1
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Zhang M, Livi A, Carter M, Schoknecht H, Burkhalter A, Holy TE, Padoa-Schioppa C. The representation of decision variables in orbitofrontal cortex is longitudinally stable. Cell Rep 2024; 43:114772. [PMID: 39331504 DOI: 10.1016/j.celrep.2024.114772] [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: 03/03/2024] [Revised: 07/31/2024] [Accepted: 09/02/2024] [Indexed: 09/29/2024] Open
Abstract
The computation and comparison of subjective values underlying economic choices rely on the orbitofrontal cortex (OFC). In this area, distinct groups of neurons encode the value of individual options, the binary choice outcome, and the chosen value. These variables capture both the choice input and the choice output, suggesting that the cell groups found in the OFC constitute the building blocks of a decision circuit. Here, we show that this neural circuit is longitudinally stable. Using two-photon calcium imaging, we record from the OFC of mice engaged in a juice-choice task. Imaging of individual cells continues for up to 40 weeks. For each cell and each session pair, we compare activity profiles using cosine similarity, and we assess whether the neuron encodes the same variable in both sessions. We find a high degree of stability and a modest representational drift. Quantitative estimates indicate that this drift would not randomize the circuit within the animal's lifetime.
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Affiliation(s)
- Manning Zhang
- Department of Neuroscience, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Alessandro Livi
- Department of Neuroscience, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Mary Carter
- Department of Neuroscience, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Heide Schoknecht
- Department of Neuroscience, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Andreas Burkhalter
- Department of Neuroscience, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Timothy E Holy
- Department of Neuroscience, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Camillo Padoa-Schioppa
- Department of Neuroscience, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Economics, Washington University in St. Louis, St. Louis, MO 63110, USA.
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2
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Shi J, Nutkovich B, Kushinsky D, Rao BY, Herrlinger SA, Tsivourakis E, Mihaila TS, Paredes MEC, Malina KCK, O’Toole CK, Yong HC, Sanner BM, Xie A, Varol E, Losonczy A, Spiegel I. 2P-NucTag: on-demand phototagging for molecular analysis of functionally identified cortical neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.21.586118. [PMID: 38585980 PMCID: PMC10996538 DOI: 10.1101/2024.03.21.586118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Neural circuits are characterized by genetically and functionally diverse cell types. A mechanistic understanding of circuit function is predicated on linking the genetic and physiological properties of individual neurons. However, it remains highly challenging to map the transcriptional properties to functionally heterogeneous neuronal subtypes in mammalian cortical circuits in vivo. Here, we introduce a high-throughput two-photon nuclear phototagging (2P-NucTag) approach optimized for on-demand and indelible labeling of single neurons via a photoactivatable red fluorescent protein following in vivo functional characterization in behaving mice. We demonstrate the utility of this function-forward pipeline by selectively labeling and transcriptionally profiling previously inaccessible 'place' and 'silent' cells in the mouse hippocampus. Our results reveal unexpected differences in gene expression between these hippocampal pyramidal neurons with distinct spatial coding properties. Thus, 2P-NucTag opens a new way to uncover the molecular principles that govern the functional organization of neural circuits.
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Affiliation(s)
- Jingcheng Shi
- Department of Neuroscience, Columbia University, New York, NY, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
- Doctoral Program in Neurobiology and Behavior, Columbia University, New York, NY, United States
| | - Boaz Nutkovich
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot, Israel
| | - Dahlia Kushinsky
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot, Israel
| | - Bovey Y. Rao
- Department of Neuroscience, Columbia University, New York, NY, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
- Doctoral Program in Neurobiology and Behavior, Columbia University, New York, NY, United States
| | - Stephanie A. Herrlinger
- Department of Neuroscience, Columbia University, New York, NY, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Emmanouil Tsivourakis
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot, Israel
| | - Tiberiu S. Mihaila
- Department of Neuroscience, Columbia University, New York, NY, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Margaret E. Conde Paredes
- Department of Neuroscience, Columbia University, New York, NY, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
- Doctoral Program in Neurobiology and Behavior, Columbia University, New York, NY, United States
- Tandon School of Engineering, New York University, New York, NY, United States
| | - Katayun Cohen-Kashi Malina
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot, Israel
| | - Cliodhna K. O’Toole
- Department of Neuroscience, Columbia University, New York, NY, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Hyun Choong Yong
- Department of Neuroscience, Columbia University, New York, NY, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Brynn M. Sanner
- Department of Neuroscience, Columbia University, New York, NY, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Angel Xie
- Department of Neuroscience, Columbia University, New York, NY, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Erdem Varol
- Tandon School of Engineering, New York University, New York, NY, United States
| | - Attila Losonczy
- Department of Neuroscience, Columbia University, New York, NY, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Ivo Spiegel
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
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3
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Guerreiro IC, Clopath C. Memory's gatekeeper: The role of PFC in the encoding of congruent events. Proc Natl Acad Sci U S A 2024; 121:e2403648121. [PMID: 39018188 PMCID: PMC11287283 DOI: 10.1073/pnas.2403648121] [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: 02/21/2024] [Accepted: 06/17/2024] [Indexed: 07/19/2024] Open
Abstract
Theoretical models conventionally portray the consolidation of memories as a slow process that unfolds during sleep. According to the classical Complementary Learning Systems theory, the hippocampus (HPC) rapidly changes its connectivity during wakefulness to encode ongoing events and create memory ensembles that are later transferred to the prefrontal cortex (PFC) during sleep. However, recent experimental studies challenge this notion by showing that new information consistent with prior knowledge can be rapidly consolidated in PFC during wakefulness and that PFC lesions disrupt the encoding of congruent events in the HPC. The contributions of the PFC to memory encoding have therefore largely been overlooked. Moreover, most theoretical frameworks assume random and uncorrelated patterns representing memories, disregarding the correlations between our experiences. To address these shortcomings, we developed a HPC-PFC network model that simulates interactions between the HPC and PFC during the encoding of a memory (awake stage), and subsequent consolidation (sleeping stage) to examine the contributions of each region to the consolidation of novel and congruent memories. Our results show that the PFC network uses stored memory "schemas" consolidated during previous experiences to identify inputs that evoke congruent patterns of activity, quickly integrate it into its network, and gate which components are encoded in the HPC. More specifically, the PFC uses GABAergic long-range projections to inhibit HPC neurons representing input components correlated with a previously stored memory "schema," eliciting sparse hippocampal activity during exposure to congruent events, as it has been experimentally observed.
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Affiliation(s)
- Inês C. Guerreiro
- Department of Bioengineering, Imperial College London, LondonSW7 2AZ, United Kingdom
| | - Claudia Clopath
- Department of Bioengineering, Imperial College London, LondonSW7 2AZ, United Kingdom
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4
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Chen Z, Padmanabhan K. Adult-neurogenesis allows for representational stability and flexibility in early olfactory system. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.02.601573. [PMID: 39005290 PMCID: PMC11244980 DOI: 10.1101/2024.07.02.601573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
In the early olfactory system, adult-neurogenesis, a process of neuronal replacement results in the continuous reorganization of synaptic connections and network architecture throughout the animal's life. This poses a critical challenge: How does the olfactory system maintain stable representations of odors and therefore allow for stable sensory perceptions amidst this ongoing circuit instability? Utilizing a detailed spiking network model of early olfactory circuits, we uncovered dual roles for adult-neurogenesis: one that both supports representational stability to faithfully encode odor information and also one that facilitates plasticity to allow for learning and adaptation. In the main olfactory bulb, adult-neurogenesis affects neural codes in individual mitral and tufted cells but preserves odor representations at the neuronal population level. By contrast, in the olfactory piriform cortex, both individual cell responses and overall population dynamics undergo progressive changes due to adult-neurogenesis. This leads to representational drift, a gradual alteration in sensory perception. Both processes are dynamic and depend on experience such that repeated exposure to specific odors reduces the drift due to adult-neurogenesis; thus, when the odor environment is stable over the course of adult-neurogenesis, it is neurogenesis that actually allows the representations to remain stable in piriform cortex; when those olfactory environments change, adult-neurogenesis allows the cortical representations to track environmental change. Whereas perceptual stability and plasticity due to learning are often thought of as two distinct, often contradictory processing in neuronal coding, we find that adult-neurogenesis serves as a shared mechanism for both. In this regard, the quixotic presence of adult-neurogenesis in the mammalian olfactory bulb that has been the focus of considerable debate in chemosensory neuroscience may be the mechanistic underpinning behind an array of complex computations.
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Affiliation(s)
- Zhen Chen
- Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY14627
| | - Krishnan Padmanabhan
- Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642
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5
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Fenton AA. Remapping revisited: how the hippocampus represents different spaces. Nat Rev Neurosci 2024; 25:428-448. [PMID: 38714834 DOI: 10.1038/s41583-024-00817-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2024] [Indexed: 05/25/2024]
Abstract
The representation of distinct spaces by hippocampal place cells has been linked to changes in their place fields (the locations in the environment where the place cells discharge strongly), a phenomenon that has been termed 'remapping'. Remapping has been assumed to be accompanied by the reorganization of subsecond cofiring relationships among the place cells, potentially maximizing hippocampal information coding capacity. However, several observations challenge this standard view. For example, place cells exhibit mixed selectivity, encode non-positional variables, can have multiple place fields and exhibit unreliable discharge in fixed environments. Furthermore, recent evidence suggests that, when measured at subsecond timescales, the moment-to-moment cofiring of a pair of cells in one environment is remarkably similar in another environment, despite remapping. Here, I propose that remapping is a misnomer for the changes in place fields across environments and suggest instead that internally organized manifold representations of hippocampal activity are actively registered to different environments to enable navigation, promote memory and organize knowledge.
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Affiliation(s)
- André A Fenton
- Center for Neural Science, New York University, New York, NY, USA.
- Neuroscience Institute at the NYU Langone Medical Center, New York, NY, USA.
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6
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Uytiepo M, Zhu Y, Bushong E, Polli F, Chou K, Zhao E, Kim C, Luu D, Chang L, Quach T, Haberl M, Patapoutian L, Beutter E, Zhang W, Dong B, McCue E, Ellisman M, Maximov A. Synaptic architecture of a memory engram in the mouse hippocampus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.23.590812. [PMID: 38712256 PMCID: PMC11071366 DOI: 10.1101/2024.04.23.590812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Memory engrams are formed through experience-dependent remodeling of neural circuits, but their detailed architectures have remained unresolved. Using 3D electron microscopy, we performed nanoscale reconstructions of the hippocampal CA3-CA1 pathway following chemogenetic labeling of cellular ensembles with a remote history of correlated excitation during associative learning. Projection neurons involved in memory acquisition expanded their connectomes via multi-synaptic boutons without altering the numbers and spatial arrangements of individual axonal terminals and dendritic spines. This expansion was driven by presynaptic activity elicited by specific negative valence stimuli, regardless of the co-activation state of postsynaptic partners. The rewiring of initial ensembles representing an engram coincided with local, input-specific changes in the shapes and organelle composition of glutamatergic synapses, reflecting their weights and potential for further modifications. Our findings challenge the view that the connectivity among neuronal substrates of memory traces is governed by Hebbian mechanisms, and offer a structural basis for representational drifts.
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7
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Tamboli S, Singh S, Topolnik D, El Amine Barkat M, Radhakrishnan R, Guet-McCreight A, Topolnik L. Mouse hippocampal CA1 VIP interneurons detect novelty in the environment and support recognition memory. Cell Rep 2024; 43:114115. [PMID: 38607918 DOI: 10.1016/j.celrep.2024.114115] [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: 08/08/2023] [Revised: 02/17/2024] [Accepted: 03/29/2024] [Indexed: 04/14/2024] Open
Abstract
In the CA1 hippocampus, vasoactive intestinal polypeptide-expressing interneurons (VIP-INs) play a prominent role in disinhibitory circuit motifs. However, the specific behavioral conditions that lead to circuit disinhibition remain uncertain. To investigate the behavioral relevance of VIP-IN activity, we employed wireless technologies allowing us to monitor and manipulate their function in freely behaving mice. Our findings reveal that, during spatial exploration in new environments, VIP-INs in the CA1 hippocampal region become highly active, facilitating the rapid encoding of novel spatial information. Remarkably, both VIP-INs and pyramidal neurons (PNs) exhibit increased activity when encountering novel changes in the environment, including context- and object-related alterations. Concurrently, somatostatin- and parvalbumin-expressing inhibitory populations show an inverse relationship with VIP-IN and PN activity, revealing circuit disinhibition that occurs on a timescale of seconds. Thus, VIP-IN-mediated disinhibition may constitute a crucial element in the rapid encoding of novelty and the acquisition of recognition memory.
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Affiliation(s)
- Suhel Tamboli
- Neuroscience Axis, CRCHUQ-CHUL, Quebec City, PQ, Canada; Department of Biochemistry, Microbiology, and Bioinformatics, Université Laval, Quebec City, PQ, Canada
| | - Sanjay Singh
- Neuroscience Axis, CRCHUQ-CHUL, Quebec City, PQ, Canada; Department of Biochemistry, Microbiology, and Bioinformatics, Université Laval, Quebec City, PQ, Canada
| | - Dimitry Topolnik
- Neuroscience Axis, CRCHUQ-CHUL, Quebec City, PQ, Canada; Department of Biochemistry, Microbiology, and Bioinformatics, Université Laval, Quebec City, PQ, Canada
| | - Mohamed El Amine Barkat
- Neuroscience Axis, CRCHUQ-CHUL, Quebec City, PQ, Canada; Department of Biochemistry, Microbiology, and Bioinformatics, Université Laval, Quebec City, PQ, Canada
| | - Risna Radhakrishnan
- Neuroscience Axis, CRCHUQ-CHUL, Quebec City, PQ, Canada; Department of Biochemistry, Microbiology, and Bioinformatics, Université Laval, Quebec City, PQ, Canada
| | | | - Lisa Topolnik
- Neuroscience Axis, CRCHUQ-CHUL, Quebec City, PQ, Canada; Department of Biochemistry, Microbiology, and Bioinformatics, Université Laval, Quebec City, PQ, Canada.
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8
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Ghazinouri B, Nejad MM, Cheng S. Navigation and the efficiency of spatial coding: insights from closed-loop simulations. Brain Struct Funct 2024; 229:577-592. [PMID: 37029811 PMCID: PMC10978723 DOI: 10.1007/s00429-023-02637-8] [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: 01/10/2023] [Accepted: 03/28/2023] [Indexed: 04/09/2023]
Abstract
Spatial learning is critical for survival and its underlying neuronal mechanisms have been studied extensively. These studies have revealed a wealth of information about the neural representations of space, such as place cells and boundary cells. While many studies have focused on how these representations emerge in the brain, their functional role in driving spatial learning and navigation has received much less attention. We extended an existing computational modeling tool-chain to study the functional role of spatial representations using closed-loop simulations of spatial learning. At the heart of the model agent was a spiking neural network that formed a ring attractor. This network received inputs from place and boundary cells and the location of the activity bump in this network was the output. This output determined the movement directions of the agent. We found that the navigation performance depended on the parameters of the place cell input, such as their number, the place field sizes, and peak firing rate, as well as, unsurprisingly, the size of the goal zone. The dependence on the place cell parameters could be accounted for by just a single variable, the overlap index, but this dependence was nonmonotonic. By contrast, performance scaled monotonically with the Fisher information of the place cell population. Our results therefore demonstrate that efficiently encoding spatial information is critical for navigation performance.
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Affiliation(s)
- Behnam Ghazinouri
- Faculty of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Universitätsstrasse 150, 44801, Bochum, Germany
| | - Mohammadreza Mohagheghi Nejad
- Faculty of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Universitätsstrasse 150, 44801, Bochum, Germany
| | - Sen Cheng
- Faculty of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Universitätsstrasse 150, 44801, Bochum, Germany.
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9
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Yuste R, Cossart R, Yaksi E. Neuronal ensembles: Building blocks of neural circuits. Neuron 2024; 112:875-892. [PMID: 38262413 PMCID: PMC10957317 DOI: 10.1016/j.neuron.2023.12.008] [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: 02/14/2022] [Revised: 06/07/2023] [Accepted: 12/13/2023] [Indexed: 01/25/2024]
Abstract
Neuronal ensembles, defined as groups of neurons displaying recurring patterns of coordinated activity, represent an intermediate functional level between individual neurons and brain areas. Novel methods to measure and optically manipulate the activity of neuronal populations have provided evidence of ensembles in the neocortex and hippocampus. Ensembles can be activated intrinsically or in response to sensory stimuli and play a causal role in perception and behavior. Here we review ensemble phenomenology, developmental origin, biophysical and synaptic mechanisms, and potential functional roles across different brain areas and species, including humans. As modular units of neural circuits, ensembles could provide a mechanistic underpinning of fundamental brain processes, including neural coding, motor planning, decision-making, learning, and adaptability.
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Affiliation(s)
- Rafael Yuste
- NeuroTechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA.
| | - Rosa Cossart
- Inserm, INMED, Turing Center for Living Systems Aix-Marseille University, Marseille, France.
| | - Emre Yaksi
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway; Koç University Research Center for Translational Medicine, Koç University School of Medicine, Istanbul, Turkey.
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10
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Jeffery KJ. The mosaic structure of the mammalian cognitive map. Learn Behav 2024; 52:19-34. [PMID: 38231426 PMCID: PMC10923978 DOI: 10.3758/s13420-023-00618-9] [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] [Accepted: 11/27/2023] [Indexed: 01/18/2024]
Abstract
The cognitive map, proposed by Tolman in the 1940s, is a hypothetical internal representation of space constructed by the brain to enable an animal to undertake flexible spatial behaviors such as navigation. The subsequent discovery of place cells in the hippocampus of rats suggested that such a map-like representation does exist, and also provided a tool with which to explore its properties. Single-neuron studies in rodents conducted in small singular spaces have suggested that the map is founded on a metric framework, preserving distances and directions in an abstract representational format. An open question is whether this metric structure pertains over extended, often complexly structured real-world space. The data reviewed here suggest that this is not the case. The emerging picture is that instead of being a single, unified construct, the map is a mosaic of fragments that are heterogeneous, variably metric, multiply scaled, and sometimes laid on top of each other. Important organizing factors within and between fragments include boundaries, context, compass direction, and gravity. The map functions not to provide a comprehensive and precise rendering of the environment but rather to support adaptive behavior, tailored to the species and situation.
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Affiliation(s)
- Kate J Jeffery
- School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
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11
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Zhang M, Livi A, Carter M, Schoknecht H, Burkhalter A, Holy TE, Padoa-Schioppa C. The Representation of Decision Variables in Orbitofrontal Cortex is Longitudinally Stable. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.16.580715. [PMID: 38712111 PMCID: PMC11071317 DOI: 10.1101/2024.02.16.580715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
The computation and comparison of subjective values underlying economic choices rely on the orbitofrontal cortex (OFC). In this area, distinct groups of neurons encode the value of individual options, the binary choice outcome, and the chosen value. These variables capture both the input and the output of the choice process, suggesting that the cell groups found in OFC constitute the building blocks of a decision circuit. Here we show that this neural circuit is longitudinally stable. Using two-photon calcium imaging, we recorded from mice choosing between different juice flavors. Recordings of individual cells continued for up to 20 weeks. For each cell and each pair of sessions, we compared the activity profiles using cosine similarity, and we assessed whether the cell encoded the same variable in both sessions. These analyses revealed a high degree of stability and a modest representational drift. A quantitative estimate indicated this drift would not randomize the circuit within the animal's lifetime.
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12
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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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13
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Spivak L, Someck S, Levi A, Sivroni S, Stark E. Wired together, change together: Spike timing modifies transmission in converging assemblies. SCIENCE ADVANCES 2024; 10:eadj4411. [PMID: 38232172 DOI: 10.1126/sciadv.adj4411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 12/15/2023] [Indexed: 01/19/2024]
Abstract
The precise timing of neuronal spikes may lead to changes in synaptic connectivity and is thought to be crucial for learning and memory. However, the effect of spike timing on neuronal connectivity in the intact brain remains unknown. Using closed-loop optogenetic stimulation in CA1 of freely moving mice, we generated unique spike patterns between presynaptic pyramidal cells (PYRs) and postsynaptic parvalbumin (PV)-immunoreactive cells. The stimulation led to spike transmission changes that occurred together across all presynaptic PYRs connected to the same postsynaptic PV cell. The precise timing of all presynaptic and postsynaptic cell spikes affected transmission changes. These findings reveal an unexpected plasticity mechanism, in which the spike timing of an entire cell assembly has a more substantial impact on effective connectivity than that of individual cell pairs.
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Affiliation(s)
- Lidor Spivak
- Sagol School of Neuroscience and Department of Physiology and Pharmacology, Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Shirly Someck
- Sagol School of Neuroscience and Department of Physiology and Pharmacology, Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Amir Levi
- Sagol School of Neuroscience and Department of Physiology and Pharmacology, Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Shir Sivroni
- Sagol School of Neuroscience and Department of Physiology and Pharmacology, Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
- Department of Mathematics, Afeka-Tel Aviv College of Engineering, Tel-Aviv 6910717, Israel
- Department of Mathematics, The Open University of Israel, Ra'anana 4353701, Israel
| | - Eran Stark
- Sagol School of Neuroscience and Department of Physiology and Pharmacology, Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
- Sagol Department of Neurobiology, Faculty of Natural Sciences, Haifa University, Haifa 3103301, Israel
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14
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Krishnan S, Sheffield ME. Reward Expectation Reduces Representational Drift in the Hippocampus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.21.572809. [PMID: 38187677 PMCID: PMC10769341 DOI: 10.1101/2023.12.21.572809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Spatial memory in the hippocampus involves dynamic neural patterns that change over days, termed representational drift. While drift may aid memory updating, excessive drift could impede retrieval. Memory retrieval is influenced by reward expectation during encoding, so we hypothesized that diminished reward expectation would exacerbate representational drift. We found that high reward expectation limited drift, with CA1 representations on one day gradually re-emerging over successive trials the following day. Conversely, the absence of reward expectation resulted in increased drift, as the gradual re-emergence of the previous day's representation did not occur. At the single cell level, lowering reward expectation caused an immediate increase in the proportion of place-fields with low trial-to-trial reliability. These place fields were less likely to be reinstated the following day, underlying increased drift in this condition. In conclusion, heightened reward expectation improves memory encoding and retrieval by maintaining reliable place fields that are gradually reinstated across days, thereby minimizing representational drift.
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15
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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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16
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Chiu Y, Dong C, Krishnan S, Sheffield MEJ. The Precision of Place Fields Governs Their Fate across Epochs of Experience. eNeuro 2023; 10:ENEURO.0261-23.2023. [PMID: 37973379 PMCID: PMC10706252 DOI: 10.1523/eneuro.0261-23.2023] [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: 07/25/2023] [Revised: 10/30/2023] [Accepted: 10/31/2023] [Indexed: 11/19/2023] Open
Abstract
Spatial memories are represented by hippocampal place cells during navigation. This spatial code is dynamic, undergoing changes across time, known as representational drift, and across changes in internal state, even while navigating the same spatial environment with consistent behavior. A dynamic code may provide the hippocampus a means to track distinct epochs of experience that occur at different times or during different internal states and update spatial memories. Changes to the spatial code include place fields (PFs) that remap to new locations and place fields that vanish, while others are stable. However, what determines place field fate across epochs remains unclear. We measured the lap-by-lap properties of place cells in mice during navigation for a block of trials in a rewarded virtual environment. We then determined the position of the place fields in another block of trials in the same spatial environment either separated by a day (a distinct temporal epoch) or during the same session but with reward removed to change reward expectation (a distinct internal state epoch). We found that place cells with remapped place fields across epochs tended to have lower spatial precision during navigation in the initial epoch. Place cells with stable or vanished place fields tended to have higher spatial precision. We conclude that place cells with less precise place fields have greater spatial flexibility, allowing them to respond to, and track, distinct epochs of experience in the same spatial environment, while place cells with precise place fields generally preserve spatial information when their fields reappear.
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Affiliation(s)
- YuHung Chiu
- Department of Physics, University of Chicago, Chicago, 60637, IL
- Institute for Neuroscience, University of Chicago, Chicago, 60637, IL
| | - Can Dong
- Department of Neurobiology, University of Chicago, Chicago, 60637, IL
- Institute for Neuroscience, University of Chicago, Chicago, 60637, IL
| | - Seetha Krishnan
- Department of Neurobiology, University of Chicago, Chicago, 60637, IL
- Institute for Neuroscience, University of Chicago, Chicago, 60637, IL
| | - Mark E J Sheffield
- Department of Neurobiology, University of Chicago, Chicago, 60637, IL
- Institute for Neuroscience, University of Chicago, Chicago, 60637, IL
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17
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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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18
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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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19
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De A, Chaudhuri R. Common population codes produce extremely nonlinear neural manifolds. Proc Natl Acad Sci U S A 2023; 120:e2305853120. [PMID: 37733742 PMCID: PMC10523500 DOI: 10.1073/pnas.2305853120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 08/03/2023] [Indexed: 09/23/2023] Open
Abstract
Populations of neurons represent sensory, motor, and cognitive variables via patterns of activity distributed across the population. The size of the population used to encode a variable is typically much greater than the dimension of the variable itself, and thus, the corresponding neural population activity occupies lower-dimensional subsets of the full set of possible activity states. Given population activity data with such lower-dimensional structure, a fundamental question asks how close the low-dimensional data lie to a linear subspace. The linearity or nonlinearity of the low-dimensional structure reflects important computational features of the encoding, such as robustness and generalizability. Moreover, identifying such linear structure underlies common data analysis methods such as Principal Component Analysis (PCA). Here, we show that for data drawn from many common population codes the resulting point clouds and manifolds are exceedingly nonlinear, with the dimension of the best-fitting linear subspace growing at least exponentially with the true dimension of the data. Consequently, linear methods like PCA fail dramatically at identifying the true underlying structure, even in the limit of arbitrarily many data points and no noise.
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Affiliation(s)
- Anandita De
- Center for Neuroscience, University of California, Davis, CA95618
- Department of Physics, University of California, Davis, CA95616
| | - Rishidev Chaudhuri
- Center for Neuroscience, University of California, Davis, CA95618
- Department of Neurobiology, Physiology and Behavior, University of California, Davis, CA95616
- Department of Mathematics, University of California, Davis, CA95616
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20
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Barwich AS, Severino GJ. The Wire Is Not the Territory: Understanding Representational Drift in Olfaction With Dynamical Systems Theory. Top Cogn Sci 2023. [PMID: 37690113 DOI: 10.1111/tops.12689] [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: 03/22/2023] [Revised: 08/21/2023] [Accepted: 08/22/2023] [Indexed: 09/12/2023]
Abstract
Representational drift is a phenomenon of increasing interest in the cognitive and neural sciences. While investigations are ongoing for other sensory cortices, recent research has demonstrated the pervasiveness in which it occurs in the piriform cortex for olfaction. This gradual weakening and shifting of stimulus-responsive cells has critical implications for sensory stimulus-response models and perceptual decision-making. While representational drift may complicate traditional sensory processing models, it could be seen as an advantage in olfaction, as animals live in environments with constantly changing and unpredictable chemical information. Non-topographical encoding in the olfactory system may aid in contextualizing reactions to promiscuous odor stimuli, facilitating adaptive animal behavior and survival. This article suggests that traditional models of stimulus-(neural) response mapping in olfaction may need to be reevaluated and instead motivates the use of dynamical systems theory as a methodology and conceptual framework.
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Affiliation(s)
- Ann-Sophie Barwich
- Cognitive Science Program, Indiana University
- Department of History and Philosophy of Science and Medicine, Indiana University
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21
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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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22
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Levenstein D, Okun M. Logarithmically scaled, gamma distributed neuronal spiking. J Physiol 2023; 601:3055-3069. [PMID: 36086892 PMCID: PMC10952267 DOI: 10.1113/jp282758] [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: 05/09/2022] [Accepted: 07/28/2022] [Indexed: 11/08/2022] Open
Abstract
Naturally log-scaled quantities abound in the nervous system. Distributions of these quantities have non-intuitive properties, which have implications for data analysis and the understanding of neural circuits. Here, we review the log-scaled statistics of neuronal spiking and the relevant analytical probability distributions. Recent work using log-scaling revealed that interspike intervals of forebrain neurons segregate into discrete modes reflecting spiking at different timescales and are each well-approximated by a gamma distribution. Each neuron spends most of the time in an irregular spiking 'ground state' with the longest intervals, which determines the mean firing rate of the neuron. Across the entire neuronal population, firing rates are log-scaled and well approximated by the gamma distribution, with a small number of highly active neurons and an overabundance of low rate neurons (the 'dark matter'). These results are intricately linked to a heterogeneous balanced operating regime, which confers upon neuronal circuits multiple computational advantages and has evolutionarily ancient origins.
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Affiliation(s)
- Daniel Levenstein
- Department of Neurology and NeurosurgeryMcGill UniversityMontrealQCCanada
- MilaMontréalQCCanada
| | - Michael Okun
- Department of Psychology and Neuroscience InstituteUniversity of SheffieldSheffieldUK
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23
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Geva N, Deitch D, Rubin A, Ziv Y. Time and experience differentially affect distinct aspects of hippocampal representational drift. Neuron 2023:S0896-6273(23)00378-1. [PMID: 37315556 DOI: 10.1016/j.neuron.2023.05.005] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 02/22/2023] [Accepted: 05/08/2023] [Indexed: 06/16/2023]
Abstract
Hippocampal activity is critical for spatial memory. Within a fixed, familiar environment, hippocampal codes gradually change over timescales of days to weeks-a phenomenon known as representational drift. The passage of time and the amount of experience are two factors that profoundly affect memory. However, thus far, it has remained unclear to what extent these factors drive hippocampal representational drift. Here, we longitudinally recorded large populations of hippocampal neurons in mice while they repeatedly explored two different familiar environments that they visited at different time intervals over weeks. We found that time and experience differentially affected distinct aspects of representational drift: the passage of time drove changes in neuronal activity rates, whereas experience drove changes in the cells' spatial tuning. Changes in spatial tuning were context specific and largely independent of changes in activity rates. Thus, our results suggest that representational drift is a multi-faceted process governed by distinct neuronal mechanisms.
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Affiliation(s)
- Nitzan Geva
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Daniel Deitch
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Alon Rubin
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel.
| | - Yaniv Ziv
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel.
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24
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Srinivasan A, Srinivasan A, Goodman MR, Riceberg JS, Guise KG, Shapiro ML. Hippocampal and Medial Prefrontal Cortex Fractal Spiking Patterns Encode Episodes and Rules. CHAOS, SOLITONS, AND FRACTALS 2023; 171:113508. [PMID: 37251275 PMCID: PMC10217776 DOI: 10.1016/j.chaos.2023.113508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
A central question in neuroscience is how the brain represents and processes information to guide behavior. The principles that organize brain computations are not fully known, and could include scale-free, or fractal patterns of neuronal activity. Scale-free brain activity may be a natural consequence of the relatively small subsets of neuronal populations that respond to task features, i.e., sparse coding. The size of the active subsets constrains the possible sequences of inter-spike intervals (ISI), and selecting from this limited set may produce firing patterns across wide-ranging timescales that form fractal spiking patterns. To investigate the extent to which fractal spiking patterns corresponded with task features, we analyzed ISIs in simultaneously recorded populations of CA1 and medial prefrontal cortical (mPFC) neurons in rats performing a spatial memory task that required both structures. CA1 and mPFC ISI sequences formed fractal patterns that predicted memory performance. CA1 pattern duration, but not length or content, varied with learning speed and memory performance whereas mPFC patterns did not. The most common CA1 and mPFC patterns corresponded with each region's cognitive function: CA1 patterns encoded behavioral episodes which linked the start, choice, and goal of paths through the maze whereas mPFC patterns encoded behavioral "rules" which guided goal selection. mPFC patterns predicted changing CA1 spike patterns only as animals learned new rules. Together, the results suggest that CA1 and mPFC population activity may predict choice outcomes by using fractal ISI patterns to compute task features.
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Affiliation(s)
- Aditya Srinivasan
- Department of Neuroscience and Experimental Therapeutics, Albany Medical College, 47 New Scotland Ave, Mail Code 126, Albany, NY 12208
| | - Arvind Srinivasan
- College of Health Sciences, California Northstate University, 2910 Prospect Park Drive, Rancho Cordova, CA 95670
| | - Michael R. Goodman
- Department of Neuroscience and Experimental Therapeutics, Albany Medical College, 47 New Scotland Ave, Mail Code 126, Albany, NY 12208
| | - Justin S. Riceberg
- Department of Neuroscience and Experimental Therapeutics, Albany Medical College, 47 New Scotland Ave, Mail Code 126, Albany, NY 12208
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, Hess Center for Science and Medicine, 1470 Madison Avenue New York, NY 10029
| | - Kevin G. Guise
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, Hess Center for Science and Medicine, 1470 Madison Avenue New York, NY 10029
| | - Matthew L. Shapiro
- Department of Neuroscience and Experimental Therapeutics, Albany Medical College, 47 New Scotland Ave, Mail Code 126, Albany, NY 12208
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25
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Parra-Barrero E, Cheng S. Learning to predict future locations with internally generated theta sequences. PLoS Comput Biol 2023; 19:e1011101. [PMID: 37172053 DOI: 10.1371/journal.pcbi.1011101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 05/24/2023] [Accepted: 04/13/2023] [Indexed: 05/14/2023] Open
Abstract
Representing past, present and future locations is key for spatial navigation. Indeed, within each cycle of the theta oscillation, the population of hippocampal place cells appears to represent trajectories starting behind the current position of the animal and sweeping ahead of it. In particular, we reported recently that the position represented by CA1 place cells at a given theta phase corresponds to the location where animals were or will be located at a fixed time interval into the past or future assuming the animal ran at its typical, not the current, speed through that part of the environment. This coding scheme leads to longer theta trajectories, larger place fields and shallower phase precession in areas where animals typically run faster. Here we present a mechanistic computational model that accounts for these experimental observations. The model consists of a continuous attractor network with short-term synaptic facilitation and depression that internally generates theta sequences that advance at a fixed pace. Spatial locations are then mapped onto the active units via modified Hebbian plasticity. As a result, neighboring units become associated with spatial locations further apart where animals run faster, reproducing our earlier experimental results. The model also accounts for the higher density of place fields generally observed where animals slow down, such as around rewards. Furthermore, our modeling results reveal that an artifact of the decoding analysis might be partly responsible for the observation that theta trajectories start behind the animal's current position. Overall, our results shed light on how the hippocampal code might arise from the interplay between behavior, sensory input and predefined network dynamics.
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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
| | - 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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26
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Kong E, Lee KH, Do J, Kim P, Lee D. Dynamic and stable hippocampal representations of social identity and reward expectation support associative social memory in male mice. Nat Commun 2023; 14:2597. [PMID: 37147388 PMCID: PMC10163237 DOI: 10.1038/s41467-023-38338-3] [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: 06/07/2022] [Accepted: 04/26/2023] [Indexed: 05/07/2023] Open
Abstract
Recognizing an individual and retrieving and updating the value information assigned to the individual are fundamental abilities for establishing social relationships. To understand the neural mechanisms underlying the association between social identity and reward value, we developed Go-NoGo social discrimination paradigms that required male subject mice to distinguish between familiar mice based on their individually unique characteristics and associate them with reward availability. We found that mice could discriminate individual conspecifics through a brief nose-to-nose investigation, and this ability depended on the dorsal hippocampus. Two-photon calcium imaging revealed that dorsal CA1 hippocampal neurons represented reward expectation during social, but not non-social tasks, and these activities were maintained over days regardless of the identity of the associated mouse. Furthermore, a dynamically changing subset of hippocampal CA1 neurons discriminated between individual mice with high accuracy. Our findings suggest that the neuronal activities in CA1 provide possible neural substrates for associative social memory.
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Affiliation(s)
- Eunji Kong
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
- KI for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Kyu-Hee Lee
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea
| | - Jongrok Do
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Pilhan Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
- KI for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
| | - Doyun Lee
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea.
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27
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Yun M, Hwang JY, Jung MW. Septotemporal variations in hippocampal value and outcome processing. Cell Rep 2023; 42:112094. [PMID: 36763498 DOI: 10.1016/j.celrep.2023.112094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 11/11/2022] [Accepted: 01/26/2023] [Indexed: 02/11/2023] Open
Abstract
A large body of evidence indicates functional variations along the hippocampal longitudinal axis. To investigate whether and how value and outcome processing vary between the dorsal (DH) and the ventral hippocampus (VH), we examined neuronal activity and inactivation effects of the DH and VH in mice performing probabilistic classical conditioning tasks. Inactivation of either structure disrupts value-dependent anticipatory licking, and value-coding neurons are found in both structures, indicating their involvement in value processing. However, the DH neuronal population increases activity as a function of value, while the VH neuronal population is preferentially responsive to the highest-value sensory cue. Also, signals related to outcome-dependent value learning are stronger in the DH. VH neurons instead show rapid responses to punishment and strongly biased responses to negative prediction error. These findings suggest that the DH faithfully represents the external value landscape, whereas the VH preferentially represents behaviorally relevant, salient features of experienced events.
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Affiliation(s)
- Miru Yun
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea; Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Korea
| | - Ji Young Hwang
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea; Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Korea
| | - Min Whan Jung
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea; Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Korea.
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28
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Fan LZ, Kim DK, Jennings JH, Tian H, Wang PY, Ramakrishnan C, Randles S, Sun Y, Thadhani E, Kim YS, Quirin S, Giocomo L, Cohen AE, Deisseroth K. All-optical physiology resolves a synaptic basis for behavioral timescale plasticity. Cell 2023; 186:543-559.e19. [PMID: 36669484 PMCID: PMC10327443 DOI: 10.1016/j.cell.2022.12.035] [Citation(s) in RCA: 46] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 10/19/2022] [Accepted: 12/19/2022] [Indexed: 01/20/2023]
Abstract
Learning has been associated with modifications of synaptic and circuit properties, but the precise changes storing information in mammals have remained largely unclear. We combined genetically targeted voltage imaging with targeted optogenetic activation and silencing of pre- and post-synaptic neurons to study the mechanisms underlying hippocampal behavioral timescale plasticity. In mice navigating a virtual-reality environment, targeted optogenetic activation of individual CA1 cells at specific places induced stable representations of these places in the targeted cells. Optical elicitation, recording, and modulation of synaptic transmission in behaving mice revealed that activity in presynaptic CA2/3 cells was required for the induction of plasticity in CA1 and, furthermore, that during induction of these place fields in single CA1 cells, synaptic input from CA2/3 onto these same cells was potentiated. These results reveal synaptic implementation of hippocampal behavioral timescale plasticity and define a methodology to resolve synaptic plasticity during learning and memory in behaving mammals.
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Affiliation(s)
- Linlin Z Fan
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Doo Kyung Kim
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Joshua H Jennings
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - He Tian
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Peter Y Wang
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | | | - Sawyer Randles
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Yanjun Sun
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Elina Thadhani
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Yoon Seok Kim
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Sean Quirin
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Lisa Giocomo
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA; Department of Physics, Harvard University, Cambridge, MA, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, USA; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Howard Hughes Medical Institute, Stanford, CA, USA.
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29
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Qin S, Farashahi S, Lipshutz D, Sengupta AM, Chklovskii DB, Pehlevan C. Coordinated drift of receptive fields in Hebbian/anti-Hebbian network models during noisy representation learning. Nat Neurosci 2023; 26:339-349. [PMID: 36635497 DOI: 10.1038/s41593-022-01225-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 10/28/2022] [Indexed: 01/13/2023]
Abstract
Recent experiments have revealed that neural population codes in many brain areas continuously change even when animals have fully learned and stably perform their tasks. This representational 'drift' naturally leads to questions about its causes, dynamics and functions. Here we explore the hypothesis that neural representations optimize a representational objective with a degenerate solution space, and noisy synaptic updates drive the network to explore this (near-)optimal space causing representational drift. We illustrate this idea and explore its consequences in simple, biologically plausible Hebbian/anti-Hebbian network models of representation learning. We find that the drifting receptive fields of individual neurons can be characterized by a coordinated random walk, with effective diffusion constants depending on various parameters such as learning rate, noise amplitude and input statistics. Despite such drift, the representational similarity of population codes is stable over time. Our model recapitulates experimental observations in the hippocampus and posterior parietal cortex and makes testable predictions that can be probed in future experiments.
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Affiliation(s)
- Shanshan Qin
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
- Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Shiva Farashahi
- Center for Computational Neuroscience, Flatiron Institute, New York, NY, USA
| | - David Lipshutz
- Center for Computational Neuroscience, Flatiron Institute, New York, NY, USA
| | - Anirvan M Sengupta
- Center for Computational Neuroscience, Flatiron Institute, New York, NY, USA
- Department of Physics and Astronomy, Rutgers University, New Brunswick, NJ, USA
| | - Dmitri B Chklovskii
- Center for Computational Neuroscience, Flatiron Institute, New York, NY, USA
- NYU Langone Medical Center, New York, NY, USA
| | - Cengiz Pehlevan
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
- Center for Brain Science, Harvard University, Cambridge, MA, USA.
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30
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Goldt S, Krzakala F, Zdeborová L, Brunel N. Bayesian reconstruction of memories stored in neural networks from their connectivity. PLoS Comput Biol 2023; 19:e1010813. [PMID: 36716332 PMCID: PMC9910750 DOI: 10.1371/journal.pcbi.1010813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 02/09/2023] [Accepted: 12/12/2022] [Indexed: 02/01/2023] Open
Abstract
The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in a recurrent network of neurons, given its synaptic connectivity matrix. Here, we address this question by determining when solving such an inference problem is theoretically possible in specific attractor network models and by providing a practical algorithm to do so. The algorithm builds on ideas from statistical physics to perform approximate Bayesian inference and is amenable to exact analysis. We study its performance on three different models, compare the algorithm to standard algorithms such as PCA, and explore the limitations of reconstructing stored patterns from synaptic connectivity.
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Affiliation(s)
- Sebastian Goldt
- International School of Advanced Studies (SISSA), Trieste, Italy
- * E-mail:
| | - Florent Krzakala
- IdePHICS laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
| | - Lenka Zdeborová
- SPOC laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
| | - Nicolas Brunel
- Department of Neurobiology, Duke University, Durham, North Carolina, United States of America
- Department of Physics, Duke University, Durham, North Carolina, United States of America
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31
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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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32
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Jeong N, Singer AC. Learning from inhibition: Functional roles of hippocampal CA1 inhibition in spatial learning and memory. Curr Opin Neurobiol 2022; 76:102604. [PMID: 35810533 PMCID: PMC11414469 DOI: 10.1016/j.conb.2022.102604] [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: 01/14/2022] [Revised: 05/19/2022] [Accepted: 06/07/2022] [Indexed: 11/19/2022]
Abstract
Hippocampal inhibitory interneurons exert a powerful influence on learning and memory. Inhibitory interneurons are known to play a major role in many diseases that affect memory, and to strongly influence brain functions required for memory-related tasks. While previous studies involving genetic, optogenetic, and pharmacological manipulations have shown that hippocampal interneurons play essential roles in spatial and episodic learning and memory, exactly how interneurons affect local circuit computations during spatial navigation is not well understood. Given the significant anatomical, morphological, and functional heterogeneity in hippocampal interneurons, one may suspect cell-type specific roles in circuit computations. Here, we review emerging evidence of CA1 hippocampal interneurons' role in local circuit computations that support spatial learning and memory and discuss open questions about CA1 interneurons in spatial learning.
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Affiliation(s)
- Nuri Jeong
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA; Neuroscience Graduate Program, Graduate Division of Biological and Biomedical Sciences, Emory University, Atlanta, GA, 30322, USA. https://twitter.com/nuriscientist
| | - Annabelle C Singer
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA.
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33
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Hodapp A, Kaiser ME, Thome C, Ding L, Rozov A, Klumpp M, Stevens N, Stingl M, Sackmann T, Lehmann N, Draguhn A, Burgalossi A, Engelhardt M, Both M. Dendritic axon origin enables information gating by perisomatic inhibition in pyramidal neurons. Science 2022; 377:1448-1452. [PMID: 36137045 DOI: 10.1126/science.abj1861] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Information processing in neuronal networks involves the recruitment of selected neurons into coordinated spatiotemporal activity patterns. This sparse activation results from widespread synaptic inhibition in conjunction with neuron-specific synaptic excitation. We report the selective recruitment of hippocampal pyramidal cells into patterned network activity. During ripple oscillations in awake mice, spiking is much more likely in cells in which the axon originates from a basal dendrite rather than from the soma. High-resolution recordings in vitro and computer modeling indicate that these spikes are elicited by synaptic input to the axon-carrying dendrite and thus escape perisomatic inhibition. Pyramidal cells with somatic axon origin can be activated during ripple oscillations by blocking their somatic inhibition. The recruitment of neurons into active ensembles is thus determined by axonal morphological features.
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Affiliation(s)
- Alexander Hodapp
- Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Martin E Kaiser
- Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Christian Thome
- Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany.,Institute of Anatomy and Cell Biology, Medical Faculty, Johannes Kepler University, Linz, Austria.,Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - Lingjun Ding
- Institute of Neurobiology, University of Tübingen, Tübingen, Germany.,Werner-Reichardt Centre for Integrative Neuroscience, Tübingen, Germany.,Graduate Training Centre of Neuroscience, IMPRS, Tübingen, Germany
| | - Andrei Rozov
- Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany.,Federal Center of Brain Research and Neurotechnologies, Moscow, Russian Federation.,OpenLab of Neurobiology, Kazan Federal University, Kazan, Russian Federation
| | - Matthias Klumpp
- Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Nikolas Stevens
- Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Moritz Stingl
- Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Tina Sackmann
- Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Nadja Lehmann
- Institute of Neuroanatomy, Mannheim Center for Translational Neuroscience (MCTN), Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Andreas Draguhn
- Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Andrea Burgalossi
- Institute of Neurobiology, University of Tübingen, Tübingen, Germany.,Werner-Reichardt Centre for Integrative Neuroscience, Tübingen, Germany
| | - Maren Engelhardt
- Institute of Anatomy and Cell Biology, Medical Faculty, Johannes Kepler University, Linz, Austria.,Institute of Neuroanatomy, Mannheim Center for Translational Neuroscience (MCTN), Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Martin Both
- Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany
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34
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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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35
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Huszár R, Zhang Y, Blockus H, Buzsáki G. Preconfigured dynamics in the hippocampus are guided by embryonic birthdate and rate of neurogenesis. Nat Neurosci 2022; 25:1201-1212. [PMID: 35995878 PMCID: PMC10807234 DOI: 10.1038/s41593-022-01138-x] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 07/12/2022] [Indexed: 02/08/2023]
Abstract
The incorporation of new information into the hippocampal network is likely to be constrained by its innate architecture and internally generated activity patterns. However, the origin, organization and consequences of such patterns remain poorly understood. In the present study we show that hippocampal network dynamics are affected by sequential neurogenesis. We birthdated CA1 pyramidal neurons with in utero electroporation over 4 embryonic days, encompassing the peak of hippocampal neurogenesis, and compared their functional features in freely moving adult mice. Neurons of the same birthdate displayed distinct connectivity, coactivity across brain states and assembly dynamics. Same-birthdate neurons exhibited overlapping spatial representations, which were maintained across different environments. Overall, the wiring and functional features of CA1 pyramidal neurons reflected a combination of birthdate and the rate of neurogenesis. These observations demonstrate that sequential neurogenesis during embryonic development shapes the preconfigured forms of adult network dynamics.
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Affiliation(s)
- Roman Huszár
- Neuroscience Institute, New York University, New York, NY, USA.
- Center for Neural Science, New York University, New York, NY, USA.
| | - Yunchang Zhang
- Neuroscience Institute, New York University, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Heike Blockus
- Department of Neuroscience, Columbia University, New York, NY, USA
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - György Buzsáki
- Neuroscience Institute, New York University, New York, NY, USA.
- Center for Neural Science, New York University, New York, NY, USA.
- Department of Neurology, Langone Medical Center, New York, NY, USA.
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36
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Tanni S, de Cothi W, Barry C. State transitions in the statistically stable place cell population correspond to rate of perceptual change. Curr Biol 2022; 32:3505-3514.e7. [PMID: 35835121 PMCID: PMC9616721 DOI: 10.1016/j.cub.2022.06.046] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 04/20/2022] [Accepted: 06/15/2022] [Indexed: 11/25/2022]
Abstract
The hippocampus occupies a central role in mammalian navigation and memory. Yet an understanding of the rules that govern the statistics and granularity of the spatial code, as well as its interactions with perceptual stimuli, is lacking. We analyzed CA1 place cell activity recorded while rats foraged in different large-scale environments. We found that place cell activity was subject to an unexpected but precise homeostasis—the distribution of activity in the population as a whole being constant at all locations within and between environments. Using a virtual reconstruction of the largest environment, we showed that the rate of transition through this statistically stable population matches the rate of change in the animals’ visual scene. Thus, place fields near boundaries were small but numerous, while in the environment’s interior, they were larger but more dispersed. These results indicate that hippocampal spatial activity is governed by a small number of simple laws and, in particular, suggest the presence of an information-theoretic bound imposed by perception on the fidelity of the spatial memory system. Neural activity in rodent CA1 place cell populations is homeostatically balanced Hippocampal place field size and frequency are governed by proximity to boundaries Transition rate through place cell population matches rate of change in visual scene
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Affiliation(s)
- Sander Tanni
- Department of Cell and Developmental Biology, University College London, London, UK
| | - William de Cothi
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Caswell Barry
- Department of Cell and Developmental Biology, University College London, London, UK.
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37
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Fuchsberger T, Paulsen O. Modulation of hippocampal plasticity in learning and memory. Curr Opin Neurobiol 2022; 75:102558. [PMID: 35660989 DOI: 10.1016/j.conb.2022.102558] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/15/2022] [Accepted: 04/25/2022] [Indexed: 11/17/2022]
Abstract
Synaptic plasticity plays a central role in the study of neural mechanisms of learning and memory. Plasticity rules are not invariant over time but are under neuromodulatory control, enabling behavioral states to influence memory formation. Neuromodulation controls synaptic plasticity at network level by directing information flow, at circuit level through changes in excitation/inhibition balance, and at synaptic level through modulation of intracellular signaling cascades. Although most research has focused on modulation of principal neurons, recent progress has uncovered important roles for interneurons in not only routing information, but also setting conditions for synaptic plasticity. Moreover, astrocytes have been shown to both gate and mediate plasticity. These additional mechanisms must be considered for a comprehensive mechanistic understanding of learning and memory.
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Affiliation(s)
- Tanja Fuchsberger
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Ole Paulsen
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.
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38
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Masset P, Qin S, Zavatone-Veth JA. Drifting neuronal representations: Bug or feature? BIOLOGICAL CYBERNETICS 2022; 116:253-266. [PMID: 34993613 DOI: 10.1007/s00422-021-00916-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 11/17/2021] [Indexed: 06/14/2023]
Abstract
The brain displays a remarkable ability to sustain stable memories, allowing animals to execute precise behaviors or recall stimulus associations years after they were first learned. Yet, recent long-term recording experiments have revealed that single-neuron representations continuously change over time, contravening the classical assumption that learned features remain static. How do unstable neural codes support robust perception, memories, and actions? Here, we review recent experimental evidence for such representational drift across brain areas, as well as dissections of its functional characteristics and underlying mechanisms. We emphasize theoretical proposals for how drift need not only be a form of noise for which the brain must compensate. Rather, it can emerge from computationally beneficial mechanisms in hierarchical networks performing robust probabilistic computations.
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Affiliation(s)
- Paul Masset
- Center for Brain Science, Harvard University, Cambridge, MA, USA.
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
| | - Shanshan Qin
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Jacob A Zavatone-Veth
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- Department of Physics, Harvard University, Cambridge, MA, USA
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39
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Keinath AT, Mosser CA, Brandon MP. The representation of context in mouse hippocampus is preserved despite neural drift. Nat Commun 2022; 13:2415. [PMID: 35504915 PMCID: PMC9065029 DOI: 10.1038/s41467-022-30198-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 04/19/2022] [Indexed: 12/18/2022] Open
Abstract
The hippocampus is thought to mediate episodic memory through the instantiation and reinstatement of context-specific cognitive maps. However, recent longitudinal experiments have challenged this view, reporting that most hippocampal cells change their tuning properties over days even in the same environment. Often referred to as neural or representational drift, these dynamics raise questions about the capacity and content of the hippocampal code. One such question is whether and how these long-term dynamics impact the hippocampal code for context. To address this, we image large CA1 populations over more than a month of daily experience as freely behaving mice participate in an extended geometric morph paradigm. We find that long-timescale changes in population activity occur orthogonally to the representation of context in network space, allowing for consistent readout of contextual information across weeks. This population-level structure is supported by heterogeneous patterns of activity at the level of individual cells, where we observe evidence of a positive relationship between interpretable contextual coding and long-term stability. Together, these results demonstrate that long-timescale changes to the CA1 spatial code preserve the relative structure of contextual representation.
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Affiliation(s)
- Alexandra T Keinath
- Department of Psychiatry, Douglas Hospital Research Centre, McGill University, 6875 Boulevard LaSalle, Verdun, QC, H4H 1R3, Canada.
| | - Coralie-Anne Mosser
- Department of Psychiatry, Douglas Hospital Research Centre, McGill University, 6875 Boulevard LaSalle, Verdun, QC, H4H 1R3, Canada
| | - Mark P Brandon
- Department of Psychiatry, Douglas Hospital Research Centre, McGill University, 6875 Boulevard LaSalle, Verdun, QC, H4H 1R3, Canada.
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40
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Feng Y, Brunel N. Storage capacity of networks with discrete synapses and sparsely encoded memories. Phys Rev E 2022; 105:054408. [PMID: 35706193 DOI: 10.1103/physreve.105.054408] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 03/11/2022] [Indexed: 06/15/2023]
Abstract
Attractor neural networks are one of the leading theoretical frameworks for the formation and retrieval of memories in networks of biological neurons. In this framework, a pattern imposed by external inputs to the network is said to be learned when this pattern becomes a fixed point attractor of the network dynamics. The storage capacity is the maximum number of patterns that can be learned by the network. In this paper, we study the storage capacity of fully connected and sparsely connected networks with a binarized Hebbian rule, for arbitrary coding levels. Our results show that a network with discrete synapses has a similar storage capacity as the model with continuous synapses, and that this capacity tends asymptotically towards the optimal capacity, in the space of all possible binary connectivity matrices, in the sparse coding limit. We also derive finite coding level corrections for the asymptotic solution in the sparse coding limit. The result indicates the capacity of networks with Hebbian learning rules converges to the optimal capacity extremely slowly when the coding level becomes small. Our results also show that in networks with sparse binary connectivity matrices, the information capacity per synapse is larger than in the fully connected case, and thus such networks store information more efficiently.
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Affiliation(s)
- Yu Feng
- Department of Physics, Duke University, Durham, North Carolina 27710, USA
| | - Nicolas Brunel
- Department of Physics, Duke University, Durham, North Carolina 27710, USA
- Department of Neurobiology, Duke University, Durham, North Carolina 27710, USA
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41
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Networking brainstem and basal ganglia circuits for movement. Nat Rev Neurosci 2022; 23:342-360. [DOI: 10.1038/s41583-022-00581-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/10/2022] [Indexed: 12/14/2022]
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42
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O’Hare JK, Gonzalez KC, Herrlinger SA, Hirabayashi Y, Hewitt VL, Blockus H, Szoboszlay M, Rolotti SV, Geiller TC, Negrean A, Chelur V, Polleux F, Losonczy A. Compartment-specific tuning of dendritic feature selectivity by intracellular Ca 2+ release. Science 2022; 375:eabm1670. [PMID: 35298275 PMCID: PMC9667905 DOI: 10.1126/science.abm1670] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Dendritic calcium signaling is central to neural plasticity mechanisms that allow animals to adapt to the environment. Intracellular calcium release (ICR) from the endoplasmic reticulum has long been thought to shape these mechanisms. However, ICR has not been investigated in mammalian neurons in vivo. We combined electroporation of single CA1 pyramidal neurons, simultaneous imaging of dendritic and somatic activity during spatial navigation, optogenetic place field induction, and acute genetic augmentation of ICR cytosolic impact to reveal that ICR supports the establishment of dendritic feature selectivity and shapes integrative properties determining output-level receptive fields. This role for ICR was more prominent in apical than in basal dendrites. Thus, ICR cooperates with circuit-level architecture in vivo to promote the emergence of behaviorally relevant plasticity in a compartment-specific manner.
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Affiliation(s)
- Justin K. O’Hare
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
| | - Kevin C. Gonzalez
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
| | - Stephanie A. Herrlinger
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
| | - Yusuke Hirabayashi
- Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo; Tokyo, Japan
| | - Victoria L. Hewitt
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
| | - Heike Blockus
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
| | - Miklos Szoboszlay
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
| | - Sebi V. Rolotti
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
| | - Tristan C. Geiller
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
| | - Adrian Negrean
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
| | - Vikas Chelur
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
| | - Franck Polleux
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
- Kavli Institute for Brain Science, Columbia University; New York, NY, 10027, United States
| | - Attila Losonczy
- Department of Neuroscience, Columbia University; New York, NY, 10027, United States
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University; New York, NY, 10027, United States
- Kavli Institute for Brain Science, Columbia University; New York, NY, 10027, United States
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43
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Rolotti SV, Blockus H, Sparks FT, Priestley JB, Losonczy A. Reorganization of CA1 dendritic dynamics by hippocampal sharp-wave ripples during learning. Neuron 2022; 110:977-991.e4. [PMID: 35041805 PMCID: PMC8930454 DOI: 10.1016/j.neuron.2021.12.017] [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: 03/23/2021] [Revised: 07/23/2021] [Accepted: 12/10/2021] [Indexed: 12/17/2022]
Abstract
The hippocampus plays a critical role in memory consolidation, mediated by coordinated network activity during sharp-wave ripple (SWR) events. Despite the link between SWRs and hippocampal plasticity, little is known about how network state affects information processing in dendrites, the primary sites of synaptic input integration and plasticity. Here, we monitored somatic and basal dendritic activity in CA1 pyramidal cells in behaving mice using longitudinal two-photon calcium imaging integrated with simultaneous local field potential recordings. We found immobility was associated with an increase in dendritic activity concentrated during SWRs. Coincident dendritic and somatic activity during SWRs predicted increased coupling during subsequent exploration of a novel environment. In contrast, somatic-dendritic coupling and SWR recruitment varied with cells' tuning distance to reward location during a goal-learning task. Our results connect SWRs with the stabilization of information processing within CA1 neurons and suggest that these mechanisms may be dynamically biased by behavioral demands.
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Affiliation(s)
- Sebi V Rolotti
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Doctoral Program in Neurobiology and Behavior, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA.
| | - Heike Blockus
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Fraser T Sparks
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - James B Priestley
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Doctoral Program in Neurobiology and Behavior, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, 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; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA.
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44
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Lee JQ, McHugh R, Morgan E, Sutherland RJ, McDonald RJ. Behaviour-driven Arc expression is greater in dorsal than ventral CA1 regardless of task or sex differences. Behav Brain Res 2022; 423:113790. [PMID: 35149121 DOI: 10.1016/j.bbr.2022.113790] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 01/31/2022] [Accepted: 02/06/2022] [Indexed: 11/30/2022]
Abstract
Evidence from genetic, behavioural, anatomical, and physiological study suggests that the hippocampus functionally differs across its longitudinal (dorsoventral or septotemporal) axis. Although, how to best characterize functional and representational differences in the hippocampus across its long axis remains unclear. While some suggest that the hippocampus can be divided into dorsal and ventral subregions that support distinct cognitive functions, others posit that these regions vary in their granularity of representation, wherein spatial-temporal resolution decreases in the ventral (temporal) direction. Importantly, the cognitive and granular hypotheses also make distinct predictions on cellular recruitment dynamics under conditions when animals perform tasks with qualitatively different cognitive-behavioural demands. One interpretation of the cognitive function account implies that dorsal and ventral cellular recruitment differs depending on relevant behavioural demands, while the granularity account suggests similar recruitment dynamics regardless of the nature of the task performed. Here, we quantified cellular recruitment with the immediate early gene (IEG) Arc across the entire longitudinal CA1 axis in female and male rats performing spatial- and fear-guided memory tasks. Our results show that recruitment is greater in dorsal than ventral CA1 regardless of task or sex, and thus support a granular view of hippocampal function across the long axis. We further discuss how future experiments might determine the relative contributions of cognitive function and granularity of representation to neuronal activity dynamics in hippocampal circuits.
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Affiliation(s)
- J Quinn Lee
- Department of Neuroscience, Science Commons, University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 6T5, Canada; Department of Psychiatry, Douglas Hospital Research Centre, McGill University, 6875 Boulevard LaSalle, Verdun, QC H4H 1R3, Canada.
| | - Rebecca McHugh
- Department of Neuroscience, Science Commons, University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 6T5, Canada
| | - Erik Morgan
- Department of Neuroscience, Science Commons, University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 6T5, Canada
| | - Robert J Sutherland
- Department of Neuroscience, Science Commons, University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 6T5, Canada
| | - Robert J McDonald
- Department of Neuroscience, Science Commons, University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 6T5, Canada
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45
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Nyberg N, Duvelle É, Barry C, Spiers HJ. Spatial goal coding in the hippocampal formation. Neuron 2022; 110:394-422. [PMID: 35032426 DOI: 10.1016/j.neuron.2021.12.012] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 10/18/2021] [Accepted: 12/08/2021] [Indexed: 12/22/2022]
Abstract
The mammalian hippocampal formation contains several distinct populations of neurons involved in representing self-position and orientation. These neurons, which include place, grid, head direction, and boundary-vector cells, are thought to collectively instantiate cognitive maps supporting flexible navigation. However, to flexibly navigate, it is necessary to also maintain internal representations of goal locations, such that goal-directed routes can be planned and executed. Although it has remained unclear how the mammalian brain represents goal locations, multiple neural candidates have recently been uncovered during different phases of navigation. For example, during planning, sequential activation of spatial cells may enable simulation of future routes toward the goal. During travel, modulation of spatial cells by the prospective route, or by distance and direction to the goal, may allow maintenance of route and goal-location information, supporting navigation on an ongoing basis. As the goal is approached, an increased activation of spatial cells may enable the goal location to become distinctly represented within cognitive maps, aiding goal localization. Lastly, after arrival at the goal, sequential activation of spatial cells may represent the just-taken route, enabling route learning and evaluation. Here, we review and synthesize these and other evidence for goal coding in mammalian brains, relate the experimental findings to predictions from computational models, and discuss outstanding questions and future challenges.
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Affiliation(s)
- Nils Nyberg
- Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London, UK.
| | - Éléonore Duvelle
- 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 Behavioural Neuroscience, Department of Experimental Psychology, University College London, London, UK.
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46
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Different encoding of reward location in dorsal and intermediate hippocampus. Curr Biol 2022; 32:834-841.e5. [PMID: 35016008 DOI: 10.1016/j.cub.2021.12.024] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 11/05/2021] [Accepted: 12/08/2021] [Indexed: 01/29/2023]
Abstract
Hippocampal place cells fire at specific locations in the environment. They form a cognitive map that encodes spatial relations in the environment, including reward locations.1 As part of this encoding, dorsal CA1 (dCA1) place cells accumulate at reward.2-5 The encoding of learned reward location could vary between the dorsal and intermediate hippocampus, which differ in gene expression and cortical and subcortical connectivity.6 While the dorsal hippocampus is critical for spatial navigation, the involvement of intermediate CA1 (iCA1) in spatial navigation might depend on task complexity7 and learning phase.8-10 The intermediate-to-ventral hippocampus regulates reward-seeking,11-15 but little is known about the involvement in reward-directed navigation. Here, we compared the encoding of learned reward locations in dCA1 and iCA1 during spatial navigation. We used calcium imaging with a head-mounted microscope to track the activity of CA1 cells over multiple days during which mice learned different reward locations. In dCA1, the fraction of active place cells increased in anticipation of reward, but the pool of active cells changed with the reward location. In iCA1, the same cells anticipated multiple reward locations. Our results support a model in which the dCA1 cognitive map incorporates a changing population of cells that encodes reward proximity through increased population activity, while iCA1 provides a reward-predictive code through a dedicated subpopulation. Both of these location-invariant codes persisted over time, and together they provide a dual hippocampal reward location code, assisting goal-directed navigation.16,17.
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Abstract
By linking the past with the future, our memories define our sense of identity. Because human memory engages the conscious realm, its examination has historically been approached from language and introspection and proceeded largely along separate parallel paths in humans and other animals. Here, we first highlight the achievements and limitations of this mind-based approach and make the case for a new brain-based understanding of declarative memory with a focus on hippocampal physiology. Next, we discuss the interleaved nature and common physiological mechanisms of navigation in real and mental spacetime. We suggest that a distinguishing feature of memory types is whether they subserve actions for single or multiple uses. Finally, in contrast to the persisting view of the mind as a highly plastic blank slate ready for the world to make its imprint, we hypothesize that neuronal networks are endowed with a reservoir of neural trajectories, and the challenge faced by the brain is how to select and match preexisting neuronal trajectories with events in the world.
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Affiliation(s)
- György Buzsáki
- Neuroscience Institute and Department of Neurology, NYU Grossman School of Medicine, New York University, New York, NY 10016, USA;
- Center for Neural Science, New York University, New York, NY 10003, USA
| | - Sam McKenzie
- Department of Neurosciences, University of New Mexico, Albuquerque, New Mexico 87131, USA
| | - Lila Davachi
- Department of Psychology, Columbia University, New York, NY 10027, USA
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York 10962, USA
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48
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Jiang WC, Xu S, Dudman JT. Hippocampal representations of foraging trajectories depend upon spatial context. Nat Neurosci 2022; 25:1693-1705. [PMID: 36446934 PMCID: PMC9708565 DOI: 10.1038/s41593-022-01201-7] [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: 01/12/2021] [Accepted: 10/12/2022] [Indexed: 11/30/2022]
Abstract
Animals learn trajectories to rewards in both spatial, navigational contexts and relational, non-navigational contexts. Synchronous reactivation of hippocampal activity is thought to be critical for recall and evaluation of trajectories for learning. Do hippocampal representations differentially contribute to experience-dependent learning of trajectories across spatial and relational contexts? In this study, we trained mice to navigate to a hidden target in a physical arena or manipulate a joystick to a virtual target to collect delayed rewards. In a navigational context, calcium imaging in freely moving mice revealed that synchronous CA1 reactivation was retrospective and important for evaluation of prior navigational trajectories. In a non-navigational context, reactivation was prospective and important for initiation of joystick trajectories, even in the same animals trained in both contexts. Adaptation of trajectories to a new target was well-explained by a common learning algorithm in which hippocampal activity makes dissociable contributions to reinforcement learning computations depending upon spatial context.
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Affiliation(s)
- Wan-Chen Jiang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
| | - Shengjin Xu
- grid.443970.dJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA ,grid.507732.4Present Address: Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Joshua T. Dudman
- grid.443970.dJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
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Benna MK, Fusi S. Place cells may simply be memory cells: Memory compression leads to spatial tuning and history dependence. Proc Natl Acad Sci U S A 2021; 118:e2018422118. [PMID: 34916282 PMCID: PMC8713479 DOI: 10.1073/pnas.2018422118] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/02/2021] [Indexed: 11/18/2022] Open
Abstract
The observation of place cells has suggested that the hippocampus plays a special role in encoding spatial information. However, place cell responses are modulated by several nonspatial variables and reported to be rather unstable. Here, we propose a memory model of the hippocampus that provides an interpretation of place cells consistent with these observations. We hypothesize that the hippocampus is a memory device that takes advantage of the correlations between sensory experiences to generate compressed representations of the episodes that are stored in memory. A simple neural network model that can efficiently compress information naturally produces place cells that are similar to those observed in experiments. It predicts that the activity of these cells is variable and that the fluctuations of the place fields encode information about the recent history of sensory experiences. Place cells may simply be a consequence of a memory compression process implemented in the hippocampus.
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Affiliation(s)
- Marcus K Benna
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027;
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027
- Neurobiology Section, Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027;
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027
- Kavli Institute for Brain Sciences, Columbia University, New York, NY 10027
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50
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Milstein AD, Li Y, Bittner KC, Grienberger C, Soltesz I, Magee JC, Romani S. Bidirectional synaptic plasticity rapidly modifies hippocampal representations. eLife 2021; 10:e73046. [PMID: 34882093 PMCID: PMC8776257 DOI: 10.7554/elife.73046] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 12/08/2021] [Indexed: 11/13/2022] Open
Abstract
Learning requires neural adaptations thought to be mediated by activity-dependent synaptic plasticity. A relatively non-standard form of synaptic plasticity driven by dendritic calcium spikes, or plateau potentials, has been reported to underlie place field formation in rodent hippocampal CA1 neurons. Here, we found that this behavioral timescale synaptic plasticity (BTSP) can also reshape existing place fields via bidirectional synaptic weight changes that depend on the temporal proximity of plateau potentials to pre-existing place fields. When evoked near an existing place field, plateau potentials induced less synaptic potentiation and more depression, suggesting BTSP might depend inversely on postsynaptic activation. However, manipulations of place cell membrane potential and computational modeling indicated that this anti-correlation actually results from a dependence on current synaptic weight such that weak inputs potentiate and strong inputs depress. A network model implementing this bidirectional synaptic learning rule suggested that BTSP enables population activity, rather than pairwise neuronal correlations, to drive neural adaptations to experience.
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Affiliation(s)
- Aaron D Milstein
- Department of Neurosurgery and Stanford Neurosciences Institute, Stanford University School of MedicineStanfordUnited States
- Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical School and Center for Advanced Biotechnology and Medicine, Rutgers UniversityPiscatawayUnited States
| | - Yiding Li
- Howard Hughes Medical Institute, Baylor College of MedicineHoustonUnited States
| | - Katie C Bittner
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
| | | | - Ivan Soltesz
- Department of Neurosurgery and Stanford Neurosciences Institute, Stanford University School of MedicineStanfordUnited States
| | - Jeffrey C Magee
- Howard Hughes Medical Institute, Baylor College of MedicineHoustonUnited States
| | - Sandro Romani
- Howard Hughes Medical Institute, Janelia Research CampusAshburnUnited States
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