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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Yang X, La Camera G. Co-existence of synaptic plasticity and metastable dynamics in a spiking model of cortical circuits. PLoS Comput Biol 2024; 20:e1012220. [PMID: 38950068 DOI: 10.1371/journal.pcbi.1012220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 06/01/2024] [Indexed: 07/03/2024] Open
Abstract
Evidence for metastable dynamics and its role in brain function is emerging at a fast pace and is changing our understanding of neural coding by putting an emphasis on hidden states of transient activity. Clustered networks of spiking neurons have enhanced synaptic connections among groups of neurons forming structures called cell assemblies; such networks are capable of producing metastable dynamics that is in agreement with many experimental results. However, it is unclear how a clustered network structure producing metastable dynamics may emerge from a fully local plasticity rule, i.e., a plasticity rule where each synapse has only access to the activity of the neurons it connects (as opposed to the activity of other neurons or other synapses). Here, we propose a local plasticity rule producing ongoing metastable dynamics in a deterministic, recurrent network of spiking neurons. The metastable dynamics co-exists with ongoing plasticity and is the consequence of a self-tuning mechanism that keeps the synaptic weights close to the instability line where memories are spontaneously reactivated. In turn, the synaptic structure is stable to ongoing dynamics and random perturbations, yet it remains sufficiently plastic to remap sensory representations to encode new sets of stimuli. Both the plasticity rule and the metastable dynamics scale well with network size, with synaptic stability increasing with the number of neurons. Overall, our results show that it is possible to generate metastable dynamics over meaningful hidden states using a simple but biologically plausible plasticity rule which co-exists with ongoing neural dynamics.
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Affiliation(s)
- Xiaoyu Yang
- Graduate Program in Physics and Astronomy, Stony Brook University, Stony Brook, New York, United States of America
- Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, New York, United States of America
- Center for Neural Circuit Dynamics, Stony Brook University, Stony Brook, New York, United States of America
| | - Giancarlo La Camera
- Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, New York, United States of America
- Center for Neural Circuit Dynamics, Stony Brook University, Stony Brook, New York, United States of America
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3
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Xiao S, Yadav S, Jayant K. Probing multiplexed basal dendritic computations using two-photon 3D holographic uncaging. Cell Rep 2024; 43:114413. [PMID: 38943640 DOI: 10.1016/j.celrep.2024.114413] [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: 09/29/2022] [Revised: 05/06/2024] [Accepted: 06/12/2024] [Indexed: 07/01/2024] Open
Abstract
Basal dendrites of layer 5 cortical pyramidal neurons exhibit Na+ and N-methyl-D-aspartate receptor (NMDAR) regenerative spikes and are uniquely poised to influence somatic output. Nevertheless, due to technical limitations, how multibranch basal dendritic integration shapes and enables multiplexed barcoding of synaptic streams remains poorly mapped. Here, we combine 3D two-photon holographic transmitter uncaging, whole-cell dynamic clamp, and biophysical modeling to reveal how synchronously activated synapses (distributed and clustered) across multiple basal dendritic branches are multiplexed under quiescent and in vivo-like conditions. While dendritic regenerative Na+ spikes promote millisecond somatic spike precision, distributed synaptic inputs and NMDAR spikes regulate gain. These concomitantly occurring dendritic nonlinearities enable multiplexed information transfer amid an ongoing noisy background, including under back-propagating voltage resets, by barcoding the axo-somatic spike structure. Our results unveil a multibranch dendritic integration framework in which dendritic nonlinearities are critical for multiplexing different spatial-temporal synaptic input patterns, enabling optimal feature binding.
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Affiliation(s)
- Shulan Xiao
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
| | - Saumitra Yadav
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
| | - Krishna Jayant
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA; Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA.
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4
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Yang X, La Camera G. Co-existence of synaptic plasticity and metastable dynamics in a spiking model of cortical circuits. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.07.570692. [PMID: 38106233 PMCID: PMC10723399 DOI: 10.1101/2023.12.07.570692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Evidence for metastable dynamics and its role in brain function is emerging at a fast pace and is changing our understanding of neural coding by putting an emphasis on hidden states of transient activity. Clustered networks of spiking neurons have enhanced synaptic connections among groups of neurons forming structures called cell assemblies; such networks are capable of producing metastable dynamics that is in agreement with many experimental results. However, it is unclear how a clustered network structure producing metastable dynamics may emerge from a fully local plasticity rule, i.e., a plasticity rule where each synapse has only access to the activity of the neurons it connects (as opposed to the activity of other neurons or other synapses). Here, we propose a local plasticity rule producing ongoing metastable dynamics in a deterministic, recurrent network of spiking neurons. The metastable dynamics co-exists with ongoing plasticity and is the consequence of a self-tuning mechanism that keeps the synaptic weights close to the instability line where memories are spontaneously reactivated. In turn, the synaptic structure is stable to ongoing dynamics and random perturbations, yet it remains sufficiently plastic to remap sensory representations to encode new sets of stimuli. Both the plasticity rule and the metastable dynamics scale well with network size, with synaptic stability increasing with the number of neurons. Overall, our results show that it is possible to generate metastable dynamics over meaningful hidden states using a simple but biologically plausible plasticity rule which co-exists with ongoing neural dynamics.
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Affiliation(s)
- Xiaoyu Yang
- Graduate Program in Physics and Astronomy, Stony Brook University
- Department of Neurobiology & Behavior, Stony Brook University
- Center for Neural Circuit Dynamics, Stony Brook University
| | - Giancarlo La Camera
- Department of Neurobiology & Behavior, Stony Brook University
- Center for Neural Circuit Dynamics, Stony Brook University
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5
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Bredenberg C, Savin C. Desiderata for Normative Models of Synaptic Plasticity. Neural Comput 2024; 36:1245-1285. [PMID: 38776950 DOI: 10.1162/neco_a_01671] [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: 08/09/2023] [Accepted: 02/06/2024] [Indexed: 05/25/2024]
Abstract
Normative models of synaptic plasticity use computational rationales to arrive at predictions of behavioral and network-level adaptive phenomena. In recent years, there has been an explosion of theoretical work in this realm, but experimental confirmation remains limited. In this review, we organize work on normative plasticity models in terms of a set of desiderata that, when satisfied, are designed to ensure that a given model demonstrates a clear link between plasticity and adaptive behavior, is consistent with known biological evidence about neural plasticity and yields specific testable predictions. As a prototype, we include a detailed analysis of the REINFORCE algorithm. We also discuss how new models have begun to improve on the identified criteria and suggest avenues for further development. Overall, we provide a conceptual guide to help develop neural learning theories that are precise, powerful, and experimentally testable.
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Affiliation(s)
- Colin Bredenberg
- Center for Neural Science, New York University, New York, NY 10003, U.S.A
- Mila-Quebec AI Institute, Montréal, QC H2S 3H1, Canada
| | - Cristina Savin
- Center for Neural Science, New York University, New York, NY 10003, U.S.A
- Center for Data Science, New York University, New York, NY 10011, U.S.A.
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6
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Buccino AP, Damart T, Bartram J, Mandge D, Xue X, Zbili M, Gänswein T, Jaquier A, Emmenegger V, Markram H, Hierlemann A, Van Geit W. A Multimodal Fitting Approach to Construct Single-Neuron Models With Patch Clamp and High-Density Microelectrode Arrays. Neural Comput 2024; 36:1286-1331. [PMID: 38776965 DOI: 10.1162/neco_a_01672] [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: 03/15/2023] [Accepted: 02/20/2024] [Indexed: 05/25/2024]
Abstract
In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of nonsomatic compartments. In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density microelectrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at subcellular resolution. In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures. The proposed multimodal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and provide the field with neuronal models that are more realistic and can be better validated.
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Affiliation(s)
- Alessio Paolo Buccino
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Tanguy Damart
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Julian Bartram
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Darshan Mandge
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Xiaohan Xue
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Mickael Zbili
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Tobias Gänswein
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Aurélien Jaquier
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Vishalini Emmenegger
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Henry Markram
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Andreas Hierlemann
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Werner Van Geit
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland Present address: Foundation for Research on Information Technologies in Society (IT'IS), Zurich 8004, Switzerland
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7
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Jordan J, Sacramento J, Wybo WAM, Petrovici MA, Senn W. Conductance-based dendrites perform Bayes-optimal cue integration. PLoS Comput Biol 2024; 20:e1012047. [PMID: 38865345 PMCID: PMC11168673 DOI: 10.1371/journal.pcbi.1012047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 03/31/2024] [Indexed: 06/14/2024] Open
Abstract
A fundamental function of cortical circuits is the integration of information from different sources to form a reliable basis for behavior. While animals behave as if they optimally integrate information according to Bayesian probability theory, the implementation of the required computations in the biological substrate remains unclear. We propose a novel, Bayesian view on the dynamics of conductance-based neurons and synapses which suggests that they are naturally equipped to optimally perform information integration. In our approach apical dendrites represent prior expectations over somatic potentials, while basal dendrites represent likelihoods of somatic potentials. These are parametrized by local quantities, the effective reversal potentials and membrane conductances. We formally demonstrate that under these assumptions the somatic compartment naturally computes the corresponding posterior. We derive a gradient-based plasticity rule, allowing neurons to learn desired target distributions and weight synaptic inputs by their relative reliabilities. Our theory explains various experimental findings on the system and single-cell level related to multi-sensory integration, which we illustrate with simulations. Furthermore, we make experimentally testable predictions on Bayesian dendritic integration and synaptic plasticity.
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Affiliation(s)
- Jakob Jordan
- Department of Physiology, University of Bern, Bern, Switzerland
- Electrical Engineering, Yale University, New Haven, Connecticut, United States of America
| | - João Sacramento
- Department of Physiology, University of Bern, Bern, Switzerland
- Institute of Neuroinformatics, UZH / ETH Zurich, Zurich, Switzerland
| | - Willem A. M. Wybo
- Department of Physiology, University of Bern, Bern, Switzerland
- Institute of Neuroscience and Medicine, Forschungszentrum Jülich, Jülich, Germany
| | | | - Walter Senn
- Department of Physiology, University of Bern, Bern, Switzerland
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8
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Kim HH, Bonekamp KE, Gillie GR, Autio DM, Keller T, Crandall SR. Functional Dynamics and Selectivity of Two Parallel Corticocortical Pathways from Motor Cortex to Layer 5 Circuits in Somatosensory Cortex. eNeuro 2024; 11:ENEURO.0154-24.2024. [PMID: 38834298 PMCID: PMC11209671 DOI: 10.1523/eneuro.0154-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 05/20/2024] [Accepted: 05/28/2024] [Indexed: 06/06/2024] Open
Abstract
In the rodent whisker system, active sensing and sensorimotor integration are mediated in part by the dynamic interactions between the motor cortex (M1) and somatosensory cortex (S1). However, understanding these dynamic interactions requires knowledge about the synapses and how specific neurons respond to their input. Here, we combined optogenetics, retrograde labeling, and electrophysiology to characterize the synaptic connections between M1 and layer 5 (L5) intratelencephalic (IT) and pyramidal tract (PT) neurons in S1 of mice (both sexes). We found that M1 synapses onto IT cells displayed modest short-term depression, whereas synapses onto PT neurons showed robust short-term facilitation. Despite M1 inputs to IT cells depressing, their slower kinetics resulted in summation and a response that increased during short trains. In contrast, summation was minimal in PT neurons due to the fast time course of their M1 responses. The functional consequences of this reduced summation, however, were outweighed by the strong facilitation at these M1 synapses, resulting in larger response amplitudes in PT neurons than IT cells during repetitive stimulation. To understand the impact of facilitating M1 inputs on PT output, we paired trains of inputs with single backpropagating action potentials, finding that repetitive M1 activation increased the probability of bursts in PT cells without impacting the time dependence of this coupling. Thus, there are two parallel but dynamically distinct systems of M1 synaptic excitation in L5 of S1, each defined by the short-term dynamics of its synapses, the class of postsynaptic neurons, and how the neurons respond to those inputs.
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Affiliation(s)
- Hye-Hyun Kim
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
| | - Kelly E Bonekamp
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University, East Lansing, Michigan 48824
| | - Grant R Gillie
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University, East Lansing, Michigan 48824
| | - Dawn M Autio
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
| | - Tryton Keller
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
| | - Shane R Crandall
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University, East Lansing, Michigan 48824
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9
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Granato A, Phillips WA, Schulz JM, Suzuki M, Larkum ME. Dysfunctions of cellular context-sensitivity in neurodevelopmental learning disabilities. Neurosci Biobehav Rev 2024; 161:105688. [PMID: 38670298 DOI: 10.1016/j.neubiorev.2024.105688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 04/17/2024] [Accepted: 04/21/2024] [Indexed: 04/28/2024]
Abstract
Pyramidal neurons have a pivotal role in the cognitive capabilities of neocortex. Though they have been predominantly modeled as integrate-and-fire point processors, many of them have another point of input integration in their apical dendrites that is central to mechanisms endowing them with the sensitivity to context that underlies basic cognitive capabilities. Here we review evidence implicating impairments of those mechanisms in three major neurodevelopmental disabilities, fragile X, Down syndrome, and fetal alcohol spectrum disorders. Multiple dysfunctions of the mechanisms by which pyramidal cells are sensitive to context are found to be implicated in all three syndromes. Further deciphering of these cellular mechanisms would lead to the understanding of and therapies for learning disabilities beyond any that are currently available.
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Affiliation(s)
- Alberto Granato
- Dept. of Veterinary Sciences. University of Turin, Grugliasco, Turin 10095, Italy.
| | - William A Phillips
- Psychology, Faculty of Natural Sciences, University of Stirling, Scotland FK9 4LA, UK
| | - Jan M Schulz
- Roche Pharma Research & Early Development, Neuroscience & Rare Diseases Discovery, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, Basel 4070, Switzerland
| | - Mototaka Suzuki
- Dept. of Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam 1098 XH, the Netherlands
| | - Matthew E Larkum
- Neurocure Center for Excellence, Charité Universitätsmedizin Berlin, Berlin 10117, Germany; Institute of Biology, Humboldt University Berlin, Berlin, Germany
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10
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Kim HH, Bonekamp KE, Gillie GR, Autio DM, Keller T, Crandall SR. Functional dynamics and selectivity of two parallel corticocortical pathways from motor cortex to layer 5 circuits in somatosensory cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.11.579810. [PMID: 38405888 PMCID: PMC10888929 DOI: 10.1101/2024.02.11.579810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
In the rodent whisker system, active sensing and sensorimotor integration are mediated in part by the dynamic interactions between the motor cortex (M1) and somatosensory cortex (S1). However, understanding these dynamic interactions requires knowledge about the synapses and how specific neurons respond to their input. Here, we combined optogenetics, retrograde labeling, and electrophysiology to characterize the synaptic connections between M1 and layer 5 (L5) intratelencephalic (IT) and pyramidal tract (PT) neurons in S1 of mice (both sexes). We found that M1 synapses onto IT cells displayed modest short-term depression, whereas synapses onto PT neurons showed robust short-term facilitation. Despite M1 inputs to IT cells depressing, their slower kinetics resulted in summation and a response that increased during short trains. In contrast, summation was minimal in PT neurons due to the fast time course of their M1 responses. The functional consequences of this reduced summation, however, were outweighed by the strong facilitation at these M1 synapses, resulting in larger response amplitudes in PT neurons than IT cells during repetitive stimulation. To understand the impact of facilitating M1 inputs on PT output, we paired trains of inputs with single backpropagating action potentials, finding that repetitive M1 activation increased the probability of bursts in PT cells without impacting the time-dependence of this coupling. Thus, there are two parallel but dynamically distinct systems of M1 synaptic excitation in L5 of S1, each defined by the short-term dynamics of its synapses, the class of postsynaptic neurons, and how the neurons respond to those inputs.
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Affiliation(s)
- Hye-Hyun Kim
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
| | - Kelly E. Bonekamp
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University East Lansing, MI 48824, USA
| | - Grant R. Gillie
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University East Lansing, MI 48824, USA
| | - Dawn M. Autio
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
| | - Tryton Keller
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
| | - Shane R. Crandall
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University East Lansing, MI 48824, USA
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11
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Park P, Wong-Campos D, Itkis DG, Lee BH, Qi Y, Davis H, Antin B, Pasarkar A, Grimm JB, Plutkis SE, Holland KL, Paninski L, Lavis LD, Cohen AE. Dendritic excitations govern back-propagation via a spike-rate accelerometer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.02.543490. [PMID: 37398232 PMCID: PMC10312650 DOI: 10.1101/2023.06.02.543490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Dendrites on neurons support nonlinear electrical excitations, but the computational significance of these events is not well understood. We developed molecular, optical, and analytical tools to map sub-millisecond voltage dynamics throughout the dendritic trees of CA1 pyramidal neurons under diverse optogenetic and synaptic stimulus patterns, in acute brain slices. We observed history-dependent spike back-propagation in distal dendrites, driven by locally generated Na+ spikes (dSpikes). Dendritic depolarization created a transient window for dSpike propagation, opened by A-type K V channel inactivation, and closed by slow N a V inactivation. Collisions of dSpikes with synaptic inputs triggered calcium channel and N-methyl-D-aspartate receptor (NMDAR)-dependent plateau potentials, with accompanying complex spikes at the soma. This hierarchical ion channel network acts as a spike-rate accelerometer, providing an intuitive picture of how dendritic excitations shape associative plasticity rules.
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Affiliation(s)
- Pojeong Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - David Wong-Campos
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Daniel G Itkis
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Byung Hun Lee
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Yitong Qi
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Hunter Davis
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Benjamin Antin
- Departments of Statistics and Neuroscience, Columbia University, New York, NY, USA
| | - Amol Pasarkar
- Departments of Statistics and Neuroscience, Columbia University, New York, NY, USA
| | - Jonathan B Grimm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Sarah E Plutkis
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Katie L Holland
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Liam Paninski
- Departments of Statistics and Neuroscience, Columbia University, New York, NY, USA
| | - Luke D Lavis
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Physics, Harvard University, Cambridge, MA, USA
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12
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Schiff ND. Toward an interventional science of recovery after coma. Neuron 2024; 112:1595-1610. [PMID: 38754372 DOI: 10.1016/j.neuron.2024.04.027] [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: 02/20/2024] [Revised: 04/04/2024] [Accepted: 04/24/2024] [Indexed: 05/18/2024]
Abstract
Recovery of consciousness after coma remains one of the most challenging areas for accurate diagnosis and effective therapeutic engagement in the clinical neurosciences. Recovery depends on preservation of neuronal integrity and evolving changes in network function that re-establish environmental responsiveness. It typically occurs in defined steps: it begins with eye opening and unresponsiveness in a vegetative state, then limited recovery of responsiveness characterizes the minimally conscious state, and this is followed by recovery of reliable communication. This review considers several points for novel interventions, for example, in persons with cognitive motor dissociation in whom a hidden cognitive reserve is revealed. Circuit mechanisms underlying restoration of behavioral responsiveness and communication are discussed. An emerging theme is the possibility to rescue latent capacities in partially damaged human networks across time. These opportunities should be exploited for therapeutic engagement to achieve individualized solutions for restoration of communication and environmental interaction across varying levels of recovery.
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Affiliation(s)
- Nicholas D Schiff
- Jerold B. Katz Professor of Neurology and Neuroscience, Weill Cornell Medicine, New York, NY, USA.
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13
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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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14
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Tye KM, Miller EK, Taschbach FH, Benna MK, Rigotti M, Fusi S. Mixed selectivity: Cellular computations for complexity. Neuron 2024:S0896-6273(24)00278-2. [PMID: 38729151 DOI: 10.1016/j.neuron.2024.04.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 03/08/2024] [Accepted: 04/12/2024] [Indexed: 05/12/2024]
Abstract
The property of mixed selectivity has been discussed at a computational level and offers a strategy to maximize computational power by adding versatility to the functional role of each neuron. Here, we offer a biologically grounded implementational-level mechanistic explanation for mixed selectivity in neural circuits. We define pure, linear, and nonlinear mixed selectivity and discuss how these response properties can be obtained in simple neural circuits. Neurons that respond to multiple, statistically independent variables display mixed selectivity. If their activity can be expressed as a weighted sum, then they exhibit linear mixed selectivity; otherwise, they exhibit nonlinear mixed selectivity. Neural representations based on diverse nonlinear mixed selectivity are high dimensional; hence, they confer enormous flexibility to a simple downstream readout neural circuit. However, a simple neural circuit cannot possibly encode all possible mixtures of variables simultaneously, as this would require a combinatorially large number of mixed selectivity neurons. Gating mechanisms like oscillations and neuromodulation can solve this problem by dynamically selecting which variables are mixed and transmitted to the readout.
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Affiliation(s)
- Kay M Tye
- Salk Institute for Biological Studies, La Jolla, CA, USA; Howard Hughes Medical Institute, La Jolla, CA; Department of Neurobiology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Kavli Institute for Brain and Mind, San Diego, CA, USA.
| | - Earl K Miller
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Felix H Taschbach
- Salk Institute for Biological Studies, La Jolla, CA, USA; Biological Science Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA; Department of Neurobiology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Marcus K Benna
- Department of Neurobiology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA.
| | | | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA; Department of Neuroscience, Columbia University, New York, NY, USA; Kavli Institute for Brain Science, Columbia University, New York, NY, USA.
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15
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Xu NL. How the brain's primary processing units compute to give rise to intelligence. Nat Rev Neurosci 2024; 25:288. [PMID: 38480831 DOI: 10.1038/s41583-024-00810-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2024]
Affiliation(s)
- Ning-Long Xu
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
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16
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Galloni AR, Yuan Y, Zhu M, Yu H, Bisht RS, Wu CTM, Grienberger C, Ramanathan S, Milstein AD. Neuromorphic one-shot learning utilizing a phase-transition material. Proc Natl Acad Sci U S A 2024; 121:e2318362121. [PMID: 38630718 PMCID: PMC11047090 DOI: 10.1073/pnas.2318362121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 03/25/2024] [Indexed: 04/19/2024] Open
Abstract
Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy- and sample-efficient AI and learning machines. An important factor in selection of the hardware building blocks is the identification of candidate materials with physical properties suitable to emulate the large dynamic ranges and varied timescales of neuronal signaling. Previous work has shown that the all-or-none spiking behavior of neurons can be mimicked by threshold switches utilizing material phase transitions. Here, we demonstrate that devices based on a prototypical metal-insulator-transition material, vanadium dioxide (VO2), can be dynamically controlled to access a continuum of intermediate resistance states. Furthermore, the timescale of their intrinsic relaxation can be configured to match a range of biologically relevant timescales from milliseconds to seconds. We exploit these device properties to emulate three aspects of neuronal analog computation: fast (~1 ms) spiking in a neuronal soma compartment, slow (~100 ms) spiking in a dendritic compartment, and ultraslow (~1 s) biochemical signaling involved in temporal credit assignment for a recently discovered biological mechanism of one-shot learning. Simulations show that an artificial neural network using properties of VO2 devices to control an agent navigating a spatial environment can learn an efficient path to a reward in up to fourfold fewer trials than standard methods. The phase relaxations described in our study may be engineered in a variety of materials and can be controlled by thermal, electrical, or optical stimuli, suggesting further opportunities to emulate biological learning in neuromorphic hardware.
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Affiliation(s)
- Alessandro R. Galloni
- Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, Piscataway, NJ08854
- Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway, NJ08854
| | - Yifan Yuan
- Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ08854
| | - Minning Zhu
- Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ08854
| | - Haoming Yu
- School of Materials Engineering, Purdue University, West Lafayette, IN47907
| | - Ravindra S. Bisht
- Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ08854
| | - Chung-Tse Michael Wu
- Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ08854
| | - Christine Grienberger
- Department of Neuroscience, Brandeis University, Waltham, MA02453
- Department of Biology and Volen National Center for Complex Systems, Brandeis University, Waltham, MA02453
| | - Shriram Ramanathan
- Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ08854
| | - Aaron D. Milstein
- Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, Piscataway, NJ08854
- Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway, NJ08854
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17
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Marvan T, Phillips WA. Cellular mechanisms of cooperative context-sensitive predictive inference. CURRENT RESEARCH IN NEUROBIOLOGY 2024; 6:100129. [PMID: 38665363 PMCID: PMC11043869 DOI: 10.1016/j.crneur.2024.100129] [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: 11/11/2023] [Revised: 02/14/2024] [Accepted: 03/25/2024] [Indexed: 04/28/2024] Open
Abstract
We argue that prediction success maximization is a basic objective of cognition and cortex, that it is compatible with but distinct from prediction error minimization, that neither objective requires subtractive coding, that there is clear neurobiological evidence for the amplification of predicted signals, and that we are unconvinced by evidence proposed in support of subtractive coding. We outline recent discoveries showing that pyramidal cells on which our cognitive capabilities depend usually transmit information about input to their basal dendrites and amplify that transmission when input to their distal apical dendrites provides a context that agrees with the feedforward basal input in that both are depolarizing, i.e., both are excitatory rather than inhibitory. Though these intracellular discoveries require a level of technical expertise that is beyond the current abilities of most neuroscience labs, they are not controversial and acclaimed as groundbreaking. We note that this cellular cooperative context-sensitivity greatly enhances the cognitive capabilities of the mammalian neocortex, and that much remains to be discovered concerning its evolution, development, and pathology.
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Affiliation(s)
- Tomáš Marvan
- Institute of Philosophy, Czech Academy of Sciences (CAS), Czech Republic
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18
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Lewis CM, Wunderle T, Fries P. Top-down modulation of visual cortical stimulus encoding and gamma independent of firing rates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.11.589006. [PMID: 38645050 PMCID: PMC11030389 DOI: 10.1101/2024.04.11.589006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Neurons in primary visual cortex integrate sensory input with signals reflecting the animal's internal state to support flexible behavior. Internal variables, such as expectation, attention, or current goals, are imposed in a top-down manner via extensive feedback projections from higher-order areas. We optogenetically activated a high-order visual area, area 21a, in the lightly anesthetized cat (OptoTD), while recording from neuronal populations in V1. OptoTD induced strong, up to several fold, changes in gamma-band synchronization together with much smaller changes in firing rate, and the two effects showed no correlation. OptoTD effects showed specificity for the features of the simultaneously presented visual stimuli. OptoTD-induced changes in gamma synchronization, but not firing rates, were predictive of simultaneous changes in the amount of encoded stimulus information. Our findings suggest that one important role of top-down signals is to modulate synchronization and the information encoded by populations of sensory neurons.
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19
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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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20
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Gowers RP, Schreiber S. How neuronal morphology impacts the synchronisation state of neuronal networks. PLoS Comput Biol 2024; 20:e1011874. [PMID: 38437226 PMCID: PMC10939433 DOI: 10.1371/journal.pcbi.1011874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 03/14/2024] [Accepted: 01/30/2024] [Indexed: 03/06/2024] Open
Abstract
The biophysical properties of neurons not only affect how information is processed within cells, they can also impact the dynamical states of the network. Specifically, the cellular dynamics of action-potential generation have shown relevance for setting the (de)synchronisation state of the network. The dynamics of tonically spiking neurons typically fall into one of three qualitatively distinct types that arise from distinct mathematical bifurcations of voltage dynamics at the onset of spiking. Accordingly, changes in ion channel composition or even external factors, like temperature, have been demonstrated to switch network behaviour via changes in the spike onset bifurcation and hence its associated dynamical type. A thus far less addressed modulator of neuronal dynamics is cellular morphology. Based on simplified and anatomically realistic mathematical neuron models, we show here that the extent of dendritic arborisation has an influence on the neuronal dynamical spiking type and therefore on the (de)synchronisation state of the network. Specifically, larger dendritic trees prime neuronal dynamics for in-phase-synchronised or splayed-out activity in weakly coupled networks, in contrast to cells with otherwise identical properties yet smaller dendrites. Our biophysical insights hold for generic multicompartmental classes of spiking neuron models (from ball-and-stick-type to anatomically reconstructed models) and establish a connection between neuronal morphology and the susceptibility of neural tissue to synchronisation in health and disease.
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Affiliation(s)
- Robert P Gowers
- Institute for Theoretical Biology, Humboldt-University of Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Susanne Schreiber
- Institute for Theoretical Biology, Humboldt-University of Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
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21
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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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22
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Baronig M, Legenstein R. Context association in pyramidal neurons through local synaptic plasticity in apical dendrites. Front Neurosci 2024; 17:1276706. [PMID: 38357522 PMCID: PMC10864492 DOI: 10.3389/fnins.2023.1276706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 12/26/2023] [Indexed: 02/16/2024] Open
Abstract
The unique characteristics of neocortical pyramidal neurons are thought to be crucial for many aspects of information processing and learning in the brain. Experimental data suggests that their segregation into two distinct compartments, the basal dendrites close to the soma and the apical dendrites branching out from the thick apical dendritic tuft, plays an essential role in cortical organization. A recent hypothesis states that layer 5 pyramidal cells associate top-down contextual information arriving at their apical tuft with features of the sensory input that predominantly arrives at their basal dendrites. It has however remained unclear whether such context association could be established by synaptic plasticity processes. In this work, we formalize the objective of such context association learning through a mathematical loss function and derive a plasticity rule for apical synapses that optimizes this loss. The resulting plasticity rule utilizes information that is available either locally at the synapse, through branch-local NMDA spikes, or through global Ca2+events, both of which have been observed experimentally in layer 5 pyramidal cells. We show in computer simulations that the plasticity rule enables pyramidal cells to associate top-down contextual input patterns with high somatic activity. Furthermore, it enables networks of pyramidal neuron models to perform context-dependent tasks and enables continual learning by allocating new dendritic branches to novel contexts.
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Affiliation(s)
| | - Robert Legenstein
- Institute of Theoretical Computer Science, Graz University of Technology, Graz, Austria
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23
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Friedenberger Z, Naud R. Dendritic excitability controls overdispersion. NATURE COMPUTATIONAL SCIENCE 2024; 4:19-28. [PMID: 38177495 DOI: 10.1038/s43588-023-00580-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 11/29/2023] [Indexed: 01/06/2024]
Abstract
The brain is an intricate assembly of intercommunicating neurons whose input-output function is only partially understood. The role of active dendrites in shaping spiking responses, in particular, is unclear. Although existing models account for active dendrites and spiking responses, they are too complex to analyze analytically and demand long stochastic simulations. Here we combine cable and renewal theory to describe how input fluctuations shape the response of neuronal ensembles with active dendrites. We found that dendritic input readily and potently controls interspike interval dispersion. This phenomenon can be understood by considering that neurons display three fundamental operating regimes: one mean-driven regime and two fluctuation-driven regimes. We show that these results are expected to appear for a wide range of dendritic properties and verify predictions of the model in experimental data. These findings have implications for the role of interspike interval dispersion in learning and for theories of attractor states.
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Affiliation(s)
- Zachary Friedenberger
- Centre for Neural Dynamics and Artificial Intelligence, University of Ottawa, Ottawa, Ontario, Canada
- Department of Physics, University of Ottawa, Ottawa, Ontario, Canada
| | - Richard Naud
- Centre for Neural Dynamics and Artificial Intelligence, University of Ottawa, Ottawa, Ontario, Canada.
- Department of Physics, University of Ottawa, Ottawa, Ontario, Canada.
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada.
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24
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Kenwood MM, Souaiaia T, Kovner R, Fox AS, French DA, Oler JA, Roseboom PH, Riedel MK, Mueller SAL, Kalin NH. Gene expression in the primate orbitofrontal cortex related to anxious temperament. Proc Natl Acad Sci U S A 2023; 120:e2305775120. [PMID: 38011550 DOI: 10.1073/pnas.2305775120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 10/13/2023] [Indexed: 11/29/2023] Open
Abstract
Anxiety disorders are among the most prevalent psychiatric disorders, causing significant suffering and disability. Relative to other psychiatric disorders, anxiety disorders tend to emerge early in life, supporting the importance of developmental mechanisms in their emergence and maintenance. Behavioral inhibition (BI) is a temperament that emerges early in life and, when stable and extreme, is linked to an increased risk for the later development of anxiety disorders and other stress-related psychopathology. Understanding the neural systems and molecular mechanisms underlying this dispositional risk could provide insight into treatment targets for anxiety disorders. Nonhuman primates (NHPs) have an anxiety-related temperament, called anxious temperament (AT), that is remarkably similar to BI in humans, facilitating the design of highly translational models for studying the early risk for stress-related psychopathology. Because of the recent evolutionary divergence between humans and NHPs, many of the anxiety-related brain regions that contribute to psychopathology are highly similar in terms of their structure and function, particularly with respect to the prefrontal cortex. The orbitofrontal cortex plays a critical role in the flexible encoding and regulation of threat responses, in part through connections with subcortical structures like the amygdala. Here, we explore individual differences in the transcriptional profile of cells within the region, using laser capture microdissection and single nuclear sequencing, providing insight into the molecules underlying individual differences in AT-related function of the pOFC, with a particular focus on previously implicated cellular systems, including neurotrophins and glucocorticoid signaling.
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Affiliation(s)
- Margaux M Kenwood
- Neuroscience Training Program, University of Wisconsin, Madison, WI 53705
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | - Tade Souaiaia
- Department of Cell Biology, State University of New York Downstate, New York, NY 11228
| | - Rothem Kovner
- Yale School of Medicine, Yale University, New Haven, CT 06510
| | - Andrew S Fox
- Department of Psychology and California National Primate Research Center, University of California, Davis, CA 95616
| | - Delores A French
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | - Jonathan A Oler
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | | | - Marissa K Riedel
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | | | - Ned H Kalin
- Neuroscience Training Program, University of Wisconsin, Madison, WI 53705
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
- Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53715
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25
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Schiff ND, Giacino JT, Butson CR, Choi EY, Baker JL, O'Sullivan KP, Janson AP, Bergin M, Bronte-Stewart HM, Chua J, DeGeorge L, Dikmen S, Fogarty A, Gerber LM, Krel M, Maldonado J, Radovan M, Shah SA, Su J, Temkin N, Tourdias T, Victor JD, Waters A, Kolakowsky-Hayner SA, Fins JJ, Machado AG, Rutt BK, Henderson JM. Thalamic deep brain stimulation in traumatic brain injury: a phase 1, randomized feasibility study. Nat Med 2023; 29:3162-3174. [PMID: 38049620 PMCID: PMC11087147 DOI: 10.1038/s41591-023-02638-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 10/10/2023] [Indexed: 12/06/2023]
Abstract
Converging evidence indicates that impairments in executive function and information-processing speed limit quality of life and social reentry after moderate-to-severe traumatic brain injury (msTBI). These deficits reflect dysfunction of frontostriatal networks for which the central lateral (CL) nucleus of the thalamus is a critical node. The primary objective of this feasibility study was to test the safety and efficacy of deep brain stimulation within the CL and the associated medial dorsal tegmental (CL/DTTm) tract.Six participants with msTBI, who were between 3 and 18 years post-injury, underwent surgery with electrode placement guided by imaging and subject-specific biophysical modeling to predict activation of the CL/DTTm tract. The primary efficacy measure was improvement in executive control indexed by processing speed on part B of the trail-making test.All six participants were safely implanted. Five participants completed the study and one was withdrawn for protocol non-compliance. Processing speed on part B of the trail-making test improved 15% to 52% from baseline, exceeding the 10% benchmark for improvement in all five cases.CL/DTTm deep brain stimulation can be safely applied and may improve executive control in patients with msTBI who are in the chronic phase of recovery.ClinicalTrials.gov identifier: NCT02881151 .
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Affiliation(s)
- Nicholas D Schiff
- Feil Family Brain Mind Institute, Weill Cornell Medicine, New York, NY, USA.
- Department of Neurology, Weill Cornell Medicine, New York, NY, USA.
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Boston, MA, USA
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA, USA
| | - Christopher R Butson
- Scientific Computing and Imaging Institute Department of Bioengineering, University of Utah, Salt Lake City, UT, USA
- Norman Fixel Institute for Neurological Diseases Departments of Neurology and Neurosurgery, University of Florida, Gainesville, FL, USA
| | - Eun Young Choi
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Jonathan L Baker
- Feil Family Brain Mind Institute, Weill Cornell Medicine, New York, NY, USA
| | - Kyle P O'Sullivan
- Scientific Computing and Imaging Institute Department of Bioengineering, University of Utah, Salt Lake City, UT, USA
| | - Andrew P Janson
- Scientific Computing and Imaging Institute Department of Bioengineering, University of Utah, Salt Lake City, UT, USA
- Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA
| | - Michael Bergin
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Boston, MA, USA
| | | | - Jason Chua
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Laurel DeGeorge
- Feil Family Brain Mind Institute, Weill Cornell Medicine, New York, NY, USA
| | - Sureyya Dikmen
- Department of Rehabilitation Medicine, University of Washington, Seattle, WA, USA
| | - Adam Fogarty
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Linda M Gerber
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Mark Krel
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Jose Maldonado
- Department of Psychiatry, Stanford University, Stanford, CA, USA
| | - Matthew Radovan
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Sudhin A Shah
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Jason Su
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Nancy Temkin
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - Thomas Tourdias
- Department of Neuroimaging, University of Bordeaux, Nouvelle-Aquitaine, France
| | - Jonathan D Victor
- Feil Family Brain Mind Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Abigail Waters
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Boston, MA, USA
| | | | - Joseph J Fins
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Andre G Machado
- Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Brian K Rutt
- Department of Radiology, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Bio-X Program, Stanford University, Stanford, CA, USA
| | - Jaimie M Henderson
- Department of Neurosurgery, Stanford University, Stanford, CA, USA.
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
- Bio-X Program, Stanford University, Stanford, CA, USA.
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26
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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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27
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Bhaskaran AA, Gauvrit T, Vyas Y, Bony G, Ginger M, Frick A. Endogenous noise of neocortical neurons correlates with atypical sensory response variability in the Fmr1 -/y mouse model of autism. Nat Commun 2023; 14:7905. [PMID: 38036566 PMCID: PMC10689491 DOI: 10.1038/s41467-023-43777-z] [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: 02/10/2023] [Accepted: 11/20/2023] [Indexed: 12/02/2023] Open
Abstract
Excessive neural variability of sensory responses is a hallmark of atypical sensory processing in autistic individuals with cascading effects on other core autism symptoms but unknown neurobiological substrate. Here, by recording neocortical single neuron activity in a well-established mouse model of Fragile X syndrome and autism, we characterized atypical sensory processing and probed the role of endogenous noise sources in exaggerated response variability in males. The analysis of sensory stimulus evoked activity and spontaneous dynamics, as well as neuronal features, reveals a complex cellular and network phenotype. Neocortical sensory information processing is more variable and temporally imprecise. Increased trial-by-trial and inter-neuronal response variability is strongly related to key endogenous noise features, and may give rise to behavioural sensory responsiveness variability in autism. We provide a novel preclinical framework for understanding the sources of endogenous noise and its contribution to core autism symptoms, and for testing the functional consequences for mechanism-based manipulation of noise.
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Affiliation(s)
- Arjun A Bhaskaran
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Théo Gauvrit
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Yukti Vyas
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Guillaume Bony
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Melanie Ginger
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Andreas Frick
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France.
- University of Bordeaux, 33000, Bordeaux, France.
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28
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Li M, Eltabbal M, Tran HD, Kuhn B. Scn2a insufficiency alters spontaneous neuronal Ca 2+ activity in somatosensory cortex during wakefulness. iScience 2023; 26:108138. [PMID: 37876801 PMCID: PMC10590963 DOI: 10.1016/j.isci.2023.108138] [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: 04/17/2023] [Revised: 07/22/2023] [Accepted: 10/02/2023] [Indexed: 10/26/2023] Open
Abstract
SCN2A protein-truncating variants (PTV) can result in neurological disorders such as autism spectrum disorder and intellectual disability, but they are less likely to cause epilepsy in comparison to missense variants. While in vitro studies showed PTV reduce action potential firing, consequences at in vivo network level remain elusive. Here, we generated a mouse model of Scn2a insufficiency using antisense oligonucleotides (Scn2a ASO mice), which recapitulated key clinical feature of SCN2A PTV disorders. Simultaneous two-photon Ca2+ imaging and electrocorticography (ECoG) in awake mice showed that spontaneous Ca2+ transients in somatosensory cortical neurons, as well as their pairwise co-activities were generally decreased in Scn2a ASO mice during spontaneous awake state and induced seizure state. The reduction of neuronal activities and paired co-activity are mechanisms associated with motor, social and cognitive deficits observed in our mouse model of severe Scn2a insufficiency, indicating these are likely mechanisms driving SCN2A PTV pathology.
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Affiliation(s)
- Melody Li
- Optical Neuroimaging Unit, Okinawa Institute of Science and Technology Graduate University (OIST), 1919-1 Tancha, Onna-son, Okinawa 904-0495, Japan
| | - Mohamed Eltabbal
- Optical Neuroimaging Unit, Okinawa Institute of Science and Technology Graduate University (OIST), 1919-1 Tancha, Onna-son, Okinawa 904-0495, Japan
| | - Hoang-Dai Tran
- Optical Neuroimaging Unit, Okinawa Institute of Science and Technology Graduate University (OIST), 1919-1 Tancha, Onna-son, Okinawa 904-0495, Japan
| | - Bernd Kuhn
- Optical Neuroimaging Unit, Okinawa Institute of Science and Technology Graduate University (OIST), 1919-1 Tancha, Onna-son, Okinawa 904-0495, Japan
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29
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Arnaudon A, Reva M, Zbili M, Markram H, Van Geit W, Kanari L. Controlling morpho-electrophysiological variability of neurons with detailed biophysical models. iScience 2023; 26:108222. [PMID: 37953946 PMCID: PMC10638024 DOI: 10.1016/j.isci.2023.108222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/21/2023] [Accepted: 10/12/2023] [Indexed: 11/14/2023] Open
Abstract
Variability, which is known to be a universal feature among biological units such as neuronal cells, holds significant importance, as, for example, it enables a robust encoding of a high volume of information in neuronal circuits and prevents hypersynchronizations. While most computational studies on electrophysiological variability in neuronal circuits were done with single-compartment neuron models, we instead focus on the variability of detailed biophysical models of neuron multi-compartmental morphologies. We leverage a Markov chain Monte Carlo method to generate populations of electrical models reproducing the variability of experimental recordings while being compatible with a set of morphologies to faithfully represent specifi morpho-electrical type. We demonstrate our approach on layer 5 pyramidal cells and study the morpho-electrical variability and in particular, find that morphological variability alone is insufficient to reproduce electrical variability. Overall, this approach provides a strong statistical basis to create detailed models of neurons with controlled variability.
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Affiliation(s)
- Alexis Arnaudon
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Maria Reva
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Mickael Zbili
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Henry Markram
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Werner Van Geit
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Lida Kanari
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
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30
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Munn BR, Müller EJ, Aru J, Whyte CJ, Gidon A, Larkum ME, Shine JM. A thalamocortical substrate for integrated information via critical synchronous bursting. Proc Natl Acad Sci U S A 2023; 120:e2308670120. [PMID: 37939085 PMCID: PMC10655573 DOI: 10.1073/pnas.2308670120] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 09/21/2023] [Indexed: 11/10/2023] Open
Abstract
Understanding the neurobiological mechanisms underlying consciousness remains a significant challenge. Recent evidence suggests that the coupling between distal-apical and basal-somatic dendrites in thick-tufted layer 5 pyramidal neurons (L5PN), regulated by the nonspecific-projecting thalamus, is crucial for consciousness. Yet, it is uncertain whether this thalamocortical mechanism can support emergent signatures of consciousness, such as integrated information. To address this question, we constructed a biophysical network of dual-compartment thick-tufted L5PN, with dendrosomatic coupling controlled by thalamic inputs. Our findings demonstrate that integrated information is maximized when nonspecific thalamic inputs drive the system into a regime of time-varying synchronous bursting. Here, the system exhibits variable spiking dynamics with broad pairwise correlations, supporting the enhanced integrated information. Further, the observed peak in integrated information aligns with criticality signatures and empirically observed layer 5 pyramidal bursting rates. These results suggest that the thalamocortical core of the mammalian brain may be evolutionarily configured to optimize effective information processing, providing a potential neuronal mechanism that integrates microscale theories with macroscale signatures of consciousness.
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Affiliation(s)
- Brandon R. Munn
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney2050, Australia
- Complex Systems, School of Physics, Faculty of Science, University of Sydney, Sydney2050, Australia
| | - Eli J. Müller
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney2050, Australia
- Complex Systems, School of Physics, Faculty of Science, University of Sydney, Sydney2050, Australia
| | - Jaan Aru
- Institute of Computer Science, University of Tartu, Tartu51009, Estonia
| | - Christopher J. Whyte
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney2050, Australia
- Complex Systems, School of Physics, Faculty of Science, University of Sydney, Sydney2050, Australia
| | - Albert Gidon
- Institute of Biology, Humboldt University of Berlin, Berlin10099, Germany
- NeuroCure Center of Excellence, Charité Universitätsmedizin Berlin, Berlin10099, Germany
| | - Matthew E. Larkum
- Institute of Biology, Humboldt University of Berlin, Berlin10099, Germany
- NeuroCure Center of Excellence, Charité Universitätsmedizin Berlin, Berlin10099, Germany
| | - James M. Shine
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney2050, Australia
- Complex Systems, School of Physics, Faculty of Science, University of Sydney, Sydney2050, Australia
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31
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Pisciottani A, Croci L, Lauria F, Marullo C, Savino E, Ambrosi A, Podini P, Marchioretto M, Casoni F, Cremona O, Taverna S, Quattrini A, Cioni JM, Viero G, Codazzi F, Consalez GG. Neuronal models of TDP-43 proteinopathy display reduced axonal translation, increased oxidative stress, and defective exocytosis. Front Cell Neurosci 2023; 17:1253543. [PMID: 38026702 PMCID: PMC10679756 DOI: 10.3389/fncel.2023.1253543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 10/13/2023] [Indexed: 12/01/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a progressive, lethal neurodegenerative disease mostly affecting people around 50-60 years of age. TDP-43, an RNA-binding protein involved in pre-mRNA splicing and controlling mRNA stability and translation, forms neuronal cytoplasmic inclusions in an overwhelming majority of ALS patients, a phenomenon referred to as TDP-43 proteinopathy. These cytoplasmic aggregates disrupt mRNA transport and localization. The axon, like dendrites, is a site of mRNA translation, permitting the local synthesis of selected proteins. This is especially relevant in upper and lower motor neurons, whose axon spans long distances, likely accentuating their susceptibility to ALS-related noxae. In this work we have generated and characterized two cellular models, consisting of virtually pure populations of primary mouse cortical neurons expressing a human TDP-43 fusion protein, wt or carrying an ALS mutation. Both forms facilitate cytoplasmic aggregate formation, unlike the corresponding native proteins, giving rise to bona fide primary culture models of TDP-43 proteinopathy. Neurons expressing TDP-43 fusion proteins exhibit a global impairment in axonal protein synthesis, an increase in oxidative stress, and defects in presynaptic function and electrical activity. These changes correlate with deregulation of axonal levels of polysome-engaged mRNAs playing relevant roles in the same processes. Our data support the emerging notion that deregulation of mRNA metabolism and of axonal mRNA transport may trigger the dying-back neuropathy that initiates motor neuron degeneration in ALS.
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Affiliation(s)
- Alessandra Pisciottani
- Faculty of Medicine and Surgery, Università Vita-Salute San Raffaele, Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Laura Croci
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Fabio Lauria
- Institute of Biophysics, CNR Unit at Trento, Povo, Italy
| | - Chiara Marullo
- Faculty of Medicine and Surgery, Università Vita-Salute San Raffaele, Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisa Savino
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Ambrosi
- Faculty of Medicine and Surgery, Università Vita-Salute San Raffaele, Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paola Podini
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Filippo Casoni
- Faculty of Medicine and Surgery, Università Vita-Salute San Raffaele, Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Ottavio Cremona
- Faculty of Medicine and Surgery, Università Vita-Salute San Raffaele, Milan, Italy
| | - Stefano Taverna
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Angelo Quattrini
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Jean-Michel Cioni
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Franca Codazzi
- Faculty of Medicine and Surgery, Università Vita-Salute San Raffaele, Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - G. Giacomo Consalez
- Faculty of Medicine and Surgery, Università Vita-Salute San Raffaele, Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
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32
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Francioni V, Tang VD, Brown NJ, Toloza EH, Harnett M. Vectorized instructive signals in cortical dendrites during a brain-computer interface task. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.03.565534. [PMID: 37961227 PMCID: PMC10635122 DOI: 10.1101/2023.11.03.565534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Backpropagation of error is the most widely used learning algorithm in artificial neural networks, forming the backbone of modern machine learning and artificial intelligence1,2. Backpropagation provides a solution to the credit assignment problem by vectorizing an error signal tailored to individual neurons. Recent theoretical models have suggested that neural circuits could implement backpropagation-like learning by semi-independently processing feedforward and feedback information streams in separate dendritic compartments3-7. This presents a compelling, but untested, hypothesis for how cortical circuits could solve credit assignment in the brain. We designed a neurofeedback brain-computer interface (BCI) task with an experimenter-defined reward function to evaluate the key requirements for dendrites to implement backpropagation-like learning. We trained mice to modulate the activity of two spatially intermingled populations (4 or 5 neurons each) of layer 5 pyramidal neurons in the retrosplenial cortex to rotate a visual grating towards a target orientation while we recorded GCaMP activity from somas and corresponding distal apical dendrites. We observed that the relative magnitudes of somatic versus dendritic signals could be predicted using the activity of the surrounding network and contained information about task-related variables that could serve as instructive signals, including reward and error. The signs of these putative teaching signals both depended on the causal role of individual neurons in the task and predicted changes in overall activity over the course of learning. These results provide the first biological evidence of a backpropagation-like solution to the credit assignment problem in the brain.
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Affiliation(s)
- Valerio Francioni
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Vincent D Tang
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Norma J. Brown
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Enrique H.S. Toloza
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Mark Harnett
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
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33
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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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34
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Argunsah AÖ, Israely I. Homosynaptic plasticity induction causes heterosynaptic changes at the unstimulated neighbors in an induction pattern and location-specific manner. Front Cell Neurosci 2023; 17:1253446. [PMID: 37829671 PMCID: PMC10564986 DOI: 10.3389/fncel.2023.1253446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 08/24/2023] [Indexed: 10/14/2023] Open
Abstract
Dendritic spines are highly dynamic structures whose structural and functional fluctuations depend on multiple factors. Changes in synaptic strength are not limited to synapses directly involved in specific activity patterns. Unstimulated clusters of neighboring spines in and around the site of stimulation can also undergo alterations in strength. Usually, when plasticity is induced at single dendritic spines with glutamate uncaging, neighboring spines do not show any significant structural fluctuations. Here, using two-photon imaging and glutamate uncaging at single dendritic spines of hippocampal pyramidal neurons, we show that structural modifications at unstimulated neighboring spines occur and are a function of the temporal pattern of the plasticity-inducing stimulus. Further, the relative location of the unstimulated neighbors within the local dendritic segment correlates with the extent of heterosynaptic plasticity that is observed. These findings indicate that naturalistic patterns of activity at single spines can shape plasticity at nearby clusters of synapses, and may play a role in priming local inputs for further modifications.
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Affiliation(s)
- Ali Özgür Argunsah
- Laboratory of Neuronal Circuit Assembly, Brain Research Institute (HiFo), University of Zurich, Zurich, Switzerland
- Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, Türkiye
| | - Inbal Israely
- Department of Physiology and Biophysics, University of Washington School of Medicine, Seattle, WA, United States
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35
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Benjamin AS, Kording KP. A role for cortical interneurons as adversarial discriminators. PLoS Comput Biol 2023; 19:e1011484. [PMID: 37768890 PMCID: PMC10538760 DOI: 10.1371/journal.pcbi.1011484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 08/31/2023] [Indexed: 09/30/2023] Open
Abstract
The brain learns representations of sensory information from experience, but the algorithms by which it does so remain unknown. One popular theory formalizes representations as inferred factors in a generative model of sensory stimuli, meaning that learning must improve this generative model and inference procedure. This framework underlies many classic computational theories of sensory learning, such as Boltzmann machines, the Wake/Sleep algorithm, and a more recent proposal that the brain learns with an adversarial algorithm that compares waking and dreaming activity. However, in order for such theories to provide insights into the cellular mechanisms of sensory learning, they must be first linked to the cell types in the brain that mediate them. In this study, we examine whether a subtype of cortical interneurons might mediate sensory learning by serving as discriminators, a crucial component in an adversarial algorithm for representation learning. We describe how such interneurons would be characterized by a plasticity rule that switches from Hebbian plasticity during waking states to anti-Hebbian plasticity in dreaming states. Evaluating the computational advantages and disadvantages of this algorithm, we find that it excels at learning representations in networks with recurrent connections but scales poorly with network size. This limitation can be partially addressed if the network also oscillates between evoked activity and generative samples on faster timescales. Consequently, we propose that an adversarial algorithm with interneurons as discriminators is a plausible and testable strategy for sensory learning in biological systems.
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Affiliation(s)
- Ari S. Benjamin
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Konrad P. Kording
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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36
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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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Zhang K, Yang Z, Gaffield MA, Gross GG, Arnold DB, Christie JM. Molecular layer disinhibition unlocks climbing-fiber-instructed motor learning in the cerebellum. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.04.552059. [PMID: 38654827 PMCID: PMC11037867 DOI: 10.1101/2023.08.04.552059] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Climbing fibers supervise cerebellar learning by providing signals to Purkinje cells (PCs) that instruct adaptive changes to mistakenly performed movements. Yet, climbing fibers are regularly active, even during well performed movements, suggesting that a mechanism dynamically regulates the ability of climbing fibers to induce corrective plasticity in response to motor errors. We found that molecular layer interneurons (MLIs), whose inhibition of PCs powerfully opposes climbing-fiber-mediated excitation, serve this function. Optogenetically suppressing the activity of floccular MLIs in mice during the vestibulo-ocular reflex (VOR) induces a learned increase in gain despite the absence of performance errors. Suppressing MLIs when the VOR is mistakenly underperformed reveled that their inhibitory output is necessary to orchestrate gain-increase learning by conditionally permitting climbing fibers to instruct plasticity induction during ipsiversive head turns. Ablation of an MLI circuit for PC disinhibition prevents gain-increase learning during VOR performance errors which was rescued by re-imposing PC disinhibition through MLI activity suppression. Our findings point to a decisive role for MLIs in gating climbing-fiber-mediated learning through their context-dependent inhibition of PCs.
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38
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Levenstein D, Okun M. Logarithmically scaled, gamma distributed neuronal spiking. J Physiol 2023; 601:3055-3069. [PMID: 36086892 PMCID: PMC10952267 DOI: 10.1113/jp282758] [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: 05/09/2022] [Accepted: 07/28/2022] [Indexed: 11/08/2022] Open
Abstract
Naturally log-scaled quantities abound in the nervous system. Distributions of these quantities have non-intuitive properties, which have implications for data analysis and the understanding of neural circuits. Here, we review the log-scaled statistics of neuronal spiking and the relevant analytical probability distributions. Recent work using log-scaling revealed that interspike intervals of forebrain neurons segregate into discrete modes reflecting spiking at different timescales and are each well-approximated by a gamma distribution. Each neuron spends most of the time in an irregular spiking 'ground state' with the longest intervals, which determines the mean firing rate of the neuron. Across the entire neuronal population, firing rates are log-scaled and well approximated by the gamma distribution, with a small number of highly active neurons and an overabundance of low rate neurons (the 'dark matter'). These results are intricately linked to a heterogeneous balanced operating regime, which confers upon neuronal circuits multiple computational advantages and has evolutionarily ancient origins.
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Affiliation(s)
- Daniel Levenstein
- Department of Neurology and NeurosurgeryMcGill UniversityMontrealQCCanada
- MilaMontréalQCCanada
| | - Michael Okun
- Department of Psychology and Neuroscience InstituteUniversity of SheffieldSheffieldUK
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Meszéna D, Barlay A, Boldog P, Furuglyás K, Cserpán D, Wittner L, Ulbert I, Somogyvári Z. Seeing beyond the spikes: reconstructing the complete spatiotemporal membrane potential distribution from paired intra- and extracellular recordings. J Physiol 2023; 601:3351-3376. [PMID: 36511176 DOI: 10.1113/jp283550] [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: 06/30/2022] [Accepted: 11/28/2022] [Indexed: 12/15/2022] Open
Abstract
Although electrophysiologists have been recording intracellular neural activity routinely ever since the ground-breaking work of Hodgkin and Huxley, and extracellular multichannel electrodes have also been used frequently and extensively, a practical experimental method to track changes in membrane potential along a complete single neuron is still lacking. Instead of obtaining multiple intracellular measurements on the same neuron, we propose an alternative method by combining single-channel somatic patch-clamp and multichannel extracellular potential recordings. In this work, we show that it is possible to reconstruct the complete spatiotemporal distribution of the membrane potential of a single neuron with the spatial resolution of an extracellular probe during action potential generation. Moreover, the reconstruction of the membrane potential allows us to distinguish between the two major but previously hidden components of the current source density (CSD) distribution: the resistive and the capacitive currents. This distinction provides a clue to the clear interpretation of the CSD analysis, because the resistive component corresponds to transmembrane ionic currents (all the synaptic, voltage-sensitive and passive currents), whereas capacitive currents are considered to be the main contributors of counter-currents. We validate our model-based reconstruction approach on simulations and demonstrate its application to experimental data obtained in vitro via paired extracellular and intracellular recordings from a single pyramidal cell of the rat hippocampus. In perspective, the estimation of the spatial distribution of resistive membrane currents makes it possible to distiguish between active and passive sinks and sources of the CSD map and the localization of the synaptic input currents, which make the neuron fire. KEY POINTS: A new computational method is introduced to calculate the unbiased current source density distribution on a single neuron with known morphology. The relationship between extracellular and intracellular electric potential is determined via mathematical formalism, and a new reconstruction method is applied to reveal the full spatiotemporal distribution of the membrane potential and the resistive and capacitive current components. The new reconstruction method was validated on simulations. Simultaneous and colocalized whole-cell patch-clamp and multichannel silicon probe recordings were performed from the same pyramidal neuron in the rat hippocampal CA1 region, in vitro. The method was applied in experimental measurements and returned precise and distinctive characteristics of various intracellular phenomena, such as action potential generation, signal back-propagation and the initial dendritic depolarization preceding the somatic action potential.
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Affiliation(s)
- Domokos Meszéna
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Anna Barlay
- Theoretical Neuroscience and Complex Systems Research Group, Department of Computational Sciences, Wigner Research Center for Physics, Budapest, Hungary
- Bolyai Institute, University of Szeged, Szeged, Hungary
| | - Péter Boldog
- Theoretical Neuroscience and Complex Systems Research Group, Department of Computational Sciences, Wigner Research Center for Physics, Budapest, Hungary
- Bolyai Institute, University of Szeged, Szeged, Hungary
| | - Kristóf Furuglyás
- Theoretical Neuroscience and Complex Systems Research Group, Department of Computational Sciences, Wigner Research Center for Physics, Budapest, Hungary
- Doctoral School of Physics, Faculty of Science, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Dorottya Cserpán
- Theoretical Neuroscience and Complex Systems Research Group, Department of Computational Sciences, Wigner Research Center for Physics, Budapest, Hungary
| | - Lucia Wittner
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- National Institute of Clinical Neurosciences, Budapest, Hungary
| | - István Ulbert
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Zoltán Somogyvári
- Theoretical Neuroscience and Complex Systems Research Group, Department of Computational Sciences, Wigner Research Center for Physics, Budapest, Hungary
- Axoncord LLC, Budapest, Hungary
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40
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Kastellakis G, Tasciotti S, Pandi I, Poirazi P. The dendritic engram. Front Behav Neurosci 2023; 17:1212139. [PMID: 37576932 PMCID: PMC10412934 DOI: 10.3389/fnbeh.2023.1212139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 07/11/2023] [Indexed: 08/15/2023] Open
Abstract
Accumulating evidence from a wide range of studies, including behavioral, cellular, molecular and computational findings, support a key role of dendrites in the encoding and recall of new memories. Dendrites can integrate synaptic inputs in non-linear ways, provide the substrate for local protein synthesis and facilitate the orchestration of signaling pathways that regulate local synaptic plasticity. These capabilities allow them to act as a second layer of computation within the neuron and serve as the fundamental unit of plasticity. As such, dendrites are integral parts of the memory engram, namely the physical representation of memories in the brain and are increasingly studied during learning tasks. Here, we review experimental and computational studies that support a novel, dendritic view of the memory engram that is centered on non-linear dendritic branches as elementary memory units. We highlight the potential implications of dendritic engrams for the learning and memory field and discuss future research directions.
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Affiliation(s)
- George Kastellakis
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Heraklion, Greece
| | - Simone Tasciotti
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Heraklion, Greece
- Department of Biology, University of Crete, Heraklion, Greece
| | - Ioanna Pandi
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Heraklion, Greece
- Department of Biology, University of Crete, Heraklion, Greece
| | - Panayiota Poirazi
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Heraklion, Greece
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41
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Graham RT, Parrish RR, Alberio L, Johnson EL, Owens L, Trevelyan AJ. Optogenetic stimulation reveals a latent tipping point in cortical networks during ictogenesis. Brain 2023; 146:2814-2827. [PMID: 36572952 PMCID: PMC10316782 DOI: 10.1093/brain/awac487] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 11/17/2022] [Accepted: 12/06/2022] [Indexed: 12/28/2022] Open
Abstract
Brain-state transitions are readily apparent from changes in brain rhythms,1 but are difficult to predict, suggestive that the underlying cause is latent to passive recording methods. Among the most important transitions, clinically, are the starts of seizures. We here show that an 'active probing' approach may have several important benefits for epileptic management, including by helping predict these transitions. We used mice expressing the optogenetic actuator, channelrhodopsin, in pyramidal cells, allowing this population to be stimulated in isolation. Intermittent stimulation at frequencies as low as 0.033 Hz (period = 30 s) delayed the onset of seizure-like events in an acute brain slice model of ictogenesis, but the effect was lost if stimulation was delivered at even lower frequencies (1/min). Notably, active probing additionally provides advance indication of when seizure-like activity is imminent, revealed by monitoring the postsynaptic response to stimulation. The postsynaptic response, recorded extracellularly, showed an all-or-nothing change in both amplitude and duration, a few hundred seconds before seizure-like activity began-a sufficient length of time to provide a helpful warning of an impending seizure. The change in the postsynaptic response then persisted for the remainder of the recording, indicative of a state change from a pre-epileptic to a pro-epileptic network. This occurred in parallel with a large increase in the stimulation-triggered Ca2+ entry into pyramidal dendrites, and a step increase in the number of evoked postsynaptic action potentials, both consistent with a reduction in the threshold for dendritic action potentials. In 0 Mg2+ bathing media, the reduced threshold was not associated with changes in glutamatergic synaptic function, nor of GABAergic release from either parvalbumin or somatostatin interneurons, but simulations indicate that the step change in the optogenetic response can instead arise from incremental increases in intracellular [Cl-]. The change in the response to stimulation was replicated by artificially raising intracellular [Cl-], using the optogenetic chloride pump, halorhodopsin. By contrast, increases in extracellular [K+] cannot account for the firing patterns in the response to stimulation, although this, and other cellular changes, may contribute to ictal initiation in other circumstances. We describe how these various cellular changes form a synergistic network of positive feedback mechanisms, which may explain the precipitous nature of seizure onset. This model of seizure initiation draws together several major lines of epilepsy research as well as providing an important proof-of-principle regarding the utility of open-loop brain stimulation for clinical management of the condition.
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Affiliation(s)
- Robert T Graham
- Medical School, Newcastle University Biosciences Institute, Framlington Place, Newcastle upon Tyne NE2 4HH, UK
| | - R Ryley Parrish
- Medical School, Newcastle University Biosciences Institute, Framlington Place, Newcastle upon Tyne NE2 4HH, UK
| | - Laura Alberio
- Medical School, Newcastle University Biosciences Institute, Framlington Place, Newcastle upon Tyne NE2 4HH, UK
| | - Emily L Johnson
- Medical School, Newcastle University Biosciences Institute, Framlington Place, Newcastle upon Tyne NE2 4HH, UK
| | - Laura Owens
- Medical School, Newcastle University Biosciences Institute, Framlington Place, Newcastle upon Tyne NE2 4HH, UK
| | - Andrew J Trevelyan
- Medical School, Newcastle University Biosciences Institute, Framlington Place, Newcastle upon Tyne NE2 4HH, UK
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Yazdanbakhsh A, Barbas H, Zikopoulos B. Sleep spindles in primates: Modeling the effects of distinct laminar thalamocortical connectivity in core, matrix, and reticular thalamic circuits. Netw Neurosci 2023; 7:743-768. [PMID: 37397882 PMCID: PMC10312265 DOI: 10.1162/netn_a_00311] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 03/01/2023] [Indexed: 10/16/2023] Open
Abstract
Sleep spindles are associated with the beginning of deep sleep and memory consolidation and are disrupted in schizophrenia and autism. In primates, distinct core and matrix thalamocortical (TC) circuits regulate sleep spindle activity through communications that are filtered by the inhibitory thalamic reticular nucleus (TRN); however, little is known about typical TC network interactions and the mechanisms that are disrupted in brain disorders. We developed a primate-specific, circuit-based TC computational model with distinct core and matrix loops that can simulate sleep spindles. We implemented novel multilevel cortical and thalamic mixing, and included local thalamic inhibitory interneurons, and direct layer 5 projections of variable density to TRN and thalamus to investigate the functional consequences of different ratios of core and matrix node connectivity contribution to spindle dynamics. Our simulations showed that spindle power in primates can be modulated based on the level of cortical feedback, thalamic inhibition, and engagement of model core versus matrix, with the latter having a greater role in spindle dynamics. The study of the distinct spatial and temporal dynamics of core-, matrix-, and mix-generated sleep spindles establishes a framework to study disruption of TC circuit balance underlying deficits in sleep and attentional gating seen in autism and schizophrenia.
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Affiliation(s)
- Arash Yazdanbakhsh
- Computational Neuroscience and Vision Lab, Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston, MA, USA
| | - Helen Barbas
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston, MA, USA
- Neural Systems Laboratory, Program in Human Physiology, Department of Health Sciences, College of Health and Rehabilitation Sciences (Sargent College), Boston University, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston University, Boston, MA, USA
| | - Basilis Zikopoulos
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston University, Boston, MA, USA
- Human Systems Neuroscience Laboratory, Program in Human Physiology, Department of Health Sciences, College of Health and Rehabilitation Sciences (Sargent College), Boston University, Boston, MA, USA
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43
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Fernandez Pujol C, Blundon EG, Dykstra AR. Laminar specificity of the auditory perceptual awareness negativity: A biophysical modeling study. PLoS Comput Biol 2023; 19:e1011003. [PMID: 37384802 DOI: 10.1371/journal.pcbi.1011003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 06/17/2023] [Indexed: 07/01/2023] Open
Abstract
How perception of sensory stimuli emerges from brain activity is a fundamental question of neuroscience. To date, two disparate lines of research have examined this question. On one hand, human neuroimaging studies have helped us understand the large-scale brain dynamics of perception. On the other hand, work in animal models (mice, typically) has led to fundamental insight into the micro-scale neural circuits underlying perception. However, translating such fundamental insight from animal models to humans has been challenging. Here, using biophysical modeling, we show that the auditory awareness negativity (AAN), an evoked response associated with perception of target sounds in noise, can be accounted for by synaptic input to the supragranular layers of auditory cortex (AC) that is present when target sounds are heard but absent when they are missed. This additional input likely arises from cortico-cortical feedback and/or non-lemniscal thalamic projections and targets the apical dendrites of layer-5 (L5) pyramidal neurons. In turn, this leads to increased local field potential activity, increased spiking activity in L5 pyramidal neurons, and the AAN. The results are consistent with current cellular models of conscious processing and help bridge the gap between the macro and micro levels of perception-related brain activity.
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Affiliation(s)
- Carolina Fernandez Pujol
- Department of Biomedical Engineering, University of Miami, Coral Gables, Florida, United States of America
| | - Elizabeth G Blundon
- Department of Biomedical Engineering, University of Miami, Coral Gables, Florida, United States of America
| | - Andrew R Dykstra
- Department of Biomedical Engineering, University of Miami, Coral Gables, Florida, United States of America
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44
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Schiff ND. Mesocircuit mechanisms in the diagnosis and treatment of disorders of consciousness. Presse Med 2023; 52:104161. [PMID: 36563999 DOI: 10.1016/j.lpm.2022.104161] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 11/14/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
The 'mesocircuit hypothesis' proposes mechanisms underlying the recovery of consciousness following severe brain injuries. The model builds up from a single premise that multifocal brain injuries resulting in coma and subsequent disorders of consciousness produce widespread neuronal death and dysfunction. Considering the general properties of cortical, thalamic, and striatal neurons, a lawful and specific circuit-level mechanism is constructed based on these known anatomical and physiological specializations of neuronal subtypes. The mesocircuit model generates many testable predictions at the mesocircuit, local circuit, and cellular level across multiple cerebral structures to correlate diagnostic measurements and interpret therapeutic interventions. The anterior forebrain mesocircuit is integrally related to the frontal-parietal network, another network demonstrated to show strong correlation with levels of recovery in disorders of consciousness. A further extension known as the "ABCD" model has been used to examine interaction of these models in recovery of consciousness using electrophysiological data types. Many studies have examined predictions of the mesocircuit model; here we first present the model and review the accumulated evidence for several predictions of model across multiple stages of recovery function in human subjects. Recent studies linking the mesocircuit model, the ABCD model, and interactions with the frontoparietal network are reviewed. Finally, theoretical implications of the mesocircuit model at the neuronal level are considered to interpret recent studies of deep brain stimulation in the central lateral thalamus in patients recovering from coma and in new experimental models in the context of emerging understanding of neuronal and local circuit mechanisms underlying conscious brain states.
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Affiliation(s)
- Nicholas D Schiff
- Jerold B. Katz Professor of Neurology and Neuroscience, Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, United States.
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45
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Auksztulewicz R, Rajendran VG, Peng F, Schnupp JWH, Harper NS. Omission responses in local field potentials in rat auditory cortex. BMC Biol 2023; 21:130. [PMID: 37254137 DOI: 10.1186/s12915-023-01592-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 04/11/2023] [Indexed: 06/01/2023] Open
Abstract
BACKGROUND Non-invasive recordings of gross neural activity in humans often show responses to omitted stimuli in steady trains of identical stimuli. This has been taken as evidence for the neural coding of prediction or prediction error. However, evidence for such omission responses from invasive recordings of cellular-scale responses in animal models is scarce. Here, we sought to characterise omission responses using extracellular recordings in the auditory cortex of anaesthetised rats. We profiled omission responses across local field potentials (LFP), analogue multiunit activity (AMUA), and single/multi-unit spiking activity, using stimuli that were fixed-rate trains of acoustic noise bursts where 5% of bursts were randomly omitted. RESULTS Significant omission responses were observed in LFP and AMUA signals, but not in spiking activity. These omission responses had a lower amplitude and longer latency than burst-evoked sensory responses, and omission response amplitude increased as a function of the number of preceding bursts. CONCLUSIONS Together, our findings show that omission responses are most robustly observed in LFP and AMUA signals (relative to spiking activity). This has implications for models of cortical processing that require many neurons to encode prediction errors in their spike output.
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Affiliation(s)
- Ryszard Auksztulewicz
- Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany.
- Dept of Neuroscience, City University of Hong Kong, Hong Kong, Hong Kong S.A.R..
| | | | - Fei Peng
- Dept of Neuroscience, City University of Hong Kong, Hong Kong, Hong Kong S.A.R
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46
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Swindale NV, Spacek MA, Krause M, Mitelut C. Spontaneous activity in cortical neurons is stereotyped and non-Poisson. Cereb Cortex 2023; 33:6508-6525. [PMID: 36708015 PMCID: PMC10233306 DOI: 10.1093/cercor/bhac521] [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: 09/15/2022] [Revised: 12/09/2022] [Accepted: 12/10/2022] [Indexed: 01/29/2023] Open
Abstract
Neurons fire even in the absence of sensory stimulation or task demands. Numerous theoretical studies have modeled this spontaneous activity as a Poisson process with uncorrelated intervals between successive spikes and a variance in firing rate equal to the mean. Experimental tests of this hypothesis have yielded variable results, though most have concluded that firing is not Poisson. However, these tests say little about the ways firing might deviate from randomness. Nor are they definitive because many different distributions can have equal means and variances. Here, we characterized spontaneous spiking patterns in extracellular recordings from monkey, cat, and mouse cerebral cortex neurons using rate-normalized spike train autocorrelation functions (ACFs) and a logarithmic timescale. If activity was Poisson, this function should be flat. This was almost never the case. Instead, ACFs had diverse shapes, often with characteristic peaks in the 1-700 ms range. Shapes were stable over time, up to the longest recording periods used (51 min). They did not fall into obvious clusters. ACFs were often unaffected by visual stimulation, though some abruptly changed during brain state shifts. These behaviors may have their origin in the intrinsic biophysics and dendritic anatomy of the cells or in the inputs they receive.
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Affiliation(s)
- Nicholas V Swindale
- Department of Ophthalmology and Visual Sciences, University of British Columbia, 2550 Willow St., Vancouver, BC V5Z 3N9, Canada
| | - Martin A Spacek
- Division of Neurobiology, Department of Biology II, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Matthew Krause
- Montreal Neurological Institute, McGill University, 3801 University St., Montreal, QC H3A 2B4, Canada
| | - Catalin Mitelut
- Institute of Molecular and Clinical Ophthalmology, University of Basel, Mittlere Strasse 91, CH-4031 Basel, Switzerland
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47
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Aceituno PV, Farinha MT, Loidl R, Grewe BF. Learning cortical hierarchies with temporal Hebbian updates. Front Comput Neurosci 2023; 17:1136010. [PMID: 37293353 PMCID: PMC10244748 DOI: 10.3389/fncom.2023.1136010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 04/25/2023] [Indexed: 06/10/2023] Open
Abstract
A key driver of mammalian intelligence is the ability to represent incoming sensory information across multiple abstraction levels. For example, in the visual ventral stream, incoming signals are first represented as low-level edge filters and then transformed into high-level object representations. Similar hierarchical structures routinely emerge in artificial neural networks (ANNs) trained for object recognition tasks, suggesting that similar structures may underlie biological neural networks. However, the classical ANN training algorithm, backpropagation, is considered biologically implausible, and thus alternative biologically plausible training methods have been developed such as Equilibrium Propagation, Deep Feedback Control, Supervised Predictive Coding, and Dendritic Error Backpropagation. Several of those models propose that local errors are calculated for each neuron by comparing apical and somatic activities. Notwithstanding, from a neuroscience perspective, it is not clear how a neuron could compare compartmental signals. Here, we propose a solution to this problem in that we let the apical feedback signal change the postsynaptic firing rate and combine this with a differential Hebbian update, a rate-based version of classical spiking time-dependent plasticity (STDP). We prove that weight updates of this form minimize two alternative loss functions that we prove to be equivalent to the error-based losses used in machine learning: the inference latency and the amount of top-down feedback necessary. Moreover, we show that the use of differential Hebbian updates works similarly well in other feedback-based deep learning frameworks such as Predictive Coding or Equilibrium Propagation. Finally, our work removes a key requirement of biologically plausible models for deep learning and proposes a learning mechanism that would explain how temporal Hebbian learning rules can implement supervised hierarchical learning.
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Affiliation(s)
- Pau Vilimelis Aceituno
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
- ETH AI Center, ETH Zurich, Zurich, Switzerland
| | | | - Reinhard Loidl
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Benjamin F. Grewe
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
- ETH AI Center, ETH Zurich, Zurich, Switzerland
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48
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Keijser J, Sprekeler H. Cortical interneurons: fit for function and fit to function? Evidence from development and evolution. Front Neural Circuits 2023; 17:1172464. [PMID: 37215503 PMCID: PMC10192557 DOI: 10.3389/fncir.2023.1172464] [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: 02/23/2023] [Accepted: 03/30/2023] [Indexed: 05/24/2023] Open
Abstract
Cortical inhibitory interneurons form a broad spectrum of subtypes. This diversity suggests a division of labor, in which each cell type supports a distinct function. In the present era of optimisation-based algorithms, it is tempting to speculate that these functions were the evolutionary or developmental driving force for the spectrum of interneurons we see in the mature mammalian brain. In this study, we evaluated this hypothesis using the two most common interneuron types, parvalbumin (PV) and somatostatin (SST) expressing cells, as examples. PV and SST interneurons control the activity in the cell bodies and the apical dendrites of excitatory pyramidal cells, respectively, due to a combination of anatomical and synaptic properties. But was this compartment-specific inhibition indeed the function for which PV and SST cells originally evolved? Does the compartmental structure of pyramidal cells shape the diversification of PV and SST interneurons over development? To address these questions, we reviewed and reanalyzed publicly available data on the development and evolution of PV and SST interneurons on one hand, and pyramidal cell morphology on the other. These data speak against the idea that the compartment structure of pyramidal cells drove the diversification into PV and SST interneurons. In particular, pyramidal cells mature late, while interneurons are likely committed to a particular fate (PV vs. SST) during early development. Moreover, comparative anatomy and single cell RNA-sequencing data indicate that PV and SST cells, but not the compartment structure of pyramidal cells, existed in the last common ancestor of mammals and reptiles. Specifically, turtle and songbird SST cells also express the Elfn1 and Cbln4 genes that are thought to play a role in compartment-specific inhibition in mammals. PV and SST cells therefore evolved and developed the properties that allow them to provide compartment-specific inhibition before there was selective pressure for this function. This suggest that interneuron diversity originally resulted from a different evolutionary driving force and was only later co-opted for the compartment-specific inhibition it seems to serve in mammals today. Future experiments could further test this idea using our computational reconstruction of ancestral Elfn1 protein sequences.
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Affiliation(s)
- Joram Keijser
- Modelling of Cognitive Processes, Technical University of Berlin, Berlin, Germany
- Einstein Center for Neurosciences, Charité University Medicine Berlin, Berlin, Germany
| | - Henning Sprekeler
- Modelling of Cognitive Processes, Technical University of Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Humboldt University of Berlin, Berlin, Germany
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49
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Fişek M, Herrmann D, Egea-Weiss A, Cloves M, Bauer L, Lee TY, Russell LE, Häusser M. Cortico-cortical feedback engages active dendrites in visual cortex. Nature 2023; 617:769-776. [PMID: 37138089 DOI: 10.1038/s41586-023-06007-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 03/23/2023] [Indexed: 05/05/2023]
Abstract
Sensory processing in the neocortex requires both feedforward and feedback information flow between cortical areas1. In feedback processing, higher-level representations provide contextual information to lower levels, and facilitate perceptual functions such as contour integration and figure-ground segmentation2,3. However, we have limited understanding of the circuit and cellular mechanisms that mediate feedback influence. Here we use long-range all-optical connectivity mapping in mice to show that feedback influence from the lateromedial higher visual area (LM) to the primary visual cortex (V1) is spatially organized. When the source and target of feedback represent the same area of visual space, feedback is relatively suppressive. By contrast, when the source is offset from the target in visual space, feedback is relatively facilitating. Two-photon calcium imaging data show that this facilitating feedback is nonlinearly integrated in the apical tuft dendrites of V1 pyramidal neurons: retinotopically offset (surround) visual stimuli drive local dendritic calcium signals indicative of regenerative events, and two-photon optogenetic activation of LM neurons projecting to identified feedback-recipient spines in V1 can drive similar branch-specific local calcium signals. Our results show how neocortical feedback connectivity and nonlinear dendritic integration can together form a substrate to support both predictive and cooperative contextual interactions.
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Affiliation(s)
- Mehmet Fişek
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
| | - Dustin Herrmann
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Alexander Egea-Weiss
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Matilda Cloves
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Lisa Bauer
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Tai-Ying Lee
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Lloyd E Russell
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Michael Häusser
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
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Pujol CF, Blundon EG, Dykstra AR. Laminar Specificity of the Auditory Perceptual Awareness Negativity: A Biophysical Modeling Study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023. [PMID: 36945469 PMCID: PMC10028885 DOI: 10.1101/2023.03.06.531459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Abstract
How perception of sensory stimuli emerges from brain activity is a fundamental question of neuroscience. To date, two disparate lines of research have examined this question. On one hand, human neuroimaging studies have helped us understand the large-scale brain dynamics of perception. On the other hand, work in animal models (mice, typically) has led to fundamental insight into the micro-scale neural circuits underlying perception. However, translating such fundamental insight from animal models to humans has been challenging. Here, using biophysical modeling, we show that the auditory awareness negativity (AAN), an evoked response associated with perception of target sounds in noise, can be accounted for by synaptic input to the supragranular layers of auditory cortex (AC) that is present when target sounds are heard but absent when they are missed. This additional input likely arises from cortico-cortical feedback and/or non-lemniscal thalamic projections and targets the apical dendrites of layer-V pyramidal neurons (PNs). In turn, this leads to increased local field potential activity, increased spiking activity in layer-V PNs, and the AAN. The results are consistent with current cellular models of conscious processing and help bridge the gap between the macro and micro levels of perception-related brain activity. Author Summary To date, our understanding of the brain basis of conscious perception has mostly been restricted to large-scale, network-level activity that can be measured non-invasively in human subjects. However, we lack understanding of how such network-level activity is supported by individual neurons and neural circuits. This is at least partially because conscious perception is difficult to study in experimental animals, where such detailed characterization of neural activity is possible. To address this gap, we used biophysical modeling to gain circuit-level insight into an auditory brain response known as the auditory awareness negativity (AAN). This response can be recorded non-invasively in humans and is associated with perceptual awareness of sounds of interest. Our model shows that the AAN likely arises from specific cortical layers and cell types. These data help bridge the gap between circuit- and network-level theories of consciousness, and could lead to new, targeted treatments for perceptual dysfunction and disorders of consciousness.
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