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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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2
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Vöröslakos M, Zhang Y, McClain K, Huszár R, Rothstein A, Buzsáki G. ThermoMaze: A behavioral paradigm for readout of immobility-related brain events. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.25.550518. [PMID: 37546818 PMCID: PMC10402115 DOI: 10.1101/2023.07.25.550518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Brain states fluctuate between exploratory and consummatory phases of behavior. These state changes affect both internal computation and the organism's responses to sensory inputs. Understanding neuronal mechanisms supporting exploratory and consummatory states and their switching requires experimental control of behavioral shifts and collecting sufficient amounts of brain data. To achieve this goal, we developed the ThermoMaze, which exploits the animal's natural warmth-seeking homeostatic behavior. By decreasing the floor temperature and selectively heating unmarked areas, mice avoid the aversive state by exploring the maze and finding the warm spot. In its design, the ThermoMaze is analogous to the widely used water maze but without the inconvenience of a wet environment and, therefore, allows the collection of physiological data in many trials. We combined the ThermoMaze with electrophysiology recording, and report that spiking activity of hippocampal CA1 neurons during sharp-wave ripple events encode the position of the animal. Thus, place-specific firing is not confined to locomotion and associated theta oscillations but persist during waking immobility and sleep at the same location. The ThermoMaze will allow for detailed studies of brain correlates of immobility, preparatory-consummatory transitions and open new options for studying behavior-mediated temperature homeostasis.
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Affiliation(s)
- Mihály Vöröslakos
- Neuroscience Institute and New York University, New York, NY 10016, USA
| | - Yunchang Zhang
- Neuroscience Institute and New York University, New York, NY 10016, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Kathryn McClain
- Neuroscience Institute and New York University, New York, NY 10016, USA
| | - Roman Huszár
- Neuroscience Institute and New York University, New York, NY 10016, USA
| | - Aryeh Rothstein
- Neuroscience Institute and New York University, New York, NY 10016, USA
| | - György Buzsáki
- Neuroscience Institute and New York University, New York, NY 10016, USA
- Department of Neurology, School of Medicine, New York University, New York, NY 10016, USA
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3
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Chen HT, van der Meer MAA. Paradoxical replay can protect contextual task representations from destructive interference when experience is unbalanced. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.09.593332. [PMID: 38766204 PMCID: PMC11100794 DOI: 10.1101/2024.05.09.593332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Experience replay is a powerful mechanism to learn efficiently from limited experience. Despite several decades of compelling experimental results, the factors that determine which experiences are selected for replay remain unclear. A particular challenge for current theories is that on tasks that feature unbalanced experience, rats paradoxically replay the less-experienced trajectory. To understand why, we simulated a feedforward neural network with two regimes: rich learning (structured representations tailored to task demands) and lazy learning (unstructured, task-agnostic representations). Rich, but not lazy, representations degraded following unbalanced experience, an effect that could be reversed with paradoxical replay. To test if this computational principle can account for the experimental data, we examined the relationship between paradoxical replay and learned task representations in the rat hippocampus. Strikingly, we found a strong association between the richness of learned task representations and the paradoxicality of replay. Taken together, these results suggest that paradoxical replay specifically serves to protect rich representations from the destructive effects of unbalanced experience, and more generally demonstrate a novel interaction between the nature of task representations and the function of replay in artificial and biological systems.
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Affiliation(s)
- Hung-Tu Chen
- Department of Psychological & Brain Sciences, Dartmouth College, Hanover, NH 03755
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4
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Maboudi K, Giri B, Miyawaki H, Kemere C, Diba K. Retuning of hippocampal representations during sleep. Nature 2024; 629:630-638. [PMID: 38720085 DOI: 10.1038/s41586-024-07397-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] [Received: 10/21/2022] [Accepted: 04/09/2024] [Indexed: 05/18/2024]
Abstract
Hippocampal representations that underlie spatial memory undergo continuous refinement following formation1. Here, to track the spatial tuning of neurons dynamically during offline states, we used a new Bayesian learning approach based on the spike-triggered average decoded position in ensemble recordings from freely moving rats. Measuring these tunings, we found spatial representations within hippocampal sharp-wave ripples that were stable for hours during sleep and were strongly aligned with place fields initially observed during maze exploration. These representations were explained by a combination of factors that included preconfigured structure before maze exposure and representations that emerged during θ-oscillations and awake sharp-wave ripples while on the maze, revealing the contribution of these events in forming ensembles. Strikingly, the ripple representations during sleep predicted the future place fields of neurons during re-exposure to the maze, even when those fields deviated from previous place preferences. By contrast, we observed tunings with poor alignment to maze place fields during sleep and rest before maze exposure and in the later stages of sleep. In sum, the new decoding approach allowed us to infer and characterize the stability and retuning of place fields during offline periods, revealing the rapid emergence of representations following new exploration and the role of sleep in the representational dynamics of the hippocampus.
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Affiliation(s)
- Kourosh Maboudi
- Dept of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
- Dept of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Bapun Giri
- Dept of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
- Dept of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Hiroyuki Miyawaki
- Dept of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
- Osaka Metropolitan University, Osaka, Japan
| | - Caleb Kemere
- Dept of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Kamran Diba
- Dept of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA.
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, USA.
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5
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Seenivasan P, Basak R, Narayanan R. Cross-strata co-occurrence of ripples with theta-frequency oscillations in the hippocampus of foraging rats. J Physiol 2024; 602:2315-2341. [PMID: 38654581 PMCID: PMC7615956 DOI: 10.1113/jp284629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 04/04/2024] [Indexed: 04/26/2024] Open
Abstract
Brain rhythms have been postulated to play central roles in animal cognition. A prominently reported dichotomy of hippocampal rhythms links theta-frequency oscillations (4-12 Hz) and ripples (120-250 Hz) exclusively to preparatory and consummatory behaviours, respectively. However, because of the differential power expression of these two signals across hippocampal strata, such exclusivity requires validation through analyses of simultaneous multi-strata recordings. We assessed co-occurrence of theta-frequency oscillations with ripples in multi-channel recordings of extracellular potentials across hippocampal strata from foraging rats. We detected all ripple events from an identified stratum pyramidale (SP) channel. We then defined theta epochs based on theta oscillations detected from the stratum lacunosum-moleculare (SLM) or the stratum radiatum (SR). We found ∼20% of ripple events (in SP) to co-occur with theta epochs identified from SR/SLM channels, defined here as theta ripples. Strikingly, when theta epochs were instead identified from the SP channel, such co-occurrences were significantly reduced because of a progressive reduction in theta power along the SLM-SR-SP axis. Behaviourally, we found most theta ripples to occur during immobile periods, with comparable theta power during exploratory and immobile theta epochs. Furthermore, the progressive reduction in theta power along the SLM-SR-SP axis was common to exploratory and immobile periods. Finally, we found a strong theta-phase preference of theta ripples within the fourth quadrant [3π/2 - 2π] of the associated theta oscillation. The prevalence of theta ripples expands the potential roles of ripple-frequency oscillations to span the continuum of encoding, retrieval and consolidation, achieved through interactions with theta oscillations. KEY POINTS: The brain manifests oscillations in recorded electrical potentials, with different frequencies of oscillation associated with distinct behavioural states. A prominently reported dichotomy assigns theta-frequency oscillations (4-12 Hz) and ripples (120-250 Hz) recorded in the hippocampus to be exclusively associated with preparatory and consummatory behaviours, respectively. Our multi-strata recordings from the rodent hippocampus coupled with cross-strata analyses provide direct quantitative evidence for the occurrence of ripple events nested within theta oscillations. These results highlight the need for an analysis pipeline that explicitly accounts for the specific strata where individual oscillatory power is high, in analysing simultaneously recorded data from multiple strata. Our observations open avenues for investigations involving cross-strata interactions between theta oscillations and ripples across different behavioural states.
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Affiliation(s)
- Pavithraa Seenivasan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
| | - Reshma Basak
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
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Cortese A, Kawato M. The cognitive reality monitoring network and theories of consciousness. Neurosci Res 2024; 201:31-38. [PMID: 38316366 DOI: 10.1016/j.neures.2024.01.007] [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: 12/26/2023] [Revised: 01/17/2024] [Accepted: 01/17/2024] [Indexed: 02/07/2024]
Abstract
Theories of consciousness abound. However, it is difficult to arbitrate reliably among competing theories because they target different levels of neural and cognitive processing or anatomical loci, and only some were developed with computational models in mind. In particular, theories of consciousness need to fully address the three levels of understanding of the brain proposed by David Marr: computational theory, algorithms and hardware. Most major theories refer to only one or two levels, often indirectly. The cognitive reality monitoring network (CRMN) model is derived from computational theories of mixture-of-experts architecture, hierarchical reinforcement learning and generative/inference computing modules, addressing all three levels of understanding. A central feature of the CRMN is the mapping of a gating network onto the prefrontal cortex, making it a prime coding circuit involved in monitoring the accuracy of one's mental states and distinguishing them from external reality. Because the CRMN builds on the hierarchical and layer structure of the cerebral cortex, it may connect research and findings across species, further enabling concrete computational models of consciousness with new, explicitly testable hypotheses. In sum, we discuss how the CRMN model can help further our understanding of the nature and function of consciousness.
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Affiliation(s)
- Aurelio Cortese
- Computational Neuroscience Labs, ATR Institute International, Kyoto 619-0228, Japan.
| | - Mitsuo Kawato
- Computational Neuroscience Labs, ATR Institute International, Kyoto 619-0228, Japan; XNef, Kyoto 619-0288, Japan.
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7
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Yang Y, Leopold DA, Duyn JH, Liu X. Hippocampal replay sequence governed by spontaneous brain-wide dynamics. PNAS NEXUS 2024; 3:pgae078. [PMID: 38562584 PMCID: PMC10983782 DOI: 10.1093/pnasnexus/pgae078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 02/01/2024] [Indexed: 04/04/2024]
Abstract
Neurons in the hippocampus exhibit spontaneous spiking activity during rest that appears to recapitulate previously experienced events. While this replay activity is frequently linked to memory consolidation and learning, the underlying mechanisms are not well understood. Recent large-scale neural recordings in mice have demonstrated that resting-state spontaneous activity is expressed as quasi-periodic cascades of spiking activity that pervade the forebrain, with each cascade engaging a high proportion of recorded neurons. Hippocampal ripples are known to be coordinated with cortical dynamics; however, less is known about the occurrence of replay activity relative to other brain-wide spontaneous events. Here we analyzed responses across the mouse brain to multiple viewings of natural movies, as well as subsequent patterns of neural activity during rest. We found that hippocampal neurons showed time-selectivity, with individual neurons responding consistently during particular moments of the movie. During rest, the population of time-selective hippocampal neurons showed both forward and time-reversed replay activity that matched the sequence observed in the movie. Importantly, these replay events were strongly time-locked to brain-wide spiking cascades, with forward and time-reversed replay activity associated with distinct cascade types. Thus, intrinsic hippocampal replay activity is temporally structured according to large-scale spontaneous physiology affecting areas throughout the forebrain. These findings shed light on the coordination between hippocampal and cortical circuits thought to be critical for memory consolidation.
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Affiliation(s)
- Yifan Yang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - David A Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, and National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
- Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiao Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA 16802, USA
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8
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Pezzulo G, D'Amato L, Mannella F, Priorelli M, Van de Maele T, Stoianov IP, Friston K. Neural representation in active inference: Using generative models to interact with-and understand-the lived world. Ann N Y Acad Sci 2024; 1534:45-68. [PMID: 38528782 DOI: 10.1111/nyas.15118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ generative models to minimize the discrepancy between predictions and observations (as scored with variational free energy). The ensuing analysis suggests that the brain learns generative models to navigate the world adaptively, not (or not solely) to understand it. Different living organisms may possess an array of generative models, spanning from those that support action-perception cycles to those that underwrite planning and imagination; namely, from explicit models that entail variables for predicting concurrent sensations, like objects, faces, or people-to action-oriented models that predict action outcomes. It then elucidates how generative models and belief dynamics might link to neural representation and the implications of different types of generative models for understanding an agent's cognitive capabilities in relation to its ecological niche. The paper concludes with open questions regarding the evolution of generative models and the development of advanced cognitive abilities-and the gradual transition from pragmatic to detached neural representations. The analysis on offer foregrounds the diverse roles that generative models play in cognitive processes and the evolution of neural representation.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Leo D'Amato
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
- Polytechnic University of Turin, Turin, Italy
| | - Francesco Mannella
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Matteo Priorelli
- Institute of Cognitive Sciences and Technologies, National Research Council, Padua, Italy
| | - Toon Van de Maele
- IDLab, Department of Information Technology, Ghent University - imec, Ghent, Belgium
| | - Ivilin Peev Stoianov
- Institute of Cognitive Sciences and Technologies, National Research Council, Padua, Italy
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK
- VERSES Research Lab, Los Angeles, California, USA
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9
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Yang W, Sun C, Huszár R, Hainmueller T, Kiselev K, Buzsáki G. Selection of experience for memory by hippocampal sharp wave ripples. Science 2024; 383:1478-1483. [PMID: 38547293 PMCID: PMC11068097 DOI: 10.1126/science.adk8261] [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: 09/12/2023] [Accepted: 02/23/2024] [Indexed: 04/02/2024]
Abstract
Experiences need to be tagged during learning for further consolidation. However, neurophysiological mechanisms that select experiences for lasting memory are not known. By combining large-scale neural recordings in mice with dimensionality reduction techniques, we observed that successive maze traversals were tracked by continuously drifting populations of neurons, providing neuronal signatures of both places visited and events encountered. When the brain state changed during reward consumption, sharp wave ripples (SPW-Rs) occurred on some trials, and their specific spike content decoded the trial blocks that surrounded them. During postexperience sleep, SPW-Rs continued to replay those trial blocks that were reactivated most frequently during waking SPW-Rs. Replay content of awake SPW-Rs may thus provide a neurophysiological tagging mechanism to select aspects of experience that are preserved and consolidated for future use.
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Affiliation(s)
- Wannan Yang
- Neuroscience Institute and Department of Neurology, NYU Grossman School of Medicine, New York University, New York City, NY, USA
- Center for Neural Science, New York University, New York City, NY, USA
| | - Chen Sun
- Mila - Quebec AI Institute, Montréal, Quebec, Canada
| | - Roman Huszár
- Neuroscience Institute and Department of Neurology, NYU Grossman School of Medicine, New York University, New York City, NY, USA
- Center for Neural Science, New York University, New York City, NY, USA
| | - Thomas Hainmueller
- Neuroscience Institute and Department of Neurology, NYU Grossman School of Medicine, New York University, New York City, NY, USA
- Department of Psychiatry, New York University Langone Medical Center, New York City, NY, USA
| | - Kirill Kiselev
- Center for Neural Science, New York University, New York City, NY, USA
| | - György Buzsáki
- Neuroscience Institute and Department of Neurology, NYU Grossman School of Medicine, New York University, New York City, NY, USA
- Center for Neural Science, New York University, New York City, NY, USA
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Hoffman C, Cheng J, Morales R, Ji D, Dabaghian Y. Altered patterning of neural activity in a tauopathy mouse model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.23.586417. [PMID: 38585991 PMCID: PMC10996513 DOI: 10.1101/2024.03.23.586417] [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
Alzheimer's disease (AD) is a complex neurodegenerative condition that manifests at multiple levels and involves a spectrum of abnormalities ranging from the cellular to cognitive. Here, we investigate the impact of AD-related tau-pathology on hippocampal circuits in mice engaged in spatial navigation, and study changes of neuronal firing and dynamics of extracellular fields. While most studies are based on analyzing instantaneous or time-averaged characteristics of neuronal activity, we focus on intermediate timescales-spike trains and waveforms of oscillatory potentials, which we consider as single entities. We find that, in healthy mice, spike arrangements and wave patterns (series of crests or troughs) are coupled to the animal's location, speed, and acceleration. In contrast, in tau-mice, neural activity is structurally disarrayed: brainwave cadence is detached from locomotion, spatial selectivity is lost, the spike flow is scrambled. Importantly, these alterations start early and accumulate with age, which exposes progressive disinvolvement the hippocampus circuit in spatial navigation. These features highlight qualitatively different neurodynamics than the ones provided by conventional analyses, and are more salient, thus revealing a new level of the hippocampal circuit disruptions.
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Affiliation(s)
- C Hoffman
- Department of Neurology, The University of Texas McGovern Medical School, 6431 Fannin St, Houston, TX 77030
| | - J Cheng
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030
| | - R Morales
- Department of Neurology, The University of Texas McGovern Medical School, 6431 Fannin St, Houston, TX 77030
| | - D Ji
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030
| | - Y Dabaghian
- Department of Neurology, The University of Texas McGovern Medical School, 6431 Fannin St, Houston, TX 77030
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Deceuninck L, Kloosterman F. Disruption of awake sharp-wave ripples does not affect memorization of locations in repeated-acquisition spatial memory tasks. eLife 2024; 13:e84004. [PMID: 38530125 PMCID: PMC11018343 DOI: 10.7554/elife.84004] [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: 10/06/2022] [Accepted: 03/25/2024] [Indexed: 03/27/2024] Open
Abstract
Storing and accessing memories is required to successfully perform day-to-day tasks, for example for engaging in a meaningful conversation. Previous studies in both rodents and primates have correlated hippocampal cellular activity with behavioral expression of memory. A key role has been attributed to awake hippocampal replay - a sequential reactivation of neurons representing a trajectory through space. However, it is unclear if awake replay impacts immediate future behavior, gradually creates and stabilizes long-term memories over a long period of time (hours and longer), or enables the temporary memorization of relevant events at an intermediate time scale (seconds to minutes). In this study, we aimed to address the uncertainty around the timeframe of impact of awake replay by collecting causal evidence from behaving rats. We detected and disrupted sharp wave ripples (SWRs) - signatures of putative replay events - using electrical stimulation of the ventral hippocampal commissure in rats that were trained on three different spatial memory tasks. In each task, rats were required to memorize a new set of locations in each trial or each daily session. Interestingly, the rats performed equally well with or without SWR disruptions. These data suggest that awake SWRs - and potentially replay - does not affect the immediate behavior nor the temporary memorization of relevant events at a short timescale that are required to successfully perform the spatial tasks. Based on these results, we hypothesize that the impact of awake replay on memory and behavior is long-term and cumulative over time.
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Affiliation(s)
- Lies Deceuninck
- KU Leuven, Department of Physics and Astronomy, Soft Matter and BiophysicsHeverleeBelgium
- NERF-NeuroElectronics Research Flanders, Kloosterman LabHeverleeBelgium
| | - Fabian Kloosterman
- NERF-NeuroElectronics Research Flanders, Kloosterman LabHeverleeBelgium
- KU Leuven, Faculty of Psychology & Educational SciencesLeuvenBelgium
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12
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Jimenez CA, Meyer ML. The dorsomedial prefrontal cortex prioritizes social learning during rest. Proc Natl Acad Sci U S A 2024; 121:e2309232121. [PMID: 38466844 PMCID: PMC10962978 DOI: 10.1073/pnas.2309232121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 02/12/2024] [Indexed: 03/13/2024] Open
Abstract
Sociality is a defining feature of the human experience: We rely on others to ensure survival and cooperate in complex social networks to thrive. Are there brain mechanisms that help ensure we quickly learn about our social world to optimally navigate it? We tested whether portions of the brain's default network engage "by default" to quickly prioritize social learning during the memory consolidation process. To test this possibility, participants underwent functional MRI (fMRI) while viewing scenes from the documentary film, Samsara. This film shows footage of real people and places from around the world. We normed the footage to select scenes that differed along the dimension of sociality, while matched on valence, arousal, interestingness, and familiarity. During fMRI, participants watched the "social" and "nonsocial" scenes, completed a rest scan, and a surprise recognition memory test. Participants showed superior social (vs. nonsocial) memory performance, and the social memory advantage was associated with neural pattern reinstatement during rest in the dorsomedial prefrontal cortex (DMPFC), a key node of the default network. Moreover, it was during early rest that DMPFC social pattern reinstatement was greatest and predicted subsequent social memory performance most strongly, consistent with the "prioritization" account. Results simultaneously update 1) theories of memory consolidation, which have not addressed how social information may be prioritized in the learning process, and 2) understanding of default network function, which remains to be fully characterized. More broadly, the results underscore the inherent human drive to understand our vastly social world.
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Affiliation(s)
| | - Meghan L. Meyer
- Department of Psychology, Columbia University, New York, NY10027
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13
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Stöckl C, Yang Y, Maass W. Local prediction-learning in high-dimensional spaces enables neural networks to plan. Nat Commun 2024; 15:2344. [PMID: 38490999 PMCID: PMC10943103 DOI: 10.1038/s41467-024-46586-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 03/01/2024] [Indexed: 03/18/2024] Open
Abstract
Planning and problem solving are cornerstones of higher brain function. But we do not know how the brain does that. We show that learning of a suitable cognitive map of the problem space suffices. Furthermore, this can be reduced to learning to predict the next observation through local synaptic plasticity. Importantly, the resulting cognitive map encodes relations between actions and observations, and its emergent high-dimensional geometry provides a sense of direction for reaching distant goals. This quasi-Euclidean sense of direction provides a simple heuristic for online planning that works almost as well as the best offline planning algorithms from AI. If the problem space is a physical space, this method automatically extracts structural regularities from the sequence of observations that it receives so that it can generalize to unseen parts. This speeds up learning of navigation in 2D mazes and the locomotion with complex actuator systems, such as legged bodies. The cognitive map learner that we propose does not require a teacher, similar to self-attention networks (Transformers). But in contrast to Transformers, it does not require backpropagation of errors or very large datasets for learning. Hence it provides a blue-print for future energy-efficient neuromorphic hardware that acquires advanced cognitive capabilities through autonomous on-chip learning.
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Affiliation(s)
- Christoph Stöckl
- Institute of Theoretical Computer Science, Graz University of Technology, 8010, Graz, Austria
| | - Yukun Yang
- Institute of Theoretical Computer Science, Graz University of Technology, 8010, Graz, Austria
| | - Wolfgang Maass
- Institute of Theoretical Computer Science, Graz University of Technology, 8010, Graz, Austria.
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14
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Calvin OL, Erickson MT, Walters CJ, Redish AD. Dorsal hippocampus represents locations to avoid as well as locations to approach during approach-avoidance conflict. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.10.584295. [PMID: 38559154 PMCID: PMC10979882 DOI: 10.1101/2024.03.10.584295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Worrying about perceived threats is a hallmark of multiple psychological disorders including anxiety. This concern about future events is particularly important when an individual is faced with an approach-avoidance conflict. Potential goals to approach are known to be represented in the dorsal hippocampus during theta sweeps. Similarly, important non-local information is represented during hippocampal high synchrony events (HSEs), which are correlated with sharp-wave ripples (SWRs). It is likely that potential future threats may be similarly represented. We examined how threats and rewards were represented within the hippocampus during approach-avoidance conflicts in rats faced with a predator-like robot guarding a food reward. We found representations of the pseudo-predator during HSEs when hesitating in the nest, and during theta prior to retreating as the rats approached the pseudo-predator. After the first attack, we observed new place fields appearing at the location of the robot (not the location the rat was when attacked). The anxiolytic diazepam reduced anxiety-like behavior and altered hippocampal local field potentials, including reducing SWRs, suggesting that one potential mechanism of diazepam's actions may be through altered representations of imagined threat. These results suggest that hippocampal representation of potential threats could be an important mechanism that underlies worry and a potential target for anxiolytics.
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Affiliation(s)
- Olivia L. Calvin
- Department of Neuroscience, University of Minnesota, Minneapolis MN 55455
| | | | | | - A. David Redish
- Department of Neuroscience, University of Minnesota, Minneapolis MN 55455
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15
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Sagiv Y, Akam T, Witten IB, Daw ND. Prioritizing replay when future goals are unknown. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.29.582822. [PMID: 38496674 PMCID: PMC10942393 DOI: 10.1101/2024.02.29.582822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Although hippocampal place cells replay nonlocal trajectories, the computational function of these events remains controversial. One hypothesis, formalized in a prominent reinforcement learning account, holds that replay plans routes to current goals. However, recent puzzling data appear to contradict this perspective by showing that replayed destinations lag current goals. These results may support an alternative hypothesis that replay updates route information to build a "cognitive map." Yet no similar theory exists to formalize this view, and it is unclear how such a map is represented or what role replay plays in computing it. We address these gaps by introducing a theory of replay that learns a map of routes to candidate goals, before reward is available or when its location may change. Our work extends the planning account to capture a general map-building function for replay, reconciling it with data, and revealing an unexpected relationship between the seemingly distinct hypotheses.
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Affiliation(s)
- Yotam Sagiv
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA
| | - Thomas Akam
- Department of Experimental Psychology, Oxford University, Oxford, UK
| | - Ilana B Witten
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA
| | - Nathaniel D Daw
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA
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16
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Sheridan CL, Lang S, Knappenberger M, Albers C, Loper R, Tillett B, Sanchez J, Wilcox A, Harrison T, Panoz-Brown D, Crystal JD. Replay of incidentally encoded episodic memories in the rat. Curr Biol 2024; 34:641-647.e5. [PMID: 38218186 DOI: 10.1016/j.cub.2023.12.043] [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: 02/28/2023] [Revised: 04/03/2023] [Accepted: 12/13/2023] [Indexed: 01/15/2024]
Abstract
Although events are not always known to be important when they occur, people can remember details about such incidentally encoded information using episodic memory. Importantly, when information is explicitly encoded for use in an expected test of retention (as in most assessments in animals), it is possible that it is used to generate a planned action1,2,3; thus, the remembered action can occur without remembering the earlier episode. By contrast, when a test is unexpected, transforming information into an action plan is unlikely because the importance of the information and the nature of the test are not yet known. Thus, accurate performance in an unexpected test after incidental encoding documents episodic memory.1,2,3,4,5,6,7,8 Here, we present evidence that rats replay episodic memories of incidentally encoded information in an unexpected assessment of memory. In one task,9 rats reported the third-last item in an explicitly encoded list of trial-unique odors. In a second task,10 rats foraged in a radial maze in the absence of odors. On a critical test, rats foraged in the radial maze, but scented lids covered the food. Next, memory of the third-last odor was assessed. All participating rats correctly answered the unexpected question. These results suggest that rats encoded multiple pieces of putatively unimportant information, and later they replayed a stream of episodic memories when that information was needed to solve an unexpected problem. We propose that rats replay episodic memories of incidentally encoded information, which documents a critical aspect of human episodic memory in a non-human animal.
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Affiliation(s)
- Cassandra L Sheridan
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA
| | - Stephen Lang
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA
| | - Mya Knappenberger
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA
| | - Cami Albers
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA
| | - Ryleigh Loper
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA
| | - Baily Tillett
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA
| | - Jonah Sanchez
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA
| | - Alyssa Wilcox
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA
| | - Tess Harrison
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA
| | - Danielle Panoz-Brown
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA
| | - Jonathon D Crystal
- Department of Psychological and Brain Sciences, Indiana University, 1101 E 10(TH) ST, Bloomington, IN 47405-7007, USA.
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17
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Nguyen ND, Lutas A, Amsalem O, Fernando J, Ahn AYE, Hakim R, Vergara J, McMahon J, Dimidschstein J, Sabatini BL, Andermann ML. Cortical reactivations predict future sensory responses. Nature 2024; 625:110-118. [PMID: 38093002 PMCID: PMC11014741 DOI: 10.1038/s41586-023-06810-1] [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: 10/10/2022] [Accepted: 10/31/2023] [Indexed: 01/05/2024]
Abstract
Many theories of offline memory consolidation posit that the pattern of neurons activated during a salient sensory experience will be faithfully reactivated, thereby stabilizing the pattern1,2. However, sensory-evoked patterns are not stable but, instead, drift across repeated experiences3-6. Here, to investigate the relationship between reactivations and the drift of sensory representations, we imaged the calcium activity of thousands of excitatory neurons in the mouse lateral visual cortex. During the minute after a visual stimulus, we observed transient, stimulus-specific reactivations, often coupled with hippocampal sharp-wave ripples. Stimulus-specific reactivations were abolished by local cortical silencing during the preceding stimulus. Reactivations early in a session systematically differed from the pattern evoked by the previous stimulus-they were more similar to future stimulus response patterns, thereby predicting both within-day and across-day representational drift. In particular, neurons that participated proportionally more or less in early stimulus reactivations than in stimulus response patterns gradually increased or decreased their future stimulus responses, respectively. Indeed, we could accurately predict future changes in stimulus responses and the separation of responses to distinct stimuli using only the rate and content of reactivations. Thus, reactivations may contribute to a gradual drift and separation in sensory cortical response patterns, thereby enhancing sensory discrimination7.
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Affiliation(s)
- Nghia D Nguyen
- Program in Neuroscience, Harvard University, Boston, MA, USA
| | - Andrew Lutas
- Division of Endocrinology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Diabetes, Endocrinology and Obesity Branch, National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Oren Amsalem
- Division of Endocrinology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Jesseba Fernando
- Division of Endocrinology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Andy Young-Eon Ahn
- Division of Endocrinology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Richard Hakim
- Program in Neuroscience, Harvard University, Boston, MA, USA
- Howard Hughes Medical Institute, Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Josselyn Vergara
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Justin McMahon
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Jordane Dimidschstein
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Bernardo L Sabatini
- Program in Neuroscience, Harvard University, Boston, MA, USA
- Howard Hughes Medical Institute, Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Mark L Andermann
- Program in Neuroscience, Harvard University, Boston, MA, USA.
- Division of Endocrinology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
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18
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Tuncdemir SN, Grosmark AD, Chung H, Luna VM, Lacefield CO, Losonczy A, Hen R. Adult-born granule cells facilitate remapping of spatial and non-spatial representations in the dentate gyrus. Neuron 2023; 111:4024-4039.e7. [PMID: 37820723 PMCID: PMC10841867 DOI: 10.1016/j.neuron.2023.09.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 06/10/2023] [Accepted: 09/13/2023] [Indexed: 10/13/2023]
Abstract
Adult-born granule cells (abGCs) have been implicated in memory discrimination through a neural computation known as pattern separation. Here, using in vivo Ca2+ imaging, we examined how chronic ablation or acute chemogenetic silencing of abGCs affects the activity of mature granule cells (mGCs). In both cases, we observed altered remapping of mGCs. Rather than broadly modulating the activity of all mGCs, abGCs promote the remapping of place cells' firing fields while increasing rate remapping of mGCs that represent sensory cues. In turn, these remapping deficits are associated with behavioral impairments in animals' ability to correctly identify new goal locations. Thus, abGCs facilitate pattern separation through the formation of non-overlapping representations for identical sensory cues encountered in different locations. In the absence of abGCs, the dentate gyrus shifts to a state that is dominated by cue information, a situation that is consistent with the overgeneralization often observed in anxiety or age-related disorders.
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Affiliation(s)
- Sebnem N Tuncdemir
- Departments of Psychiatry and Neuroscience, Columbia University, New York, NY 10032, USA; Division of Systems Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA
| | - Andres D Grosmark
- Department of Neuroscience, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Hannah Chung
- Division of Systems Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA
| | - Victor M Luna
- Departments of Psychiatry and Neuroscience, Columbia University, New York, NY 10032, USA; Division of Systems Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA
| | - Clay O Lacefield
- Departments of Psychiatry and Neuroscience, Columbia University, New York, NY 10032, USA; Division of Systems Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA
| | - Attila Losonczy
- Department of Neuroscience, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Rene Hen
- Departments of Psychiatry and Neuroscience, Columbia University, New York, NY 10032, USA; Division of Systems Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA.
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19
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Nicholas J, Daw ND, Shohamy D. Proactive and reactive construction of memory-based preferences. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.10.570977. [PMID: 38106137 PMCID: PMC10723393 DOI: 10.1101/2023.12.10.570977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
We are often faced with decisions we have never encountered before, requiring us to infer possible outcomes before making a choice. Computational theories suggest that one way to make these types of decisions is by accessing and linking related experiences stored in memory. Past work has shown that such memory-based preference construction can occur at a number of different timepoints relative to the moment a decision is made. Some studies have found that memories are integrated at the time a decision is faced (reactively) while others found that memory integration happens earlier, when memories are encoded (proactively). Here we offer a resolution to this inconsistency. We demonstrate behavioral and neural evidence for both strategies and for how they tradeoff rationally depending on the associative structure of memory. Using fMRI to decode patterns of brain responses unique to categories of images in memory, we found that proactive memory access is more common and allows more efficient inference. However, participants also use reactive access when choice options are linked to more numerous memory associations. Together, these results indicate that the brain judiciously conducts proactive inference by accessing memories ahead of time in conditions when this strategy is most favorable.
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Affiliation(s)
- Jonathan Nicholas
- Department of Psychology, Columbia University, New York, NY, USA
- Mortimer B. Zuckerman Mind, Brain, Behavior Institute, Columbia University, New York, NY, USA
- Department of Psychology, New York University, New York, NY, USA
| | - Nathaniel D Daw
- Department of Psychology, Princeton University, Princeton, NJ, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Daphna Shohamy
- Department of Psychology, Columbia University, New York, NY, USA
- Mortimer B. Zuckerman Mind, Brain, Behavior Institute, Columbia University, New York, NY, USA
- The Kavli Institute for Brain Science, Columbia University, New York, NY, USA
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20
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Jeong H, Namboodiri VMK, Jung MW, Andermann ML. Sensory cortical ensembles exhibit differential coupling to ripples in distinct hippocampal subregions. Curr Biol 2023; 33:5185-5198.e4. [PMID: 37995696 PMCID: PMC10842729 DOI: 10.1016/j.cub.2023.10.073] [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: 04/22/2023] [Revised: 08/29/2023] [Accepted: 10/31/2023] [Indexed: 11/25/2023]
Abstract
Cortical neurons activated during recent experiences often reactivate with dorsal hippocampal CA1 ripples during subsequent rest. Less is known about cortical interactions with intermediate hippocampal CA1, whose connectivity, functions, and ripple events differ from dorsal CA1. We identified three clusters of putative excitatory neurons in mouse visual cortex that are preferentially excited together with either dorsal or intermediate CA1 ripples or suppressed before both ripples. Neurons in each cluster were evenly distributed across primary and higher visual cortices and co-active even in the absence of ripples. These ensembles exhibited similar visual responses but different coupling to thalamus and pupil-indexed arousal. We observed a consistent activity sequence preceding and predicting ripples: (1) suppression of ripple-suppressed cortical neurons, (2) thalamic silence, and (3) activation of intermediate CA1-ripple-activated cortical neurons. We propose that coordinated dynamics of these ensembles relay visual experiences to distinct hippocampal subregions for incorporation into different cognitive maps.
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Affiliation(s)
- Huijeong Jeong
- Department of Neurology, University of California, San Francisco, 1651 4th Street, San Francisco, CA 94158, USA; Center for Synaptic Brain Dysfunctions, Institute for Basic Science, 291 Daehak-ro, Daejeon 34141, Republic of Korea; Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Daejeon 34141, Republic of Korea
| | - Vijay Mohan K Namboodiri
- Department of Neurology, University of California, San Francisco, 1651 4th Street, San Francisco, CA 94158, USA; Neuroscience Graduate Program, University of California, San Francisco, 1651 4th Street, San Francisco, CA 94158, USA; Weill Institute for Neuroscience, Kavli Institute for Fundamental Neuroscience, Center for Integrative Neuroscience, University of California, San Francisco, 1651 4th Street, San Francisco, CA 94158, USA.
| | - Min Whan Jung
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, 291 Daehak-ro, Daejeon 34141, Republic of Korea; Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Daejeon 34141, Republic of Korea.
| | - Mark L Andermann
- Division of Endocrinology, Metabolism, and Diabetes, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA; Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
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21
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Sebastian ER, Quintanilla JP, Sánchez-Aguilera A, Esparza J, Cid E, de la Prida LM. Topological analysis of sharp-wave ripple waveforms reveals input mechanisms behind feature variations. Nat Neurosci 2023; 26:2171-2181. [PMID: 37946048 PMCID: PMC10689241 DOI: 10.1038/s41593-023-01471-9] [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: 02/28/2023] [Accepted: 09/22/2023] [Indexed: 11/12/2023]
Abstract
The reactivation of experience-based neural activity patterns in the hippocampus is crucial for learning and memory. These reactivation patterns and their associated sharp-wave ripples (SWRs) are highly variable. However, this variability is missed by commonly used spectral methods. Here, we use topological and dimensionality reduction techniques to analyze the waveform of ripples recorded at the pyramidal layer of CA1. We show that SWR waveforms distribute along a continuum in a low-dimensional space, which conveys information about the underlying layer-specific synaptic inputs. A decoder trained in this space successfully links individual ripples with their expected sinks and sources, demonstrating how physiological mechanisms shape SWR variability. Furthermore, we found that SWR waveforms segregated differently during wakefulness and sleep before and after a series of cognitive tasks, with striking effects of novelty and learning. Our results thus highlight how the topological analysis of ripple waveforms enables a deeper physiological understanding of SWRs.
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Affiliation(s)
| | | | - Alberto Sánchez-Aguilera
- Instituto Cajal. CSIC, Madrid, Spain
- Department of Physiology, Faculty of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | | | - Elena Cid
- Instituto Cajal. CSIC, Madrid, Spain
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22
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Vickrey B, Lerner I. Overnight exposure to pink noise could jeopardize sleep-dependent insight and pattern detection. Front Hum Neurosci 2023; 17:1302836. [PMID: 38107593 PMCID: PMC10722168 DOI: 10.3389/fnhum.2023.1302836] [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: 09/27/2023] [Accepted: 11/13/2023] [Indexed: 12/19/2023] Open
Abstract
Accumulated evidence from the past decades suggests that sleep plays a crucial role in memory consolidation and the facilitation of higher-level cognitive processes such as abstraction and gist extraction. In addition, recent studies show that applying pink noise during sleep can further enhance sleep-dependent memory consolidation, potentially by modulating sleep physiology through stochastic resonance. However, whether this enhancement extends to higher cognitive processes remains untested. In this study, we investigated how the application of open-loop pink noise during sleep influences the gain of insight into hidden patterns. Seventy-two participants were assigned to three groups: daytime-wake, silent sleep, and sleep with pink noise. Each group completed the number reduction task, an established insight paradigm known to be influenced by sleep, over two sessions with a 12-h interval. Sleep groups were monitored by the DREEM 3 headband in home settings. Contrary to our prediction, pink noise did not induce an increase in insight compared to silent sleep and was statistically more similar to the wake condition despite evidence for its typical influence on sleep physiology. Particularly, we found that pink noise limited the time spent in the initial cycle of N1 just after sleep onset, while time spent in N1 positively predicted insight. These results echo recent suggestions that the time in the initial cycle of N1 plays a critical role in insight formation. Overall, our results suggest that open-loop pink noise during sleep may be detrimental to insight formation and creativity due to the alterations it causes to normal sleep architecture.
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Affiliation(s)
- Beverly Vickrey
- Department of Psychology, The University of Texas at San Antonio, San Antonio, TX, United States
| | - Itamar Lerner
- Department of Psychology, The University of Texas at San Antonio, San Antonio, TX, United States
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23
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Yang W, Sun C, Huszár R, Hainmueller T, Buzsáki G. Selection of experience for memory by hippocampal sharp wave ripples. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.07.565935. [PMID: 37987008 PMCID: PMC10659301 DOI: 10.1101/2023.11.07.565935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
A general wisdom is that experiences need to be tagged during learning for further consolidation. However, brain mechanisms that select experiences for lasting memory are not known. Combining large-scale neural recordings with a novel application of dimensionality reduction techniques, we observed that successive traversals in the maze were tracked by continuously drifting populations of neurons, providing neuronal signatures of both places visited and events encountered (trial number). When the brain state changed during reward consumption, sharp wave ripples (SPW-Rs) occurred on some trials and their unique spike content most often decoded the trial in which they occurred. In turn, during post-experience sleep, SPW-Rs continued to replay those trials that were reactivated most frequently during awake SPW-Rs. These findings suggest that replay content of awake SPW-Rs provides a tagging mechanism to select aspects of experience that are preserved and consolidated for future use.
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Affiliation(s)
- Wannan Yang
- Center for Neural Science, New York University, NY, USA
- Neuroscience Institute, NYU Grossman School of Medicine, New York University, New York, NY, USA
| | - Chen Sun
- Mila - Quebec AI Institute, Montréal, Canada
| | - Roman Huszár
- Neuroscience Institute, NYU Grossman School of Medicine, New York University, New York, NY, USA
| | - Thomas Hainmueller
- Neuroscience Institute, NYU Grossman School of Medicine, New York University, New York, NY, USA
- Department of Psychiatry, New York University Langone Medical Center, New York, NY, USA
| | - György Buzsáki
- Center for Neural Science, New York University, NY, USA
- Neuroscience Institute, NYU Grossman School of Medicine, New York University, New York, NY, USA
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24
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Schwartenbeck P, Baram A, Liu Y, Mark S, Muller T, Dolan R, Botvinick M, Kurth-Nelson Z, Behrens T. Generative replay underlies compositional inference in the hippocampal-prefrontal circuit. Cell 2023; 186:4885-4897.e14. [PMID: 37804832 PMCID: PMC10914680 DOI: 10.1016/j.cell.2023.09.004] [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: 05/02/2022] [Revised: 01/23/2023] [Accepted: 09/06/2023] [Indexed: 10/09/2023]
Abstract
Human reasoning depends on reusing pieces of information by putting them together in new ways. However, very little is known about how compositional computation is implemented in the brain. Here, we ask participants to solve a series of problems that each require constructing a whole from a set of elements. With fMRI, we find that representations of novel constructed objects in the frontal cortex and hippocampus are relational and compositional. With MEG, we find that replay assembles elements into compounds, with each replay sequence constituting a hypothesis about a possible configuration of elements. The content of sequences evolves as participants solve each puzzle, progressing from predictable to uncertain elements and gradually converging on the correct configuration. Together, these results suggest a computational bridge between apparently distinct functions of hippocampal-prefrontal circuitry and a role for generative replay in compositional inference and hypothesis testing.
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Affiliation(s)
- Philipp Schwartenbeck
- University of Tübingen, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Baden-Württemberg, Germany; Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3AR, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK.
| | - Alon Baram
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Shirley Mark
- Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3AR, UK
| | - Timothy Muller
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK; Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Raymond Dolan
- Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3AR, UK; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK; Department of Psychiatry, Universitätsmedizin Berlin (Campus Charité Mitte), Berlin, Germany
| | - Matthew Botvinick
- Google DeepMind, London, UK; Gatsby Computational Neuroscience Unit, University College London, London, UK
| | - Zeb Kurth-Nelson
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK; Google DeepMind, London, UK
| | - Timothy Behrens
- Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3AR, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK; Sainsbury Wellcome Centre for Neural Circuits and Behaviour, UCL, London W1T 4JG, UK
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25
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Liu C, Todorova R, Tang W, Oliva A, Fernandez-Ruiz A. Associative and predictive hippocampal codes support memory-guided behaviors. Science 2023; 382:eadi8237. [PMID: 37856604 PMCID: PMC10894649 DOI: 10.1126/science.adi8237] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 08/21/2023] [Indexed: 10/21/2023]
Abstract
Episodic memory involves learning and recalling associations between items and their spatiotemporal context. Those memories can be further used to generate internal models of the world that enable predictions to be made. The mechanisms that support these associative and predictive aspects of memory are not yet understood. In this study, we used an optogenetic manipulation to perturb the sequential structure, but not global network dynamics, of place cells as rats traversed specific spatial trajectories. This perturbation abolished replay of those trajectories and the development of predictive representations, leading to impaired learning of new optimal trajectories during memory-guided navigation. However, place cell assembly reactivation and reward-context associative learning were unaffected. Our results show a mechanistic dissociation between two complementary hippocampal codes: an associative code (through coactivity) and a predictive code (through sequences).
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Affiliation(s)
| | | | - Wenbo Tang
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY, USA
| | - Azahara Oliva
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY, USA
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26
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Nardin M, Kaefer K, Stella F, Csicsvari J. Theta oscillations as a substrate for medial prefrontal-hippocampal assembly interactions. Cell Rep 2023; 42:113015. [PMID: 37632747 DOI: 10.1016/j.celrep.2023.113015] [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: 09/14/2022] [Revised: 06/21/2023] [Accepted: 08/04/2023] [Indexed: 08/28/2023] Open
Abstract
The execution of cognitive functions requires coordinated circuit activity across different brain areas that involves the associated firing of neuronal assemblies. Here, we tested the circuit mechanism behind assembly interactions between the hippocampus and the medial prefrontal cortex (mPFC) of adult rats by recording neuronal populations during a rule-switching task. We identified functionally coupled CA1-mPFC cells that synchronized their activity beyond that expected from common spatial coding or oscillatory firing. When such cell pairs fired together, the mPFC cell strongly phase locked to CA1 theta oscillations and maintained consistent theta firing phases, independent of the theta timing of their CA1 counterpart. These functionally connected CA1-mPFC cells formed interconnected assemblies. While firing together with their CA1 assembly partners, mPFC cells fired along specific theta sequences. Our results suggest that upregulated theta oscillatory firing of mPFC cells can signal transient interactions with specific CA1 assemblies, thus enabling distributed computations.
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Affiliation(s)
- Michele Nardin
- IST Austria, 3400 Klosterneuburg, Austria; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.
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27
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Mehrotra D, Dubé L. Accounting for multiscale processing in adaptive real-world decision-making via the hippocampus. Front Neurosci 2023; 17:1200842. [PMID: 37732307 PMCID: PMC10508350 DOI: 10.3389/fnins.2023.1200842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 08/25/2023] [Indexed: 09/22/2023] Open
Abstract
For adaptive real-time behavior in real-world contexts, the brain needs to allow past information over multiple timescales to influence current processing for making choices that create the best outcome as a person goes about making choices in their everyday life. The neuroeconomics literature on value-based decision-making has formalized such choice through reinforcement learning models for two extreme strategies. These strategies are model-free (MF), which is an automatic, stimulus-response type of action, and model-based (MB), which bases choice on cognitive representations of the world and causal inference on environment-behavior structure. The emphasis of examining the neural substrates of value-based decision making has been on the striatum and prefrontal regions, especially with regards to the "here and now" decision-making. Yet, such a dichotomy does not embrace all the dynamic complexity involved. In addition, despite robust research on the role of the hippocampus in memory and spatial learning, its contribution to value-based decision making is just starting to be explored. This paper aims to better appreciate the role of the hippocampus in decision-making and advance the successor representation (SR) as a candidate mechanism for encoding state representations in the hippocampus, separate from reward representations. To this end, we review research that relates hippocampal sequences to SR models showing that the implementation of such sequences in reinforcement learning agents improves their performance. This also enables the agents to perform multiscale temporal processing in a biologically plausible manner. Altogether, we articulate a framework to advance current striatal and prefrontal-focused decision making to better account for multiscale mechanisms underlying various real-world time-related concepts such as the self that cumulates over a person's life course.
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Affiliation(s)
- Dhruv Mehrotra
- Integrated Program in Neuroscience, McGill University, Montréal, QC, Canada
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Laurette Dubé
- Desautels Faculty of Management, McGill University, Montréal, QC, Canada
- McGill Center for the Convergence of Health and Economics, McGill University, Montréal, QC, Canada
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Mahr JB, van Bergen P, Sutton J, Schacter DL, Heyes C. Mnemicity: A Cognitive Gadget? PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2023; 18:1160-1177. [PMID: 36649218 DOI: 10.1177/17456916221141352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Episodic representations can be entertained either as "remembered" or "imagined"-as outcomes of experience or as simulations of such experience. Here, we argue that this feature is the product of a dedicated cognitive function: the metacognitive capacity to determine the mnemicity of mental event simulations. We argue that mnemicity attribution should be distinguished from other metacognitive operations (such as reality monitoring) and propose that this attribution is a "cognitive gadget"-a distinctively human ability made possible by cultural learning. Cultural learning is a type of social learning in which traits are inherited through social interaction. In the case of mnemicity, one culturally learns to discriminate metacognitive "feelings of remembering" from other perceptual, emotional, action-related, and metacognitive feelings; to interpret feelings of remembering as indicators of memory rather than imagination; and to broadcast the interpreted feelings in culture- and context-specific ways, such as "I was there" or "I witnessed it myself." We review evidence from the literature on memory development and scaffolding, metacognitive learning and teaching, as well as cross-cultural psychology in support of this view before pointing out various open questions about the nature and development of mnemicity highlighted by our account.
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Affiliation(s)
| | | | - John Sutton
- Department of Philosophy, Macquarie University
| | | | - Cecilia Heyes
- All Souls College, University of Oxford
- Department of Experimental Psychology, University of Oxford
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29
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Milstein AD, Tran S, Ng G, Soltesz I. Offline memory replay in recurrent neuronal networks emerges from constraints on online dynamics. J Physiol 2023; 601:3241-3264. [PMID: 35907087 PMCID: PMC9885000 DOI: 10.1113/jp283216] [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: 04/13/2022] [Accepted: 07/22/2022] [Indexed: 02/01/2023] Open
Abstract
During spatial exploration, neural circuits in the hippocampus store memories of sequences of sensory events encountered in the environment. When sensory information is absent during 'offline' resting periods, brief neuronal population bursts can 'replay' sequences of activity that resemble bouts of sensory experience. These sequences can occur in either forward or reverse order, and can even include spatial trajectories that have not been experienced, but are consistent with the topology of the environment. The neural circuit mechanisms underlying this variable and flexible sequence generation are unknown. Here we demonstrate in a recurrent spiking network model of hippocampal area CA3 that experimental constraints on network dynamics such as population sparsity, stimulus selectivity, rhythmicity and spike rate adaptation, as well as associative synaptic connectivity, enable additional emergent properties, including variable offline memory replay. In an online stimulus-driven state, we observed the emergence of neuronal sequences that swept from representations of past to future stimuli on the timescale of the theta rhythm. In an offline state driven only by noise, the network generated both forward and reverse neuronal sequences, and recapitulated the experimental observation that offline memory replay events tend to include salient locations like the site of a reward. These results demonstrate that biological constraints on the dynamics of recurrent neural circuits are sufficient to enable memories of sensory events stored in the strengths of synaptic connections to be flexibly read out during rest and sleep, which is thought to be important for memory consolidation and planning of future behaviour. KEY POINTS: A recurrent spiking network model of hippocampal area CA3 was optimized to recapitulate experimentally observed network dynamics during simulated spatial exploration. During simulated offline rest, the network exhibited the emergent property of generating flexible forward, reverse and mixed direction memory replay events. Network perturbations and analysis of model diversity and degeneracy identified associative synaptic connectivity and key features of network dynamics as important for offline sequence generation. Network simulations demonstrate that population over-representation of salient positions like the site of reward results in biased memory replay.
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Affiliation(s)
- Aaron D. Milstein
- Department of Neurosurgery, Stanford University School of Medicine, Stanford CA
- Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical School and Center for Advanced Biotechnology and Medicine, Rutgers University, Piscataway, NJ
| | - Sarah Tran
- Department of Neurosurgery, Stanford University School of Medicine, Stanford CA
| | - Grace Ng
- Department of Neurosurgery, Stanford University School of Medicine, Stanford CA
| | - Ivan Soltesz
- Department of Neurosurgery, Stanford University School of Medicine, Stanford CA
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30
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Sun W, Advani M, Spruston N, Saxe A, Fitzgerald JE. Organizing memories for generalization in complementary learning systems. Nat Neurosci 2023; 26:1438-1448. [PMID: 37474639 PMCID: PMC10400413 DOI: 10.1038/s41593-023-01382-9] [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: 10/24/2022] [Accepted: 06/13/2023] [Indexed: 07/22/2023]
Abstract
Memorization and generalization are complementary cognitive processes that jointly promote adaptive behavior. For example, animals should memorize safe routes to specific water sources and generalize from these memories to discover environmental features that predict new ones. These functions depend on systems consolidation mechanisms that construct neocortical memory traces from hippocampal precursors, but why systems consolidation only applies to a subset of hippocampal memories is unclear. Here we introduce a new neural network formalization of systems consolidation that reveals an overlooked tension-unregulated neocortical memory transfer can cause overfitting and harm generalization in an unpredictable world. We resolve this tension by postulating that memories only consolidate when it aids generalization. This framework accounts for partial hippocampal-cortical memory transfer and provides a normative principle for reconceptualizing numerous observations in the field. Generalization-optimized systems consolidation thus provides new insight into how adaptive behavior benefits from complementary learning systems specialized for memorization and generalization.
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Affiliation(s)
- Weinan Sun
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Madhu Advani
- Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Nelson Spruston
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Andrew Saxe
- Center for Brain Science, Harvard University, Cambridge, MA, USA.
- Department of Experimental Psychology, University of Oxford, Oxford, UK.
- Gatsby Computational Neuroscience Unit & Sainsbury Wellcome Centre, UCL, London, UK.
- CIFAR Azrieli Global Scholars Program, CIFAR, Toronto, Ontario, Canada.
| | - James E Fitzgerald
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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31
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Duszkiewicz AJ, Rossato JI, Moreno A, Takeuchi T, Yamasaki M, Genzel L, Spooner P, Canals S, Morris RGM. Execution of new trajectories toward a stable goal without a functional hippocampus. Hippocampus 2023; 33:769-786. [PMID: 36798045 PMCID: PMC10946713 DOI: 10.1002/hipo.23497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 12/06/2022] [Accepted: 12/14/2022] [Indexed: 02/18/2023]
Abstract
The hippocampus is a critical component of a mammalian spatial navigation system, with the firing sequences of hippocampal place cells during sleep or immobility constituting a "replay" of an animal's past trajectories. A novel spatial navigation task recently revealed that such "replay" sequences of place fields can also prospectively map onto imminent new paths to a goal that occupies a stable location during each session. It was hypothesized that such "prospective replay" sequences may play a causal role in goal-directed navigation. In the present study, we query this putative causal role in finding only minimal effects of muscimol-induced inactivation of the dorsal and intermediate hippocampus on the same spatial navigation task. The concentration of muscimol used demonstrably inhibited hippocampal cell firing in vivo and caused a severe deficit in a hippocampal-dependent "episodic-like" spatial memory task in a watermaze. These findings call into question whether "prospective replay" of an imminent and direct path is actually necessary for its execution in certain navigational tasks.
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Affiliation(s)
- Adrian J. Duszkiewicz
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Department of PsychologyUniversity of StirlingStirlingScotlandUK
| | - Janine I. Rossato
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Department of PhysiologyUniversidade Federal do Rio Grande do NorteRio Grande do NorteBrazil
| | - Andrea Moreno
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Instituto de Neurociencias, CSIC‐UMHSan Juan de AlicanteSpain
- Department of Biomedicine, Danish Research Institute of Translational Neuroscience (DANDRITE)Aarhus UniversityAarhus CDenmark
| | - Tomonori Takeuchi
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Department of Biomedicine, Danish Research Institute of Translational Neuroscience (DANDRITE)Aarhus UniversityAarhus CDenmark
| | - Miwako Yamasaki
- Department of Anatomy, Graduate School of MedicineHokkaido UniversitySapporoJapan
| | - Lisa Genzel
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Donders Institute for Brain, Cognition, and BehaviourRadboud University and RadboudumcNijmegenThe Netherlands
| | - Patrick Spooner
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
| | - Santiago Canals
- Instituto de Neurociencias, CSIC‐UMHSan Juan de AlicanteSpain
| | - Richard G. M. Morris
- Centre for Discovery Brain Sciences, Edinburgh NeuroscienceUniversity of EdinburghEdinburghUK
- Instituto de Neurociencias, CSIC‐UMHSan Juan de AlicanteSpain
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32
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Hahamy A, Dubossarsky H, Behrens TEJ. The human brain reactivates context-specific past information at event boundaries of naturalistic experiences. Nat Neurosci 2023:10.1038/s41593-023-01331-6. [PMID: 37248340 DOI: 10.1038/s41593-023-01331-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 04/13/2023] [Indexed: 05/31/2023]
Abstract
Although we perceive the world in a continuous manner, our experience is partitioned into discrete events. However, to make sense of these events, they must be stitched together into an overarching narrative-a model of unfolding events. It has been proposed that such a stitching process happens in offline neural reactivations when rodents build models of spatial environments. Here we show that, while understanding a natural narrative, humans reactivate neural representations of past events. Similar to offline replay, these reactivations occur in the hippocampus and default mode network, where reactivations are selective to relevant past events. However, these reactivations occur, not during prolonged offline periods, but at the boundaries between ongoing narrative events. These results, replicated across two datasets, suggest reactivations as a candidate mechanism for binding temporally distant information into a coherent understanding of ongoing experience.
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Affiliation(s)
- Avital Hahamy
- Wellcome Trust Centre for Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Haim Dubossarsky
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
- Language Technology Laboratory, University of Cambridge, Cambridge, UK
| | - Timothy E J Behrens
- Wellcome Trust Centre for Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, John Radcliffe Hospital, Oxford, UK
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33
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Srinivasan A, Riceberg JS, Goodman MR, Srinivasan A, Guise KG, Shapiro ML. Goal Choices Modify Frontotemporal Memory Representations. J Neurosci 2023; 43:3353-3364. [PMID: 36977579 PMCID: PMC10162456 DOI: 10.1523/jneurosci.1939-22.2023] [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: 10/14/2022] [Revised: 03/08/2023] [Accepted: 03/13/2023] [Indexed: 03/29/2023] Open
Abstract
Adapting flexibly to changing circumstances is guided by memory of past choices, their outcomes in similar circumstances, and a method for choosing among potential actions. The hippocampus (HPC) is needed to remember episodes, and the prefrontal cortex (PFC) helps guide memory retrieval. Single-unit activity in the HPC and PFC correlates with such cognitive functions. Previous work recorded CA1 and mPFC activity as male rats performed a spatial reversal task in a plus maze that requires both structures, found that PFC activity helps reactivate HPC representations of pending goal choices but did not describe frontotemporal interactions after choices. We describe these interactions after choices here. CA1 activity tracked both current goal location and the past starting location of single trials; PFC activity tracked current goal location better than past start location. CA1 and PFC reciprocally modulated representations of each other both before and after goal choices. After choices, CA1 activity predicted changes in PFC activity in subsequent trials, and the magnitude of this prediction correlated with faster learning. In contrast, PFC start arm activity more strongly modulated CA1 activity after choices correlated with slower learning. Together, the results suggest post-choice HPC activity conveys retrospective signals to the PFC, which combines different paths to common goals into rules. In subsequent trials, prechoice mPFC activity modulates prospective CA1 signals informing goal selection.SIGNIFICANCE STATEMENT HPC and PFC activity supports cognitive flexibility in changing circumstances. HPC signals represent behavioral episodes that link the start, choice, and goal of paths. PFC signals represent rules that guide goal-directed actions. Although prior studies described HPC-PFC interactions preceding decisions in the plus maze, post-decision interactions were not investigated. Here, we show post-choice HPC and PFC activity distinguished the start and goal of paths, and CA1 signaled the past start of each trial more accurately than mPFC. Postchoice CA1 activity modulated subsequent PFC activity, so rewarded actions were more likely to occur. Together, the results show that in changing circumstances, HPC retrospective codes modulate subsequent PFC coding, which in turn modulates HPC prospective codes that predict choices.
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Affiliation(s)
- Aditya Srinivasan
- Department of Neuroscience and Experimental Therapeutics, Albany Medical College, Albany, New York 12208
| | - Justin S Riceberg
- Department of Neuroscience and Experimental Therapeutics, Albany Medical College, Albany, New York 12208
- Department of Psychiatry, Leon and Norma Hess Center for Science and Medicine, Icahn School of Medicine at Mount Sinai, New York, New York 10029
| | - Michael R Goodman
- Department of Neuroscience and Experimental Therapeutics, Albany Medical College, Albany, New York 12208
| | - Arvind Srinivasan
- College of Health Sciences, California Northstate University, Rancho Cordova, California 95670
| | - Kevin G Guise
- Friedman Brain Institute, Leon and Norma Hess Center for Science and Medicine, Icahn School of Medicine at Mount Sinai, New York, New York 10029
| | - Matthew L Shapiro
- Department of Neuroscience and Experimental Therapeutics, Albany Medical College, Albany, New York 12208
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34
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McFadyen J, Dolan RJ. Spatiotemporal Precision of Neuroimaging in Psychiatry. Biol Psychiatry 2023; 93:671-680. [PMID: 36376110 DOI: 10.1016/j.biopsych.2022.08.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 07/20/2022] [Accepted: 08/12/2022] [Indexed: 12/23/2022]
Abstract
Aberrant patterns of cognition, perception, and behavior seen in psychiatric disorders are thought to be driven by a complex interplay of neural processes that evolve at a rapid temporal scale. Understanding these dynamic processes in vivo in humans has been hampered by a trade-off between spatial and temporal resolutions inherent to current neuroimaging technology. A recent trend in psychiatric research has been the use of high temporal resolution imaging, particularly magnetoencephalography, often in conjunction with sophisticated machine learning decoding techniques. Developments here promise novel insights into the spatiotemporal dynamics of cognitive phenomena, including domains relevant to psychiatric illnesses such as reward and avoidance learning, memory, and planning. This review considers recent advances afforded by exploiting this increased spatiotemporal precision, with specific reference to applications that seek to drive a mechanistic understanding of psychopathology and the realization of preclinical translation.
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Affiliation(s)
- Jessica McFadyen
- UCL Max Planck Centre for Computational Psychiatry and Ageing Research and Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
| | - Raymond J Dolan
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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35
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McFadyen J, Liu Y, Dolan RJ. Differential replay of reward and punishment paths predicts approach and avoidance. Nat Neurosci 2023; 26:627-637. [PMID: 37020116 DOI: 10.1038/s41593-023-01287-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 02/16/2023] [Indexed: 04/07/2023]
Abstract
Neural replay is implicated in planning, where states relevant to a task goal are rapidly reactivated in sequence. It remains unclear whether, during planning, replay relates to an actual prospective choice. Here, using magnetoencephalography (MEG), we studied replay in human participants while they planned to either approach or avoid an uncertain environment containing paths leading to reward or punishment. We find evidence for forward sequential replay during planning, with rapid state-to-state transitions from 20 to 90 ms. Replay of rewarding paths was boosted, relative to aversive paths, before a decision to avoid and attenuated before a decision to approach. A trial-by-trial bias toward replaying prospective punishing paths predicted irrational decisions to approach riskier environments, an effect more pronounced in participants with higher trait anxiety. The findings indicate a coupling of replay with planned behavior, where replay prioritizes an online representation of a worst-case scenario for approaching or avoiding.
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Affiliation(s)
- Jessica McFadyen
- The UCL Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| | - Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Raymond J Dolan
- The UCL Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
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36
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Burke DA, Jeong H, Wu B, Lee SA, Floeder JR, Namboodiri VMK. Few-shot learning: temporal scaling in behavioral and dopaminergic learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.31.535173. [PMID: 37034619 PMCID: PMC10081323 DOI: 10.1101/2023.03.31.535173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
How do we learn associations in the world (e.g., between cues and rewards)? Cue-reward associative learning is controlled in the brain by mesolimbic dopamine1-4. It is widely believed that dopamine drives such learning by conveying a reward prediction error (RPE) in accordance with temporal difference reinforcement learning (TDRL) algorithms5. TDRL implementations are "trial-based": learning progresses sequentially across individual cue-outcome experiences. Accordingly, a foundational assumption-often considered a mere truism-is that the more cue-reward pairings one experiences, the more one learns this association. Here, we disprove this assumption, thereby falsifying a foundational principle of trial-based learning algorithms. Specifically, when a group of head-fixed mice received ten times fewer experiences over the same total time as another, a single experience produced as much learning as ten experiences in the other group. This quantitative scaling also holds for mesolimbic dopaminergic learning, with the increase in learning rate being so high that the group with fewer experiences exhibits dopaminergic learning in as few as four cue-reward experiences and behavioral learning in nine. An algorithm implementing reward-triggered retrospective learning explains these findings. The temporal scaling and few-shot learning observed here fundamentally changes our understanding of the neural algorithms of associative learning.
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Affiliation(s)
- Dennis A Burke
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Huijeong Jeong
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Brenda Wu
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Seul Ah Lee
- Department of Neurology, University of California, San Francisco, CA, USA
- University of California, Berkeley, CA, USA
| | - Joseph R Floeder
- Neuroscience Graduate Program, University of California, San Francisco, CA, USA
| | - Vijay Mohan K Namboodiri
- Department of Neurology, University of California, San Francisco, CA, USA
- Neuroscience Graduate Program, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, Kavli Institute for Fundamental Neuroscience, Center for Integrative Neuroscience, University of California, San Francisco, CA, USA
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37
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Surinach D, Rynes ML, Saxena K, Ko E, Redish AD, Kodandaramaiah SB. Distinct mesoscale cortical dynamics encode search strategies during spatial navigation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.27.534480. [PMID: 37034682 PMCID: PMC10081171 DOI: 10.1101/2023.03.27.534480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Spatial navigation is a complex cognitive process that involves neural computations in distributed regions of the brain. Little is known about how cortical regions are coordinated when animals navigate novel spatial environments or how that coordination changes as environments become familiar. We recorded mesoscale calcium (Ca2+) dynamics across large swathes of the dorsal cortex in mice solving the Barnes maze, a 2D spatial navigation task where mice used random, serial, and spatial search strategies to navigate to the goal. Cortical dynamics exhibited patterns of repeated calcium activity with rapid and abrupt shifts between cortical activation patterns at sub-second time scales. We used a clustering algorithm to decompose the spatial patterns of cortical calcium activity in a low dimensional state space, identifying 7 states, each corresponding to a distinct spatial pattern of cortical activation, sufficient to describe the cortical dynamics across all the mice. When mice used serial or spatial search strategies to navigate to the goal, the frontal regions of the cortex were reliably activated for prolonged durations of time (> 1s) shortly after trial initiation. These frontal cortex activation events coincided with mice approaching the edge of the maze from the center and were preceded by temporal sequences of cortical activation patterns that were distinct for serial and spatial search strategies. In serial search trials, frontal cortex activation events were preceded by activation of the posterior regions of the cortex followed by lateral activation of one hemisphere. In spatial search trials, frontal cortical events were preceded by activation of posterior regions of the cortex followed by broad activation of the lateral regions of the cortex. Our results delineated cortical components that differentiate goal- and non-goal oriented spatial navigation strategies.
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Affiliation(s)
- Daniel Surinach
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Mathew L Rynes
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
| | - Kapil Saxena
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Eunsong Ko
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
| | - A David Redish
- Department of Neuroscience, University of Minnesota, Twin Cities
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
- Department of Neuroscience, University of Minnesota, Twin Cities
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38
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Ormond J, Serka SA, Johansen JP. Enhanced Reactivation of Remapping Place Cells during Aversive Learning. J Neurosci 2023; 43:2153-2167. [PMID: 36596695 PMCID: PMC10039748 DOI: 10.1523/jneurosci.1450-22.2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 11/23/2022] [Accepted: 12/01/2022] [Indexed: 01/05/2023] Open
Abstract
Study of the hippocampal place cell system has greatly enhanced our understanding of memory encoding for distinct places, but how episodic memories for distinct experiences occurring within familiar environments are encoded is less clear. We developed a spatial decision-making task in which male rats learned to navigate a multiarm maze to a goal location for food reward while avoiding maze arms in which aversive stimuli were delivered. Task learning induced partial remapping in CA1 place cells, allowing us to identify both remapping and stable cell populations. Remapping cells were recruited into sharp-wave ripples and associated replay events to a greater extent than stable cells, despite having similar firing rates during navigation of the maze. Our results suggest that recruitment into replay events may be a mechanism to incorporate new contextual information into a previously formed and stabilized spatial representation.SIGNIFICANCE STATEMENT Hippocampal place cells provide a map of space that animals use to navigate. This map can change to reflect changes in the physical properties of the environment in which the animal finds itself, and also in response to nonphysical contextual changes, such as changes in the valence of specific locations within that environment. We show here that cells which change their spatial tuning after a change in context are preferentially recruited into sharp-wave ripple-associated replay events compared with stable nonremapping cells. Thus, our data lend strong support to the hypothesis that replay is a mechanism for the storage of new spatial maps.
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Affiliation(s)
- Jake Ormond
- Laboratory for Neural Circuitry of Memory, RIKEN Center for Brain Science, Saitama 351-0198, Japan
| | - Simon A Serka
- Laboratory for Neural Circuitry of Memory, RIKEN Center for Brain Science, Saitama 351-0198, Japan
| | - Joshua P Johansen
- Laboratory for Neural Circuitry of Memory, RIKEN Center for Brain Science, Saitama 351-0198, Japan
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39
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Picard-Deland C, Bernardi G, Genzel L, Dresler M, Schoch SF. Memory reactivations during sleep: a neural basis of dream experiences? Trends Cogn Sci 2023; 27:568-582. [PMID: 36959079 DOI: 10.1016/j.tics.2023.02.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/18/2023] [Accepted: 02/28/2023] [Indexed: 03/25/2023]
Abstract
Newly encoded memory traces are spontaneously reactivated during sleep. Since their discovery in the 1990s, these memory reactivations have been discussed as a potential neural basis for dream experiences. New results from animal and human research, as well as from the rapidly growing field of sleep and dream engineering, provide essential insights into this question, and reveal both strong parallels and disparities between the two phenomena. We suggest that, although memory reactivations may contribute to subjective experiences across different states of consciousness, they are not likely to be the primary neural basis of dreaming. We identify important limitations in current research paradigms and suggest novel strategies to address this question empirically.
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Affiliation(s)
- Claudia Picard-Deland
- Dream and Nightmare Laboratory, Center for Advanced Research in Sleep Medicine, University of Montreal, Montreal, QC, Canada
| | - Giulio Bernardi
- Institutions, Markets, Technologies (IMT) School for Advanced Studies Lucca, Lucca, Italy
| | - Lisa Genzel
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Martin Dresler
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Sarah F Schoch
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands; Center of Competence Sleep and Health Zurich, University of Zurich, Zurich, Switzerland.
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40
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Jeong H, Namboodiri VMK, Jung MW, Andermann ML. Sensory cortical ensembles exhibit differential coupling to ripples in distinct hippocampal subregions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.17.533028. [PMID: 36993665 PMCID: PMC10055189 DOI: 10.1101/2023.03.17.533028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Cortical neurons activated during recent experiences often reactivate with dorsal hippocampal CA1 sharp-wave ripples (SWRs) during subsequent rest. Less is known about cortical interactions with intermediate hippocampal CA1, whose connectivity, functions, and SWRs differ from those of dorsal CA1. We identified three clusters of visual cortical excitatory neurons that are excited together with either dorsal or intermediate CA1 SWRs, or suppressed before both SWRs. Neurons in each cluster were distributed across primary and higher visual cortices and co-active even in the absence of SWRs. These ensembles exhibited similar visual responses but different coupling to thalamus and pupil-indexed arousal. We observed a consistent activity sequence: (i) suppression of SWR-suppressed cortical neurons, (ii) thalamic silence, and (iii) activation of the cortical ensemble preceding and predicting intermediate CA1 SWRs. We propose that the coordinated dynamics of these ensembles relay visual experiences to distinct hippocampal subregions for incorporation into different cognitive maps.
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Affiliation(s)
- Huijeong Jeong
- Department of Neurology, University of California, San Francisco, CA 94158, USA
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Korea
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
| | - Vijay Mohan K Namboodiri
- Department of Neurology, University of California, San Francisco, CA 94158, USA
- Neuroscience Graduate Program, University of California, San Francisco, CA 94158, USA
- Weill Institute for Neuroscience, Kavli Institute for Fundamental Neuroscience, Center for Integrative Neuroscience, University of California, San Francisco 94158, CA, USA
| | - Min Whan Jung
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Korea
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
| | - Mark L. Andermann
- Division of Endocrinology, Metabolism, and Diabetes, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115 USA
- Lead contact
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41
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Chen ZS, Wilson MA. How our understanding of memory replay evolves. J Neurophysiol 2023; 129:552-580. [PMID: 36752404 PMCID: PMC9988534 DOI: 10.1152/jn.00454.2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 01/20/2023] [Accepted: 01/20/2023] [Indexed: 02/09/2023] Open
Abstract
Memory reactivations and replay, widely reported in the hippocampus and cortex across species, have been implicated in memory consolidation, planning, and spatial and skill learning. Technological advances in electrophysiology, calcium imaging, and human neuroimaging techniques have enabled neuroscientists to measure large-scale neural activity with increasing spatiotemporal resolution and have provided opportunities for developing robust analytic methods to identify memory replay. In this article, we first review a large body of historically important and representative memory replay studies from the animal and human literature. We then discuss our current understanding of memory replay functions in learning, planning, and memory consolidation and further discuss the progress in computational modeling that has contributed to these improvements. Next, we review past and present analytic methods for replay analyses and discuss their limitations and challenges. Finally, looking ahead, we discuss some promising analytic methods for detecting nonstereotypical, behaviorally nondecodable structures from large-scale neural recordings. We argue that seamless integration of multisite recordings, real-time replay decoding, and closed-loop manipulation experiments will be essential for delineating the role of memory replay in a wide range of cognitive and motor functions.
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Affiliation(s)
- Zhe Sage Chen
- Department of Psychiatry, New York University Grossman School of Medicine, New York, New York, United States
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, New York, United States
- Neuroscience Institute, New York University Grossman School of Medicine, New York, New York, United States
- Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, New York, United States
| | - Matthew A Wilson
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
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42
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Dafni-Merom A, Arzy S. Consciousness, Memory, and the Human Self: Commentary on "Consciousness as a Memory System" by Budson et al (2022). Cogn Behav Neurol 2023; 36:48-53. [PMID: 36622641 DOI: 10.1097/wnn.0000000000000330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 08/09/2022] [Indexed: 01/10/2023]
Abstract
Philosophical theories have attempted to shed light on the intricate relationships between consciousness and memory since long before this became a major theme in psychology and neuroscience. In the December 2022 issue of Cognitive and Behavioral Neurology , Budson, Richman, and Kensinger (2022) introduced a comprehensive theoretical framework pertaining to the origins of consciousness in relation to the memory system, its implications on our real-time perception of the world, and the neuroanatomical correlates underlying these phenomena. Throughout their paper, Budson et al (2022) focus on their theory's explanatory value regarding several clinical syndromes and experimental findings. In this commentary, we first summarize the theory presented by Budson and colleagues (2022). Then, we suggest a complementary approach of studying the relationships between consciousness and memory through the concept of the human self and its protracted representation through time (so-called mental time travel). Finally, we elaborate on Budson and colleagues' (2022) neuroanatomical explanation to their theory and suggest that adding the concepts of brain networks and cortical gradients may contribute to their theory's interpretability.
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Affiliation(s)
- Amnon Dafni-Merom
- Neuropsychiatry Laboratory, Department of Medical Neurosciences, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Shahar Arzy
- Neuropsychiatry Laboratory, Department of Medical Neurosciences, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Neurology, Hadassah Hebrew University Medical School, Jerusalem, Israel
- Department of Cognitive Sciences, Hebrew University of Jerusalem, Jerusalem, Israel
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43
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Ananthamurthy KG, Bhalla US. Synthetic Data Resource and Benchmarks for Time Cell Analysis and Detection Algorithms. eNeuro 2023; 10:ENEURO.0007-22.2023. [PMID: 36823166 PMCID: PMC10027052 DOI: 10.1523/eneuro.0007-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 11/21/2022] [Accepted: 02/09/2023] [Indexed: 02/25/2023] Open
Abstract
Hippocampal CA1 cells take part in reliable, time-locked activity sequences in tasks that involve an association between temporally separated stimuli, in a manner that tiles the interval between the stimuli. Such cells have been termed time cells. Here, we adopt a first-principles approach to comparing diverse analysis and detection algorithms for identifying time cells. We generated synthetic activity datasets using calcium signals recorded in vivo from the mouse hippocampus using two-photon (2-P) imaging, as template response waveforms. We assigned known, ground truth values to perturbations applied to perfect activity signals, including noise, calcium event width, timing imprecision, hit trial ratio and background (untuned) activity. We tested a range of published and new algorithms and their variants on this dataset. We find that most algorithms correctly classify over 80% of cells, but have different balances between true and false positives, and different sensitivity to the five categories of perturbation. Reassuringly, most methods are reasonably robust to perturbations, including background activity, and show good concordance in classification of time cells. The same algorithms were also used to analyze and identify time cells in experimental physiology datasets recorded in vivo and most show good concordance.
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Affiliation(s)
- Kambadur G Ananthamurthy
- National Centre for Biological Sciences - Tata Institute of Fundamental Research, Bellary Road, Bengaluru - 560065, Karnataka, India
| | - Upinder S Bhalla
- National Centre for Biological Sciences - Tata Institute of Fundamental Research, Bellary Road, Bengaluru - 560065, Karnataka, India
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44
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Giri B, Kaya U, Maboudi K, Abel T, Diba K. Sleep loss diminishes hippocampal reactivation and replay. RESEARCH SQUARE 2023:rs.3.rs-2540186. [PMID: 36824950 PMCID: PMC9949250 DOI: 10.21203/rs.3.rs-2540186/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
Memories benefit from sleep, and sleep loss immediately following learning has a negative impact on subsequent memory storage. Several prominent hypotheses ascribe a central role to hippocampal sharp-wave ripples (SWRs), and the concurrent reactivation and replay of neuronal patterns from waking experience, in the offline memory consolidation process that occurs during sleep. However, little is known about how SWRs, reactivation, and replay are affected when animals are subjected to sleep deprivation. We performed long duration (~12 h), high-density silicon probe recordings from rat hippocampal CA1 neurons, in animals that were either sleeping or sleep deprived following exposure to a novel maze environment. We found that SWRs showed a sustained rate of activity during sleep deprivation, similar to or higher than in natural sleep, but with decreased amplitudes for the sharp-waves combined with higher frequencies for the ripples. Furthermore, while hippocampal pyramidal cells showed a log-normal distribution of firing rates during sleep, these distributions were negatively skewed with a higher mean firing rate in both pyramidal cells and interneurons during sleep deprivation. During SWRs, however, firing rates were remarkably similar between both groups. Despite the abundant quantity of SWRs and the robust firing activity during these events in both groups, we found that reactivation of neurons was either completely abolished or significantly diminished during sleep deprivation compared to sleep. Interestingly, reactivation partially rebounded upon recovery sleep, but failed to reach the levels characteristic of natural sleep. Similarly, the number of replays were significantly lower during sleep deprivation and recovery sleep compared to natural sleep. These results provide a network-level account for the negative impact of sleep loss on hippocampal function and demonstrate that sleep loss impacts memory storage by causing a dissociation between the amount of SWRs and the replays and reactivations that take place during these events.
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Affiliation(s)
- Bapun Giri
- Dept of Anesthesiology and Neuroscience Graduate Program, 1150 W Medical Center Dr, University of Michigan Medical School, Ann Arbor, MI 48109
- Dept of Psychology, University of Wisconsin-Milwaukee, PO Box 413, Milwaukee, WI 53201
| | - Utku Kaya
- Dept of Anesthesiology and Neuroscience Graduate Program, 1150 W Medical Center Dr, University of Michigan Medical School, Ann Arbor, MI 48109
| | - Kourosh Maboudi
- Dept of Anesthesiology and Neuroscience Graduate Program, 1150 W Medical Center Dr, University of Michigan Medical School, Ann Arbor, MI 48109
- Dept of Psychology, University of Wisconsin-Milwaukee, PO Box 413, Milwaukee, WI 53201
| | - Ted Abel
- Department of Neuroscience and Pharmacology, Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa, USA
| | - Kamran Diba
- Dept of Anesthesiology and Neuroscience Graduate Program, 1150 W Medical Center Dr, University of Michigan Medical School, Ann Arbor, MI 48109
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45
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Kurth-Nelson Z, Behrens T, Wayne G, Miller K, Luettgau L, Dolan R, Liu Y, Schwartenbeck P. Replay and compositional computation. Neuron 2023; 111:454-469. [PMID: 36640765 DOI: 10.1016/j.neuron.2022.12.028] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/11/2022] [Accepted: 12/18/2022] [Indexed: 01/15/2023]
Abstract
Replay in the brain has been viewed as rehearsal or, more recently, as sampling from a transition model. Here, we propose a new hypothesis: that replay is able to implement a form of compositional computation where entities are assembled into relationally bound structures to derive qualitatively new knowledge. This idea builds on recent advances in neuroscience, which indicate that the hippocampus flexibly binds objects to generalizable roles and that replay strings these role-bound objects into compound statements. We suggest experiments to test our hypothesis, and we end by noting the implications for AI systems which lack the human ability to radically generalize past experience to solve new problems.
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Affiliation(s)
- Zeb Kurth-Nelson
- DeepMind, London, UK; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, UK.
| | - Timothy Behrens
- Wellcome Centre for Human Neuroimaging, University College London, London, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | | | - Kevin Miller
- DeepMind, London, UK; Institute of Ophthalmology, University College London, London, UK
| | - Lennart Luettgau
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, UK
| | - Ray Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, UK; Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Philipp Schwartenbeck
- Max Planck Institute for Biological Cybernetics, Tubingen, Germany; University of Tubingen, Tubingen, Germany
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46
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Wimmer GE, Liu Y, McNamee DC, Dolan RJ. Distinct replay signatures for prospective decision-making and memory preservation. Proc Natl Acad Sci U S A 2023; 120:e2205211120. [PMID: 36719914 PMCID: PMC9963918 DOI: 10.1073/pnas.2205211120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 12/05/2022] [Indexed: 02/01/2023] Open
Abstract
Theories of neural replay propose that it supports a range of functions, most prominently planning and memory consolidation. Here, we test the hypothesis that distinct signatures of replay in the same task are related to model-based decision-making ("planning") and memory preservation. We designed a reward learning task wherein participants utilized structure knowledge for model-based evaluation, while at the same time had to maintain knowledge of two independent and randomly alternating task environments. Using magnetoencephalography and multivariate analysis, we first identified temporally compressed sequential reactivation, or replay, both prior to choice and following reward feedback. Before choice, prospective replay strength was enhanced for the current task-relevant environment when a model-based planning strategy was beneficial. Following reward receipt, and consistent with a memory preservation role, replay for the alternative distal task environment was enhanced as a function of decreasing recency of experience with that environment. Critically, these planning and memory preservation relationships were selective to pre-choice and post-feedback periods, respectively. Our results provide support for key theoretical proposals regarding the functional role of replay and demonstrate that the relative strength of planning and memory-related signals are modulated by ongoing computational and task demands.
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Affiliation(s)
- G. Elliott Wimmer
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, LondonWC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, LondonWC1N 3BG, UK
| | - Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing100875, China
- Chinese Institute for Brain Research, Beijing100875, China
| | - Daniel C. McNamee
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, LondonWC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, LondonWC1N 3BG, UK
- Neuroscience Programme, Champalimaud Research, Lisbon1400-038, Portugal
| | - Raymond J. Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, LondonWC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, LondonWC1N 3BG, UK
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing100875, China
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47
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Ekman M, Kusch S, de Lange FP. Successor-like representation guides the prediction of future events in human visual cortex and hippocampus. eLife 2023; 12:78904. [PMID: 36729024 PMCID: PMC9894584 DOI: 10.7554/elife.78904] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 01/13/2023] [Indexed: 02/03/2023] Open
Abstract
Human agents build models of their environment, which enable them to anticipate and plan upcoming events. However, little is known about the properties of such predictive models. Recently, it has been proposed that hippocampal representations take the form of a predictive map-like structure, the so-called successor representation (SR). Here, we used human functional magnetic resonance imaging to probe whether activity in the early visual cortex (V1) and hippocampus adhere to the postulated properties of the SR after visual sequence learning. Participants were exposed to an arbitrary spatiotemporal sequence consisting of four items (A-B-C-D). We found that after repeated exposure to the sequence, merely presenting single sequence items (e.g., - B - -) resulted in V1 activation at the successor locations of the full sequence (e.g., C-D), but not at the predecessor locations (e.g., A). This highlights that visual representations are skewed toward future states, in line with the SR. Similar results were also found in the hippocampus. Moreover, the hippocampus developed a coactivation profile that showed sensitivity to the temporal distance in sequence space, with fading representations for sequence events in the more distant past and future. V1, in contrast, showed a coactivation profile that was only sensitive to spatial distance in stimulus space. Taken together, these results provide empirical evidence for the proposition that both visual and hippocampal cortex represent a predictive map of the visual world akin to the SR.
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Affiliation(s)
- Matthias Ekman
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and BehaviourNijmegenNetherlands
| | - Sarah Kusch
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and BehaviourNijmegenNetherlands
| | - Floris P de Lange
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and BehaviourNijmegenNetherlands
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48
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Hall AF, Wang DV. The two tales of hippocampal sharp-wave ripple content: The rigid and the plastic. Prog Neurobiol 2023; 221:102396. [PMID: 36563928 PMCID: PMC9899323 DOI: 10.1016/j.pneurobio.2022.102396] [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: 08/11/2022] [Revised: 12/09/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022]
Abstract
Sharp-wave ripples, prominently in the CA1 region of the hippocampus, are short oscillatory events accompanied by bursts of neural firing. Ripples and associated hippocampal place cell sequences communicate with cortical ensembles during slow-wave sleep, which has been shown to be critical for systems consolidation of episodic memories. This consolidation is not limited to a newly formed memory trace; instead, ripples appear to reactivate and consolidate memories spanning various experiences. Despite this broad spanning influence, ripples remain capable of producing precise memories. The underlying mechanisms that enable ripples to consolidate memories broadly and with specificity across experiences remain unknown. In this review, we discuss data that uncovers circuit-level processes that generate ripples and influence their characteristics during consolidation. Based on current knowledge, we propose that memory emerges from the integration of two parallel consolidation pathways in CA1: the rigid and plastic pathways. The rigid pathway generates ripples stochastically, providing a backbone upon which dynamic plastic pathway inputs carrying novel information are integrated.
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Affiliation(s)
- Arron F Hall
- Department of Neurobiology & Anatomy, Drexel University College of Medicine, Philadelphia, PA 19129, USA
| | - Dong V Wang
- Department of Neurobiology & Anatomy, Drexel University College of Medicine, Philadelphia, PA 19129, USA.
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49
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Aru J, Drüke M, Pikamäe J, Larkum ME. Mental navigation and the neural mechanisms of insight. Trends Neurosci 2023; 46:100-109. [PMID: 36462993 DOI: 10.1016/j.tins.2022.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 11/01/2022] [Accepted: 11/07/2022] [Indexed: 12/03/2022]
Abstract
How do new ideas come about? The central hypothesis presented here states that insights might happen during mental navigation and correspond to rapid plasticity at the cellular level. We highlight the differences between neocortical and hippocampal mechanisms of insight. We argue that the suddenness of insight can be related to the sudden emergence of place fields in the hippocampus. According to our hypothesis, insights are supported by a state of mind-wandering that can be tied to the process of combining knowledge pieces during sharp-wave ripples (SWRs). Our framework connects the dots between research on creativity, mental navigation, and specific synaptic plasticity mechanisms in the hippocampus.
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Affiliation(s)
- Jaan Aru
- Institute of Computer Science, University of Tartu, Tartu, Estonia.
| | - Moritz Drüke
- Institute of Biology, Humboldt University Berlin, Berlin, Germany
| | - Juhan Pikamäe
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Matthew E Larkum
- Institute of Biology, Humboldt University Berlin, Berlin, Germany; Neurocure Center for Excellence, Charité Universitätsmedizin Berlin, Berlin, Germany
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50
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Zeng X, Diekmann N, Wiskott L, Cheng S. Modeling the function of episodic memory in spatial learning. Front Psychol 2023; 14:1160648. [PMID: 37138984 PMCID: PMC10149844 DOI: 10.3389/fpsyg.2023.1160648] [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: 02/07/2023] [Accepted: 03/31/2023] [Indexed: 05/05/2023] Open
Abstract
Episodic memory has been studied extensively in the past few decades, but so far little is understood about how it drives future behavior. Here we propose that episodic memory can facilitate learning in two fundamentally different modes: retrieval and replay, which is the reinstatement of hippocampal activity patterns during later sleep or awake quiescence. We study their properties by comparing three learning paradigms using computational modeling based on visually-driven reinforcement learning. Firstly, episodic memories are retrieved to learn from single experiences (one-shot learning); secondly, episodic memories are replayed to facilitate learning of statistical regularities (replay learning); and, thirdly, learning occurs online as experiences arise with no access to memories of past experiences (online learning). We found that episodic memory benefits spatial learning in a broad range of conditions, but the performance difference is meaningful only when the task is sufficiently complex and the number of learning trials is limited. Furthermore, the two modes of accessing episodic memory affect spatial learning differently. One-shot learning is typically faster than replay learning, but the latter may reach a better asymptotic performance. In the end, we also investigated the benefits of sequential replay and found that replaying stochastic sequences results in faster learning as compared to random replay when the number of replays is limited. Understanding how episodic memory drives future behavior is an important step toward elucidating the nature of episodic memory.
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Affiliation(s)
- Xiangshuai Zeng
- Department of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Nicolas Diekmann
- Department of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Laurenz Wiskott
- Department of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Sen Cheng
- Department of Computer Science, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
- *Correspondence: Sen Cheng
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