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Lee SY, Kozalakis K, Baftizadeh F, Campagnola L, Jarsky T, Koch C, Anastassiou CA. Cell-class-specific electric field entrainment of neural activity. Neuron 2024; 112:2614-2630.e5. [PMID: 38838670 PMCID: PMC11309920 DOI: 10.1016/j.neuron.2024.05.009] [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: 02/06/2023] [Revised: 12/14/2023] [Accepted: 05/08/2024] [Indexed: 06/07/2024]
Abstract
Electric fields affect the activity of neurons and brain circuits, yet how this happens at the cellular level remains enigmatic. Lack of understanding of how to stimulate the brain to promote or suppress specific activity significantly limits basic research and clinical applications. Here, we study how electric fields impact subthreshold and spiking properties of major cortical neuronal classes. We find that neurons in the rodent and human cortex exhibit strong, cell-class-dependent entrainment that depends on stimulation frequency. Excitatory pyramidal neurons, with their slower spike rate, entrain to both slow and fast electric fields, while inhibitory classes like Pvalb and Sst (with their fast spiking) predominantly phase-lock to fast fields. We show that this spike-field entrainment is the result of two effects: non-specific membrane polarization occurring across classes and class-specific excitability properties. Importantly, these properties are present across cortical areas and species. These findings allow for the design of selective and class-specific neuromodulation.
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Affiliation(s)
| | | | | | | | | | | | - Costas A Anastassiou
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Center for Biomedical Science, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
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2
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Barzó P, Szöts I, Tóth M, Csajbók ÉA, Molnár G, Tamás G. Electrophysiology and Morphology of Human Cortical Supragranular Pyramidal Cells in a Wide Age Range. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.13.598792. [PMID: 38915496 PMCID: PMC11195274 DOI: 10.1101/2024.06.13.598792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
The basic excitatory neurons of the cerebral cortex, the pyramidal cells, are the most important signal integrators for the local circuit. They have quite characteristic morphological and electrophysiological properties that are known to be largely constant with age in the young and adult cortex. However, the brain undergoes several dynamic changes throughout life, such as in the phases of early development and cognitive decline in the aging brain. We set out to search for intrinsic cellular changes in supragranular pyramidal cells across a broad age range: from birth to 85 years of age and we found differences in several biophysical properties between defined age groups. During the first year of life, subthreshold and suprathreshold electrophysiological properties changed in a way that shows that pyramidal cells become less excitable with maturation, but also become temporarily more precise. According to our findings, the morphological features of the three-dimensional reconstructions from different life stages showed consistent morphological properties and systematic dendritic spine analysis of an infantile and an old pyramidal cell showed clear significant differences in the distribution of spine shapes. Overall, the changes that occur during development and aging may have lasting effects on the properties of pyramidal cells in the cerebral cortex. Understanding these changes is important to unravel the complex mechanisms underlying brain development, cognition and age-related neurodegenerative diseases.
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Affiliation(s)
- Pál Barzó
- Department of Neurosurgery, University of Szeged, Szeged, Hungary
| | - Ildikó Szöts
- ELKH-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
| | - Martin Tóth
- ELKH-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
| | - Éva Adrienn Csajbók
- ELKH-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
| | - Gábor Molnár
- ELKH-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
| | - Gábor Tamás
- ELKH-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
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3
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Merino‐Serrais P, Plaza‐Alonso S, Hellal F, Valero‐Freitag S, Kastanauskaite A, Plesnila N, DeFelipe J. Structural changes of CA1 pyramidal neurons after stroke in the contralesional hippocampus. Brain Pathol 2024; 34:e13222. [PMID: 38012061 PMCID: PMC11007010 DOI: 10.1111/bpa.13222] [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: 06/15/2023] [Accepted: 10/30/2023] [Indexed: 11/29/2023] Open
Abstract
Significant progress has been made with regard to understanding how the adult brain responds after a stroke. However, a large number of patients continue to suffer lifelong disabilities without adequate treatment. In the present study, we have analyzed possible microanatomical alterations in the contralesional hippocampus from the ischemic stroke mouse model tMCAo 12-14 weeks after transient middle cerebral artery occlusion. After individually injecting Lucifer yellow into pyramidal neurons from the CA1 field of the hippocampus, we performed a detailed three-dimensional analysis of the neuronal complexity, dendritic spine density, and morphology. We found that, in both apical (stratum radiatum) and basal (stratum oriens) arbors, CA1 pyramidal neurons in the contralesional hippocampus of tMCAo mice have a significantly higher neuronal complexity, as well as reduced spine density and alterations in spine volume and spine length. Our results show that when the ipsilateral hippocampus is dramatically damaged, the contralesional hippocampus exhibits several statistically significant selective alterations. However, these alterations are not as significant as expected, which may help to explain the recovery of hippocampal function after stroke. Further anatomical and physiological studies are necessary to better understand the modifications in the "intact" contralesional lesioned brain regions, which are probably fundamental to recover functions after stroke.
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Affiliation(s)
- Paula Merino‐Serrais
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología BiomédicaUniversidad Politécnica de MadridMadridSpain
- Departamento de Neurobiología Funcional y de SistemasInstituto Cajal, CSICMadridSpain
| | - Sergio Plaza‐Alonso
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología BiomédicaUniversidad Politécnica de MadridMadridSpain
- Departamento de Neurobiología Funcional y de SistemasInstituto Cajal, CSICMadridSpain
| | - Farida Hellal
- Laboratory of Experimental Stroke Research, Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig‐Maximilians‐University Munich (LMU)MunichGermany
- iTERM, Helmholtz CenterMunichGermany
- Munich Cluster of Systems Neurology (Synergy)MunichGermany
| | - Susana Valero‐Freitag
- Laboratory of Experimental Stroke Research, Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig‐Maximilians‐University Munich (LMU)MunichGermany
| | - Asta Kastanauskaite
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología BiomédicaUniversidad Politécnica de MadridMadridSpain
- Departamento de Neurobiología Funcional y de SistemasInstituto Cajal, CSICMadridSpain
| | - Nikolaus Plesnila
- Laboratory of Experimental Stroke Research, Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig‐Maximilians‐University Munich (LMU)MunichGermany
- Munich Cluster of Systems Neurology (Synergy)MunichGermany
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología BiomédicaUniversidad Politécnica de MadridMadridSpain
- Departamento de Neurobiología Funcional y de SistemasInstituto Cajal, CSICMadridSpain
- CIBER de Enfermedades Neurodegenerativas, Instituto de Salud Carlos IIIMadridSpain
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4
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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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5
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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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6
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Wilbers R, Galakhova AA, Driessens SL, Heistek TS, Metodieva VD, Hagemann J, Heyer DB, Mertens EJ, Deng S, Idema S, de Witt Hamer PC, Noske DP, van Schie P, Kommers I, Luan G, Li T, Shu Y, de Kock CP, Mansvelder HD, Goriounova NA. Structural and functional specializations of human fast-spiking neurons support fast cortical signaling. SCIENCE ADVANCES 2023; 9:eadf0708. [PMID: 37824618 PMCID: PMC10569701 DOI: 10.1126/sciadv.adf0708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 05/17/2023] [Indexed: 10/14/2023]
Abstract
Fast-spiking interneurons (FSINs) provide fast inhibition that synchronizes neuronal activity and is critical for cognitive function. Fast synchronization frequencies are evolutionary conserved in the expanded human neocortex despite larger neuron-to-neuron distances that challenge fast input-output transfer functions of FSINs. Here, we test in human neurons from neurosurgery tissue, which mechanistic specializations of human FSINs explain their fast-signaling properties in human cortex. With morphological reconstructions, multipatch recordings, and biophysical modeling, we find that despite threefold longer dendritic path, human FSINs maintain fast inhibition between connected pyramidal neurons through several mechanisms: stronger synapse strength of excitatory inputs, larger dendrite diameter with reduced complexity, faster AP initiation, and faster and larger inhibitory output, while Na+ current activation/inactivation properties are similar. These adaptations underlie short input-output delays in fast inhibition of human pyramidal neurons through FSINs, explaining how cortical synchronization frequencies are conserved despite expanded and sparse network topology of human cortex.
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Affiliation(s)
- René Wilbers
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
| | - Anna A. Galakhova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
| | - Stan L.W. Driessens
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
| | - Tim S. Heistek
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
| | - Verjinia D. Metodieva
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
| | - Jim Hagemann
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
| | - Djai B. Heyer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
| | - Eline J. Mertens
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
| | - Suixin Deng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, 19 Xinjiekou Wai Street, Beijing 100875, China
- Department of Neurosurgery, Jinshan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Fudan University, Shanghai 201508, China
| | - Sander Idema
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, de Boelelaan 1117, 1081 HV Amsterdam, Netherlands
| | - Philip C. de Witt Hamer
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, de Boelelaan 1117, 1081 HV Amsterdam, Netherlands
| | - David P. Noske
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, de Boelelaan 1117, 1081 HV Amsterdam, Netherlands
| | - Paul van Schie
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, de Boelelaan 1117, 1081 HV Amsterdam, Netherlands
| | - Ivar Kommers
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, de Boelelaan 1117, 1081 HV Amsterdam, Netherlands
| | - Guoming Luan
- Department of Neurosurgery, Epilepsy Center, Sanbo Brain Hospital, Capital Medical University, Xiangshan Yikesong 50, Beijing 100093, China
| | - Tianfu Li
- Department of Neurosurgery, Epilepsy Center, Sanbo Brain Hospital, Capital Medical University, Xiangshan Yikesong 50, Beijing 100093, China
| | - Yousheng Shu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, 19 Xinjiekou Wai Street, Beijing 100875, China
- Department of Neurosurgery, Jinshan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Fudan University, Shanghai 201508, China
| | - Christiaan P.J. de Kock
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
| | - Huibert D. Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
| | - Natalia A. Goriounova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, de Boelelaan 1085, 1081 HV Amsterdam, Netherlands
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7
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Wilbers R, Metodieva VD, Duverdin S, Heyer DB, Galakhova AA, Mertens EJ, Versluis TD, Baayen JC, Idema S, Noske DP, Verburg N, Willemse RB, de Witt Hamer PC, Kole MH, de Kock CP, Mansvelder HD, Goriounova NA. Human voltage-gated Na + and K + channel properties underlie sustained fast AP signaling. SCIENCE ADVANCES 2023; 9:eade3300. [PMID: 37824607 PMCID: PMC10569700 DOI: 10.1126/sciadv.ade3300] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 01/09/2023] [Indexed: 10/14/2023]
Abstract
Human cortical pyramidal neurons are large, have extensive dendritic trees, and yet have unexpectedly fast input-output properties: Rapid subthreshold synaptic membrane potential changes are reliably encoded in timing of action potentials (APs). Here, we tested whether biophysical properties of voltage-gated sodium (Na+) and potassium (K+) currents in human pyramidal neurons can explain their fast input-output properties. Human Na+ and K+ currents exhibited more depolarized voltage dependence, slower inactivation, and faster recovery from inactivation compared with their mouse counterparts. Computational modeling showed that despite lower Na+ channel densities in human neurons, the biophysical properties of Na+ channels resulted in higher channel availability and contributed to fast AP kinetics stability. Last, human Na+ channel properties also resulted in a larger dynamic range for encoding of subthreshold membrane potential changes. Thus, biophysical adaptations of voltage-gated Na+ and K+ channels enable fast input-output properties of large human pyramidal neurons.
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Affiliation(s)
- René Wilbers
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, Netherlands
| | - Verjinia D. Metodieva
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, Netherlands
| | - Sarah Duverdin
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, Netherlands
| | - Djai B. Heyer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, Netherlands
| | - Anna A. Galakhova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, Netherlands
| | - Eline J. Mertens
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, Netherlands
| | - Tamara D. Versluis
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, Netherlands
| | - Johannes C. Baayen
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, Amsterdam 1081 HV, Netherlands
| | - Sander Idema
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, Amsterdam 1081 HV, Netherlands
| | - David P. Noske
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, Amsterdam 1081 HV, Netherlands
| | - Niels Verburg
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, Amsterdam 1081 HV, Netherlands
| | - Ronald B. Willemse
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, Amsterdam 1081 HV, Netherlands
| | - Philip C. de Witt Hamer
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center, Amsterdam Brain Tumor Center, Amsterdam 1081 HV, Netherlands
| | - Maarten H. P. Kole
- Department of Axonal Signaling, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam 1105 BA, Netherlands
- Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, Utrecht 3584 CH, Netherlands
| | - Christiaan P. J. de Kock
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, Netherlands
| | - Huibert D. Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, Netherlands
| | - Natalia A. Goriounova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, Netherlands
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8
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de Kock CPJ, Feldmeyer D. Shared and divergent principles of synaptic transmission between cortical excitatory neurons in rodent and human brain. Front Synaptic Neurosci 2023; 15:1274383. [PMID: 37731775 PMCID: PMC10508294 DOI: 10.3389/fnsyn.2023.1274383] [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: 08/08/2023] [Accepted: 08/21/2023] [Indexed: 09/22/2023] Open
Abstract
Information transfer between principal neurons in neocortex occurs through (glutamatergic) synaptic transmission. In this focussed review, we provide a detailed overview on the strength of synaptic neurotransmission between pairs of excitatory neurons in human and laboratory animals with a specific focus on data obtained using patch clamp electrophysiology. We reach two major conclusions: (1) the synaptic strength, measured as unitary excitatory postsynaptic potential (or uEPSP), is remarkably consistent across species, cortical regions, layers and/or cell-types (median 0.5 mV, interquartile range 0.4-1.0 mV) with most variability associated with the cell-type specific connection studied (min 0.1-max 1.4 mV), (2) synaptic function cannot be generalized across human and rodent, which we exemplify by discussing the differences in anatomical and functional properties of pyramidal-to-pyramidal connections within human and rodent cortical layers 2 and 3. With only a handful of studies available on synaptic transmission in human, it is obvious that much remains unknown to date. Uncovering the shared and divergent principles of synaptic transmission across species however, will almost certainly be a pivotal step toward understanding human cognitive ability and brain function in health and disease.
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Affiliation(s)
- Christiaan P. J. de Kock
- Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Dirk Feldmeyer
- Research Center Juelich, Institute of Neuroscience and Medicine, Jülich, Germany
- Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University Hospital, Aachen, Germany
- Jülich-Aachen Research Alliance, Translational Brain Medicine (JARA Brain), Aachen, Germany
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9
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Mc Hugh J, Makarchuk S, Mozheiko D, Fernandez-Villegas A, Kaminski Schierle GS, Kaminski CF, Keyser UF, Holcman D, Rouach N. Diversity of dynamic voltage patterns in neuronal dendrites revealed by nanopipette electrophysiology. NANOSCALE 2023. [PMID: 37455621 PMCID: PMC10373629 DOI: 10.1039/d2nr03475a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
Dendrites and dendritic spines are the essential cellular compartments in neuronal communication, conveying information through transient voltage signals. Our understanding of these compartmentalized voltage dynamics in fine, distal neuronal dendrites remains poor due to the difficulties inherent to accessing and stably recording from such small, nanoscale cellular compartments for a sustained time. To overcome these challenges, we use nanopipettes that permit long and stable recordings directly from fine neuronal dendrites. We reveal a diversity of voltage dynamics present locally in dendrites, such as spontaneous voltage transients, bursting events and oscillating periods of silence and firing activity, all of which we characterized using segmentation analysis. Remarkably, we find that neuronal dendrites can display spontaneous hyperpolarisation events, and sustain transient hyperpolarised states. The voltage patterns were activity-dependent, with a stronger dependency on synaptic activity than on action potentials. Long-time recordings of fine dendritic protrusions show complex voltage dynamics that may represent a previously unexplored contribution to dendritic computations.
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Affiliation(s)
- Jeffrey Mc Hugh
- Centre for Interdisciplinary Research in Biology, Collège de France, CNRS, INSERM, Université PSL, Labex Memolife, Paris, France.
- Cavendish Laboratory, University of Cambridge, Cambridge CB3 0HE, UK
| | - Stanislaw Makarchuk
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, UK
| | - Daria Mozheiko
- Centre for Interdisciplinary Research in Biology, Collège de France, CNRS, INSERM, Université PSL, Labex Memolife, Paris, France.
- Doctoral School No 158, Sorbonne Université, Paris, France
| | - Ana Fernandez-Villegas
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, UK
| | - Gabriele S Kaminski Schierle
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, UK
| | - Clemens F Kaminski
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, UK
| | - Ulrich F Keyser
- Cavendish Laboratory, University of Cambridge, Cambridge CB3 0HE, UK
| | - David Holcman
- Group Data Modelling, Computational Biology and Predictive Medicine, Institut de Biologie de l'Ecole Normale Supérieure (IBENS), CNRS, INSERM, Université PSL, Labex Memolife, Paris, France
- Churchill College, University of Cambridge, Cambridge CB3 0DS, UK
| | - Nathalie Rouach
- Centre for Interdisciplinary Research in Biology, Collège de France, CNRS, INSERM, Université PSL, Labex Memolife, Paris, France.
- Churchill College, University of Cambridge, Cambridge CB3 0DS, UK
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10
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Driessens SLW, Galakhova AA, Heyer DB, Pieterse IJ, Wilbers R, Mertens EJ, Waleboer F, Heistek TS, Coenen L, Meijer JR, Idema S, de Witt Hamer PC, Noske DP, de Kock CPJ, Lee BR, Smith K, Ting JT, Lein ES, Mansvelder HD, Goriounova NA. Genes associated with cognitive ability and HAR show overlapping expression patterns in human cortical neuron types. Nat Commun 2023; 14:4188. [PMID: 37443107 PMCID: PMC10345092 DOI: 10.1038/s41467-023-39946-9] [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: 11/07/2022] [Accepted: 07/04/2023] [Indexed: 07/15/2023] Open
Abstract
GWAS have identified numerous genes associated with human cognition but their cell type expression profiles in the human brain are unknown. These genes overlap with human accelerated regions (HARs) implicated in human brain evolution and might act on the same biological processes. Here, we investigated whether these gene sets are expressed in adult human cortical neurons, and how their expression relates to neuronal function and structure. We find that these gene sets are preferentially expressed in L3 pyramidal neurons in middle temporal gyrus (MTG). Furthermore, neurons with higher expression had larger total dendritic length (TDL) and faster action potential (AP) kinetics, properties previously linked to intelligence. We identify a subset of genes associated with TDL or AP kinetics with predominantly synaptic functions and high abundance of HARs.
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Affiliation(s)
- Stan L W Driessens
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Anna A Galakhova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Djai B Heyer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Isabel J Pieterse
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - René Wilbers
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Eline J Mertens
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Femke Waleboer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Tim S Heistek
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Loet Coenen
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Julia R Meijer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Sander Idema
- Department of Neurosurgery, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands
| | - Philip C de Witt Hamer
- Department of Neurosurgery, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands
| | - David P Noske
- Department of Neurosurgery, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands
| | - Christiaan P J de Kock
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Brian R Lee
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA, 98109, USA
| | - Kimberly Smith
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA, 98109, USA
| | - Jonathan T Ting
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA, 98109, USA
| | - Ed S Lein
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA, 98109, USA
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Natalia A Goriounova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands.
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11
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Caspi Y, Mazar M, Kushnir Y, Mazor Y, Katz B, Lev S, Binshtok AM. Structural plasticity of axon initial segment in spinal cord neurons underlies inflammatory pain. Pain 2023; 164:1388-1401. [PMID: 36645177 DOI: 10.1097/j.pain.0000000000002829] [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: 08/03/2022] [Accepted: 10/19/2022] [Indexed: 01/17/2023]
Abstract
ABSTRACT Physiological or pathology-mediated changes in neuronal activity trigger structural plasticity of the action potential generation site-the axon initial segment (AIS). These changes affect intrinsic neuronal excitability, thus tuning neuronal and overall network output. Using behavioral, immunohistochemical, electrophysiological, and computational approaches, we characterized inflammation-related AIS plasticity in rat's superficial (lamina II) spinal cord dorsal horn (SDH) neurons and established how AIS plasticity regulates the activity of SDH neurons, thus contributing to pain hypersensitivity. We show that in naive conditions, AIS in SDH inhibitory neurons is located closer to the soma than in excitatory neurons. Shortly after inducing inflammation, when the inflammatory hyperalgesia is at its peak, AIS in inhibitory neurons is shifted distally away from the soma. The shift in AIS location is accompanied by the decrease in excitability of SDH inhibitory neurons. These AIS location and excitability changes are selective for inhibitory neurons and reversible. We show that AIS shift back close to the soma, and SDH inhibitory neurons' excitability increases to baseline levels following recovery from inflammatory hyperalgesia. The computational model of SDH inhibitory neurons predicts that the distal shift of AIS is sufficient to decrease the intrinsic excitability of these neurons. Our results provide evidence of inflammatory pain-mediated AIS plasticity in the central nervous system, which differentially affects the excitability of inhibitory SDH neurons and contributes to inflammatory hyperalgesia.
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Affiliation(s)
- Yaki Caspi
- Department of Medical Neurobiology, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah School of Medicine, Jerusalem, Israel
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Michael Mazar
- Department of Medical Neurobiology, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah School of Medicine, Jerusalem, Israel
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yishai Kushnir
- Department of Medical Neurobiology, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah School of Medicine, Jerusalem, Israel
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yoav Mazor
- Department of Medical Neurobiology, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah School of Medicine, Jerusalem, Israel
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Gastroenterology, Rambam Health Care Campus, Haifa, Israel
| | - Ben Katz
- Department of Medical Neurobiology, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah School of Medicine, Jerusalem, Israel
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Shaya Lev
- Department of Medical Neurobiology, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah School of Medicine, Jerusalem, Israel
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Alexander M Binshtok
- Department of Medical Neurobiology, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah School of Medicine, Jerusalem, Israel
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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12
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Hunt S, Leibner Y, Mertens EJ, Barros-Zulaica N, Kanari L, Heistek TS, Karnani MM, Aardse R, Wilbers R, Heyer DB, Goriounova NA, Verhoog MB, Testa-Silva G, Obermayer J, Versluis T, Benavides-Piccione R, de Witt-Hamer P, Idema S, Noske DP, Baayen JC, Lein ES, DeFelipe J, Markram H, Mansvelder HD, Schürmann F, Segev I, de Kock CPJ. Strong and reliable synaptic communication between pyramidal neurons in adult human cerebral cortex. Cereb Cortex 2023; 33:2857-2878. [PMID: 35802476 PMCID: PMC10016070 DOI: 10.1093/cercor/bhac246] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/25/2022] [Accepted: 05/26/2022] [Indexed: 12/25/2022] Open
Abstract
Synaptic transmission constitutes the primary mode of communication between neurons. It is extensively studied in rodent but not human neocortex. We characterized synaptic transmission between pyramidal neurons in layers 2 and 3 using neurosurgically resected human middle temporal gyrus (MTG, Brodmann area 21), which is part of the distributed language circuitry. We find that local connectivity is comparable with mouse layer 2/3 connections in the anatomical homologue (temporal association area), but synaptic connections in human are 3-fold stronger and more reliable (0% vs 25% failure rates, respectively). We developed a theoretical approach to quantify properties of spinous synapses showing that synaptic conductance and voltage change in human dendritic spines are 3-4-folds larger compared with mouse, leading to significant NMDA receptor activation in human unitary connections. This model prediction was validated experimentally by showing that NMDA receptor activation increases the amplitude and prolongs decay of unitary excitatory postsynaptic potentials in human but not in mouse connections. Since NMDA-dependent recurrent excitation facilitates persistent activity (supporting working memory), our data uncovers cortical microcircuit properties in human that may contribute to language processing in MTG.
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Affiliation(s)
| | | | - Eline J Mertens
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Natalí Barros-Zulaica
- Blue Brain Project, Ecole polytechnique fédérale de Lausanne, Campus Biotech, Geneva 1202, Switzerland
| | - Lida Kanari
- Blue Brain Project, Ecole polytechnique fédérale de Lausanne, Campus Biotech, Geneva 1202, Switzerland
| | - Tim S Heistek
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Mahesh M Karnani
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Romy Aardse
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - René Wilbers
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Djai B Heyer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Natalia A Goriounova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | | | | | - Joshua Obermayer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Tamara Versluis
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Ruth Benavides-Piccione
- Laboratorio Cajal de Circuitos Corticales, Universidad Politécnica de Madrid and Instituto Cajal (CSIC), Pozuelo de Alarcón, Madrid 28223, Spain
| | - Philip de Witt-Hamer
- Neurosurgery Department, Amsterdam Universitair Medische Centra, location VUmc, 1081 HV Amsterdam, the Netherlands
| | - Sander Idema
- Neurosurgery Department, Amsterdam Universitair Medische Centra, location VUmc, 1081 HV Amsterdam, the Netherlands
| | - David P Noske
- Neurosurgery Department, Amsterdam Universitair Medische Centra, location VUmc, 1081 HV Amsterdam, the Netherlands
| | - Johannes C Baayen
- Neurosurgery Department, Amsterdam Universitair Medische Centra, location VUmc, 1081 HV Amsterdam, the Netherlands
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Universidad Politécnica de Madrid and Instituto Cajal (CSIC), Pozuelo de Alarcón, Madrid 28223, Spain
| | - Henry Markram
- Blue Brain Project, Ecole polytechnique fédérale de Lausanne, Campus Biotech, Geneva 1202, Switzerland
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Felix Schürmann
- Blue Brain Project, Ecole polytechnique fédérale de Lausanne, Campus Biotech, Geneva 1202, Switzerland
| | - Idan Segev
- Department of Neurobiology and Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, 9190501 Jerusalem, Israel
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13
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Yayon N, Amsalem O, Zorbaz T, Yakov O, Dubnov S, Winek K, Dudai A, Adam G, Schmidtner AK, Tessier‐Lavigne M, Renier N, Habib N, Segev I, London M, Soreq H. High-throughput morphometric and transcriptomic profiling uncovers composition of naïve and sensory-deprived cortical cholinergic VIP/CHAT neurons. EMBO J 2022; 42:e110565. [PMID: 36377476 PMCID: PMC9811618 DOI: 10.15252/embj.2021110565] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 10/03/2022] [Accepted: 10/17/2022] [Indexed: 11/16/2022] Open
Abstract
Cortical neuronal networks control cognitive output, but their composition and modulation remain elusive. Here, we studied the morphological and transcriptional diversity of cortical cholinergic VIP/ChAT interneurons (VChIs), a sparse population with a largely unknown function. We focused on VChIs from the whole barrel cortex and developed a high-throughput automated reconstruction framework, termed PopRec, to characterize hundreds of VChIs from each mouse in an unbiased manner, while preserving 3D cortical coordinates in multiple cleared mouse brains, accumulating thousands of cells. We identified two fundamentally distinct morphological types of VChIs, bipolar and multipolar that differ in their cortical distribution and general morphological features. Following mild unilateral whisker deprivation on postnatal day seven, we found after three weeks both ipsi- and contralateral dendritic arborization differences and modified cortical depth and distribution patterns in the barrel fields alone. To seek the transcriptomic drivers, we developed NuNeX, a method for isolating nuclei from fixed tissues, to explore sorted VChIs. This highlighted differentially expressed neuronal structural transcripts, altered exitatory innervation pathways and established Elmo1 as a key regulator of morphology following deprivation.
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Affiliation(s)
- Nadav Yayon
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,The Department of Biological Chemistry, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | - Oren Amsalem
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,The Department of Neurobiology, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | - Tamara Zorbaz
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,The Department of Biological Chemistry, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,Biochemistry and Organic Analytical Chemistry UnitThe Institute of Medical Research and Occupational HealthZagrebCroatia
| | - Or Yakov
- The Department of Biological Chemistry, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | - Serafima Dubnov
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,The Department of Biological Chemistry, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | - Katarzyna Winek
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,The Department of Biological Chemistry, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | - Amir Dudai
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,The Department of Neurobiology, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | - Gil Adam
- The Department of Biological Chemistry, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | - Anna K Schmidtner
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | | | - Nicolas Renier
- Sorbonne Université, Paris Brain Institute ‐ ICM, INSERM, CNRS, AP‐HP, Hôpital de la Pitié SalpêtrièreParisFrance
| | - Naomi Habib
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,The Department of Neurobiology, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | - Idan Segev
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,The Department of Neurobiology, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | - Michael London
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,The Department of Neurobiology, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
| | - Hermona Soreq
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael,The Department of Biological Chemistry, The Life Sciences InstituteThe Hebrew University of JerusalemJerusalemIsrael
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14
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Galakhova AA, Hunt S, Wilbers R, Heyer DB, de Kock CPJ, Mansvelder HD, Goriounova NA. Evolution of cortical neurons supporting human cognition. Trends Cogn Sci 2022; 26:909-922. [PMID: 36117080 PMCID: PMC9561064 DOI: 10.1016/j.tics.2022.08.012] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 08/18/2022] [Accepted: 08/24/2022] [Indexed: 01/12/2023]
Abstract
Human cognitive abilities are generally thought to arise from cortical expansion over the course of human brain evolution. In addition to increased neuron numbers, this cortical expansion might be driven by adaptations in the properties of single neurons and their local circuits. We review recent findings on the distinct structural, functional, and transcriptomic features of human cortical neurons and their organization in cortical microstructure. We focus on the supragranular cortical layers, which showed the most prominent expansion during human brain evolution, and the properties of their principal cells: pyramidal neurons. We argue that the evolutionary adaptations in neuronal features that accompany the expansion of the human cortex partially underlie interindividual variability in human cognitive abilities.
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Affiliation(s)
- A A Galakhova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - S Hunt
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - R Wilbers
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - D B Heyer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - C P J de Kock
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - H D Mansvelder
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - N A Goriounova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands.
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15
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Moubarak E, Inglebert Y, Tell F, Goaillard JM. Morphological Determinants of Cell-to-Cell Variations in Action Potential Dynamics in Substantia Nigra Dopaminergic Neurons. J Neurosci 2022; 42:7530-7546. [PMID: 36658458 PMCID: PMC9546446 DOI: 10.1523/jneurosci.2331-21.2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 06/22/2022] [Accepted: 07/19/2022] [Indexed: 02/02/2023] Open
Abstract
Action potential (AP) shape is a critical electrophysiological parameter, in particular because it strongly modulates neurotransmitter release. As it greatly varies between neuronal types, AP shape is also used to distinguish neuronal populations. For instance, AP duration ranges from hundreds of microseconds in cerebellar granule cells to 2-3 ms in SNc dopaminergic (DA) neurons. While most of this variation across cell types seems to arise from differences in the voltage- and calcium-gated ion channels expressed, a few studies suggested that dendritic morphology also affects AP shape. AP duration also displays significant variability in a same neuronal type, although the determinants of these variations are poorly known. Using electrophysiological recordings, morphological reconstructions, and realistic Hodgkin-Huxley modeling, we investigated the relationships between dendritic morphology and AP shape in rat SNc DA neurons from both sexes. In this neuronal type where the axon arises from an axon-bearing dendrite (ABD), the duration of the somatic AP could be predicted from a linear combination of the ABD and non-ABDs' complexities. Dendrotomy experiments and simulation showed that these correlations arise from the causal influence of dendritic topology on AP duration, due in particular to a high density of sodium channels in the somatodendritic compartment. Surprisingly, computational modeling suggested that this effect arises from the influence of sodium currents on the decaying phase of the AP. Consistent with previous findings, these results demonstrate that dendritic morphology plays a major role in defining the electrophysiological properties of SNc DA neurons and their cell-to-cell variations.SIGNIFICANCE STATEMENT Action potential (AP) shape is a critical electrophysiological parameter, in particular because it strongly modulates neurotransmitter release. AP shape (e.g., duration) greatly varies between neuronal types but also within a same neuronal type. While differences in ion channel expression seem to explain most of AP shape variation across cell types, the determinants of cell-to-cell variations in a same neuronal type are mostly unknown. We used electrophysiological recordings, neuronal reconstruction, and modeling to show that, because of the presence of sodium channels in the somatodendritic compartment, a large part of cell-to-cell variations in somatic AP duration in substantia nigra pars compacta dopaminergic neurons is explained by variations in dendritic topology.
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Affiliation(s)
- Estelle Moubarak
- Unité Mixte de Recherche_S 1072, Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Faculté de Médecine Secteur Nord, Marseille, France 13015
| | - Yanis Inglebert
- Unité Mixte de Recherche_S 1072, Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Faculté de Médecine Secteur Nord, Marseille, France 13015
| | - Fabien Tell
- Unité Mixte de Recherche_S 1072, Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Faculté de Médecine Secteur Nord, Marseille, France 13015
| | - Jean-Marc Goaillard
- Unité Mixte de Recherche_S 1072, Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Faculté de Médecine Secteur Nord, Marseille, France 13015
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16
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Physiological noise facilitates multiplexed coding of vibrotactile-like signals in somatosensory cortex. Proc Natl Acad Sci U S A 2022; 119:e2118163119. [PMID: 36067307 PMCID: PMC9478643 DOI: 10.1073/pnas.2118163119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Neurons can use different aspects of their spiking to simultaneously represent (multiplex) different features of a stimulus. For example, some pyramidal neurons in primary somatosensory cortex (S1) use the rate and timing of their spikes to, respectively, encode the intensity and frequency of vibrotactile stimuli. Doing so has several requirements. Because they fire at low rates, pyramidal neurons cannot entrain 1:1 with high-frequency (100 to 600 Hz) inputs and, instead, must skip (i.e., not respond to) some stimulus cycles. The proportion of skipped cycles must vary inversely with stimulus intensity for firing rate to encode stimulus intensity. Spikes must phase-lock to the stimulus for spike times (intervals) to encode stimulus frequency, but, in addition, skipping must occur irregularly to avoid aliasing. Using simulations and in vitro experiments in which mouse S1 pyramidal neurons were stimulated with inputs emulating those induced by vibrotactile stimuli, we show that fewer cycles are skipped as stimulus intensity increases, as required for rate coding, and that intrinsic or synaptic noise can induce irregular skipping without disrupting phase locking, as required for temporal coding. This occurs because noise can modulate the reliability without disrupting the precision of spikes evoked by small-amplitude, fast-onset signals. Specifically, in the fluctuation-driven regime associated with sparse spiking, rate and temporal coding are both paradoxically improved by the strong synaptic noise characteristic of the intact cortex. Our results demonstrate that multiplexed coding by S1 pyramidal neurons is not only feasible under in vivo conditions, but that background synaptic noise is actually beneficial.
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17
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Ostos S, Aparicio G, Fernaud-Espinosa I, DeFelipe J, Muñoz A. Quantitative analysis of the GABAergic innervation of the soma and axon initial segment of pyramidal cells in the human and mouse neocortex. Cereb Cortex 2022; 33:3882-3909. [PMID: 36058205 DOI: 10.1093/cercor/bhac314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/16/2022] [Accepted: 07/17/2022] [Indexed: 11/13/2022] Open
Abstract
Perisomatic GABAergic innervation in the cerebral cortex is carried out mostly by basket and chandelier cells, which differentially participate in the control of pyramidal cell action potential output and synchronization. These cells establish multiple synapses with the cell body (and proximal dendrites) and the axon initial segment (AIS) of pyramidal neurons, respectively. Using multiple immunofluorescence, confocal microscopy and 3D quantification techniques, we have estimated the number and density of GABAergic boutons on the cell body and AIS of pyramidal neurons located through cortical layers of the human and mouse neocortex. The results revealed, in both species, that there is clear variability across layers regarding the density and number of perisomatic GABAergic boutons. We found a positive linear correlation between the surface area of the soma, or the AIS, and the number of GABAergic terminals in apposition to these 2 neuronal domains. Furthermore, the density of perisomatic GABAergic boutons was higher in the human cortex than in the mouse. These results suggest a selectivity for the GABAergic innervation of the cell body and AIS that might be related to the different functional attributes of the microcircuits in which neurons from different layers are involved in both human and mouse.
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Affiliation(s)
- Sandra Ostos
- Departamento de Neurobiología Funcional y de Sistemas, Instituto Cajal (CSIC), Avenida Doctor Arce 37, 28002, Madrid, Spain.,Laboratorio Cajal de Circuitos Corticales (CTB), Universidad Politécnica de Madrid, Campus de Montegancedo, 28223, Pozuelo de Alarcón, Madrid, Spain
| | - Guillermo Aparicio
- Departamento de Neurobiología Funcional y de Sistemas, Instituto Cajal (CSIC), Avenida Doctor Arce 37, 28002, Madrid, Spain.,Laboratorio Cajal de Circuitos Corticales (CTB), Universidad Politécnica de Madrid, Campus de Montegancedo, 28223, Pozuelo de Alarcón, Madrid, Spain
| | - Isabel Fernaud-Espinosa
- Departamento de Neurobiología Funcional y de Sistemas, Instituto Cajal (CSIC), Avenida Doctor Arce 37, 28002, Madrid, Spain.,Laboratorio Cajal de Circuitos Corticales (CTB), Universidad Politécnica de Madrid, Campus de Montegancedo, 28223, Pozuelo de Alarcón, Madrid, Spain
| | - Javier DeFelipe
- Departamento de Neurobiología Funcional y de Sistemas, Instituto Cajal (CSIC), Avenida Doctor Arce 37, 28002, Madrid, Spain.,Laboratorio Cajal de Circuitos Corticales (CTB), Universidad Politécnica de Madrid, Campus de Montegancedo, 28223, Pozuelo de Alarcón, Madrid, Spain.,CIBERNED, Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, Avenida Monforte de Lemos, 3-5, 28029 Madrid, Spain
| | - Alberto Muñoz
- Departamento de Neurobiología Funcional y de Sistemas, Instituto Cajal (CSIC), Avenida Doctor Arce 37, 28002, Madrid, Spain.,Laboratorio Cajal de Circuitos Corticales (CTB), Universidad Politécnica de Madrid, Campus de Montegancedo, 28223, Pozuelo de Alarcón, Madrid, Spain.,Departamento de Biología Celular, Universidad Complutense, José Antonio Novais 12, 28040 Madrid, Spain
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18
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Knodel MM, Dutta Roy R, Wittum G. Influence of T-Bar on Calcium Concentration Impacting Release Probability. Front Comput Neurosci 2022; 16:855746. [PMID: 35586479 PMCID: PMC9108211 DOI: 10.3389/fncom.2022.855746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 03/09/2022] [Indexed: 11/25/2022] Open
Abstract
The relation of form and function, namely the impact of the synaptic anatomy on calcium dynamics in the presynaptic bouton, is a major challenge of present (computational) neuroscience at a cellular level. The Drosophila larval neuromuscular junction (NMJ) is a simple model system, which allows studying basic effects in a rather simple way. This synapse harbors several special structures. In particular, in opposite to standard vertebrate synapses, the presynaptic boutons are rather large, and they have several presynaptic zones. In these zones, different types of anatomical structures are present. Some of the zones bear a so-called T-bar, a particular anatomical structure. The geometric form of the T-bar resembles the shape of the letter “T” or a table with one leg. When an action potential arises, calcium influx is triggered. The probability of vesicle docking and neurotransmitter release is superlinearly proportional to the concentration of calcium close to the vesicular release site. It is tempting to assume that the T-bar causes some sort of calcium accumulation and hence triggers a higher release probability and thus enhances neurotransmitter exocytosis. In order to study this influence in a quantitative manner, we constructed a typical T-bar geometry and compared the calcium concentration close to the active zones (AZs). We compared the case of synapses with and without T-bars. Indeed, we found a substantial influence of the T-bar structure on the presynaptic calcium concentrations close to the AZs, indicating that this anatomical structure increases vesicle release probability. Therefore, our study reveals how the T-bar zone implies a strong relation between form and function. Our study answers the question of experimental studies (namely “Wichmann and Sigrist, Journal of neurogenetics 2010”) concerning the sense of the anatomical structure of the T-bar.
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Affiliation(s)
- Markus M. Knodel
- Goethe Center for Scientific Computing (GCSC), Goethe Universität Frankfurt, Frankfurt, Germany
- *Correspondence: Markus M. Knodel ; orcid.org/0000-0001-8739-0803
| | | | - Gabriel Wittum
- Goethe Center for Scientific Computing (GCSC), Goethe Universität Frankfurt, Frankfurt, Germany
- Applied Mathematics and Computational Science, Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
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19
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Rogers ER, Zander HJ, Lempka SF. Neural Recruitment During Conventional, Burst, and 10-kHz Spinal Cord Stimulation for Pain. THE JOURNAL OF PAIN 2022; 23:434-449. [PMID: 34583022 PMCID: PMC8925309 DOI: 10.1016/j.jpain.2021.09.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 09/09/2021] [Accepted: 09/11/2021] [Indexed: 10/20/2022]
Abstract
Spinal cord stimulation (SCS) is a popular neurostimulation therapy for severe chronic pain. To improve stimulation efficacy, multiple modes are now used clinically, including conventional, burst, and 10-kHz SCS. Clinical observations have produced speculation that these modes target different neural elements and/or work via distinct mechanisms of action. However, in humans, these hypotheses cannot be conclusively answered via experimental methods. Therefore, we utilized computational modeling to assess the response of primary afferents, interneurons, and projection neurons to conventional, burst, and 10-kHz SCS. We found that local cell thresholds were always higher than afferent thresholds, arguing against direct recruitment of these local cells. Furthermore, although we observed relative threshold differences between conventional, burst, and 10-kHz SCS, the recruitment order was the same. Finally, contrary to previous reports, axon collateralization produced complex changes in activation thresholds of primary afferents. These results motivate future work to contextualize clinical observations across SCS paradigms. PERSPECTIVE: This article presents the first computational modeling study to investigate neural recruitment during conventional, burst, and 10-kilohertz spinal cord stimulation for chronic pain within a single modeling framework. The results provide insight into these treatments' unknown mechanisms of action and offer context to interpreting clinical observations.
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Affiliation(s)
- Evan R. Rogers
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA,Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Hans J. Zander
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA,Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Scott F. Lempka
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA,Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA,Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
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20
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Ultrafast population coding and axo-somatic compartmentalization. PLoS Comput Biol 2022; 18:e1009775. [PMID: 35041645 PMCID: PMC8797191 DOI: 10.1371/journal.pcbi.1009775] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 01/28/2022] [Accepted: 12/16/2021] [Indexed: 02/05/2023] Open
Abstract
Populations of cortical neurons respond to common input within a millisecond. Morphological features and active ion channel properties were suggested to contribute to this astonishing processing speed. Here we report an exhaustive study of ultrafast population coding for varying axon initial segment (AIS) location, soma size, and axonal current properties. In particular, we studied their impact on two experimentally observed features 1) precise action potential timing, manifested in a wide-bandwidth dynamic gain, and 2) high-frequency boost under slowly fluctuating correlated input. While the density of axonal channels and their distance from the soma had a very small impact on bandwidth, it could be moderately improved by increasing soma size. When the voltage sensitivity of axonal currents was increased we observed ultrafast coding and high-frequency boost. We conclude that these computationally relevant features are strongly dependent on axonal ion channels’ voltage sensitivity, but not their number or exact location. We point out that ion channel properties, unlike dendrite size, can undergo rapid physiological modification, suggesting that the temporal accuracy of neuronal population encoding could be dynamically regulated. Our results are in line with recent experimental findings in AIS pathologies and establish a framework to study structure-function relations in AIS molecular design. In large nervous systems, a signal often diverges to hundreds or thousands of neurons. This population’s spike rate can track changes in this common input for frequencies up to several hundred Hertz. This ultrafast population response is experimentally well established and critically impacts cortical information processing. Its underlying biophysical determinants, however, are not understood. Experiments suggest that the ion channels at the axon initial segment strongly contribute to the ultrafast response, but recent theoretical studies emphasize the importance of neuron morphology and the resulting resistive coupling between axon and somato-dendritic compartments. We provide an exhaustive analysis of the population response of a simplified multi-compartment model. We vary the axo-somatic interaction and also active axonal properties and compare models at equivalent working points, avoiding bias. This approach provides a guideline for future experimental and theoretical studies. In this framework, the population response is closely associated with the AP generation speed at the AP initiation site, which is mostly determined by axonal ion channel voltage sensitivity. The resistive axo-somatic coupling has an additional modulatory influence. These insights are expected to hold for encoding mechanisms of more sophisticated models, suggesting that physiological changes to axonal ion channels could modulate the population response rapidly.
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21
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Resurgent Na + currents promote ultrafast spiking in projection neurons that drive fine motor control. Nat Commun 2021; 12:6762. [PMID: 34799550 PMCID: PMC8604930 DOI: 10.1038/s41467-021-26521-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 10/08/2021] [Indexed: 11/29/2022] Open
Abstract
The underlying mechanisms that promote precise spiking in upper motor neurons controlling fine motor skills are not well understood. Here we report that projection neurons in the adult zebra finch song nucleus RA display robust high-frequency firing, ultra-narrow spike waveforms, superfast Na+ current inactivation kinetics, and large resurgent Na+ currents (INaR). These properties of songbird pallial motor neurons closely resemble those of specialized large pyramidal neurons in mammalian primary motor cortex. They emerge during the early phases of song development in males, but not females, coinciding with a complete switch of Na+ channel subunit expression from Navβ3 to Navβ4. Dynamic clamping and dialysis of Navβ4's C-terminal peptide into juvenile RA neurons provide evidence that Navβ4, and its associated INaR, promote neuronal excitability. We thus propose that INaR modulates the excitability of upper motor neurons that are required for the execution of fine motor skills.
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22
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Douw L, Nissen IA, Fitzsimmons SMDD, Santos FAN, Hillebrand A, van Straaten ECW, Stam CJ, De Witt Hamer PC, Baayen JC, Klein M, Reijneveld JC, Heyer DB, Verhoog MB, Wilbers R, Hunt S, Mansvelder HD, Geurts JJG, de Kock CPJ, Goriounova NA. Cellular Substrates of Functional Network Integration and Memory in Temporal Lobe Epilepsy. Cereb Cortex 2021; 32:2424-2436. [PMID: 34564728 PMCID: PMC9157285 DOI: 10.1093/cercor/bhab349] [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: 05/18/2021] [Revised: 08/19/2021] [Accepted: 08/22/2021] [Indexed: 11/12/2022] Open
Abstract
Temporal lobe epilepsy (TLE) patients are at risk of memory deficits, which have been linked to functional network disturbances, particularly of integration of the default mode network (DMN). However, the cellular substrates of functional network integration are unknown. We leverage a unique cross-scale dataset of drug-resistant TLE patients (n = 31), who underwent pseudo resting-state functional magnetic resonance imaging (fMRI), resting-state magnetoencephalography (MEG) and/or neuropsychological testing before neurosurgery. fMRI and MEG underwent atlas-based connectivity analyses. Functional network centrality of the lateral middle temporal gyrus, part of the DMN, was used as a measure of local network integration. Subsequently, non-pathological cortical tissue from this region was used for single cell morphological and electrophysiological patch-clamp analysis, assessing integration in terms of total dendritic length and action potential rise speed. As could be hypothesized, greater network centrality related to better memory performance. Moreover, greater network centrality correlated with more integrative properties at the cellular level across patients. We conclude that individual differences in cognitively relevant functional network integration of a DMN region are mirrored by differences in cellular integrative properties of this region in TLE patients. These findings connect previously separate scales of investigation, increasing translational insight into focal pathology and large-scale network disturbances in TLE.
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Affiliation(s)
- Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands.,Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 02129 MA, Charlestown, USA
| | - Ida A Nissen
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Sophie M D D Fitzsimmons
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Fernando A N Santos
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Elisabeth C W van Straaten
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Philip C De Witt Hamer
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center Amsterdam Brain Tumor Center Amsterdam, 1081 HV, Amsterdam, the Netherlands
| | - Johannes C Baayen
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center Amsterdam Brain Tumor Center Amsterdam, 1081 HV, Amsterdam, the Netherlands
| | - Martin Klein
- Department of Medical Psychology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center Amsterdam Brain Tumor Center Amsterdam, 1081 HV, Amsterdam, the Netherlands
| | - Jaap C Reijneveld
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, VUmc Cancer Center Amsterdam Brain Tumor Center Amsterdam, 1081 HV, Amsterdam, the Netherlands.,Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede 2103 SW, Heemstede, the Netherlands
| | - Djai B Heyer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Matthijs B Verhoog
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands.,Department of Human Biology, Division of Cell Biology, Neuroscience Institute, University of Cape Town, 7935, Cape Town, South Africa
| | - René Wilbers
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Sarah Hunt
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Christiaan P J de Kock
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
| | - Natalia A Goriounova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HV, Amsterdam, the Netherlands
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23
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Heyer DB, Wilbers R, Galakhova AA, Hartsema E, Braak S, Hunt S, Verhoog MB, Muijtjens ML, Mertens EJ, Idema S, Baayen JC, de Witt Hamer P, Klein M, McGraw M, Lein ES, de Kock CPJ, Mansvelder HD, Goriounova NA. Verbal and General IQ Associate with Supragranular Layer Thickness and Cell Properties of the Left Temporal Cortex. Cereb Cortex 2021; 32:2343-2357. [PMID: 34550325 PMCID: PMC9157308 DOI: 10.1093/cercor/bhab330] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/10/2021] [Accepted: 08/11/2021] [Indexed: 11/27/2022] Open
Abstract
The left temporal lobe is an integral part of the language system and its cortical structure and function associate with general intelligence. However, whether cortical laminar architecture and cellular properties of this brain area relate to verbal intelligence is unknown. Here, we addressed this using histological analysis and cellular recordings of neurosurgically resected temporal cortex in combination with presurgical IQ scores. We find that subjects with higher general and verbal IQ scores have thicker left (but not right) temporal cortex (Brodmann area 21, BA21). The increased thickness is due to the selective increase in layers 2 and 3 thickness, accompanied by lower neuron densities, and larger dendrites and cell body size of pyramidal neurons in these layers. Furthermore, these neurons sustain faster action potential kinetics, which improves information processing. Our results indicate that verbal mental ability associates with selective adaptations of supragranular layers and their cellular micro-architecture and function in left, but not right temporal cortex.
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Affiliation(s)
- D B Heyer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - R Wilbers
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - A A Galakhova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - E Hartsema
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - S Braak
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - S Hunt
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - M B Verhoog
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands.,Department of Human Biology, Neuroscience Institute, University of Cape Town, Cape Town 7925, South Africa
| | - M L Muijtjens
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - E J Mertens
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - S Idema
- Department of Neurosurgery, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - J C Baayen
- Department of Neurosurgery, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - P de Witt Hamer
- Department of Neurosurgery, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - M Klein
- Department of Medical Psychology, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam 1081HZ, The Netherlands
| | - M McGraw
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - E S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - C P J de Kock
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - H D Mansvelder
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - N A Goriounova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
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24
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Harkin EF, Shen PR, Goel A, Richards BA, Naud R. Parallel and Recurrent Cascade Models as a Unifying Force for Understanding Sub-cellular Computation. Neuroscience 2021; 489:200-215. [PMID: 34358629 DOI: 10.1016/j.neuroscience.2021.07.026] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 07/06/2021] [Accepted: 07/25/2021] [Indexed: 11/15/2022]
Abstract
Neurons are very complicated computational devices, incorporating numerous non-linear processes, particularly in their dendrites. Biophysical models capture these processes directly by explicitly modelling physiological variables, such as ion channels, current flow, membrane capacitance, etc. However, another option for capturing the complexities of real neural computation is to use cascade models, which treat individual neurons as a cascade of linear and non-linear operations, akin to a multi-layer artificial neural network. Recent research has shown that cascade models can capture single-cell computation well, but there are still a number of sub-cellular, regenerative dendritic phenomena that they cannot capture, such as the interaction between sodium, calcium, and NMDA spikes in different compartments. Here, we propose that it is possible to capture these additional phenomena using parallel, recurrent cascade models, wherein an individual neuron is modelled as a cascade of parallel linear and non-linear operations that can be connected recurrently, akin to a multi-layer, recurrent, artificial neural network. Given their tractable mathematical structure, we show that neuron models expressed in terms of parallel recurrent cascades can themselves be integrated into multi-layered artificial neural networks and trained to perform complex tasks. We go on to discuss potential implications and uses of these models for artificial intelligence. Overall, we argue that parallel, recurrent cascade models provide an important, unifying tool for capturing single-cell computation and exploring the algorithmic implications of physiological phenomena.
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Affiliation(s)
- Emerson F Harkin
- uOttawa Brain and Mind Institute, Centre for Neural Dynamics, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Peter R Shen
- Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada
| | - Anish Goel
- Lisgar Collegiate Institute, Ottawa, ON, Canada
| | - Blake A Richards
- Mila, Montréal, QC, Canada; Montreal Neurological Institute, Montréal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada; School of Computer Science, McGill University, Montréal, QC, Canada.
| | - Richard Naud
- uOttawa Brain and Mind Institute, Centre for Neural Dynamics, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada; Department of Physics, University of Ottawa, Ottawa, ON, Canada.
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25
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Benavides-Piccione R, Rojo C, Kastanauskaite A, DeFelipe J. Variation in Pyramidal Cell Morphology Across the Human Anterior Temporal Lobe. Cereb Cortex 2021; 31:3592-3609. [PMID: 33723567 PMCID: PMC8258433 DOI: 10.1093/cercor/bhab034] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 02/03/2021] [Accepted: 02/04/2021] [Indexed: 11/13/2022] Open
Abstract
Pyramidal neurons are the most abundant and characteristic neuronal type in the cerebral cortex and their dendritic spines are the main postsynaptic elements of cortical excitatory synapses. Previous studies have shown that pyramidal cell structure differs across layers, cortical areas, and species. However, within the human cortex, the pyramidal dendritic morphology has been quantified in detail in relatively few cortical areas. In the present work, we performed intracellular injections of Lucifer Yellow at several distances from the temporal pole. We found regional differences in pyramidal cell morphology, which showed large inter-individual variability in most of the morphological variables measured. However, some values remained similar in all cases. The smallest and least complex cells in the most posterior temporal region showed the greatest dendritic spine density. Neurons in the temporal pole showed the greatest sizes with the highest number of spines. Layer V cells were larger, more complex, and had a greater number of dendritic spines than those in layer III. The present results suggest that, while some aspects of pyramidal structure are conserved, there are specific variations across cortical regions, and species.
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Affiliation(s)
- Ruth Benavides-Piccione
- Instituto Cajal, Consejo Superior de Investigaciones Científicas, Madrid 28002, Spain.,Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid 28223, Spain.,Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Madrid 28031, Spain
| | - Concepcion Rojo
- Sección Departamental de Anatomía y Embriología, Facultad de Veterinaria, Universidad Complutense de Madrid, Madrid 28040, Spain
| | - Asta Kastanauskaite
- Instituto Cajal, Consejo Superior de Investigaciones Científicas, Madrid 28002, Spain.,Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid 28223, Spain
| | - Javier DeFelipe
- Instituto Cajal, Consejo Superior de Investigaciones Científicas, Madrid 28002, Spain.,Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid 28223, Spain.,Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Madrid 28031, Spain
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26
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Is there a “g-neuron”? Establishing a systematic link between general intelligence (g) and the von Economo neuron. INTELLIGENCE 2021. [DOI: 10.1016/j.intell.2021.101540] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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27
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Aldohbeyb AA, Vigh J, Lear KL. New methods for quantifying rapidity of action potential onset differentiate neuron types. PLoS One 2021; 16:e0247242. [PMID: 33831000 PMCID: PMC8032118 DOI: 10.1371/journal.pone.0247242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 02/03/2021] [Indexed: 11/23/2022] Open
Abstract
Two new methods for quantifying the rapidity of action potential onset have lower relative standard deviations and better distinguish neuron cell types than current methods. Action potentials (APs) in most central mammalian neurons exhibit sharp onset dynamics. The main views explaining such an abrupt onset differ. Some studies suggest sharp onsets reflect cooperative sodium channels activation, while others suggest they reflect AP backpropagation from the axon initial segment. However, AP onset rapidity is defined subjectively in these studies, often using the slope at an arbitrary value on the phase plot. Thus, we proposed more systematic methods using the membrane potential's second-time derivative ([Formula: see text]) peak width. Here, the AP rapidity was measured for four different cortical and hippocampal neuron types using four quantification methods: the inverse of full-width at the half maximum of the [Formula: see text] peak (IFWd2), the inverse of half-width at the half maximum of the [Formula: see text] peak (IHWd2), the phase plot slope, and the error ratio method. The IFWd2 and IHWd2 methods show the smallest variation among neurons of the same type. Furthermore, the AP rapidity, using the [Formula: see text] peak width methods, significantly differentiates between different types of neurons, indicating that AP rapidity can be used to classify neuron types. The AP rapidity measured using the IFWd2 method was able to differentiate between all four neuron types analyzed. Therefore, the [Formula: see text] peak width methods provide another sensitive tool to investigate the mechanisms impacting the AP onset dynamics.
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Affiliation(s)
- Ahmed A. Aldohbeyb
- School of Biomedical Engineering, Colorado State University, Fort Collins, CO, United States of America
- Department of Biomedical Technology, King Saud University, Riyadh, Kingdom of Saudi Arabia
| | - Jozsef Vigh
- School of Biomedical Engineering, Colorado State University, Fort Collins, CO, United States of America
- Department of Biomedical Sciences, Colorado State University, Fort Collins, CO, United States of America
| | - Kevin L. Lear
- School of Biomedical Engineering, Colorado State University, Fort Collins, CO, United States of America
- Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO, United States of America
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28
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Mihaljević B, Larrañaga P, Bielza C. Comparing the Electrophysiology and Morphology of Human and Mouse Layer 2/3 Pyramidal Neurons With Bayesian Networks. Front Neuroinform 2021; 15:580873. [PMID: 33679362 PMCID: PMC7930221 DOI: 10.3389/fninf.2021.580873] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 01/14/2021] [Indexed: 11/13/2022] Open
Abstract
Pyramidal neurons are the most common neurons in the cerebral cortex. Understanding how they differ between species is a key challenge in neuroscience. We compared human temporal cortex and mouse visual cortex pyramidal neurons from the Allen Cell Types Database in terms of their electrophysiology and dendritic morphology. We found that, among other differences, human pyramidal neurons had a higher action potential threshold voltage, a lower input resistance, and larger dendritic arbors. We learned Gaussian Bayesian networks from the data in order to identify correlations and conditional independencies between the variables and compare them between the species. We found strong correlations between electrophysiological and morphological variables in both species. In human cells, electrophysiological variables were correlated even with morphological variables that are not directly related to dendritic arbor size or diameter, such as mean bifurcation angle and mean branch tortuosity. Cortical depth was correlated with both electrophysiological and morphological variables in both species, and its effect on electrophysiology could not be explained in terms of the morphological variables. For some variables, the effect of cortical depth was opposite in the two species. Overall, the correlations among the variables differed strikingly between human and mouse neurons. Besides identifying correlations and conditional independencies, the learned Bayesian networks might be useful for probabilistic reasoning regarding the morphology and electrophysiology of pyramidal neurons.
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Affiliation(s)
- Bojan Mihaljević
- Computational Intelligence Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Boadilla del Monte, Spain
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29
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Monosynaptic inference via finely-timed spikes. J Comput Neurosci 2021; 49:131-157. [PMID: 33507429 DOI: 10.1007/s10827-020-00770-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 09/04/2020] [Accepted: 10/19/2020] [Indexed: 10/22/2022]
Abstract
Observations of finely-timed spike relationships in population recordings have been used to support partial reconstruction of neural microcircuit diagrams. In this approach, fine-timescale components of paired spike train interactions are isolated and subsequently attributed to synaptic parameters. Recent perturbation studies strengthen the case for such an inference, yet the complete set of measurements needed to calibrate statistical models is unavailable. To address this gap, we study features of pairwise spiking in a large-scale in vivo dataset where presynaptic neurons were explicitly decoupled from network activity by juxtacellular stimulation. We then construct biophysical models of paired spike trains to reproduce the observed phenomenology of in vivo monosynaptic interactions, including both fine-timescale spike-spike correlations and firing irregularity. A key characteristic of these models is that the paired neurons are coupled by rapidly-fluctuating background inputs. We quantify a monosynapse's causal effect by comparing the postsynaptic train with its counterfactual, when the monosynapse is removed. Subsequently, we develop statistical techniques for estimating this causal effect from the pre- and post-synaptic spike trains. A particular focus is the justification and application of a nonparametric separation of timescale principle to implement synaptic inference. Using simulated data generated from the biophysical models, we characterize the regimes in which the estimators accurately identify the monosynaptic effect. A secondary goal is to initiate a critical exploration of neurostatistical assumptions in terms of biophysical mechanisms, particularly with regards to the challenging but arguably fundamental issue of fast, unobservable nonstationarities in background dynamics.
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30
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Glutamatergic Dysfunction and Synaptic Ultrastructural Alterations in Schizophrenia and Autism Spectrum Disorder: Evidence from Human and Rodent Studies. Int J Mol Sci 2020; 22:ijms22010059. [PMID: 33374598 PMCID: PMC7793137 DOI: 10.3390/ijms22010059] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 12/15/2020] [Accepted: 12/22/2020] [Indexed: 12/12/2022] Open
Abstract
The correlation between dysfunction in the glutamatergic system and neuropsychiatric disorders, including schizophrenia and autism spectrum disorder, is undisputed. Both disorders are associated with molecular and ultrastructural alterations that affect synaptic plasticity and thus the molecular and physiological basis of learning and memory. Altered synaptic plasticity, accompanied by changes in protein synthesis and trafficking of postsynaptic proteins, as well as structural modifications of excitatory synapses, are critically involved in the postnatal development of the mammalian nervous system. In this review, we summarize glutamatergic alterations and ultrastructural changes in synapses in schizophrenia and autism spectrum disorder of genetic or drug-related origin, and briefly comment on the possible reversibility of these neuropsychiatric disorders in the light of findings in regular synaptic physiology.
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31
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Verbist C, Müller MG, Mansvelder HD, Legenstein R, Giugliano M. The location of the axon initial segment affects the bandwidth of spike initiation dynamics. PLoS Comput Biol 2020; 16:e1008087. [PMID: 32701953 PMCID: PMC7402515 DOI: 10.1371/journal.pcbi.1008087] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 08/04/2020] [Accepted: 06/22/2020] [Indexed: 11/19/2022] Open
Abstract
The dynamics and the sharp onset of action potential (AP) generation have recently been the subject of intense experimental and theoretical investigations. According to the resistive coupling theory, an electrotonic interplay between the site of AP initiation in the axon and the somato-dendritic load determines the AP waveform. This phenomenon not only alters the shape of APs recorded at the soma, but also determines the dynamics of excitability across a variety of time scales. Supporting this statement, here we generalize a previous numerical study and extend it to the quantification of the input-output gain of the neuronal dynamical response. We consider three classes of multicompartmental mathematical models, ranging from ball-and-stick simplified descriptions of neuronal excitability to 3D-reconstructed biophysical models of excitatory neurons of rodent and human cortical tissue. For each model, we demonstrate that increasing the distance between the axonal site of AP initiation and the soma markedly increases the bandwidth of neuronal response properties. We finally consider the Liquid State Machine paradigm, exploring the impact of altering the site of AP initiation at the level of a neuronal population, and demonstrate that an optimal distance exists to boost the computational performance of the network in a simple classification task. The neurons in the brain encode information through electrical impulses. The performance of a cell in terms of its ability to process and transfer information downstream thus depends heavily on the machinery of initiation of these impulses. In this work, we consider both the cell morphology and the biophysical properties of impulse initiation as the primary parameters that influence information processing in single neurons, as well as in networks. We specifically analyze the location of nerve impulse initiation along the cell’s axon and the way the neuron transfers incoming information. By using single-cell models of various complexity as well as network models, we conclude that information processing is sensitive to the geometrical details of impulse initiation.
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Affiliation(s)
- Christophe Verbist
- Molecular, Cellular, and Network Excitability Laboratory, Institute Born-Bunge and Department of Biomedical Sciences, Universiteit Antwerpen, Wilrijk, Belgium
- * E-mail: (CV); (MG)
| | - Michael G. Müller
- Institute of Theoretical Computer Science, Graz University of Technology, Graz, Austria
| | - Huibert D. Mansvelder
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Robert Legenstein
- Institute of Theoretical Computer Science, Graz University of Technology, Graz, Austria
| | - Michele Giugliano
- Molecular, Cellular, and Network Excitability Laboratory, Institute Born-Bunge and Department of Biomedical Sciences, Universiteit Antwerpen, Wilrijk, Belgium
- International School of Advanced Studies, Neuroscience Area, Trieste, Italy
- * E-mail: (CV); (MG)
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32
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Borda Bossana S, Verbist C, Giugliano M. Homogeneous and Narrow Bandwidth of Spike Initiation in Rat L1 Cortical Interneurons. Front Cell Neurosci 2020; 14:118. [PMID: 32625063 PMCID: PMC7313227 DOI: 10.3389/fncel.2020.00118] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 04/14/2020] [Indexed: 12/02/2022] Open
Abstract
The cortical layer 1 (L1) contains a population of GABAergic interneurons, considered a key component of information integration, processing, and relaying in neocortical networks. In fact, L1 interneurons combine top–down information with feed-forward sensory inputs in layer 2/3 and 5 pyramidal cells (PCs), while filtering their incoming signals. Despite the importance of L1 for network emerging phenomena, little is known on the dynamics of the spike initiation and the encoding properties of its neurons. Using acute brain tissue slices from the rat neocortex, combined with the analysis of an existing database of model neurons, we investigated the dynamical transfer properties of these cells by sampling an entire population of known “electrical classes” and comparing experiments and model predictions. We found the bandwidth of spike initiation to be significantly narrower than in L2/3 and 5 PCs, with values below 100 cycle/s, but without significant heterogeneity in the cell response properties across distinct electrical types. The upper limit of the neuronal bandwidth was significantly correlated to the mean firing rate, as anticipated from theoretical studies but not reported for PCs. At high spectral frequencies, the magnitude of the neuronal response attenuated as a power-law, with an exponent significantly smaller than what was reported for pyramidal neurons and reminiscent of the dynamics of a “leaky” integrate-and-fire model of spike initiation. Finally, most of our in vitro results matched quantitatively the numerical simulations of the models as a further contribution to independently validate the models against novel experimental data.
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Affiliation(s)
- Stefano Borda Bossana
- Molecular, Cellular, and Network Excitability Laboratory, Department of Biomedical Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, Institute Born-Bunge, Universiteit Antwerpen, Wilrijk, Belgium
| | - Christophe Verbist
- Molecular, Cellular, and Network Excitability Laboratory, Department of Biomedical Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, Institute Born-Bunge, Universiteit Antwerpen, Wilrijk, Belgium
| | - Michele Giugliano
- Molecular, Cellular, and Network Excitability Laboratory, Department of Biomedical Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, Institute Born-Bunge, Universiteit Antwerpen, Wilrijk, Belgium.,Neuroscience Area, Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy
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33
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Poirazi P, Papoutsi A. Illuminating dendritic function with computational models. Nat Rev Neurosci 2020; 21:303-321. [PMID: 32393820 DOI: 10.1038/s41583-020-0301-7] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/25/2020] [Indexed: 02/06/2023]
Abstract
Dendrites have always fascinated researchers: from the artistic drawings by Ramon y Cajal to the beautiful recordings of today, neuroscientists have been striving to unravel the mysteries of these structures. Theoretical work in the 1960s predicted important dendritic effects on neuronal processing, establishing computational modelling as a powerful technique for their investigation. Since then, modelling of dendrites has been instrumental in driving neuroscience research in a targeted manner, providing experimentally testable predictions that range from the subcellular level to the systems level, and their relevance extends to fields beyond neuroscience, such as machine learning and artificial intelligence. Validation of modelling predictions often requires - and drives - new technological advances, thus closing the loop with theory-driven experimentation that moves the field forward. This Review features the most important, to our understanding, contributions of modelling of dendritic computations, including those pending experimental verification, and highlights studies of successful interactions between the modelling and experimental neuroscience communities.
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Affiliation(s)
- Panayiota Poirazi
- Institute of Molecular Biology & Biotechnology, Foundation for Research & Technology - Hellas, Heraklion, Crete, Greece.
| | - Athanasia Papoutsi
- Institute of Molecular Biology & Biotechnology, Foundation for Research & Technology - Hellas, Heraklion, Crete, Greece
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34
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Ofer N, Shefi O, Yaari G. Axonal Tree Morphology and Signal Propagation Dynamics Improve Interneuron Classification. Neuroinformatics 2020; 18:581-590. [PMID: 32346847 DOI: 10.1007/s12021-020-09466-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Neurons are diverse and can be differentiated by their morphological, electrophysiological, and molecular properties. Current morphology-based classification approaches largely rely on the dendritic tree structure or on the overall axonal projection layout. Here, we use data from public databases of neuronal reconstructions and membrane properties to study the characteristics of the axonal and dendritic trees for interneuron classification. We show that combining signal propagation patterns observed by biophysical simulations of the activity along ramified axonal trees with morphological parameters of the axonal and dendritic trees, significantly improve classification results compared to previous approaches. The classification schemes introduced here can be utilized for robust neuronal classification. Our work paves the way for understanding and utilizing form-function principles in realistic neuronal reconstructions.
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Affiliation(s)
- Netanel Ofer
- Faculty of Engineering, Bar Ilan University, Ramat Gan, 5290002, Israel.,Bar Ilan Institute of Nanotechnologies and Advanced Materials, Bar Ilan University, Ramat Gan, 5290002, Israel
| | - Orit Shefi
- Faculty of Engineering, Bar Ilan University, Ramat Gan, 5290002, Israel. .,Bar Ilan Institute of Nanotechnologies and Advanced Materials, Bar Ilan University, Ramat Gan, 5290002, Israel.
| | - Gur Yaari
- Faculty of Engineering, Bar Ilan University, Ramat Gan, 5290002, Israel.
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35
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Gowers RP, Timofeeva Y, Richardson MJE. Low-rate firing limit for neurons with axon, soma and dendrites driven by spatially distributed stochastic synapses. PLoS Comput Biol 2020; 16:e1007175. [PMID: 32310936 PMCID: PMC7217482 DOI: 10.1371/journal.pcbi.1007175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 05/12/2020] [Accepted: 01/27/2020] [Indexed: 11/18/2022] Open
Abstract
Analytical forms for neuronal firing rates are important theoretical tools for the analysis of network states. Since the 1960s, the majority of approaches have treated neurons as being electrically compact and therefore isopotential. These approaches have yielded considerable insight into how single-cell properties affect network activity; however, many neuronal classes, such as cortical pyramidal cells, are electrically extended objects. Calculation of the complex flow of electrical activity driven by stochastic spatio-temporal synaptic input streams in these structures has presented a significant analytical challenge. Here we demonstrate that an extension of the level-crossing method of Rice, previously used for compact cells, provides a general framework for approximating the firing rate of neurons with spatial structure. Even for simple models, the analytical approximations derived demonstrate a surprising richness including: independence of the firing rate to the electrotonic length for certain models, but with a form distinct to the point-like leaky integrate-and-fire model; a non-monotonic dependence of the firing rate on the number of dendrites receiving synaptic drive; a significant effect of the axonal and somatic load on the firing rate; and the role that the trigger position on the axon for spike initiation has on firing properties. The approach necessitates only calculating the mean and variances of the non-thresholded voltage and its rate of change in neuronal structures subject to spatio-temporal synaptic fluctuations. The combination of simplicity and generality promises a framework that can be built upon to incorporate increasing levels of biophysical detail and extend beyond the low-rate firing limit treated in this paper.
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Affiliation(s)
- Robert P. Gowers
- Mathematics for Real-World Systems Centre for Doctoral Training, University of Warwick, Coventry, United Kingdom
- Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Philippstrasse 13, Haus 4, Berlin, Germany
| | - Yulia Timofeeva
- Department of Computer Science, University of Warwick, Coventry, United Kingdom
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
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36
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Goethals S, Brette R. Theoretical relation between axon initial segment geometry and excitability. eLife 2020; 9:53432. [PMID: 32223890 PMCID: PMC7170651 DOI: 10.7554/elife.53432] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 03/30/2020] [Indexed: 12/29/2022] Open
Abstract
In most vertebrate neurons, action potentials are triggered at the distal end of the axon initial segment (AIS). Both position and length of the AIS vary across and within neuron types, with activity, development and pathology. What is the impact of AIS geometry on excitability? Direct empirical assessment has proven difficult because of the many potential confounding factors. Here, we carried a principled theoretical analysis to answer this question. We provide a simple formula relating AIS geometry and sodium conductance density to the somatic voltage threshold. A distal shift of the AIS normally produces a (modest) increase in excitability, but we explain how this pattern can reverse if a hyperpolarizing current is present at the AIS, due to resistive coupling with the soma. This work provides a theoretical tool to assess the significance of structural AIS plasticity for electrical function.
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Affiliation(s)
- Sarah Goethals
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Romain Brette
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
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37
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Lee K, Park TIH, Heppner P, Schweder P, Mee EW, Dragunow M, Montgomery JM. Human in vitro systems for examining synaptic function and plasticity in the brain. J Neurophysiol 2020; 123:945-965. [PMID: 31995449 DOI: 10.1152/jn.00411.2019] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The human brain shows remarkable complexity in its cellular makeup and function, which are distinct from nonhuman species, signifying the need for human-based research platforms for the study of human cellular neurophysiology and neuropathology. However, the use of adult human brain tissue for research purposes is hampered by technical, methodological, and accessibility challenges. One of the major problems is the limited number of in vitro systems that, in contrast, are readily available from rodent brain tissue. With recent advances in the optimization of protocols for adult human brain preparations, there is a significant opportunity for neuroscientists to validate their findings in human-based systems. This review addresses the methodological aspects, advantages, and disadvantages of human neuron in vitro systems, focusing on the unique properties of human neurons and synapses in neocortical microcircuits. These in vitro models provide the incomparable advantage of being a direct representation of the neurons that have formed part of the human brain until the point of recording, which cannot be replicated by animal models nor human stem-cell systems. Important distinct cellular mechanisms are observed in human neurons that may underlie the higher order cognitive abilities of the human brain. The use of human brain tissue in neuroscience research also raises important ethical, diversity, and control tissue limitations that need to be considered. Undoubtedly however, these human neuron systems provide critical information to increase the potential of translation of treatments from the laboratory to the clinic in a way animal models are failing to provide.
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Affiliation(s)
- Kevin Lee
- Department of Physiology, University of Auckland, Auckland, New Zealand.,Centre for Brain Research, University of Auckland, New Zealand
| | - Thomas I-H Park
- Centre for Brain Research, University of Auckland, New Zealand.,Department of Pharmacology, University of Auckland, Auckland, New Zealand
| | - Peter Heppner
- Centre for Brain Research, University of Auckland, New Zealand.,Department of Neurosurgery, Auckland City Hospital, Auckland, New Zealand
| | - Patrick Schweder
- Centre for Brain Research, University of Auckland, New Zealand.,Department of Neurosurgery, Auckland City Hospital, Auckland, New Zealand
| | - Edward W Mee
- Centre for Brain Research, University of Auckland, New Zealand.,Department of Neurosurgery, Auckland City Hospital, Auckland, New Zealand
| | - Michael Dragunow
- Centre for Brain Research, University of Auckland, New Zealand.,Department of Pharmacology, University of Auckland, Auckland, New Zealand
| | - Johanna M Montgomery
- Department of Physiology, University of Auckland, Auckland, New Zealand.,Centre for Brain Research, University of Auckland, New Zealand
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38
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Abstract
Axons functionally link the somato-dendritic compartment to synaptic terminals. Structurally and functionally diverse, they accomplish a central role in determining the delays and reliability with which neuronal ensembles communicate. By combining their active and passive biophysical properties, they ensure a plethora of physiological computations. In this review, we revisit the biophysics of generation and propagation of electrical signals in the axon and their dynamics. We further place the computational abilities of axons in the context of intracellular and intercellular coupling. We discuss how, by means of sophisticated biophysical mechanisms, axons expand the repertoire of axonal computation, and thereby, of neural computation.
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Affiliation(s)
- Pepe Alcami
- Division of Neurobiology, Department of Biology II, Ludwig-Maximilians-Universitaet Muenchen, Martinsried, Germany
- Department of Behavioural Neurobiology, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Ahmed El Hady
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States
- Howard Hughes Medical Institute, Princeton University, Princeton, NJ, United States
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39
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Dynamic Gain Analysis Reveals Encoding Deficiencies in Cortical Neurons That Recover from Hypoxia-Induced Spreading Depolarizations. J Neurosci 2019; 39:7790-7800. [PMID: 31399533 DOI: 10.1523/jneurosci.3147-18.2019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2018] [Revised: 07/23/2019] [Accepted: 07/23/2019] [Indexed: 11/21/2022] Open
Abstract
Cortical regions that are damaged by insults, such as ischemia, hypoxia, and trauma, frequently generate spreading depolarization (SD). At the neuronal level, SDs entail complete breakdown of ionic gradients, persisting for seconds to minutes. It is unclear whether these transient events have a more lasting influence on neuronal function. Here, we describe electrophysiological changes in cortical neurons after recovery from hypoxia-induced SD. When examined with standard measures of neuronal excitability several hours after recovery from SD, layer 5 pyramidal neurons in brain slices from mice of either sex appear surprisingly normal. However, we here introduce an additional parameter, dynamic gain, which characterizes the bandwidth of action potential encoding by a neuron, and thereby reflects its potential efficiency in a multineuronal circuit. We find that the ability of neurons that recover from SD to track high-frequency inputs is markedly curtailed; exposure to hypoxia did not have this effect when SD was prevented pharmacologically. Staining for Ankyrin G revealed at least a fourfold decrease in the number of intact axon initial segments in post-SD slices. Since this effect, along with the effect on encoding, was blocked by an inhibitor of the Ca2+-dependent enzyme, calpain, we conclude that both effects were mediated by the SD-induced rise in intracellular Ca2+ Although effects of calpain activation were detected in the axon initial segment, changes in soma-dendritic compartments may also be involved. Whatever the precise molecular mechanism, our findings indicate that in the context of cortical circuit function, effectiveness of neurons that survive SD may be limited.SIGNIFICANCE STATEMENT Spreading depolarization, which commonly accompanies cortical injury, entails transient massive breakdown of neuronal ionic gradients. The function of cortical neurons that recover from hypoxia-induced spreading depolarization is not obviously abnormal when tested for usual measures of neuronal excitability. However, we now demonstrate that they have a reduced bandwidth, reflecting a significant impairment of their ability to precisely encode high-frequency components of their synaptic input in output spike trains. Thus, neurons that recover from spreading depolarizations are less able to function normally as elements in the multineuronal cortical circuitry. These changes are correlated with activation of the calcium-dependent enzyme, calpain.
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40
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Qu G, Fan B, Fu X, Yu Y. The Impact of Frequency Scale on the Response Sensitivity and Reliability of Cortical Neurons to 1/f β Input Signals. Front Cell Neurosci 2019; 13:311. [PMID: 31354432 PMCID: PMC6637762 DOI: 10.3389/fncel.2019.00311] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 06/25/2019] [Indexed: 12/16/2022] Open
Abstract
What type of principle features intrinsic inside of the fluctuated input signals could drive neurons with the maximal excitations is one of the crucial neural coding issues. In this article, we examined both experimentally and theoretically the cortical neuronal responsivity (including firing rate and spike timing reliability) to input signals with different intrinsic correlational statistics (e.g., white-type noise, showed 1/f0 power spectrum, pink noise 1/f, and brown noises 1/f2) and different frequency ranges. Our results revealed that the response sensitivity and reliability of cortical neurons is much higher in response to 1/f noise stimuli with long-term correlations than 1/f0 with short-term correlations for a broad frequency range, and also higher than 1/f2 for all frequency ranges. In addition, we found that neuronal sensitivity diverges to opposite directions for 1/f noise comparing with 1/f0 white noise as a function of cutoff frequency of input signal. As the cutoff frequency is progressively increased from 50 to 1,000 Hz, the neuronal responsiveness increased gradually for 1/f noise, while decreased exponentially for white noise. Computational simulations of a general cortical model revealed that, neuronal sensitivity and reliability to input signal statistics was majorly dominated by fast sodium inactivation, potassium activation, and membrane time constants.
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Affiliation(s)
| | | | | | - Yuguo Yu
- State Key Laboratory of Medical Neurobiology, School of Life Science, Human Phenome Institute, Institute of Brain Science, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
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41
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Kroon T, van Hugte E, van Linge L, Mansvelder HD, Meredith RM. Early postnatal development of pyramidal neurons across layers of the mouse medial prefrontal cortex. Sci Rep 2019; 9:5037. [PMID: 30911152 PMCID: PMC6433913 DOI: 10.1038/s41598-019-41661-9] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 03/12/2019] [Indexed: 12/24/2022] Open
Abstract
Mammalian neocortex is a highly layered structure. Each layer is populated by distinct subtypes of principal cells that are born at different times during development. While the differences between principal cells across layers have been extensively studied, it is not known how the developmental profiles of neurons in different layers compare. Here, we provide a detailed morphological and functional characterisation of pyramidal neurons in mouse mPFC during the first postnatal month, corresponding to known critical periods for synapse and neuron formation in mouse sensory neocortex. Our data demonstrate similar maturation profiles of dendritic morphology and intrinsic properties of pyramidal neurons in both deep and superficial layers. In contrast, the balance of synaptic excitation and inhibition differs in a layer-specific pattern from one to four postnatal weeks of age. Our characterisation of the early development and maturation of pyramidal neurons in mouse mPFC not only demonstrates a comparable time course of postnatal maturation to that in other neocortical circuits, but also implies that consideration of layer- and time-specific changes in pyramidal neurons may be relevant for studies in mouse models of neuropsychiatric and neurodevelopmental disorders.
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Affiliation(s)
- Tim Kroon
- Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands.
- MRC Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, New Hunt's House, Guy's Campus, London, SE1 1UL, UK.
| | - Eline van Hugte
- Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
- Department Cognitive Neurosciences, Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Geert Grooteplein 10 Noord, 6500 HB, Nijmegen, The Netherlands
| | - Lola van Linge
- Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
- Department of Functional Genomics, Center for Neurogenomics & Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
| | - Rhiannon M Meredith
- Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
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42
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Alpizar SA, Cho IH, Hoppa MB. Subcellular control of membrane excitability in the axon. Curr Opin Neurobiol 2019; 57:117-125. [PMID: 30784979 DOI: 10.1016/j.conb.2019.01.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 01/21/2019] [Indexed: 12/11/2022]
Abstract
Ion channels are microscopic pore proteins in the membrane that open and close in response to chemical and electrical stimuli. This simple concept underlies rapid electrical signaling in the brain as well as several important aspects of neural plasticity. Although the soma accounts for less than 1% of many neurons by membrane area, it has been the major site of measuring ion channel function. However, the axon is one of the longest processes found in cellular biology and hosts a multitude of critical signaling functions in the brain. Not only does the axon initiate and rapidly propagate action potentials (APs) across the brain but it also forms the presynaptic terminals that convert these electrical inputs into chemical outputs. Here, we review recent advances in the physiological role of ion channels within the diverse landscape of the axon and presynaptic terminals.
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Affiliation(s)
- Scott A Alpizar
- Dartmouth College, Department of Biological Sciences, Hanover, NH, United States
| | - In Ha Cho
- Dartmouth College, Department of Biological Sciences, Hanover, NH, United States
| | - Michael B Hoppa
- Dartmouth College, Department of Biological Sciences, Hanover, NH, United States.
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Goriounova NA, Mansvelder HD. Genes, Cells and Brain Areas of Intelligence. Front Hum Neurosci 2019; 13:44. [PMID: 30828294 PMCID: PMC6384251 DOI: 10.3389/fnhum.2019.00044] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2018] [Accepted: 01/25/2019] [Indexed: 12/18/2022] Open
Abstract
What is the neurobiological basis of human intelligence? The brains of some people seem to be more efficient than those of others. Understanding the biological foundations of these differences is of great interest to basic and applied neuroscience. Somehow, the secret must lie in the cells in our brain with which we think. However, at present, research into the neurobiology of intelligence is divided between two main strategies: brain imaging studies investigate macroscopic brain structure and function to identify brain areas involved in intelligence, while genetic associations studies aim to pinpoint genes and genetic loci associated with intelligence. Nothing is known about how properties of brain cells relate to intelligence. The emergence of transcriptomics and cellular neuroscience of intelligence might, however, provide a third strategy and bridge the gap between identified genes for intelligence and brain function and structure. Here, we discuss the latest developments in the search for the biological basis of intelligence. In particular, the recent availability of very large cohorts with hundreds of thousands of individuals have propelled exciting developments in the genetics of intelligence. Furthermore, we discuss the first studies that show that specific populations of brain cells associate with intelligence. Finally, we highlight how specific genes that have been identified generate cellular properties associated with intelligence and may ultimately explain structure and function of the brain areas involved. Thereby, the road is paved for a cellular understanding of intelligence, which will provide a conceptual scaffold for understanding how the constellation of identified genes benefit cellular functions that support intelligence.
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Affiliation(s)
- Natalia A. Goriounova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Neuroscience Amsterdam, VU University Amsterdam, Amsterdam, Netherlands
| | - Huibert D. Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Neuroscience Amsterdam, VU University Amsterdam, Amsterdam, Netherlands
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Tiroshi L, Goldberg JA. Population dynamics and entrainment of basal ganglia pacemakers are shaped by their dendritic arbors. PLoS Comput Biol 2019; 15:e1006782. [PMID: 30730886 PMCID: PMC6382172 DOI: 10.1371/journal.pcbi.1006782] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 02/20/2019] [Accepted: 01/10/2019] [Indexed: 11/30/2022] Open
Abstract
The theory of phase oscillators is an essential tool for understanding population dynamics of pacemaking neurons. GABAergic pacemakers in the substantia nigra pars reticulata (SNr), a main basal ganglia (BG) output nucleus, receive inputs from the direct and indirect pathways at distal and proximal regions of their dendritic arbors, respectively. We combine theory, optogenetic stimulation and electrophysiological experiments in acute brain slices to ask how dendritic properties impact the propensity of the various inputs, arriving at different locations along the dendrite, to recruit or entrain SNr pacemakers. By combining cable theory with sinusoidally-modulated optogenetic activation of either proximal somatodendritic regions or the entire somatodendritic arbor of SNr neurons, we construct an analytical model that accurately fits the empirically measured somatic current response to inputs arising from illuminating the soma and various portions of the dendritic field. We show that the extent of the dendritic tree that is illuminated generates measurable and systematic differences in the pacemaker’s phase response curve (PRC), causing a shift in its peak. Finally, we show that the divergent PRCs correctly predict differences in two major features of the collective dynamics of SNr neurons: the fidelity of population responses to sudden step-like changes in inputs; and the phase latency at which SNr neurons are entrained by rhythmic stimulation, which can occur in the BG under both physiological and pathophysiological conditions. Our novel method generates measurable and physiologically meaningful spatial effects, and provides the first empirical demonstration of how the collective responses of SNr pacemakers are determined by the transmission properties of their dendrites. SNr dendrites may serve to delay distal striatal inputs so that they impinge on the spike initiation zone simultaneously with pallidal and subthalamic inputs in order to guarantee a fair competition between the influence of the monosynaptic direct- and polysynaptic indirect pathways. The substantia nigra pars reticulata (SNr) is a main output nucleus of the basal ganglia (BG), where inputs from the competing direct and indirect pathways converge onto the same neurons. Interestingly, these inputs are differentially distributed with direct and indirect pathway projections arriving at distal and proximal regions of the dendritic arbor, respectively. We employ a novel method combining theory with electrophysiological experiments and optogenetics to study the distinct effects of inputs arriving at different locations along the dendrite. Our approach represents a useful compromise between complexity and reduction in modelling. Our work addresses the question of high fidelity encoding of inputs by networks of neurons in the new context of pacemaking neurons, which are driven to fire by their intrinsic dynamics rather than by a network state. We provide the first empirical demonstration that dendritic delays can introduce latencies in the responses of a population of neurons that are commensurate with synaptic delays, suggesting a new role for SNr dendrites with implications for BG function.
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Affiliation(s)
- Lior Tiroshi
- Department of Medical Neurobiology, Institute of Medical Research Israel–Canada, The Faculty of Medicine, Jerusalem, Israel
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Joshua A. Goldberg
- Department of Medical Neurobiology, Institute of Medical Research Israel–Canada, The Faculty of Medicine, Jerusalem, Israel
- * E-mail:
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Alpizar SA, Baker AL, Gulledge AT, Hoppa MB. Loss of Neurofascin-186 Disrupts Alignment of AnkyrinG Relative to Its Binding Partners in the Axon Initial Segment. Front Cell Neurosci 2019; 13:1. [PMID: 30723396 PMCID: PMC6349729 DOI: 10.3389/fncel.2019.00001] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2018] [Accepted: 01/07/2019] [Indexed: 12/14/2022] Open
Abstract
The axon initial segment (AIS) is a specialized region within the proximal portion of the axon that initiates action potentials thanks in large part to an enrichment of sodium channels. The scaffolding protein ankyrinG (AnkG) is essential for the recruitment of sodium channels as well as several other intracellular and extracellular proteins to the AIS. In the present study, we explore the role of the cell adhesion molecule (CAM) neurofascin-186 (NF-186) in arranging the individual molecular components of the AIS in cultured rat hippocampal neurons. Using a CRISPR depletion strategy to ablate NF expression, we found that the loss of NF selectively perturbed AnkG accumulation and its relative proximal distribution within the AIS. We found that the overexpression of sodium channels could restore AnkG accumulation, but not its altered distribution within the AIS without NF present. We go on to show that although the loss of NF altered AnkG distribution, sodium channel function within the AIS remained normal. Taken together, these results demonstrate that the regulation of AnkG and sodium channel accumulation within the AIS can occur independently of one another, potentially mediated by other binding partners such as NF.
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Affiliation(s)
- Scott A Alpizar
- Department of Biological Sciences, Dartmouth College, Hanover, NH, United States
| | - Arielle L Baker
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth College, Hanover, NH, United States
| | - Allan T Gulledge
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth College, Hanover, NH, United States
| | - Michael B Hoppa
- Department of Biological Sciences, Dartmouth College, Hanover, NH, United States
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Goriounova NA, Heyer DB, Wilbers R, Verhoog MB, Giugliano M, Verbist C, Obermayer J, Kerkhofs A, Smeding H, Verberne M, Idema S, Baayen JC, Pieneman AW, de Kock CP, Klein M, Mansvelder HD. Large and fast human pyramidal neurons associate with intelligence. eLife 2018; 7:41714. [PMID: 30561325 PMCID: PMC6363383 DOI: 10.7554/elife.41714] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 12/17/2018] [Indexed: 11/13/2022] Open
Abstract
It is generally assumed that human intelligence relies on efficient processing by neurons in our brain. Although grey matter thickness and activity of temporal and frontal cortical areas correlate with IQ scores, no direct evidence exists that links structural and physiological properties of neurons to human intelligence. Here, we find that high IQ scores and large temporal cortical thickness associate with larger, more complex dendrites of human pyramidal neurons. We show in silico that larger dendritic trees enable pyramidal neurons to track activity of synaptic inputs with higher temporal precision, due to fast action potential kinetics. Indeed, we find that human pyramidal neurons of individuals with higher IQ scores sustain fast action potential kinetics during repeated firing. These findings provide the first evidence that human intelligence is associated with neuronal complexity, action potential kinetics and efficient information transfer from inputs to output within cortical neurons. Our brains are made up of almost 100 billion brain cells. Each of them acts like a small chip: they collect, process and pass on information in the form of electrical signals. In brain areas that integrate different types of information, such as frontal and temporal lobes, brain cells have larger dendrites – long projections specialized to collect signals. Theoretical studies predict that larger dendrites help cells to initiate electrical signals faster. Because of difficulty in accessing human neurons, it has been unknown whether any of these features also relate to human intelligence. Previous studies have revealed that people with a higher IQ have a thicker outer layer (the cortex) in areas such as the frontal and temporal lobes. But does a thicker cortex also contain cells with larger dendrites and is their role different? To test whether smarter brains are equipped with faster and larger cells, Goriounova et al. studied 46 people who needed surgery for brain tumors or epilepsy. Each took an IQ test before the operation. To access the diseased tissue deep in the brain, the surgeon also removed small, undamaged samples of temporal lobe. These samples still contained living cells and their electrical signals were measured in the lab. The experiments showed that cells from people with a higher IQ had larger dendrites that transported information more quickly, especially when they are very active. Computer models were then used to understand how these findings can lead to more efficient information transfer in human neurons. Traditionally, research on human intelligence has focused on three main strategies: to study brain structure and function, to find genes associated with intelligence and to study the connection between our mind and behavior. Goriounova et al. are the first to take the single-cell perspective and link cell properties to human intelligence. The findings could help connect these separate approaches, and explain how genes for intelligence lead to thicker cortices and faster reaction times in people with higher IQ.
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Affiliation(s)
- Natalia A Goriounova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Djai B Heyer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - René Wilbers
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Matthijs B Verhoog
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Michele Giugliano
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium.,Department of Computer Science, University of Sheffield, Sheffield, United Kingdom.,Brain Mind Institute, Lausanne, Switzerland
| | - Christophe Verbist
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Joshua Obermayer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Amber Kerkhofs
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Harriët Smeding
- Department of Psychology, Stichting Epilepsie Instellingen Nederland (SEIN), Zwolle, The Netherlands
| | - Maaike Verberne
- Department of Psychology, Stichting Epilepsie Instellingen Nederland (SEIN), Zwolle, The Netherlands
| | - Sander Idema
- Department of Neurosurgery, VU medical center (VUmc), Amsterdam, The Netherlands
| | - Johannes C Baayen
- Department of Neurosurgery, VU medical center (VUmc), Amsterdam, The Netherlands
| | - Anton W Pieneman
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Christiaan Pj de Kock
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Martin Klein
- Department of Medical Psychology, VU medical center (VUmc), Amsterdam, The Netherlands
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Aberra AS, Peterchev AV, Grill WM. Biophysically realistic neuron models for simulation of cortical stimulation. J Neural Eng 2018; 15:066023. [PMID: 30127100 PMCID: PMC6239949 DOI: 10.1088/1741-2552/aadbb1] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
OBJECTIVE We implemented computational models of human and rat cortical neurons for simulating the neural response to cortical stimulation with electromagnetic fields. APPROACH We adapted model neurons from the library of Blue Brain models to reflect biophysical and geometric properties of both adult rat and human cortical neurons and coupled the model neurons to exogenous electric fields (E-fields). The models included 3D reconstructed axonal and dendritic arbors, experimentally-validated electrophysiological behaviors, and multiple, morphological variants within cell types. Using these models, we characterized the single-cell responses to intracortical microstimulation (ICMS) and uniform E-field with dc as well as pulsed currents. MAIN RESULTS The strength-duration and current-distance characteristics of the model neurons to ICMS agreed with published experimental results, as did the subthreshold polarization of cell bodies and axon terminals by uniform dc E-fields. For all forms of stimulation, the lowest threshold elements were terminals of the axon collaterals, and the dependence of threshold and polarization on spatial and temporal stimulation parameters was strongly affected by morphological features of the axonal arbor, including myelination, diameter, and branching. SIGNIFICANCE These results provide key insights into the mechanisms of cortical stimulation. The presented models can be used to study various cortical stimulation modalities while incorporating detailed spatial and temporal features of the applied E-field.
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Affiliation(s)
- Aman S Aberra
- Department of Biomedical Engineering, School of Engineering, Duke University, Durham, NC 27710, United States of America
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Lazarov E, Dannemeyer M, Feulner B, Enderlein J, Gutnick MJ, Wolf F, Neef A. An axon initial segment is required for temporal precision in action potential encoding by neuronal populations. SCIENCE ADVANCES 2018; 4:eaau8621. [PMID: 30498783 PMCID: PMC6261658 DOI: 10.1126/sciadv.aau8621] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2018] [Accepted: 10/26/2018] [Indexed: 06/09/2023]
Abstract
Central neurons initiate action potentials (APs) in the axon initial segment (AIS), a compartment characterized by a high concentration of voltage-dependent ion channels and specialized cytoskeletal anchoring proteins arranged in a regular nanoscale pattern. Although the AIS was a key evolutionary innovation in neurons, the functional benefits it confers are not clear. Using a mutation of the AIS cytoskeletal protein βIV-spectrin, we here establish an in vitro model of neurons with a perturbed AIS architecture that retains nanoscale order but loses the ability to maintain a high NaV density. Combining experiments and simulations, we show that a high NaV density in the AIS is not required for axonal AP initiation; it is, however, crucial for a high bandwidth of information encoding and AP timing precision. Our results provide the first experimental demonstration of axonal AP initiation without high axonal channel density and suggest that increasing the bandwidth of the neuronal code and, hence, the computational efficiency of network function, was a major benefit of the evolution of the AIS.
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Affiliation(s)
- Elinor Lazarov
- Koret School of Veterinary Medicine, The Hebrew University of Jerusalem, P.O. Box 12, Rehovot 76100, Israel
- Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany
- Bernstein Center for Computational Neuroscience, Georg-August-University Göttingen, Am Faßberg 17, 37077 Göttingen, Germany
- University Medical Center Göttingen, Department of Pediatrics and Adolescent Medicine, Division of Pediatric Neurology, Robert Koch Str. 40, 37075 Göttingen, Germany
| | - Melanie Dannemeyer
- Bernstein Center for Computational Neuroscience, Georg-August-University Göttingen, Am Faßberg 17, 37077 Göttingen, Germany
- III. Institute of Physics, Georg-August-University Göttingen, Friedrich Hund Pl. 1, 37077 Göttingen, Germany
| | - Barbara Feulner
- Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany
- Bernstein Center for Computational Neuroscience, Georg-August-University Göttingen, Am Faßberg 17, 37077 Göttingen, Germany
- Max Planck Institute for Experimental Medicine, Hermann Rein St. 3, 37075 Göttingen, Germany
| | - Jörg Enderlein
- Bernstein Center for Computational Neuroscience, Georg-August-University Göttingen, Am Faßberg 17, 37077 Göttingen, Germany
- III. Institute of Physics, Georg-August-University Göttingen, Friedrich Hund Pl. 1, 37077 Göttingen, Germany
| | - Michael J. Gutnick
- Koret School of Veterinary Medicine, The Hebrew University of Jerusalem, P.O. Box 12, Rehovot 76100, Israel
| | - Fred Wolf
- Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany
- Bernstein Center for Computational Neuroscience, Georg-August-University Göttingen, Am Faßberg 17, 37077 Göttingen, Germany
- Max Planck Institute for Experimental Medicine, Hermann Rein St. 3, 37075 Göttingen, Germany
- Institute for Nonlinear Dynamics, Georg-August-University Göttingen, Friedrich Hund Pl. 1, 37077 Göttingen, Germany
- Center for Biostructural Imaging of Neurodegeneration, Von-Siebold-Straße 3A, 37075 Göttingen, Germany
- Campus Institute for Dynamics of Biological Networks, Hermann Rein St. 3, 37075 Göttingen, Germany
| | - Andreas Neef
- Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany
- Bernstein Center for Computational Neuroscience, Georg-August-University Göttingen, Am Faßberg 17, 37077 Göttingen, Germany
- Max Planck Institute for Experimental Medicine, Hermann Rein St. 3, 37075 Göttingen, Germany
- Institute for Nonlinear Dynamics, Georg-August-University Göttingen, Friedrich Hund Pl. 1, 37077 Göttingen, Germany
- Center for Biostructural Imaging of Neurodegeneration, Von-Siebold-Straße 3A, 37075 Göttingen, Germany
- Campus Institute for Dynamics of Biological Networks, Hermann Rein St. 3, 37075 Göttingen, Germany
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Kalmbach BE, Buchin A, Long B, Close J, Nandi A, Miller JA, Bakken TE, Hodge RD, Chong P, de Frates R, Dai K, Maltzer Z, Nicovich PR, Keene CD, Silbergeld DL, Gwinn RP, Cobbs C, Ko AL, Ojemann JG, Koch C, Anastassiou CA, Lein ES, Ting JT. h-Channels Contribute to Divergent Intrinsic Membrane Properties of Supragranular Pyramidal Neurons in Human versus Mouse Cerebral Cortex. Neuron 2018; 100:1194-1208.e5. [PMID: 30392798 DOI: 10.1016/j.neuron.2018.10.012] [Citation(s) in RCA: 85] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 09/05/2018] [Accepted: 10/05/2018] [Indexed: 12/18/2022]
Abstract
Gene expression studies suggest that differential ion channel expression contributes to differences in rodent versus human neuronal physiology. We tested whether h-channels more prominently contribute to the physiological properties of human compared to mouse supragranular pyramidal neurons. Single-cell/nucleus RNA sequencing revealed ubiquitous HCN1-subunit expression in excitatory neurons in human, but not mouse, supragranular layers. Using patch-clamp recordings, we found stronger h-channel-related membrane properties in supragranular pyramidal neurons in human temporal cortex, compared to mouse supragranular pyramidal neurons in temporal association area. The magnitude of these differences depended upon cortical depth and was largest in pyramidal neurons in deep L3. Additionally, pharmacologically blocking h-channels produced a larger change in membrane properties in human compared to mouse neurons. Finally, using biophysical modeling, we provide evidence that h-channels promote the transfer of theta frequencies from dendrite-to-soma in human L3 pyramidal neurons. Thus, h-channels contribute to between-species differences in a fundamental neuronal property.
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Affiliation(s)
- Brian E Kalmbach
- Allen Institute for Brain Science, Seattle, WA 98109, USA; Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA.
| | - Anatoly Buchin
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Brian Long
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jennie Close
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Anirban Nandi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | | | - Peter Chong
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Kael Dai
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Zoe Maltzer
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - C Dirk Keene
- Department of Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Daniel L Silbergeld
- Department of Neurological Surgery, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Ryder P Gwinn
- Epilepsy Surgery and Functional Neurosurgery, Swedish Neuroscience Institute, Seattle, WA 98122, USA
| | - Charles Cobbs
- The Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA 98122, USA
| | - Andrew L Ko
- Department of Neurological Surgery, University of Washington School of Medicine, Seattle, WA 98195, USA; Regional Epilepsy Center at Harborview Medical Center, Seattle, WA 98104, USA
| | - Jeffrey G Ojemann
- Department of Neurological Surgery, University of Washington School of Medicine, Seattle, WA 98195, USA; Regional Epilepsy Center at Harborview Medical Center, Seattle, WA 98104, USA
| | - Christof Koch
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Costas A Anastassiou
- Allen Institute for Brain Science, Seattle, WA 98109, USA; Department of Neurology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA; Department of Neurological Surgery, University of Washington School of Medicine, Seattle, WA 98195, USA
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DSCAM differentially modulates pre- and postsynaptic structural and functional central connectivity during visual system wiring. Neural Dev 2018; 13:22. [PMID: 30219101 PMCID: PMC6138929 DOI: 10.1186/s13064-018-0118-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Accepted: 08/26/2018] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Proper patterning of dendritic and axonal arbors is a critical step in the formation of functional neuronal circuits. Developing circuits rely on an array of molecular cues to shape arbor morphology, but the underlying mechanisms guiding the structural formation and interconnectivity of pre- and postsynaptic arbors in real time remain unclear. Here we explore how Down syndrome cell adhesion molecule (DSCAM) differentially shapes the dendritic morphology of central neurons and their presynaptic retinal ganglion cell (RGC) axons in the developing vertebrate visual system. METHODS The cell-autonomous role of DSCAM, in tectal neurons and in RGCs, was examined using targeted single-cell knockdown and overexpression approaches in developing Xenopus laevis tadpoles. Axonal arbors of RGCs and dendritic arbors of tectal neurons were visualized using real-time in vivo confocal microscopy imaging over the course of 3 days. RESULTS In the Xenopus visual system, DSCAM immunoreactivity is present in RGCs, cells in the optic tectum and the tectal neuropil at the time retinotectal synaptic connections are made. Downregulating DSCAM in tectal neurons significantly increased dendritic growth and branching rates while inducing dendrites to take on tortuous paths. Overexpression of DSCAM, in contrast, reduced dendritic branching and growth rate. Functional deficits mediated by tectal DSCAM knockdown were examined using visually guided behavioral assays in swimming tadpoles, revealing irregular behavioral responses to visual stimulus. Functional deficits in visual behavior also corresponded with changes in VGLUT/VGAT expression, markers of excitatory and inhibitory transmission, in the tectum. Conversely, single-cell DSCAM knockdown in the retina revealed that RGC axon arborization at the target is influenced by DSCAM, where axons grew at a slower rate and remained relatively simple. In the retina, dendritic arbors of RGCs were not affected by the reduction of DSCAM expression. CONCLUSIONS Together, our observations implicate DSCAM in the control of both pre- and postsynaptic structural and functional connectivity in the developing retinotectal circuit, where it primarily acts as a neuronal brake to limit and guide postsynaptic dendrite growth of tectal neurons while it also facilitates arborization of presynaptic RGC axons cell autonomously.
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