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Inferring monosynaptic connections from paired dendritic spine Ca2+imaging and large-scale recording of extracellular spiking.
Xue, Xiaohan; Buccino, Alessio Paolo; Kumar, Sreedhar Saseendran; Hierlemann, Andreas; Bartram, Julian.
Afiliación
  • Xue X; Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
  • Buccino AP; Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
  • Kumar SS; Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
  • Hierlemann A; Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
  • Bartram J; Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
J Neural Eng ; 19(4)2022 08 23.
Article en En | MEDLINE | ID: mdl-35931040
ABSTRACT

Objective:

Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others.

Approach:

Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays.Main

results:

We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it onin vitrorecordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+transients based on measured spike trains in order to obtain simulated ground-truth connections.

Significance:

The proposed approach offers unique advantages as (a) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, (b) it provides precise information of presynaptic spiking, and (c) postsynaptic spine Ca2+signals and, finally, (d) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Sinapsis / Espinas Dendríticas Idioma: En Revista: J Neural Eng Asunto de la revista: NEUROLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Sinapsis / Espinas Dendríticas Idioma: En Revista: J Neural Eng Asunto de la revista: NEUROLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Suiza