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Bhasin BJ, Raymond JL, Goldman MS. Synaptic weight dynamics underlying memory consolidation: implications for learning rules, circuit organization, and circuit function. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.20.586036. [PMID: 38585936 PMCID: PMC10996481 DOI: 10.1101/2024.03.20.586036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures with two sites of plasticity, one in an early-learning and one in a late-learning brain area. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle naturally leads to a speed-accuracy tradeoff in systems consolidation and provides insight into how the circuit mitigates the stability-plasticity dilemma of storing new memories while preserving core features of older ones. Furthermore, it imposes two constraints on the circuit. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We propose two biologically plausible implementations for this reset that suggest novel roles for core elements of the cerebellar circuit. Significance Statement How are memories transformed over time? We propose a simple organizing principle for how long term memories are moved from an initial to a final site of storage. We show that successful transfer occurs when the late site of memory storage is endowed with synaptic plasticity rules that stably accumulate changes in activity occurring at the early site of memory storage. We instantiate this principle in a simple computational model that is representative of brain circuits underlying a variety of behaviors. The model suggests how a neural circuit can store new memories while preserving core features of older ones, and suggests novel roles for core elements of the cerebellar circuit.
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2
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Upchurch CM, Knowlton CJ, Chamberland S, Canavier CC. Persistent Interruption in Parvalbumin-Positive Inhibitory Interneurons: Biophysical and Mathematical Mechanisms. eNeuro 2024; 11:ENEURO.0190-24.2024. [PMID: 38886063 PMCID: PMC11236577 DOI: 10.1523/eneuro.0190-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 06/05/2024] [Accepted: 06/11/2024] [Indexed: 06/20/2024] Open
Abstract
Persistent activity in excitatory pyramidal cells (PYRs) is a putative mechanism for maintaining memory traces during working memory. We have recently demonstrated persistent interruption of firing in fast-spiking parvalbumin-expressing interneurons (PV-INs), a phenomenon that could serve as a substrate for persistent activity in PYRs through disinhibition lasting hundreds of milliseconds. Here, we find that hippocampal CA1 PV-INs exhibit type 2 excitability, like striatal and neocortical PV-INs. Modeling and mathematical analysis showed that the slowly inactivating potassium current KV1 contributes to type 2 excitability, enables the multiple firing regimes observed experimentally in PV-INs, and provides a mechanism for robust persistent interruption of firing. Using a fast/slow separation of times scales approach with the KV1 inactivation variable as a bifurcation parameter shows that the initial inhibitory stimulus stops repetitive firing by moving the membrane potential trajectory onto a coexisting stable fixed point corresponding to a nonspiking quiescent state. As KV1 inactivation decays, the trajectory follows the branch of stable fixed points until it crosses a subcritical Hopf bifurcation (HB) and then spirals out into repetitive firing. In a model describing entorhinal cortical PV-INs without KV1, interruption of firing could be achieved by taking advantage of the bistability inherent in type 2 excitability based on a subcritical HB, but the interruption was not robust to noise. Persistent interruption of firing is therefore broadly applicable to PV-INs in different brain regions but is only made robust to noise in the presence of a slow variable, KV1 inactivation.
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Affiliation(s)
- Carol M Upchurch
- Department of Cell Biology and Anatomy, Louisiana State University Health Sciences Center, New Orleans, Louisiana 70112
| | - Christopher J Knowlton
- Department of Cell Biology and Anatomy, Louisiana State University Health Sciences Center, New Orleans, Louisiana 70112
| | - Simon Chamberland
- Neuroscience Institute and Department of Neuroscience and Physiology, New York University Langone Medical Center, New York 10016
| | - Carmen C Canavier
- Department of Cell Biology and Anatomy, Louisiana State University Health Sciences Center, New Orleans, Louisiana 70112
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3
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Klapp ST, Maslovat D. Working memory involvement in action planning does not include timing initiation structure. PSYCHOLOGICAL RESEARCH 2024; 88:1413-1425. [PMID: 38874596 DOI: 10.1007/s00426-024-01986-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Accepted: 06/03/2024] [Indexed: 06/15/2024]
Abstract
A fundamental limitation in the type of information that can be retained in working memory is identified in this theoretical / review article. The analysis is based on studies of skilled motor performance that were not initially conceived in terms of working memory. Findings from a long history of experimentation involving reaction time (RT) prior to making a brief motor response indicate that although the parameters representing the goal to be achieved by the response can be retained in working memory, the control code that implements timing of action components cannot. This lack of working memory requires that the "timing code" must be compiled immediately prior to the moment that it is to be utilized; it is not possible to be fully ready to respond earlier. This compiling process increases RT and may also underlie both the psychological refractory period effect and the difficulty of generating concurrent motor actions with independent timing. These conclusions extend, but do not conflict with, other models of working memory.
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Affiliation(s)
- Stuart T Klapp
- Department of Psychology, California State University, East Bay, Hayward, CA, USA
| | - Dana Maslovat
- School of Human Kinetics, University of Ottawa, 125 University Private, Ottawa, ON, K1N 1A2, Canada.
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4
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Wang DC, Santos-Valencia F, Song JH, Franks KM, Luo L. Embryonically active piriform cortex neurons promote intracortical recurrent connectivity during development. Neuron 2024:S0896-6273(24)00414-8. [PMID: 38964330 DOI: 10.1016/j.neuron.2024.06.007] [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: 07/24/2023] [Revised: 04/28/2024] [Accepted: 06/11/2024] [Indexed: 07/06/2024]
Abstract
Neuronal activity plays a critical role in the maturation of circuits that propagate sensory information into the brain. How widely does early activity regulate circuit maturation across the developing brain? Here, we used targeted recombination in active populations (TRAP) to perform a brain-wide survey for prenatally active neurons in mice and identified the piriform cortex as an abundantly TRAPed region. Whole-cell recordings in neonatal slices revealed preferential interconnectivity within embryonically TRAPed piriform neurons and their enhanced synaptic connectivity with other piriform neurons. In vivo Neuropixels recordings in neonates demonstrated that embryonically TRAPed piriform neurons exhibit broad functional connectivity within piriform and lead spontaneous synchronized population activity during a transient neonatal period, when recurrent connectivity is strengthening. Selectively activating or silencing these neurons in neonates enhanced or suppressed recurrent synaptic strength, respectively. Thus, embryonically TRAPed piriform neurons represent an interconnected hub-like population whose activity promotes recurrent connectivity in early development.
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Affiliation(s)
- David C Wang
- Howard Hughes Medical Institute and Department of Biology, Stanford University, Stanford, CA 94305, USA; Stanford MSTP, Stanford, CA 94305, USA
| | | | - Jun H Song
- Howard Hughes Medical Institute and Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Kevin M Franks
- Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA.
| | - Liqun Luo
- Howard Hughes Medical Institute and Department of Biology, Stanford University, Stanford, CA 94305, USA.
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5
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Qiu J, Voliotis M, Bosch MA, Li XF, Zweifel LS, Tsaneva-Atanasova K, O’Byrne KT, Rønnekleiv OK, Kelly MJ. Estradiol elicits distinct firing patterns in arcuate nucleus kisspeptin neurons of females through altering ion channel conductances. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.20.581121. [PMID: 38915596 PMCID: PMC11195100 DOI: 10.1101/2024.02.20.581121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Hypothalamic kisspeptin (Kiss1) neurons are vital for pubertal development and reproduction. Arcuate nucleus Kiss1 (Kiss1ARH) neurons are responsible for the pulsatile release of Gonadotropin-releasing Hormone (GnRH). In females, the behavior of Kiss1ARH neurons, expressing Kiss1, Neurokinin B (NKB), and Dynorphin (Dyn), varies throughout the ovarian cycle. Studies indicate that 17β-estradiol (E2) reduces peptide expression but increases Vglut2 mRNA and glutamate neurotransmission in these neurons, suggesting a shift from peptidergic to glutamatergic signaling. To investigate this shift, we combined transcriptomics, electrophysiology, and mathematical modeling. Our results demonstrate that E2 treatment upregulates the mRNA expression of voltage-activated calcium channels, elevating the whole-cell calcium current and that contribute to high-frequency burst firing. Additionally, E2 treatment decreased the mRNA levels of Canonical Transient Receptor Potential (TPRC) 5 and G protein-coupled K+ (GIRK) channels. When TRPC5 channels in Kiss1ARH neurons were deleted using CRISPR, the slow excitatory postsynaptic potential (sEPSP) was eliminated. Our data enabled us to formulate a biophysically realistic mathematical model of the Kiss1ARH neuron, suggesting that E2 modifies ionic conductances in Kiss1ARH neurons, enabling the transition from high frequency synchronous firing through NKB-driven activation of TRPC5 channels to a short bursting mode facilitating glutamate release. In a low E2 milieu, synchronous firing of Kiss1ARH neurons drives pulsatile release of GnRH, while the transition to burst firing with high, preovulatory levels of E2 would facilitate the GnRH surge through its glutamatergic synaptic connection to preoptic Kiss1 neurons.
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Affiliation(s)
- Jian Qiu
- Department of Chemical Physiology and Biochemistry, Oregon Health and Science University, Portland, OR 97239, USA
| | - Margaritis Voliotis
- Department of Mathematics and Statistics, University of Exeter, Stocker Rd, Exeter, EX4 4PY, UK
- Living Systems Institute, University of Exeter, Stocker Rd, Exeter, EX4 4PY, UK
| | - Martha A. Bosch
- Department of Chemical Physiology and Biochemistry, Oregon Health and Science University, Portland, OR 97239, USA
| | - Xiao Feng Li
- Department of Women and Children’s Health, School of Life Course and Population Sciences, King’s College London, Guy’s Campus, London SE1 1UL, UK
| | - Larry S. Zweifel
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA
- Depatment of Pharmacology, University of Washington, Seattle, WA 98195, USA
| | - Krasimira Tsaneva-Atanasova
- Department of Mathematics and Statistics, University of Exeter, Stocker Rd, Exeter, EX4 4PY, UK
- Living Systems Institute, University of Exeter, Stocker Rd, Exeter, EX4 4PY, UK
| | - Kevin T. O’Byrne
- Department of Women and Children’s Health, School of Life Course and Population Sciences, King’s College London, Guy’s Campus, London SE1 1UL, UK
| | - Oline K. Rønnekleiv
- Department of Chemical Physiology and Biochemistry, Oregon Health and Science University, Portland, OR 97239, USA
- Division of Neuroscience, Oregon National Primate Research Center, Beaverton, OR 97006, USA
| | - Martin J. Kelly
- Department of Chemical Physiology and Biochemistry, Oregon Health and Science University, Portland, OR 97239, USA
- Division of Neuroscience, Oregon National Primate Research Center, Beaverton, OR 97006, USA
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Liu B, Buonomano DV. Ex Vivo Cortical Circuits Learn to Predict and Spontaneously Replay Temporal Patterns. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.30.596702. [PMID: 38853859 PMCID: PMC11160783 DOI: 10.1101/2024.05.30.596702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
It has been proposed that prediction and timing are computational primitives of neocortical microcircuits, specifically, that neural mechanisms are in place to allow neocortical circuits to autonomously learn the temporal structure of external stimuli and generate internal predictions. To test this hypothesis, we trained cortical organotypic slices on two specific temporal patterns using dual-optical stimulation. After 24-hours of training, whole-cell recordings revealed network dynamics consistent with training-specific timed prediction. Unexpectedly, there was replay of the learned temporal structure during spontaneous activity. Furthermore, some neurons exhibited timed prediction errors. Mechanistically our results indicate that learning relied in part on asymmetric connectivity between distinct neuronal ensembles with temporally-ordered activation. These findings further suggest that local cortical microcircuits are intrinsically capable of learning temporal information and generating predictions, and that the learning rules underlying temporal learning and spontaneous replay can be intrinsic to local cortical microcircuits and not necessarily dependent on top-down interactions.
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Wang DC, Santos-Valencia F, Song JH, Franks KM, Luo L. Embryonically Active Piriform Cortex Neurons Promote Intracortical Recurrent Connectivity during Development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.08.593265. [PMID: 38766173 PMCID: PMC11100831 DOI: 10.1101/2024.05.08.593265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Neuronal activity plays a critical role in the maturation of circuits that propagate sensory information into the brain. How widely does early activity regulate circuit maturation across the developing brain? Here, we used Targeted Recombination in Active Populations (TRAP) to perform a brain-wide survey for prenatally active neurons in mice and identified the piriform cortex as an abundantly TRAPed region. Whole-cell recordings in neonatal slices revealed preferential interconnectivity within embryonically TRAPed piriform neurons and their enhanced synaptic connectivity with other piriform neurons. In vivo Neuropixels recordings in neonates demonstrated that embryonically TRAPed piriform neurons exhibit broad functional connectivity within piriform and lead spontaneous synchronized population activity during a transient neonatal period, when recurrent connectivity is strengthening. Selectively activating or silencing of these neurons in neonates enhanced or suppressed recurrent synaptic strength, respectively. Thus, embryonically TRAPed piriform neurons represent an interconnected hub-like population whose activity promotes recurrent connectivity in early development.
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8
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Bellafard A, Namvar G, Kao JC, Vaziri A, Golshani P. Volatile working memory representations crystallize with practice. Nature 2024; 629:1109-1117. [PMID: 38750359 PMCID: PMC11136659 DOI: 10.1038/s41586-024-07425-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 04/15/2024] [Indexed: 05/31/2024]
Abstract
Working memory, the process through which information is transiently maintained and manipulated over a brief period, is essential for most cognitive functions1-4. However, the mechanisms underlying the generation and evolution of working-memory neuronal representations at the population level over long timescales remain unclear. Here, to identify these mechanisms, we trained head-fixed mice to perform an olfactory delayed-association task in which the mice made decisions depending on the sequential identity of two odours separated by a 5 s delay. Optogenetic inhibition of secondary motor neurons during the late-delay and choice epochs strongly impaired the task performance of the mice. Mesoscopic calcium imaging of large neuronal populations of the secondary motor cortex (M2), retrosplenial cortex (RSA) and primary motor cortex (M1) showed that many late-delay-epoch-selective neurons emerged in M2 as the mice learned the task. Working-memory late-delay decoding accuracy substantially improved in the M2, but not in the M1 or RSA, as the mice became experts. During the early expert phase, working-memory representations during the late-delay epoch drifted across days, while the stimulus and choice representations stabilized. In contrast to single-plane layer 2/3 (L2/3) imaging, simultaneous volumetric calcium imaging of up to 73,307 M2 neurons, which included superficial L5 neurons, also revealed stabilization of late-delay working-memory representations with continued practice. Thus, delay- and choice-related activities that are essential for working-memory performance drift during learning and stabilize only after several days of expert performance.
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Affiliation(s)
- Arash Bellafard
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
| | - Ghazal Namvar
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Jonathan C Kao
- Department of Electrical and Computer Engineering, Henry Samueli School of Engineering, University of California, Los Angeles, CA, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY, USA
| | - Peyman Golshani
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Greater Los Angeles VA Medical Center, Los Angeles, CA, USA.
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA.
- Integrative Center for Learning and Memory, University of California, Los Angeles, CA, USA.
- Intellectual and Developmental Disability Research Center, University of California, Los Angeles, CA, USA.
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9
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Tomasello R, Carriere M, Pulvermüller F. The impact of early and late blindness on language and verbal working memory: A brain-constrained neural model. Neuropsychologia 2024; 196:108816. [PMID: 38331022 DOI: 10.1016/j.neuropsychologia.2024.108816] [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: 10/02/2023] [Revised: 01/26/2024] [Accepted: 02/04/2024] [Indexed: 02/10/2024]
Abstract
Neural circuits related to language exhibit a remarkable ability to reorganize and adapt in response to visual deprivation. Particularly, early and late blindness induce distinct neuroplastic changes in the visual cortex, repurposing it for language and semantic processing. Interestingly, these functional changes provoke a unique cognitive advantage - enhanced verbal working memory, particularly in early blindness. Yet, the underlying neuromechanisms and the impact on language and memory-related circuits remain not fully understood. Here, we applied a brain-constrained neural network mimicking the structural and functional features of the frontotemporal-occipital cortices, to model conceptual acquisition in early and late blindness. The results revealed differential expansion of conceptual-related neural circuits into deprived visual areas depending on the timing of visual loss, which is most prominent in early blindness. This neural recruitment is fundamentally governed by the biological principles of neural circuit expansion and the absence of uncorrelated sensory input. Critically, the degree of these changes is constrained by the availability of neural matter previously allocated to visual experiences, as in the case of late blindness. Moreover, we shed light on the implication of visual deprivation on the neural underpinnings of verbal working memory, revealing longer reverberatory neural activity in 'blind models' as compared to the sighted ones. These findings provide a better understanding of the interplay between visual deprivations, neuroplasticity, language processing and verbal working memory.
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Affiliation(s)
- Rosario Tomasello
- Brain Language Laboratory, Department of Philosophy and Humanities, WE4 Freie Universität Berlin, 14195, Berlin, Germany; Cluster of Excellence' Matters of Activity. Image Space Material', Humboldt Universität zu Berlin, 10099, Berlin, Germany.
| | - Maxime Carriere
- Brain Language Laboratory, Department of Philosophy and Humanities, WE4 Freie Universität Berlin, 14195, Berlin, Germany
| | - Friedemann Pulvermüller
- Brain Language Laboratory, Department of Philosophy and Humanities, WE4 Freie Universität Berlin, 14195, Berlin, Germany; Cluster of Excellence' Matters of Activity. Image Space Material', Humboldt Universität zu Berlin, 10099, Berlin, Germany; Berlin School of Mind and Brain, Humboldt Universität zu Berlin, 10117, Berlin, Germany; Einstein Center for Neurosciences, 10117, Berlin, Germany
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10
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Fitz H, Hagoort P, Petersson KM. Neurobiological Causal Models of Language Processing. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:225-247. [PMID: 38645618 PMCID: PMC11025648 DOI: 10.1162/nol_a_00133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 12/18/2023] [Indexed: 04/23/2024]
Abstract
The language faculty is physically realized in the neurobiological infrastructure of the human brain. Despite significant efforts, an integrated understanding of this system remains a formidable challenge. What is missing from most theoretical accounts is a specification of the neural mechanisms that implement language function. Computational models that have been put forward generally lack an explicit neurobiological foundation. We propose a neurobiologically informed causal modeling approach which offers a framework for how to bridge this gap. A neurobiological causal model is a mechanistic description of language processing that is grounded in, and constrained by, the characteristics of the neurobiological substrate. It intends to model the generators of language behavior at the level of implementational causality. We describe key features and neurobiological component parts from which causal models can be built and provide guidelines on how to implement them in model simulations. Then we outline how this approach can shed new light on the core computational machinery for language, the long-term storage of words in the mental lexicon and combinatorial processing in sentence comprehension. In contrast to cognitive theories of behavior, causal models are formulated in the "machine language" of neurobiology which is universal to human cognition. We argue that neurobiological causal modeling should be pursued in addition to existing approaches. Eventually, this approach will allow us to develop an explicit computational neurobiology of language.
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Affiliation(s)
- Hartmut Fitz
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Neurobiology of Language Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Peter Hagoort
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Neurobiology of Language Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Karl Magnus Petersson
- Neurobiology of Language Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Faculty of Medicine and Biomedical Sciences, University of Algarve, Faro, Portugal
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11
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Upchurch CM, Knowlton CJ, Chamberland S, Canavier CC. Persistent Interruption in Parvalbumin Positive Inhibitory Interneurons: Biophysical and Mathematical Mechanisms. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.04.583352. [PMID: 38496528 PMCID: PMC10942299 DOI: 10.1101/2024.03.04.583352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Persistent activity in principal cells is a putative mechanism for maintaining memory traces during working memory. We recently demonstrated persistent interruption of firing in fast-spiking parvalbumin-expressing interneurons (PV-INs), a phenomenon which could serve as a substrate for persistent activity in principal cells through disinhibition lasting hundreds of milliseconds. Here, we find that hippocampal CA1 PV-INs exhibit type 2 excitability, like striatal and neocortical PV-INs. Modelling and mathematical analysis showed that the slowly inactivating potassium current Kv1 contributes to type 2 excitability, enables the multiple firing regimes observed experimentally in PV-INs, and provides a mechanism for robust persistent interruption of firing. Using a fast/slow separation of times scales approach with the Kv1 inactivation variable as a bifurcation parameter shows that the initial inhibitory stimulus stops repetitive firing by moving the membrane potential trajectory onto a co-existing stable fixed point corresponding to a non-spiking quiescent state. As Kv1 inactivation decays, the trajectory follows the branch of stable fixed points until it crosses a subcritical Hopf bifurcation then spirals out into repetitive firing. In a model describing entorhinal cortical PV-INs without Kv1, interruption of firing could be achieved by taking advantage of the bistability inherent in type 2 excitability based on a subcritical Hopf bifurcation, but the interruption was not robust to noise. Persistent interruption of firing is therefore broadly applicable to PV-INs in different brain regions but is only made robust to noise in the presence of a slow variable.
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Affiliation(s)
- Carol M Upchurch
- Department of Cell Biology and Anatomy, Louisiana State University Health Sciences Center, New Orleans, LA 70112
| | - Christopher J Knowlton
- Department of Cell Biology and Anatomy, Louisiana State University Health Sciences Center, New Orleans, LA 70112
| | - Simon Chamberland
- NYU Neuroscience Institute and Department of Neuroscience and Physiology, NYU Langone Medical Center, New York, NY 10016, USA
| | - Carmen C Canavier
- Department of Cell Biology and Anatomy, Louisiana State University Health Sciences Center, New Orleans, LA 70112
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12
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Kidder K, Gillis R, Miles J, Mizumori SJY. The medial prefrontal cortex during flexible decisions: Evidence for its role in distinct working memory processes. Hippocampus 2024; 34:141-155. [PMID: 38095152 DOI: 10.1002/hipo.23594] [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: 06/14/2023] [Revised: 10/31/2023] [Accepted: 11/25/2023] [Indexed: 02/20/2024]
Abstract
During decisions that involve working memory, task-related information must be encoded, maintained across delays, and retrieved. Few studies have attempted to causally disambiguate how different brain structures contribute to each of these components of working memory. In the present study, we used transient optogenetic disruptions of rat medial prefrontal cortex (mPFC) during a serial spatial reversal learning (SSRL) task to test its role in these specific working memory processes. By analyzing numerous performance metrics, we found: (1) mPFC disruption impaired performance during only the choice epoch of initial discrimination learning of the SSRL task; (2) mPFC disruption impaired performance in dissociable ways across all task epochs (delay, choice, return) during flexible decision-making; (3) mPFC disruption resulted in a reduction of the typical vicarious-trial-and-error rate modulation that was related to changes in task demands. Taken together, these findings suggest that the mPFC plays an outsized role in working memory retrieval, becomes involved in encoding and maintenance when recent memories conflict with task demands, and enables animals to flexibly utilize working memory to update behavior as environments change.
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Affiliation(s)
- Kevan Kidder
- Department of Psychology, University of Washington, Seattle, Washington, USA
| | - Ryan Gillis
- Department of Psychology, University of Washington, Seattle, Washington, USA
| | - Jesse Miles
- Graduate Program in Neuroscience, University of Washington, Seattle, Washington, USA
| | - Sheri J Y Mizumori
- Department of Psychology, University of Washington, Seattle, Washington, USA
- Graduate Program in Neuroscience, University of Washington, Seattle, Washington, USA
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13
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Glasgow SD, Fisher TAJ, Wong EW, Lançon K, Feighan KM, Beamish IV, Gibon J, Séguéla P, Ruthazer ES, Kennedy TE. Acetylcholine synergizes with netrin-1 to drive persistent firing in the entorhinal cortex. Cell Rep 2024; 43:113812. [PMID: 38377003 DOI: 10.1016/j.celrep.2024.113812] [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: 10/13/2021] [Revised: 12/18/2023] [Accepted: 02/01/2024] [Indexed: 02/22/2024] Open
Abstract
The ability of the mammalian brain to maintain spatial representations of external or internal information for short periods of time has been associated with sustained neuronal spiking and reverberatory neural network activity in the medial entorhinal cortex. Here, we show that conditional genetic deletion of netrin-1 or the netrin receptor deleted-in-colorectal cancer (DCC) from forebrain excitatory neurons leads to deficits in short-term spatial memory. We then demonstrate that conditional deletion of either netrin-1 or DCC inhibits cholinergic persistent firing and show that cholinergic activation of muscarinic receptors expressed by entorhinal cortical neurons promotes persistent firing by recruiting DCC to the plasma membrane. Together, these findings indicate that normal short-term spatial memory function requires the synergistic actions of acetylcholine and netrin-1.
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Affiliation(s)
- Stephen D Glasgow
- Department of Neurology & Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montréal, QC H3A 2B4, Canada
| | - Teddy A J Fisher
- Department of Neurology & Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montréal, QC H3A 2B4, Canada
| | - Edwin W Wong
- Department of Neurology & Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montréal, QC H3A 2B4, Canada
| | - Kevin Lançon
- Department of Neurology & Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montréal, QC H3A 2B4, Canada
| | - Kira M Feighan
- Department of Neurology & Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montréal, QC H3A 2B4, Canada
| | - Ian V Beamish
- Department of Neurology & Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montréal, QC H3A 2B4, Canada
| | - Julien Gibon
- Department of Neurology & Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montréal, QC H3A 2B4, Canada
| | - Philippe Séguéla
- Department of Neurology & Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montréal, QC H3A 2B4, Canada
| | - Edward S Ruthazer
- Department of Neurology & Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montréal, QC H3A 2B4, Canada.
| | - Timothy E Kennedy
- Department of Neurology & Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montréal, QC H3A 2B4, Canada.
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14
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Yao J, Hou R, Fan H, Liu J, Chen Z, Hou J, Cheng Q, Li CT. Prefrontal projections modulate recurrent circuitry in the insular cortex to support short-term memory. Cell Rep 2024; 43:113756. [PMID: 38358886 DOI: 10.1016/j.celrep.2024.113756] [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: 05/01/2023] [Revised: 11/30/2023] [Accepted: 01/23/2024] [Indexed: 02/17/2024] Open
Abstract
Short-term memory (STM) maintains information during a short delay period. How long-range and local connections interact to support STM encoding remains elusive. Here, we tackle the problem focusing on long-range projections from the medial prefrontal cortex (mPFC) to the anterior agranular insular cortex (aAIC) in head-fixed mice performing an olfactory delayed-response task. Optogenetic and electrophysiological experiments reveal the behavioral importance of the two regions in encoding STM information. Spike-correlogram analysis reveals strong local and cross-region functional coupling (FC) between memory neurons encoding the same information. Optogenetic suppression of mPFC-aAIC projections during the delay period reduces behavioral performance, the proportion of memory neurons, and memory-specific FC within the aAIC, whereas optogenetic excitation enhances all of them. mPFC-aAIC projections also bidirectionally modulate the efficacy of STM-information transfer, measured by the contribution of FC spiking pairs to the memory-coding ability of following neurons. Thus, prefrontal projections modulate insular neurons' functional connectivity and memory-coding ability to support STM.
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Affiliation(s)
- Jian 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; Lingang Laboratory, Shanghai 200031, China
| | - Ruiqing Hou
- 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
| | - Hongmei Fan
- 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
| | - Jiawei 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
| | - Zhaoqin Chen
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 200031, China
| | - Jincan Hou
- 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; Lingang Laboratory, Shanghai 200031, China
| | - Qi Cheng
- 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; Lingang Laboratory, Shanghai 200031, China
| | - Chengyu T Li
- 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; Lingang Laboratory, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 200031, China.
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15
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Andreyanov M, Heinrich R, Berlin S. Design of Ultrapotent Genetically Encoded Inhibitors of Kv4.2 for Gating Neural Plasticity. J Neurosci 2024; 44:e2295222023. [PMID: 38154956 PMCID: PMC10869153 DOI: 10.1523/jneurosci.2295-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 11/05/2023] [Accepted: 11/22/2023] [Indexed: 12/30/2023] Open
Abstract
The Kv4.2 potassium channel plays established roles in neuronal excitability, while also being implicated in plasticity. Current means to study the roles of Kv4.2 are limited, motivating us to design a genetically encoded membrane tethered Heteropodatoxin-2 (MetaPoda). We find that MetaPoda is an ultrapotent and selective gating-modifier of Kv4.2. We narrow its site of contact with the channel to two adjacent residues within the voltage sensitive domain (VSD) and, with docking simulations, suggest that the toxin binds the VSD from within the membrane. We also show that MetaPoda does not require an external linker of the channel for its activity. In neurons (obtained from female and male rat neonates), MetaPoda specifically, and potently, inhibits all Kv4 currents, leaving all other A-type currents unaffected. Inhibition of Kv4 in hippocampal neurons does not promote excessive excitability, as is expected from a simple potassium channel blocker. We do find that MetaPoda's prolonged expression (1 week) increases expression levels of the immediate early gene cFos and prevents potentiation. These findings argue for a major role of Kv4.2 in facilitating plasticity of hippocampal neurons. Lastly, we show that our engineering strategy is suitable for the swift engineering of another potent Kv4.2-selective membrane-tethered toxin, Phrixotoxin-1, denoted MetaPhix. Together, we provide two uniquely potent genetic tools to study Kv4.2 in neuronal excitability and plasticity.
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Affiliation(s)
- Michael Andreyanov
- Department of Neuroscience, Ruth and Bruce Rappaport Faculty of Medicine, Technion- Israel Institute of Technology, Haifa 3525433, Israel
| | - Ronit Heinrich
- Department of Neuroscience, Ruth and Bruce Rappaport Faculty of Medicine, Technion- Israel Institute of Technology, Haifa 3525433, Israel
| | - Shai Berlin
- Department of Neuroscience, Ruth and Bruce Rappaport Faculty of Medicine, Technion- Israel Institute of Technology, Haifa 3525433, Israel
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16
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Sanhedrai H, Havlin S, Dvir H. Mechanistic description of spontaneous loss of memory persistent activity based on neuronal synaptic strength. Heliyon 2024; 10:e23949. [PMID: 38223719 PMCID: PMC10787259 DOI: 10.1016/j.heliyon.2023.e23949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 11/06/2023] [Accepted: 12/16/2023] [Indexed: 01/16/2024] Open
Abstract
Persistent neural activity associated with working memory (WM) lasts for a limited time duration. Current theories suggest that its termination is actively obtained via inhibitory currents, and there is currently no theory regarding the possibility of a passive memory-loss mechanism that terminates memory persistent activity. Here, we develop an analytical-framework, based on synaptic strength, and show via simulations and fitting to wet-lab experiments, that passive memory-loss might be a result of an ionic-current long-term plateau, i.e., very slow reduction of memory followed by abrupt loss. We describe analytically the plateau, when the memory state is just below criticality. These results, including the plateau, are supported by experiments performed on rats. Moreover, we show that even just above criticality, forgetfulness can occur due to neuronal noise with ionic-current fluctuations, yielding a plateau, representing memory with very slow decay, and eventually a fast memory decay. Our results could have implications for developing new medications, targeted against memory impairments, through modifying neuronal noise.
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Affiliation(s)
| | - Shlomo Havlin
- Department of Physics, Bar-Ilan University, Ramat-Gan, Israel
| | - Hila Dvir
- Department of Physics, Bar-Ilan University, Ramat-Gan, Israel
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17
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Kim I, Kupers ER, Lerma-Usabiaga G, Grill-Spector K. Characterizing Spatiotemporal Population Receptive Fields in Human Visual Cortex with fMRI. J Neurosci 2024; 44:e0803232023. [PMID: 37963768 PMCID: PMC10866195 DOI: 10.1523/jneurosci.0803-23.2023] [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: 04/04/2023] [Revised: 10/20/2023] [Accepted: 10/24/2023] [Indexed: 11/16/2023] Open
Abstract
The use of fMRI and computational modeling has advanced understanding of spatial characteristics of population receptive fields (pRFs) in human visual cortex. However, we know relatively little about the spatiotemporal characteristics of pRFs because neurons' temporal properties are one to two orders of magnitude faster than fMRI BOLD responses. Here, we developed an image-computable framework to estimate spatiotemporal pRFs from fMRI data. First, we developed a simulation software that predicts fMRI responses to a time-varying visual input given a spatiotemporal pRF model and solves the model parameters. The simulator revealed that ground-truth spatiotemporal parameters can be accurately recovered at the millisecond resolution from synthesized fMRI responses. Then, using fMRI and a novel stimulus paradigm, we mapped spatiotemporal pRFs in individual voxels across human visual cortex in 10 participants (both females and males). We find that a compressive spatiotemporal (CST) pRF model better explains fMRI responses than a conventional spatial pRF model across visual areas spanning the dorsal, lateral, and ventral streams. Further, we find three organizational principles of spatiotemporal pRFs: (1) from early to later areas within a visual stream, spatial and temporal windows of pRFs progressively increase in size and show greater compressive nonlinearities, (2) later visual areas show diverging spatial and temporal windows across streams, and (3) within early visual areas (V1-V3), both spatial and temporal windows systematically increase with eccentricity. Together, this computational framework and empirical results open exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses using fMRI.
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Affiliation(s)
- Insub Kim
- Department of Psychology, Stanford University, Stanford, CA, 94305
| | - Eline R Kupers
- Department of Psychology, Stanford University, Stanford, CA, 94305
| | - Garikoitz Lerma-Usabiaga
- BCBL. Basque Center on Cognition, Brain and Language, 20009 San Sebastian, Spain
- IKERBASQUE. Basque Foundation for Science, 48009 Bilbao, Spain
| | - Kalanit Grill-Spector
- Department of Psychology, Stanford University, Stanford, CA, 94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, 94305
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18
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Fazekas P, Cleeremans A, Overgaard M. A construct-first approach to consciousness science. Neurosci Biobehav Rev 2024; 156:105480. [PMID: 38008237 DOI: 10.1016/j.neubiorev.2023.105480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/26/2023] [Accepted: 11/20/2023] [Indexed: 11/28/2023]
Abstract
We propose a new approach to consciousness science that instead of comparing complex theoretical positions deconstructs existing theories, takes their central assumptions while disregarding their auxiliary hypotheses, and focuses its investigations on the main constructs that these central assumptions rely on (like global workspace, recurrent processing, metarepresentation). Studying how these main constructs are anchored in lower-level constructs characterizing underlying neural processing will not just offer an alternative to theory comparisons but will also take us one step closer to empirical resolutions. Moreover, exploring the compatibility and possible combinations of the lower-level constructs will allow for new theoretical syntheses. This construct-first approach will improve our ability to understand the commitments of existing theories and pave the way for moving beyond them.
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Affiliation(s)
- Peter Fazekas
- Aarhus Institute of Advanced Studies, Aarhus University, Høegh-Guldbergs Gade 6B, 8000 Aarhus, Denmark; Center of Functionally Integrative Neuroscience, Aarhus University, Universitetsbyen 3, 8000 Aarhus, Denmark.
| | - Axel Cleeremans
- Center for Research in Cognition & Neurosciences, Université Libre De Bruxelles, 50 avenue F.D. Roosevelt CP191, 1050 Bruxelles, Belgium
| | - Morten Overgaard
- Center of Functionally Integrative Neuroscience, Aarhus University, Universitetsbyen 3, 8000 Aarhus, Denmark
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19
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Lansner A, Fiebig F, Herman P. Fast Hebbian plasticity and working memory. Curr Opin Neurobiol 2023; 83:102809. [PMID: 37980802 DOI: 10.1016/j.conb.2023.102809] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 10/10/2023] [Accepted: 10/19/2023] [Indexed: 11/21/2023]
Abstract
Theories and models of working memory (WM) were at least since the mid-1990s dominated by the persistent activity hypothesis. The past decade has seen rising concerns about the shortcomings of sustained activity as the mechanism for short-term maintenance of WM information in the light of accumulating experimental evidence for so-called activity-silent WM and the fundamental difficulty in explaining robust multi-item WM. In consequence, alternative theories are now explored mostly in the direction of fast synaptic plasticity as the underlying mechanism. The question of non-Hebbian vs Hebbian synaptic plasticity emerges naturally in this context. In this review, we focus on fast Hebbian plasticity and trace the origins of WM theories and models building on this form of associative learning.
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Affiliation(s)
- Anders Lansner
- Stockholm University, Department of Mathematics, SE-106 91 Stockholm, Sweden; KTH Royal Institute of Technology, Dept of Computational Science and Technology, 100 44 Stockholm, Sweden; SeRC (Swedish e-Science Research Center), Sweden.
| | - Florian Fiebig
- KTH Royal Institute of Technology, Dept of Computational Science and Technology, 100 44 Stockholm, Sweden.
| | - Pawel Herman
- KTH Royal Institute of Technology, Dept of Computational Science and Technology, 100 44 Stockholm, Sweden; Digital Futures, KTH Royal Institute of Technology, Stockholm, Sweden; SeRC (Swedish e-Science Research Center), Sweden. https://twitter.com/PHermanKTHbrain
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20
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Ekins TG, Brooks I, Kailasa S, Rybicki-Kler C, Jedrasiak-Cape I, Donoho E, Mashour GA, Rech J, Ahmed OJ. Cellular rules underlying psychedelic control of prefrontal pyramidal neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.20.563334. [PMID: 37961554 PMCID: PMC10634703 DOI: 10.1101/2023.10.20.563334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Classical psychedelic drugs are thought to increase excitability of pyramidal cells in prefrontal cortex via activation of serotonin 2A receptors (5-HT2ARs). Here, we instead find that multiple classes of psychedelics dose-dependently suppress intrinsic excitability of pyramidal neurons, and that extracellular delivery of psychedelics decreases excitability significantly more than intracellular delivery. A previously unknown mechanism underlies this psychedelic drug action: enhancement of ubiquitously expressed potassium "M-current" channels that is independent of 5-HT2R activation. Using machine-learning-based data assimilation models, we show that M-current activation interacts with previously described mechanisms to dramatically reduce intrinsic excitability and shorten working memory timespan. Thus, psychedelic drugs suppress intrinsic excitability by modulating ion channels that are expressed throughout the brain, potentially triggering homeostatic adjustments that can contribute to widespread therapeutic benefits.
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Affiliation(s)
- Tyler G Ekins
- Dept. of Psychology, University of Michigan, Ann Arbor, MI 48109
- Michigan Psychedelic Center, University of Michigan, Ann Arbor, MI 48109
| | - Isla Brooks
- Dept. of Psychology, University of Michigan, Ann Arbor, MI 48109
| | - Sameer Kailasa
- Dept. of Mathematics, University of Michigan, Ann Arbor, MI 48109
| | - Chloe Rybicki-Kler
- Dept. of Psychology, University of Michigan, Ann Arbor, MI 48109
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109
| | | | - Ethan Donoho
- Dept. of Psychology, University of Michigan, Ann Arbor, MI 48109
| | - George A. Mashour
- Michigan Psychedelic Center, University of Michigan, Ann Arbor, MI 48109
| | - Jason Rech
- Department of Medicinal Chemistry, University of Michigan, Ann Arbor, MI 48109
| | - Omar J Ahmed
- Dept. of Psychology, University of Michigan, Ann Arbor, MI 48109
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109
- Michigan Psychedelic Center, University of Michigan, Ann Arbor, MI 48109
- Dept. of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109
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21
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Ma H, Qi Y, Gong P, Zhang J, Lu WL, Feng J. Self-Organization of Nonlinearly Coupled Neural Fluctuations Into Synergistic Population Codes. Neural Comput 2023; 35:1820-1849. [PMID: 37725705 DOI: 10.1162/neco_a_01612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 06/26/2023] [Indexed: 09/21/2023]
Abstract
Neural activity in the brain exhibits correlated fluctuations that may strongly influence the properties of neural population coding. However, how such correlated neural fluctuations may arise from the intrinsic neural circuit dynamics and subsequently affect the computational properties of neural population activity remains poorly understood. The main difficulty lies in resolving the nonlinear coupling between correlated fluctuations with the overall dynamics of the system. In this study, we investigate the emergence of synergistic neural population codes from the intrinsic dynamics of correlated neural fluctuations in a neural circuit model capturing realistic nonlinear noise coupling of spiking neurons. We show that a rich repertoire of spatial correlation patterns naturally emerges in a bump attractor network and further reveals the dynamical regime under which the interplay between differential and noise correlations leads to synergistic codes. Moreover, we find that negative correlations may induce stable bound states between two bumps, a phenomenon previously unobserved in firing rate models. These noise-induced effects of bump attractors lead to a number of computational advantages including enhanced working memory capacity and efficient spatiotemporal multiplexing and can account for a range of cognitive and behavioral phenomena related to working memory. This study offers a dynamical approach to investigating realistic correlated neural fluctuations and insights to their roles in cortical computations.
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Affiliation(s)
- Hengyuan Ma
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Yang Qi
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai 200433, China
| | - Pulin Gong
- School of Physics, University of Sydney, Sydney, NSW 2006, Australia
| | - Jie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai 200433, China
| | - Wen-Lian Lu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai 200433, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai 200433, China
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, U.K.
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22
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Nolan SO, Melugin PR, Erickson KR, Adams WR, Farahbakhsh ZZ, Mcgonigle CE, Kwon MH, Costa VD, Lapish CC, Hackett TA, Cuzon Carlson VC, Constantinidis C, Grant KA, Siciliano CA. Recurrent activity within microcircuits of macaque dorsolateral prefrontal cortex tracks cognitive flexibility. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.23.559125. [PMID: 38529503 PMCID: PMC10962741 DOI: 10.1101/2023.09.23.559125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Human and non-human primate data clearly implicate the dorsolateral prefrontal cortex (dlPFC) as critical for advanced cognitive functions 1,2 . It is thought that intracortical synaptic architectures within dlPFC are the integral neurobiological substrate that gives rise to these processes, including working memory, inferential reasoning, and decision-making 3-7 . In the prevailing model, each cortical column makes up one fundamental processing unit composed of dense intrinsic connectivity, conceptualized as the 'canonical' cortical microcircuit 3,8 . Each cortical microcircuit receives sensory and cognitive information from a variety of sources which are represented by sustained activity within the microcircuit, referred to as persistent or recurrent activity 4,9 . Via recurrent connections within the microcircuit, activity can propagate for a variable length of time, thereby allowing temporary storage and computations to occur locally before ultimately passing a transformed representation to a downstream output 4,5,10 . Competing theories regarding how microcircuit activity is coordinated have proven difficult to reconcile in vivo where intercortical and intracortical computations cannot be fully dissociated 5,9,11,12 . Here, we interrogated the intrinsic features of isolated microcircuit networks using high-density calcium imaging of macaque dlPFC ex vivo . We found that spontaneous activity is intrinsically maintained by microcircuit architecture, persisting at a high rate in the absence of extrinsic connections. Further, using perisulcal stimulation to evoke persistent activity in deep layers, we found that activity propagates through stochastically assembled intracortical networks, creating predictable population-level events from largely non-overlapping ensembles. Microcircuit excitability covaried with individual cognitive performance, thus anchoring heuristic models of abstract cortical functions within quantifiable constraints imposed by the underlying synaptic architecture.
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23
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Tan PK, Tang C, Herikstad R, Pillay A, Libedinsky C. Distinct Lateral Prefrontal Regions Are Organized in an Anterior-Posterior Functional Gradient. J Neurosci 2023; 43:6564-6572. [PMID: 37607819 PMCID: PMC10513068 DOI: 10.1523/jneurosci.0007-23.2023] [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: 01/03/2023] [Revised: 08/13/2023] [Accepted: 08/15/2023] [Indexed: 08/24/2023] Open
Abstract
The dorsolateral prefrontal cortex (dlPFC) is composed of multiple anatomically defined regions involved in higher-order cognitive processes, including working memory and selective attention. It is organized in an anterior-posterior global gradient where posterior regions track changes in the environment, whereas anterior regions support abstract neural representations. However, it remains unknown if such a global gradient results from a smooth gradient that spans regions or an emergent property arising from functionally distinct regions, that is, an areal gradient. Here, we recorded single neurons in the dlPFC of nonhuman primates trained to perform a memory-guided saccade task with an interfering distractor and analyzed their physiological properties along the anterior-posterior axis. We found that these physiological properties were best described by an areal gradient. Further, population analyses revealed that there is a distributed representation of spatial information across the dlPFC. Our results validate the functional boundaries between anatomically defined dlPFC regions and highlight the distributed nature of computations underlying working memory across the dlPFC.SIGNIFICANCE STATEMENT Activity of frontal lobe regions is known to possess an anterior-posterior functional gradient. However, it is not known whether this gradient is the result of individual brain regions organized in a gradient (like a staircase), or a smooth gradient that spans regions (like a slide). Analysis of physiological properties of individual neurons in the primate frontal regions suggest that individual regions are organized as a gradient, rather than a smooth gradient. At the population level, working memory was more prominent in posterior regions, although it was also present in anterior regions. This is consistent with the functional segregation of brain regions that is also observed in other systems (i.e., the visual system).
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Affiliation(s)
- Pin Kwang Tan
- Institute of Neuroscience, University of Texas at Austin, Austin, Texas 78712
| | - Cheng Tang
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Roger Herikstad
- The N1 Institute for Health, National University of Singapore, Singapore 117456
| | - Arunika Pillay
- Department of Psychology, Royal Holloway University of London, Egham TW20 OEX, United Kingdom
| | - Camilo Libedinsky
- The N1 Institute for Health, National University of Singapore, Singapore 117456
- Department of Psychology, National University of Singapore, Singapore 117570
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, National University of Singapore, Singapore 138632
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24
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Zimin IA, Kazantsev VB, Stasenko SV. Artificial Neural Network Model with Astrocyte-Driven Short-Term Memory. Biomimetics (Basel) 2023; 8:422. [PMID: 37754173 PMCID: PMC10526164 DOI: 10.3390/biomimetics8050422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 08/10/2023] [Accepted: 09/03/2023] [Indexed: 09/28/2023] Open
Abstract
In this study, we introduce an innovative hybrid artificial neural network model incorporating astrocyte-driven short-term memory. The model combines a convolutional neural network with dynamic models of short-term synaptic plasticity and astrocytic modulation of synaptic transmission. The model's performance was evaluated using simulated data from visual change detection experiments conducted on mice. Comparisons were made between the proposed model, a recurrent neural network simulating short-term memory based on sustained neural activity, and a feedforward neural network with short-term synaptic depression (STPNet) trained to achieve the same performance level as the mice. The results revealed that incorporating astrocytic modulation of synaptic transmission enhanced the model's performance.
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Affiliation(s)
- Ilya A. Zimin
- Laboratory of Advanced Methods for High-Dimensional Data Analysis, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia; (I.A.Z.); (V.B.K.)
| | - Victor B. Kazantsev
- Laboratory of Advanced Methods for High-Dimensional Data Analysis, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia; (I.A.Z.); (V.B.K.)
- Laboratory of Neurobiomorphic Technologies, Moscow Institute of Physics and Technology, 117303 Moscow, Russia
| | - Sergey V. Stasenko
- Laboratory of Advanced Methods for High-Dimensional Data Analysis, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia; (I.A.Z.); (V.B.K.)
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25
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Champion KP, Gozel O, Lankow BS, Ermentrout GB, Goldman MS. An oscillatory mechanism for multi-level storage in short-term memory. Commun Biol 2023; 6:829. [PMID: 37563448 PMCID: PMC10415352 DOI: 10.1038/s42003-023-05200-7] [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: 04/01/2022] [Accepted: 08/01/2023] [Indexed: 08/12/2023] Open
Abstract
Oscillatory activity is commonly observed during the maintenance of information in short-term memory, but its role remains unclear. Non-oscillatory models of short-term memory storage are able to encode stimulus identity through their spatial patterns of activity, but are typically limited to either an all-or-none representation of stimulus amplitude or exhibit a biologically implausible exact-tuning condition. Here we demonstrate a simple mechanism by which oscillatory input enables a circuit to generate persistent or sequential activity that encodes information not only in the spatial pattern of activity, but also in the amplitude of activity. This is accomplished through a phase-locking phenomenon that permits many different amplitudes of persistent activity to be stored without requiring exact tuning of model parameters. Altogether, this work proposes a class of models for the storage of information in working memory, a potential role for brain oscillations, and a dynamical mechanism for maintaining multi-stable neural representations.
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Affiliation(s)
- Kathleen P Champion
- Department of Applied Mathematics, University of Washington, Seattle, WA, 98195, USA
| | - Olivia Gozel
- Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, 60637, USA
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL, 60637, USA
| | - Benjamin S Lankow
- Center for Neuroscience, University of California, Davis, Davis, CA, 95618, USA
| | - G Bard Ermentrout
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, 15213, USA.
| | - Mark S Goldman
- Center for Neuroscience, University of California, Davis, Davis, CA, 95618, USA.
- Department of Neurobiology, Physiology, and Behavior, and Department of Ophthalmology and Vision Science, University of California, Davis, Davis, CA, 95618, USA.
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26
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Osanai H, Nair IR, Kitamura T. Dissecting cell-type-specific pathways in medial entorhinal cortical-hippocampal network for episodic memory. J Neurochem 2023; 166:172-188. [PMID: 37248771 PMCID: PMC10538947 DOI: 10.1111/jnc.15850] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 05/07/2023] [Accepted: 05/10/2023] [Indexed: 05/31/2023]
Abstract
Episodic memory, which refers to our ability to encode and recall past events, is essential to our daily lives. Previous research has established that both the entorhinal cortex (EC) and hippocampus (HPC) play a crucial role in the formation and retrieval of episodic memories. However, to understand neural circuit mechanisms behind these processes, it has become necessary to monitor and manipulate the neural activity in a cell-type-specific manner with high temporal precision during memory formation, consolidation, and retrieval in the EC-HPC networks. Recent studies using cell-type-specific labeling, monitoring, and manipulation have demonstrated that medial EC (MEC) contains multiple excitatory neurons that have differential molecular markers, physiological properties, and anatomical features. In this review, we will comprehensively examine the complementary roles of superficial layers of neurons (II and III) and the roles of deeper layers (V and VI) in episodic memory formation and recall based on these recent findings.
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Affiliation(s)
- Hisayuki Osanai
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Indrajith R Nair
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Takashi Kitamura
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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Yang H, Zhang J, Jin Z, Bashivan P, Li L. Using modular connectome-based predictive modeling to reveal brain-behavior relationships of individual differences in working memory. Brain Struct Funct 2023; 228:1479-1492. [PMID: 37349540 DOI: 10.1007/s00429-023-02666-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 06/11/2023] [Indexed: 06/24/2023]
Abstract
Working memory plays a crucial role in our daily lives, and brain imaging has been used to predict working memory performance. Here, we present an improved connectome-based predictive modeling approach for building a predictive model of individual working memory performance from whole-brain functional connectivity. The model was built using n-back task-based fMRI and resting-state fMRI data from the Human Connectome Project. Compared to prior models, our model was more interpretable, demonstrated a closer connection to the known anatomical and functional network. The model also demonstrates strong generalization on nine other cognitive behaviors from the HCP database and can well predict the working memory performance of healthy individuals in external datasets. By comparing the differences in prediction effects of different brain networks and anatomical feature analysis on n-back tasks, we found the essential role of some networks in differentiating between high and low working memory loads conditions.
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Affiliation(s)
- Huayi Yang
- MOE Key Lab for NeuroInformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Psychiatry and Psychology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
- Department of Physiology, McGill University, Montréal, QC, H3G 1Y6, Canada
| | - Junjun Zhang
- MOE Key Lab for NeuroInformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Psychiatry and Psychology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Zhenlan Jin
- MOE Key Lab for NeuroInformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Psychiatry and Psychology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Pouya Bashivan
- Department of Physiology, McGill University, Montréal, QC, H3G 1Y6, Canada
- Mila, University of Montreal, Montréal, QC, H2S 3H1, Canada
| | - Ling Li
- MOE Key Lab for NeuroInformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Psychiatry and Psychology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China.
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28
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Kim I, Kupers ER, Lerma-Usabiaga G, Grill-Spector K. Characterizing spatiotemporal population receptive fields in human visual cortex with fMRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.02.539164. [PMID: 37205541 PMCID: PMC10187260 DOI: 10.1101/2023.05.02.539164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
The use of fMRI and computational modeling has advanced understanding of spatial characteristics of population receptive fields (pRFs) in human visual cortex. However, we know relatively little about the spatiotemporal characteristics of pRFs because neurons' temporal properties are one to two orders of magnitude faster than fMRI BOLD responses. Here, we developed an image-computable framework to estimate spatiotemporal pRFs from fMRI data. First, we developed a simulation software that predicts fMRI responses to a time varying visual input given a spatiotemporal pRF model and solves the model parameters. The simulator revealed that ground-truth spatiotemporal parameters can be accurately recovered at the millisecond resolution from synthesized fMRI responses. Then, using fMRI and a novel stimulus paradigm, we mapped spatiotemporal pRFs in individual voxels across human visual cortex in 10 participants. We find that a compressive spatiotemporal (CST) pRF model better explains fMRI responses than a conventional spatial pRF model across visual areas spanning the dorsal, lateral, and ventral streams. Further, we find three organizational principles of spatiotemporal pRFs: (i) from early to later areas within a visual stream, spatial and temporal integration windows of pRFs progressively increase in size and show greater compressive nonlinearities, (ii) later visual areas show diverging spatial and temporal integration windows across streams, and (iii) within early visual areas (V1-V3), both spatial and temporal integration windows systematically increase with eccentricity. Together, this computational framework and empirical results open exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses in the human brain using fMRI.
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Affiliation(s)
- Insub Kim
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Eline R. Kupers
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Garikoitz Lerma-Usabiaga
- BCBL. Basque Center on Cognition, Brain and Language, San Sebastian, Spain
- IKERBASQUE. Basque foundation for science, Bilbao, Spain
| | - Kalanit Grill-Spector
- Department of Psychology, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
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29
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Domanski APF, Kucewicz MT, Russo E, Tricklebank MD, Robinson ESJ, Durstewitz D, Jones MW. Distinct hippocampal-prefrontal neural assemblies coordinate memory encoding, maintenance, and recall. Curr Biol 2023; 33:1220-1236.e4. [PMID: 36898372 PMCID: PMC10728550 DOI: 10.1016/j.cub.2023.02.029] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 01/05/2023] [Accepted: 02/08/2023] [Indexed: 03/11/2023]
Abstract
Short-term memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both the prefrontal cortex and hippocampus, where neurons encode task cues, rules, and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC populations lead in maintaining sample information across delays of an operant non-match to sample task, despite individual neurons firing only transiently. During sample encoding, distinct mPFC subpopulations joined distributed CA1-mPFC cell assemblies hallmarked by 4-5 Hz rhythmic modulation; CA1-mPFC assemblies re-emerged during choice episodes but were not 4-5 Hz modulated. Delay-dependent errors arose when attenuated rhythmic assembly activity heralded collapse of sustained mPFC encoding. Our results map component processes of memory-guided decisions onto heterogeneous CA1-mPFC subpopulations and the dynamics of physiologically distinct, distributed cell assemblies.
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Affiliation(s)
- Aleksander P F Domanski
- School of Physiology, Pharmacology & Neuroscience, Faculty of Life Sciences, University of Bristol, University Walk, Bristol BS8 1TD, UK; The Alan Turing Institute, British Library, 96 Euston Rd, London, UK; The Francis Crick Institute, 1 Midland Road, London, UK
| | - Michal T Kucewicz
- School of Physiology, Pharmacology & Neuroscience, Faculty of Life Sciences, University of Bristol, University Walk, Bristol BS8 1TD, UK; BioTechMed Center, Brain & Mind Electrophysiology Laboratory, Multimedia Systems Department, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdansk, Poland.
| | - Eleonora Russo
- Department of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, 68159 Mannheim, Germany; Department of Psychiatry and Psychotherapy, University Medical Center, Johannes Gutenberg University, 55131 Mainz, Germany
| | - Mark D Tricklebank
- Centre for Neuroimaging Science, King's College London, Denmark Hill, London SE5 8AF, UK
| | - Emma S J Robinson
- School of Physiology, Pharmacology & Neuroscience, Faculty of Life Sciences, University of Bristol, University Walk, Bristol BS8 1TD, UK
| | - Daniel Durstewitz
- Department of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, 68159 Mannheim, Germany
| | - Matt W Jones
- School of Physiology, Pharmacology & Neuroscience, Faculty of Life Sciences, University of Bristol, University Walk, Bristol BS8 1TD, UK
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30
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Daume J, Kaminski J, Schjetnan AGP, Salimpour Y, Khan U, Reed C, Anderson W, Valiante TA, Mamelak AN, Rutishauser U. Control of working memory maintenance by theta-gamma phase amplitude coupling of human hippocampal neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.05.535772. [PMID: 37066145 PMCID: PMC10104113 DOI: 10.1101/2023.04.05.535772] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Retaining information in working memory (WM) is a demanding process that relies on cognitive control to protect memoranda-specific persistent activity from interference. How cognitive control regulates WM storage, however, remains unknown. We hypothesized that interactions of frontal control and hippocampal persistent activity are coordinated by theta-gamma phase amplitude coupling (TG-PAC). We recorded single neurons in the human medial temporal and frontal lobe while patients maintained multiple items in WM. In the hippocampus, TG-PAC was indicative of WM load and quality. We identified cells that selectively spiked during nonlinear interactions of theta phase and gamma amplitude. These PAC neurons were more strongly coordinated with frontal theta activity when cognitive control demand was high, and they introduced information-enhancing and behaviorally relevant noise correlations with persistently active neurons in the hippocampus. We show that TG-PAC integrates cognitive control and WM storage to improve the fidelity of WM representations and facilitate behavior.
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Affiliation(s)
- Jonathan Daume
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jan Kaminski
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Nencki Institute of Experimental Biology, Warsaw, Poland
| | - Andrea G P Schjetnan
- Krembil Research Institute and Division of Neurosurgery, University Health Network (UHN), University of Toronto, Toronto, ON, Canada
| | - Yousef Salimpour
- Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Umais Khan
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Chrystal Reed
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - William Anderson
- Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Taufik A Valiante
- Krembil Research Institute and Division of Neurosurgery, University Health Network (UHN), University of Toronto, Toronto, ON, Canada
| | - Adam N Mamelak
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Ueli Rutishauser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
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31
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Fallahnezhad M, Le Mero J, Zenelaj X, Vincent J, Rochefort C, Rondi-Reig L. Cerebellar control of a unitary head direction sense. Proc Natl Acad Sci U S A 2023; 120:e2214539120. [PMID: 36812198 PMCID: PMC9992783 DOI: 10.1073/pnas.2214539120] [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: 08/24/2022] [Accepted: 01/17/2023] [Indexed: 02/24/2023] Open
Abstract
The head-direction (HD) system, a key neural circuit for navigation, consists of several anatomical structures containing neurons selective to the animal's head direction. HD cells exhibit ubiquitous temporal coordination across brain regions, independently of the animal's behavioral state or sensory inputs. Such temporal coordination mediates a single, stable, and persistent HD signal, which is essential for intact orientation. However, the mechanistic processes behind the temporal organization of HD cells are unknown. By manipulating the cerebellum, we identify pairs of HD cells recorded from two brain structures (anterodorsal thalamus and retrosplenial cortex) that lose their temporal coordination, specifically during the removal of the external sensory inputs. Further, we identify distinct cerebellar mechanisms that participate in the spatial stability of the HD signal depending on sensory signals. We show that while cerebellar protein phosphatase 2B-dependent mechanisms facilitate the anchoring of the HD signal on the external cues, the cerebellar protein kinase C-dependent mechanisms are required for the stability of the HD signal by self-motion cues. These results indicate that the cerebellum contributes to the preservation of a single and stable sense of direction.
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Affiliation(s)
- Mehdi Fallahnezhad
- Sorbonne Université, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médical, Institut de Biologie Paris Seine, Neurosciences Paris Seine, Cerebellum, Navigation and Memory Team, 75005Paris, France
- Inovarion, 75005Paris, France
| | - Julia Le Mero
- Sorbonne Université, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médical, Institut de Biologie Paris Seine, Neurosciences Paris Seine, Cerebellum, Navigation and Memory Team, 75005Paris, France
| | - Xhensjana Zenelaj
- Sorbonne Université, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médical, Institut de Biologie Paris Seine, Neurosciences Paris Seine, Cerebellum, Navigation and Memory Team, 75005Paris, France
| | - Jean Vincent
- Sorbonne Université, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médical, Institut de Biologie Paris Seine, Neurosciences Paris Seine, Cerebellum, Navigation and Memory Team, 75005Paris, France
| | - Christelle Rochefort
- Sorbonne Université, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médical, Institut de Biologie Paris Seine, Neurosciences Paris Seine, Cerebellum, Navigation and Memory Team, 75005Paris, France
| | - Laure Rondi-Reig
- Sorbonne Université, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médical, Institut de Biologie Paris Seine, Neurosciences Paris Seine, Cerebellum, Navigation and Memory Team, 75005Paris, France
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32
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Liu A, Milner ES, Peng YR, Blume HA, Brown MC, Bryman GS, Emanuel AJ, Morquette P, Viet NM, Sanes JR, Gamlin PD, Do MTH. Encoding of environmental illumination by primate melanopsin neurons. Science 2023; 379:376-381. [PMID: 36701440 PMCID: PMC10445534 DOI: 10.1126/science.ade2024] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 11/21/2022] [Indexed: 01/27/2023]
Abstract
Light regulates physiology, mood, and behavior through signals sent to the brain by intrinsically photosensitive retinal ganglion cells (ipRGCs). How primate ipRGCs sense light is unclear, as they are rare and challenging to target for electrophysiological recording. We developed a method of acute identification within the live, ex vivo retina. Using it, we found that ipRGCs of the macaque monkey are highly specialized to encode irradiance (the overall intensity of illumination) by blurring spatial, temporal, and chromatic features of the visual scene. We describe mechanisms at the molecular, cellular, and population scales that support irradiance encoding across orders-of-magnitude changes in light intensity. These mechanisms are conserved quantitatively across the ~70 million years of evolution that separate macaques from mice.
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Affiliation(s)
- Andreas Liu
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital and Harvard Medical School. Boston, MA 02115, USA
| | - Elliott S. Milner
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital and Harvard Medical School. Boston, MA 02115, USA
- Present address: Sainsbury Wellcome Centre for Neural Circuits and Behavior, University College London, 25 Howland Street, London, W1T 4JG, UK
| | - Yi-Rong Peng
- Department of Molecular and Cellular Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Present address: Department of Ophthalmology, Stein Eye Institute, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA
| | - Hannah A. Blume
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital and Harvard Medical School. Boston, MA 02115, USA
| | - Michael C. Brown
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital and Harvard Medical School. Boston, MA 02115, USA
| | - Gregory S. Bryman
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital and Harvard Medical School. Boston, MA 02115, USA
- Present address: Merck & Co., Inc., 320 Bent St, Cambridge, MA 02141, USA
| | - Alan J. Emanuel
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital and Harvard Medical School. Boston, MA 02115, USA
- Present address: Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA, 02115, USA
| | - Philippe Morquette
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital and Harvard Medical School. Boston, MA 02115, USA
| | - Nguyen-Minh Viet
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital and Harvard Medical School. Boston, MA 02115, USA
| | - Joshua R. Sanes
- Department of Molecular and Cellular Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Paul D. Gamlin
- Department of Ophthalmology and Visual Sciences, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Michael Tri H. Do
- F. M. Kirby Neurobiology Center and Department of Neurology, Boston Children’s Hospital and Harvard Medical School. Boston, MA 02115, USA
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33
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Lu L, Gao Z, Wei Z, Yi M. Working memory depends on the excitatory-inhibitory balance in neuron-astrocyte network. CHAOS (WOODBURY, N.Y.) 2023; 33:013127. [PMID: 36725632 DOI: 10.1063/5.0126890] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 12/19/2022] [Indexed: 06/18/2023]
Abstract
Previous studies have shown that astrocytes are involved in information processing and working memory (WM) in the central nervous system. Here, the neuron-astrocyte network model with biological properties is built to study the effects of excitatory-inhibitory balance and neural network structures on WM tasks. It is found that the performance metrics of WM tasks under the scale-free network are higher than other network structures, and the WM task can be successfully completed when the proportion of excitatory neurons in the network exceeds 30%. There exists an optimal region for the proportion of excitatory neurons and synaptic weight that the memory performance metrics of the WM tasks are higher. The multi-item WM task shows that the spatial calcium patterns for different items overlap significantly in the astrocyte network, which is consistent with the formation of cognitive memory in the brain. Moreover, complex image tasks show that cued recall can significantly reduce systematic noise and maintain the stability of the WM tasks. The results may contribute to understand the mechanisms of WM formation and provide some inspirations into the dynamic storage and recall of memory.
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Affiliation(s)
- Lulu Lu
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
| | - Zhuoheng Gao
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
| | - Zhouchao Wei
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
| | - Ming Yi
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
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34
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Persistence in a large network of sparsely interacting neurons. J Math Biol 2022; 86:16. [PMID: 36534174 DOI: 10.1007/s00285-022-01844-x] [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: 12/15/2021] [Revised: 09/26/2022] [Accepted: 11/22/2022] [Indexed: 12/23/2022]
Abstract
This article presents a biological neural network model driven by inhomogeneous Poisson processes accounting for the intrinsic randomness of synapses. The main novelty is the introduction of sparse interactions: each firing neuron triggers an instantaneous increase in electric potential to a fixed number of randomly chosen neurons. We prove that, as the number of neurons approaches infinity, the finite network converges to a nonlinear mean-field process characterised by a jump-type stochastic differential equation. We show that this process displays a phase transition: the activity of a typical neuron in the infinite network either rapidly dies out, or persists forever, depending on the global parameters describing the intensity of interconnection. This provides a way to understand the emergence of persistent activity triggered by weak input signals in large neural networks.
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35
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Kirschhock ME, Nieder A. Number selective sensorimotor neurons in the crow translate perceived numerosity into number of actions. Nat Commun 2022; 13:6913. [PMID: 36376297 PMCID: PMC9663431 DOI: 10.1038/s41467-022-34457-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 10/25/2022] [Indexed: 11/16/2022] Open
Abstract
Translating a perceived number into a matching number of self-generated actions is a hallmark of numerical reasoning in humans and animals alike. To explore this sensorimotor transformation, we trained crows to judge numerical values in displays and to flexibly plan and perform a matching number of pecks. We report number selective sensorimotor neurons in the crow telencephalon that signaled the impending number of self-generated actions. Neuronal population activity during the sensorimotor transformation period predicted whether the crows mistakenly planned fewer or more pecks than instructed. During sensorimotor transformation, both a static neuronal code characterized by persistently number-selective neurons and a dynamic code originating from neurons carrying rapidly changing numerical information emerged. The findings indicate there are distinct functions of abstract neuronal codes supporting the sensorimotor number system.
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Affiliation(s)
- Maximilian E. Kirschhock
- grid.10392.390000 0001 2190 1447Animal Physiology Unit, Institute of Neurobiology, University of Tübingen, Auf der Morgenstelle 28, 72076 Tübingen, Germany
| | - Andreas Nieder
- grid.10392.390000 0001 2190 1447Animal Physiology Unit, Institute of Neurobiology, University of Tübingen, Auf der Morgenstelle 28, 72076 Tübingen, Germany
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36
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Karigo T, Deutsch D. Flexibility of neural circuits regulating mating behaviors in mice and flies. Front Neural Circuits 2022; 16:949781. [PMID: 36426135 PMCID: PMC9679785 DOI: 10.3389/fncir.2022.949781] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 07/28/2022] [Indexed: 11/11/2022] Open
Abstract
Mating is essential for the reproduction of animal species. As mating behaviors are high-risk and energy-consuming processes, it is critical for animals to make adaptive mating decisions. This includes not only finding a suitable mate, but also adapting mating behaviors to the animal's needs and environmental conditions. Internal needs include physical states (e.g., hunger) and emotional states (e.g., fear), while external conditions include both social cues (e.g., the existence of predators or rivals) and non-social factors (e.g., food availability). With recent advances in behavioral neuroscience, we are now beginning to understand the neural basis of mating behaviors, particularly in genetic model organisms such as mice and flies. However, how internal and external factors are integrated by the nervous system to enable adaptive mating-related decision-making in a state- and context-dependent manner is less well understood. In this article, we review recent knowledge regarding the neural basis of flexible mating behaviors from studies of flies and mice. By contrasting the knowledge derived from these two evolutionarily distant model organisms, we discuss potential conserved and divergent neural mechanisms involved in the control of flexible mating behaviors in invertebrate and vertebrate brains.
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Affiliation(s)
- Tomomi Karigo
- Kennedy Krieger Institute, Baltimore, MD, United States,The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, United States,*Correspondence: Tomomi Karigo,
| | - David Deutsch
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel,David Deutsch,
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37
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Differences in temporal processing speeds between the right and left auditory cortex reflect the strength of recurrent synaptic connectivity. PLoS Biol 2022; 20:e3001803. [PMID: 36269764 PMCID: PMC9629599 DOI: 10.1371/journal.pbio.3001803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 11/02/2022] [Accepted: 08/24/2022] [Indexed: 11/23/2022] Open
Abstract
Brain asymmetry in the sensitivity to spectrotemporal modulation is an established functional feature that underlies the perception of speech and music. The left auditory cortex (ACx) is believed to specialize in processing fast temporal components of speech sounds, and the right ACx slower components. However, the circuit features and neural computations behind these lateralized spectrotemporal processes are poorly understood. To answer these mechanistic questions we use mice, an animal model that captures some relevant features of human communication systems. In this study, we screened for circuit features that could subserve temporal integration differences between the left and right ACx. We mapped excitatory input to principal neurons in all cortical layers and found significantly stronger recurrent connections in the superficial layers of the right ACx compared to the left. We hypothesized that the underlying recurrent neural dynamics would exhibit differential characteristic timescales corresponding to their hemispheric specialization. To investigate, we recorded spike trains from awake mice and estimated the network time constants using a statistical method to combine evidence from multiple weak signal-to-noise ratio neurons. We found longer temporal integration windows in the superficial layers of the right ACx compared to the left as predicted by stronger recurrent excitation. Our study shows substantial evidence linking stronger recurrent synaptic connections to longer network timescales. These findings support speech processing theories that purport asymmetry in temporal integration is a crucial feature of lateralization in auditory processing.
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38
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Spike Afterhyperpolarizations Govern Persistent Firing Dynamics in Rat Neocortical and Hippocampal Pyramidal Cells. J Neurosci 2022; 42:7690-7706. [PMID: 36414011 PMCID: PMC9581562 DOI: 10.1523/jneurosci.0570-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 08/10/2022] [Accepted: 08/28/2022] [Indexed: 12/14/2022] Open
Abstract
Persistent firing is commonly reported in both cortical and subcortical neurons under a variety of behavioral conditions. Yet the mechanisms responsible for persistent activity are only partially resolved with support for both intrinsic and synaptic circuit-based mechanisms. Little also is known about physiological factors that enable epochs of persistent firing to continue beyond brief pauses and then spontaneously terminate. In the present study, we used intracellular recordings in rat (both sexes) neocortical and hippocampal brain slices to assess the ionic mechanisms underlying persistent firing dynamics. Previously, we showed that blockade of ether-á-go-go-related gene (ERG) potassium channels abolished intrinsic persistent firing in the presence of low concentrations of muscarinic receptor agonists and following optogenetic activation of cholinergic axons. Here we show the slow dynamics of ERG conductance changes allows persistent firing to outlast the triggering stimulus and even to initiate discharges following ∼7 s poststimulus firing pauses. We find that persistent firing dynamics is regulated by the interaction between ERG conductance and spike afterhyperpolarizations (AHPs). Increasing the amplitude of spike AHPs using either SK channel activators or a closed-loop reactive feedback system allows persistent discharges to spontaneously terminate in both neocortical neurons and hippocampal CA1 pyramidal cells. The interplay between ERG and the potassium channels that mediate spike AHPs grades the duration of persistent firing, providing a novel, generalizable mechanism to explain self-terminating persistent firing modes observed behaving animals.SIGNIFICANCE STATEMENT Many classes of neurons generate prolonged spiking responses to transient stimuli. These discharges often outlast the stimulus by seconds to minutes in some in vitro models of persistent firing. While recent work has identified key synaptic and intrinsic components that enable persistent spiking responses, less is known about mechanisms that can terminate and regulate the dynamics of these responses. The present study identified the spike afterhyperpolarizations as a potent mechanism that regulates the duration of persistent firing. We found that amplifying spike afterpotentials converted bistable persistent firing into self-terminating discharges. Varying the spike AHP amplitude grades the duration of persistent discharges, generating in vitro responses that mimic firing modes associated with neurons associated with short-term memory function.
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39
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Deere JU, Devineni AV. Taste cues elicit prolonged modulation of feeding behavior in Drosophila. iScience 2022; 25:105159. [PMID: 36204264 PMCID: PMC9529979 DOI: 10.1016/j.isci.2022.105159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 08/02/2022] [Accepted: 09/15/2022] [Indexed: 11/29/2022] Open
Abstract
Taste cues regulate immediate feeding behavior, but their ability to modulate future behavior has been less well studied. Pairing one taste with another can modulate subsequent feeding responses through associative learning, but this requires simultaneous exposure to both stimuli. We investigated whether exposure to one taste modulates future responses to other tastes even when they do not overlap in time. Using Drosophila, we found that brief exposure to sugar enhanced future feeding responses, whereas bitter exposure suppressed them. This modulation relies on neural pathways distinct from those that acutely regulate feeding or mediate learning-dependent changes. Sensory neuron activity was required not only during initial taste exposure but also afterward, suggesting that ongoing sensory activity may maintain experience-dependent changes in downstream circuits. Thus, the brain stores a memory of each taste stimulus after it disappears, enabling animals to integrate information as they sequentially sample different taste cues that signal local food quality. Brief exposure to taste cues modulates future feeding responses Distinct neural pathways regulate feeding in different contexts Sensory neuron activity is required during and after taste exposure for modulation Prolonged modulation may allow animals to integrate taste information over time
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Affiliation(s)
- Julia U. Deere
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Anita V. Devineni
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
- Department of Biology, Emory University, Atlanta, GA 30322, USA
- Corresponding author
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40
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Jiang LX, Huang GD, Wang HL, Zhang C, Yu X. The protocol for assessing olfactory working memory capacity in mice. Brain Behav 2022; 12:e2703. [PMID: 35849713 PMCID: PMC9392537 DOI: 10.1002/brb3.2703] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 06/04/2022] [Accepted: 06/27/2022] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Working memory capacity (WMC) is the ability to maintain information over a few seconds. Although it has been extensively studied in healthy subjects and neuropsychiatric patients, few tasks have been developed to measure such changes in rodents. Many procedures have been used to measure WM in rodents, including the radial arm maze, the WM version of the Morris swimming task, and various delayed matching and nonmatching-to-sample tasks. It should be noted, however, that the memory components assessed in these procedures do not include memory capacity. METHODS We developed an olfactory working memory capacity (OWMC) paradigm to assess the WMC of 3-month-old 5×FAD mice, a mouse model of Alzheimer's disease. The task is divided into five phases: context adaptation, digging training, rule learning for nonmatching to a single sample odor (NMSS), rule learning for nonmatching to multiple sample odors (NMMS), and capacity testing. RESULTS In the NMSS rule-learning phase, there was no difference between wild-type (WT) mice and 5×FAD mice in the performance correct rate, correct option rate, and correct rejection rate. The WT mice and 5×FAD mice showed similar memory capacity in the NMMS rule-learning phase. After capacity test, we found that the WMC was significantly diminished in 5×FAD mice. As the memory load increased, 5×FAD mice also made significantly more errors than WT mice. CONCLUSION The OWMC task, based on a nonmatch-to-sample rule, is a sensitive and robust behavioral assay that we validated as a reliable method for measuring WMC and exploring different components of memory in mice.
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Affiliation(s)
- Li-Xin Jiang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University), Beijing, China.,Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Geng-Di Huang
- Peking University Shenzhen Graduate School, Shenzhen, China.,Shenzhen Kangning Hospital & Shenzhen Mental Health Center, Shenzhen, China
| | - Hua-Li Wang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University), Beijing, China.,Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Chen Zhang
- Capital Medical University, Youanmenwai, Beijing, China
| | - Xin Yu
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University), Beijing, China.,Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
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41
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Voitov I, Mrsic-Flogel TD. Cortical feedback loops bind distributed representations of working memory. Nature 2022; 608:381-389. [PMID: 35896749 PMCID: PMC9365695 DOI: 10.1038/s41586-022-05014-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 06/22/2022] [Indexed: 11/16/2022]
Abstract
Working memory—the brain’s ability to internalize information and use it flexibly to guide behaviour—is an essential component of cognition. Although activity related to working memory has been observed in several brain regions1–3, how neural populations actually represent working memory4–7 and the mechanisms by which this activity is maintained8–12 remain unclear13–15. Here we describe the neural implementation of visual working memory in mice alternating between a delayed non-match-to-sample task and a simple discrimination task that does not require working memory but has identical stimulus, movement and reward statistics. Transient optogenetic inactivations revealed that distributed areas of the neocortex were required selectively for the maintenance of working memory. Population activity in visual area AM and premotor area M2 during the delay period was dominated by orderly low-dimensional dynamics16,17 that were, however, independent of working memory. Instead, working memory representations were embedded in high-dimensional population activity, present in both cortical areas, persisted throughout the inter-stimulus delay period, and predicted behavioural responses during the working memory task. To test whether the distributed nature of working memory was dependent on reciprocal interactions between cortical regions18–20, we silenced one cortical area (AM or M2) while recording the feedback it received from the other. Transient inactivation of either area led to the selective disruption of inter-areal communication of working memory. Therefore, reciprocally interconnected cortical areas maintain bound high-dimensional representations of working memory. Experiments in mice alternating between a visual working memory task and a task that is independent of working memory provide insight into the neural representation of working memory and the distributed nature of its maintenance.
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Affiliation(s)
- Ivan Voitov
- Sainsbury Wellcome Centre, University College London, London, UK. .,Biozentrum, University of Basel, Basel, Switzerland.
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42
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Ursino M, Cesaretti N, Pirazzini G. A model of working memory for encoding multiple items and ordered sequences exploiting the theta-gamma code. Cogn Neurodyn 2022; 17:489-521. [PMID: 37007198 PMCID: PMC10050512 DOI: 10.1007/s11571-022-09836-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 02/25/2022] [Accepted: 05/27/2022] [Indexed: 11/24/2022] Open
Abstract
AbstractRecent experimental evidence suggests that oscillatory activity plays a pivotal role in the maintenance of information in working memory, both in rodents and humans. In particular, cross-frequency coupling between theta and gamma oscillations has been suggested as a core mechanism for multi-item memory. The aim of this work is to present an original neural network model, based on oscillating neural masses, to investigate mechanisms at the basis of working memory in different conditions. We show that this model, with different synapse values, can be used to address different problems, such as the reconstruction of an item from partial information, the maintenance of multiple items simultaneously in memory, without any sequential order, and the reconstruction of an ordered sequence starting from an initial cue. The model consists of four interconnected layers; synapses are trained using Hebbian and anti-Hebbian mechanisms, in order to synchronize features in the same items, and desynchronize features in different items. Simulations show that the trained network is able to desynchronize up to nine items without a fixed order using the gamma rhythm. Moreover, the network can replicate a sequence of items using a gamma rhythm nested inside a theta rhythm. The reduction in some parameters, mainly concerning the strength of GABAergic synapses, induce memory alterations which mimic neurological deficits. Finally, the network, isolated from the external environment (“imagination phase”) and stimulated with high uniform noise, can randomly recover sequences previously learned, and link them together by exploiting the similarity among items.
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Affiliation(s)
- Mauro Ursino
- Department of Electrical, Electronic and Information Engineering “Guglielmo Marconi”, University of Bologna, Campus of Cesena Area di Campus Cesena Via Dell’Università 50, 47521 Cesena, FC Italy
| | - Nicole Cesaretti
- Department of Electrical, Electronic and Information Engineering “Guglielmo Marconi”, University of Bologna, Campus of Cesena Area di Campus Cesena Via Dell’Università 50, 47521 Cesena, FC Italy
| | - Gabriele Pirazzini
- Department of Electrical, Electronic and Information Engineering “Guglielmo Marconi”, University of Bologna, Campus of Cesena Area di Campus Cesena Via Dell’Università 50, 47521 Cesena, FC Italy
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Inagaki HK, Chen S, Daie K, Finkelstein A, Fontolan L, Romani S, Svoboda K. Neural Algorithms and Circuits for Motor Planning. Annu Rev Neurosci 2022; 45:249-271. [PMID: 35316610 DOI: 10.1146/annurev-neuro-092021-121730] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The brain plans and executes volitional movements. The underlying patterns of neural population activity have been explored in the context of movements of the eyes, limbs, tongue, and head in nonhuman primates and rodents. How do networks of neurons produce the slow neural dynamics that prepare specific movements and the fast dynamics that ultimately initiate these movements? Recent work exploits rapid and calibrated perturbations of neural activity to test specific dynamical systems models that are capable of producing the observed neural activity. These joint experimental and computational studies show that cortical dynamics during motor planning reflect fixed points of neural activity (attractors). Subcortical control signals reshape and move attractors over multiple timescales, causing commitment to specific actions and rapid transitions to movement execution. Experiments in rodents are beginning to reveal how these algorithms are implemented at the level of brain-wide neural circuits.
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Affiliation(s)
| | - Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Kayvon Daie
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA.,Allen Institute for Neural Dynamics, Seattle, Washington, USA;
| | - Arseny Finkelstein
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA.,Department of Physiology and Pharmacology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Lorenzo Fontolan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Sandro Romani
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA.,Allen Institute for Neural Dynamics, Seattle, Washington, USA;
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Andreau JM, Funahashi S. Prefrontal Neuronal Activities During Active Retrieval of Information From Long-Term Memory. J PSYCHOPHYSIOL 2022. [DOI: 10.1027/0269-8803/a000306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Abstract. Single-neuron studies performed in the primate prefrontal cortex (PFC) revealed that retaining information in working memory (WM) is associated with sustained firing during the delay period in a match-to-sample task. On the other hand, single-neuron studies using a pair-association task have shown that retrieving information from long-term memory (LTM) is related to two kinds of neural activities: decreasing activity representing information linked to the sample stimulus and increasing activity predicting information for the forthcoming matching stimulus. To further examine neuronal behavioral patterns during LTM retrieval, we used a partial correlation coefficient analysis to analyze single-neuron activities in the PFC while monkeys performed the visual pair-association task. Results showed that, for most of the task-related neurons, firing activity depicted information from the sample stimulus. Nevertheless, some neurons showed an opposite pattern, this is, increasing activity during the delay period, possibly indicating a prospective memory coding from LTM. Interestingly, both activities seem to be present at different degrees as the delay period progresses. Together, these results unveil a new aspect of PFC neurons when retrieving unseen information from LTM.
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Affiliation(s)
- Jorge Mario Andreau
- Instituto de Investigación, Facultad de Psicología y Psicopedagogía, Universidad del Salvador, Ciudad Autónoma de Buenos Aires, Argentina
- Department of Cognitive and Behavioral Sciences, Graduate School of Human and Environment Studies, Kyoto University, Kyoto, Japan
| | - Shintaro Funahashi
- Department of Cognitive and Behavioral Sciences, Graduate School of Human and Environment Studies, Kyoto University, Kyoto, Japan
- Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing, PR China
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45
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Smith D, Wolff A, Wolman A, Ignaszewski J, Northoff G. Temporal continuity of self: Long autocorrelation windows mediate self-specificity. Neuroimage 2022; 257:119305. [PMID: 35568347 DOI: 10.1016/j.neuroimage.2022.119305] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 04/13/2022] [Accepted: 05/10/2022] [Indexed: 11/27/2022] Open
Abstract
The self is characterized by an intrinsic temporal component consisting in continuity across time. On the neural level, this temporal continuity manifests in the brain's intrinsic neural timescales (INT) that can be measured by the autocorrelation window (ACW). Recent EEG studies reveal a relationship between resting state ACW and self-consciousness. However, it remains unclear whether ACW exhibits different degrees of task-related changes during self-specific compared to non-self-specific activities. To this end, participants in our study initially recorded an eight-minute autobiographical narrative. Following a resting-state session, participants were presented with their own narrative and the narrative of a stranger while undergoing concurrent EEG recording. Behaviorally, subjects evaluated both of the narratives and indicated their perceptions of positivity or negativity on a moment-to-moment basis by positioning a cursor relative to the center of the computer screen. Our results indicate: (a) greater spatial extension and velocity in the behavioral cursor movement during the self narrative assessment compared to the non-self narrative assessment; and (b) longer neural ACWs in response to the self- compared to the non-self narrative and rest. These findings demonstrate the importance of longer temporal windows in neural activity measured by ACWs for self-specificity. More broadly, the results highlight the relevance of temporal continuity for the self on the neural level. Such temporal continuity may, correspondingly, also manifest on the psychological level as a "common currency" between brain and self.
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Affiliation(s)
- David Smith
- Carleton University, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada; Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada.
| | - Annemarie Wolff
- Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
| | - Angelika Wolman
- Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
| | - Julia Ignaszewski
- Carleton University, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada; Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada; Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, Roger Guindon Hall, 451 Smyth Road, Ottawa, ON K1H 8M5, Canada; Mental Health Centre, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, China; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Tianmu Road 305, Hangzhou 310013, China.
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Yang S, Gao T, Wang J, Deng B, Azghadi MR, Lei T, Linares-Barranco B. Self-Adaptive Multicompartment: A Unified Self-Adaptive Multicompartmental Spiking Neuron Model for Learning With Working Memory. Front Neurosci 2022; 16:850945. [PMID: 35527819 PMCID: PMC9074872 DOI: 10.3389/fnins.2022.850945] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 03/15/2022] [Indexed: 11/13/2022] Open
Abstract
Working memory is a fundamental feature of biological brains for perception, cognition, and learning. In addition, learning with working memory, which has been show in conventional artificial intelligence systems through recurrent neural networks, is instrumental to advanced cognitive intelligence. However, it is hard to endow a simple neuron model with working memory, and to understand the biological mechanisms that have resulted in such a powerful ability at the neuronal level. This article presents a novel self-adaptive multicompartment spiking neuron model, referred to as SAM, for spike-based learning with working memory. SAM integrates four major biological principles including sparse coding, dendritic non-linearity, intrinsic self-adaptive dynamics, and spike-driven learning. We first describe SAM’s design and explore the impacts of critical parameters on its biological dynamics. We then use SAM to build spiking networks to accomplish several different tasks including supervised learning of the MNIST dataset using sequential spatiotemporal encoding, noisy spike pattern classification, sparse coding during pattern classification, spatiotemporal feature detection, meta-learning with working memory applied to a navigation task and the MNIST classification task, and working memory for spatiotemporal learning. Our experimental results highlight the energy efficiency and robustness of SAM in these wide range of challenging tasks. The effects of SAM model variations on its working memory are also explored, hoping to offer insight into the biological mechanisms underlying working memory in the brain. The SAM model is the first attempt to integrate the capabilities of spike-driven learning and working memory in a unified single neuron with multiple timescale dynamics. The competitive performance of SAM could potentially contribute to the development of efficient adaptive neuromorphic computing systems for various applications from robotics to edge computing.
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Affiliation(s)
- Shuangming Yang
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
- *Correspondence: Shuangming Yang,
| | - Tian Gao
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Jiang Wang
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Bin Deng
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | | | - Tao Lei
- School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, China
- Tao Lei,
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Ye H, Liu ZX, He YJ, Wang X. Effects of M currents on the persistent activity of pyramidal neurons in mouse primary auditory cortex. J Neurophysiol 2022; 127:1269-1278. [PMID: 35294269 DOI: 10.1152/jn.00332.2021] [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: 11/22/2022] Open
Abstract
Neuronal persistent activity (PA) is a common phenomenon observed in many types of neurons. PA can be induced in neurons in the mouse auditory nucleus by activating cholinergic receptors with carbachol (CCh), a dual muscarinic and nicotinic receptor agonist. PA is presumed to be associated with learning-related auditory plasticity at the cellular level. However, the mechanism is not clearly understood. Many studies have reported that muscarinic cholinergic receptor agonists inhibit muscarinic-sensitive potassium channels (M channels). Potassium influx through M channels produces potassium currents, called M currents, which play an essential role in regulating neural excitability and synaptic plasticity. Further study is needed to determine whether M currents affect the PA of auditory central neurons and provide additional analysis of the variations in electrophysiological properties. We used in vitro whole-cell patch-clamp recordings in isolated mouse brain slices to investigate the effects of M currents on the PA in pyramidal neurons in layer V of the primary auditory cortex (AI-L5). We found that blocking M currents with XE991 depolarized the AI-L5 pyramidal neurons, which significantly increased the input resistance. The active threshold and threshold intensity were significantly reduced, indicating that the intrinsic excitability was enhanced. Our results also showed that blocking M currents with XE991 switched the neuronal firing patterns in the AI-L5 pyramidal neurons from regular-spiking to intrinsic-bursting. Blocking M currents facilitated PA by increasing the plateau potential and enhancing intrinsic excitability. Our results suggested that blocking M currents might facilitate the PA in AI-L5 pyramidal neurons, which underlies auditory plasticity.
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Affiliation(s)
- Huan Ye
- Hubei Key Lab of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, China
| | - Zhen-Xu Liu
- Hubei Key Lab of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, China
| | - Ya-Jie He
- Hubei Key Lab of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, China
| | - Xin Wang
- Hubei Key Lab of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, China
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48
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Nguyen DL, Hutson AN, Zhang Y, Daniels SD, Peard AR, Tabuchi M. Age-Related Unstructured Spike Patterns and Molecular Localization in Drosophila Circadian Neurons. Front Physiol 2022; 13:845236. [PMID: 35356078 PMCID: PMC8959858 DOI: 10.3389/fphys.2022.845236] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 02/09/2022] [Indexed: 01/02/2023] Open
Abstract
Aging decreases sleep quality by disrupting the molecular machinery that regulates the circadian rhythm. However, we do not fully understand the mechanism that underlies this process. In Drosophila, sleep quality is regulated by precisely timed patterns of spontaneous firing activity in posterior DN1 (DN1p) circadian clock neurons. How aging affects the physiological function of DN1p neurons is unknown. In this study, we found that aging altered functional parameters related to neural excitability and disrupted patterned spike sequences in DN1p neurons during nighttime. We also characterized age-associated changes in intrinsic membrane properties related to spike frequency adaptations and synaptic properties, which may account for the unstructured spike patterns in aged DN1p neurons. Because Slowpoke binding protein (SLOB) and the Na+/K+ ATPase β subunit (NaKβ) regulate clock-dependent spiking patterns in circadian networks, we compared the subcellular organization of these factors between young and aged DN1p neurons. Young DN1p neurons showed circadian cycling of HA-tagged SLOB and myc-tagged NaKβ targeting the plasma membrane, whereas aged DN1p neurons showed significantly disrupted subcellular localization patterns of both factors. The distribution of SLOB and NaKβ signals also showed greater variability in young vs. aged DN1p neurons, suggesting aging leads to a loss of actively formed heterogeneity for these factors. These findings showed that aging disrupts precisely structured molecular patterns that regulate structured neural activity in the circadian network, leading to age-associated declines in sleep quality. Thus, it is possible to speculate that a recovery of unstructured neural activity in aging clock neurons could help to rescue age-related poor sleep quality.
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49
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Graf J, Rahmati V, Majoros M, Witte OW, Geis C, Kiebel SJ, Holthoff K, Kirmse K. Network instability dynamics drive a transient bursting period in the developing hippocampus in vivo. eLife 2022; 11:82756. [PMID: 36534089 PMCID: PMC9762703 DOI: 10.7554/elife.82756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 12/05/2022] [Indexed: 12/23/2022] Open
Abstract
Spontaneous correlated activity is a universal hallmark of immature neural circuits. However, the cellular dynamics and intrinsic mechanisms underlying network burstiness in the intact developing brain are largely unknown. Here, we use two-photon Ca2+ imaging to comprehensively map the developmental trajectories of spontaneous network activity in the hippocampal area CA1 of mice in vivo. We unexpectedly find that network burstiness peaks after the developmental emergence of effective synaptic inhibition in the second postnatal week. We demonstrate that the enhanced network burstiness reflects an increased functional coupling of individual neurons to local population activity. However, pairwise neuronal correlations are low, and network bursts (NBs) recruit CA1 pyramidal cells in a virtually random manner. Using a dynamic systems modeling approach, we reconcile these experimental findings and identify network bi-stability as a potential regime underlying network burstiness at this age. Our analyses reveal an important role of synaptic input characteristics and network instability dynamics for NB generation. Collectively, our data suggest a mechanism, whereby developing CA1 performs extensive input-discrimination learning prior to the onset of environmental exploration.
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Affiliation(s)
- Jürgen Graf
- Department of Neurology, Jena University HospitalJenaGermany
| | - Vahid Rahmati
- Department of Neurology, Jena University HospitalJenaGermany,Section Translational Neuroimmunology, Jena University HospitalJenaGermany,Department of Psychology, Technical University DresdenDresdenGermany
| | - Myrtill Majoros
- Department of Neurology, Jena University HospitalJenaGermany
| | - Otto W Witte
- Department of Neurology, Jena University HospitalJenaGermany
| | - Christian Geis
- Department of Neurology, Jena University HospitalJenaGermany,Section Translational Neuroimmunology, Jena University HospitalJenaGermany
| | - Stefan J Kiebel
- Department of Psychology, Technical University DresdenDresdenGermany
| | - Knut Holthoff
- Department of Neurology, Jena University HospitalJenaGermany
| | - Knut Kirmse
- Department of Neurology, Jena University HospitalJenaGermany,Department of Neurophysiology, Institute of Physiology, University of WürzburgWürzburgGermany
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50
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Medial Entorhinal Cortex Excitatory Neurons Are Necessary for Accurate Timing. J Neurosci 2021; 41:9932-9943. [PMID: 34670849 DOI: 10.1523/jneurosci.0750-21.2021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 09/03/2021] [Accepted: 09/28/2021] [Indexed: 11/21/2022] Open
Abstract
The hippocampal region has long been considered critical for memory of time, and recent evidence shows that network operations and single-unit activity in the hippocampus and medial entorhinal cortex (MEC) correlate with elapsed time. However, whether MEC activity is necessary for timing remains largely unknown. Here we expressed DREADDs (designer receptors exclusively activated by designer drugs) under the CaMKIIa promoter to preferentially target MEC excitatory neurons for chemogenetic silencing, while freely moving male rats reproduced a memorized time interval by waiting inside a region of interest. We found that such silencing impaired the reproduction of the memorized interval and led to an overestimation of elapsed time. Trial history analyses under this condition revealed a reduced influence of previous trials on current waiting times, suggesting an impairment in maintaining temporal memories across trials. Moreover, using GLM (logistic regression), we show that decoding behavioral performance from preceding waiting times was significantly compromised when MEC was silenced. In addition to revealing an important role of MEC excitatory neurons for timing behavior, our results raise the possibility that these neurons contribute to such behavior by holding temporal information across trials.SIGNIFICANCE STATEMENT Medial temporal lobe (MTL) structures are implicated in processing temporal information. However, little is known about the role MTL structures, such as the hippocampus and the entorhinal cortex, play in perceiving or reproducing temporal intervals. By chemogenetically silencing medial entorhinal cortex (MEC) excitatory activity during a timing task, we show that this structure is necessary for the accurate reproduction of temporal intervals. Furthermore, trial history analyses suggest that silencing MEC disrupts memory mechanisms during timing. Together, these results suggest that MEC is necessary for timing behavior, possibly by representing the target interval in memory.
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