Cargando…
Quantitative firing pattern phenotyping of hippocampal neuron types
Systematically organizing the anatomical, molecular, and physiological properties of cortical neurons is important for understanding their computational functions. Hippocampome.org defines 122 neuron types in the rodent hippocampal formation based on their somatic, axonal, and dendritic locations, p...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6884469/ https://www.ncbi.nlm.nih.gov/pubmed/31784578 http://dx.doi.org/10.1038/s41598-019-52611-w |
_version_ | 1783474554268549120 |
---|---|
author | Komendantov, Alexander O. Venkadesh, Siva Rees, Christopher L. Wheeler, Diek W. Hamilton, David J. Ascoli, Giorgio A. |
author_facet | Komendantov, Alexander O. Venkadesh, Siva Rees, Christopher L. Wheeler, Diek W. Hamilton, David J. Ascoli, Giorgio A. |
author_sort | Komendantov, Alexander O. |
collection | PubMed |
description | Systematically organizing the anatomical, molecular, and physiological properties of cortical neurons is important for understanding their computational functions. Hippocampome.org defines 122 neuron types in the rodent hippocampal formation based on their somatic, axonal, and dendritic locations, putative excitatory/inhibitory outputs, molecular marker expression, and biophysical properties. We augmented the electrophysiological data of this knowledge base by collecting, quantifying, and analyzing the firing responses to depolarizing current injections for every hippocampal neuron type from published experiments. We designed and implemented objective protocols to classify firing patterns based on 5 transients (delay, adapting spiking, rapidly adapting spiking, transient stuttering, and transient slow-wave bursting) and 4 steady states (non-adapting spiking, persistent stuttering, persistent slow-wave bursting, and silence). This automated approach revealed 9 unique (plus one spurious) families of firing pattern phenotypes while distinguishing potential new neuronal subtypes. Novel statistical associations emerged between firing responses and other electrophysiological properties, morphological features, and molecular marker expression. The firing pattern parameters, experimental conditions, spike times, references to the original empirical evidences, and analysis scripts are released open-source through Hippocampome.org for all neuron types, greatly enhancing the existing search and browse capabilities. This information, collated online in human- and machine-accessible form, will help design and interpret both experiments and model simulations. |
format | Online Article Text |
id | pubmed-6884469 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68844692019-12-06 Quantitative firing pattern phenotyping of hippocampal neuron types Komendantov, Alexander O. Venkadesh, Siva Rees, Christopher L. Wheeler, Diek W. Hamilton, David J. Ascoli, Giorgio A. Sci Rep Article Systematically organizing the anatomical, molecular, and physiological properties of cortical neurons is important for understanding their computational functions. Hippocampome.org defines 122 neuron types in the rodent hippocampal formation based on their somatic, axonal, and dendritic locations, putative excitatory/inhibitory outputs, molecular marker expression, and biophysical properties. We augmented the electrophysiological data of this knowledge base by collecting, quantifying, and analyzing the firing responses to depolarizing current injections for every hippocampal neuron type from published experiments. We designed and implemented objective protocols to classify firing patterns based on 5 transients (delay, adapting spiking, rapidly adapting spiking, transient stuttering, and transient slow-wave bursting) and 4 steady states (non-adapting spiking, persistent stuttering, persistent slow-wave bursting, and silence). This automated approach revealed 9 unique (plus one spurious) families of firing pattern phenotypes while distinguishing potential new neuronal subtypes. Novel statistical associations emerged between firing responses and other electrophysiological properties, morphological features, and molecular marker expression. The firing pattern parameters, experimental conditions, spike times, references to the original empirical evidences, and analysis scripts are released open-source through Hippocampome.org for all neuron types, greatly enhancing the existing search and browse capabilities. This information, collated online in human- and machine-accessible form, will help design and interpret both experiments and model simulations. Nature Publishing Group UK 2019-11-29 /pmc/articles/PMC6884469/ /pubmed/31784578 http://dx.doi.org/10.1038/s41598-019-52611-w Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Komendantov, Alexander O. Venkadesh, Siva Rees, Christopher L. Wheeler, Diek W. Hamilton, David J. Ascoli, Giorgio A. Quantitative firing pattern phenotyping of hippocampal neuron types |
title | Quantitative firing pattern phenotyping of hippocampal neuron types |
title_full | Quantitative firing pattern phenotyping of hippocampal neuron types |
title_fullStr | Quantitative firing pattern phenotyping of hippocampal neuron types |
title_full_unstemmed | Quantitative firing pattern phenotyping of hippocampal neuron types |
title_short | Quantitative firing pattern phenotyping of hippocampal neuron types |
title_sort | quantitative firing pattern phenotyping of hippocampal neuron types |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6884469/ https://www.ncbi.nlm.nih.gov/pubmed/31784578 http://dx.doi.org/10.1038/s41598-019-52611-w |
work_keys_str_mv | AT komendantovalexandero quantitativefiringpatternphenotypingofhippocampalneurontypes AT venkadeshsiva quantitativefiringpatternphenotypingofhippocampalneurontypes AT reeschristopherl quantitativefiringpatternphenotypingofhippocampalneurontypes AT wheelerdiekw quantitativefiringpatternphenotypingofhippocampalneurontypes AT hamiltondavidj quantitativefiringpatternphenotypingofhippocampalneurontypes AT ascoligiorgioa quantitativefiringpatternphenotypingofhippocampalneurontypes |