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73. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC)
Joint Meeting mit der Griechischen Gesellschaft für Neurochirurgie

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

29.05. - 01.06.2022, Köln

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From Euler to the Neocortex – The potential of graph analytical approaches to characterise electrophysiological network properties of human cortical brain slice cultures

Von Euler zum Neocortex – Das Potential Graphen-Analytischer Ansätze zur Charakterisierung von Elektrophysiologischen Eigenschaften humaner Cortex-Hirnschnittkulturen

Meeting Abstract

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  • presenting/speaker Jonas Ort - Universitätsklinikum RWTH Aachen, Klinik für Neurochirurgie, Aachen, Deutschland; Universitätsklinikum RWTH Aachen, Neurosurgical Artificial Intelligence Laboratory Aachen (NAILA), Aachen, Deutschland; Universitätsklinikum RWTH Aachen, Klinik für Neurologie, Epileptologie, Aachen, Deutschland
  • Jenny Wickham - Universität Tübingen, Neurophysics, Natural and Medical Sciences Institute, Reutlingen, Deutschland
  • Aniella Bak - Universitätsklinikum RWTH Aachen, Klinik für Neurologie, Epileptologie, Aachen, Deutschland
  • Andrea Corna - Universität Tübingen, Neurophysics, Natural and Medical Sciences Institute, Reutlingen, Deutschland; TU Wien, Institute of Biomedical Electronics, Wien, Österreich
  • Julia Schmierer - Universität Tübingen, Neurophysics, Natural and Medical Sciences Institute, Reutlingen, Deutschland
  • Thomas V. Wuttke - Universitätsklinikum Tübingen, Department of Neurosurgery, Tübingen, Deutschland; Universitätsklinikum Tübingen, Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, Tübingen, Deutschland
  • Niklas Schwarz - Universitätsklinikum Tübingen, Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, Tübingen, Deutschland
  • Hans Clusmann - Universitätsklinikum RWTH Aachen, Klinik für Neurochirurgie, Aachen, Deutschland
  • Yvonne Weber - Universitätsklinikum RWTH Aachen, Klinik für Neurologie, Epileptologie, Aachen, Deutschland
  • Günther Zeck - Universität Tübingen, Neurophysics, Natural and Medical Sciences Institute, Reutlingen, Deutschland; TU Wien, Institute of Biomedical Electronics, Wien, Österreich
  • Henner Koch - Universitätsklinikum RWTH Aachen, Klinik für Neurologie, Epileptologie, Aachen, Deutschland
  • Daniel Delev - Universitätsklinikum RWTH Aachen, Klinik für Neurochirurgie, Aachen, Deutschland; Universitätsklinikum RWTH Aachen, Neurosurgical Artificial Intelligence Laboratory Aachen (NAILA), Aachen, Deutschland

Deutsche Gesellschaft für Neurochirurgie. 73. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Griechischen Gesellschaft für Neurochirurgie. Köln, 29.05.-01.06.2022. Düsseldorf: German Medical Science GMS Publishing House; 2022. DocP093

doi: 10.3205/22dgnc403, urn:nbn:de:0183-22dgnc4039

Veröffentlicht: 25. Mai 2022

© 2022 Ort et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.

Gliederung

Text

Objective: Micro-electrode array (MEA) technique offers a possibility to record massive parallel electrophysiological potentials with spatial resolution. Thus, MEA recordings can be leveraged to investigate for network properties of brain slice cultures which could provide novel insights into the electrophysiological pathogenesis of epilepsy or tumour growth. However, the huge extent of the detected data makes analysis challenging and most published articles using MEAs only concentrate on general parameters including firing rate, number of active channels, or interspike-interval distribution. Here, we use graph analytical tools to describe connections of spatially distant areas of human organotypic neocortical slice cultures.

Methods: Spare tissue from resective epilepsy or tumour surgeries were cultured as organotypic cortical brain slice cultures. MEA recordings were obtained using a 256-MEA with either artificial or human cerebrospinal fluid (aCSF/hCSF). Custom Python scripts were used for data analysis. The main libraries for our network analytical approach include Numpy, Scipy, and Networkx. Spike times were extracted using a mean absolute deviation threshold-based approach without spikesorting. For each of the 252-recording channels, we then identified bursting episodes using an adaptive threshold. We then created a graph with each node equaling one MEA channel and each edge referring to shared bursting events. We then calculated the degree centrality, which is a metric for the number of connections a node has within a network that can be used to identify functional hubs within the anatomy.

Results: Channels with a high degree centrality were identified in all neocortical layers. Network properties changed depending on the used medium suggesting adaptive properties and possibly underlying subnetworks. Thus, hCSF led to an increase in degree centrality in Layers 2, 3, and 4. Further, novel nodes could be identified in hCSF that were not present in aCSF.

Conclusion: Using MEA technology to investigate human organotypic brain slice cultures offer a powerful tool for the identification and characterization of functional networks and their alterations in pathological conditions. Graph-theoretical approaches could prove as a useful extension of the analytical armoury, which allows deciphering not only spatially static but also directionally dynamic network properties and thus leveraging the possibility to examine the spread of ictal activity or tumour growth.