Journal Article

DZNE-2022-00332

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Implementation of biohybrid olfactory bulb on a high-density CMOS-chip to reveal large-scale spatiotemporal circuit information.

Hu, X. (First author)DZNE* ; Khanzada, S.DZNE* ; Klütsch, D.DZNE* ; Calegari, F. ; Amin, H. (Last author)DZNE*

2022
Elsevier Science Amsterdam [u.a.]

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Please use a persistent id in citations: doi:10.1016/j.bios.2021.113834

Abstract: Large-scale multi-site biosensors are essential to probe the olfactory bulb (OB) circuitry for understanding the spatiotemporal dynamics of simultaneous discharge patterns. Current ex-vivo biosensing techniques are limited to recording a small set of neurons and cannot provide an adequate resolution, which hinders revealing the fast dynamic underlying the information coding mechanisms in the OB circuit. Here, we demonstrate a novel biohybrid OB-CMOS biosensing platform to decipher the cross-scale dynamics of the OB electrogenesis and quantify the distinct neuronal coding properties. The approach with 4096-microelectrodes offers a non-invasive, label-free, bioelectrical imaging to decode simultaneous firing patterns from thousands of connected neuronal ensembles in acute OB slices. The platform can measure spontaneous and drug-induced extracellular field potential activity with substantially improved spatiotemporal resolution over conventional OB-based biosensors. Also, we employ our OB-CMOS recordings to perform multidimensional analysis to instantiate specific neurophysiological metrics underlying the olfactory spatiotemporal coding that emerged from the OB interconnected layers. Our results delineate the computational implications of large-scale activity patterns in functional olfactory processing. The systematic interplay of the experimental CMOS-base platform architecture and the high-content characterization of the olfactory circuit with various computational analyses endow significant functional interrogations of the OB information processing, high-spatiotemporal connectivity mapping, and global circuit dynamics. Thus, our study can inspire the design of advanced biomimetic olfactory-based biosensors and neuromorphic approaches for diagnostic biomarkers and drug discovery applications.

Keyword(s): Biosensing Techniques (MeSH) ; Microelectrodes (MeSH) ; Neurons (MeSH) ; Odorants (MeSH) ; Olfactory Bulb (MeSH) ; Smell (MeSH) ; Bioelectronics nose ; CMOS-MEAs ; Electrogenesis ; Neural circuits ; Olfactory bulb-based biosensors ; Olfactory spatiotemporal coding

Note: (CC BY)

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Contributing Institute(s):

1. Plasticity models in aging and neurodegeneration (AG Amin)

Research Program(s):

1. 351 - Brain Function (POF4-351) (POF4-351)

Appears in the scientific report 2022

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Database coverage:
; ; ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Agriculture, Biology and Environmental Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 10 ; JCR ; Nationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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Linked articles:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Preprint Hu, X. (First author)DZNE* ; Khanzada, S.DZNE* ; Klütsch, D.DZNE* ; Calegari, F. (Collaboration author) ; Amin, H. (Last author)DZNE*
Revealing Spatiotemporal Circuit Information of Olfactory Bulb in Large-scale Neural Recordings
[10.1101/2021.03.05.434081] BibTeX | EndNote: XML, Text | RIS

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