1
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Regele-Blasco E, Palmer LM. The plasticity of pyramidal neurons in the behaving brain. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230231. [PMID: 38853566 DOI: 10.1098/rstb.2023.0231] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 04/23/2024] [Indexed: 06/11/2024] Open
Abstract
Neurons are plastic. That is, they change their activity according to different behavioural conditions. This endows pyramidal neurons with an incredible computational power for the integration and processing of synaptic inputs. Plasticity can be investigated at different levels of investigation within a single neuron, from spines to dendrites, to synaptic input. Although most of our knowledge stems from the in vitro brain slice preparation, plasticity plays a vital role during behaviour by providing a flexible substrate for the execution of appropriate actions in our ever-changing environment. Owing to advances in recording techniques, the plasticity of neurons and the neural networks in which they are embedded is now beginning to be realized in the in vivo intact brain. This review focuses on the structural and functional synaptic plasticity of pyramidal neurons, with a specific focus on the latest developments from in vivo studies. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.
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Affiliation(s)
- Elena Regele-Blasco
- The Florey Institute of Neuroscience and Mental Health, The Florey Department of Neuroscience and Mental Health, University of Melbourne , Victoria 3052, Australia
| | - Lucy M Palmer
- The Florey Institute of Neuroscience and Mental Health, The Florey Department of Neuroscience and Mental Health, University of Melbourne , Victoria 3052, Australia
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2
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Lee DG, McLachlan CA, Nogueira R, Kwon O, Carey AE, House G, Lagani GD, LaMay D, Fusi S, Chen JL. Perirhinal cortex learns a predictive map of the task environment. Nat Commun 2024; 15:5544. [PMID: 38956015 PMCID: PMC11219840 DOI: 10.1038/s41467-024-47365-7] [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: 08/09/2023] [Accepted: 03/25/2024] [Indexed: 07/04/2024] Open
Abstract
Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that can progressively be decoded earlier in the trial as training advances and that generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and systemic pharmacological perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.
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Affiliation(s)
- David G Lee
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
| | - Caroline A McLachlan
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Ramon Nogueira
- Center for Theoretical Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Osung Kwon
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Alanna E Carey
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Garrett House
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Gavin D Lagani
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Danielle LaMay
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA.
- Department of Biology, Boston University, Boston, MA, 02215, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA.
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3
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Miller JA, Constantinidis C. Timescales of learning in prefrontal cortex. Nat Rev Neurosci 2024:10.1038/s41583-024-00836-8. [PMID: 38937654 DOI: 10.1038/s41583-024-00836-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/03/2024] [Indexed: 06/29/2024]
Abstract
The lateral prefrontal cortex (PFC) in humans and other primates is critical for immediate, goal-directed behaviour and working memory, which are classically considered distinct from the cognitive and neural circuits that support long-term learning and memory. Over the past few years, a reconsideration of this textbook perspective has emerged, in that different timescales of memory-guided behaviour are in constant interaction during the pursuit of immediate goals. Here, we will first detail how neural activity related to the shortest timescales of goal-directed behaviour (which requires maintenance of current states and goals in working memory) is sculpted by long-term knowledge and learning - that is, how the past informs present behaviour. Then, we will outline how learning across different timescales (from seconds to years) drives plasticity in the primate lateral PFC, from single neuron firing rates to mesoscale neuroimaging activity patterns. Finally, we will review how, over days and months of learning, dense local and long-range connectivity patterns in PFC facilitate longer-lasting changes in population activity by changing synaptic weights and recruiting additional neural resources to inform future behaviour. Our Review sheds light on how the machinery of plasticity in PFC circuits facilitates the integration of learned experiences across time to best guide adaptive behaviour.
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Affiliation(s)
- Jacob A Miller
- Wu Tsai Institute, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Christos Constantinidis
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.
- Neuroscience Program, Vanderbilt University, Nashville, TN, USA.
- Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
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4
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Hartung J, Schroeder A, Péréz Vázquez RA, Poorthuis RB, Letzkus JJ. Layer 1 NDNF interneurons are specialized top-down master regulators of cortical circuits. Cell Rep 2024; 43:114212. [PMID: 38743567 DOI: 10.1016/j.celrep.2024.114212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/10/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024] Open
Abstract
Diverse types of inhibitory interneurons (INs) impart computational power and flexibility to neocortical circuits. Whereas markers for different IN types in cortical layers 2-6 (L2-L6) have been instrumental for generating a wealth of functional insights, only the recent identification of a selective marker (neuron-derived neurotrophic factor [NDNF]) has opened comparable opportunities for INs in L1 (L1INs). However, at present we know very little about the connectivity of NDNF L1INs with other IN types, their input-output conversion, and the existence of potential NDNF L1IN subtypes. Here, we report pervasive inhibition of L2/3 INs (including parvalbumin INs and vasoactive intestinal peptide INs) by NDNF L1INs. Intersectional genetics revealed similar physiology and connectivity in the NDNF L1IN subpopulation co-expressing neuropeptide Y. Finally, NDNF L1INs prominently and selectively engage in persistent firing, a physiological hallmark disconnecting their output from the current input. Collectively, our work therefore identifies NDNF L1INs as specialized master regulators of superficial neocortex according to their pervasive top-down afferents.
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Affiliation(s)
- Jan Hartung
- Institute for Physiology, Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany; BrainLinks-BrainTools, IMBIT (Institute for Machine-Brain Interfacing Technology), University of Freiburg, Georges-Köhler-Allee 201, 79110 Freiburg, Germany.
| | - Anna Schroeder
- Institute for Physiology, Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany
| | | | - Rogier B Poorthuis
- Department of Translational Neuroscience, UMC Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - Johannes J Letzkus
- Institute for Physiology, Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany; BrainLinks-BrainTools, IMBIT (Institute for Machine-Brain Interfacing Technology), University of Freiburg, Georges-Köhler-Allee 201, 79110 Freiburg, Germany; Center for Basics in NeuroModulation (NeuroModul Basics), University of Freiburg, 79106 Freiburg, Germany.
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5
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Storm JF, Klink PC, Aru J, Senn W, Goebel R, Pigorini A, Avanzini P, Vanduffel W, Roelfsema PR, Massimini M, Larkum ME, Pennartz CMA. An integrative, multiscale view on neural theories of consciousness. Neuron 2024; 112:1531-1552. [PMID: 38447578 DOI: 10.1016/j.neuron.2024.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 12/20/2023] [Accepted: 02/05/2024] [Indexed: 03/08/2024]
Abstract
How is conscious experience related to material brain processes? A variety of theories aiming to answer this age-old question have emerged from the recent surge in consciousness research, and some are now hotly debated. Although most researchers have so far focused on the development and validation of their preferred theory in relative isolation, this article, written by a group of scientists representing different theories, takes an alternative approach. Noting that various theories often try to explain different aspects or mechanistic levels of consciousness, we argue that the theories do not necessarily contradict each other. Instead, several of them may converge on fundamental neuronal mechanisms and be partly compatible and complementary, so that multiple theories can simultaneously contribute to our understanding. Here, we consider unifying, integration-oriented approaches that have so far been largely neglected, seeking to combine valuable elements from various theories.
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Affiliation(s)
- Johan F Storm
- The Brain Signaling Group, Division of Physiology, IMB, Faculty of Medicine, University of Oslo, Domus Medica, Sognsvannsveien 9, Blindern, 0317 Oslo, Norway.
| | - P Christiaan Klink
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Experimental Psychology, Helmholtz Institute, Utrecht University, 3584 CS Utrecht, the Netherlands; Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la Vision, Paris 75012, France
| | - Jaan Aru
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Walter Senn
- Department of Physiology, University of Bern, Bern, Switzerland
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands
| | - Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan 20122, Italy
| | - Pietro Avanzini
- Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, 43125 Parma, Italy
| | - Wim Vanduffel
- Department of Neurosciences, Laboratory of Neuro and Psychophysiology, KU Leuven Medical School, 3000 Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Harvard Medical School, Boston, MA 02144, USA
| | - Pieter R Roelfsema
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la Vision, Paris 75012, France; Department of Integrative Neurophysiology, VU University, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands; Department of Neurosurgery, Academisch Medisch Centrum, Postbus 22660, 1100 DD Amsterdam, the Netherlands
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan 20157, Italy; Istituto di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan 20122, Italy; Azrieli Program in Brain, Mind and Consciousness, Canadian Institute for Advanced Research (CIFAR), Toronto, ON M5G 1M1, Canada
| | - Matthew E Larkum
- Institute of Biology, Humboldt University Berlin, Berlin, Germany; Neurocure Center for Excellence, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Sciencepark 904, Amsterdam 1098 XH, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
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6
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Zolnik TA, Bronec A, Ross A, Staab M, Sachdev RNS, Molnár Z, Eickholt BJ, Larkum ME. Layer 6b controls brain state via apical dendrites and the higher-order thalamocortical system. Neuron 2024; 112:805-820.e4. [PMID: 38101395 DOI: 10.1016/j.neuron.2023.11.021] [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: 03/10/2023] [Revised: 09/11/2023] [Accepted: 11/18/2023] [Indexed: 12/17/2023]
Abstract
The deepest layer of the cortex (layer 6b [L6b]) contains relatively few neurons, but it is the only cortical layer responsive to the potent wake-promoting neuropeptide orexin/hypocretin. Can these few neurons significantly influence brain state? Here, we show that L6b-photoactivation causes a surprisingly robust enhancement of attention-associated high-gamma oscillations and population spiking while abolishing slow waves in sleep-deprived mice. To explain this powerful impact on brain state, we investigated L6b's synaptic output using optogenetics, electrophysiology, and monoCaTChR ex vivo. We found powerful output in the higher-order thalamus and apical dendrites of L5 pyramidal neurons, via L1a and L5a, as well as in superior colliculus and L6 interneurons. L6b subpopulations with distinct morphologies and short- and long-term plasticities project to these diverse targets. The L1a-targeting subpopulation triggered powerful NMDA-receptor-dependent spikes that elicited burst firing in L5. We conclude that orexin/hypocretin-activated cortical neurons form a multifaceted, fine-tuned circuit for the sustained control of the higher-order thalamocortical system.
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Affiliation(s)
- Timothy Adam Zolnik
- Department of Biochemistry, Charité Universitätsmedizin Berlin, Berlin 10117, Germany; Department of Biology, Humboldt Universität zu Berlin, Berlin 10117, Germany.
| | - Anna Bronec
- Department of Biology, Humboldt Universität zu Berlin, Berlin 10117, Germany
| | - Annemarie Ross
- Department of Biology, Humboldt Universität zu Berlin, Berlin 10117, Germany
| | - Marcel Staab
- Department of Biology, Humboldt Universität zu Berlin, Berlin 10117, Germany
| | - Robert N S Sachdev
- Department of Biology, Humboldt Universität zu Berlin, Berlin 10117, Germany
| | - Zoltán Molnár
- Department of Biochemistry, Charité Universitätsmedizin Berlin, Berlin 10117, Germany; Department of Physiology, Anatomy, and Genetics, University of Oxford, Parks Road, Sherrington Building, Oxford OX1 3PT, UK
| | | | - Matthew Evan Larkum
- Department of Biology, Humboldt Universität zu Berlin, Berlin 10117, Germany.
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7
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Rvachev MM. An operating principle of the cerebral cortex, and a cellular mechanism for attentional trial-and-error pattern learning and useful classification extraction. Front Neural Circuits 2024; 18:1280604. [PMID: 38505865 PMCID: PMC10950307 DOI: 10.3389/fncir.2024.1280604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 02/13/2024] [Indexed: 03/21/2024] Open
Abstract
A feature of the brains of intelligent animals is the ability to learn to respond to an ensemble of active neuronal inputs with a behaviorally appropriate ensemble of active neuronal outputs. Previously, a hypothesis was proposed on how this mechanism is implemented at the cellular level within the neocortical pyramidal neuron: the apical tuft or perisomatic inputs initiate "guess" neuron firings, while the basal dendrites identify input patterns based on excited synaptic clusters, with the cluster excitation strength adjusted based on reward feedback. This simple mechanism allows neurons to learn to classify their inputs in a surprisingly intelligent manner. Here, we revise and extend this hypothesis. We modify synaptic plasticity rules to align with behavioral time scale synaptic plasticity (BTSP) observed in hippocampal area CA1, making the framework more biophysically and behaviorally plausible. The neurons for the guess firings are selected in a voluntary manner via feedback connections to apical tufts in the neocortical layer 1, leading to dendritic Ca2+ spikes with burst firing, which are postulated to be neural correlates of attentional, aware processing. Once learned, the neuronal input classification is executed without voluntary or conscious control, enabling hierarchical incremental learning of classifications that is effective in our inherently classifiable world. In addition to voluntary, we propose that pyramidal neuron burst firing can be involuntary, also initiated via apical tuft inputs, drawing attention toward important cues such as novelty and noxious stimuli. We classify the excitations of neocortical pyramidal neurons into four categories based on their excitation pathway: attentional versus automatic and voluntary/acquired versus involuntary. Additionally, we hypothesize that dendrites within pyramidal neuron minicolumn bundles are coupled via depolarization cross-induction, enabling minicolumn functions such as the creation of powerful hierarchical "hyperneurons" and the internal representation of the external world. We suggest building blocks to extend the microcircuit theory to network-level processing, which, interestingly, yields variants resembling the artificial neural networks currently in use. On a more speculative note, we conjecture that principles of intelligence in universes governed by certain types of physical laws might resemble ours.
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8
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Ford AN, Czarny JE, Rogalla MM, Quass GL, Apostolides PF. Auditory Corticofugal Neurons Transmit Auditory and Non-auditory Information During Behavior. J Neurosci 2024; 44:e1190232023. [PMID: 38123993 PMCID: PMC10869159 DOI: 10.1523/jneurosci.1190-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 11/08/2023] [Accepted: 11/29/2023] [Indexed: 12/23/2023] Open
Abstract
Layer 5 pyramidal neurons of sensory cortices project "corticofugal" axons to myriad sub-cortical targets, thereby broadcasting high-level signals important for perception and learning. Recent studies suggest dendritic Ca2+ spikes as key biophysical mechanisms supporting corticofugal neuron function: these long-lasting events drive burst firing, thereby initiating uniquely powerful signals to modulate sub-cortical representations and trigger learning-related plasticity. However, the behavioral relevance of corticofugal dendritic spikes is poorly understood. We shed light on this issue using 2-photon Ca2+ imaging of auditory corticofugal dendrites as mice of either sex engage in a GO/NO-GO sound-discrimination task. Unexpectedly, only a minority of dendritic spikes were triggered by behaviorally relevant sounds under our conditions. Task related dendritic activity instead mostly followed sound cue termination and co-occurred with mice's instrumental licking during the answer period of behavioral trials, irrespective of reward consumption. Temporally selective, optogenetic silencing of corticofugal neurons during the trial answer period impaired auditory discrimination learning. Thus, auditory corticofugal systems' contribution to learning and plasticity may be partially nonsensory in nature.
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Affiliation(s)
- Alexander N Ford
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research Institute, Ann Arbor, Michigan 48109
| | - Jordyn E Czarny
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research Institute, Ann Arbor, Michigan 48109
| | - Meike M Rogalla
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research Institute, Ann Arbor, Michigan 48109
| | - Gunnar L Quass
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research Institute, Ann Arbor, Michigan 48109
| | - Pierre F Apostolides
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research Institute, Ann Arbor, Michigan 48109
- Department of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, Michigan 48109
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9
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Fiorilli J, Marchesi P, Ruikes T, Huis in ‘t Veld G, Buckton R, Quintero MD, Reiten I, Bjaalie JG, Pennartz CMA. Neural correlates of object identity and reward outcome in the sensory cortical-hippocampal hierarchy: coding of motivational information in perirhinal cortex. Cereb Cortex 2024; 34:bhae002. [PMID: 38314581 PMCID: PMC10847907 DOI: 10.1093/cercor/bhae002] [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: 05/24/2023] [Revised: 12/21/2023] [Accepted: 12/24/2023] [Indexed: 02/06/2024] Open
Abstract
Neural circuits support behavioral adaptations by integrating sensory and motor information with reward and error-driven learning signals, but it remains poorly understood how these signals are distributed across different levels of the corticohippocampal hierarchy. We trained rats on a multisensory object-recognition task and compared visual and tactile responses of simultaneously recorded neuronal ensembles in somatosensory cortex, secondary visual cortex, perirhinal cortex, and hippocampus. The sensory regions primarily represented unisensory information, whereas hippocampus was modulated by both vision and touch. Surprisingly, the sensory cortices and the hippocampus coded object-specific information, whereas the perirhinal cortex did not. Instead, perirhinal cortical neurons signaled trial outcome upon reward-based feedback. A majority of outcome-related perirhinal cells responded to a negative outcome (reward omission), whereas a minority of other cells coded positive outcome (reward delivery). Our results highlight a distributed neural coding of multisensory variables in the cortico-hippocampal hierarchy. Notably, the perirhinal cortex emerges as a crucial region for conveying motivational outcomes, whereas distinct functions related to object identity are observed in the sensory cortices and hippocampus.
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Affiliation(s)
- Julien Fiorilli
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Pietro Marchesi
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Thijs Ruikes
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Gerjan Huis in ‘t Veld
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Rhys Buckton
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Mariana D Quintero
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Ingrid Reiten
- Institute of Basic Medical Sciences, University of Oslo, NO-0316 Oslo, Norway
| | - Jan G Bjaalie
- Institute of Basic Medical Sciences, University of Oslo, NO-0316 Oslo, Norway
| | - Cyriel M A Pennartz
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
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10
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Huang S, Wu SJ, Sansone G, Ibrahim LA, Fishell G. Layer 1 neocortex: Gating and integrating multidimensional signals. Neuron 2024; 112:184-200. [PMID: 37913772 PMCID: PMC11180419 DOI: 10.1016/j.neuron.2023.09.041] [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: 07/24/2023] [Revised: 09/23/2023] [Accepted: 09/28/2023] [Indexed: 11/03/2023]
Abstract
Layer 1 (L1) of the neocortex acts as a nexus for the collection and processing of widespread information. By integrating ascending inputs with extensive top-down activity, this layer likely provides critical information regulating how the perception of sensory inputs is reconciled with expectation. This is accomplished by sorting, directing, and integrating the complex network of excitatory inputs that converge onto L1. These signals are combined with neuromodulatory afferents and gated by the wealth of inhibitory interneurons that either are embedded within L1 or send axons from other cortical layers. Together, these interactions dynamically calibrate information flow throughout the neocortex. This review will primarily focus on L1 within the primary sensory cortex and will use these insights to understand L1 in other cortical areas.
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Affiliation(s)
- Shuhan Huang
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Program in Neuroscience, Harvard University, Cambridge, MA 02138, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sherry Jingjing Wu
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Giulia Sansone
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Leena Ali Ibrahim
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.
| | - Gord Fishell
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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11
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Guzulaitis R, Palmer LM. A thalamocortical pathway controlling impulsive behavior. Trends Neurosci 2023; 46:1018-1024. [PMID: 37778915 DOI: 10.1016/j.tins.2023.09.001] [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: 06/08/2023] [Revised: 08/14/2023] [Accepted: 09/08/2023] [Indexed: 10/03/2023]
Abstract
Planning and anticipating motor actions enables movements to be quickly and accurately executed. However, if anticipation is not properly controlled, it can lead to premature impulsive actions. Impulsive behavior is defined as actions that are poorly conceived and are often risky and inappropriate. Historically, impulsive behavior was thought to be primarily controlled by the frontal cortex and basal ganglia. More recently, two additional brain regions, the ventromedial (VM) thalamus and the anterior lateral motor cortex (ALM), have been shown to have an important role in mice. Here, we explore this newly discovered role of the thalamocortical pathway and suggest cellular mechanisms that may be involved in driving the cortical activity that contributes to impulsive behavior.
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Affiliation(s)
| | - Lucy M Palmer
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3010, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC 3010, Australia.
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12
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Friedenberger Z, Harkin E, Tóth K, Naud R. Silences, spikes and bursts: Three-part knot of the neural code. J Physiol 2023; 601:5165-5193. [PMID: 37889516 DOI: 10.1113/jp281510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 09/28/2023] [Indexed: 10/28/2023] Open
Abstract
When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emitted at a particularly high frequency with a metonym - bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high-frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is beneficial.
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Affiliation(s)
- Zachary Friedenberger
- Brain and Mind Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Centre for Neural Dynamics and Artifical Intelligence, Department of Physics, University of Ottawa, Ottawa, Ontario, Ottawa
| | - Emerson Harkin
- Brain and Mind Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Katalin Tóth
- Brain and Mind Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Richard Naud
- Brain and Mind Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Centre for Neural Dynamics and Artifical Intelligence, Department of Physics, University of Ottawa, Ottawa, Ontario, Ottawa
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13
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Ledderose JMT, Zolnik TA, Toumazou M, Trimbuch T, Rosenmund C, Eickholt BJ, Jaeger D, Larkum ME, Sachdev RNS. Layer 1 of somatosensory cortex: an important site for input to a tiny cortical compartment. Cereb Cortex 2023; 33:11354-11372. [PMID: 37851709 PMCID: PMC10690867 DOI: 10.1093/cercor/bhad371] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 09/17/2023] [Indexed: 10/20/2023] Open
Abstract
Neocortical layer 1 has been proposed to be at the center for top-down and bottom-up integration. It is a locus for interactions between long-range inputs, layer 1 interneurons, and apical tuft dendrites of pyramidal neurons. While input to layer 1 has been studied intensively, the level and effect of input to this layer has still not been completely characterized. Here we examined the input to layer 1 of mouse somatosensory cortex with retrograde tracing and optogenetics. Our assays reveal that local input to layer 1 is predominantly from layers 2/3 and 5 pyramidal neurons and interneurons, and that subtypes of local layers 5 and 6b neurons project to layer 1 with different probabilities. Long-range input from sensory-motor cortices to layer 1 of somatosensory cortex arose predominantly from layers 2/3 neurons. Our optogenetic experiments showed that intra-telencephalic layer 5 pyramidal neurons drive layer 1 interneurons but have no effect locally on layer 5 apical tuft dendrites. Dual retrograde tracing revealed that a fraction of local and long-range neurons was both presynaptic to layer 5 neurons and projected to layer 1. Our work highlights the prominent role of local inputs to layer 1 and shows the potential for complex interactions between long-range and local inputs, which are both in position to modify the output of somatosensory cortex.
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Affiliation(s)
- Julia M T Ledderose
- Institute of Biology, Humboldt Universität zu Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
- Institute of Molecular Biology and Biochemistry, Charité—Universitätsmedizin Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | - Timothy A Zolnik
- Institute of Biology, Humboldt Universität zu Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
- Institute of Molecular Biology and Biochemistry, Charité—Universitätsmedizin Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | - Maria Toumazou
- Institute of Biology, Humboldt Universität zu Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | - Thorsten Trimbuch
- Institute of Neurophysiology, Charité—Universitätsmedizin Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | - Christian Rosenmund
- Institute of Neurophysiology, Charité—Universitätsmedizin Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
- Neurocure Centre for Excellence Charité—Universitätsmedizin Berlin Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | | | - Dieter Jaeger
- Department of Biology, Emory University, Atlanta, GA 30322, USA
| | - Matthew E Larkum
- Institute of Biology, Humboldt Universität zu Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
- Neurocure Centre for Excellence Charité—Universitätsmedizin Berlin Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
| | - Robert N S Sachdev
- Institute of Biology, Humboldt Universität zu Berlin, Charitéplatz 1, Virchowweg 6, 10117 Berlin, Germany
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14
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Munn BR, Müller EJ, Medel V, Naismith SL, Lizier JT, Sanders RD, Shine JM. Neuronal connected burst cascades bridge macroscale adaptive signatures across arousal states. Nat Commun 2023; 14:6846. [PMID: 37891167 PMCID: PMC10611774 DOI: 10.1038/s41467-023-42465-2] [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: 11/29/2022] [Accepted: 10/11/2023] [Indexed: 10/29/2023] Open
Abstract
The human brain displays a rich repertoire of states that emerge from the microscopic interactions of cortical and subcortical neurons. Difficulties inherent within large-scale simultaneous neuronal recording limit our ability to link biophysical processes at the microscale to emergent macroscopic brain states. Here we introduce a microscale biophysical network model of layer-5 pyramidal neurons that display graded coarse-sampled dynamics matching those observed in macroscale electrophysiological recordings from macaques and humans. We invert our model to identify the neuronal spike and burst dynamics that differentiate unconscious, dreaming, and awake arousal states and provide insights into their functional signatures. We further show that neuromodulatory arousal can mediate different modes of neuronal dynamics around a low-dimensional energy landscape, which in turn changes the response of the model to external stimuli. Our results highlight the promise of multiscale modelling to bridge theories of consciousness across spatiotemporal scales.
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Affiliation(s)
- Brandon R Munn
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia.
- Complex Systems, School of Physics, University of Sydney, Sydney, NSW, Australia.
- Centre for Complex Systems, The University of Sydney, Sydney, NSW, Australia.
| | - Eli J Müller
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
- Complex Systems, School of Physics, University of Sydney, Sydney, NSW, Australia
- Centre for Complex Systems, The University of Sydney, Sydney, NSW, Australia
| | - Vicente Medel
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
| | - Sharon L Naismith
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
- School of Psychology, Faculty of Science & Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia
| | - Joseph T Lizier
- Centre for Complex Systems, The University of Sydney, Sydney, NSW, Australia
- School of Computer Science, The University of Sydney, Sydney, NSW, Australia
| | - Robert D Sanders
- Department of Anaesthetics & Institute of Academic Surgery, Royal Prince Alfred Hospital, Camperdown, Australia
- Central Clinical School & NHMRC Clinical Trials Centre, The University of Sydney, Sydney, NSW, Australia
| | - James M Shine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
- Complex Systems, School of Physics, University of Sydney, Sydney, NSW, Australia
- Centre for Complex Systems, The University of Sydney, Sydney, NSW, Australia
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15
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Stachniak TJ, Argunsah AÖ, Yang JW, Cai L, Karayannis T. Presynaptic Kainate Receptors onto Somatostatin Interneurons Are Recruited by Activity throughout Development and Contribute to Cortical Sensory Adaptation. J Neurosci 2023; 43:7101-7118. [PMID: 37709538 PMCID: PMC10601374 DOI: 10.1523/jneurosci.1461-22.2023] [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: 07/30/2022] [Revised: 08/24/2023] [Accepted: 08/30/2023] [Indexed: 09/16/2023] Open
Abstract
Somatostatin (SST) interneurons produce delayed inhibition because of the short-term facilitation of their excitatory inputs created by the expression of metabotropic glutamate receptor 7 (mGluR7) and presynaptic GluK2-containing kainate receptors (GluK2-KARs). Using mice of both sexes, we find that as synaptic facilitation at layer (L)2/3 SST cell inputs increases during the first few postnatal weeks, so does GluK2-KAR expression. Removal of sensory input by whisker trimming does not affect mGluR7 but prevents the emergence of presynaptic GluK2-KARs, which can be restored by allowing whisker regrowth or by acute calmodulin activation. Conversely, late trimming or acute inhibition of Ca2+/calmodulin-dependent protein kinase II is sufficient to reduce GluK2-KAR activity. This developmental and activity-dependent regulation also produces a specific reduction of L4 GluK2-KARs that advances in parallel with the maturation of sensory processing in L2/3. Finally, we find that removal of both GluK2-KARs and mGluR7 from the synapse eliminates short-term facilitation and reduces sensory adaptation to repetitive stimuli, first in L4 of somatosensory cortex, then later in development in L2/3. The dynamic regulation of presynaptic GluK2-KARs potentially allows for flexible scaling of late inhibition and sensory adaptation.SIGNIFICANCE STATEMENT Excitatory synapses onto somatostatin (SST) interneurons express presynaptic, calcium-permeable kainate receptors containing the GluK2 subunit (GluK2-KARs), activated by high-frequency activity. In this study we find that their presence on L2/3 SST synapses in the barrel cortex is not based on a hardwired genetic program but instead is regulated by sensory activity, in contrast to that of mGluR7. Thus, in addition to standard synaptic potentiation and depression mechanisms, excitatory synapses onto SST neurons undergo an activity-dependent presynaptic modulation that uses GluK2-KARs. Further, we present evidence that loss of the frequency-dependent synaptic components (both GluK2-KARs and mGluR7 via Elfn1 deletion) contributes to a decrease in the sensory adaptation commonly seen on repetitive stimulus presentation.
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Affiliation(s)
- Tevye J Stachniak
- Laboratory of Neural Circuit Assembly, Brain Research Institute, Neuroscience Center Zurich, University of Zurich, CH-8057 Zurich, Switzerland
| | - Ali Ö Argunsah
- Laboratory of Neural Circuit Assembly, Brain Research Institute, Neuroscience Center Zurich, University of Zurich, CH-8057 Zurich, Switzerland
| | - Jenq-Wei Yang
- Laboratory of Neural Circuit Assembly, Brain Research Institute, Neuroscience Center Zurich, University of Zurich, CH-8057 Zurich, Switzerland
| | - Linbi Cai
- Laboratory of Neural Circuit Assembly, Brain Research Institute, Neuroscience Center Zurich, University of Zurich, CH-8057 Zurich, Switzerland
| | - Theofanis Karayannis
- Laboratory of Neural Circuit Assembly, Brain Research Institute, Neuroscience Center Zurich, University of Zurich, CH-8057 Zurich, Switzerland
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16
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Zhu JJ. Architectural organization of ∼1,500-neuron modular minicolumnar disinhibitory circuits in healthy and Alzheimer's cortices. Cell Rep 2023; 42:112904. [PMID: 37531251 DOI: 10.1016/j.celrep.2023.112904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 06/21/2023] [Accepted: 07/13/2023] [Indexed: 08/04/2023] Open
Abstract
Acquisition of neuronal circuit architectures, central to understanding brain function and dysfunction, remains prohibitively challenging. Here I report the development of a simultaneous and sequential octuple-sexdecuple whole-cell patch-clamp recording system that enables architectural reconstruction of complex cortical circuits. The method unveils the canonical layer 1 single bouquet cell (SBC)-led disinhibitory neuronal circuits across the mouse somatosensory, motor, prefrontal, and medial entorhinal cortices. The ∼1,500-neuron modular circuits feature the translaminar, unidirectional, minicolumnar, and independent disinhibition and optimize cortical complexity, subtlety, plasticity, variation, and redundancy. Moreover, architectural reconstruction uncovers age-dependent deficits at SBC-disinhibited synapses in the senescence-accelerated mouse prone 8, an animal model of Alzheimer's disease. The deficits exhibit the characteristic Alzheimer's-like cortical spread and correlation with cognitive impairments. These findings decrypt operations of the elementary processing units in healthy and Alzheimer's mouse cortices and validate the efficacy of octuple-sexdecuple patch-clamp recordings for architectural reconstruction of complex neuronal circuits.
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Affiliation(s)
- J Julius Zhu
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, 7491 Trondheim, Norway; Department of Neurophysiology, Donders Institute for Brain, Cognition and Behavior, Radboud University, 6500 GL Nijmegen, the Netherlands; Departments of Pharmacology and Neuroscience, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.
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17
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Wybo WAM, Tsai MC, Tran VAK, Illing B, Jordan J, Morrison A, Senn W. NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways. Proc Natl Acad Sci U S A 2023; 120:e2300558120. [PMID: 37523562 PMCID: PMC10410730 DOI: 10.1073/pnas.2300558120] [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: 01/13/2023] [Accepted: 06/14/2023] [Indexed: 08/02/2023] Open
Abstract
While sensory representations in the brain depend on context, it remains unclear how such modulations are implemented at the biophysical level, and how processing layers further in the hierarchy can extract useful features for each possible contextual state. Here, we demonstrate that dendritic N-Methyl-D-Aspartate spikes can, within physiological constraints, implement contextual modulation of feedforward processing. Such neuron-specific modulations exploit prior knowledge, encoded in stable feedforward weights, to achieve transfer learning across contexts. In a network of biophysically realistic neuron models with context-independent feedforward weights, we show that modulatory inputs to dendritic branches can solve linearly nonseparable learning problems with a Hebbian, error-modulated learning rule. We also demonstrate that local prediction of whether representations originate either from different inputs, or from different contextual modulations of the same input, results in representation learning of hierarchical feedforward weights across processing layers that accommodate a multitude of contexts.
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Affiliation(s)
- Willem A. M. Wybo
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure–Function Relationships (INM-10), Jülich Research Center, DE-52428Jülich, Germany
| | - Matthias C. Tsai
- Department of Physiology, University of Bern, CH-3012Bern, Switzerland
| | - Viet Anh Khoa Tran
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure–Function Relationships (INM-10), Jülich Research Center, DE-52428Jülich, Germany
- Department of Computer Science - 3, Faculty 1, RWTH Aachen University, DE-52074Aachen, Germany
| | - Bernd Illing
- Laboratory of Computational Neuroscience, École Polytechnique Fédérale de Lausanne, CH-1015Lausanne, Switzerland
| | - Jakob Jordan
- Department of Physiology, University of Bern, CH-3012Bern, Switzerland
| | - Abigail Morrison
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure–Function Relationships (INM-10), Jülich Research Center, DE-52428Jülich, Germany
- Department of Computer Science - 3, Faculty 1, RWTH Aachen University, DE-52074Aachen, Germany
| | - Walter Senn
- Department of Physiology, University of Bern, CH-3012Bern, Switzerland
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18
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Fernández-Moya SM, Ganesh AJ, Plass M. Neural cell diversity in the light of single-cell transcriptomics. Transcription 2023; 14:158-176. [PMID: 38229529 PMCID: PMC10807474 DOI: 10.1080/21541264.2023.2295044] [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: 06/27/2023] [Accepted: 11/10/2023] [Indexed: 01/18/2024] Open
Abstract
The development of highly parallel and affordable high-throughput single-cell transcriptomics technologies has revolutionized our understanding of brain complexity. These methods have been used to build cellular maps of the brain, its different regions, and catalog the diversity of cells in each of them during development, aging and even in disease. Now we know that cellular diversity is way beyond what was previously thought. Single-cell transcriptomics analyses have revealed that cell types previously considered homogeneous based on imaging techniques differ depending on several factors including sex, age and location within the brain. The expression profiles of these cells have also been exploited to understand which are the regulatory programs behind cellular diversity and decipher the transcriptional pathways driving them. In this review, we summarize how single-cell transcriptomics have changed our view on the cellular diversity in the human brain, and how it could impact the way we study neurodegenerative diseases. Moreover, we describe the new computational approaches that can be used to study cellular differentiation and gain insight into the functions of individual cell populations under different conditions and their alterations in disease.
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Affiliation(s)
- Sandra María Fernández-Moya
- Gene Regulation of Cell Identity, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), Barcelona, L’Hospitalet del Llobregat, Spain
- Program for Advancing Clinical Translation of Regenerative Medicine of Catalonia, P- CMR[C], Barcelona, L’Hospitalet del Llobregat, Spain
| | - Akshay Jaya Ganesh
- Gene Regulation of Cell Identity, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), Barcelona, L’Hospitalet del Llobregat, Spain
- Program for Advancing Clinical Translation of Regenerative Medicine of Catalonia, P- CMR[C], Barcelona, L’Hospitalet del Llobregat, Spain
| | - Mireya Plass
- Gene Regulation of Cell Identity, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), Barcelona, L’Hospitalet del Llobregat, Spain
- Program for Advancing Clinical Translation of Regenerative Medicine of Catalonia, P- CMR[C], Barcelona, L’Hospitalet del Llobregat, Spain
- Center for Networked Biomedical Research on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
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19
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Zhao Z, Ji H, Zhang C, Pei J, Zhang X, Yuan Y. Modulation effects of low-intensity transcranial ultrasound stimulation on the neuronal firing activity and synaptic plasticity of mice. Neuroimage 2023; 270:119952. [PMID: 36805093 DOI: 10.1016/j.neuroimage.2023.119952] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 02/14/2023] [Accepted: 02/16/2023] [Indexed: 02/19/2023] Open
Abstract
Low-intensity transcranial ultrasound stimulation (TUS) has been effective in modulating several neurological and psychiatric disorders. However, how TUS modulates neuronal firing activity and synaptic plasticity remains unclear. Thus, we behaviorally tested the whisker-dependent novel object discrimination ability in mice after ultrasound stimulation and examined the cortical neuronal firing activity and synaptic plasticity in awake mice after ultrasound stimulation by two-photon fluorescence imaging. The current study presented the following results: (1) TUS could significantly improve the whisker-dependent new object discrimination ability of mice, suggesting that their learning and memory abilities were significantly enhanced; (2) TUS significantly enhanced neuronal firing activity; and (3) TUS increased the growth rate of dendritic spines in the barrel cortex, but did not promote the extinction of dendritic spines, resulting in enhanced synaptic plasticity. The above results indicate that TUS can improve the learning and memory ability of mice and enhance the neuronal firing activity and synaptic plasticity that are closely related to it. This study provides a research basis for the application of ultrasound stimulation in the treatment of learning- and memory-related diseases.
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Affiliation(s)
- Zhe Zhao
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China; Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Yanshan University, Qinhuangdao 066004, China
| | - Hui Ji
- Department of Neurology, Hebei Key Laboratory of Vascular Homeostasis and Hebei Collaborative Innovation Center for Cardio-cerebrovascular Disease, the Second Hospital of Hebei Medical University, Shijiazhuang 050000, China
| | - Cong Zhang
- Department of Neurology, Hebei Key Laboratory of Vascular Homeostasis and Hebei Collaborative Innovation Center for Cardio-cerebrovascular Disease, the Second Hospital of Hebei Medical University, Shijiazhuang 050000, China
| | - Jiamin Pei
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China; Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Yanshan University, Qinhuangdao 066004, China
| | - Xiangjian Zhang
- Department of Neurology, Hebei Key Laboratory of Vascular Homeostasis and Hebei Collaborative Innovation Center for Cardio-cerebrovascular Disease, the Second Hospital of Hebei Medical University, Shijiazhuang 050000, China.
| | - Yi Yuan
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China; Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Yanshan University, Qinhuangdao 066004, China.
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20
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Lee DG, McLachlan CA, Nogueira R, Kwon O, Carey AE, House G, Lagani GD, LaMay D, Fusi S, Chen JL. PERIRHINAL CORTEX LEARNS A PREDICTIVE MAP (INTERNAL MODEL) OF THE TASK ENVIRONMENT. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.17.532214. [PMID: 36993645 PMCID: PMC10055158 DOI: 10.1101/2023.03.17.532214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chemogenetic inactivation demonstrated that Prh is involved in task learning. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that expand in a retrospective manner and generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.
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Affiliation(s)
- David G Lee
- Department of Biomedical Engineering, Boston University, Boston MA 02215, USA
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
| | - Caroline A McLachlan
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Ramon Nogueira
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
- Department of Neuroscience, Columbia University, New York NY 10027, USA
| | - Osung Kwon
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Alanna E Carey
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Garrett House
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Gavin D Lagani
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Danielle LaMay
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
- Department of Neuroscience, Columbia University, New York NY 10027, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston MA 02215, USA
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
- Center for Systems Neuroscience, Boston University, Boston MA 02215, USA
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21
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Cao Y, Zhang Y, Jia Z, Jia H, Sun Y, Yuan H, Bian Y, Xu B, Fu J, Qin F. Theaflavin-3,3'-digallate ameliorates learning and memory impairments in mice with premature brain aging induced by D-galactose. Physiol Behav 2023; 261:114077. [PMID: 36638877 DOI: 10.1016/j.physbeh.2023.114077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 01/08/2023] [Accepted: 01/09/2023] [Indexed: 01/12/2023]
Abstract
Age-related neurodegenerative diseases accompanied by learning and memory deficits are growing in prevalence due to population aging. Cellular oxidative stress is a common pathomechanism in multiple age-related disorders, and various antioxidants have demonstrated therapeutic efficacy in patients or animal models. Many plants and plant extracts possess potent antioxidant activity, but the compounds responsible are frequently unknown. Identification and evaluation of these phytochemicals is necessary for optimal targeted therapy. A recent study identified theaflavin-3,3'-digallate (TFDG) as the most potent among a large series of phytochemical antioxidants. Here we examined if TFDG can mitigate learning and memory impairments in the D-galactose model of age-related neurodegeneration. Experimental mice were injected subcutaneously with D-galactose (120 mg/kg) for 56 days. In treatment groups, different doses of TFDG were administered daily by gavage starting on day 29 of D-galactose injection. Model mice exhibited poor learning and memory in the novel object recognition and Y-maze tests, reduced brain/body mass ratio, increased brain glutamate concentration and acetylcholinesterase activity, decreased brain acetylcholine concentration, and lower choline acetyltransferase, glutaminase, and glutamine synthetase activities. Activities of antioxidant enzymes glutathione peroxidase and superoxide dismutase were also reduced, while the concentration of malondialdehyde, a lipid peroxidation product, was elevated. Further, antioxidant genes Nrf2, Prx2, Gsh-px1, and Sod1 were downregulated in brain. Each one of these changes was dose-dependently reversed by TFDG. TFDG is an effective antioxidant response inducer and neuroprotectant that can restore normal neurotransmitter metabolism and ameliorate learning and memory dysfunction in the D-galactose model of age-related cognitive decline.
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Affiliation(s)
- Yichou Cao
- School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou 215009, China
| | - Yunyi Zhang
- School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou 215009, China
| | - Zehan Jia
- School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou 215009, China
| | - Huining Jia
- School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou 215009, China
| | - Yuanchen Sun
- School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou 215009, China
| | - Hongxia Yuan
- School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou 215009, China
| | - Yongle Bian
- School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou 215009, China
| | - BingJie Xu
- School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou 215009, China
| | - Jing Fu
- Key Laboratory of Bio-resources of Shaanxi Province, College of Biological Science and Engineering, Shaanxi University of Technology, Hanzhong 723001, Shaanxi, China; Qinba State Key Laboratory of biological resources and ecological environment (Cultivation), Shaanxi University of Technology, Hanzhong 723001, Shaanxi, China.
| | - Fenju Qin
- School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou 215009, China.
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22
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Schroeder A, Pardi MB, Keijser J, Dalmay T, Groisman AI, Schuman EM, Sprekeler H, Letzkus JJ. Inhibitory top-down projections from zona incerta mediate neocortical memory. Neuron 2023; 111:727-738.e8. [PMID: 36610397 DOI: 10.1016/j.neuron.2022.12.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 10/19/2022] [Accepted: 12/08/2022] [Indexed: 01/07/2023]
Abstract
Top-down projections convey a family of signals encoding previous experiences and current aims to the sensory neocortex, where they converge with external bottom-up information to enable perception and memory. Whereas top-down control has been attributed to excitatory pathways, the existence, connectivity, and information content of inhibitory top-down projections remain elusive. Here, we combine synaptic two-photon calcium imaging, circuit mapping, cortex-dependent learning, and chemogenetics in mice to identify GABAergic afferents from the subthalamic zona incerta as a major source of top-down input to the neocortex. Incertocortical transmission undergoes robust plasticity during learning that improves information transfer and mediates behavioral memory. Unlike excitatory pathways, incertocortical afferents form a disinhibitory circuit that encodes learned top-down relevance in a bidirectional manner where the rapid appearance of negative responses serves as the main driver of changes in stimulus representation. Our results therefore reveal the distinctive contribution of long-range (dis)inhibitory afferents to the computational flexibility of neocortical circuits.
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Affiliation(s)
- Anna Schroeder
- Institute for Physiology, Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany; Max Planck Institute for Brain Research, 60438 Frankfurt, Germany.
| | - M Belén Pardi
- Institute for Physiology, Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany; Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, 75014 Paris, France
| | - Joram Keijser
- Modelling of Cognitive Processes, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, 10587 Berlin, Germany; Charité - Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, 10117 Berlin, Germany
| | - Tamas Dalmay
- Institute of Molecular and Clinical Ophthalmology Basel, 4031 Basel, Switzerland
| | - Ayelén I Groisman
- Institute for Physiology, Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany
| | - Erin M Schuman
- Max Planck Institute for Brain Research, 60438 Frankfurt, Germany
| | - Henning Sprekeler
- Modelling of Cognitive Processes, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, 10587 Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, 10115 Berlin, Germany; Science of Intelligence, Research Cluster of Excellence, 10587 Berlin, Germany
| | - Johannes J Letzkus
- Institute for Physiology, Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany; Center for Basics in NeuroModulation (NeuroModul Basics), University of Freiburg, 79106 Freiburg, Germany; IMBIT//BrainLinks-BrainTools, University of Freiburg, 79110 Freiburg, Germany.
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23
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Vandevelde JR, Yang JW, Albrecht S, Lam H, Kaufmann P, Luhmann HJ, Stüttgen MC. Layer- and cell-type-specific differences in neural activity in mouse barrel cortex during a whisker detection task. Cereb Cortex 2023; 33:1361-1382. [PMID: 35417918 DOI: 10.1093/cercor/bhac141] [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: 05/27/2021] [Revised: 03/17/2022] [Accepted: 03/18/2022] [Indexed: 11/14/2022] Open
Abstract
To address the question which neocortical layers and cell types are important for the perception of a sensory stimulus, we performed multielectrode recordings in the barrel cortex of head-fixed mice performing a single-whisker go/no-go detection task with vibrotactile stimuli of differing intensities. We found that behavioral detection probability decreased gradually over the course of each session, which was well explained by a signal detection theory-based model that posits stable psychometric sensitivity and a variable decision criterion updated after each reinforcement, reflecting decreasing motivation. Analysis of multiunit activity demonstrated highest neurometric sensitivity in layer 4, which was achieved within only 30 ms after stimulus onset. At the level of single neurons, we observed substantial heterogeneity of neurometric sensitivity within and across layers, ranging from nonresponsiveness to approaching or even exceeding psychometric sensitivity. In all cortical layers, putative inhibitory interneurons on average proffered higher neurometric sensitivity than putative excitatory neurons. In infragranular layers, neurons increasing firing rate in response to stimulation featured higher sensitivities than neurons decreasing firing rate. Offline machine-learning-based analysis of videos of behavioral sessions showed that mice performed better when not moving, which at the neuronal level, was reflected by increased stimulus-evoked firing rates.
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Affiliation(s)
- Jens R Vandevelde
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128 Mainz, Germany.,Institute of Pathophysiology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128 Mainz, Germany
| | - Jenq-Wei Yang
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128 Mainz, Germany
| | - Steffen Albrecht
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128 Mainz, Germany
| | - Henry Lam
- Computational Intelligence, Faculty of Law, Management and Economics, Johannes Gutenberg University Mainz, Jakob-Welder-Weg 9, 55128 Mainz, Germany
| | - Paul Kaufmann
- Computational Intelligence, Faculty of Law, Management and Economics, Johannes Gutenberg University Mainz, Jakob-Welder-Weg 9, 55128 Mainz, Germany
| | - Heiko J Luhmann
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128 Mainz, Germany
| | - Maik C Stüttgen
- Institute of Pathophysiology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128 Mainz, Germany
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24
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Aru J, Drüke M, Pikamäe J, Larkum ME. Mental navigation and the neural mechanisms of insight. Trends Neurosci 2023; 46:100-109. [PMID: 36462993 DOI: 10.1016/j.tins.2022.11.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 11/01/2022] [Accepted: 11/07/2022] [Indexed: 12/03/2022]
Abstract
How do new ideas come about? The central hypothesis presented here states that insights might happen during mental navigation and correspond to rapid plasticity at the cellular level. We highlight the differences between neocortical and hippocampal mechanisms of insight. We argue that the suddenness of insight can be related to the sudden emergence of place fields in the hippocampus. According to our hypothesis, insights are supported by a state of mind-wandering that can be tied to the process of combining knowledge pieces during sharp-wave ripples (SWRs). Our framework connects the dots between research on creativity, mental navigation, and specific synaptic plasticity mechanisms in the hippocampus.
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Affiliation(s)
- Jaan Aru
- Institute of Computer Science, University of Tartu, Tartu, Estonia.
| | - Moritz Drüke
- Institute of Biology, Humboldt University Berlin, Berlin, Germany
| | - Juhan Pikamäe
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Matthew E Larkum
- Institute of Biology, Humboldt University Berlin, Berlin, Germany; Neurocure Center for Excellence, Charité Universitätsmedizin Berlin, Berlin, Germany
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25
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Quantitative Fluorescence Analysis Reveals Dendrite-Specific Thalamocortical Plasticity in L5 Pyramidal Neurons during Learning. J Neurosci 2023; 43:584-600. [PMID: 36639912 PMCID: PMC9888508 DOI: 10.1523/jneurosci.1372-22.2022] [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: 07/07/2022] [Revised: 10/28/2022] [Accepted: 11/23/2022] [Indexed: 12/14/2022] Open
Abstract
High-throughput anatomic data can stimulate and constrain new hypotheses about how neural circuits change in response to experience. Here, we use fluorescence-based reagents for presynaptic and postsynaptic labeling to monitor changes in thalamocortical synapses onto different compartments of layer 5 (L5) pyramidal (Pyr) neurons in somatosensory (barrel) cortex from mixed-sex mice during whisker-dependent learning (Audette et al., 2019). Using axonal fills and molecular-genetic tags for synapse identification in fixed tissue from Rbp4-Cre transgenic mice, we found that thalamocortical synapses from the higher-order posterior medial thalamic nucleus showed rapid morphologic changes in both presynaptic and postsynaptic structures at the earliest stages of sensory association training. Detected increases in thalamocortical synaptic size were compartment specific, occurring selectively in the proximal dendrites onto L5 Pyr and not at inputs onto their apical tufts in L1. Both axonal and dendritic changes were transient, normalizing back to baseline as animals became expert in the task. Anatomical measurements were corroborated by electrophysiological recordings at different stages of training. Thus, fluorescence-based analysis of input- and target-specific synapses can reveal compartment-specific changes in synapse properties during learning.SIGNIFICANCE STATEMENT Synaptic changes underlie the cellular basis of learning, experience, and neurologic diseases. Neuroanatomical methods to assess synaptic plasticity can provide critical spatial information necessary for building models of neuronal computations during learning and experience but are technically and fiscally intensive. Here, we describe a confocal fluorescence microscopy-based analytical method to assess input, cell type, and dendritic location-specific synaptic plasticity in a sensory learning assay. Our method not only confirms prior electrophysiological measurements but allows us to predict functional strength of synapses in a pathway-specific manner. Our findings also indicate that changes in primary sensory cortices are transient, occurring during early learning. Fluorescence-based synapse identification can be an efficient and easily adopted approach to study synaptic changes in a variety of experimental paradigms.
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26
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Probing top-down information in neocortical layer 1. Trends Neurosci 2023; 46:20-31. [PMID: 36428192 DOI: 10.1016/j.tins.2022.11.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 10/26/2022] [Accepted: 11/01/2022] [Indexed: 11/23/2022]
Abstract
Accurate perception of the environment is a constructive process that requires integration of external bottom-up sensory signals with internally generated top-down information. Decades of work have elucidated how sensory neocortex processes physical stimulus features. By contrast, examining how top-down information is encoded and integrated with bottom-up signals has been challenging using traditional neuroscience methods. Recent technological advances in functional imaging of brain-wide afferents in behaving mice have enabled the direct measurement of top-down information. Here, we review the emerging literature on encoding of these internally generated signals by different projection systems enriched in neocortical layer 1 during defined brain functions, including memory, attention, and predictive coding. Moreover, we identify gaps in current knowledge and highlight future directions for this rapidly advancing field.
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27
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Neurodynamical Computing at the Information Boundaries of Intelligent Systems. Cognit Comput 2022. [DOI: 10.1007/s12559-022-10081-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
AbstractArtificial intelligence has not achieved defining features of biological intelligence despite models boasting more parameters than neurons in the human brain. In this perspective article, we synthesize historical approaches to understanding intelligent systems and argue that methodological and epistemic biases in these fields can be resolved by shifting away from cognitivist brain-as-computer theories and recognizing that brains exist within large, interdependent living systems. Integrating the dynamical systems view of cognition with the massive distributed feedback of perceptual control theory highlights a theoretical gap in our understanding of nonreductive neural mechanisms. Cell assemblies—properly conceived as reentrant dynamical flows and not merely as identified groups of neurons—may fill that gap by providing a minimal supraneuronal level of organization that establishes a neurodynamical base layer for computation. By considering information streams from physical embodiment and situational embedding, we discuss this computational base layer in terms of conserved oscillatory and structural properties of cortical-hippocampal networks. Our synthesis of embodied cognition, based in dynamical systems and perceptual control, aims to bypass the neurosymbolic stalemates that have arisen in artificial intelligence, cognitive science, and computational neuroscience.
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28
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Chowdhury A, Luchetti A, Fernandes G, Filho DA, Kastellakis G, Tzilivaki A, Ramirez EM, Tran MY, Poirazi P, Silva AJ. A locus coeruleus-dorsal CA1 dopaminergic circuit modulates memory linking. Neuron 2022; 110:3374-3388.e8. [PMID: 36041433 PMCID: PMC10508214 DOI: 10.1016/j.neuron.2022.08.001] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/07/2022] [Accepted: 07/31/2022] [Indexed: 11/20/2022]
Abstract
Individual memories are often linked so that the recall of one triggers the recall of another. For example, contextual memories acquired close in time can be linked, and this is known to depend on a temporary increase in excitability that drives the overlap between dorsal CA1 (dCA1) hippocampal ensembles that encode the linked memories. Here, we show that locus coeruleus (LC) cells projecting to dCA1 have a key permissive role in contextual memory linking, without affecting contextual memory formation, and that this effect is mediated by dopamine. Additionally, we found that LC-to-dCA1-projecting neurons modulate the excitability of dCA1 neurons and the extent of overlap between dCA1 memory ensembles as well as the stability of coactivity patterns within these ensembles. This discovery of a neuromodulatory system that specifically affects memory linking without affecting memory formation reveals a fundamental separation between the brain mechanisms modulating these two distinct processes.
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Affiliation(s)
- Ananya Chowdhury
- Departments of Neurobiology, Psychiatry & Biobehavioral Sciences, and Psychology, Integrative Center for Learning and Memory, and Brain Research Institute, UCLA, Los Angeles, CA 90095
| | - Alessandro Luchetti
- Departments of Neurobiology, Psychiatry & Biobehavioral Sciences, and Psychology, Integrative Center for Learning and Memory, and Brain Research Institute, UCLA, Los Angeles, CA 90095
| | - Giselle Fernandes
- Departments of Neurobiology, Psychiatry & Biobehavioral Sciences, and Psychology, Integrative Center for Learning and Memory, and Brain Research Institute, UCLA, Los Angeles, CA 90095
| | - Daniel Almeida Filho
- Departments of Neurobiology, Psychiatry & Biobehavioral Sciences, and Psychology, Integrative Center for Learning and Memory, and Brain Research Institute, UCLA, Los Angeles, CA 90095
| | - George Kastellakis
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Hellas (FORTH), Vassilica Vouton, PO Box 1527, GR 711 10 Heraklion, Crete, Greece
| | - Alexandra Tzilivaki
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Hellas (FORTH), Vassilica Vouton, PO Box 1527, GR 711 10 Heraklion, Crete, Greece
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health Charitéplatz 1, 10117 Berlin Germany
- Einstein Center for Neurosciences Berlin Charitéplatz 1, 10117 Berlin Germany
- Neurocure Cluster of Excellence Charitéplatz 1, 10117 Berlin, Germany
| | - Erica M Ramirez
- Departments of Neurobiology, Psychiatry & Biobehavioral Sciences, and Psychology, Integrative Center for Learning and Memory, and Brain Research Institute, UCLA, Los Angeles, CA 90095
| | - Mary Y Tran
- Departments of Neurobiology, Psychiatry & Biobehavioral Sciences, and Psychology, Integrative Center for Learning and Memory, and Brain Research Institute, UCLA, Los Angeles, CA 90095
| | - Panayiota Poirazi
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Hellas (FORTH), Vassilica Vouton, PO Box 1527, GR 711 10 Heraklion, Crete, Greece
| | - Alcino J Silva
- Departments of Neurobiology, Psychiatry & Biobehavioral Sciences, and Psychology, Integrative Center for Learning and Memory, and Brain Research Institute, UCLA, Los Angeles, CA 90095
- Lead contact
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29
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Gooch HM, Bluett T, Perumal MB, Vo HD, Fletcher LN, Papacostas J, Jeffree RL, Wood M, Colditz MJ, McMillen J, Tsahtsarlis T, Amato D, Campbell R, Gillinder L, Williams SR. High-fidelity dendritic sodium spike generation in human layer 2/3 neocortical pyramidal neurons. Cell Rep 2022; 41:111500. [DOI: 10.1016/j.celrep.2022.111500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/22/2022] [Accepted: 09/21/2022] [Indexed: 11/03/2022] Open
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30
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Brombas A, Zhou X, Williams SR. Light-evoked dendritic spikes in sustained but not transient rabbit retinal ganglion cells. Neuron 2022; 110:2802-2814.e3. [PMID: 35803269 DOI: 10.1016/j.neuron.2022.06.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/27/2022] [Accepted: 06/07/2022] [Indexed: 10/17/2022]
Abstract
Dendritic computations have a central role in neuronal function, but it is unknown how cell-class heterogeneity of dendritic electrical excitability shapes physiologically engaged neuronal and circuit computations. To address this, we examined dendritic integration in closely related classes of retinal ganglion cells (GCs) using simultaneous somato-dendritic electrical recording techniques in a functionally intact circuit. Simultaneous recordings revealed sustained OFF-GCs generated powerful dendritic spikes in response to visual input that drove action potential firing. In contrast, the dendrites of transient OFF-GCs were passive and did not generate dendritic spikes. Dendritic spike generation allowed sustained, but not transient, OFF-GCs to signal into action potential output the local motion of visual stimuli to produce a continuous wave of action potential firing in adjacent cells as images moved across the retina. Conversely, this representation was highly fragmented in transient OFF-GCs. Thus, a heterogeneity of dendritic excitability defines the computations executed by classes of GCs.
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Affiliation(s)
- Arne Brombas
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Xiangyu Zhou
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Stephen R Williams
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia.
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31
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Vafidis P, Owald D, D'Albis T, Kempter R. Learning accurate path integration in ring attractor models of the head direction system. eLife 2022; 11:69841. [PMID: 35723252 PMCID: PMC9286743 DOI: 10.7554/elife.69841] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 06/17/2022] [Indexed: 11/13/2022] Open
Abstract
Ring attractor models for angular path integration have received strong experimental support. To function as integrators, head direction circuits require precisely tuned connectivity, but it is currently unknown how such tuning could be achieved. Here, we propose a network model in which a local, biologically plausible learning rule adjusts synaptic efficacies during development, guided by supervisory allothetic cues. Applied to the Drosophila head direction system, the model learns to path-integrate accurately and develops a connectivity strikingly similar to the one reported in experiments. The mature network is a quasi-continuous attractor and reproduces key experiments in which optogenetic stimulation controls the internal representation of heading, and where the network remaps to integrate with different gains in rodents. Our model predicts that path integration requires self-supervised learning during a developmental phase, and proposes a general framework to learn to path-integrate with gain-1 even in architectures that lack the physical topography of a ring.
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Affiliation(s)
- Pantelis Vafidis
- Computation and Neural Systems, California Institute of Technology, Pasadena, United States
| | - David Owald
- NeuroCure, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Tiziano D'Albis
- Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Richard Kempter
- Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
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32
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Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse. Nat Commun 2022; 13:2811. [PMID: 35589710 PMCID: PMC9120471 DOI: 10.1038/s41467-022-30432-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 04/25/2022] [Indexed: 12/02/2022] Open
Abstract
Neuromorphic computing targets the hardware embodiment of neural network, and device implementation of individual neuron and synapse has attracted considerable attention. The emulation of synaptic plasticity has shown promising results after the advent of memristors. However, neuronal intrinsic plasticity, which involves in learning process through interactions with synaptic plasticity, has been rarely demonstrated. Synaptic and intrinsic plasticity occur concomitantly in learning process, suggesting the need of the simultaneous implementation. Here, we report a neurosynaptic device that mimics synaptic and intrinsic plasticity concomitantly in a single cell. Threshold switch and phase change memory are merged in threshold switch-phase change memory device. Neuronal intrinsic plasticity is demonstrated based on bottom threshold switch layer, which resembles the modulation of firing frequency in biological neuron. Synaptic plasticity is also introduced through the nonvolatile switching of top phase change layer. Intrinsic and synaptic plasticity are simultaneously emulated in a single cell to establish the positive feedback between them. A positive feedback learning loop which mimics the retraining process in biological system is implemented in threshold switch-phase change memory array for accelerated training. Synaptic plasticity and neuronal intrinsic plasticity are both involved in the learning process of hardware artificial neural network. Here, Lee et al. integrate a threshold switch and a phase change memory in a single device, which emulates biological synaptic and intrinsic plasticity simultaneously.
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33
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Genescu I, Aníbal-Martínez M, Kouskoff V, Chenouard N, Mailhes-Hamon C, Cartonnet H, Lokmane L, Rijli FM, López-Bendito G, Gambino F, Garel S. Dynamic interplay between thalamic activity and Cajal-Retzius cells regulates the wiring of cortical layer 1. Cell Rep 2022; 39:110667. [PMID: 35417707 PMCID: PMC9035679 DOI: 10.1016/j.celrep.2022.110667] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 02/17/2022] [Accepted: 03/18/2022] [Indexed: 11/30/2022] Open
Abstract
Cortical wiring relies on guidepost cells and activity-dependent processes that are thought to act sequentially. Here, we show that the construction of layer 1 (L1), a main site of top-down integration, is regulated by crosstalk between transient Cajal-Retzius cells (CRc) and spontaneous activity of the thalamus, a main driver of bottom-up information. While activity was known to regulate CRc migration and elimination, we found that prenatal spontaneous thalamic activity and NMDA receptors selectively control CRc early density, without affecting their demise. CRc density, in turn, regulates the distribution of upper layer interneurons and excitatory synapses, thereby drastically impairing the apical dendrite activity of output pyramidal neurons. In contrast, postnatal sensory-evoked activity had a limited impact on L1 and selectively perturbed basal dendrites synaptogenesis. Collectively, our study highlights a remarkable interplay between thalamic activity and CRc in L1 functional wiring, with major implications for our understanding of cortical development. Prenatal thalamic waves of activity regulate CRc density in L1 Prenatal and postnatal CRc manipulations alter specific interneuron populations Postnatal CRc shape L5 apical dendrite structural and functional properties Early sensory activity selectively regulates L5 basal dendrite spine formation
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Affiliation(s)
- Ioana Genescu
- Institut de Biologie de l'École Normale Supérieure (IBENS), Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
| | - Mar Aníbal-Martínez
- Instituto de Neurosciencias de Alicante, Universidad Miguel Hernandez, Sant Joan d'Alacant, Spain
| | - Vladimir Kouskoff
- University of Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS UMR 5297, 33000 Bordeaux, France
| | - Nicolas Chenouard
- University of Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS UMR 5297, 33000 Bordeaux, France
| | - Caroline Mailhes-Hamon
- Acute Transgenesis Facility, Institut de Biologie de l'École Normale Supérieure (IBENS), École Normale Supérieure, CNRS, INSERM, PSL Université Paris, 75005 Paris, France
| | - Hugues Cartonnet
- Institut de Biologie de l'École Normale Supérieure (IBENS), Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
| | - Ludmilla Lokmane
- Institut de Biologie de l'École Normale Supérieure (IBENS), Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
| | - Filippo M Rijli
- Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland; University of Basel, 4056 Basel, Switzerland
| | | | - Frédéric Gambino
- University of Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS UMR 5297, 33000 Bordeaux, France
| | - Sonia Garel
- Institut de Biologie de l'École Normale Supérieure (IBENS), Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France; Collège de France, 75005 Paris, France.
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34
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Linking Brain Structure, Activity, and Cognitive Function through Computation. eNeuro 2022; 9:ENEURO.0316-21.2022. [PMID: 35217544 PMCID: PMC8925650 DOI: 10.1523/eneuro.0316-21.2022] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 01/11/2022] [Accepted: 01/17/2022] [Indexed: 01/19/2023] Open
Abstract
Understanding the human brain is a “Grand Challenge” for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuroscience, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic principles and concepts interoperable, the Human Brain Project (HBP) has launched EBRAINS, a digital neuroscience research infrastructure, which brings together a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating insights and perspectives for societal benefits.
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35
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Larkum M. Are dendrites conceptually useful? Neuroscience 2022; 489:4-14. [DOI: 10.1016/j.neuroscience.2022.03.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 02/10/2022] [Accepted: 03/05/2022] [Indexed: 12/13/2022]
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36
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Larkum ME, Wu J, Duverdin SA, Gidon A. The guide to dendritic spikes of the mammalian cortex in vitro and in vivo. Neuroscience 2022; 489:15-33. [PMID: 35182699 DOI: 10.1016/j.neuroscience.2022.02.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 02/01/2022] [Accepted: 02/10/2022] [Indexed: 12/23/2022]
Abstract
Half a century since their discovery by Llinás and colleagues, dendritic spikes have been observed in various neurons in different brain regions, from the neocortex and cerebellum to the basal ganglia. Dendrites exhibit a terrifically diverse but stereotypical repertoire of spikes, sometimes specific to subregions of the dendrite. Despite their prevalence, we only have a glimpse into their role in the behaving animal. This article aims to survey the full range of dendritic spikes found in excitatory and inhibitory neurons, compare them in vivo versus in vitro, and discuss new studies describing dendritic spikes in the human cortex. We focus on dendritic spikes in neocortical and hippocampal neurons and present a roadmap to identify and understand the broader role of dendritic spikes in single-cell computation.
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Affiliation(s)
- Matthew E Larkum
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; NeuroCure Cluster, Charité - Universitätsmedizin Berlin, Germany
| | - Jiameng Wu
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Berlin, Germany
| | - Sarah A Duverdin
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Albert Gidon
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany
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37
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Waiblinger C, McDonnell ME, Reedy AR, Borden PY, Stanley GB. Emerging experience-dependent dynamics in primary somatosensory cortex reflect behavioral adaptation. Nat Commun 2022; 13:534. [PMID: 35087056 PMCID: PMC8795122 DOI: 10.1038/s41467-022-28193-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 01/05/2022] [Indexed: 11/09/2022] Open
Abstract
Behavioral experience and flexibility are crucial for survival in a constantly changing environment. Despite evolutionary pressures to develop adaptive behavioral strategies in a dynamically changing sensory landscape, the underlying neural correlates have not been well explored. Here, we use genetically encoded voltage imaging to measure signals in primary somatosensory cortex (S1) during sensory learning and behavioral adaptation in the mouse. In response to changing stimulus statistics, mice adopt a strategy that modifies their detection behavior in a context dependent manner as to maintain reward expectation. Surprisingly, neuronal activity in S1 shifts from simply representing stimulus properties to transducing signals necessary for adaptive behavior in an experience dependent manner. Our results suggest that neuronal signals in S1 are part of an adaptive framework that facilitates flexible behavior as individuals gain experience, which could be part of a general scheme that dynamically distributes the neural correlates of behavior during learning. Waiblinger et al. investigate the role of primary sensory cortex in flexible behaviors. They show that neuronal signals in S1 are part of an adaptive and dynamic framework that facilitates flexible behavior as an individual gains experience, indicating a role for S1 in long-term adaptive strategies.
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Affiliation(s)
- Christian Waiblinger
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Megan E McDonnell
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - April R Reedy
- Integrated Cellular Imaging Core, Emory University School of Medicine, Emory University, Atlanta, GA, USA
| | - Peter Y Borden
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Garrett B Stanley
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
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38
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Selective control of synaptically-connected circuit elements by all-optical synapses. Commun Biol 2022; 5:33. [PMID: 35017641 PMCID: PMC8752598 DOI: 10.1038/s42003-021-02981-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 12/15/2021] [Indexed: 12/29/2022] Open
Abstract
Understanding percepts, engrams and actions requires methods for selectively modulating synaptic communication between specific subsets of interconnected cells. Here, we develop an approach to control synaptically connected elements using bioluminescent light: Luciferase-generated light, originating from a presynaptic axon terminal, modulates an opsin in its postsynaptic target. Vesicular-localized luciferase is released into the synaptic cleft in response to presynaptic activity, creating a real-time Optical Synapse. Light production is under experimenter-control by introduction of the small molecule luciferin. Signal transmission across this optical synapse is temporally defined by the presence of both the luciferin and presynaptic activity. We validate synaptic Interluminescence by multi-electrode recording in cultured neurons and in mice in vivo. Interluminescence represents a powerful approach to achieve synapse-specific and activity-dependent circuit control in vivo.
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39
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Condylis C, Ghanbari A, Manjrekar N, Bistrong K, Yao S, Yao Z, Nguyen TN, Zeng H, Tasic B, Chen JL. Dense functional and molecular readout of a circuit hub in sensory cortex. Science 2022; 375:eabl5981. [PMID: 34990233 DOI: 10.1126/science.abl5981] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Although single-cell transcriptomics of the neocortex has uncovered more than 300 putative cell types, whether this molecular classification predicts distinct functional roles is unclear. We combined two-photon calcium imaging with spatial transcriptomics to functionally and molecularly investigate cortical circuits. We characterized behavior-related responses across major neuronal subclasses in layers 2 or 3 of the primary somatosensory cortex as mice performed a tactile working memory task. We identified an excitatory intratelencephalic cell type, Baz1a, that exhibits high tactile feature selectivity. Baz1a neurons homeostatically maintain stimulus responsiveness during altered experience and show persistent enrichment of subsets of immediately early genes. Functional and anatomical connectivity reveals that Baz1a neurons residing in upper portions of layers 2 or 3 preferentially innervate somatostatin-expressing inhibitory neurons. This motif defines a circuit hub that orchestrates local sensory processing in superficial layers of the neocortex.
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Affiliation(s)
- Cameron Condylis
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.,Center for Neurophotonics, Boston University, Boston, MA 02215, USA
| | - Abed Ghanbari
- Department of Biology, Boston University, Boston, MA 02215, USA
| | | | - Karina Bistrong
- Department of Biology, Boston University, Boston, MA 02215, USA
| | - Shenqin Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Bosiljka Tasic
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.,Center for Neurophotonics, Boston University, Boston, MA 02215, USA.,Department of Biology, Boston University, Boston, MA 02215, USA.,Center for Systems Neuroscience, Boston University, Boston, MA 02215, USA
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40
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Geng HY, Arbuthnott G, Yung WH, Ke Y. Long-Range Monosynaptic Inputs Targeting Apical and Basal Dendrites of Primary Motor Cortex Deep Output Neurons. Cereb Cortex 2021; 32:3975-3989. [PMID: 34905771 DOI: 10.1093/cercor/bhab460] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/10/2021] [Accepted: 11/16/2021] [Indexed: 12/31/2022] Open
Abstract
The primary motor cortex (M1) integrates various long-range signals from other brain regions for the learning and execution of goal-directed movements. How the different inputs target the distinct apical and basal dendrites of M1 pyramidal neurons is crucial in understanding the functions of M1, but the detailed connectivity pattern is still largely unknown. Here, by combining cre-dependent rabies virus tracing, layer-specific chemical retrograde tracing, optogenetic stimulation, and electrophysiological recording, we mapped all long-range monosynaptic inputs to M1 deep output neurons in layer 5 (L5) in mice. We revealed that most upstream areas innervate both dendritic compartments concurrently. These include the sensory cortices, higher motor cortices, sensory and motor thalamus, association cortices, as well as many subcortical nuclei. Furthermore, the dichotomous inputs arise mostly from spatially segregated neuronal subpopulations within an upstream nucleus, and even in the case of an individual cortical layer. Therefore, these input areas could serve as both feedforward and feedback sources albeit via different subpopulations. Taken together, our findings revealed a previously unknown and highly intricate synaptic input pattern of M1L5 neurons, which implicates that the dendritic computations carried out by these neurons during motor execution or learning are far more complicated than we currently understand.
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Affiliation(s)
- Hong-Yan Geng
- School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong
| | - Gordon Arbuthnott
- Brain Mechanisms for Behaviour Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa 904-0485, Japan
| | - Wing-Ho Yung
- School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong.,Gerald Choa Neuroscience Centre, The Chinese University of Hong Kong, Hong Kong
| | - Ya Ke
- School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong.,Gerald Choa Neuroscience Centre, The Chinese University of Hong Kong, Hong Kong
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41
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Vercruysse F, Naud R, Sprekeler H. Self-organization of a doubly asynchronous irregular network state for spikes and bursts. PLoS Comput Biol 2021; 17:e1009478. [PMID: 34748532 PMCID: PMC8575278 DOI: 10.1371/journal.pcbi.1009478] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 09/24/2021] [Indexed: 11/21/2022] Open
Abstract
Cortical pyramidal cells (PCs) have a specialized dendritic mechanism for the generation of bursts, suggesting that these events play a special role in cortical information processing. In vivo, bursts occur at a low, but consistent rate. Theory suggests that this network state increases the amount of information they convey. However, because burst activity relies on a threshold mechanism, it is rather sensitive to dendritic input levels. In spiking network models, network states in which bursts occur rarely are therefore typically not robust, but require fine-tuning. Here, we show that this issue can be solved by a homeostatic inhibitory plasticity rule in dendrite-targeting interneurons that is consistent with experimental data. The suggested learning rule can be combined with other forms of inhibitory plasticity to self-organize a network state in which both spikes and bursts occur asynchronously and irregularly at low rate. Finally, we show that this network state creates the network conditions for a recently suggested multiplexed code and thereby indeed increases the amount of information encoded in bursts.
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Affiliation(s)
- Filip Vercruysse
- Department for Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Richard Naud
- Department of Physics, University of Ottawa, Ottawa, Canada
- uOttawa Brain Mind Institute, Center for Neural Dynamics, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Canada
| | - Henning Sprekeler
- Department for Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
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42
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Abstract
[Figure: see text].
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Affiliation(s)
- Jiyun N Shin
- New York University Comprehensive Epilepsy Center, New York, NY, USA.,Department of Neurology, New York University School of Medicine, New York, NY, USA
| | - Guy Doron
- Scientific and Competitive Intelligence, R&D, Pharmaceuticals, Bayer AG, Berlin, Germany.,Institute for Biology, Humboldt University of Berlin, Berlin, Germany.,NeuroCure Cluster of Excellence, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Matthew E Larkum
- Institute for Biology, Humboldt University of Berlin, Berlin, Germany.,NeuroCure Cluster of Excellence, Charité - Universitätsmedizin Berlin, Berlin, Germany
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43
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Marvan T, Polák M, Bachmann T, Phillips WA. Apical amplification-a cellular mechanism of conscious perception? Neurosci Conscious 2021; 2021:niab036. [PMID: 34650815 PMCID: PMC8511476 DOI: 10.1093/nc/niab036] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 07/09/2021] [Accepted: 09/23/2021] [Indexed: 11/25/2022] Open
Abstract
We present a theoretical view of the cellular foundations for network-level processes involved in producing our conscious experience. Inputs to apical synapses in layer 1 of a large subset of neocortical cells are summed at an integration zone near the top of their apical trunk. These inputs come from diverse sources and provide a context within which the transmission of information abstracted from sensory input to their basal and perisomatic synapses can be amplified when relevant. We argue that apical amplification enables conscious perceptual experience and makes it more flexible, and thus more adaptive, by being sensitive to context. Apical amplification provides a possible mechanism for recurrent processing theory that avoids strong loops. It makes the broadcasting hypothesized by global neuronal workspace theories feasible while preserving the distinct contributions of the individual cells receiving the broadcast. It also provides mechanisms that contribute to the holistic aspects of integrated information theory. As apical amplification is highly dependent on cholinergic, aminergic, and other neuromodulators, it relates the specific contents of conscious experience to global mental states and to fluctuations in arousal when awake. We conclude that apical dendrites provide a cellular mechanism for the context-sensitive selective amplification that is a cardinal prerequisite of conscious perception.
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Affiliation(s)
- Tomáš Marvan
- Department of Analytic Philosophy, Institute of Philosophy, Czech Academy of Sciences, Jilská 1, Prague 110 00, Czech Republic
| | - Michal Polák
- Department of Philosophy, University of West Bohemia, Sedláčkova 19, Pilsen 306 14, Czech Republic
| | - Talis Bachmann
- School of Law and Cognitive Neuroscience Laboratory, University of Tartu (Tallinn branch), Kaarli pst 3, Tallinn 10119, Estonia
| | - William A Phillips
- Faculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UK
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44
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Acharya J, Basu A, Legenstein R, Limbacher T, Poirazi P, Wu X. Dendritic Computing: Branching Deeper into Machine Learning. Neuroscience 2021; 489:275-289. [PMID: 34656706 DOI: 10.1016/j.neuroscience.2021.10.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 09/07/2021] [Accepted: 10/03/2021] [Indexed: 12/31/2022]
Abstract
In this paper, we discuss the nonlinear computational power provided by dendrites in biological and artificial neurons. We start by briefly presenting biological evidence about the type of dendritic nonlinearities, respective plasticity rules and their effect on biological learning as assessed by computational models. Four major computational implications are identified as improved expressivity, more efficient use of resources, utilizing internal learning signals, and enabling continual learning. We then discuss examples of how dendritic computations have been used to solve real-world classification problems with performance reported on well known data sets used in machine learning. The works are categorized according to the three primary methods of plasticity used-structural plasticity, weight plasticity, or plasticity of synaptic delays. Finally, we show the recent trend of confluence between concepts of deep learning and dendritic computations and highlight some future research directions.
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Affiliation(s)
| | - Arindam Basu
- Department of Electrical Engineering, City University of Hong Kong, Hong Kong
| | - Robert Legenstein
- Institute of Theoretical Computer Science, Graz University of Technology, Austria
| | - Thomas Limbacher
- Institute of Theoretical Computer Science, Graz University of Technology, Austria
| | - Panayiota Poirazi
- Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology-Hellas (FORTH), Greece
| | - Xundong Wu
- School of Computer Science, Hangzhou Dianzi University, China
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45
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Schulz JM, Kay JW, Bischofberger J, Larkum ME. GABA B Receptor-Mediated Regulation of Dendro-Somatic Synergy in Layer 5 Pyramidal Neurons. Front Cell Neurosci 2021; 15:718413. [PMID: 34512268 PMCID: PMC8425515 DOI: 10.3389/fncel.2021.718413] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 07/20/2021] [Indexed: 11/24/2022] Open
Abstract
Synergistic interactions between independent synaptic input streams may fundamentally change the action potential (AP) output. Using partial information decomposition, we demonstrate here a substantial contribution of synergy between somatic and apical dendritic inputs to the information in the AP output of L5b pyramidal neurons. Activation of dendritic GABAB receptors (GABABRs), known to decrease APs in vivo, potently decreased synergy and increased somatic control of AP output. Synergy was the result of the voltage-dependence of the transfer resistance between dendrite and soma, which showed a two-fold increase per 28.7 mV dendritic depolarization. GIRK channels activated by dendritic GABABRs decreased voltage-dependent transfer resistances and AP output. In contrast, inhibition of dendritic L-type Ca2+ channels prevented high-frequency bursts of APs, but did not affect dendro-somatic synergy. Finally, we show that NDNF-positive neurogliaform cells effectively control somatic AP via synaptic activation of dendritic GIRK channels. These results uncover a novel inhibitory mechanism that powerfully gates cellular information flow in the cortex.
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Affiliation(s)
- Jan M Schulz
- Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Jim W Kay
- Department of Statistics, University of Glasgow, Glasgow, United Kingdom
| | | | - Matthew E Larkum
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany
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46
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Sinha M, Narayanan R. Active Dendrites and Local Field Potentials: Biophysical Mechanisms and Computational Explorations. Neuroscience 2021; 489:111-142. [PMID: 34506834 PMCID: PMC7612676 DOI: 10.1016/j.neuroscience.2021.08.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 08/30/2021] [Accepted: 08/31/2021] [Indexed: 10/27/2022]
Abstract
Neurons and glial cells are endowed with membranes that express a rich repertoire of ion channels, transporters, and receptors. The constant flux of ions across the neuronal and glial membranes results in voltage fluctuations that can be recorded from the extracellular matrix. The high frequency components of this voltage signal contain information about the spiking activity, reflecting the output from the neurons surrounding the recording location. The low frequency components of the signal, referred to as the local field potential (LFP), have been traditionally thought to provide information about the synaptic inputs that impinge on the large dendritic trees of various neurons. In this review, we discuss recent computational and experimental studies pointing to a critical role of several active dendritic mechanisms that can influence the genesis and the location-dependent spectro-temporal dynamics of LFPs, spanning different brain regions. We strongly emphasize the need to account for the several fast and slow dendritic events and associated active mechanisms - including gradients in their expression profiles, inter- and intra-cellular spatio-temporal interactions spanning neurons and glia, heterogeneities and degeneracy across scales, neuromodulatory influences, and activitydependent plasticity - towards gaining important insights about the origins of LFP under different behavioral states in health and disease. We provide simple but essential guidelines on how to model LFPs taking into account these dendritic mechanisms, with detailed methodology on how to account for various heterogeneities and electrophysiological properties of neurons and synapses while studying LFPs.
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Affiliation(s)
- Manisha Sinha
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka 560012, India
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka 560012, India.
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47
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Williams E, Payeur A, Gidon A, Naud R. Neural burst codes disguised as rate codes. Sci Rep 2021; 11:15910. [PMID: 34354118 PMCID: PMC8342467 DOI: 10.1038/s41598-021-95037-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 07/13/2021] [Indexed: 02/07/2023] Open
Abstract
The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. Many neurons, however, do not produce clearly demarcated bursts, an observation invoked to rule out the pervasiveness of this coding scheme across brain areas and cell types. Here we ask how detrimental ambiguous spike patterns, those that are neither clearly bursts nor isolated spikes, are for neuronal information transfer. We addressed this question using information theory and computational simulations. By quantifying how information transmission depends on firing statistics, we found that the information transmitted is not strongly influenced by the presence of clearly demarcated modes in the interspike interval distribution, a feature often used to identify the presence of burst coding. Instead, we found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on dynamical properties of the synapses as well as the length and relative frequency of bursts. Furthermore, we found that common metrics used to quantify burstiness were unable to predict the degree with which bursts could be used to carry information. Our results provide guiding principles for the implementation of coding strategies based on spike-timing patterns, and show that even unimodal firing statistics can be consistent with a bivariate neural code.
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Affiliation(s)
- Ezekiel Williams
- grid.28046.380000 0001 2182 2255Department of Mathematics and Statistics, University of Ottawa, 150 Louis Pasteur, Ottawa, K1N 6N5 Canada
| | - Alexandre Payeur
- grid.28046.380000 0001 2182 2255University of Ottawa Brain and Mind Institute, Centre for Neural Dynamics, Department of Cellular and Molecular Medicine, University of Ottawa, 451 Smyth Rd., Ottawa, K1H 8M5 Canada
| | - Albert Gidon
- grid.7468.d0000 0001 2248 7639Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Richard Naud
- grid.28046.380000 0001 2182 2255University of Ottawa Brain and Mind Institute, Centre for Neural Dynamics, Department of Cellular and Molecular Medicine, University of Ottawa, 451 Smyth Rd., Ottawa, K1H 8M5 Canada ,grid.28046.380000 0001 2182 2255Department of Physics, University of Ottawa, 150 Louis Pasteur, Ottawa, K1N 6N5 Canada
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48
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Harkin EF, Shen PR, Goel A, Richards BA, Naud R. Parallel and Recurrent Cascade Models as a Unifying Force for Understanding Sub-cellular Computation. Neuroscience 2021; 489:200-215. [PMID: 34358629 DOI: 10.1016/j.neuroscience.2021.07.026] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 07/06/2021] [Accepted: 07/25/2021] [Indexed: 11/15/2022]
Abstract
Neurons are very complicated computational devices, incorporating numerous non-linear processes, particularly in their dendrites. Biophysical models capture these processes directly by explicitly modelling physiological variables, such as ion channels, current flow, membrane capacitance, etc. However, another option for capturing the complexities of real neural computation is to use cascade models, which treat individual neurons as a cascade of linear and non-linear operations, akin to a multi-layer artificial neural network. Recent research has shown that cascade models can capture single-cell computation well, but there are still a number of sub-cellular, regenerative dendritic phenomena that they cannot capture, such as the interaction between sodium, calcium, and NMDA spikes in different compartments. Here, we propose that it is possible to capture these additional phenomena using parallel, recurrent cascade models, wherein an individual neuron is modelled as a cascade of parallel linear and non-linear operations that can be connected recurrently, akin to a multi-layer, recurrent, artificial neural network. Given their tractable mathematical structure, we show that neuron models expressed in terms of parallel recurrent cascades can themselves be integrated into multi-layered artificial neural networks and trained to perform complex tasks. We go on to discuss potential implications and uses of these models for artificial intelligence. Overall, we argue that parallel, recurrent cascade models provide an important, unifying tool for capturing single-cell computation and exploring the algorithmic implications of physiological phenomena.
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Affiliation(s)
- Emerson F Harkin
- uOttawa Brain and Mind Institute, Centre for Neural Dynamics, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Peter R Shen
- Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada
| | - Anish Goel
- Lisgar Collegiate Institute, Ottawa, ON, Canada
| | - Blake A Richards
- Mila, Montréal, QC, Canada; Montreal Neurological Institute, Montréal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada; School of Computer Science, McGill University, Montréal, QC, Canada.
| | - Richard Naud
- uOttawa Brain and Mind Institute, Centre for Neural Dynamics, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada; Department of Physics, University of Ottawa, Ottawa, ON, Canada.
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49
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Stuyt G, Godenzini L, Palmer LM. Local and Global Dynamics of Dendritic Activity in the Pyramidal Neuron. Neuroscience 2021; 489:176-184. [PMID: 34280492 DOI: 10.1016/j.neuroscience.2021.07.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 07/06/2021] [Accepted: 07/08/2021] [Indexed: 12/22/2022]
Abstract
There has been increasing interest in the measurement and comparison of activity across compartments of the pyramidal neuron. Dendritic activity can occur both locally, on a single dendritic segment, or globally, involving multiple compartments of the single neuron. Little is known about how these dendritic dynamics shape and contribute to information processing and behavior. Although it has been difficult to characterize local and global activity in vivo due to the technical challenge of simultaneously recording from the entire dendritic arbor and soma, the rise of calcium imaging has driven the increased feasibility and interest of these experiments. However, the distinction between local and global activity made by calcium imaging requires careful consideration. In this review we describe local and global activity, discuss the difficulties and caveats of this distinction, and present the evidence of local and global activity in information processing and behavior.
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Affiliation(s)
- George Stuyt
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Luca Godenzini
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Lucy M Palmer
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3052, Australia.
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50
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Fiorilli J, Bos JJ, Grande X, Lim J, Düzel E, Pennartz CMA. Reconciling the object and spatial processing views of the perirhinal cortex through task-relevant unitization. Hippocampus 2021; 31:737-755. [PMID: 33523577 PMCID: PMC8359385 DOI: 10.1002/hipo.23304] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 11/27/2020] [Accepted: 01/02/2021] [Indexed: 12/21/2022]
Abstract
The perirhinal cortex is situated on the border between sensory association cortex and the hippocampal formation. It serves an important function as a transition area between the sensory neocortex and the medial temporal lobe. While the perirhinal cortex has traditionally been associated with object coding and the "what" pathway of the temporal lobe, current evidence suggests a broader function of the perirhinal cortex in solving feature ambiguity and processing complex stimuli. Besides fulfilling functions in object coding, recent neurophysiological findings in freely moving rodents indicate that the perirhinal cortex also contributes to spatial and contextual processing beyond individual sensory modalities. Here, we address how these two opposing views on perirhinal cortex-the object-centered and spatial-contextual processing hypotheses-may be reconciled. The perirhinal cortex is consistently recruited when different features can be merged perceptually or conceptually into a single entity. Features that are unitized in these entities include object information from multiple sensory domains, reward associations, semantic features and spatial/contextual associations. We propose that the same perirhinal network circuits can be flexibly deployed for multiple cognitive functions, such that the perirhinal cortex performs similar unitization operations on different types of information, depending on behavioral demands and ranging from the object-related domain to spatial, contextual and semantic information.
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Affiliation(s)
- Julien Fiorilli
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
| | - Jeroen J. Bos
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud University and Radboud University Medical CentreNijmegenThe Netherlands
| | - Xenia Grande
- Institute of Cognitive Neurology and Dementia ResearchOtto‐von‐Guericke University MagdeburgMagdeburgGermany
- German Center for Neurodegenerative DiseasesMagdeburgGermany
| | - Judith Lim
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia ResearchOtto‐von‐Guericke University MagdeburgMagdeburgGermany
- German Center for Neurodegenerative DiseasesMagdeburgGermany
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
| | - Cyriel M. A. Pennartz
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
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