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Giri B, Kinsky N, Kaya U, Maboudi K, Abel T, Diba K. Sleep loss diminishes hippocampal reactivation and replay. Nature 2024; 630:935-942. [PMID: 38867049 DOI: 10.1038/s41586-024-07538-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 05/07/2024] [Indexed: 06/14/2024]
Abstract
Memories benefit from sleep1, and the reactivation and replay of waking experiences during hippocampal sharp-wave ripples (SWRs) are considered to be crucial for this process2. However, little is known about how these patterns are impacted by sleep loss. Here we recorded CA1 neuronal activity over 12 h in rats across maze exploration, sleep and sleep deprivation, followed by recovery sleep. We found that SWRs showed sustained or higher rates during sleep deprivation but with lower power and higher frequency ripples. Pyramidal cells exhibited sustained firing during sleep deprivation and reduced firing during sleep, yet their firing rates were comparable during SWRs regardless of sleep state. Despite the robust firing and abundance of SWRs during sleep deprivation, we found that the reactivation and replay of neuronal firing patterns was diminished during these periods and, in some cases, completely abolished compared to ad libitum sleep. Reactivation partially rebounded after recovery sleep but failed to reach the levels found in natural sleep. These results delineate the adverse consequences of sleep loss on hippocampal function at the network level and reveal a dissociation between the many SWRs elicited during sleep deprivation and the few reactivations and replays that occur during these events.
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Affiliation(s)
- Bapun Giri
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Nathaniel Kinsky
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Utku Kaya
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Kourosh Maboudi
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Ted Abel
- Department of Neuroscience and Pharmacology, Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, USA
| | - Kamran Diba
- Department 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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2
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Samona EA, Chowdury A, Kopchick J, Thomas P, Rajan U, Khatib D, Zajac-Benitez C, Amirsadri A, Haddad L, Stanley JA, Diwadkar VA. The importance of covert memory consolidation in schizophrenia: Dysfunctional network profiles of the hippocampus and the dorsolateral prefrontal cortex. Psychiatry Res Neuroimaging 2024; 340:111805. [PMID: 38447230 PMCID: PMC11188056 DOI: 10.1016/j.pscychresns.2024.111805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 01/24/2024] [Accepted: 02/20/2024] [Indexed: 03/08/2024]
Abstract
Altered brain network profiles in schizophrenia (SCZ) during memory consolidation are typically observed during task-active periods such as encoding or retrieval. However active processes are also sub served by covert periods of memory consolidation. These periods are active in that they allow memories to be recapitulated even in the absence of overt sensorimotor processing. It is plausible that regions central to memory formation like the dlPFC and the hippocampus, exert network signatures during covert periods. Are these signatures altered in patients? The question is clinically relevant because real world learning and memory is facilitated by covert processing, and may be impaired in schizophrenia. Here, we compared network signatures of the dlPFC and the hippocampus during covert periods of a learning and memory task. Because behavioral proficiency increased non-linearly, functional connectivity of the dlPFC and hippocampus [psychophysiological interaction (PPI)] was estimated for each of the Early (linear increases in performance) and Late (asymptotic performance) covert periods. During Early periods, we observed hypo-modulation by the hippocampus but hyper-modulation by dlPFC. Conversely, during Late periods, we observed hypo-modulation by both the dlPFC and the hippocampus. We stitch these results into a conceptual model of network deficits during covert periods of memory consolidation.
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Affiliation(s)
- Elias A Samona
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Asadur Chowdury
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - John Kopchick
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Patricia Thomas
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Usha Rajan
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Dalal Khatib
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Caroline Zajac-Benitez
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Alireza Amirsadri
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Luay Haddad
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Jeffrey A Stanley
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Vaibhav A Diwadkar
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States.
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3
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Dragoi G. The generative grammar of the brain: a critique of internally generated representations. Nat Rev Neurosci 2024; 25:60-75. [PMID: 38036709 DOI: 10.1038/s41583-023-00763-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/18/2023] [Indexed: 12/02/2023]
Abstract
The past decade of progress in neurobiology has uncovered important organizational principles for network preconfiguration and neuronal selection that suggest a generative grammar exists in the brain. In this Perspective, I discuss the competence of the hippocampal neural network to generically express temporally compressed sequences of neuronal firing that represent novel experiences, which is envisioned as a form of generative neural syntax supporting a neurobiological perspective on brain function. I compare this neural competence with the hippocampal network performance that represents specific experiences with higher fidelity after new learning during replay, which is envisioned as a form of neural semantic that supports a complementary neuropsychological perspective. I also demonstrate how the syntax of network competence emerges a priori during early postnatal life and is followed by the later development of network performance that enables rapid encoding and memory consolidation. Thus, I propose that this generative grammar of the brain is essential for internally generated representations, which are crucial for the cognitive processes underlying learning and memory, prospection, and inference, which ultimately underlie our reason and representation of the world.
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Affiliation(s)
- George Dragoi
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, USA.
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4
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Grieves RM. Estimating neuronal firing density: A quantitative analysis of firing rate map algorithms. PLoS Comput Biol 2023; 19:e1011763. [PMID: 38150481 PMCID: PMC10775984 DOI: 10.1371/journal.pcbi.1011763] [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: 06/12/2023] [Revised: 01/09/2024] [Accepted: 12/15/2023] [Indexed: 12/29/2023] Open
Abstract
The analysis of neurons that exhibit receptive fields dependent on an organism's spatial location, such as grid, place or boundary cells typically begins by mapping their activity in space using firing rate maps. However, mapping approaches are varied and depend on multiple tuning parameters that are usually chosen qualitatively by the experimenter and thus vary significantly across studies. Small changes in parameters such as these can impact results significantly, yet, to date a quantitative investigation of firing rate maps has not been attempted. Using simulated datasets, we examined how tuning parameters, recording duration and firing field size affect the accuracy of spatial maps generated using the most widely used approaches. For each approach we found a clear subset of parameters which yielded low-error firing rate maps and isolated the parameters yielding 1) the least error possible and 2) the Pareto-optimal parameter set which balanced error, computation time, place field detection accuracy and the extrapolation of missing values. Smoothed bivariate histograms and averaged shifted histograms were consistently associated with the fastest computation times while still providing accurate maps. Adaptive smoothing and binning approaches were found to compensate for low positional sampling the most effectively. Kernel smoothed density estimation also compensated for low sampling well and resulted in accurate maps, but it was also among the slowest methods tested. Overall, the bivariate histogram, coupled with spatial smoothing, is likely the most desirable method in the majority of cases.
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Affiliation(s)
- Roddy M. Grieves
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, United States of America
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5
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Nguyen R, Koukoutselos K, Forro T, Ciocchi S. Fear extinction relies on ventral hippocampal safety codes shaped by the amygdala. SCIENCE ADVANCES 2023; 9:eadg4881. [PMID: 37256958 PMCID: PMC10413664 DOI: 10.1126/sciadv.adg4881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 04/25/2023] [Indexed: 06/02/2023]
Abstract
Extinction memory retrieval is influenced by spatial contextual information that determines responding to conditioned stimuli (CS). However, it is poorly understood whether contextual representations are imbued with emotional values to support memory selection. Here, we performed activity-dependent engram tagging and in vivo single-unit electrophysiological recordings from the ventral hippocampus (vH) while optogenetically manipulating basolateral amygdala (BLA) inputs during the formation of cued fear extinction memory. During fear extinction when CS acquire safety properties, we found that CS-related activity in the vH reactivated during sleep consolidation and was strengthened upon memory retrieval. Moreover, fear extinction memory was facilitated when the extinction context exhibited precise coding of its affective zones. Last, these activity patterns along with the retrieval of the fear extinction memory were dependent on glutamatergic transmission from the BLA during extinction learning. Thus, fear extinction memory relies on the formation of contextual and stimulus safety representations in the vH instructed by the BLA.
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Affiliation(s)
| | | | - Thomas Forro
- Laboratory of Systems Neuroscience, Department of Physiology, University of Bern, Bern, Switzerland
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6
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Chen HT, Manning JR, van der Meer MAA. Between-subject prediction reveals a shared representational geometry in the rodent hippocampus. Curr Biol 2021; 31:4293-4304.e5. [PMID: 34428470 DOI: 10.1016/j.cub.2021.07.061] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 05/27/2021] [Accepted: 07/26/2021] [Indexed: 11/24/2022]
Abstract
The rodent hippocampus constructs statistically independent representations across environments ("global remapping") and assigns individual neuron firing fields to locations within an environment in an apparently random fashion, processes thought to contribute to the role of the hippocampus in episodic memory. This random mapping implies that it should be challenging to predict hippocampal encoding of a given experience in one subject based on the encoding of that same experience in another subject. Contrary to this prediction, we find that by constructing a common representational space across rats in which neural activity is aligned using geometric operations (rotation, reflection, and translation; "hyperalignment"), we can predict data of "right" trials (R) on a T-maze in a target rat based on (1) the "left" trials (L) of the target rat and (2) the relationship between L and R trials from a different source rat. These cross-subject predictions relied on ensemble activity patterns, including both firing rate and field location, and outperformed a number of control mappings, such as those based on permuted data that broke the relationship between L and R activity for individual neurons and those based solely on within-subject prediction. This work constitutes proof of principle for successful cross-subject prediction of ensemble activity patterns in the hippocampus and provides new insights in understanding how different experiences are structured, enabling further work identifying what aspects of experience encoding are shared versus unique to an individual.
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Affiliation(s)
- Hung-Tu Chen
- Department of Psychological & Brain Sciences, Dartmouth College, Hanover, NH 03755, USA
| | - Jeremy R Manning
- Department of Psychological & Brain Sciences, Dartmouth College, Hanover, NH 03755, USA
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Duvelle É, Grieves RM, Liu A, Jedidi-Ayoub S, Holeniewska J, Harris A, Nyberg N, Donnarumma F, Lefort JM, Jeffery KJ, Summerfield C, Pezzulo G, Spiers HJ. Hippocampal place cells encode global location but not connectivity in a complex space. Curr Biol 2021; 31:1221-1233.e9. [PMID: 33581073 PMCID: PMC7988036 DOI: 10.1016/j.cub.2021.01.005] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/22/2020] [Accepted: 01/05/2021] [Indexed: 11/20/2022]
Abstract
Flexible navigation relies on a cognitive map of space, thought to be implemented by hippocampal place cells: neurons that exhibit location-specific firing. In connected environments, optimal navigation requires keeping track of one's location and of the available connections between subspaces. We examined whether the dorsal CA1 place cells of rats encode environmental connectivity in four geometrically identical boxes arranged in a square. Rats moved between boxes by pushing saloon-type doors that could be locked in one or both directions. Although rats demonstrated knowledge of environmental connectivity, their place cells did not respond to connectivity changes, nor did they represent doorways differently from other locations. Place cells coded location in a global reference frame, with a different map for each box and minimal repetitive fields despite the repetitive geometry. These results suggest that CA1 place cells provide a spatial map that does not explicitly include connectivity.
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Affiliation(s)
- Éléonore Duvelle
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
| | - Roddy M Grieves
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Anyi Liu
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK
| | - Selim Jedidi-Ayoub
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK
| | - Joanna Holeniewska
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK
| | - Adam Harris
- Department of Experimental Psychology, University of Oxford, OX2 6BW Oxford, UK
| | - Nils Nyberg
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK
| | - Francesco Donnarumma
- Institute of Cognitive Sciences and Technologies, National Research Council, via S. Martino d. Battaglia 44, 00185 Rome, Italy
| | - Julie M Lefort
- University College London, Department of Cell and Developmental Biology, London, UK
| | - Kate J Jeffery
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK
| | | | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, via S. Martino d. Battaglia 44, 00185 Rome, Italy
| | - Hugo J Spiers
- Department of Experimental Psychology, Institute of Behavioural Neuroscience, University College London, London, UK.
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8
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van der Meer MAA, Kemere C, Diba K. Progress and issues in second-order analysis of hippocampal replay. Philos Trans R Soc Lond B Biol Sci 2020; 375:20190238. [PMID: 32248780 DOI: 10.1098/rstb.2019.0238] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Patterns of neural activity that occur spontaneously during sharp-wave ripple (SWR) events in the hippocampus are thought to play an important role in memory formation, consolidation and retrieval. Typical studies examining the content of SWRs seek to determine whether the identity and/or temporal order of cell firing is different from chance. Such 'first-order' analyses are focused on a single time point and template (map), and have been used to show, for instance, the existence of preplay. The major methodological challenge in first-order analyses is the construction and interpretation of different chance distributions. By contrast, 'second-order' analyses involve a comparison of SWR content between different time points, and/or between different templates. Typical second-order questions include tests of experience-dependence (replay) that compare SWR content before and after experience, and comparisons or replay between different arms of a maze. Such questions entail additional methodological challenges that can lead to biases in results and associated interpretations. We provide an inventory of analysis challenges for second-order questions about SWR content, and suggest ways of preventing, identifying and addressing possible analysis biases. Given evolving interest in understanding SWR content in more complex experimental scenarios and across different time scales, we expect these issues to become increasingly pervasive. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.
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Affiliation(s)
| | - Caleb Kemere
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Kamran Diba
- Neuroscience Graduate Program, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
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9
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Reward revaluation biases hippocampal replay content away from the preferred outcome. Nat Neurosci 2019; 22:1450-1459. [DOI: 10.1038/s41593-019-0464-6] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Accepted: 07/09/2019] [Indexed: 02/01/2023]
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10
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Coherent Coding of Spatial Position Mediated by Theta Oscillations in the Hippocampus and Prefrontal Cortex. J Neurosci 2019; 39:4550-4565. [PMID: 30940717 DOI: 10.1523/jneurosci.0106-19.2019] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2019] [Revised: 03/05/2019] [Accepted: 03/31/2019] [Indexed: 11/21/2022] Open
Abstract
Interactions between the hippocampus (area CA1) and prefrontal cortex (PFC) are crucial for memory-guided behavior. Theta oscillations (∼8 Hz) underlie a key physiological mechanism for mediating these coordinated interactions, and theta oscillatory coherence and phase-locked spiking in the two regions have been shown to be important for spatial memory. Hippocampal place-cell activity associated with theta oscillations encodes spatial position during behavior, and theta phase-associated spiking is known to further mediate a temporal code for space within CA1 place fields. Although prefrontal neurons are prominently phase-locked to hippocampal theta oscillations in spatial memory tasks, whether and how theta oscillations mediate processing of spatial information across these networks remains unclear. Here, we addressed these questions using simultaneous recordings of dorsal CA1-PFC ensembles and population decoding analyses in male rats performing a continuous spatial working memory task known to require hippocampal-prefrontal interactions. We found that in addition to CA1, population activity in PFC can also encode the animal's current spatial position on a theta-cycle timescale during memory-guided behavior. Coding of spatial position was coherent for CA1 and PFC ensembles, exhibiting correlated position representations within theta cycles. In addition, incorporating theta-phase information during decoding to account for theta-phase associated spiking resulted in a significant improvement in the accuracy of prefrontal spatial representations, similar to concurrent CA1 representations. These findings indicate a theta-oscillation-mediated mechanism of temporal coordination for shared processing and communication of spatial information across the two networks during spatial memory-guided behavior.SIGNIFICANCE STATEMENT Theta oscillation- (∼8 Hz) mediated interactions between the hippocampus and prefrontal cortex are known to be important for spatial memory. Hippocampal place-cell activity associated with theta oscillations underlies a rate and temporal code for spatial position, but it is not known whether these oscillations mediate simultaneous coding of spatial information in hippocampal-prefrontal networks. Here, we found that population activity in prefrontal cortex encodes animals' current position coherently with hippocampal populations on a theta-cycle timescale. Further we found that theta phase-associated spiking significantly improves prefrontal coding of spatial position, in parallel with hippocampal coding. Our findings establish that theta oscillations mediate a temporal coordination mechanism for coherent coding of spatial position in hippocampal-prefrontal networks during memory-guided behavior.
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Ciliberti D, Michon F, Kloosterman F. Real-time classification of experience-related ensemble spiking patterns for closed-loop applications. eLife 2018; 7:36275. [PMID: 30373716 PMCID: PMC6207426 DOI: 10.7554/elife.36275] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 09/27/2018] [Indexed: 02/06/2023] Open
Abstract
Communication in neural circuits across the cortex is thought to be mediated by spontaneous temporally organized patterns of population activity lasting ~50 –200 ms. Closed-loop manipulations have the unique power to reveal direct and causal links between such patterns and their contribution to cognition. Current brain–computer interfaces, however, are not designed to interpret multi-neuronal spiking patterns at the millisecond timescale. To bridge this gap, we developed a system for classifying ensemble patterns in a closed-loop setting and demonstrated its application in the online identification of hippocampal neuronal replay sequences in the rat. Our system decodes multi-neuronal patterns at 10 ms resolution, identifies within 50 ms experience-related patterns with over 70% sensitivity and specificity, and classifies their content with 95% accuracy. This technology scales to high-count electrode arrays and will help to shed new light on the contribution of internally generated neural activity to coordinated neural assembly interactions and cognition.
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Affiliation(s)
- Davide Ciliberti
- Neuro-Electronics Research Flanders, Leuven, Belgium.,Brain and Cognition, KU Leuven, Leuven, Belgium.,VIB, Leuven, Belgium
| | - Frédéric Michon
- Neuro-Electronics Research Flanders, Leuven, Belgium.,Brain and Cognition, KU Leuven, Leuven, Belgium.,VIB, Leuven, Belgium
| | - Fabian Kloosterman
- Neuro-Electronics Research Flanders, Leuven, Belgium.,Brain and Cognition, KU Leuven, Leuven, Belgium.,VIB, Leuven, Belgium.,imec, Leuven, Belgium
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