1
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Abbaspoor S, Hoffman KL. Circuit dynamics of superficial and deep CA1 pyramidal cells and inhibitory cells in freely-moving macaques. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.06.570369. [PMID: 38106053 PMCID: PMC10723348 DOI: 10.1101/2023.12.06.570369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Diverse neuron classes in hippocampal CA1 have been identified through the heterogeneity of their cellular/molecular composition. How these classes relate to hippocampal function and the network dynamics that support cognition in primates remains unclear. Here we report inhibitory functional cell groups in CA1 of freely-moving macaques whose diverse response profiles to network states and each other suggest distinct and specific roles in the functional microcircuit of CA1. In addition, pyramidal cells that were segregated into superficial and deep layers differed in firing rate, burstiness, and sharp-wave ripple-associated firing. They also showed strata-specific spike-timing interactions with inhibitory cell groups, suggestive of segregated neural populations. Furthermore, ensemble recordings revealed that cell assemblies were preferentially organized according to these strata. These results suggest sublayer-specific circuit organization in hippocampal CA1 of the freely-moving macaques that may underlie its role in cognition.
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Affiliation(s)
- S Abbaspoor
- Department of Psychology, Vanderbilt Vision Research Center, Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee
| | - K L Hoffman
- Department of Psychology, Vanderbilt Vision Research Center, Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
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2
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Beau M, Herzfeld DJ, Naveros F, Hemelt ME, D’Agostino F, Oostland M, Sánchez-López A, Chung YY, Michael Maibach, Kyranakis S, Stabb HN, Martínez Lopera MG, Lajko A, Zedler M, Ohmae S, Hall NJ, Clark BA, Cohen D, Lisberger SG, Kostadinov D, Hull C, Häusser M, Medina JF. A deep-learning strategy to identify cell types across species from high-density extracellular recordings. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.30.577845. [PMID: 38352514 PMCID: PMC10862837 DOI: 10.1101/2024.01.30.577845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
High-density probes allow electrophysiological recordings from many neurons simultaneously across entire brain circuits but don't reveal cell type. Here, we develop a strategy to identify cell types from extracellular recordings in awake animals, revealing the computational roles of neurons with distinct functional, molecular, and anatomical properties. We combine optogenetic activation and pharmacology using the cerebellum as a testbed to generate a curated ground-truth library of electrophysiological properties for Purkinje cells, molecular layer interneurons, Golgi cells, and mossy fibers. We train a semi-supervised deep-learning classifier that predicts cell types with greater than 95% accuracy based on waveform, discharge statistics, and layer of the recorded neuron. The classifier's predictions agree with expert classification on recordings using different probes, in different laboratories, from functionally distinct cerebellar regions, and across animal species. Our classifier extends the power of modern dynamical systems analyses by revealing the unique contributions of simultaneously-recorded cell types during behavior.
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Affiliation(s)
- Maxime Beau
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - David J. Herzfeld
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA
| | - Francisco Naveros
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Department of Computer Engineering, Automation and Robotics, Research Centre for Information and Communication Technologies, University of Granada, Granada, Spain
| | - Marie E. Hemelt
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA
| | - Federico D’Agostino
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Marlies Oostland
- Wolfson Institute for Biomedical Research, University College London, London, UK
- Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands
| | | | - Young Yoon Chung
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Michael Maibach
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Stephen Kyranakis
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Hannah N. Stabb
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | | | - Agoston Lajko
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Marie Zedler
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Shogo Ohmae
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Nathan J. Hall
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA
| | - Beverley A. Clark
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Dana Cohen
- The Leslie and Susan Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
| | | | - Dimitar Kostadinov
- Wolfson Institute for Biomedical Research, University College London, London, UK
- Centre for Developmental Neurobiology, King’s College London, London, UK
| | - Court Hull
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Javier F. Medina
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
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3
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Mozumder R, Chung S, Li S, Constantinidis C. Contributions of narrow- and broad-spiking prefrontal and parietal neurons on working memory tasks. Front Syst Neurosci 2024; 18:1365622. [PMID: 38577690 PMCID: PMC10991738 DOI: 10.3389/fnsys.2024.1365622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 03/11/2024] [Indexed: 04/06/2024] Open
Abstract
Neurons that generate persistent activity in the primate dorsolateral prefrontal and posterior parietal cortex have been shown to be predictive of behavior in working memory tasks, though subtle differences between them have been observed in how information is represented. The role of different neuron types in each of these areas has not been investigated at depth. We thus compared the activity of neurons classified as narrow-spiking, putative interneurons, and broad-spiking, putative pyramidal neurons, recorded from the dorsolateral prefrontal and posterior parietal cortex of male monkeys, to analyze their role in the maintenance of working memory. Our results demonstrate that narrow-spiking neurons are active during a range of tasks and generate persistent activity during the delay period over which stimuli need to be maintained in memory. Furthermore, the activity of narrow-spiking neurons was predictive of the subject's recall no less than that of broad-spiking neurons, which are exclusively projection neurons in the cortex. Our results show that putative interneurons play an active role during the maintenance of working memory and shed light onto the fundamental neural circuits that determine subjects' memories and judgments.
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Affiliation(s)
- Rana Mozumder
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Sophia Chung
- Neuroscience Program, Vanderbilt University, Nashville, TN, United States
| | - Sihai Li
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
| | - Christos Constantinidis
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
- Neuroscience Program, Vanderbilt University, Nashville, TN, United States
- Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
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4
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Hornauer P, Prack G, Anastasi N, Ronchi S, Kim T, Donner C, Fiscella M, Borgwardt K, Taylor V, Jagasia R, Roqueiro D, Hierlemann A, Schröter M. DeePhys: A machine learning-assisted platform for electrophysiological phenotyping of human neuronal networks. Stem Cell Reports 2024; 19:285-298. [PMID: 38278155 PMCID: PMC10874850 DOI: 10.1016/j.stemcr.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 12/18/2023] [Accepted: 12/20/2023] [Indexed: 01/28/2024] Open
Abstract
Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell-derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings.
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Affiliation(s)
- Philipp Hornauer
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland.
| | - Gustavo Prack
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland
| | - Nadia Anastasi
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche, 4070 Basel, Switzerland
| | - Silvia Ronchi
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland
| | - Taehoon Kim
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland
| | | | - Michele Fiscella
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland; MaxWell Biosystems AG, 8047 Zürich, Switzerland
| | - Karsten Borgwardt
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Verdon Taylor
- Department of Biomedicine, University of Basel, 4031 Basel, Switzerland
| | - Ravi Jagasia
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche, 4070 Basel, Switzerland
| | - Damian Roqueiro
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland; Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche, 4070 Basel, Switzerland
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland
| | - Manuel Schröter
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland
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5
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Haynes VR, Zhou Y, Crook SM. Discovering optimal features for neuron-type identification from extracellular recordings. Front Neuroinform 2024; 18:1303993. [PMID: 38371496 PMCID: PMC10869512 DOI: 10.3389/fninf.2024.1303993] [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: 09/28/2023] [Accepted: 01/15/2024] [Indexed: 02/20/2024] Open
Abstract
Advancements in multichannel recordings of single-unit activity (SUA) in vivo present an opportunity to discover novel features of spatially-varying extracellularly-recorded action potentials (EAPs) that are useful for identifying neuron-types. Traditional approaches to classifying neuron-types often rely on computing EAP waveform features based on conventions of single-channel recordings and thus inherit their limitations. However, spatiotemporal EAP waveforms are the product of signals from underlying current sources being mixed within the extracellular space. We introduce a machine learning approach to demix the underlying sources of spatiotemporal EAP waveforms. Using biophysically realistic computational models, we simulate EAP waveforms and characterize them by the relative prevalence of these sources, which we use as features for identifying the neuron-types corresponding to recorded single units. These EAP sources have distinct spatial and multi-resolution temporal patterns that are robust to various sampling biases. EAP sources also are shared across many neuron-types, are predictive of gross morphological features, and expose underlying morphological domains. We then organize known neuron-types into a hierarchy of latent morpho-electrophysiological types based on differences in the source prevalences, which provides a multi-level classification scheme. We validate the robustness, accuracy, and interpretations of our demixing approach by analyzing simulated EAPs from morphologically detailed models with classification and clustering methods. This simulation-based approach provides a machine learning strategy for neuron-type identification.
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Affiliation(s)
- Vergil R. Haynes
- Laboratory for Auditory Computation and Neurophysiology, College of Health Solutions, Arizona State University, Tempe, AZ, United States
- Laboratory for Informatics and Computation in Open Neuroscience, School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, United States
| | - Yi Zhou
- Laboratory for Auditory Computation and Neurophysiology, College of Health Solutions, Arizona State University, Tempe, AZ, United States
| | - Sharon M. Crook
- Laboratory for Informatics and Computation in Open Neuroscience, School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, United States
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6
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Wang C, Lin C, Zhao Y, Samantzis M, Sedlak P, Sah P, Balbi M. 40-Hz optogenetic stimulation rescues functional synaptic plasticity after stroke. Cell Rep 2023; 42:113475. [PMID: 37979173 DOI: 10.1016/j.celrep.2023.113475] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 10/18/2023] [Accepted: 11/03/2023] [Indexed: 11/20/2023] Open
Abstract
Evoked brain oscillations in the gamma range have been shown to assist in stroke recovery. However, the causal relationship between evoked oscillations and neuroprotection is not well understood. We have used optogenetic stimulation to investigate how evoked gamma oscillations modulate cortical dynamics in the acute phase after stroke. Our results reveal that stimulation at 40 Hz drives activity in interneurons at the stimulation frequency and phase-locked activity in principal neurons at a lower frequency, leading to increased cross-frequency coupling. In addition, 40-Hz stimulation after stroke enhances interregional communication. These effects are observed up to 24 h after stimulation. Our stimulation protocol also rescues functional synaptic plasticity 24 h after stroke and leads to an upregulation of plasticity genes and a downregulation of cell death genes. Together these results suggest that restoration of cortical dynamics may confer neuroprotection after stroke.
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Affiliation(s)
- Cong Wang
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia; Engineering Research Centre of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai 201203, China
| | - Caixia Lin
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Yue Zhao
- Departments of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Centre, Shanghai 200032, China; Institute of Thoracic Oncology, Fudan University, Shanghai 200032, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Montana Samantzis
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Petra Sedlak
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Pankaj Sah
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Matilde Balbi
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia.
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7
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Ceccarelli F, Ferrucci L, Londei F, Ramawat S, Brunamonti E, Genovesio A. Static and dynamic coding in distinct cell types during associative learning in the prefrontal cortex. Nat Commun 2023; 14:8325. [PMID: 38097560 PMCID: PMC10721651 DOI: 10.1038/s41467-023-43712-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 11/17/2023] [Indexed: 12/17/2023] Open
Abstract
The prefrontal cortex maintains information in memory through static or dynamic population codes depending on task demands, but whether the population coding schemes used are learning-dependent and differ between cell types is currently unknown. We investigate the population coding properties and temporal stability of neurons recorded from male macaques in two mapping tasks during and after stimulus-response associative learning, and then we use a Strategy task with the same stimuli and responses as control. We identify a heterogeneous population coding for stimuli, responses, and novel associations: static for putative pyramidal cells and dynamic for putative interneurons that show the strongest selectivity for all the variables. The population coding of learned associations shows overall the highest stability driven by cell types, with interneurons changing from dynamic to static coding after successful learning. The results support that prefrontal microcircuitry expresses mixed population coding governed by cell types and changes its stability during associative learning.
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Affiliation(s)
- Francesco Ceccarelli
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
| | - Lorenzo Ferrucci
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
| | - Fabrizio Londei
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
- PhD program in Behavioral Neuroscience, Sapienza University, Rome, Italy
| | - Surabhi Ramawat
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
| | - Emiliano Brunamonti
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
| | - Aldo Genovesio
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy.
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8
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Jiang J, Tan S, Feng X, Peng Y, Long C, Yang L. Distinct ACC Neural Mechanisms Underlie Authentic and Transmitted Anxiety Induced by Maternal Separation in Mice. J Neurosci 2023; 43:8201-8218. [PMID: 37845036 PMCID: PMC10697407 DOI: 10.1523/jneurosci.0558-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 09/07/2023] [Accepted: 09/13/2023] [Indexed: 10/18/2023] Open
Abstract
It is known that humans and rodents are capable of transmitting stress to their naive partners via social interaction. However, a comprehensive understanding of transmitted stress, which may differ from authentic stress, thus revealing unique neural mechanisms of social interaction resulting from transmitted stress and the associated anxiety, is missing. We used, in the present study, maternal separation (MS) as a stress model to investigate whether MS causes abnormal behavior in adolescence. A key concern in the analysis of stress transmission is whether the littermates of MS mice who only witness MS stress ("Partners") exhibit behavioral abnormalities similar to those of MS mice themselves. Of special interest is the establishment of the neural mechanisms underlying transmitted stress and authentic stress. The results show that Partners, similar to MS mice, exhibit anxiety-like behavior and hyperalgesia after witnessing littermates being subjected to early-life repetitive MS. Electrophysiological analysis revealed that mice subjected to MS demonstrate a reduction in both the excitatory and inhibitory synaptic activities of parvalbumin interneurons (PVINs) in the anterior cingulate cortex (ACC). However, Partners differed from MS mice in showing an increase in the number and excitability of GABAergic PVINs in the ACC and in the ability of chemogenetic PVIN inactivation to eliminate abnormal behavior. Furthermore, the social transfer of anxiety-like behavior required intact olfactory, but not visual, perception. This study suggests a functional involvement of ACC PVINs in mediating the distinct neural basis of transmitted anxiety.SIGNIFICANCE STATEMENT The anterior cingulate cortex (ACC) is a critical brain area in physical and social pain and contributes to the exhibition of abnormal behavior. ACC glutamatergic neurons have been shown to encode transmitted stress, but it remains unclear whether inhibitory ACC neurons also play a role. We evaluate, in this study, ACC neuronal, synaptic and network activities and uncover a critical role of parvalbumin interneurons (PVINs) in the expression of transmitted stress in adolescent mice who had witnessed MS of littermates in infancy. Furthermore, inactivation of ACC PVINs blocks transmitted stress. The results suggest that emotional contagion has a severe effect on brain function, and identify a potential target for the treatment of transmitted anxiety.
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Affiliation(s)
- Jinxiang Jiang
- School of Life Sciences, Guangzhou University, Guangzhou 510006, China
- School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Shuyi Tan
- School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Xiaoyi Feng
- School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Yigang Peng
- School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Cheng Long
- School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Li Yang
- School of Life Sciences, Guangzhou University, Guangzhou 510006, China
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9
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López Espejo M, David SV. A sparse code for natural sound context in auditory cortex. CURRENT RESEARCH IN NEUROBIOLOGY 2023; 6:100118. [PMID: 38152461 PMCID: PMC10749876 DOI: 10.1016/j.crneur.2023.100118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 10/27/2023] [Accepted: 11/14/2023] [Indexed: 12/29/2023] Open
Abstract
Accurate sound perception can require integrating information over hundreds of milliseconds or even seconds. Spectro-temporal models of sound coding by single neurons in auditory cortex indicate that the majority of sound-evoked activity can be attributed to stimuli with a few tens of milliseconds. It remains uncertain how the auditory system integrates information about sensory context on a longer timescale. Here we characterized long-lasting contextual effects in auditory cortex (AC) using a diverse set of natural sound stimuli. We measured context effects as the difference in a neuron's response to a single probe sound following two different context sounds. Many AC neurons showed context effects lasting longer than the temporal window of a traditional spectro-temporal receptive field. The duration and magnitude of context effects varied substantially across neurons and stimuli. This diversity of context effects formed a sparse code across the neural population that encoded a wider range of contexts than any constituent neuron. Encoding model analysis indicates that context effects can be explained by activity in the local neural population, suggesting that recurrent local circuits support a long-lasting representation of sensory context in auditory cortex.
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Affiliation(s)
- Mateo López Espejo
- Neuroscience Graduate Program, Oregon Health & Science University, Portland, OR, USA
| | - Stephen V. David
- Otolaryngology, Oregon Health & Science University, Portland, OR, USA
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10
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Wu EG, Rudzite AM, Bohlen MO, Li PH, Kling A, Cooler S, Rhoades C, Brackbill N, Gogliettino AR, Shah NP, Madugula SS, Sher A, Litke AM, Field GD, Chichilnisky E. Decomposition of retinal ganglion cell electrical images for cell type and functional inference. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.06.565889. [PMID: 37986895 PMCID: PMC10659265 DOI: 10.1101/2023.11.06.565889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Identifying neuronal cell types and their biophysical properties based on their extracellular electrical features is a major challenge for experimental neuroscience and the development of high-resolution brain-machine interfaces. One example is identification of retinal ganglion cell (RGC) types and their visual response properties, which is fundamental for developing future electronic implants that can restore vision. The electrical image (EI) of a RGC, or the mean spatio-temporal voltage footprint of its recorded spikes on a high-density electrode array, contains substantial information about its anatomical, morphological, and functional properties. However, the analysis of these properties is complex because of the high-dimensional nature of the EI. We present a novel optimization-based algorithm to decompose electrical image into a low-dimensional, biophysically-based representation: the temporally-shifted superposition of three learned basis waveforms corresponding to spike waveforms produced in the somatic, dendritic and axonal cellular compartments. Large-scale multi-electrode recordings from the macaque retina were used to test the effectiveness of the decomposition. The decomposition accurately localized the somatic and dendritic compartments of the cell. The imputed dendritic fields of RGCs correctly predicted the location and shape of their visual receptive fields. The inferred waveform amplitudes and shapes accurately identified the four major primate RGC types (ON and OFF midget and parasol cells), a substantial advance. Together, these findings may contribute to more accurate inference of RGC types and their original light responses in the degenerated retina, with possible implications for other electrical imaging applications.
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Affiliation(s)
- Eric G. Wu
- Department of Electrical Engineering, Stanford University
| | | | | | - Peter H. Li
- Department of Neurosurgery, Stanford University
- Department of Ophthalmology, Stanford University
- Hansen Experimental Physics Laboratory, Stanford University
| | - Alexandra Kling
- Department of Neurosurgery, Stanford University
- Department of Ophthalmology, Stanford University
- Hansen Experimental Physics Laboratory, Stanford University
| | - Sam Cooler
- Department of Neurosurgery, Stanford University
| | | | | | | | - Nishal P. Shah
- Department of Electrical Engineering, Stanford University
- Department of Neurosurgery, Stanford University
| | - Sasidhar S. Madugula
- Neurosciences PhD Program, Stanford University
- Stanford School of Medicine, Stanford University
| | - Alexander Sher
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz
| | - Alan M. Litke
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz
| | - Greg D. Field
- Department of Neurobiology, Duke University
- Stein Eye Institute, Department of Ophthalmology, University of California, Los Angeles
| | - E.J. Chichilnisky
- Department of Neurosurgery, Stanford University
- Department of Ophthalmology, Stanford University
- Hansen Experimental Physics Laboratory, Stanford University
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11
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Odean NN, Sanayei M, Shadlen MN. Transient Oscillations of Neural Firing Rate Associated With Routing of Evidence in a Perceptual Decision. J Neurosci 2023; 43:6369-6383. [PMID: 37550053 PMCID: PMC10500999 DOI: 10.1523/jneurosci.2200-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 07/07/2023] [Accepted: 07/12/2023] [Indexed: 08/09/2023] Open
Abstract
To form a perceptual decision, the brain must acquire samples of evidence from the environment and incorporate them in computations that mediate choice behavior. While much is known about the neural circuits that process sensory information and those that form decisions, less is known about the mechanisms that establish the functional linkage between them. We trained monkeys of both sexes to make difficult decisions about the net direction of visual motion under conditions that required trial-by-trial control of functional connectivity. In one condition, the motion appeared at different locations on different trials. In the other, two motion patches appeared, only one of which was informative. Neurons in the parietal cortex produced brief oscillations in their firing rate at the time routing was established: upon onset of the motion display when its location was unpredictable across trials, and upon onset of an attention cue that indicated in which of two locations an informative patch of dots would appear. The oscillation was absent when the stimulus location was fixed across trials. We interpret the oscillation as a manifestation of the mechanism that establishes the source and destination of flexibly routed information, but not the transmission of the information per se Significance Statement It has often been suggested that oscillations in neural activity might serve a role in routing information appropriately. We observe an oscillation in neural firing rate in the lateral intraparietal area consistent with such a role. The oscillations are transient. They coincide with the establishment of routing, but they do not appear to play a role in the transmission (or conveyance) of the routed information itself.
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Affiliation(s)
- Naomi N Odean
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, New York 10025
| | - Mehdi Sanayei
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, New York 10025
| | - Michael N Shadlen
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, New York 10025
- Howard Hughes Medical Institute, Columbia University, New York, New York 10025
- Kavli Institute, New York, New York 10025
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12
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Jung YJ, Sun SH, Almasi A, Yunzab M, Meffin H, Ibbotson MR. Characterization of extracellular spike waveforms recorded in wallaby primary visual cortex. Front Neurosci 2023; 17:1244952. [PMID: 37746137 PMCID: PMC10517629 DOI: 10.3389/fnins.2023.1244952] [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: 06/23/2023] [Accepted: 08/25/2023] [Indexed: 09/26/2023] Open
Abstract
Extracellular recordings were made from 642 units in the primary visual cortex (V1) of a highly visual marsupial, the Tammar wallaby. The receptive field (RF) characteristics of the cells were objectively estimated using the non-linear input model (NIM), and these were correlated with spike shapes. We found that wallaby cortical units had 68% regular spiking (RS), 12% fast spiking (FS), 4% triphasic spiking (TS), 5% compound spiking (CS) and 11% positive spiking (PS). RS waveforms are most often associated with recordings from pyramidal or spiny stellate cell bodies, suggesting that recordings from these cell types dominate in the wallaby cortex. In wallaby, 70-80% of FS and RS cells had orientation selective RFs and had evenly distributed linear and nonlinear RFs. We found that 47% of wallaby PS units were non-orientation selective and they were dominated by linear RFs. Previous studies suggest that the PS units represent recordings from the axon terminals of non-orientation selective cells originating in the lateral geniculate nucleus (LGN). If this is also true in wallaby, as strongly suggested by their low response latencies and bursty spiking properties, the results suggest that significantly more neurons in wallaby LGN are already orientation selective. In wallaby, less than 10% of recorded spikes had triphasic (TS) or sluggish compound spiking (CS) waveforms. These units had a mixture of orientation selective and non-oriented properties, and their cellular origins remain difficult to classify.
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Affiliation(s)
- Young Jun Jung
- Department of Biomedical Engineering, The University of Melbourne, Melbourne, VIC, Australia
- National Vision Research Institute, Australian College of Optometry Carlton, Carlton, VIC, Australia
- Department of Optometry and Vision Sciences, The University of Melbourne, Melbourne, VIC, Australia
| | - Shi H. Sun
- National Vision Research Institute, Australian College of Optometry Carlton, Carlton, VIC, Australia
| | - Ali Almasi
- National Vision Research Institute, Australian College of Optometry Carlton, Carlton, VIC, Australia
| | - Molis Yunzab
- National Vision Research Institute, Australian College of Optometry Carlton, Carlton, VIC, Australia
| | - Hamish Meffin
- Department of Biomedical Engineering, The University of Melbourne, Melbourne, VIC, Australia
| | - Michael R. Ibbotson
- Department of Biomedical Engineering, The University of Melbourne, Melbourne, VIC, Australia
- National Vision Research Institute, Australian College of Optometry Carlton, Carlton, VIC, Australia
- Department of Optometry and Vision Sciences, The University of Melbourne, Melbourne, VIC, Australia
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13
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Khazali MF, Wong YT, Dean HL, Hagan MA, Fabiszak MM, Pesaran B. Putative cell-type-specific multiregional mode in posterior parietal cortex during coordinated visual behavior. Neuron 2023; 111:1979-1992.e7. [PMID: 37044088 PMCID: PMC10935574 DOI: 10.1016/j.neuron.2023.03.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 01/09/2023] [Accepted: 03/16/2023] [Indexed: 04/14/2023]
Abstract
In the reach and saccade regions of the posterior parietal cortex (PPC), multiregional communication depends on the timing of neuronal activity with respect to beta-frequency (10-30 Hz) local field potential (LFP) activity, termed dual coherence. Neural coherence is believed to reflect neural excitability, whereby spiking tends to occur at a particular phase of LFP activity, but the mechanisms of multiregional dual coherence remain unknown. Here, we investigate dual coherence in the PPC of non-human primates performing eye-hand movements. We computationally model dual coherence in terms of multiregional neural excitability and show that one latent component, a multiregional mode, reflects shared excitability across distributed PPC populations. Analyzing the power in the multiregional mode with respect to different putative cell types reveals significant modulations with the spiking of putative pyramidal neurons and not inhibitory interneurons. These results suggest a specific role for pyramidal neurons in dual coherence supporting multiregional communication in PPC.
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Affiliation(s)
- Mohammad Farhan Khazali
- Center for Neural Science, New York University, New York, NY 10003, USA; Freiburg Epilepsy Center, Medical Center - University of Freiburg, 79106 Freiburg, Germany
| | - Yan T Wong
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia; Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia
| | - Heather L Dean
- Center for Neural Science, New York University, New York, NY 10003, USA
| | - Maureen A Hagan
- Department of Physiology and Neuroscience Program, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | | | - Bijan Pesaran
- Center for Neural Science, New York University, New York, NY 10003, USA; Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 190104, USA; Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 190104, USA; Department of Bioengineering, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 190104, USA.
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14
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Schneider A, Azabou M, McDougall-Vigier L, Parks DF, Ensley S, Bhaskaran-Nair K, Nowakowski T, Dyer EL, Hengen KB. Transcriptomic cell type structures in vivo neuronal activity across multiple timescales. Cell Rep 2023; 42:112318. [PMID: 36995938 PMCID: PMC10539488 DOI: 10.1016/j.celrep.2023.112318] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 02/04/2023] [Accepted: 03/15/2023] [Indexed: 03/30/2023] Open
Abstract
Cell type is hypothesized to be a key determinant of a neuron's role within a circuit. Here, we examine whether a neuron's transcriptomic type influences the timing of its activity. We develop a deep-learning architecture that learns features of interevent intervals across timescales (ms to >30 min). We show that transcriptomic cell-class information is embedded in the timing of single neuron activity in the intact brain of behaving animals (calcium imaging and extracellular electrophysiology) as well as in a bio-realistic model of the visual cortex. Further, a subset of excitatory cell types are distinguishable but can be classified with higher accuracy when considering cortical layer and projection class. Finally, we show that computational fingerprints of cell types may be universalizable across structured stimuli and naturalistic movies. Our results indicate that transcriptomic class and type may be imprinted in the timing of single neuron activity across diverse stimuli.
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Affiliation(s)
- Aidan Schneider
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Mehdi Azabou
- School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | | | - David F Parks
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Sahara Ensley
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Kiran Bhaskaran-Nair
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Tomasz Nowakowski
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Eva L Dyer
- School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Keith B Hengen
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA.
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15
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Wei Y, Nandi A, Jia X, Siegle JH, Denman D, Lee SY, Buchin A, Van Geit W, Mosher CP, Olsen S, Anastassiou CA. Associations between in vitro, in vivo and in silico cell classes in mouse primary visual cortex. Nat Commun 2023; 14:2344. [PMID: 37095130 PMCID: PMC10126114 DOI: 10.1038/s41467-023-37844-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 03/31/2023] [Indexed: 04/26/2023] Open
Abstract
The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.
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Affiliation(s)
- Yina Wei
- Zhejiang Lab, Hangzhou, 311100, China.
- Allen Institute for Brain Science, Seattle, WA, 98109, USA.
| | - Anirban Nandi
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | - Xiaoxuan Jia
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
- School of Life Sciences/McGovern Institute for Brain Research, Tsinghua University, 100084, Beijing, China
| | | | | | - Soo Yeun Lee
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | - Anatoly Buchin
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
- Cajal Neuroscience Inc, Seattle, WA, 98102, USA
| | - Werner Van Geit
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL) Campus Biotech, Geneva, 1202, Switzerland
| | - Clayton P Mosher
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - Shawn Olsen
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | - 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.
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
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16
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Wei Y, Nandi A, Jia X, Siegle JH, Denman D, Lee SY, Buchin A, Geit WV, Mosher CP, Olsen S, Anastassiou CA. Associations between in vitro , in vivo and in silico cell classes in mouse primary visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.17.532851. [PMID: 37131710 PMCID: PMC10153154 DOI: 10.1101/2023.04.17.532851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.
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Affiliation(s)
- Yina Wei
- Zhejiang Lab, Hangzhou 311100, China
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Anirban Nandi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Xiaoxuan Jia
- Allen Institute for Brain Science, Seattle, WA 98109, USA
- School of Life Sciences, Tsinghua University, Beijing, 100084, China, IDG/McGovern Institute for Brain Research at Tsinghua University, Beijing, 100084, China
| | | | | | - Soo Yeun Lee
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Anatoly Buchin
- Allen Institute for Brain Science, Seattle, WA 98109, USA
- Cajal Neuroscience Inc, Seattle, WA 98102, USA
| | - Werner Van Geit
- Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL) Campus Biotech, Geneva 1202, Switzerland
| | - Clayton P. Mosher
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Shawn Olsen
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - 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
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Lead contact
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17
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Wong RK, Selvanayagam J, Johnston KD, Everling S. Delay-related activity in marmoset prefrontal cortex. Cereb Cortex 2023; 33:3523-3537. [PMID: 35945687 PMCID: PMC10068290 DOI: 10.1093/cercor/bhac289] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 06/28/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Persistent delay-period activity in prefrontal cortex (PFC) has long been regarded as a neural signature of working memory (WM). Electrophysiological investigations in macaque PFC have provided much insight into WM mechanisms; however, a barrier to understanding is the fact that a portion of PFC lies buried within the principal sulcus in this species and is inaccessible for laminar electrophysiology or optical imaging. The relatively lissencephalic cortex of the New World common marmoset (Callithrix jacchus) circumvents such limitations. It remains unknown, however, whether marmoset PFC neurons exhibit persistent activity. Here, we addressed this gap by conducting wireless electrophysiological recordings in PFC of marmosets performing a delayed-match-to-location task on a home cage-based touchscreen system. As in macaques, marmoset PFC neurons exhibited sample-, delay-, and response-related activity that was directionally tuned and linked to correct task performance. Models constructed from population activity consistently and accurately predicted stimulus location throughout the delay period, supporting a framework of delay activity in which mnemonic representations are relatively stable in time. Taken together, our findings support the existence of common neural mechanisms underlying WM performance in PFC of macaques and marmosets and thus validate the marmoset as a suitable model animal for investigating the microcircuitry underlying WM.
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Affiliation(s)
- Raymond K Wong
- Graduate Program in Neuroscience, Western University, London, ON N6A 3K7, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON N6A 5B7, Canada
| | - Janahan Selvanayagam
- Graduate Program in Neuroscience, Western University, London, ON N6A 3K7, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON N6A 5B7, Canada
| | - Kevin D Johnston
- Graduate Program in Neuroscience, Western University, London, ON N6A 3K7, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON N6A 5B7, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON N6A 3K7, Canada
| | - Stefan Everling
- Graduate Program in Neuroscience, Western University, London, ON N6A 3K7, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON N6A 5B7, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON N6A 3K7, Canada
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18
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Fontanier V, Sarazin M, Stoll FM, Delord B, Procyk E. Inhibitory control of frontal metastability sets the temporal signature of cognition. eLife 2022; 11:63795. [PMID: 35635439 PMCID: PMC9200403 DOI: 10.7554/elife.63795] [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: 10/07/2020] [Accepted: 05/27/2022] [Indexed: 11/13/2022] Open
Abstract
Cortical dynamics are organized over multiple anatomical and temporal scales. The mechanistic origin of the temporal organization and its contribution to cognition remain unknown. Here we demonstrate the cause of this organization by studying a specific temporal signature (time constant and latency) of neural activity. In monkey frontal areas, recorded during flexible decisions, temporal signatures display specific area-dependent ranges, as well as anatomical and cell-type distributions. Moreover, temporal signatures are functionally adapted to behaviorally relevant timescales. Fine-grained biophysical network models, constrained to account for experimentally observed temporal signatures, reveal that after-hyperpolarization potassium and inhibitory GABA-B conductances critically determine areas' specificity. They mechanistically account for temporal signatures by organizing activity into metastable states, with inhibition controlling state stability and transitions. As predicted by models, state durations non-linearly scale with temporal signatures in monkey, matching behavioral timescales. Thus, local inhibitory-controlled metastability constitutes the dynamical core specifying the temporal organization of cognitive functions in frontal areas.
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Affiliation(s)
| | - Matthieu Sarazin
- Institute of Intelligent Systems and Robotics (ISIR) - UMR 7222, Sorbonne Université, CNRS, Paris, France
| | - Frederic M Stoll
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, United States
| | - Bruno Delord
- Institute of Intelligent Systems and Robotics (ISIR) - UMR 7222, Sorbonne Université, CNRS, Paris, France
| | - Emmanuel Procyk
- Stem Cell and Brain Research Institute U1208, Inserm, Lyon, France
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19
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Liu XP, Wang X. Distinct neuronal types contribute to hybrid temporal encoding strategies in primate auditory cortex. PLoS Biol 2022; 20:e3001642. [PMID: 35613218 PMCID: PMC9132345 DOI: 10.1371/journal.pbio.3001642] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 04/22/2022] [Indexed: 11/18/2022] Open
Abstract
Studies of the encoding of sensory stimuli by the brain often consider recorded neurons as a pool of identical units. Here, we report divergence in stimulus-encoding properties between subpopulations of cortical neurons that are classified based on spike timing and waveform features. Neurons in auditory cortex of the awake marmoset (Callithrix jacchus) encode temporal information with either stimulus-synchronized or nonsynchronized responses. When we classified single-unit recordings using either a criteria-based or an unsupervised classification method into regular-spiking, fast-spiking, and bursting units, a subset of intrinsically bursting neurons formed the most highly synchronized group, with strong phase-locking to sinusoidal amplitude modulation (SAM) that extended well above 20 Hz. In contrast with other unit types, these bursting neurons fired primarily on the rising phase of SAM or the onset of unmodulated stimuli, and preferred rapid stimulus onset rates. Such differentiating behavior has been previously reported in bursting neuron models and may reflect specializations for detection of acoustic edges. These units responded to natural stimuli (vocalizations) with brief and precise spiking at particular time points that could be decoded with high temporal stringency. Regular-spiking units better reflected the shape of slow modulations and responded more selectively to vocalizations with overall firing rate increases. Population decoding using time-binned neural activity found that decoding behavior differed substantially between regular-spiking and bursting units. A relatively small pool of bursting units was sufficient to identify the stimulus with high accuracy in a manner that relied on the temporal pattern of responses. These unit type differences may contribute to parallel and complementary neural codes. Neurons in auditory cortex show highly diverse responses to sounds. This study suggests that neuronal type inferred from baseline firing properties accounts for much of this diversity, with a subpopulation of bursting units being specialized for precise temporal encoding.
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Affiliation(s)
- Xiao-Ping Liu
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- * E-mail: (X-PL); (XW)
| | - Xiaoqin Wang
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- * E-mail: (X-PL); (XW)
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20
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Nashef A, Cohen O, Perlmutter SI, Prut Y. A cerebellar origin of feedforward inhibition to the motor cortex in non-human primates. Cell Rep 2022; 39:110803. [PMID: 35545040 DOI: 10.1016/j.celrep.2022.110803] [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: 09/10/2021] [Revised: 02/02/2022] [Accepted: 04/20/2022] [Indexed: 02/07/2023] Open
Abstract
Voluntary movements are driven by coordinated activity across a large population of motor cortical neurons. Formation of this activity is controlled by local interactions and long-range inputs. How remote areas of the brain communicate with motor cortical neurons to effectively drive movement remains unclear. We address this question by studying the cerebellar-thalamocortical system. We find that thalamic input to the motor cortex triggers feedforward inhibition by contacting inhibitory cells via highly effective GluR2-lacking AMPA receptors and that, during task performance, the activity of parvalbumin (PV) and pyramidal cells exhibits relations comparable with movement parameters. We also find that the movement-related activity of PV interneurons precedes firing of pyramidal cells. This counterintuitive sequence of events, where inhibitory cells are recruited more strongly and before excitatory cells, may amplify the cortical effect of cerebellar signals in a way that exceeds their sheer synaptic efficacy by suppressing other inputs.
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Affiliation(s)
- Abdulraheem Nashef
- Department of Medical Neurobiology, IMRIC and ELSC, The Hebrew University, Hadassah Medical School, Jerusalem 9112102, Israel
| | - Oren Cohen
- Department of Medical Neurobiology, IMRIC and ELSC, The Hebrew University, Hadassah Medical School, Jerusalem 9112102, Israel
| | - Steve I Perlmutter
- Department of Physiology & Biophysics and Washington National Primate Research Center, University of Washington, Box 357330, Seattle, WA 98195, USA
| | - Yifat Prut
- Department of Medical Neurobiology, IMRIC and ELSC, The Hebrew University, Hadassah Medical School, Jerusalem 9112102, Israel.
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21
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Krause MR, Vieira PG, Thivierge JP, Pack CC. Brain stimulation competes with ongoing oscillations for control of spike timing in the primate brain. PLoS Biol 2022; 20:e3001650. [PMID: 35613140 PMCID: PMC9132296 DOI: 10.1371/journal.pbio.3001650] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 04/27/2022] [Indexed: 11/19/2022] Open
Abstract
Transcranial alternating current stimulation (tACS) is a popular method for modulating brain activity noninvasively. In particular, tACS is often used as a targeted intervention that enhances a neural oscillation at a specific frequency to affect a particular behavior. However, these interventions often yield highly variable results. Here, we provide a potential explanation for this variability: tACS competes with the brain's ongoing oscillations. Using neural recordings from alert nonhuman primates, we find that when neural firing is independent of ongoing brain oscillations, tACS readily entrains spiking activity, but when neurons are strongly entrained to ongoing oscillations, tACS often causes a decrease in entrainment instead. Consequently, tACS can yield categorically different results on neural activity, even when the stimulation protocol is fixed. Mathematical analysis suggests that this competition is likely to occur under many experimental conditions. Attempting to impose an external rhythm on the brain may therefore often yield precisely the opposite effect.
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Affiliation(s)
- Matthew R. Krause
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Pedro G. Vieira
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jean-Philippe Thivierge
- School of Psychology, University of Ottawa, Ottawa, Ontario, Canada
- Brain and Mind Research Institute University of Ottawa, Ottawa, Ontario, Canada
| | - Christopher C. Pack
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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22
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Jung F, Witte V, Yanovsky Y, Klumpp M, Brankack J, Tort ABL, Dr Draguhn A. Differential modulation of parietal cortex activity by respiration and θ-oscillations. J Neurophysiol 2022; 127:801-817. [PMID: 35171722 DOI: 10.1152/jn.00376.2021] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The simultaneous, local integration of information from widespread brain regions is an essential feature of cortical computation and particularly relevant for multimodal association areas such as the posterior parietal cortex. Slow, rhythmic fluctuations in the local field potentials (LFP) are assumed to constitute a global signal aiding interregional communication through the long-range synchronization of neuronal activity. Recent work demonstrated the brain-wide presence of a novel class of slow neuronal oscillations which are entrained by nasal respiration. However, whether there are differences in the influence of the respiration-entrained rhythm (RR) and the endogenous theta (θ) rhythm over local networks is unknown. In this work, we aimed at characterizing the impact of both classes of oscillations on neuronal activity in the posterior parietal cortex of mice. We focused our investigations on a θ-dominated state (REM sleep) and an RR-dominated state (wake immobility). Using linear silicon probes implanted along the dorsoventral cortical axis, we found that the LFP-depth distributions of both rhythms show differences in amplitude and coherence but no phase shift. Using tetrode recordings, we demonstrate that a substantial fraction of parietal neurons is modulated by either RR or θ or even by both rhythms simultaneously. Interestingly, the phase and cortical depth-dependence of spike-field coupling differ for these oscillations. We further show through intracellular recordings in urethane-anesthetized mice that synaptic inhibition is likely to play a role in generating respiration-entrainment at the membrane potential level. We conclude that θ and respiration differentially affect neuronal activity in the parietal cortex.
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Affiliation(s)
- Felix Jung
- Institute for Physiology and Pathophysiology, Heidelberg University, Heidelberg, Germany.,Department of Biosciences and Nutrition, Karolinska Institute, Stockholm, Sweden
| | - Victoria Witte
- Institute for Physiology and Pathophysiology, Heidelberg University, Heidelberg, Germany
| | - Yevgenij Yanovsky
- Institute for Physiology and Pathophysiology, Heidelberg University, Heidelberg, Germany
| | - Matthias Klumpp
- Institute for Physiology and Pathophysiology, Heidelberg University, Heidelberg, Germany
| | - Jurij Brankack
- Institute for Physiology and Pathophysiology, Heidelberg University, Heidelberg, Germany
| | - Adriano B L Tort
- Brain Institute, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Andreas Dr Draguhn
- Institute for Physiology and Pathophysiology, Heidelberg University, Heidelberg, Germany
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23
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Jing R, Yang C, Huang X, Li W. Perceptual learning as a result of concerted changes in prefrontal and visual cortex. Curr Biol 2021; 31:4521-4533.e3. [PMID: 34450086 DOI: 10.1016/j.cub.2021.08.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 07/12/2021] [Accepted: 08/02/2021] [Indexed: 01/05/2023]
Abstract
Our perceptual ability remarkably improves with training. Some studies on visual perceptual learning have shown refined neural representation of the trained stimulus in the visual cortex, whereas others have exclusively argued for improved readout and decision-making processes in the frontoparietal cortex. The mixed results have rendered the underlying neural mechanisms puzzling and hotly debated. By simultaneously recording from monkey visual area V4 and ventrolateral prefrontal cortex (PFC) implanted with microelectrode arrays, we dissected learning-induced cortical changes over the course of training the monkeys in a global form detection task. Decoding analysis dissociated two distinct components of neuronal population codes that were progressively and markedly enhanced in both V4 and PFC. One component was closely related to the target stimulus feature and was subject to task-dependent top-down modulation; it emerged earlier in V4 than PFC and its enhancement was specific to the trained configuration of the target stimulus. The other component of the neural code was entirely related to the animal's behavioral choice; it emerged earlier in PFC than V4 and its enhancement completely generalized to an untrained stimulus configuration. These results implicate two concurrent and synergistic learning processes: a perceptual process that is specific to the details of the trained stimulus feature and a cognitive process that is dependent on the total amount of learning experience in the trained task. When combined, these two learning processes were well predictive of the animal's learning behavior.
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Affiliation(s)
- Rui Jing
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Chen Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Xin Huang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Wu Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; College of Life Sciences, Beijing Normal University, Beijing 100875, China.
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24
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Nakajima M. Neuronal identity and cognitive control dynamics in the PFC. Semin Cell Dev Biol 2021; 129:14-21. [PMID: 34535385 DOI: 10.1016/j.semcdb.2021.08.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 06/14/2021] [Accepted: 08/30/2021] [Indexed: 10/20/2022]
Abstract
Adaptive behavior is supported by context-dependent cognitive control that enables stable and flexible sensorimotor transformations. Impairments in this type of control are often attributed to dysfunction in the prefrontal cortex (PFC). However, the underlying circuit principles of PFC function that support cognitive control have remained elusive. While the complex, diverse responses of PFC neurons to cognitive variables have been studied both from the perspective of individual cell activity and overall population dynamics, these two levels have often been investigated separately. This review discusses two specific cell groups, context/brain state responsive interneuron subtypes and output decoder neurons, that might bridge conceptual frameworks derived from these two research approaches. I highlight the unique properties and functions of these cell groups and discuss how future studies leveraging their features are likely to provide a new understanding of PFC dynamics combining single-neuron and network perspectives.
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Affiliation(s)
- Miho Nakajima
- Center for Brain Science, RIKEN, Wako, Saitama 351-0198, Japan.
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25
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Tang Y, Wu Q, Gao M, Ryu E, Pei Z, Kissinger ST, Chen Y, Rao AK, Xiang Z, Wang T, Li W, Chen G, Chubykin AA. Restoration of Visual Function and Cortical Connectivity After Ischemic Injury Through NeuroD1-Mediated Gene Therapy. Front Cell Dev Biol 2021; 9:720078. [PMID: 34490268 PMCID: PMC8416524 DOI: 10.3389/fcell.2021.720078] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 07/30/2021] [Indexed: 11/13/2022] Open
Abstract
Neural circuits underlying brain functions are vulnerable to damage, including ischemic injury, leading to neuronal loss and gliosis. Recent technology of direct conversion of endogenous astrocytes into neurons in situ can simultaneously replenish the neuronal population and reverse the glial scar. However, whether these newly reprogrammed neurons undergo normal development, integrate into the existing neuronal circuit, and acquire functional properties specific for this circuit is not known. We investigated the effect of NeuroD1-mediated in vivo direct reprogramming on visual cortical circuit integration and functional recovery in a mouse model of ischemic injury. After performing electrophysiological extracellular recordings and two-photon calcium imaging of reprogrammed cells in vivo and mapping the synaptic connections formed onto these cells ex vivo, we discovered that NeuroD1 reprogrammed neurons were integrated into the cortical microcircuit and acquired direct visual responses. Furthermore, following visual experience, the reprogrammed neurons demonstrated maturation of orientation selectivity and functional connectivity. Our results show that NeuroD1-reprogrammed neurons can successfully develop and integrate into the visual cortical circuit leading to vision recovery after ischemic injury.
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Affiliation(s)
- Yu Tang
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN, United States
| | - Qiuyu Wu
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN, United States
| | - Mang Gao
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN, United States
| | - Esther Ryu
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN, United States
| | - Zifei Pei
- Department of Biology, Huck Institutes of Life Sciences, Pennsylvania State University, University Park, PA, United States
| | - Samuel T. Kissinger
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN, United States
| | - Yuchen Chen
- Department of Biology, Huck Institutes of Life Sciences, Pennsylvania State University, University Park, PA, United States
| | - Abhinav K. Rao
- Department of Biology, Huck Institutes of Life Sciences, Pennsylvania State University, University Park, PA, United States
| | - Zongqin Xiang
- Guangdong-Hong Kong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, China
| | - Tao Wang
- Guangdong-Hong Kong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, China
| | - Wen Li
- Guangdong-Hong Kong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, China
| | - Gong Chen
- Department of Biology, Huck Institutes of Life Sciences, Pennsylvania State University, University Park, PA, United States
- Guangdong-Hong Kong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, China
| | - Alexander A. Chubykin
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN, United States
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26
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Lee EK, Balasubramanian H, Tsolias A, Anakwe SU, Medalla M, Shenoy KV, Chandrasekaran C. Non-linear dimensionality reduction on extracellular waveforms reveals cell type diversity in premotor cortex. eLife 2021; 10:e67490. [PMID: 34355695 PMCID: PMC8452311 DOI: 10.7554/elife.67490] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 08/04/2021] [Indexed: 11/13/2022] Open
Abstract
Cortical circuits are thought to contain a large number of cell types that coordinate to produce behavior. Current in vivo methods rely on clustering of specified features of extracellular waveforms to identify putative cell types, but these capture only a small amount of variation. Here, we develop a new method (WaveMAP) that combines non-linear dimensionality reduction with graph clustering to identify putative cell types. We apply WaveMAP to extracellular waveforms recorded from dorsal premotor cortex of macaque monkeys performing a decision-making task. Using WaveMAP, we robustly establish eight waveform clusters and show that these clusters recapitulate previously identified narrow- and broad-spiking types while revealing previously unknown diversity within these subtypes. The eight clusters exhibited distinct laminar distributions, characteristic firing rate patterns, and decision-related dynamics. Such insights were weaker when using feature-based approaches. WaveMAP therefore provides a more nuanced understanding of the dynamics of cell types in cortical circuits.
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Affiliation(s)
- Eric Kenji Lee
- Psychological and Brain Sciences, Boston UniversityBostonUnited States
| | - Hymavathy Balasubramanian
- Bernstein Center for Computational Neuroscience, Bernstein Center for Computational NeuroscienceBerlinGermany
| | - Alexandra Tsolias
- Department of Anatomy and Neurobiology, Boston UniversityBostonUnited States
| | | | - Maria Medalla
- Department of Anatomy and Neurobiology, Boston UniversityBostonUnited States
| | - Krishna V Shenoy
- Department of Electrical Engineering, Stanford UniversityStanfordUnited States
- Department of Bioengineering, Stanford UniversityStanfordUnited States
- Department of Neurobiology, Stanford UniversityStanfordUnited States
- Wu Tsai Neurosciences Institute, Stanford UniversityStanfordUnited States
- Bio-X Institute, Stanford UniversityStanfordUnited States
- Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Chandramouli Chandrasekaran
- Psychological and Brain Sciences, Boston UniversityBostonUnited States
- Department of Anatomy and Neurobiology, Boston UniversityBostonUnited States
- Center for Systems Neuroscience, Boston UniversityBostonUnited States
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
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27
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Rodríguez-Collado A, Rueda C. A simple parametric representation of the Hodgkin-Huxley model. PLoS One 2021; 16:e0254152. [PMID: 34292948 PMCID: PMC8297874 DOI: 10.1371/journal.pone.0254152] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 06/21/2021] [Indexed: 02/04/2023] Open
Abstract
The Hodgkin-Huxley model, decades after its first presentation, is still a reference model in neuroscience as it has successfully reproduced the electrophysiological activity of many organisms. The primary signal in the model represents the membrane potential of a neuron. A simple representation of this signal is presented in this paper. The new proposal is an adapted Frequency Modulated Möbius multicomponent model defined as a signal plus error model in which the signal is decomposed as a sum of waves. The main strengths of the method are the simple parametric formulation, the interpretability and flexibility of the parameters that describe and discriminate the waveforms, the estimators' identifiability and accuracy, and the robustness against noise. The approach is validated with a broad simulation experiment of Hodgkin-Huxley signals and real data from squid giant axons. Interesting differences between simulated and real data emerge from the comparison of the parameter configurations. Furthermore, the potential of the FMM parameters to predict Hodgkin-Huxley model parameters is shown using different Machine Learning methods. Finally, promising contributions of the approach in Spike Sorting and cell-type classification are detailed.
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Affiliation(s)
| | - Cristina Rueda
- Department of Statistics and Operations Research, Universidad de Valladolid, Valladolid, Spain
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28
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Paulk AC, Yang JC, Cleary DR, Soper DJ, Halgren M, O’Donnell AR, Lee SH, Ganji M, Ro YG, Oh H, Hossain L, Lee J, Tchoe Y, Rogers N, Kiliç K, Ryu SB, Lee SW, Hermiz J, Gilja V, Ulbert I, Fabó D, Thesen T, Doyle WK, Devinsky O, Madsen JR, Schomer DL, Eskandar EN, Lee JW, Maus D, Devor A, Fried SI, Jones PS, Nahed BV, Ben-Haim S, Bick SK, Richardson RM, Raslan AM, Siler DA, Cahill DP, Williams ZM, Cosgrove GR, Dayeh SA, Cash SS. Microscale Physiological Events on the Human Cortical Surface. Cereb Cortex 2021; 31:3678-3700. [PMID: 33749727 PMCID: PMC8258438 DOI: 10.1093/cercor/bhab040] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Revised: 02/05/2021] [Accepted: 02/07/2021] [Indexed: 01/14/2023] Open
Abstract
Despite ongoing advances in our understanding of local single-cellular and network-level activity of neuronal populations in the human brain, extraordinarily little is known about their "intermediate" microscale local circuit dynamics. Here, we utilized ultra-high-density microelectrode arrays and a rare opportunity to perform intracranial recordings across multiple cortical areas in human participants to discover three distinct classes of cortical activity that are not locked to ongoing natural brain rhythmic activity. The first included fast waveforms similar to extracellular single-unit activity. The other two types were discrete events with slower waveform dynamics and were found preferentially in upper cortical layers. These second and third types were also observed in rodents, nonhuman primates, and semi-chronic recordings from humans via laminar and Utah array microelectrodes. The rates of all three events were selectively modulated by auditory and electrical stimuli, pharmacological manipulation, and cold saline application and had small causal co-occurrences. These results suggest that the proper combination of high-resolution microelectrodes and analytic techniques can capture neuronal dynamics that lay between somatic action potentials and aggregate population activity. Understanding intermediate microscale dynamics in relation to single-cell and network dynamics may reveal important details about activity in the full cortical circuit.
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Affiliation(s)
- Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jimmy C Yang
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Daniel R Cleary
- Departments of Neurosciences and Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Department of Physics, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosurgery, University of California San Diego, La Jolla, CA 92093, USA
| | - Daniel J Soper
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Mila Halgren
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | - Sang Heon Lee
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Mehran Ganji
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Yun Goo Ro
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Hongseok Oh
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Lorraine Hossain
- Materials Science and Engineering Program, University of California San Diego, La Jolla, CA 92093, USA
| | - Jihwan Lee
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Youngbin Tchoe
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Nicholas Rogers
- Department of Physics, University of California San Diego, La Jolla, CA 92093, USA
| | - Kivilcim Kiliç
- Departments of Neurosciences and Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Sang Baek Ryu
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Seung Woo Lee
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
| | - John Hermiz
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Vikash Gilja
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - István Ulbert
- Research Centre for Natural Sciences, Institute of Cognitive Neuroscience and Psychology, 1519 Budapest, Hungary
- Pázmány Péter Catholic University, Faculty of Information Technology and Bionics, H-1444 Budapest, Hungary
| | - Daniel Fabó
- Epilepsy Centrum, National Institute of Clinical Neurosciences, 1145 Budapest, Hungary
| | - Thomas Thesen
- Department of Biomedical Sciences, University of Houston College of Medicine, Houston, TX 77204, USA
- Comprehensive Epilepsy Center, New York University School of Medicine, New York City, NY 10016, USA
| | - Werner K Doyle
- Comprehensive Epilepsy Center, New York University School of Medicine, New York City, NY 10016, USA
| | - Orrin Devinsky
- Comprehensive Epilepsy Center, New York University School of Medicine, New York City, NY 10016, USA
| | - Joseph R Madsen
- Departments of Neurosurgery, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Donald L Schomer
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Emad N Eskandar
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
- Albert Einstein College of Medicine, Montefiore Medical Center, Department of Neurosurgery, Bronx, NY 10467, USA
| | - Jong Woo Lee
- Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Douglas Maus
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Anna Devor
- Departments of Neurosciences and Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Shelley I Fried
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
- Boston VA Healthcare System, 150 South Huntington Avenue, Boston, MA 02130, USA
| | - Pamela S Jones
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Brian V Nahed
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Sharona Ben-Haim
- Department of Neurosurgery, University of California San Diego, La Jolla, CA 92093, USA
| | - Sarah K Bick
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Ahmed M Raslan
- Department of Neurological Surgery, Oregon Health and Science University, Portland, OR 97239, USA
| | - Dominic A Siler
- Department of Neurological Surgery, Oregon Health and Science University, Portland, OR 97239, USA
| | - Daniel P Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Shadi A Dayeh
- Department of Neurosurgery, University of California San Diego, La Jolla, CA 92093, USA
- Materials Science and Engineering Program, University of California San Diego, La Jolla, CA 92093, USA
- Department of Nanoengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
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29
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Banaie Boroujeni K, Tiesinga P, Womelsdorf T. Interneuron-specific gamma synchronization indexes cue uncertainty and prediction errors in lateral prefrontal and anterior cingulate cortex. eLife 2021; 10:69111. [PMID: 34142661 PMCID: PMC8248985 DOI: 10.7554/elife.69111] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 06/17/2021] [Indexed: 12/27/2022] Open
Abstract
Inhibitory interneurons are believed to realize critical gating functions in cortical circuits, but it has been difficult to ascertain the content of gated information for well-characterized interneurons in primate cortex. Here, we address this question by characterizing putative interneurons in primate prefrontal and anterior cingulate cortex while monkeys engaged in attention demanding reversal learning. We find that subclasses of narrow spiking neurons have a relative suppressive effect on the local circuit indicating they are inhibitory interneurons. One of these interneuron subclasses showed prominent firing rate modulations and (35–45 Hz) gamma synchronous spiking during periods of uncertainty in both, lateral prefrontal cortex (LPFC) and anterior cingulate cortex (ACC). In LPFC, this interneuron subclass activated when the uncertainty of attention cues was resolved during flexible learning, whereas in ACC it fired and gamma-synchronized when outcomes were uncertain and prediction errors were high during learning. Computational modeling of this interneuron-specific gamma band activity in simple circuit motifs suggests it could reflect a soft winner-take-all gating of information having high degree of uncertainty. Together, these findings elucidate an electrophysiologically characterized interneuron subclass in the primate, that forms gamma synchronous networks in two different areas when resolving uncertainty during adaptive goal-directed behavior.
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Affiliation(s)
| | - Paul Tiesinga
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Thilo Womelsdorf
- Department of Psychology, Vanderbilt University, Nashville, United States.,Department of Biology, Centre for Vision Research, York University, Toronto, Canada
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30
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Bollimunta A, Santacruz SR, Eaton RW, Xu PS, Morrison JH, Moxon KA, Carmena JM, Nassi JJ. Head-mounted microendoscopic calcium imaging in dorsal premotor cortex of behaving rhesus macaque. Cell Rep 2021; 35:109239. [PMID: 34133921 PMCID: PMC8236375 DOI: 10.1016/j.celrep.2021.109239] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 04/07/2021] [Accepted: 05/18/2021] [Indexed: 01/07/2023] Open
Abstract
Microendoscopic calcium imaging with one-photon miniature microscopes enables unprecedented readout of neural circuit dynamics during active behavior in rodents. In this study, we describe successful application of this technology in the rhesus macaque, demonstrating plug-and-play, head-mounted recordings of cellular-resolution calcium dynamics from large populations of neurons simultaneously in bilateral dorsal premotor cortices during performance of a naturalistic motor reach task. Imaging is stable over several months, allowing us to longitudinally track individual neurons and monitor their relationship to motor behavior over time. We observe neuronal calcium dynamics selective for reach direction, which we could use to decode the animal's trial-by-trial motor behavior. This work establishes head-mounted microendoscopic calcium imaging in macaques as a powerful approach for studying the neural circuit mechanisms underlying complex and clinically relevant behaviors, and it promises to greatly advance our understanding of human brain function, as well as its dysfunction in neurological disease.
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Affiliation(s)
- Anil Bollimunta
- Inscopix, Inc., 2462 Embarcadero Way, Palo Alto, CA 94303, USA,These authors contributed equally
| | - Samantha R. Santacruz
- Department of Electrical Engineering and Computer Science, Helen Wills Neuroscience Institute, University of California, Berkeley, 286 Li Ka Shing, MC #3370, Berkeley, CA 94720, USA,Department of Biomedical Engineering, Institute for Neuroscience, The University of Texas at Austin, 107 W. Dean Keeton Street, Stop C0800, Austin, TX 78712, USA,These authors contributed equally
| | - Ryan W. Eaton
- Department of Biomedical Engineering, University of California, Davis, 3141 Health Sciences Drive, Davis, CA 95616, USA,California National Primate Research Center, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Pei S. Xu
- Inscopix, Inc., 2462 Embarcadero Way, Palo Alto, CA 94303, USA
| | - John H. Morrison
- California National Primate Research Center, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA,Department of Neurology, School of Medicine, University of California Davis, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Karen A. Moxon
- Department of Biomedical Engineering, University of California, Davis, 3141 Health Sciences Drive, Davis, CA 95616, USA,California National Primate Research Center, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Jose M. Carmena
- Department of Electrical Engineering and Computer Science, Helen Wills Neuroscience Institute, University of California, Berkeley, 286 Li Ka Shing, MC #3370, Berkeley, CA 94720, USA,Senior author
| | - Jonathan J. Nassi
- Inscopix, Inc., 2462 Embarcadero Way, Palo Alto, CA 94303, USA,Senior author,Lead contact,Correspondence:
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31
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Lemon RN, Baker SN, Kraskov A. Classification of Cortical Neurons by Spike Shape and the Identification of Pyramidal Neurons. Cereb Cortex 2021; 31:5131-5138. [PMID: 34117760 PMCID: PMC8491674 DOI: 10.1093/cercor/bhab147] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Many investigators who make extracellular recordings from populations of cortical neurons are now using spike shape parameters, and particularly spike duration, as a means of classifying different neuronal sub-types. Because of the nature of the experimental approach, particularly that involving nonhuman primates, it is very difficult to validate directly which spike characteristics belong to particular types of pyramidal neurons and interneurons, as defined by modern histological approaches. This commentary looks at the way antidromic identification of pyramidal cells projecting to different targets, and in particular, pyramidal tract neurons (PTN), can inform the utility of spike width classification. Spike duration may provide clues to a diversity of function across the pyramidal cell population, and also highlights important differences that exist across species. Our studies suggest that further electrophysiological and optogenetic approaches are needed to validate spike duration as a means of cell classification and to relate this to well-established histological differences in neocortical cell types.
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Affiliation(s)
- Roger N Lemon
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Stuart N Baker
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Alexander Kraskov
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
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32
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Puppo F, Sadegh S, Trujillo CA, Thunemann M, Campbell EP, Vandenberghe M, Shan X, Akkouh IA, Miller EW, Bloodgood BL, Silva GA, Dale AM, Einevoll GT, Djurovic S, Andreassen OA, Muotri AR, Devor A. All-Optical Electrophysiology in hiPSC-Derived Neurons With Synthetic Voltage Sensors. Front Cell Neurosci 2021; 15:671549. [PMID: 34122014 PMCID: PMC8193062 DOI: 10.3389/fncel.2021.671549] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 05/03/2021] [Indexed: 12/26/2022] Open
Abstract
Voltage imaging and “all-optical electrophysiology” in human induced pluripotent stem cell (hiPSC)-derived neurons have opened unprecedented opportunities for high-throughput phenotyping of activity in neurons possessing unique genetic backgrounds of individual patients. While prior all-optical electrophysiology studies relied on genetically encoded voltage indicators, here, we demonstrate an alternative protocol using a synthetic voltage sensor and genetically encoded optogenetic actuator that generate robust and reproducible results. We demonstrate the functionality of this method by measuring spontaneous and evoked activity in three independent hiPSC-derived neuronal cell lines with distinct genetic backgrounds.
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Affiliation(s)
- Francesca Puppo
- Department of Pediatrics/Rady Children's Hospital San Diego, School of Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Sanaz Sadegh
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Cleber A Trujillo
- Department of Pediatrics/Rady Children's Hospital San Diego, School of Medicine, University of California, San Diego, La Jolla, CA, United States.,Department of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Martin Thunemann
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
| | - Evan P Campbell
- Division of Biological Sciences, Section of Neurobiology, University of California, San Diego, La Jolla, CA, United States
| | - Matthieu Vandenberghe
- Division of Mental Health and Addiction, Oslo University Hospital, NORMENT, KG Jebsen Centre for Neurodevelopmental Disorders, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Xiwei Shan
- Department of Pediatrics/Rady Children's Hospital San Diego, School of Medicine, University of California, San Diego, La Jolla, CA, United States.,Department of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Ibrahim A Akkouh
- Division of Mental Health and Addiction, Oslo University Hospital, NORMENT, KG Jebsen Centre for Neurodevelopmental Disorders, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Evan W Miller
- Department of Chemistry and Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, United States
| | - Brenda L Bloodgood
- Division of Biological Sciences, Section of Neurobiology, University of California, San Diego, La Jolla, CA, United States
| | - Gabriel A Silva
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Gaute T Einevoll
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.,NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ole A Andreassen
- Division of Mental Health and Addiction, Oslo University Hospital, NORMENT, KG Jebsen Centre for Neurodevelopmental Disorders, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Alysson R Muotri
- Department of Pediatrics/Rady Children's Hospital San Diego, School of Medicine, University of California, San Diego, La Jolla, CA, United States.,Department of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, United States.,Kavli Institute for Brain and Mind and Halıcıoglu Data Science Institute, University of California, San Diego, La Jolla, CA, United States.,Center for Academic Research and Training in Anthropogeny (CARTA), La Jolla, CA, United States
| | - Anna Devor
- Department of Biomedical Engineering, Boston University, Boston, MA, United States.,Department of Radiology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
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33
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Local and system mechanisms for action execution and observation in parietal and premotor cortices. Curr Biol 2021; 31:2819-2830.e4. [PMID: 33984266 PMCID: PMC8279740 DOI: 10.1016/j.cub.2021.04.034] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 12/23/2020] [Accepted: 04/14/2021] [Indexed: 11/16/2022]
Abstract
The action observation network (AON) includes a system of brain areas largely shared with action execution in both human and nonhuman primates. Yet temporal and tuning specificities of distinct areas and of physiologically identified neuronal classes in the encoding of self and others’ action remain unknown. We recorded the activity of 355 single units from three crucial nodes of the AON, the anterior intraparietal area (AIP), and premotor areas F5 and F6, while monkeys performed a Go/No-Go grasping task and observed an experimenter performing it. At the system level, during task execution, F6 displays a prevalence of suppressed neurons and signals whether an action has to be performed, whereas AIP and F5 share a prevalence of facilitated neurons and remarkable target selectivity; during task observation, F5 stands out for its unique prevalence of facilitated neurons and its stronger and earlier modulation than AIP and F6. By applying unsupervised clustering of spike waveforms, we found distinct cell classes unevenly distributed across areas, with different firing properties and carrying specific visuomotor signals. Broadly spiking neurons exhibited a balanced amount of facilitated and suppressed activity during action execution and observation, whereas narrower spiking neurons showed more mutually facilitated responses during the execution of one’s own and others’ action, particularly in areas AIP and F5. Our findings elucidate the time course of activity and firing properties of neurons in the AON during one’s own and others’ action, from the system level of anatomically distinct areas to the local level of physiologically distinct cell classes. F6 neurons show a prevalence of suppressed activity, encoding whether to act Area F5 and AIP share a prevalence of facilitated neurons and target selectivity Across-areas, waveform-based clustering distinguished three neuronal classes Narrow-spiking neurons exhibit mutual modulation during self and others’ action
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de Filippo R, Rost BR, Stumpf A, Cooper C, Tukker JJ, Harms C, Beed P, Schmitz D. Somatostatin interneurons activated by 5-HT 2A receptor suppress slow oscillations in medial entorhinal cortex. eLife 2021; 10:66960. [PMID: 33789079 PMCID: PMC8016478 DOI: 10.7554/elife.66960] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 03/10/2021] [Indexed: 12/31/2022] Open
Abstract
Serotonin (5-HT) is one of the major neuromodulators present in the mammalian brain and has been shown to play a role in multiple physiological processes. The mechanisms by which 5-HT modulates cortical network activity, however, are not yet fully understood. We investigated the effects of 5-HT on slow oscillations (SOs), a synchronized cortical network activity universally present across species. SOs are observed during anesthesia and are considered to be the default cortical activity pattern. We discovered that (±)3,4-methylenedioxymethamphetamine (MDMA) and fenfluramine, two potent 5-HT releasers, inhibit SOs within the entorhinal cortex (EC) in anesthetized mice. Combining opto- and pharmacogenetic manipulations with in vitro electrophysiological recordings, we uncovered that somatostatin-expressing (Sst) interneurons activated by the 5-HT2A receptor (5-HT2AR) play an important role in the suppression of SOs. Since 5-HT2AR signaling is involved in the etiology of different psychiatric disorders and mediates the psychological effects of many psychoactive serotonergic drugs, we propose that the newly discovered link between Sst interneurons and 5-HT will contribute to our understanding of these complex topics.
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Affiliation(s)
- Roberto de Filippo
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Neuroscience Research Center, Berlin, Germany.,Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Cluster of Excellence NeuroCure, Berlin, Germany
| | - Benjamin R Rost
- German Centre for Neurodegenerative Diseases (DZNE), Berlin, Germany
| | - Alexander Stumpf
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Neuroscience Research Center, Berlin, Germany
| | - Claire Cooper
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Neuroscience Research Center, Berlin, Germany
| | - John J Tukker
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Neuroscience Research Center, Berlin, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Berlin, Germany
| | - Christoph Harms
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Department of Experimental Neurology, Berlin, Germany.,Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Center for Stroke Research Berlin, Berlin, Germany.,Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Einstein Center for Neurosciences Berlin, Berlin, Germany
| | - Prateep Beed
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Neuroscience Research Center, Berlin, Germany
| | - Dietmar Schmitz
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Neuroscience Research Center, Berlin, Germany.,Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Cluster of Excellence NeuroCure, Berlin, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Einstein Center for Neurosciences Berlin, Berlin, Germany
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Mosher CP, Wei Y, Kamiński J, Nandi A, Mamelak AN, Anastassiou CA, Rutishauser U. Cellular Classes in the Human Brain Revealed In Vivo by Heartbeat-Related Modulation of the Extracellular Action Potential Waveform. Cell Rep 2021; 30:3536-3551.e6. [PMID: 32160555 DOI: 10.1016/j.celrep.2020.02.027] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 12/23/2019] [Accepted: 02/05/2020] [Indexed: 01/01/2023] Open
Abstract
Determining cell types is critical for understanding neural circuits but remains elusive in the living human brain. Current approaches discriminate units into putative cell classes using features of the extracellular action potential (EAP); in absence of ground truth data, this remains a problematic procedure. We find that EAPs in deep structures of the brain exhibit robust and systematic variability during the cardiac cycle. These cardiac-related features refine neural classification. We use these features to link bio-realistic models generated from in vitro human whole-cell recordings of morphologically classified neurons to in vivo recordings. We differentiate aspiny inhibitory and spiny excitatory human hippocampal neurons and, in a second stage, demonstrate that cardiac-motion features reveal two types of spiny neurons with distinct intrinsic electrophysiological properties and phase-locking characteristics to endogenous oscillations. This multi-modal approach markedly improves cell classification in humans, offers interpretable cell classes, and is applicable to other brain areas and species.
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Affiliation(s)
- Clayton P Mosher
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Yina Wei
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jan Kamiński
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Division of Biology and Biological Engineering, Caltech, Pasadena, CA 91125, USA
| | - Anirban Nandi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Adam N Mamelak
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Costas A Anastassiou
- Allen Institute for Brain Science, Seattle, WA 98109, USA; Division of Neurology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
| | - Ueli Rutishauser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Division of Biology and Biological Engineering, Caltech, Pasadena, CA 91125, USA.
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36
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Neuronal Firing and Waveform Alterations through Ictal Recruitment in Humans. J Neurosci 2020; 41:766-779. [PMID: 33229500 DOI: 10.1523/jneurosci.0417-20.2020] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 10/29/2020] [Accepted: 11/11/2020] [Indexed: 01/04/2023] Open
Abstract
Analyzing neuronal activity during human seizures is pivotal to understanding mechanisms of seizure onset and propagation. These analyses, however, invariably using extracellular recordings, are greatly hindered by various phenomena that are well established in animal studies: changes in local ionic concentration, changes in ionic conductance, and intense, hypersynchronous firing. The first two alter the action potential waveform, whereas the third increases the "noise"; all three factors confound attempts to detect and classify single neurons. To address these analytical difficulties, we developed a novel template-matching-based spike sorting method, which enabled identification of 1239 single neurons in 27 patients (13 female) with intractable focal epilepsy, that were tracked throughout multiple seizures. These new analyses showed continued neuronal firing with widespread intense activation and stereotyped action potential alterations in tissue that was invaded by the seizure: neurons displayed increased waveform duration (p < 0.001) and reduced amplitude (p < 0.001), consistent with prior animal studies. By contrast, neurons in "penumbral" regions (those receiving intense local synaptic drive from the seizure but without neuronal evidence of local seizure invasion) showed stable waveforms. All neurons returned to their preictal waveforms after seizure termination. We conclude that the distinction between "core" territories invaded by the seizure versus "penumbral" territories is evident at the level of single neurons. Furthermore, the increased waveform duration and decreased waveform amplitude are neuron-intrinsic hallmarks of seizure invasion that impede traditional spike sorting and could be used as defining characteristics of local recruitment.SIGNIFICANCE STATEMENT Animal studies consistently show marked changes in action potential waveform during epileptic discharges, but acquiring similar evidence in humans has proven difficult. Assessing neuronal involvement in ictal events is pivotal to understanding seizure dynamics and in defining clinical localization of epileptic pathology. Using a novel method to track neuronal firing, we analyzed microelectrode array recordings of spontaneously occurring human seizures, and here report two dichotomous activity patterns. In cortex that is recruited to the seizure, neuronal firing rates increase and waveforms become longer in duration and shorter in amplitude as the neurons are recruited to the seizure, while penumbral tissue shows stable action potentials, in keeping with the "dual territory" model of seizure dynamics.
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37
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Shi Z, Chen X, Zhao C, He H, Stuphorn V, Wu D. Multi-View Broad Learning System for Primate Oculomotor Decision Decoding. IEEE Trans Neural Syst Rehabil Eng 2020; 28:1908-1920. [PMID: 32746296 PMCID: PMC7521581 DOI: 10.1109/tnsre.2020.3003342] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Multi-view learning improves the learning performance by utilizing multi-view data: data collected from multiple sources, or feature sets extracted from the same data source. This approach is suitable for primate brain state decoding using cortical neural signals. This is because the complementary components of simultaneously recorded neural signals, local field potentials (LFPs) and action potentials (spikes), can be treated as two views. In this paper, we extended broad learning system (BLS), a recently proposed wide neural network architecture, from single-view learning to multi-view learning, and validated its performance in decoding monkeys' oculomotor decision from medial frontal LFPs and spikes. We demonstrated that medial frontal LFPs and spikes in non-human primate do contain complementary information about the oculomotor decision, and that the proposed multi-view BLS is a more effective approach for decoding the oculomotor decision than several classical and state-of-the-art single-view and multi-view learning approaches.
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Affiliation(s)
- Zhenhua Shi
- Ministry of Education Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaomo Chen
- Zanvyl Krieger Mind and Brain Institute, Johns Hopkins University School of Medicine
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38
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Malvaut S, Constantinescu VS, Dehez H, Doric S, Saghatelyan A. Deciphering Brain Function by Miniaturized Fluorescence Microscopy in Freely Behaving Animals. Front Neurosci 2020; 14:819. [PMID: 32848576 PMCID: PMC7432153 DOI: 10.3389/fnins.2020.00819] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 07/14/2020] [Indexed: 11/19/2022] Open
Abstract
Animal behavior is regulated by environmental stimuli and is shaped by the activity of neural networks, underscoring the importance of assessing the morpho-functional properties of different populations of cells in freely behaving animals. In recent years, a number of optical tools have been developed to monitor and modulate neuronal and glial activity at the protein, cellular, or network level and have opened up new avenues for studying brain function in freely behaving animals. Tools such as genetically encoded sensors and actuators are now commonly used for studying brain activity and function through their expression in different neuronal ensembles. In parallel, microscopy has also made major progress over the last decades. The advent of miniature microscopes (mini-microscopes also called mini-endoscopes) has become a method of choice for studying brain activity at the cellular and network levels in different brain regions of freely behaving mice. This technique also allows for longitudinal investigations while animals carrying the microscope on their head are performing behavioral tasks. In this review, we will discuss mini-endoscopic imaging and the advantages that these devices offer to research. We will also discuss current limitations of and potential future improvements in mini-endoscopic imaging.
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Affiliation(s)
- Sarah Malvaut
- CERVO Brain Research Center, Quebec City, QC, Canada
- Department of Psychiatry and Neuroscience, Universite Laval, Quebec City, QC, Canada
| | - Vlad-Stefan Constantinescu
- CERVO Brain Research Center, Quebec City, QC, Canada
- Department of Psychiatry and Neuroscience, Universite Laval, Quebec City, QC, Canada
| | | | - Sead Doric
- Doric Lenses Inc., Quebec City, QC, Canada
| | - Armen Saghatelyan
- CERVO Brain Research Center, Quebec City, QC, Canada
- Department of Psychiatry and Neuroscience, Universite Laval, Quebec City, QC, Canada
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39
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Chari A, Thornton RC, Tisdall MM, Scott RC. Microelectrode recordings in human epilepsy: a case for clinical translation. Brain Commun 2020; 2:fcaa082. [PMID: 32954332 PMCID: PMC7472902 DOI: 10.1093/braincomms/fcaa082] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 04/21/2020] [Accepted: 04/28/2020] [Indexed: 12/25/2022] Open
Abstract
With their 'all-or-none' action potential responses, single neurons (or units) are accepted as the basic computational unit of the brain. There is extensive animal literature to support the mechanistic importance of studying neuronal firing as a way to understand neuronal microcircuits and brain function. Although most studies have emphasized physiology, there is increasing recognition that studying single units provides novel insight into system-level mechanisms of disease. Microelectrode recordings are becoming more common in humans, paralleling the increasing use of intracranial electroencephalography recordings in the context of presurgical evaluation in focal epilepsy. In addition to single-unit data, microelectrode recordings also record local field potentials and high-frequency oscillations, some of which may be different to that recorded by clinical macroelectrodes. However, microelectrodes are being used almost exclusively in research contexts and there are currently no indications for incorporating microelectrode recordings into routine clinical care. In this review, we summarize the lessons learnt from 65 years of microelectrode recordings in human epilepsy patients. We cover the electrode constructs that can be utilized, principles of how to record and process microelectrode data and insights into ictal dynamics, interictal dynamics and cognition. We end with a critique on the possibilities of incorporating single-unit recordings into clinical care, with a focus on potential clinical indications, each with their specific evidence base and challenges.
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Affiliation(s)
- Aswin Chari
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Department of Neurosurgery, Great Ormond Street Hospital, London WC1N 3JH, UK
| | - Rachel C Thornton
- Department of Clinical Neurophysiology, Great Ormond Street Hospital, London WC1N 3JH, UK
| | - Martin M Tisdall
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Department of Neurosurgery, Great Ormond Street Hospital, London WC1N 3JH, UK
| | - Rodney C Scott
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Department of Neurological Sciences, University of Vermont, Burlington, VT 05405, USA
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40
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Torres-Gomez S, Blonde JD, Mendoza-Halliday D, Kuebler E, Everest M, Wang XJ, Inoue W, Poulter MO, Martinez-Trujillo J. Changes in the Proportion of Inhibitory Interneuron Types from Sensory to Executive Areas of the Primate Neocortex: Implications for the Origins of Working Memory Representations. Cereb Cortex 2020; 30:4544-4562. [PMID: 32227119 DOI: 10.1093/cercor/bhaa056] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Neuronal spiking activity encoding working memory (WM) is robust in primate association cortices but weak or absent in early sensory cortices. This may be linked to changes in the proportion of neuronal types across areas that influence circuits' ability to generate recurrent excitation. We recorded neuronal activity from areas middle temporal (MT), medial superior temporal (MST), and the lateral prefrontal cortex (LPFC) of monkeys performing a WM task and classified neurons as narrow (NS) and broad spiking (BS). The ratio NS/BS decreased from MT > MST > LPFC. We analyzed the Allen Institute database of ex vivo mice/human intracellular recordings to interpret our data. Our analysis suggests that NS neurons correspond to parvalbumin (PV) or somatostatin (SST) interneurons while BS neurons are pyramidal (P) cells or vasoactive intestinal peptide (VIP) interneurons. We labeled neurons in monkey tissue sections of MT/MST and LPFC and found that the proportion of PV in cortical layers 2/3 decreased, while the proportion of CR cells increased from MT/MST to LPFC. Assuming that primate CR/CB/PV cells perform similar computations as mice VIP/SST/PV cells, our results suggest that changes in the proportion of CR and PV neurons in layers 2/3 cells may favor the emergence of activity encoding WM in association areas.
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Affiliation(s)
- Santiago Torres-Gomez
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and the Brain and Mind Institute, Western University, London, Ontario, N6A 5B7, Canada
| | - Jackson D Blonde
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and the Brain and Mind Institute, Western University, London, Ontario, N6A 5B7, Canada
| | - Diego Mendoza-Halliday
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Eric Kuebler
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and the Brain and Mind Institute, Western University, London, Ontario, N6A 5B7, Canada
| | - Michelle Everest
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and the Brain and Mind Institute, Western University, London, Ontario, N6A 5B7, Canada
| | - Xiao Jing Wang
- Center for Neural Science, New York University, New York, NY 10003, USA
| | - Wataru Inoue
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and the Brain and Mind Institute, Western University, London, Ontario, N6A 5B7, Canada
| | - Michael O Poulter
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and the Brain and Mind Institute, Western University, London, Ontario, N6A 5B7, Canada
| | - Julio Martinez-Trujillo
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and the Brain and Mind Institute, Western University, London, Ontario, N6A 5B7, Canada.,Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, N6A5B7, Canada
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41
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Onorato I, Neuenschwander S, Hoy J, Lima B, Rocha KS, Broggini AC, Uran C, Spyropoulos G, Klon-Lipok J, Womelsdorf T, Fries P, Niell C, Singer W, Vinck M. A Distinct Class of Bursting Neurons with Strong Gamma Synchronization and Stimulus Selectivity in Monkey V1. Neuron 2019; 105:180-197.e5. [PMID: 31732258 DOI: 10.1016/j.neuron.2019.09.039] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 07/12/2019] [Accepted: 09/23/2019] [Indexed: 12/12/2022]
Abstract
Cortical computation depends on interactions between excitatory and inhibitory neurons. The contributions of distinct neuron types to sensory processing and network synchronization in primate visual cortex remain largely undetermined. We show that in awake monkey V1, there exists a distinct cell type (››30% of neurons) that has narrow-waveform (NW) action potentials and high spontaneous discharge rates and fires in high-frequency bursts. These neurons are more stimulus selective and phase locked to 30- to 80-Hz gamma oscillations than other neuron types. Unlike other neuron types, their gamma-phase locking is highly predictive of orientation tuning. We find evidence for strong rhythmic inhibition in these neurons, suggesting that they interact with interneurons to act as excitatory pacemakers for the V1 gamma rhythm. We did not find a similar class of NW bursting neurons in L2-L4 of mouse V1. Given its properties, this class of NW bursting neurons should be pivotal for the encoding and transmission of stimulus information.
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Affiliation(s)
- Irene Onorato
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany; International Max Planck Research School for Neural Circuits, Frankfurt am Main, Germany
| | - Sergio Neuenschwander
- Max Planck Institute for Brain Research, Frankfurt, Germany; Brain Institute, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Jennifer Hoy
- Institute of Neuroscience and Department of Biology, University of Oregon, Eugene, OR, USA
| | - Bruss Lima
- Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Katia-Simone Rocha
- Brain Institute, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Ana Clara Broggini
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany
| | - Cem Uran
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany
| | - Georgios Spyropoulos
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany; International Max Planck Research School for Neural Circuits, Frankfurt am Main, Germany
| | - Johanna Klon-Lipok
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany
| | | | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany
| | - Cristopher Niell
- Institute of Neuroscience and Department of Biology, University of Oregon, Eugene, OR, USA
| | - Wolf Singer
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany; Frankfurt Institute for Advanced Studies, Frankfurt, Germany
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany.
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42
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Abstract
Neocortical cells form classes that likely take on unique functional roles in the cortical microcircuit. A new study finds that, with sufficient sampling, the electrophysiological signature of cells distinguishes four cell classes across primate frontal and parietal cortex.
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