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Rich PD, Thiberge SY, Scott BB, Guo C, Tervo DGR, Brody CD, Karpova AY, Daw ND, Tank DW. Magnetic voluntary head-fixation in transgenic rats enables lifespan imaging of hippocampal neurons. Nat Commun 2024; 15:4154. [PMID: 38755205 PMCID: PMC11099169 DOI: 10.1038/s41467-024-48505-9] [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: 08/16/2023] [Accepted: 05/01/2024] [Indexed: 05/18/2024] Open
Abstract
The precise neural mechanisms within the brain that contribute to the remarkable lifetime persistence of memory are not fully understood. Two-photon calcium imaging allows the activity of individual cells to be followed across long periods, but conventional approaches require head-fixation, which limits the type of behavior that can be studied. We present a magnetic voluntary head-fixation system that provides stable optical access to the brain during complex behavior. Compared to previous systems that used mechanical restraint, there are no moving parts and animals can engage and disengage entirely at will. This system is failsafe, easy for animals to use and reliable enough to allow long-term experiments to be routinely performed. Animals completed hundreds of trials per session of an odor discrimination task that required 2-4 s fixations. Together with a reflectance fluorescence collection scheme that increases two-photon signal and a transgenic Thy1-GCaMP6f rat line, we are able to reliably image the cellular activity in the hippocampus during behavior over long periods (median 6 months), allowing us track the same neurons over a large fraction of animals' lives (up to 19 months).
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Affiliation(s)
- P Dylan Rich
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
| | | | - Benjamin B Scott
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Caiying Guo
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - D Gowanlock R Tervo
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Howard Hughes Medical Institute, Princeton University, Princeton, NJ, USA
| | - Alla Y Karpova
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Nathaniel D Daw
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Psychology, Princeton University, Princeton, NJ, USA
| | - David W Tank
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
- Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, NJ, USA.
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA.
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2
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Gonzales DL, Khan HF, Keri HVS, Yadav S, Steward C, Muller LE, Pluta SR, Jayant K. A Translaminar Spacetime Code Supports Touch-Evoked Traveling Waves. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.09.593381. [PMID: 38766232 PMCID: PMC11100787 DOI: 10.1101/2024.05.09.593381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Linking sensory-evoked traveling waves to underlying circuit patterns is critical to understanding the neural basis of sensory perception. To form this link, we performed simultaneous electrophysiology and two-photon calcium imaging through transparent NeuroGrids and mapped touch-evoked cortical traveling waves and their underlying microcircuit dynamics. In awake mice, both passive and active whisker touch elicited traveling waves within and across barrels, with a fast early component followed by a variable late wave that lasted hundreds of milliseconds post-stimulus. Strikingly, late-wave dynamics were modulated by stimulus value and correlated with task performance. Mechanistically, the late wave component was i) modulated by motor feedback, ii) complemented by a sparse ensemble pattern across layer 2/3, which a balanced-state network model reconciled via inhibitory stabilization, and iii) aligned to regenerative Layer-5 apical dendritic Ca 2+ events. Our results reveal a translaminar spacetime pattern organized by cortical feedback in the sensory cortex that supports touch-evoked traveling waves. GRAPHICAL ABSTRACT AND HIGHLIGHTS Whisker touch evokes both early- and late-traveling waves in the barrel cortex over 100's of millisecondsReward reinforcement modulates wave dynamics Late wave emergence coincides with network sparsity in L23 and time-locked L5 dendritic Ca 2+ spikes Experimental and computational results link motor feedback to distinct translaminar spacetime patterns.
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3
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Nguyen D, Wang G, Gu Y. The medial entorhinal cortex encodes multisensory spatial information. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.09.574924. [PMID: 38313299 PMCID: PMC10836072 DOI: 10.1101/2024.01.09.574924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Animals employ spatial information in multisensory modalities to navigate their natural environments. However, it is unclear whether the brain encodes such information in separate cognitive maps or integrates all into a single, universal map. We addressed this question in the microcircuit of the medial entorhinal cortex (MEC), a cognitive map of space. Using cellular-resolution calcium imaging, we examined the MEC of mice navigating virtual reality tracks, where visual and auditory cues provided comparable spatial information. We uncovered two cell types: "unimodality cells" and "multimodality cells". The unimodality cells specifically represent either auditory or visual spatial information. They are anatomically intermingled and maintain sensory preferences across multiple tracks and behavioral states. The multimodality cells respond to both sensory modalities with their responses shaped differentially by auditory and visual information. Thus, the MEC enables accurate spatial encoding during multisensory navigation by computing spatial information in different sensory modalities and generating distinct maps.
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Affiliation(s)
- Duc Nguyen
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- Current address: Center of Neural Science, New York University, New York, NY, USA
| | - Garret Wang
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Yi Gu
- Spatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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4
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Kane GA, Senne RA, Scott BB. Rat movements reflect internal decision dynamics in an evidence accumulation task. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.11.556575. [PMID: 37745309 PMCID: PMC10515875 DOI: 10.1101/2023.09.11.556575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Perceptual decision-making involves multiple cognitive processes, including accumulation of sensory evidence, planning, and executing a motor action. How these processes are intertwined is unclear; some models assume that decision-related processes precede motor execution, whereas others propose that movements reflecting on-going decision processes occur before commitment to a choice. Here we develop and apply two complementary methods to study the relationship between decision processes and the movements leading up to a choice. The first is a free response pulse-based evidence accumulation task, in which stimuli continue until choice is reported. The second is a motion-based drift diffusion model (mDDM), in which movement variables from video pose estimation constrain decision parameters on a trial-by-trial basis. We find the mDDM provides a better model fit to rats' decisions in the free response accumulation task than traditional DDM models. Interestingly, on each trial we observed a period of time, prior to choice, that was characterized by head immobility. The length of this period was positively correlated with the rats' decision bounds and stimuli presented during this period had the greatest impact on choice. Together these results support a model in which internal decision dynamics are reflected in movements and demonstrate that inclusion of movement parameters improves the performance of diffusion-to-bound decision models.
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Affiliation(s)
- Gary A. Kane
- Department of Psychological and Brain Sciences and Center for Systems Neuroscience, Boston University, Boston MA
| | - Ryan A. Senne
- Graduate Program in Neuroscience, Boston University, Boston MA
| | - Benjamin B. Scott
- Department of Psychological and Brain Sciences and Center for Systems Neuroscience, Boston University, Boston MA
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5
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Kira S, Safaai H, Morcos AS, Panzeri S, Harvey CD. A distributed and efficient population code of mixed selectivity neurons for flexible navigation decisions. Nat Commun 2023; 14:2121. [PMID: 37055431 PMCID: PMC10102117 DOI: 10.1038/s41467-023-37804-2] [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: 12/07/2021] [Accepted: 03/30/2023] [Indexed: 04/15/2023] Open
Abstract
Decision-making requires flexibility to rapidly switch one's actions in response to sensory stimuli depending on information stored in memory. We identified cortical areas and neural activity patterns underlying this flexibility during virtual navigation, where mice switched navigation toward or away from a visual cue depending on its match to a remembered cue. Optogenetics screening identified V1, posterior parietal cortex (PPC), and retrosplenial cortex (RSC) as necessary for accurate decisions. Calcium imaging revealed neurons that can mediate rapid navigation switches by encoding a mixture of a current and remembered visual cue. These mixed selectivity neurons emerged through task learning and predicted the mouse's choices by forming efficient population codes before correct, but not incorrect, choices. They were distributed across posterior cortex, even V1, and were densest in RSC and sparsest in PPC. We propose flexibility in navigation decisions arises from neurons that mix visual and memory information within a visual-parietal-retrosplenial network.
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Affiliation(s)
- Shinichiro Kira
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Houman Safaai
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Ari S Morcos
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Stefano Panzeri
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto, Italy
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
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6
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Diekmann N, Vijayabaskaran S, Zeng X, Kappel D, Menezes MC, Cheng S. CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning. Front Neuroinform 2023; 17:1134405. [PMID: 36970657 PMCID: PMC10033763 DOI: 10.3389/fninf.2023.1134405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 02/17/2023] [Indexed: 03/11/2023] Open
Abstract
Reinforcement learning (RL) has become a popular paradigm for modeling animal behavior, analyzing neuronal representations, and studying their emergence during learning. This development has been fueled by advances in understanding the role of RL in both the brain and artificial intelligence. However, while in machine learning a set of tools and standardized benchmarks facilitate the development of new methods and their comparison to existing ones, in neuroscience, the software infrastructure is much more fragmented. Even if sharing theoretical principles, computational studies rarely share software frameworks, thereby impeding the integration or comparison of different results. Machine learning tools are also difficult to port to computational neuroscience since the experimental requirements are usually not well aligned. To address these challenges we introduce CoBeL-RL, a closed-loop simulator of complex behavior and learning based on RL and deep neural networks. It provides a neuroscience-oriented framework for efficiently setting up and running simulations. CoBeL-RL offers a set of virtual environments, e.g., T-maze and Morris water maze, which can be simulated at different levels of abstraction, e.g., a simple gridworld or a 3D environment with complex visual stimuli, and set up using intuitive GUI tools. A range of RL algorithms, e.g., Dyna-Q and deep Q-network algorithms, is provided and can be easily extended. CoBeL-RL provides tools for monitoring and analyzing behavior and unit activity, and allows for fine-grained control of the simulation via interfaces to relevant points in its closed-loop. In summary, CoBeL-RL fills an important gap in the software toolbox of computational neuroscience.
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Affiliation(s)
- Nicolas Diekmann
- Faculty for Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Sandhiya Vijayabaskaran
- Faculty for Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
| | - Xiangshuai Zeng
- Faculty for Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - David Kappel
- Faculty for Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
| | - Matheus Chaves Menezes
- Laboratory of Artificial Cognition Methods for Optimisation and Robotics, Federal University of Maranhão, São Luís, Brazil
| | - Sen Cheng
- Faculty for Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
- *Correspondence: Sen Cheng
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7
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Tiganj Z, Singh I, Esfahani ZG, Howard MW. Scanning a compressed ordered representation of the future. J Exp Psychol Gen 2022; 151:3082-3096. [PMID: 35913876 PMCID: PMC9670103 DOI: 10.1037/xge0001243] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Several authors have suggested a deep symmetry between the psychological processes that underlie our ability to remember the past and make predictions about the future. The judgment of recency (JOR) task measures temporal order judgments for the past by presenting pairs of probe stimuli; participants choose the probe that was presented more recently. We performed a short-term relative JOR task and introduced a novel judgment of imminence (JOI) task to study temporal order judgments for the future. In the JOR task, participants were presented with a sequence of stimuli and asked to choose which of two probe stimuli was presented closer to the present. In the JOI task, participants were trained on a probabilistic sequence. After training, the sequence was interrupted with probe stimuli. Participants were asked to choose which of two probe stimuli was expected to be presented closer to the present. Replicating prior work on JOR, we found that RT results supported a backward self-terminating search model operating on a temporally organized representation of the past. We also showed that RT distributions are consistent with this model and that the temporally organized representation is compressed. Critically, results for the JOI task probing expectations of the future suggest a forward self-terminating search model operating on a temporally organized representation of the future. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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8
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Arlt C, Barroso-Luque R, Kira S, Bruno CA, Xia N, Chettih SN, Soares S, Pettit NL, Harvey CD. Cognitive experience alters cortical involvement in goal-directed navigation. eLife 2022; 11:76051. [PMID: 35735909 PMCID: PMC9259027 DOI: 10.7554/elife.76051] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 06/22/2022] [Indexed: 11/29/2022] Open
Abstract
Neural activity in the mammalian cortex has been studied extensively during decision tasks, and recent work aims to identify under what conditions cortex is actually necessary for these tasks. We discovered that mice with distinct cognitive experiences, beyond sensory and motor learning, use different cortical areas and neural activity patterns to solve the same navigation decision task, revealing past learning as a critical determinant of whether cortex is necessary for goal-directed navigation. We used optogenetics and calcium imaging to study the necessity and neural activity of multiple cortical areas in mice with different training histories. Posterior parietal cortex and retrosplenial cortex were mostly dispensable for accurate performance of a simple navigation task. In contrast, these areas were essential for the same simple task when mice were previously trained on complex tasks with delay periods or association switches. Multiarea calcium imaging showed that, in mice with complex-task experience, single-neuron activity had higher selectivity and neuron–neuron correlations were weaker, leading to codes with higher task information. Therefore, past experience is a key factor in determining whether cortical areas have a causal role in goal-directed navigation.
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Affiliation(s)
- Charlotte Arlt
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | | | - Shinichiro Kira
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | - Carissa A Bruno
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | - Ningjing Xia
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | - Selmaan N Chettih
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | - Sofia Soares
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | - Noah L Pettit
- Department of Neurobiology, Harvard Medical School, Boston, United States
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9
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Pinto L, Tank DW, Brody CD. Multiple timescales of sensory-evidence accumulation across the dorsal cortex. eLife 2022; 11:e70263. [PMID: 35708483 PMCID: PMC9203055 DOI: 10.7554/elife.70263] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 05/27/2022] [Indexed: 11/13/2022] Open
Abstract
Cortical areas seem to form a hierarchy of intrinsic timescales, but the relevance of this organization for cognitive behavior remains unknown. In particular, decisions requiring the gradual accrual of sensory evidence over time recruit widespread areas across this hierarchy. Here, we tested the hypothesis that this recruitment is related to the intrinsic integration timescales of these widespread areas. We trained mice to accumulate evidence over seconds while navigating in virtual reality and optogenetically silenced the activity of many cortical areas during different brief trial epochs. We found that the inactivation of all tested areas affected the evidence-accumulation computation. Specifically, we observed distinct changes in the weighting of sensory evidence occurring during and before silencing, such that frontal inactivations led to stronger deficits on long timescales than posterior cortical ones. Inactivation of a subset of frontal areas also led to moderate effects on behavioral processes beyond evidence accumulation. Moreover, large-scale cortical Ca2+ activity during task performance displayed different temporal integration windows. Our findings suggest that the intrinsic timescale hierarchy of distributed cortical areas is an important component of evidence-accumulation mechanisms.
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Affiliation(s)
- Lucas Pinto
- Department of Neuroscience, Northwestern UniversityChicagoUnited States
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
| | - David W Tank
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
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10
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Hattori R, Komiyama T. Context-dependent persistency as a coding mechanism for robust and widely distributed value coding. Neuron 2022; 110:502-515.e11. [PMID: 34818514 PMCID: PMC8813889 DOI: 10.1016/j.neuron.2021.11.001] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 08/26/2021] [Accepted: 11/01/2021] [Indexed: 02/04/2023]
Abstract
Task-related information is widely distributed across the brain with different coding properties, such as persistency. We found in mice that coding persistency of action history and value was variable across areas, learning phases, and task context, with the highest persistency in the retrosplenial cortex of expert mice performing value-based decisions where history needs to be maintained across trials. Persistent coding also emerged in artificial networks trained to perform mouse-like reinforcement learning. Persistency allows temporally untangled value representations in neuronal manifolds where population activity exhibits cyclic trajectories that transition along the value axis after action outcomes, collectively forming cylindrical dynamics. Simulations indicated that untangled persistency facilitates robust value retrieval by downstream networks. Even leakage of persistently maintained value through non-specific connectivity could contribute to the brain-wide distributed value coding with different levels of persistency. These results reveal that context-dependent, untangled persistency facilitates reliable signal coding and its distribution across the brain.
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Affiliation(s)
- Ryoma Hattori
- Neurobiology Section, Center for Neural Circuits and Behavior, Department of Neurosciences, and Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA 90093, USA.
| | - Takaki Komiyama
- Neurobiology Section, Center for Neural Circuits and Behavior, Department of Neurosciences, and Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA 90093, USA.
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11
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Bucci-Mansilla G, Vicencio-Jimenez S, Concha-Miranda M, Loyola-Navarro R. Challenging Paradigms Through Ecological Neuroscience: Lessons From Visual Models. Front Neurosci 2021; 15:758388. [PMID: 34858130 PMCID: PMC8631428 DOI: 10.3389/fnins.2021.758388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 10/18/2021] [Indexed: 11/30/2022] Open
Affiliation(s)
- Giuliana Bucci-Mansilla
- Neurosystems Laboratory, Department of Neuroscience and Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile.,Ecological Cognitive Neuroscience Group, Santiago, Chile
| | - Sergio Vicencio-Jimenez
- The Center for Hearing and Balance, Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Miguel Concha-Miranda
- Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Rocio Loyola-Navarro
- Neuroscience, Cognition and Educational Lab, Center for Advanced Research in Education, Institute of Education, Universidad de Chile, Santiago, Chile.,Departamento de Educación Diferencial, Facultad de Filosofía y Educación, Universidad Metropolitana de Ciencias de la Educación, Santiago, Chile
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12
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Nieh EH, Schottdorf M, Freeman NW, Low RJ, Lewallen S, Koay SA, Pinto L, Gauthier JL, Brody CD, Tank DW. Geometry of abstract learned knowledge in the hippocampus. Nature 2021; 595:80-84. [PMID: 34135512 PMCID: PMC9549979 DOI: 10.1038/s41586-021-03652-7] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 05/18/2021] [Indexed: 02/05/2023]
Abstract
Hippocampal neurons encode physical variables1-7 such as space1 or auditory frequency6 in cognitive maps8. In addition, functional magnetic resonance imaging studies in humans have shown that the hippocampus can also encode more abstract, learned variables9-11. However, their integration into existing neural representations of physical variables12,13 is unknown. Here, using two-photon calcium imaging, we show that individual neurons in the dorsal hippocampus jointly encode accumulated evidence with spatial position in mice performing a decision-making task in virtual reality14-16. Nonlinear dimensionality reduction13 showed that population activity was well-described by approximately four to six latent variables, which suggests that neural activity is constrained to a low-dimensional manifold. Within this low-dimensional space, both physical and abstract variables were jointly mapped in an orderly manner, creating a geometric representation that we show is similar across mice. The existence of conjoined cognitive maps suggests that the hippocampus performs a general computation-the creation of task-specific low-dimensional manifolds that contain a geometric representation of learned knowledge.
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Affiliation(s)
- Edward H. Nieh
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA
| | - Manuel Schottdorf
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA
| | - Nicolas W. Freeman
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA
| | - Ryan J. Low
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA
| | - Sam Lewallen
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA
| | - Sue Ann Koay
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA
| | - Lucas Pinto
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA,Present address: Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Jeffrey L. Gauthier
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA
| | - Carlos D. Brody
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA,Department of Molecular Biology, Princeton University, Princeton, NJ, 08544, USA,Howard Hughes Medical Institute, Princeton University, Princeton, NJ, 08544, USA
| | - David W. Tank
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA,Department of Molecular Biology, Princeton University, Princeton, NJ, 08544, USA,Bezos Center for Neural Dynamics, Princeton University, Princeton, NJ, 08544, USA
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13
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Koay SA, Thiberge S, Brody CD, Tank DW. Amplitude modulations of cortical sensory responses in pulsatile evidence accumulation. eLife 2020; 9:e60628. [PMID: 33263278 PMCID: PMC7811404 DOI: 10.7554/elife.60628] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 11/30/2020] [Indexed: 12/27/2022] Open
Abstract
How does the brain internally represent a sequence of sensory information that jointly drives a decision-making behavior? Studies of perceptual decision-making have often assumed that sensory cortices provide noisy but otherwise veridical sensory inputs to downstream processes that accumulate and drive decisions. However, sensory processing in even the earliest sensory cortices can be systematically modified by various external and internal contexts. We recorded from neuronal populations across posterior cortex as mice performed a navigational decision-making task based on accumulating randomly timed pulses of visual evidence. Even in V1, only a small fraction of active neurons had sensory-like responses time-locked to each pulse. Here, we focus on how these 'cue-locked' neurons exhibited a variety of amplitude modulations from sensory to cognitive, notably by choice and accumulated evidence. These task-related modulations affected a large fraction of cue-locked neurons across posterior cortex, suggesting that future models of behavior should account for such influences.
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Affiliation(s)
- Sue Ann Koay
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
| | - Stephan Thiberge
- Bezos Center for Neural Circuit Dynamics, Princeton UniversityPrincetonUnited States
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
- Howard Hughes Medical Institute, Princeton UniversityPrincetonUnited States
| | - David W Tank
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
- Bezos Center for Neural Circuit Dynamics, Princeton UniversityPrincetonUnited States
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