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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] [MESH Headings] [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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2
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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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3
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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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4
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Gonzales DL, Khan HF, Keri HVS, Yadav S, Steward C, Muller LE, Pluta SR, Jayant K. A Translaminar Spacetime Code Supports Touch-Evoked Traveling Waves. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.09.593381. [PMID: 38766232 PMCID: PMC11100787 DOI: 10.1101/2024.05.09.593381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Linking sensory-evoked traveling waves to underlying circuit patterns is critical to understanding the neural basis of sensory perception. To form this link, we performed simultaneous electrophysiology and two-photon calcium imaging through transparent NeuroGrids and mapped touch-evoked cortical traveling waves and their underlying microcircuit dynamics. In awake mice, both passive and active whisker touch elicited traveling waves within and across barrels, with a fast early component followed by a variable late wave that lasted hundreds of milliseconds post-stimulus. Strikingly, late-wave dynamics were modulated by stimulus value and correlated with task performance. Mechanistically, the late wave component was i) modulated by motor feedback, ii) complemented by a sparse ensemble pattern across layer 2/3, which a balanced-state network model reconciled via inhibitory stabilization, and iii) aligned to regenerative Layer-5 apical dendritic Ca 2+ events. Our results reveal a translaminar spacetime pattern organized by cortical feedback in the sensory cortex that supports touch-evoked traveling waves. GRAPHICAL ABSTRACT AND HIGHLIGHTS Whisker touch evokes both early- and late-traveling waves in the barrel cortex over 100's of millisecondsReward reinforcement modulates wave dynamics Late wave emergence coincides with network sparsity in L23 and time-locked L5 dendritic Ca 2+ spikes Experimental and computational results link motor feedback to distinct translaminar spacetime patterns.
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5
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Haggie L, Besier T, McMorland A. Circuits in the motor cortex explain oscillatory responses to transcranial magnetic stimulation. Netw Neurosci 2024; 8:96-118. [PMID: 38562291 PMCID: PMC10861165 DOI: 10.1162/netn_a_00341] [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: 10/11/2023] [Indexed: 04/04/2024] Open
Abstract
Transcranial magnetic stimulation (TMS) is a popular method used to investigate brain function. Stimulation over the motor cortex evokes muscle contractions known as motor evoked potentials (MEPs) and also high-frequency volleys of electrical activity measured in the cervical spinal cord. The physiological mechanisms of these experimentally derived responses remain unclear, but it is thought that the connections between circuits of excitatory and inhibitory neurons play a vital role. Using a spiking neural network model of the motor cortex, we explained the generation of waves of activity, so called 'I-waves', following cortical stimulation. The model reproduces a number of experimentally known responses including direction of TMS, increased inhibition, and changes in strength. Using populations of thousands of neurons in a model of cortical circuitry we showed that the cortex generated transient oscillatory responses without any tuning, and that neuron parameters such as refractory period and delays influenced the pattern and timing of those oscillations. By comparing our network with simpler, previously proposed circuits, we explored the contributions of specific connections and found that recurrent inhibitory connections are vital in producing later waves that significantly impact the production of motor evoked potentials in downstream muscles (Thickbroom, 2011). This model builds on previous work to increase our understanding of how complex circuitry of the cortex is involved in the generation of I-waves.
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Affiliation(s)
- Lysea Haggie
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Thor Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Angus McMorland
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Exercise Sciences, University of Auckland, Auckland, New Zealand
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6
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Bast A, Fruengel R, de Kock CPJ, Oberlaender M. Network-neuron interactions underlying sensory responses of layer 5 pyramidal tract neurons in barrel cortex. PLoS Comput Biol 2024; 20:e1011468. [PMID: 38626210 PMCID: PMC11051592 DOI: 10.1371/journal.pcbi.1011468] [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: 08/25/2023] [Revised: 04/26/2024] [Accepted: 03/14/2024] [Indexed: 04/18/2024] Open
Abstract
Neurons in the cerebral cortex receive thousands of synaptic inputs per second from thousands of presynaptic neurons. How the dendritic location of inputs, their timing, strength, and presynaptic origin, in conjunction with complex dendritic physiology, impact the transformation of synaptic input into action potential (AP) output remains generally unknown for in vivo conditions. Here, we introduce a computational approach to reveal which properties of the input causally underlie AP output, and how this neuronal input-output computation is influenced by the morphology and biophysical properties of the dendrites. We demonstrate that this approach allows dissecting of how different input populations drive in vivo observed APs. For this purpose, we focus on fast and broadly tuned responses that pyramidal tract neurons in layer 5 (L5PTs) of the rat barrel cortex elicit upon passive single whisker deflections. By reducing a multi-scale model that we reported previously, we show that three features are sufficient to predict with high accuracy the sensory responses and receptive fields of L5PTs under these specific in vivo conditions: the count of active excitatory versus inhibitory synapses preceding the response, their spatial distribution on the dendrites, and the AP history. Based on these three features, we derive an analytically tractable description of the input-output computation of L5PTs, which enabled us to dissect how synaptic input from thalamus and different cell types in barrel cortex contribute to these responses. We show that the input-output computation is preserved across L5PTs despite morphological and biophysical diversity of their dendrites. We found that trial-to-trial variability in L5PT responses, and cell-to-cell variability in their receptive fields, are sufficiently explained by variability in synaptic input from the network, whereas variability in biophysical and morphological properties have minor contributions. Our approach to derive analytically tractable models of input-output computations in L5PTs provides a roadmap to dissect network-neuron interactions underlying L5PT responses across different in vivo conditions and for other cell types.
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Affiliation(s)
- Arco Bast
- In Silico Brain Sciences Group, Max Planck Institute for Neurobiology of Behavior ˗ caesar, Bonn, Germany
- International Max Planck Research School (IMPRS) for Brain and Behavior, Bonn, Germany
| | - Rieke Fruengel
- In Silico Brain Sciences Group, Max Planck Institute for Neurobiology of Behavior ˗ caesar, Bonn, Germany
- International Max Planck Research School (IMPRS) for Brain and Behavior, Bonn, Germany
| | - Christiaan P. J. de Kock
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Marcel Oberlaender
- In Silico Brain Sciences Group, Max Planck Institute for Neurobiology of Behavior ˗ caesar, Bonn, Germany
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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7
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Li R, Huang J, Li L, Zhao Z, Liang S, Liang S, Wang M, Liao X, Lyu J, Zhou Z, Wang S, Jin W, Chen H, Holder D, Liu H, Zhang J, Li M, Tang Y, Remy S, Pakan JMP, Chen X, Jia H. Holistic bursting cells store long-term memory in auditory cortex. Nat Commun 2023; 14:8090. [PMID: 38062015 PMCID: PMC10703882 DOI: 10.1038/s41467-023-43620-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 11/15/2023] [Indexed: 12/18/2023] Open
Abstract
The sensory neocortex has been suggested to be a substrate for long-term memory storage, yet which exact single cells could be specific candidates underlying such long-term memory storage remained neither known nor visible for over a century. Here, using a combination of day-by-day two-photon Ca2+ imaging and targeted single-cell loose-patch recording in an auditory associative learning paradigm with composite sounds in male mice, we reveal sparsely distributed neurons in layer 2/3 of auditory cortex emerged step-wise from quiescence into bursting mode, which then invariably expressed holistic information of the learned composite sounds, referred to as holistic bursting (HB) cells. Notably, it was not shuffled populations but the same sparse HB cells that embodied the behavioral relevance of the learned composite sounds, pinpointing HB cells as physiologically-defined single-cell candidates of an engram underlying long-term memory storage in auditory cortex.
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Affiliation(s)
- Ruijie Li
- Advanced Institute for Brain and Intelligence and School of Physical Science and Technology, Guangxi University, Nanning, 530004, China
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038, China
| | - Junjie Huang
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, 400030, China
- Leibniz Institute for Neurobiology (LIN), 39118, Magdeburg, Germany
| | - Longhui Li
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, 400030, China
| | - Zhikai Zhao
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, 400030, China
| | - Susu Liang
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, 400030, China
| | - Shanshan Liang
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038, China
| | - Meng Wang
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, 400030, China
| | - Xiang Liao
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, 400030, China
| | - Jing Lyu
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Zhenqiao Zhou
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Sibo Wang
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Wenjun Jin
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038, China
- Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing, 400064, China
| | - Haiyang Chen
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, 100101, Beijing, China
| | - Damaris Holder
- Leibniz Institute for Neurobiology (LIN), 39118, Magdeburg, Germany
| | - Hongbang Liu
- Advanced Institute for Brain and Intelligence and School of Physical Science and Technology, Guangxi University, Nanning, 530004, China
| | - Jianxiong Zhang
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038, China
| | - Min Li
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Yuguo Tang
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Stefan Remy
- Leibniz Institute for Neurobiology (LIN), 39118, Magdeburg, Germany
- Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, 39120, Magdeburg, Germany
| | - Janelle M P Pakan
- Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, 39120, Magdeburg, Germany.
- Institute for Cognitive Neurology and Dementia Research, Otto von Guericke University, 39120, Magdeburg, Germany.
- German Center for Neurodegenerative Diseases (DZNE), 39120, Magdeburg, Germany.
| | - Xiaowei Chen
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038, China.
- Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing, 400064, China.
| | - Hongbo Jia
- Advanced Institute for Brain and Intelligence and School of Physical Science and Technology, Guangxi University, Nanning, 530004, China.
- Leibniz Institute for Neurobiology (LIN), 39118, Magdeburg, Germany.
- Brain Research Instrument Innovation Center, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.
- Institute of Neuroscience and the SyNergy Cluster, Technical University of Munich, 80802, Munich, Germany.
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Lorenzon P, Antos K, Tripathi A, Vedin V, Berghard A, Medini P. In vivo spontaneous activity and coital-evoked inhibition of mouse accessory olfactory bulb output neurons. iScience 2023; 26:107545. [PMID: 37664596 PMCID: PMC10470370 DOI: 10.1016/j.isci.2023.107545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 04/11/2023] [Accepted: 08/01/2023] [Indexed: 09/05/2023] Open
Abstract
Little is known about estrous effects on brain microcircuits. We examined the accessory olfactory bulb (AOB) in vivo, in anesthetized naturally cycling females, as model microcircuit receiving coital somatosensory information. Whole-cell recordings demonstrate that output neurons are relatively hyperpolarized in estrus and unexpectedly fire high frequency bursts of action potentials. To mimic coitus, a calibrated artificial vagino-cervical stimulation (aVCS) protocol was devised. aVCS evoked stimulus-locked local field responses in the interneuron layer independent of estrous stage. The response is sensitive to α1-adrenergic receptor blockade, as expected since aVCS increases norepinephrine release in AOB. Intriguingly, only in estrus does aVCS inhibit AOB spike output. Estrus-specific output reduction coincides with prolonged aVCS activation of inhibitory interneurons. Accordingly, in estrus the AOB microcircuit sets the stage for coital stimulation to inhibit the output neurons, possibly via high frequency bursting-dependent enhancement of reciprocal synapse efficacy between inter- and output neurons.
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Affiliation(s)
- Paolo Lorenzon
- Department of Integrative Medical Biology, Umeå University, SE90187 Umeå, Sweden
| | - Kamil Antos
- Department of Integrative Medical Biology, Umeå University, SE90187 Umeå, Sweden
| | - Anushree Tripathi
- Department of Integrative Medical Biology, Umeå University, SE90187 Umeå, Sweden
| | - Viktoria Vedin
- Department of Molecular Biology, Umeå University, SE90187 Umeå, Sweden
| | - Anna Berghard
- Department of Molecular Biology, Umeå University, SE90187 Umeå, Sweden
| | - Paolo Medini
- Department of Integrative Medical Biology, Umeå University, SE90187 Umeå, Sweden
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9
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Issa LK, Sekaran NVC, Llano DA. Highly branched and complementary distributions of layer 5 and layer 6 auditory corticofugal axons in mouse. Cereb Cortex 2023; 33:9566-9582. [PMID: 37386697 PMCID: PMC10431747 DOI: 10.1093/cercor/bhad227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 07/01/2023] Open
Abstract
The auditory cortex exerts a powerful, yet heterogeneous, effect on subcortical targets. Auditory corticofugal projections emanate from layers 5 and 6 and have complementary physiological properties. While several studies suggested that layer 5 corticofugal projections branch widely, others suggested that multiple independent projections exist. Less is known about layer 6; no studies have examined whether the various layer 6 corticofugal projections are independent. Therefore, we examined branching patterns of layers 5 and 6 auditory corticofugal neurons, using the corticocollicular system as an index, using traditional and novel approaches. We confirmed that dual retrograde injections into the mouse inferior colliculus and auditory thalamus co-labeled subpopulations of layers 5 and 6 auditory cortex neurons. We then used an intersectional approach to relabel layer 5 or 6 corticocollicular somata and found that both layers sent extensive branches to multiple subcortical structures. Using a novel approach to separately label layers 5 and 6 axons in individual mice, we found that layers 5 and 6 terminal distributions partially spatially overlapped and that giant terminals were only found in layer 5-derived axons. Overall, the high degree of branching and complementarity in layers 5 and 6 axonal distributions suggest that corticofugal projections should be considered as 2 widespread systems, rather than collections of individual projections.
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Affiliation(s)
- Lina K Issa
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana—Champaign, Champaign, IL, United States
- Beckman Institute for Advanced Science and Technology, Urbana, IL, United States
| | - Nathiya V C Sekaran
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana—Champaign, Champaign, IL, United States
- Beckman Institute for Advanced Science and Technology, Urbana, IL, United States
| | - Daniel A Llano
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana—Champaign, Champaign, IL, United States
- Beckman Institute for Advanced Science and Technology, Urbana, IL, United States
- Department of Biomedical and Translational Sciences, Carle Illinois College of Medicine, Urbana, IL, United States
- Department of Speech and Hearing Science, University of Illinois at Urbana-Champaign, Champaign, IL, United States
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10
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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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11
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Ekelmans P, Kraynyukovas N, Tchumatchenko T. Targeting operational regimes of interest in recurrent neural networks. PLoS Comput Biol 2023; 19:e1011097. [PMID: 37186668 DOI: 10.1371/journal.pcbi.1011097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 05/25/2023] [Accepted: 04/11/2023] [Indexed: 05/17/2023] Open
Abstract
Neural computations emerge from local recurrent neural circuits or computational units such as cortical columns that comprise hundreds to a few thousand neurons. Continuous progress in connectomics, electrophysiology, and calcium imaging require tractable spiking network models that can consistently incorporate new information about the network structure and reproduce the recorded neural activity features. However, for spiking networks, it is challenging to predict which connectivity configurations and neural properties can generate fundamental operational states and specific experimentally reported nonlinear cortical computations. Theoretical descriptions for the computational state of cortical spiking circuits are diverse, including the balanced state where excitatory and inhibitory inputs balance almost perfectly or the inhibition stabilized state (ISN) where the excitatory part of the circuit is unstable. It remains an open question whether these states can co-exist with experimentally reported nonlinear computations and whether they can be recovered in biologically realistic implementations of spiking networks. Here, we show how to identify spiking network connectivity patterns underlying diverse nonlinear computations such as XOR, bistability, inhibitory stabilization, supersaturation, and persistent activity. We establish a mapping between the stabilized supralinear network (SSN) and spiking activity which allows us to pinpoint the location in parameter space where these activity regimes occur. Notably, we find that biologically-sized spiking networks can have irregular asynchronous activity that does not require strong excitation-inhibition balance or large feedforward input and we show that the dynamic firing rate trajectories in spiking networks can be precisely targeted without error-driven training algorithms.
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Affiliation(s)
- Pierre Ekelmans
- Theory of Neural Dynamics group, Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
| | - Nataliya Kraynyukovas
- Theory of Neural Dynamics group, Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- Institute of Experimental Epileptology and Cognition Research, Life and Brain Center, Universitätsklinikum Bonn, Bonn, Germany
| | - Tatjana Tchumatchenko
- Theory of Neural Dynamics group, Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- Institute of Experimental Epileptology and Cognition Research, Life and Brain Center, Universitätsklinikum Bonn, Bonn, Germany
- Institute of physiological chemistry, Medical center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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12
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Luhmann HJ. Malformations-related neocortical circuits in focal seizures. Neurobiol Dis 2023; 178:106018. [PMID: 36706927 DOI: 10.1016/j.nbd.2023.106018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 01/18/2023] [Accepted: 01/23/2023] [Indexed: 01/25/2023] Open
Abstract
This review article gives an overview on the molecular, cellular and network mechanisms underlying focal seizures in neocortical networks with developmental malformations. Neocortical malformations comprise a large variety of structural abnormalities associated with epilepsy and other neurological and psychiatric disorders. Genetic or acquired disorders of neocortical cell proliferation, neuronal migration and/or programmed cell death may cause pathologies ranging from the expression of dysmorphic neurons and heterotopic cell clusters to abnormal layering and cortical misfolding. After providing a brief overview on the pathogenesis and structure of neocortical malformations in humans, animal models are discussed and how they contributed to our understanding on the mechanisms of neocortical hyperexcitability associated with developmental disorders. State-of-the-art molecular biological and electrophysiological techniques have been also used in humans and on resectioned neocortical tissue of epileptic patients and provide deep insights into the subcellular, cellular and network mechanisms contributing to focal seizures. Finally, a brief outlook is given how novel models and methods can shape translational research in the near future.
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Affiliation(s)
- Heiko J Luhmann
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, Mainz, Germany.
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13
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Moberg S, Takahashi N. Neocortical layer 5 subclasses: From cellular properties to roles in behavior. Front Synaptic Neurosci 2022; 14:1006773. [DOI: 10.3389/fnsyn.2022.1006773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 09/28/2022] [Indexed: 11/13/2022] Open
Abstract
Layer 5 (L5) serves as the main output layer of cortical structures, where long-range projecting pyramidal neurons broadcast the columnar output to other cortical and extracortical regions of the brain. L5 pyramidal neurons are grouped into two subclasses based on their projection targets; while intratelencephalic (IT) neurons project to cortical areas and the striatum, extratelencephalic (ET) neurons project to subcortical areas such as the thalamus, midbrain, and brainstem. Each L5 subclass possesses distinct morphological and electrophysiological properties and is incorporated into a unique synaptic network. Thanks to recent advances in genetic tools and methodologies, it has now become possible to distinguish between the two subclasses in the living brain. There is increasing evidence indicating that each subclass plays a unique role in sensory processing, decision-making, and learning. This review first summarizes the anatomical and physiological properties as well as the neuromodulation of IT and ET neurons in the rodent neocortex, and then reviews recent literature on their roles in sensory processing and rodent behavior. Our ultimate goal is to provide a comprehensive understanding of the role of each subclass in cortical function by examining their operational regimes based on their cellular properties.
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14
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Jedlicka P, Bird AD, Cuntz H. Pareto optimality, economy-effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons. Open Biol 2022; 12:220073. [PMID: 35857898 PMCID: PMC9277232 DOI: 10.1098/rsob.220073] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Neurons encounter unavoidable evolutionary trade-offs between multiple tasks. They must consume as little energy as possible while effectively fulfilling their functions. Cells displaying the best performance for such multi-task trade-offs are said to be Pareto optimal, with their ion channel configurations underpinning their functionality. Ion channel degeneracy, however, implies that multiple ion channel configurations can lead to functionally similar behaviour. Therefore, instead of a single model, neuroscientists often use populations of models with distinct combinations of ionic conductances. This approach is called population (database or ensemble) modelling. It remains unclear, which ion channel parameters in the vast population of functional models are more likely to be found in the brain. Here we argue that Pareto optimality can serve as a guiding principle for addressing this issue by helping to identify the subpopulations of conductance-based models that perform best for the trade-off between economy and functionality. In this way, the high-dimensional parameter space of neuronal models might be reduced to geometrically simple low-dimensional manifolds, potentially explaining experimentally observed ion channel correlations. Conversely, Pareto inference might also help deduce neuronal functions from high-dimensional Patch-seq data. In summary, Pareto optimality is a promising framework for improving population modelling of neurons and their circuits.
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Affiliation(s)
- Peter Jedlicka
- ICAR3R - Interdisciplinary Centre for 3Rs in Animal Research, Faculty of Medicine, Justus-Liebig-University, Giessen, Germany,Institute of Clinical Neuroanatomy, Neuroscience Center, Goethe University, Frankfurt/Main, Germany,Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
| | - Alexander D. Bird
- ICAR3R - Interdisciplinary Centre for 3Rs in Animal Research, Faculty of Medicine, Justus-Liebig-University, Giessen, Germany,Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany,Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
| | - Hermann Cuntz
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany,Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
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15
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Tomasevic L, Siebner HR, Thielscher A, Manganelli F, Pontillo G, Dubbioso R. Relationship between high-frequency activity in the cortical sensory and the motor hand areas, and their myelin content. Brain Stimul 2022; 15:717-726. [PMID: 35525389 DOI: 10.1016/j.brs.2022.04.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The human primary sensory (S1) and primary motor (M1) hand areas feature high-frequency neuronal responses. Electrical nerve stimulation evokes high-frequency oscillations (HFO) at around 650 Hz in the contralateral S1. Likewise, transcranial magnetic stimulation (TMS) of M1 can evoke a series of descending volleys in the corticospinal pathway that can be detected non-invasively with a paired-pulse TMS protocol, called short interval intracortical facilitation (SICF). SICF features several peaks of facilitation of motor evoked potentials in contralateral hand muscles, which are separated by inter-peak intervals resembling HFO rhythmicity. HYPOTHESIS In this study, we tested the hypothesis that the individual expressions of HFO and SICF are tightly related to each other and to the regional myelin content in the sensorimotor cortex. METHODS In 24 healthy volunteers, we recorded HFO and SICF, and, in a subgroup of 20 participants, we mapped the cortical myelin content using the ratio between the T1- and T2-weighted MRI signal as read-out. RESULTS The individual frequencies and magnitudes of HFO and SICF curves were tightly correlated: the intervals between the first and second peak of cortical HFO and SICF showed a positive linear relationship (r = 0.703, p < 0.001), while their amplitudes were inversely related (r = -0.613, p = 0.001). The rhythmicity, but not the magnitude of the high-frequency responses, was related to the cortical myelin content: the higher the cortical myelin content, the shorter the inter-peak intervals of HFO and SICF. CONCLUSION The results confirm a tight functional relationship between high-frequency responses in S1 (i.e., HFO) and M1 (i.e., as measured with SICF). They also establish a link between the degree of regional cortical myelination and the expression of high-frequency responses in the human sensorimotor cortex, giving further the opportunity to infer their generators.
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Affiliation(s)
- Leo Tomasevic
- Danish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University, Hospital Amager and Hvidovre, Copenhagen, Denmark.
| | - Hartwig Roman Siebner
- Danish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University, Hospital Amager and Hvidovre, Copenhagen, Denmark; Department of Neurology, Copenhagen University Hospital Bispebjerg and Fredriksberg, Copenhagen, Denmark; Institute for Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Axel Thielscher
- Danish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University, Hospital Amager and Hvidovre, Copenhagen, Denmark; Department of Health Technology, Technical University of Denmark, Kgs, Lyngby, Denmark
| | - Fiore Manganelli
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University Federico II of Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Raffaele Dubbioso
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University Federico II of Naples, Italy.
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16
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Larkum ME, Wu J, Duverdin SA, Gidon A. The guide to dendritic spikes of the mammalian cortex in vitro and in vivo. Neuroscience 2022; 489:15-33. [PMID: 35182699 DOI: 10.1016/j.neuroscience.2022.02.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 02/01/2022] [Accepted: 02/10/2022] [Indexed: 12/23/2022]
Abstract
Half a century since their discovery by Llinás and colleagues, dendritic spikes have been observed in various neurons in different brain regions, from the neocortex and cerebellum to the basal ganglia. Dendrites exhibit a terrifically diverse but stereotypical repertoire of spikes, sometimes specific to subregions of the dendrite. Despite their prevalence, we only have a glimpse into their role in the behaving animal. This article aims to survey the full range of dendritic spikes found in excitatory and inhibitory neurons, compare them in vivo versus in vitro, and discuss new studies describing dendritic spikes in the human cortex. We focus on dendritic spikes in neocortical and hippocampal neurons and present a roadmap to identify and understand the broader role of dendritic spikes in single-cell computation.
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Affiliation(s)
- Matthew E Larkum
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; NeuroCure Cluster, Charité - Universitätsmedizin Berlin, Germany
| | - Jiameng Wu
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Berlin, Germany
| | - Sarah A Duverdin
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany; Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Albert Gidon
- Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany
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17
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Mease RA, Gonzalez AJ. Corticothalamic Pathways From Layer 5: Emerging Roles in Computation and Pathology. Front Neural Circuits 2021; 15:730211. [PMID: 34566583 PMCID: PMC8458899 DOI: 10.3389/fncir.2021.730211] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 08/10/2021] [Indexed: 11/29/2022] Open
Abstract
Large portions of the thalamus receive strong driving input from cortical layer 5 (L5) neurons but the role of this important pathway in cortical and thalamic computations is not well understood. L5-recipient "higher-order" thalamic regions participate in cortico-thalamo-cortical (CTC) circuits that are increasingly recognized to be (1) anatomically and functionally distinct from better-studied "first-order" CTC networks, and (2) integral to cortical activity related to learning and perception. Additionally, studies are beginning to elucidate the clinical relevance of these networks, as dysfunction across these pathways have been implicated in several pathological states. In this review, we highlight recent advances in understanding L5 CTC networks across sensory modalities and brain regions, particularly studies leveraging cell-type-specific tools that allow precise experimental access to L5 CTC circuits. We aim to provide a focused and accessible summary of the anatomical, physiological, and computational properties of L5-originating CTC networks, and outline their underappreciated contribution in pathology. We particularly seek to connect single-neuron and synaptic properties to network (dys)function and emerging theories of cortical computation, and highlight information processing in L5 CTC networks as a promising focus for computational studies.
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Affiliation(s)
- Rebecca A. Mease
- Institute of Physiology and Pathophysiology, Medical Biophysics, Heidelberg University, Heidelberg, Germany
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18
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Williams E, Payeur A, Gidon A, Naud R. Neural burst codes disguised as rate codes. Sci Rep 2021; 11:15910. [PMID: 34354118 PMCID: PMC8342467 DOI: 10.1038/s41598-021-95037-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 07/13/2021] [Indexed: 02/07/2023] Open
Abstract
The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. Many neurons, however, do not produce clearly demarcated bursts, an observation invoked to rule out the pervasiveness of this coding scheme across brain areas and cell types. Here we ask how detrimental ambiguous spike patterns, those that are neither clearly bursts nor isolated spikes, are for neuronal information transfer. We addressed this question using information theory and computational simulations. By quantifying how information transmission depends on firing statistics, we found that the information transmitted is not strongly influenced by the presence of clearly demarcated modes in the interspike interval distribution, a feature often used to identify the presence of burst coding. Instead, we found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on dynamical properties of the synapses as well as the length and relative frequency of bursts. Furthermore, we found that common metrics used to quantify burstiness were unable to predict the degree with which bursts could be used to carry information. Our results provide guiding principles for the implementation of coding strategies based on spike-timing patterns, and show that even unimodal firing statistics can be consistent with a bivariate neural code.
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Affiliation(s)
- Ezekiel Williams
- grid.28046.380000 0001 2182 2255Department of Mathematics and Statistics, University of Ottawa, 150 Louis Pasteur, Ottawa, K1N 6N5 Canada
| | - Alexandre Payeur
- grid.28046.380000 0001 2182 2255University of Ottawa Brain and Mind Institute, Centre for Neural Dynamics, Department of Cellular and Molecular Medicine, University of Ottawa, 451 Smyth Rd., Ottawa, K1H 8M5 Canada
| | - Albert Gidon
- grid.7468.d0000 0001 2248 7639Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Richard Naud
- grid.28046.380000 0001 2182 2255University of Ottawa Brain and Mind Institute, Centre for Neural Dynamics, Department of Cellular and Molecular Medicine, University of Ottawa, 451 Smyth Rd., Ottawa, K1H 8M5 Canada ,grid.28046.380000 0001 2182 2255Department of Physics, University of Ottawa, 150 Louis Pasteur, Ottawa, K1N 6N5 Canada
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