks that are ethologically valid for mammals—guidance, where the agent has to navigate to a goal location fixed in allocentric space, and aiming, where the agent navigates to a visible cue. We find that when both navigation strategies are available to the agent, the solutions it develops for guidance and aiming are heavily biased towards the allocentric or the egocentric strategy, respectively, as one might expect. Nevertheless, the agent can learn both tasks using either type of strategy. Furthermore, we find that place-cell-like allocentric representations emerge preferentially in guidance when using an allocentric strategy, whereas egocentric vector representations emerge when using an egocentric strategy in aiming. We thus find that alongside the type of navigational strategy, the nature of the task plays a pivotal role in the type of spatial representations that emerge. Most species rely on navigation in space to find water, food, and mates, as well as to return home. When navigating, humans and animals can use one of two reference frames: one based on stable landmarks in the external environment, such as moving due north and then east, or one centered on oneself, such as moving forward and turning left. However, it remains unclear how these reference frames are chosen and interact in navigation tasks, as well as how they are supported by representations in the brain. We therefore modeled two navigation tasks that would each benefit from using one of these reference frames, and trained an artificial agent to learn to solve them through trial and error. Our results show that when given the choice, the agent leveraged the appropriate reference frame to solve the task, but surprisingly could also use the other reference frame when constrained to do so. We also show that the representations that emerge to enable the agent to solve the tasks exist on a spectrum, and are more complex than commonly thought. These representations reflect both the task and reference frame being used, and provide useful insights for the design of experimental tasks to study the use of navigational strategies.
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Affiliation(s)
| | - Sen Cheng
- Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany
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43
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Noel JP, Balzani E, Avila E, Lakshminarasimhan KJ, Bruni S, Alefantis P, Savin C, Angelaki DE. Coding of latent variables in sensory, parietal, and frontal cortices during closed-loop virtual navigation. eLife 2022; 11:e80280. [PMID: 36282071 PMCID: PMC9668339 DOI: 10.7554/elife.80280] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 10/24/2022] [Indexed: 11/13/2022] Open
Abstract
We do not understand how neural nodes operate and coordinate within the recurrent action-perception loops that characterize naturalistic self-environment interactions. Here, we record single-unit spiking activity and local field potentials (LFPs) simultaneously from the dorsomedial superior temporal area (MSTd), parietal area 7a, and dorsolateral prefrontal cortex (dlPFC) as monkeys navigate in virtual reality to 'catch fireflies'. This task requires animals to actively sample from a closed-loop virtual environment while concurrently computing continuous latent variables: (i) the distance and angle travelled (i.e., path integration) and (ii) the distance and angle to a memorized firefly location (i.e., a hidden spatial goal). We observed a patterned mixed selectivity, with the prefrontal cortex most prominently coding for latent variables, parietal cortex coding for sensorimotor variables, and MSTd most often coding for eye movements. However, even the traditionally considered sensory area (i.e., MSTd) tracked latent variables, demonstrating path integration and vector coding of hidden spatial goals. Further, global encoding profiles and unit-to-unit coupling (i.e., noise correlations) suggested a functional subnetwork composed by MSTd and dlPFC, and not between these and 7a, as anatomy would suggest. We show that the greater the unit-to-unit coupling between MSTd and dlPFC, the more the animals' gaze position was indicative of the ongoing location of the hidden spatial goal. We suggest this MSTd-dlPFC subnetwork reflects the monkeys' natural and adaptive task strategy wherein they continuously gaze toward the location of the (invisible) target. Together, these results highlight the distributed nature of neural coding during closed action-perception loops and suggest that fine-grain functional subnetworks may be dynamically established to subserve (embodied) task strategies.
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Affiliation(s)
- Jean-Paul Noel
- Center for Neural Science, New York UniversityNew York CityUnited States
| | - Edoardo Balzani
- Center for Neural Science, New York UniversityNew York CityUnited States
| | - Eric Avila
- Center for Neural Science, New York UniversityNew York CityUnited States
| | - Kaushik J Lakshminarasimhan
- Center for Neural Science, New York UniversityNew York CityUnited States
- Center for Theoretical Neuroscience, Columbia UniversityNew YorkUnited States
| | - Stefania Bruni
- Center for Neural Science, New York UniversityNew York CityUnited States
| | - Panos Alefantis
- Center for Neural Science, New York UniversityNew York CityUnited States
| | - Cristina Savin
- Center for Neural Science, New York UniversityNew York CityUnited States
| | - Dora E Angelaki
- Center for Neural Science, New York UniversityNew York CityUnited States
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44
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Uncovering the Secrets of the Concept of Place in Cognitive Maps Aided by Artificial Intelligence. Cognit Comput 2022. [DOI: 10.1007/s12559-022-10064-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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45
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Whittington JCR, McCaffary D, Bakermans JJW, Behrens TEJ. How to build a cognitive map. Nat Neurosci 2022; 25:1257-1272. [PMID: 36163284 DOI: 10.1038/s41593-022-01153-y] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 07/25/2022] [Indexed: 11/08/2022]
Abstract
Learning and interpreting the structure of the environment is an innate feature of biological systems, and is integral to guiding flexible behaviors for evolutionary viability. The concept of a cognitive map has emerged as one of the leading metaphors for these capacities, and unraveling the learning and neural representation of such a map has become a central focus of neuroscience. In recent years, many models have been developed to explain cellular responses in the hippocampus and other brain areas. Because it can be difficult to see how these models differ, how they relate and what each model can contribute, this Review aims to organize these models into a clear ontology. This ontology reveals parallels between existing empirical results, and implies new approaches to understand hippocampal-cortical interactions and beyond.
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Affiliation(s)
- James C R Whittington
- Department of Applied Physics, Stanford University, Stanford, CA, USA.
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
| | - David McCaffary
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Jacob J W Bakermans
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Timothy E J Behrens
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
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46
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Ide K, Takahashi S. A Review of Neurologgers for Extracellular Recording of Neuronal Activity in the Brain of Freely Behaving Wild Animals. MICROMACHINES 2022; 13:1529. [PMID: 36144152 PMCID: PMC9502354 DOI: 10.3390/mi13091529] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 09/12/2022] [Accepted: 09/15/2022] [Indexed: 06/16/2023]
Abstract
Simultaneous monitoring of animal behavior and neuronal activity in the brain enables us to examine the neural underpinnings of behaviors. Conventionally, the neural activity data are buffered, amplified, multiplexed, and then converted from analog to digital in the head-stage amplifier, following which they are transferred to a storage server via a cable. Such tethered recording systems, intended for indoor use, hamper the free movement of animals in three-dimensional (3D) space as well as in large spaces or underwater, making it difficult to target wild animals active under natural conditions; it also presents challenges in realizing its applications to humans, such as the Brain-Machine Interfaces (BMI). Recent advances in micromachine technology have established a wireless logging device called a neurologger, which directly stores neural activity on ultra-compact memory media. The advent of the neurologger has triggered the examination of the neural correlates of 3D flight, underwater swimming of wild animals, and translocation experiments in the wild. Examples of the use of neurologgers will provide an insight into understanding the neural underpinnings of behaviors in the natural environment and contribute to the practical application of BMI. Here we outline the monitoring of the neural underpinnings of flying and swimming behaviors using neurologgers. We then focus on neuroethological findings and end by discussing their future perspectives.
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47
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de Cothi W, Nyberg N, Griesbauer EM, Ghanamé C, Zisch F, Lefort JM, Fletcher L, Newton C, Renaudineau S, Bendor D, Grieves R, Duvelle É, Barry C, Spiers HJ. Predictive maps in rats and humans for spatial navigation. Curr Biol 2022; 32:3676-3689.e5. [PMID: 35863351 PMCID: PMC9616735 DOI: 10.1016/j.cub.2022.06.090] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 05/19/2022] [Accepted: 06/29/2022] [Indexed: 11/25/2022]
Abstract
Much of our understanding of navigation comes from the study of individual species, often with specific tasks tailored to those species. Here, we provide a novel experimental and analytic framework integrating across humans, rats, and simulated reinforcement learning (RL) agents to interrogate the dynamics of behavior during spatial navigation. We developed a novel open-field navigation task ("Tartarus maze") requiring dynamic adaptation (shortcuts and detours) to frequently changing obstructions on the path to a hidden goal. Humans and rats were remarkably similar in their trajectories. Both species showed the greatest similarity to RL agents utilizing a "successor representation," which creates a predictive map. Humans also displayed trajectory features similar to model-based RL agents, which implemented an optimal tree-search planning procedure. Our results help refine models seeking to explain mammalian navigation in dynamic environments and highlight the utility of modeling the behavior of different species to uncover the shared mechanisms that support behavior.
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Affiliation(s)
- William de Cothi
- Department of Cell and Developmental Biology, University College London, London, UK; Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK.
| | - Nils Nyberg
- Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK
| | - Eva-Maria Griesbauer
- Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK
| | - Carole Ghanamé
- Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK
| | - Fiona Zisch
- Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK; The Bartlett School of Architecture, University College London, London, UK
| | - Julie M Lefort
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Lydia Fletcher
- Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK
| | - Coco Newton
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Sophie Renaudineau
- Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK
| | - Daniel Bendor
- Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK
| | - Roddy Grieves
- Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Éléonore Duvelle
- Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Caswell Barry
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Hugo J Spiers
- Institute of Behavioral Neuroscience, Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, UK.
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48
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Yu Y, Setogawa T, Matsumoto J, Nishimaru H, Nishijo H. Neural basis of topographical disorientation in the primate posterior cingulate gyrus based on a labeled graph. AIMS Neurosci 2022; 9:373-394. [PMID: 36329903 PMCID: PMC9581735 DOI: 10.3934/neuroscience.2022021] [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: 06/23/2022] [Revised: 08/29/2022] [Accepted: 09/06/2022] [Indexed: 11/18/2022] Open
Abstract
Patients with lesions in the posterior cingulate gyrus (PCG), including the retrosplenial cortex (RSC) and posterior cingulate cortex (PCC), cannot navigate in familiar environments, nor draw routes on a 2D map of the familiar environments. This suggests that the topographical knowledge of the environments (i.e., cognitive map) to find the right route to a goal is represented in the PCG, and the patients lack such knowledge. However, theoretical backgrounds in neuronal levels for these symptoms in primates are unclear. Recent behavioral studies suggest that human spatial knowledge is constructed based on a labeled graph that consists of topological connections (edges) between places (nodes), where local metric information, such as distances between nodes (edge weights) and angles between edges (node labels), are incorporated. We hypothesize that the population neural activity in the PCG may represent such knowledge based on a labeled graph to encode routes in both 3D environments and 2D maps. Since no previous data are available to test the hypothesis, we recorded PCG neuronal activity from a monkey during performance of virtual navigation and map drawing-like tasks. The results indicated that most PCG neurons responded differentially to spatial parameters of the environments, including the place, head direction, and reward delivery at specific reward areas. The labeled graph-based analyses of the data suggest that the population activity of the PCG neurons represents the distance traveled, locations, movement direction, and navigation routes in the 3D and 2D virtual environments. These results support the hypothesis and provide a neuronal basis for the labeled graph-based representation of a familiar environment, consistent with PCG functions inferred from the human clinicopathological studies.
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Affiliation(s)
- Yang Yu
- System Emotional Science, Faculty of Medicine, University of Toyama, Toyama, Japan
| | - Tsuyoshi Setogawa
- System Emotional Science, Faculty of Medicine, University of Toyama, Toyama, Japan
- Research Center for Idling Brain Science (RCIBS), University of Toyama, Toyama, Japan
| | - Jumpei Matsumoto
- System Emotional Science, Faculty of Medicine, University of Toyama, Toyama, Japan
- Research Center for Idling Brain Science (RCIBS), University of Toyama, Toyama, Japan
| | - Hiroshi Nishimaru
- System Emotional Science, Faculty of Medicine, University of Toyama, Toyama, Japan
- Research Center for Idling Brain Science (RCIBS), University of Toyama, Toyama, Japan
| | - Hisao Nishijo
- System Emotional Science, Faculty of Medicine, University of Toyama, Toyama, Japan
- Research Center for Idling Brain Science (RCIBS), University of Toyama, Toyama, Japan
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49
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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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50
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Sarel A, Palgi S, Blum D, Aljadeff J, Las L, Ulanovsky N. Natural switches in behaviour rapidly modulate hippocampal coding. Nature 2022; 609:119-127. [PMID: 36002570 PMCID: PMC9433324 DOI: 10.1038/s41586-022-05112-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 07/14/2022] [Indexed: 11/30/2022]
Abstract
Throughout their daily lives, animals and humans often switch between different behaviours. However, neuroscience research typically studies the brain while the animal is performing one behavioural task at a time, and little is known about how brain circuits represent switches between different behaviours. Here we tested this question using an ethological setting: two bats flew together in a long 135 m tunnel, and switched between navigation when flying alone (solo) and collision avoidance as they flew past each other (cross-over). Bats increased their echolocation click rate before each cross-over, indicating attention to the other bat1–9. Hippocampal CA1 neurons represented the bat’s own position when flying alone (place coding10–14). Notably, during cross-overs, neurons switched rapidly to jointly represent the interbat distance by self-position. This neuronal switch was very fast—as fast as 100 ms—which could be revealed owing to the very rapid natural behavioural switch. The neuronal switch correlated with the attention signal, as indexed by echolocation. Interestingly, the different place fields of the same neuron often exhibited very different tuning to interbat distance, creating a complex non-separable coding of position by distance. Theoretical analysis showed that this complex representation yields more efficient coding. Overall, our results suggest that during dynamic natural behaviour, hippocampal neurons can rapidly switch their core computation to represent the relevant behavioural variables, supporting behavioural flexibility. During rapid behavioural switches in flying bats, hippocampal neurons can rapidly switch their core computation to represent the relevant behavioural variables, supporting behavioural flexibility.
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Affiliation(s)
- Ayelet Sarel
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Shaked Palgi
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Dan Blum
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Johnatan Aljadeff
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel.,Department of Neurobiology, University of California, San Diego, CA, USA
| | - Liora Las
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel.
| | - Nachum Ulanovsky
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel.
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