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Chintaluri C, Bejtka M, Średniawa W, Czerwiński M, Dzik JM, Jędrzejewska-Szmek J, Wójcik DK. kCSD-python, reliable current source density estimation with quality control. PLoS Comput Biol 2024; 20:e1011941. [PMID: 38484020 DOI: 10.1371/journal.pcbi.1011941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 03/26/2024] [Accepted: 02/23/2024] [Indexed: 03/27/2024] Open
Abstract
Interpretation of extracellular recordings can be challenging due to the long range of electric field. This challenge can be mitigated by estimating the current source density (CSD). Here we introduce kCSD-python, an open Python package implementing Kernel Current Source Density (kCSD) method and related tools to facilitate CSD analysis of experimental data and the interpretation of results. We show how to counter the limitations imposed by noise and assumptions in the method itself. kCSD-python allows CSD estimation for an arbitrary distribution of electrodes in 1D, 2D, and 3D, assuming distributions of sources in tissue, a slice, or in a single cell, and includes a range of diagnostic aids. We demonstrate its features in a Jupyter Notebook tutorial which illustrates a typical analytical workflow and main functionalities useful in validating analysis results.
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Affiliation(s)
- Chaitanya Chintaluri
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Marta Bejtka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Władysław Średniawa
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Michał Czerwiński
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Jakub M Dzik
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Joanna Jędrzejewska-Szmek
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Daniel K Wójcik
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
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Zhang LA, Li P, Callaway EM. High-Resolution Laminar Identification in Macaque Primary Visual Cortex Using Neuropixels Probes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.23.576944. [PMID: 38328229 PMCID: PMC10849622 DOI: 10.1101/2024.01.23.576944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Laminar electrode arrays allow simultaneous recording of activity of many cortical neurons and assignment to correct layers using current source density (CSD) analyses. Electrode arrays with 100-micron contact spacing can estimate borders between layer 4 versus superficial or deep layers, but in macaque primary visual cortex (V1) there are far more layers, such as 4A which is only 50-100 microns thick. Neuropixels electrode arrays have 20-micron spacing, and thus could potentially discern thinner layers and more precisely identify laminar borders. Here we show that CSD signals lack the spatial resolution required to take advantage of high density Neuropixels arrays and describe the development of approaches based on higher resolution electrical signals and analyses, including spike waveforms and spatial spread, unit density, high-frequency action potential (AP) power spectrum, temporal power change, and coherence spectrum, that afford far higher resolution of laminar distinctions, including the ability to precisely detect the borders of even the thinnest layers of V1.
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Affiliation(s)
- Li A. Zhang
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Peichao Li
- Department of Neurology of the Second Affiliated Hospital and Interdisciplinary Institute of Neuroscience and Technology, School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science & Brain-Machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
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Chintaluri C, Bejtka M, Średniawa W, Czerwiński M, Dzik JM, Jędrzejewska-Szmek J, Kondrakiewicz K, Kublik E, Wójcik DK. What we can and what we cannot see with extracellular multielectrodes. PLoS Comput Biol 2021; 17:e1008615. [PMID: 33989280 PMCID: PMC8153483 DOI: 10.1371/journal.pcbi.1008615] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 05/26/2021] [Accepted: 04/28/2021] [Indexed: 12/02/2022] Open
Abstract
Extracellular recording is an accessible technique used in animals and humans to study the brain physiology and pathology. As the number of recording channels and their density grows it is natural to ask how much improvement the additional channels bring in and how we can optimally use the new capabilities for monitoring the brain. Here we show that for any given distribution of electrodes we can establish exactly what information about current sources in the brain can be recovered and what information is strictly unobservable. We demonstrate this in the general setting of previously proposed kernel Current Source Density method and illustrate it with simplified examples as well as using evoked potentials from the barrel cortex obtained with a Neuropixels probe and with compatible model data. We show that with conceptual separation of the estimation space from experimental setup one can recover sources not accessible to standard methods. Every set of measurements is a window into reality rendering its incomplete or distorted picture. It is often difficult to relate the obtained representation of the world to underlying ground truth. Here we show, for brain electrophysiology, for arbitrary experimental setup (distribution of electrodes), and arbitrary analytical setup (function space of current source densities), that one can identify distributions of current sources which can be recovered precisely, and those which are invisible in the system. This shows what is and what is not observable in the studied system for a given setup, allows to improve the analysis results by modifying analytical setup, and facilitates interpretation of the measured sets of LFP, ECoG and EEG recordings. In particular we show that with conceptual separation of the estimation space from experimental setup one can recover source distributions not accessible to standard methods.
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Affiliation(s)
- Chaitanya Chintaluri
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
- Centre for Neural Circuits and Behaviour, Department of Physiology Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Marta Bejtka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Władysław Średniawa
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
- University of Warsaw, Faculty of Biology, Warsaw, Poland
| | - Michał Czerwiński
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Jakub M. Dzik
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Joanna Jędrzejewska-Szmek
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Kacper Kondrakiewicz
- Laboratory of Emotions Neurobiology, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Ewa Kublik
- Laboratory of Emotions Neurobiology, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Daniel K. Wójcik
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
- * E-mail:
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Hindriks R, Schmiedt J, Arsiwalla XD, Peter A, Verschure PFMJ, Fries P, Schmid MC, Deco G. Linear distributed source modeling of local field potentials recorded with intra-cortical electrode arrays. PLoS One 2017; 12:e0187490. [PMID: 29253006 PMCID: PMC5734682 DOI: 10.1371/journal.pone.0187490] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Accepted: 10/20/2017] [Indexed: 01/04/2023] Open
Abstract
Planar intra-cortical electrode (Utah) arrays provide a unique window into the spatial organization of cortical activity. Reconstruction of the current source density (CSD) underlying such recordings, however, requires “inverting” Poisson’s equation. For inter-laminar recordings, this is commonly done by the CSD method, which consists in taking the second-order spatial derivative of the recorded local field potentials (LFPs). Although the CSD method has been tremendously successful in mapping the current generators underlying inter-laminar LFPs, its application to planar recordings is more challenging. While for inter-laminar recordings the CSD method seems reasonably robust against violations of its assumptions, is it unclear as to what extent this holds for planar recordings. One of the objectives of this study is to characterize the conditions under which the CSD method can be successfully applied to Utah array data. Using forward modeling, we find that for spatially coherent CSDs, the CSD method yields inaccurate reconstructions due to volume-conducted contamination from currents in deeper cortical layers. An alternative approach is to “invert” a constructed forward model. The advantage of this approach is that any a priori knowledge about the geometrical and electrical properties of the tissue can be taken into account. Although several inverse methods have been proposed for LFP data, the applicability of existing electroencephalographic (EEG) and magnetoencephalographic (MEG) inverse methods to LFP data is largely unexplored. Another objective of our study therefore, is to assess the applicability of the most commonly used EEG/MEG inverse methods to Utah array data. Our main conclusion is that these inverse methods provide more accurate CSD reconstructions than the CSD method. We illustrate the inverse methods using event-related potentials recorded from primary visual cortex of a macaque monkey during a motion discrimination task.
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Affiliation(s)
- Rikkert Hindriks
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Joscha Schmiedt
- Ernst StrÜngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Xerxes D Arsiwalla
- Synthetic Perceptive Emotive and Cognitive Systems (SPECS) Lab, Center of Autonomous Systems and Neurorobotics, Universitat Pompeu Fabra, Barcelona, Spain
| | - Alina Peter
- Ernst StrÜngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Paul F M J Verschure
- Synthetic Perceptive Emotive and Cognitive Systems (SPECS) Lab, Center of Autonomous Systems and Neurorobotics, Universitat Pompeu Fabra, Barcelona, Spain.,Institucio Catalana de Recerca i Estudis Avancats (ICREA), Universitat Pompeu Fabra (UPF), Barcelona, Spain.,Institute for Bioengineering of Catalonia, 08028 Barcelona, Spain.,Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Pascal Fries
- Ernst StrÜngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Michael C Schmid
- Ernst StrÜngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany.,Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.,Institucio Catalana de Recerca i Estudis Avancats (ICREA), Universitat Pompeu Fabra (UPF), Barcelona, Spain
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Hagen E, Fossum JC, Pettersen KH, Alonso JM, Swadlow HA, Einevoll GT. Focal Local Field Potential Signature of the Single-Axon Monosynaptic Thalamocortical Connection. J Neurosci 2017; 37:5123-5143. [PMID: 28432143 PMCID: PMC5444196 DOI: 10.1523/jneurosci.2715-16.2017] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2016] [Revised: 03/02/2017] [Accepted: 03/07/2017] [Indexed: 12/11/2022] Open
Abstract
A resurgence has taken place in recent years in the use of the extracellularly recorded local field potential (LFP) to investigate neural network activity. To probe monosynaptic thalamic activation of cortical postsynaptic target cells, so called spike-trigger-averaged LFP (stLFP) signatures have been measured. In these experiments, the cortical LFP is measured by multielectrodes covering several cortical lamina and averaged on spontaneous spikes of thalamocortical (TC) cells. Using a well established forward-modeling scheme, we investigated the biophysical origin of this stLFP signature with simultaneous synaptic activation of cortical layer-4 neurons, mimicking the effect of a single afferent spike from a single TC neuron. Constrained by previously measured intracellular responses of the main postsynaptic target cell types and with biologically plausible assumptions regarding the spatial distribution of thalamic synaptic inputs into layer 4, the model predicted characteristic contributions to monosynaptic stLFP signatures both for the regular-spiking (RS) excitatory neurons and the fast-spiking (FS) inhibitory interneurons. In particular, the FS cells generated stLFP signatures of shorter temporal duration than the RS cells. Added together, a sum of the stLFP signatures of these two principal synaptic targets of TC cells were observed to resemble experimentally measured stLFP signatures. Outside the volume targeted by TC afferents, the resulting postsynaptic LFP signals were found to be sharply attenuated. This implies that such stLFP signatures provide a very local measure of TC synaptic activation, and that newly developed inverse current-source density (CSD)-estimation methods are needed for precise assessment of the underlying spatiotemporal CSD profiles.SIGNIFICANCE STATEMENT Despite its long history and prevalent use, the proper interpretation of the extracellularly recorded local field potential (LFP) is still not fully established. Here we investigate by biophysical modeling the origin of the focal LFP signature of the single-axon monosynaptic thalamocortical connection as measured by spike-trigger-averaging of cortical LFPs on spontaneous spikes of thalamocortical neurons. We find that this LFP signature is well accounted for by a model assuming thalamic projections to two cortical layer-4 cell populations: one excitatory (putatively regular-spiking cells) and one inhibitory (putatively fast-spiking cells). The LFP signature is observed to decay sharply outside the cortical region receiving the thalamocortical projection, implying that it indeed provides a very local measure of thalamocortical synaptic activation.
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Affiliation(s)
- Espen Hagen
- Faculty of Science and Technology, Norwegian University of Life Sciences, Aas, Norway
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and Jülich Aachen Research Alliance - Brain Institute I, Jülich Research Centre, 52425 Jülich, Germany
- Department of Physics and
| | - Janne C Fossum
- Faculty of Science and Technology, Norwegian University of Life Sciences, Aas, Norway
| | - Klas H Pettersen
- Faculty of Science and Technology, Norwegian University of Life Sciences, Aas, Norway
- Letten Centre and GliaLab, Institute of Basic Medical Sciences, University of Oslo, 0316 Oslo, Norway
| | - Jose-Manuel Alonso
- Department of Biological Sciences, State University of New York College of Optometry, New York, New York 10036, and
| | - Harvey A Swadlow
- Department of Psychology, University of Connecticut, Storrs, Connecticut 06269
| | - Gaute T Einevoll
- Faculty of Science and Technology, Norwegian University of Life Sciences, Aas, Norway,
- Department of Physics and
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