A1 Journal article (refereed)
An update to Hippocampome.org by integrating single-cell phenotypes with circuit function in vivo (2021)

Sanchez-Aguilera, A., Wheeler, D. W., Jurado-Parras, T., Valero, M., Nokia, M. S., Cid, E., Fernandez-Lamo, I., Sutton, N., García-Rincón, D., de la Prida, L. M., & Ascoli, G. A. (2021). An update to Hippocampome.org by integrating single-cell phenotypes with circuit function in vivo. PLoS Biology, 19(5), Article e3001213. https://doi.org/10.1371/journal.pbio.3001213

JYU authors or editors

Nokia, Miriam

Publication details

All authors or editors: Sanchez-Aguilera, Alberto; Wheeler, Diek W.; Jurado-Parras, Teresa; Valero, Manuel; Nokia, Miriam S.; Cid, Elena; Fernandez-Lamo, Ivan; Sutton, Nate; García-Rincón, Daniel; de la Prida, Liset M.; et al.

Journal or series: PLoS Biology

ISSN: 1544-9173

eISSN: 1545-7885

Publication year: 2021

Publication date: 06/05/2021

Volume: 19

Issue number: 5

Article number: e3001213

Publisher: Public Library of Science (PLoS)

Publication country: United States

Publication language: English

DOI: https://doi.org/10.1371/journal.pbio.3001213

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/75734

Abstract

Understanding brain operation demands linking basic behavioral traits to cell-type specific dynamics of different brain-wide subcircuits. This requires a system to classify the basic operational modes of neurons and circuits. Single-cell phenotyping of firing behavior during ongoing oscillations in vivo has provided a large body of evidence on entorhinal–hippocampal function, but data are dispersed and diverse. Here, we mined literature to search for information regarding the phase-timing dynamics of over 100 hippocampal/entorhinal neuron types defined in Hippocampome.org. We identified missing and unresolved pieces of knowledge (e.g., the preferred theta phase for a specific neuron type) and complemented the dataset with our own new data. By confronting the effect of brain state and recording methods, we highlight the equivalences and differences across conditions and offer a number of novel observations. We show how a heuristic approach based on oscillatory features of morphologically identified neurons can aid in classifying extracellular recordings of single cells and discuss future opportunities and challenges towards integrating single-cell phenotypes with circuit function.

Keywords: hippocampus; neurons; phenotype; neural networks (biology); in vivo method