1
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Bigus ER, Lee HW, Bowler JC, Shi J, Heys JG. Medial entorhinal cortex mediates learning of context-dependent interval timing behavior. Nat Neurosci 2024; 27:1587-1598. [PMID: 38877306 DOI: 10.1038/s41593-024-01683-7] [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: 03/24/2023] [Accepted: 05/14/2024] [Indexed: 06/16/2024]
Abstract
Episodic memory requires encoding the temporal structure of experience and relies on brain circuits in the medial temporal lobe, including the medial entorhinal cortex (MEC). Recent studies have identified MEC 'time cells', which fire at specific moments during interval timing tasks, collectively tiling the entire timing period. It has been hypothesized that MEC time cells could provide temporal information necessary for episodic memories, yet it remains unknown whether they display learning dynamics required for encoding different temporal contexts. To explore this, we developed a new behavioral paradigm requiring mice to distinguish temporal contexts. Combined with methods for cellular resolution calcium imaging, we found that MEC time cells display context-dependent neural activity that emerges with task learning. Through chemogenetic inactivation we found that MEC activity is necessary for learning of context-dependent interval timing behavior. Finally, we found evidence of a common circuit mechanism that could drive sequential activity of both time cells and spatially selective neurons in MEC. Our work suggests that the clock-like firing of MEC time cells can be modulated by learning, allowing the tracking of various temporal structures that emerge through experience.
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Affiliation(s)
- Erin R Bigus
- Interdepartmental PhD Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
| | - Hyun-Woo Lee
- Department of Neurobiology, University of Utah, Salt Lake City, UT, USA
| | - John C Bowler
- Department of Neurobiology, University of Utah, Salt Lake City, UT, USA
| | - Jiani Shi
- Department of Neurobiology, University of Utah, Salt Lake City, UT, USA
| | - James G Heys
- Department of Neurobiology, University of Utah, Salt Lake City, UT, USA.
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2
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Vignoud G, Venance L, Touboul JD. Anti-Hebbian plasticity drives sequence learning in striatum. Commun Biol 2024; 7:555. [PMID: 38724614 PMCID: PMC11082161 DOI: 10.1038/s42003-024-06203-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 04/17/2024] [Indexed: 05/12/2024] Open
Abstract
Spatio-temporal activity patterns have been observed in a variety of brain areas in spontaneous activity, prior to or during action, or in response to stimuli. Biological mechanisms endowing neurons with the ability to distinguish between different sequences remain largely unknown. Learning sequences of spikes raises multiple challenges, such as maintaining in memory spike history and discriminating partially overlapping sequences. Here, we show that anti-Hebbian spike-timing dependent plasticity (STDP), as observed at cortico-striatal synapses, can naturally lead to learning spike sequences. We design a spiking model of the striatal output neuron receiving spike patterns defined as sequential input from a fixed set of cortical neurons. We use a simple synaptic plasticity rule that combines anti-Hebbian STDP and non-associative potentiation for a subset of the presented patterns called rewarded patterns. We study the ability of striatal output neurons to discriminate rewarded from non-rewarded patterns by firing only after the presentation of a rewarded pattern. In particular, we show that two biological properties of striatal networks, spiking latency and collateral inhibition, contribute to an increase in accuracy, by allowing a better discrimination of partially overlapping sequences. These results suggest that anti-Hebbian STDP may serve as a biological substrate for learning sequences of spikes.
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Affiliation(s)
- Gaëtan Vignoud
- Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS, INSERM, Université PSL, Paris, France
| | - Laurent Venance
- Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS, INSERM, Université PSL, Paris, France.
| | - Jonathan D Touboul
- Department of Mathematics and Volen National Center for Complex Systems, Brandeis University, Waltham, MA, USA.
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3
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Wang C, Lee H, Rao G, Knierim JJ. Multiplexing of temporal and spatial information in the lateral entorhinal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578307. [PMID: 38352543 PMCID: PMC10862918 DOI: 10.1101/2024.01.31.578307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Episodic memory involves the processing of spatial and temporal aspects of personal experiences. The lateral entorhinal cortex (LEC) plays an essential role in subserving memory. However, the specific mechanism by which LEC integrates spatial and temporal information remains elusive. Here, we recorded LEC neurons while rats performed foraging and shuttling behaviors on one-dimensional, linear or circular tracks. Unlike open-field foraging tasks, many LEC cells displayed spatial firing fields in these tasks and demonstrated selectivity for traveling directions. Furthermore, some LEC neurons displayed changes in the firing rates of their spatial rate maps during a session, a phenomenon referred to as rate remapping. Importantly, this temporal modulation was consistent across sessions, even when the spatial environment was altered. Notably, the strength of temporal modulation was found to be greater in LEC compared to other brain regions, such as the medial entorhinal cortex (MEC), CA1, and CA3. Thus, the spatial rate mapping observed in LEC neurons may serve as a coding mechanism for temporal context, allowing for flexible multiplexing of spatial and temporal information.
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Affiliation(s)
- Cheng Wang
- Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD
| | - Heekyung Lee
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD
| | - Geeta Rao
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD
| | - James J Knierim
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD
- Lead contact
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4
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Lamprou-Kokolaki M, Nédélec Y, Lhuillier S, van Wassenhove V. Distinctive features of experiential time: Duration, speed and event density. Conscious Cogn 2024; 118:103635. [PMID: 38219402 DOI: 10.1016/j.concog.2024.103635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 12/20/2023] [Accepted: 01/02/2024] [Indexed: 01/16/2024]
Abstract
William James's use of "time in passing" and "stream of thoughts" may be two sides of the same coin that emerge from the brain segmenting the continuous flow of information into discrete events. Herein, we investigated how the density of events affects two temporal experiences: the felt duration and speed of time. Using a temporal bisection task, participants classified seconds-long videos of naturalistic scenes as short or long (duration), or slow or fast (passage of time). Videos contained a varying number and type of events. We found that a large number of events lengthened subjective duration and accelerated the felt passage of time. Surprisingly, participants were also faster at estimating their felt passage of time compared to duration. The perception of duration scaled with duration and event density, whereas the felt passage of time scaled with the rate of change. Altogether, our results suggest that distinct mechanisms underlie these two experiential times.
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Affiliation(s)
- Marianna Lamprou-Kokolaki
- CEA, DRF/Joliot, NeuroSpin; INSERM, Cognitive Neuroimaging Unit; Université Paris-Saclay, F-91191 Gif/Yvette, France.
| | - Yvan Nédélec
- CEA, DRF/Joliot, NeuroSpin; INSERM, Cognitive Neuroimaging Unit; Université Paris-Saclay, F-91191 Gif/Yvette, France
| | - Simon Lhuillier
- LAPEA, Université Gustave Eiffel / Université de Paris, F-7800 Versailles, France
| | - Virginie van Wassenhove
- CEA, DRF/Joliot, NeuroSpin; INSERM, Cognitive Neuroimaging Unit; Université Paris-Saclay, F-91191 Gif/Yvette, France
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5
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Bigus ER, Lee HW, Bowler JC, Shi J, Heys JG. Medial entorhinal cortex plays a specialized role in learning of flexible, context-dependent interval timing behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.18.524598. [PMID: 38260332 PMCID: PMC10802491 DOI: 10.1101/2023.01.18.524598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Episodic memory requires encoding the temporal structure of experience and relies on brain circuits in the medial temporal lobe, including the medial entorhinal cortex (MEC). Recent studies have identified MEC 'time cells', which fire at specific moments during interval timing tasks, collectively tiling the entire timing period. It has been hypothesized that MEC time cells could provide temporal information necessary for episodic memories, yet it remains unknown whether MEC time cells display learning dynamics required for encoding different temporal contexts. To explore this, we developed a novel behavioral paradigm that requires distinguishing temporal contexts. Combined with methods for cellular resolution calcium imaging, we find that MEC time cells display context-dependent neural activity that emerges with task learning. Through chemogenetic inactivation we find that MEC activity is necessary for learning of context-dependent interval timing behavior. Finally, we find evidence of a common circuit mechanism that could drive sequential activity of both time cells and spatially selective neurons in MEC. Our work suggests that the clock-like firing of MEC time cells can be modulated by learning, allowing the tracking of various temporal structures that emerge through experience.
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6
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Soldado-Magraner S, Buonomano DV. Neural Sequences and the Encoding of Time. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1455:81-93. [PMID: 38918347 DOI: 10.1007/978-3-031-60183-5_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
Converging experimental and computational evidence indicate that on the scale of seconds the brain encodes time through changing patterns of neural activity. Experimentally, two general forms of neural dynamic regimes that can encode time have been observed: neural population clocks and ramping activity. Neural population clocks provide a high-dimensional code to generate complex spatiotemporal output patterns, in which each neuron exhibits a nonlinear temporal profile. A prototypical example of neural population clocks are neural sequences, which have been observed across species, brain areas, and behavioral paradigms. Additionally, neural sequences emerge in artificial neural networks trained to solve time-dependent tasks. Here, we examine the role of neural sequences in the encoding of time, and how they may emerge in a biologically plausible manner. We conclude that neural sequences may represent a canonical computational regime to perform temporal computations.
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Affiliation(s)
| | - Dean V Buonomano
- Department of Neurobiology, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA.
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7
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Sakata S. SaLSa: A Combinatory Approach of Semi-Automatic Labeling and Long Short-Term Memory to Classify Behavioral Syllables. eNeuro 2023; 10:ENEURO.0201-23.2023. [PMID: 37989587 PMCID: PMC10714892 DOI: 10.1523/eneuro.0201-23.2023] [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: 06/13/2023] [Revised: 10/19/2023] [Accepted: 11/09/2023] [Indexed: 11/23/2023] Open
Abstract
Accurately and quantitatively describing mouse behavior is an important area. Although advances in machine learning have made it possible to track their behaviors accurately, reliable classification of behavioral sequences or syllables remains a challenge. In this study, we present a novel machine learning approach, called SaLSa (a combination of semi-automatic labeling and long short-term memory-based classification), to classify behavioral syllables of mice exploring an open field. This approach consists of two major steps. First, after tracking multiple body parts, spatial and temporal features of their egocentric coordinates are extracted. A fully automated unsupervised process identifies candidates for behavioral syllables, followed by manual labeling of behavioral syllables using a graphical user interface (GUI). Second, a long short-term memory (LSTM) classifier is trained with the labeled data. We found that the classification performance was marked over 97%. It provides a performance equivalent to a state-of-the-art model while classifying some of the syllables. We applied this approach to examine how hyperactivity in a mouse model of Alzheimer's disease develops with age. When the proportion of each behavioral syllable was compared between genotypes and sexes, we found that the characteristic hyperlocomotion of female Alzheimer's disease mice emerges between four and eight months. In contrast, age-related reduction in rearing is common regardless of genotype and sex. Overall, SaLSa enables detailed characterization of mouse behavior.
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Affiliation(s)
- Shuzo Sakata
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow G4 0RE, United Kingdom
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8
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M Aghajan Z, Kreiman G, Fried I. Minute-scale periodicity of neuronal firing in the human entorhinal cortex. Cell Rep 2023; 42:113271. [PMID: 37906591 DOI: 10.1016/j.celrep.2023.113271] [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: 04/16/2023] [Revised: 07/09/2023] [Accepted: 09/28/2023] [Indexed: 11/02/2023] Open
Abstract
Grid cells in the entorhinal cortex demonstrate spatially periodic firing, thought to provide a spatial map on behaviorally relevant length scales. Whether such periodicity exists for behaviorally relevant time scales in the human brain remains unclear. We investigate neuronal firing during a temporally continuous experience by presenting 14 neurosurgical patients with a video while recording neuronal activity from multiple brain regions. We report on neurons that modulate their activity in a periodic manner across different time scales-from seconds to many minutes, most prevalently in the entorhinal cortex. These neurons remap their dominant periodicity to shorter time scales during a subsequent recognition memory task. When the video is presented at two different speeds, a significant percentage of these temporally periodic cells (TPCs) maintain their time scales, suggesting a degree of invariance. The TPCs' temporal periodicity might complement the spatial periodicity of grid cells and together provide scalable spatiotemporal metrics for human experience.
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Affiliation(s)
- Zahra M Aghajan
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA.
| | - Gabriel Kreiman
- Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Center for Brains, Minds and Machines, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Itzhak Fried
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA; Faculty of Medicine, Tel Aviv University, Tel-Aviv 69978, Israel.
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9
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Buonomano DV, Buzsáki G, Davachi L, Nobre AC. Time for Memories. J Neurosci 2023; 43:7565-7574. [PMID: 37940593 PMCID: PMC10634580 DOI: 10.1523/jneurosci.1430-23.2023] [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: 07/27/2023] [Revised: 08/22/2023] [Accepted: 08/25/2023] [Indexed: 11/10/2023] Open
Abstract
The ability to store information about the past to dynamically predict and prepare for the future is among the most fundamental tasks the brain performs. To date, the problems of understanding how the brain stores and organizes information about the past (memory) and how the brain represents and processes temporal information for adaptive behavior have generally been studied as distinct cognitive functions. This Symposium explores the inherent link between memory and temporal cognition, as well as the potential shared neural mechanisms between them. We suggest that working memory and implicit timing are interconnected and may share overlapping neural mechanisms. Additionally, we explore how temporal structure is encoded in associative and episodic memory and, conversely, the influences of episodic memory on subsequent temporal anticipation and the perception of time. We suggest that neural sequences provide a general computational motif that contributes to timing and working memory, as well as the spatiotemporal coding and recall of episodes.
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Affiliation(s)
- Dean V Buonomano
- Department of Neurobiology, University of California, Los Angeles, California 90095
- Department of Psychology, University of California, Los Angeles, Los Angeles, California 90095
- Integrative Center for Learning and Memory, UCLA, Los Angeles, California 90025
| | - György Buzsáki
- Neuroscience Institute and Department of Neurology, NYU Grossman School of Medicine, New York University, New York, New York 10016
- Center for Neural Science, New York University, New York, New York 10003
| | - Lila Davachi
- Department of Psychology, Columbia University, New York, New York 10027
- Center for Clinical Research, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York 10962
| | - Anna C Nobre
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom
- Department of Psychology, Yale University, New Haven, Connecticut 06510
- Wu Tsai Center for Neurocognition and Behavior, Wu Tsai Institute, Yale University, New Haven, Connecticut 06510
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10
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Hinault T, D'Argembeau A, Bowler DM, La Corte V, Desaunay P, Provasi J, Platel H, Tran The J, Charretier L, Giersch A, Droit-Volet S. Time processing in neurological and psychiatric conditions. Neurosci Biobehav Rev 2023; 154:105430. [PMID: 37871780 DOI: 10.1016/j.neubiorev.2023.105430] [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: 03/24/2023] [Revised: 10/18/2023] [Accepted: 10/19/2023] [Indexed: 10/25/2023]
Abstract
A central question in understanding cognition and pathology-related cognitive changes is how we process time. However, time processing difficulties across several neurological and psychiatric conditions remain seldom investigated. The aim of this review is to develop a unifying taxonomy of time processing, and a neuropsychological perspective on temporal difficulties. Four main temporal judgments are discussed: duration processing, simultaneity and synchrony, passage of time, and mental time travel. We present an integrated theoretical framework of timing difficulties across psychiatric and neurological conditions based on selected patient populations. This framework provides new mechanistic insights on both (a) the processes involved in each temporal judgement, and (b) temporal difficulties across pathologies. By identifying underlying transdiagnostic time-processing mechanisms, this framework opens fruitful avenues for future research.
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Affiliation(s)
- Thomas Hinault
- Normandie Univ, UNICAEN, PSL Research University, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14032 Caen, France.
| | - Arnaud D'Argembeau
- Psychology and Neuroscience of Cognition Research Unit, University of Liège, F.R.S-FNRS, 4000 Liège, Belgium
| | - Dermot M Bowler
- Autism Research Group, City, University of London, EC1V 0HB London, United Kingdom
| | - Valentina La Corte
- Laboratoire Mémoire, Cerveau et Cognition (MC2Lab), UR 7536, Université de Paris cité, 92774 Boulogne-Billancourt, France; Institut Universitaire de France, 75231 Paris, France
| | - Pierre Desaunay
- Normandie Univ, UNICAEN, PSL Research University, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14032 Caen, France; Service de Psychiatrie de l'enfant et de l'adolescent, CHU de Caen, 14000 Caen, France
| | - Joelle Provasi
- CHArt laboratory (Human and Artificial Cognition), EPHE-PSL, 75014 Paris, France
| | - Hervé Platel
- Normandie Univ, UNICAEN, PSL Research University, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14032 Caen, France
| | - Jessica Tran The
- Normandie Univ, UNICAEN, PSL Research University, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14032 Caen, France
| | - Laura Charretier
- Normandie Univ, UNICAEN, PSL Research University, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14032 Caen, France
| | - Anne Giersch
- Cognitive Neuropsychology and Pathophysiology of Schizophrenia Laboratory, National Institute of Health and Medical Research, University of Strasbourg, 67081 Strasbourg, France
| | - Sylvie Droit-Volet
- Université Clermont Auvergne, LAPSCO, CNRS, UMR 6024, 60032 Clermont-Ferrand, France
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11
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Azizi L, Polti I, van Wassenhove V. Spontaneous α Brain Dynamics Track the Episodic "When". J Neurosci 2023; 43:7186-7197. [PMID: 37704373 PMCID: PMC10601376 DOI: 10.1523/jneurosci.0816-23.2023] [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: 04/27/2023] [Revised: 07/14/2023] [Accepted: 08/06/2023] [Indexed: 09/15/2023] Open
Abstract
Across species, neurons track time over the course of seconds to minutes, which may feed the sense of time passing. Here, we asked whether neural signatures of time-tracking could be found in humans. Participants stayed quietly awake for a few minutes while being recorded with magnetoencephalography (MEG). They were unaware they would be asked how long the recording lasted (retrospective time) or instructed beforehand to estimate how long it will last (prospective timing). At rest, rhythmic brain activity is nonstationary and displays bursts of activity in the alpha range (α: 7-14 Hz). When participants were not instructed to attend to time, the relative duration of α bursts linearly predicted individuals' retrospective estimates of how long their quiet wakefulness lasted. The relative duration of α bursts was a better predictor than α power or burst amplitude. No other rhythmic or arrhythmic activity predicted retrospective duration. However, when participants timed prospectively, the relative duration of α bursts failed to predict their duration estimates. Consistent with this, the amount of α bursts was discriminant between prospective and retrospective timing. Last, with a control experiment, we demonstrate that the relation between α bursts and retrospective time is preserved even when participants are engaged in a visual counting task. Thus, at the time scale of minutes, we report that the relative time of spontaneous α burstiness predicts conscious retrospective time. We conclude that in the absence of overt attention to time, α bursts embody discrete states of awareness constitutive of episodic timing.SIGNIFICANCE STATEMENT The feeling that time passes is a core component of consciousness and episodic memory. A century ago, brain rhythms called "α" were hypothesized to embody an internal clock. However, rhythmic brain activity is nonstationary and displays on-and-off oscillatory bursts, which would serve irregular ticks to the hypothetical clock. Here, we discovered that in a given lapse of time, the relative bursting time of α rhythms is a good indicator of how much time an individual will report to have elapsed. Remarkably, this relation only holds true when the individual does not attend to time and vanishes when attending to it. Our observations suggest that at the scale of minutes, α brain activity tracks episodic time.
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Affiliation(s)
- Leila Azizi
- Cognitive Neuroimaging Unit, NeuroSpin, Commissariat à l'énergie atomique et aux énergies alternatives, Institut National de la Santé et de la Recherche Médicale, Université Paris-Saclay, Gif/Yvette 91191, France
| | - Ignacio Polti
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway 7030
- Department of Psychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany D-04103
| | - Virginie van Wassenhove
- Cognitive Neuroimaging Unit, NeuroSpin, Commissariat à l'énergie atomique et aux énergies alternatives, Institut National de la Santé et de la Recherche Médicale, Université Paris-Saclay, Gif/Yvette 91191, France
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12
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Robbe D. Lost in time: Relocating the perception of duration outside the brain. Neurosci Biobehav Rev 2023; 153:105312. [PMID: 37467906 DOI: 10.1016/j.neubiorev.2023.105312] [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: 05/03/2023] [Accepted: 07/08/2023] [Indexed: 07/21/2023]
Abstract
It is well-accepted in neuroscience that animals process time internally to estimate the duration of intervals lasting between one and several seconds. More than 100 years ago, Henri Bergson nevertheless remarked that, because animals have memory, their inner experience of time is ever-changing, making duration impossible to measure internally and time a source of change. Bergson proposed that quantifying the inner experience of time requires its externalization in movements (observed or self-generated), as their unfolding leaves measurable traces in space. Here, studies across species are reviewed and collectively suggest that, in line with Bergson's ideas, animals spontaneously solve time estimation tasks through a movement-based spatialization of time. Moreover, the well-known scalable anticipatory responses of animals to regularly spaced rewards can be explained by the variable pressure of time on reward-oriented actions. Finally, the brain regions linked with time perception overlap with those implicated in motor control, spatial navigation and motivation. Thus, instead of considering time as static information processed by the brain, it might be fruitful to conceptualize it as a kind of force to which animals are more or less sensitive depending on their internal state and environment.
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Affiliation(s)
- David Robbe
- Institut de Neurobiologie de la Méditerranée (INMED), INSERM, Marseille, France; Aix-Marseille Université, Marseille, France.
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13
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Zhou S, Seay M, Taxidis J, Golshani P, Buonomano DV. Multiplexing working memory and time in the trajectories of neural networks. Nat Hum Behav 2023; 7:1170-1184. [PMID: 37081099 PMCID: PMC10913811 DOI: 10.1038/s41562-023-01592-y] [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: 11/08/2022] [Accepted: 03/22/2023] [Indexed: 04/22/2023]
Abstract
Working memory (WM) and timing are generally considered distinct cognitive functions, but similar neural signatures have been implicated in both. To explore the hypothesis that WM and timing may rely on shared neural mechanisms, we used psychophysical tasks that contained either task-irrelevant timing or WM components. In both cases, the task-irrelevant component influenced performance. We then developed recurrent neural network (RNN) simulations that revealed that cue-specific neural sequences, which multiplexed WM and time, emerged as the dominant regime that captured the behavioural findings. During training, RNN dynamics transitioned from low-dimensional ramps to high-dimensional neural sequences, and depending on task requirements, steady-state or ramping activity was also observed. Analysis of RNN structure revealed that neural sequences relied primarily on inhibitory connections, and could survive the deletion of all excitatory-to-excitatory connections. Our results indicate that in some instances WM is encoded in time-varying neural activity because of the importance of predicting when WM will be used.
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Affiliation(s)
- Shanglin Zhou
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Michael Seay
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Jiannis Taxidis
- Program in Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Peyman Golshani
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Integrative Center for Learning and Memory, Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, USA
- UCLA Semel Institute for Neuroscience and Behavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
- West Los Angeles VA Medical Center, Los Angeles, CA, USA
| | - Dean V Buonomano
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Department of Psychology, University of California, Los Angeles, CA, USA.
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
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14
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Yu F, Wu Y, Ma S, Xu M, Li H, Qu H, Song C, Wang T, Zhao R, Shi L. Brain-inspired multimodal hybrid neural network for robot place recognition. Sci Robot 2023; 8:eabm6996. [PMID: 37163608 DOI: 10.1126/scirobotics.abm6996] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Place recognition is an essential spatial intelligence capability for robots to understand and navigate the world. However, recognizing places in natural environments remains a challenging task for robots because of resource limitations and changing environments. In contrast, humans and animals can robustly and efficiently recognize hundreds of thousands of places in different conditions. Here, we report a brain-inspired general place recognition system, dubbed NeuroGPR, that enables robots to recognize places by mimicking the neural mechanism of multimodal sensing, encoding, and computing through a continuum of space and time. Our system consists of a multimodal hybrid neural network (MHNN) that encodes and integrates multimodal cues from both conventional and neuromorphic sensors. Specifically, to encode different sensory cues, we built various neural networks of spatial view cells, place cells, head direction cells, and time cells. To integrate these cues, we designed a multiscale liquid state machine that can process and fuse multimodal information effectively and asynchronously using diverse neuronal dynamics and bioinspired inhibitory circuits. We deployed the MHNN on Tianjic, a hybrid neuromorphic chip, and integrated it into a quadruped robot. Our results show that NeuroGPR achieves better performance compared with conventional and existing biologically inspired approaches, exhibiting robustness to diverse environmental uncertainty, including perceptual aliasing, motion blur, light, or weather changes. Running NeuroGPR as an overall multi-neural network workload on Tianjic showcases its advantages with 10.5 times lower latency and 43.6% lower power consumption than the commonly used mobile robot processor Jetson Xavier NX.
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Affiliation(s)
- Fangwen Yu
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Yujie Wu
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
- Institute of Theoretical Computer Science, Graz University of Technology, Graz, Austria
| | - Songchen Ma
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Mingkun Xu
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Hongyi Li
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Huanyu Qu
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Chenhang Song
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Taoyi Wang
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Rong Zhao
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Luping Shi
- Center for Brain-Inspired Computing Research (CBICR), Optical Memory National Engineering Research Center, and Department of Precision Instrument, Tsinghua University, Beijing 100084, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
- THU-CET HIK Joint Research Center for Brain-Inspired Computing, Tsinghua University, Beijing 100084, China
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15
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Marciniak Dg Agra K, Dg Agra P. F = ma. Is the macaque brain Newtonian? Cogn Neuropsychol 2023; 39:376-408. [PMID: 37045793 DOI: 10.1080/02643294.2023.2191843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/14/2023]
Abstract
Intuitive Physics, the ability to anticipate how the physical events involving mass objects unfold in time and space, is a central component of intelligent systems. Intuitive physics is a promising tool for gaining insight into mechanisms that generalize across species because both humans and non-human primates are subject to the same physical constraints when engaging with the environment. Physical reasoning abilities are widely present within the animal kingdom, but monkeys, with acute 3D vision and a high level of dexterity, appreciate and manipulate the physical world in much the same way humans do.
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Affiliation(s)
- Karolina Marciniak Dg Agra
- The Rockefeller University, Laboratory of Neural Circuits, New York, NY, USA
- Center for Brain, Minds and Machines, Cambridge, MA, USA
| | - Pedro Dg Agra
- The Rockefeller University, Laboratory of Neural Circuits, New York, NY, USA
- Center for Brain, Minds and Machines, Cambridge, MA, USA
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16
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Xie T, Huang C, Zhang Y, Liu J, Yao H. Influence of Recent Trial History on Interval Timing. Neurosci Bull 2023; 39:559-575. [PMID: 36209314 PMCID: PMC10073370 DOI: 10.1007/s12264-022-00954-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Accepted: 07/10/2022] [Indexed: 11/30/2022] Open
Abstract
Interval timing is involved in a variety of cognitive behaviors such as associative learning and decision-making. While it has been shown that time estimation is adaptive to the temporal context, it remains unclear how interval timing behavior is influenced by recent trial history. Here we found that, in mice trained to perform a licking-based interval timing task, a decrease of inter-reinforcement interval in the previous trial rapidly shifted the time of anticipatory licking earlier. Optogenetic inactivation of the anterior lateral motor cortex (ALM), but not the medial prefrontal cortex, for a short time before reward delivery caused a decrease in the peak time of anticipatory licking in the next trial. Electrophysiological recordings from the ALM showed that the response profiles preceded by short and long inter-reinforcement intervals exhibited task-engagement-dependent temporal scaling. Thus, interval timing is adaptive to recent experience of the temporal interval, and ALM activity during time estimation reflects recent experience of interval.
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Affiliation(s)
- Taorong Xie
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Can Huang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yijie Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jing Liu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Haishan Yao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, 201210, China.
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17
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Sawatani F, Ide K, Takahashi S. The neural representation of time distributed across multiple brain regions differs between implicit and explicit time demands. Neurobiol Learn Mem 2023; 199:107731. [PMID: 36764645 DOI: 10.1016/j.nlm.2023.107731] [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: 08/03/2022] [Revised: 01/19/2023] [Accepted: 02/04/2023] [Indexed: 02/10/2023]
Abstract
Animals appear to possess an internal timer during action, based on the passage of time. However, the neural underpinnings of the perception of time, ranging from seconds to minutes, remain unclear. Herein, we considered the neural representation of time based on mounting evidence on the neural correlates of time perception. The passage of time in the brain is represented by two types of neural encoding as follows: (i) the modulation of firing rates in single neurons and (ii) the sequential activity in neural ensembles. Time-dependent neural activity reflects the relative time rather than the absolute time, similar to a clock. They emerge in multiple regions, including the hippocampus, medial and lateral entorhinal cortices, medial prefrontal cortex, and dorsal striatum. Moreover, they involve different brain regions, depending on an implicit or explicit event duration. Thus, the two types of internal timers distributed across multiple brain regions simultaneously engage in time perception, in response to implicit or explicit time demands.
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Affiliation(s)
- Fumiya Sawatani
- Laboratory of Cognitive and Behavioral Neuroscience, Graduate School of Brain Science, Doshisha University, Kyotanabe City, Kyoto 610-0394, Japan.
| | - Kaoru Ide
- Laboratory of Cognitive and Behavioral Neuroscience, Graduate School of Brain Science, Doshisha University, Kyotanabe City, Kyoto 610-0394, Japan
| | - Susumu Takahashi
- Laboratory of Cognitive and Behavioral Neuroscience, Graduate School of Brain Science, Doshisha University, Kyotanabe City, Kyoto 610-0394, Japan.
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18
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Zhou S, Buonomano DV. Neural population clocks: Encoding time in dynamic patterns of neural activity. Behav Neurosci 2022; 136:374-382. [PMID: 35446093 PMCID: PMC9561006 DOI: 10.1037/bne0000515] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The ability to predict and prepare for near- and far-future events is among the most fundamental computations the brain performs. Because of the importance of time for prediction and sensorimotor processing, the brain has evolved multiple mechanisms to tell and encode time across scales ranging from microseconds to days and beyond. Converging experimental and computational data indicate that, on the scale of seconds, timing relies on diverse neural mechanisms distributed across different brain areas. Among the different encoding mechanisms on the scale of seconds, we distinguish between neural population clocks and ramping activity as distinct strategies to encode time. One instance of neural population clocks, neural sequences, represents in some ways an optimal and flexible dynamic regime for the encoding of time. Specifically, neural sequences comprise a high-dimensional representation that can be used by downstream areas to flexibly generate arbitrarily simple and complex output patterns using biologically plausible learning rules. We propose that high-level integration areas may use high-dimensional dynamics such as neural sequences to encode time, providing downstream areas information to build low-dimensional ramp-like activity that can drive movements and temporal expectation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Affiliation(s)
- Shanglin Zhou
- Department of Neurobiology, University of California, Los Angeles, CA 90095, USA
| | - Dean V. Buonomano
- Department of Neurobiology, University of California, Los Angeles, CA 90095, USA
- Department of Psychology, University of California, Los Angeles, CA 90095, USA
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19
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Shi Z, Gu BM, Glasauer S, Meck WH. Beyond Scalar Timing Theory: Integrating Neural Oscillators with Computational Accessibility in Memory. TIMING & TIME PERCEPTION 2022. [DOI: 10.1163/22134468-bja10059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Abstract
One of the major challenges for computational models of timing and time perception is to identify a neurobiological plausible implementation that predicts various behavioral properties, including the scalar property and retrospective timing. The available timing models primarily focus on the scalar property and prospective timing, while virtually ignoring the computational accessibility. Here, we first selectively review timing models based on ramping activity, oscillatory pattern, and time cells, and discuss potential challenges for the existing models. We then propose a multifrequency oscillatory model that offers computational accessibility, which could account for a much broader range of timing features, including both retrospective and prospective timing.
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Affiliation(s)
- Zhuanghua Shi
- Department of Experimental Psychology, Ludwig Maximilian University of Munich, 80802 Munich, Germany
| | - Bon-Mi Gu
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
| | - Stefan Glasauer
- Chair of Computational Neuroscience, Brandenburg University of Technology Cottbus, 03046 Cottbus, Germany
| | - Warren H. Meck
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
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20
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Tsao A, Yousefzadeh SA, Meck WH, Moser MB, Moser EI. The neural bases for timing of durations. Nat Rev Neurosci 2022; 23:646-665. [PMID: 36097049 DOI: 10.1038/s41583-022-00623-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2022] [Indexed: 11/10/2022]
Abstract
Durations are defined by a beginning and an end, and a major distinction is drawn between durations that start in the present and end in the future ('prospective timing') and durations that start in the past and end either in the past or the present ('retrospective timing'). Different psychological processes are thought to be engaged in each of these cases. The former is thought to engage a clock-like mechanism that accurately tracks the continuing passage of time, whereas the latter is thought to engage a reconstructive process that utilizes both temporal and non-temporal information from the memory of past events. We propose that, from a biological perspective, these two forms of duration 'estimation' are supported by computational processes that are both reliant on population state dynamics but are nevertheless distinct. Prospective timing is effectively carried out in a single step where the ongoing dynamics of population activity directly serve as the computation of duration, whereas retrospective timing is carried out in two steps: the initial generation of population state dynamics through the process of event segmentation and the subsequent computation of duration utilizing the memory of those dynamics.
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Affiliation(s)
- Albert Tsao
- Department of Biology, Stanford University, Stanford, CA, USA.
| | | | - Warren H Meck
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - May-Britt Moser
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Edvard I Moser
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway.
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21
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Henke J, Bunk D, von Werder D, Häusler S, Flanagin VL, Thurley K. Distributed coding of duration in rodent prefrontal cortex during time reproduction. eLife 2021; 10:71612. [PMID: 34939922 PMCID: PMC8786316 DOI: 10.7554/elife.71612] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 12/14/2021] [Indexed: 11/20/2022] Open
Abstract
As we interact with the external world, we judge magnitudes from sensory information. The estimation of magnitudes has been characterized in primates, yet it is largely unexplored in nonprimate species. Here, we use time interval reproduction to study rodent behavior and its neural correlates in the context of magnitude estimation. We show that gerbils display primate-like magnitude estimation characteristics in time reproduction. Most prominently their behavioral responses show a systematic overestimation of small stimuli and an underestimation of large stimuli, often referred to as regression effect. We investigated the underlying neural mechanisms by recording from medial prefrontal cortex and show that the majority of neurons respond either during the measurement or the reproduction of a time interval. Cells that are active during both phases display distinct response patterns. We categorize the neural responses into multiple types and demonstrate that only populations with mixed responses can encode the bias of the regression effect. These results help unveil the organizing neural principles of time reproduction and perhaps magnitude estimation in general.
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Affiliation(s)
- Josephine Henke
- Faculty of Biology, Ludwig-Maximilians-Universitaet Muenchen, Planegg-Martinsried, Germany
| | - David Bunk
- Faculty of Biology, Ludwig-Maximilians-Universitaet Muenchen, Planegg-Martinsried, Germany
| | - Dina von Werder
- Faculty of Biology, Ludwig-Maximilians-Universitaet Muenchen, Planegg-Martinsried, Germany
| | - Stefan Häusler
- Faculty of Biology, Ludwig-Maximilians-Universitaet Muenchen, Planegg-Martinsried, Germany
| | - Virginia L Flanagin
- German Center for Vertigo and Balance Disorders,, Ludwig-Maximilians-Universitaet Muenchen, Munich, Germany
| | - Kay Thurley
- Faculty of Biology, Ludwig-Maximilians-Universitaet Muenchen, Planegg-Martinsried, Germany
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22
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Zempolich GW, Brown ST, Holla M, Raman IM. Simple and complex spike responses of mouse cerebellar Purkinje neurons to regular trains and omissions of somatosensory stimuli. J Neurophysiol 2021; 126:763-776. [PMID: 34346760 DOI: 10.1152/jn.00170.2021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Cerebellar Purkinje neurons help compute absolute subsecond timing, but how their firing is affected during repetitive sensory stimulation with consistent subsecond intervals remains unaddressed. Here, we investigated how simple and complex spikes of Purkinje cells change during regular application of air puffs (3.3 Hz for ∼4 min) to the whisker pad of awake, head-fixed female mice. Complex spike responses fell into two categories: those in which firing rates increased (at ∼50 ms) and then fell [complex spike elevated (CxSE) cells] and those in which firing rates decreased (at ∼70 ms) and then rose [complex spike reduced (CxSR) cells]. Both groups had indistinguishable rates of basal complex (∼1.7 Hz) and simple (∼75 Hz) spikes and initially responded to puffs with a well-timed sensory response, consisting of a short-latency (∼15 ms), transient (4 ms) suppression of simple spikes. CxSE more than CxSR cells, however, also showed a longer-latency increase in simple spike rate, previously shown to reflect motor command signals. With repeated puffs, basal simple spike rates dropped greatly in CxSR but not CxSE cells; complex spike rates remained constant, but their temporal precision rose in CxSR cells and fell in CxSE cells. Also over time, transient simple spike suppression gradually disappeared in CxSE cells, suggesting habituation, but remained stable in CxSR cells, suggesting reliable transmission of sensory stimuli. During stimulus omissions, both categories of cells showed complex spike suppression with different latencies. The data indicate two modes by which Purkinje cells transmit regular repetitive stimuli, distinguishable by their climbing fiber signals.NEW & NOTEWORTHY Responses of cerebellar Purkinje cells in awake mice form two categories defined by complex spiking during regular trains of brief, somatosensory stimuli. Cells in which complex spike probability first increases or decreases show simple spike suppressions that habituate or persist, respectively. Stimulus omissions alter complex spiking. The results provide evidence for differential suppression of olivary cells during sensory stimulation and omissions and illustrate that climbing fiber innervation defines Purkinje cell responses to repetitive stimuli.
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Affiliation(s)
- Grant W Zempolich
- Department of Neurobiology, Northwestern University, Evanston, Illinois
| | - Spencer T Brown
- Department of Neurobiology, Northwestern University, Evanston, Illinois
| | - Meghana Holla
- Department of Neurobiology, Northwestern University, Evanston, Illinois.,Northwestern University Interdepartmental Neuroscience Program, Northwestern University, Evanston, Illinois
| | - Indira M Raman
- Department of Neurobiology, Northwestern University, Evanston, Illinois.,Northwestern University Interdepartmental Neuroscience Program, Northwestern University, Evanston, Illinois
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23
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Abstract
There are currently a number of theories of rodent hippocampal function. They fall into two major groups that differ in the role they impute to space in hippocampal information processing. On one hand, the cognitive map theory sees space as crucial and central, with other types of nonspatial information embedded in a primary spatial framework. On the other hand, most other theories see the function of the hippocampal formation as broader, treating all types of information as equivalent and concentrating on the processes carried out irrespective of the specific material being represented, stored, and manipulated. One crucial difference, therefore, is the extent to which theories see hippocampal pyramidal cells as representing nonspatial information independently of a spatial framework. Studies have reported the existence of single hippocampal unit responses to nonspatial stimuli, both to simple sensory inputs as well as to more complex stimuli such as objects, conspecifics, rewards, and time, and these findings been interpreted as evidence in favor of a broader hippocampal function. Alternatively, these nonspatial responses might actually be feature-in-place signals where the spatial nature of the response has been masked by the fact that the objects or features were only presented in one location or one spatial context. In this article, we argue that when tested in multiple locations, the hippocampal response to nonspatial stimuli is almost invariably dependent on the animal's location. Looked at collectively, the data provide strong support for the cognitive map theory.
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Affiliation(s)
- John O'Keefe
- Sainsbury Wellcome Centre and Department of Cell and Developmental Biology, University College London, London, United Kingdom
| | - Julija Krupic
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
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24
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Sosa JLR, Buonomano D, Izquierdo A. The orbitofrontal cortex in temporal cognition. Behav Neurosci 2021; 135:154-164. [PMID: 34060872 DOI: 10.1037/bne0000430] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
One of the most important factors in decision-making is estimating the value of available options. Subregions of the prefrontal cortex, including the orbitofrontal cortex (OFC), have been deemed essential for this process. Value computations require a complex integration across numerous dimensions, including, reward magnitude, effort, internal state, and time. The importance of the temporal dimension is well illustrated by temporal discounting tasks, in which subjects select between smaller-sooner versus larger-later rewards. The specific role of OFC in telling time and integrating temporal information into decision-making remains unclear. Based on the current literature, in this review we reevaluate current theories of OFC function, accounting for the influence of time. Incorporating temporal information into value estimation and decision-making requires distinct, yet interrelated, forms of temporal information including the ability to tell time, represent time, create temporal expectations, and the ability to use this information for optimal decision-making in a wide range of tasks, including temporal discounting and wagering. We use the term "temporal cognition" to refer to the integrated use of these different aspects of temporal information. We suggest that the OFC may be a critical site for the integration of reward magnitude and delay, and thus important for temporal cognition. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Affiliation(s)
| | - Dean Buonomano
- Department of Psychology, University of California-Los Angeles
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25
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Committeri G, Fragueiro A, Campanile MM, Lagatta M, Burles F, Iaria G, Sestieri C, Tosoni A. Egocentric Navigation Abilities Predict Episodic Memory Performance. Front Hum Neurosci 2020; 14:574224. [PMID: 33328930 PMCID: PMC7729005 DOI: 10.3389/fnhum.2020.574224] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 10/29/2020] [Indexed: 12/25/2022] Open
Abstract
The medial temporal lobe supports both navigation and declarative memory. On this basis, a theory of phylogenetic continuity has been proposed according to which episodic and semantic memories have evolved from egocentric (e.g., path integration) and allocentric (e.g., map-based) navigation in the physical world, respectively. Here, we explored the behavioral significance of this neurophysiological model by investigating the relationship between the performance of healthy individuals on a path integration and an episodic memory task. We investigated the path integration performance through a proprioceptive Triangle Completion Task and assessed episodic memory through a picture recognition task. We evaluated the specificity of the association between performance in these two tasks by including in the study design a verbal semantic memory task. We also controlled for the effect of attention and working memory and tested the robustness of the results by including alternative versions of the path integration and semantic memory tasks. We found a significant positive correlation between the performance on the path integration the episodic, but not semantic, memory tasks. This pattern of correlation was not explained by general cognitive abilities and persisted also when considering a visual path integration task and a non-verbal semantic memory task. Importantly, a cross-validation analysis showed that participants' egocentric navigation abilities reliably predicted episodic memory performance. Altogether, our findings support the hypothesis of a phylogenetic continuity between egocentric navigation and episodic memory and pave the way for future research on the potential causal role of egocentric navigation on multiple forms of episodic memory.
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Affiliation(s)
- Giorgia Committeri
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio, Chieti, Italy
| | - Agustina Fragueiro
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio, Chieti, Italy
| | | | - Marco Lagatta
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio, Chieti, Italy
| | - Ford Burles
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | - Giuseppe Iaria
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | - Carlo Sestieri
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio, Chieti, Italy
| | - Annalisa Tosoni
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio, Chieti, Italy
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26
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Robinson EM, Wiener M. Dissociable neural indices for time and space estimates during virtual distance reproduction. Neuroimage 2020; 226:117607. [PMID: 33290808 DOI: 10.1016/j.neuroimage.2020.117607] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/23/2020] [Accepted: 11/25/2020] [Indexed: 10/22/2022] Open
Abstract
The perception and measurement of spatial and temporal dimensions have been widely studied. Yet, whether these two dimensions are processed independently is still being debated. Additionally, whether EEG components are uniquely associated with time or space, or whether they reflect a more general measure of magnitude quantity remains unknown. While undergoing EEG, subjects performed a virtual distance reproduction task, in which they were required to first walk forward for an unknown distance or time, and then reproduce that distance or time. Walking speed was varied between estimation and reproduction phases, to prevent interference between distance or time in each estimate. Behaviorally, subject performance was more variable when reproducing time than when reproducing distance, but with similar patterns of accuracy. During estimation, EEG data revealed the contingent negative variation (CNV), a measure previously associated with timing and expectation, tracked the probability of the upcoming interval, for both time and distance. However, during reproduction, the CNV exclusively oriented to the upcoming temporal interval at the start of reproduction, with no change across spatial distances. Our findings indicate that time and space are neurally separable dimensions, with the CNV both serving a supramodal role in temporal and spatial expectation, yet an exclusive role in preparing duration reproduction.
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Affiliation(s)
- Eva Marie Robinson
- Department of Psychology, University of Arizona, Tuscon, AZ 85721, United States; Department of Psychology, George Mason University, 4400 University Drive, 3F5, Fairfax, VA 22030, United States
| | - Martin Wiener
- Department of Psychology, George Mason University, 4400 University Drive, 3F5, Fairfax, VA 22030, United States.
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27
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Bellmund JLS, Polti I, Doeller CF. Sequence Memory in the Hippocampal-Entorhinal Region. J Cogn Neurosci 2020; 32:2056-2070. [PMID: 32530378 DOI: 10.1162/jocn_a_01592] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Episodic memories are constructed from sequences of events. When recalling such a memory, we not only recall individual events, but we also retrieve information about how the sequence of events unfolded. Here, we focus on the role of the hippocampal-entorhinal region in processing and remembering sequences of events, which are thought to be stored in relational networks. We summarize evidence that temporal relations are a central organizational principle for memories in the hippocampus. Importantly, we incorporate novel insights from recent studies about the role of the adjacent entorhinal cortex in sequence memory. In rodents, the lateral entorhinal subregion carries temporal information during ongoing behavior. The human homologue is recruited during memory recall where its representations reflect the temporal relationships between events encountered in a sequence. We further introduce the idea that the hippocampal-entorhinal region might enable temporal scaling of sequence representations. Flexible changes of sequence progression speed could underlie the traversal of episodic memories and mental simulations at different paces. In conclusion, we describe how the entorhinal cortex and hippocampus contribute to remembering event sequences-a core component of episodic memory.
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Affiliation(s)
- Jacob L S Bellmund
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ignacio Polti
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, The Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Norwegian University of Science and Technology, Trondheim, Norway
| | - Christian F Doeller
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Kavli Institute for Systems Neuroscience, Centre for Neural Computation, The Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Norwegian University of Science and Technology, Trondheim, Norway
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