Career Center AES Connect

Abstracts

Party Like It's 1999 Hz: Unraveling the Dance of High-frequency Oscillation in Epileptic Human Brain Slices

Abstract number : 1.05
Submission category : 1. Basic Mechanisms / 1C. Electrophysiology/High frequency oscillations
Year : 2024
Submission ID : 867
Source : www.aesnet.org
Presentation date : 12/7/2024 12:00:00 AM
Published date :

Authors :
Presenting Author: Martina Kolajova, MSc – Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic

Petr Klimes, PhD – Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic
Petr Nejedly, Msc – St. Anne's university hospital Brno, Czech Republic
Jan Cimbalnik, PhD – International Clinical Research Center, St. Anne’s University Hospital, Brno, Czech Republic
Pavel Jurak, PhD – Institute of Scientific Instruments of the CAS, Brno, Czech Republic
Josef Halamek, PhD – Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic.
Olga Svecova, PhD – Department of Physiology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
Marketa Bebarova, MD – Department of Physiology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
Eva Brichtova, MD – Department of Neurosurgery, St. Anne's University Hospital, Brno, Czech Republic
Michal Hendrych, MD – 1st Department of Pathology, Masaryk University, Brno, Czech Republic
Hana Hribkova, PhD – Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
Eva Zatloukalova, MD – Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic, member of the European Reference Network EpiCARE
Milan Brázdil, MD, PhD – 1st Department of Neurology, Faculty of Medicine, Masaryk University and St. Anne´s University Hospital, Brno, Czech Republic – member of ERN EpiCARE

Rationale: It is hypothesized that very high-frequency oscillations (500 - 2000 Hz) detected by intracerebral macroelectrodes may represent the summated activity of different neuronal subgroups that exhibit different asynchronous firing rates and phases. In recent years, multielectrode arrays (MEAs) have emerged as a powerful tool for recording electrical activity from human brain slices, providing valuable insights into the underlying mechanisms of epilepsy. The objective of our study was to perform spatiotemporal clustering of extracellular action potentials (EAPs) to contribute to the understanding of the mechanisms of VHFO generation.

Methods: We analyzed 60-minute long 60-channel (59+1 reference) MEA recordings (25 kHz sampling rate) recorded at the Department of Physiology at the Faculty of Medicine of Masaryk University in cooperation with Brno Epilepsy Center (St Anne’s Hospital). Measurements were performed on resected hippocampal tissue from 4 patients with drug-resistant mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE/HS). An automatic spike detector was employed to detect spontaneous neuronal activity. For the analysis, we developed a structured dataset that included segments of signals extracted from all channels within a predefined time window. Uniform Manifold Approximation and Projection (UMAP) was utilized for dimensionality reduction, while Hierarchical Density-Based Spatial Clustering (HDBSCAN) served as the clustering method in the spike sorting analysis. The next step involved grouping spikes by the output labels, centering waveforms around each spike, and detrending them by subtracting the mean. The average waveforms for each channel were then computed and visualized within selected clusters.

Results: Due to limited tissue viability, recordings from 4 patients out of 22 were analyzed. The clustering analysis resulted in the mean Density-Based Clustering Validation (DBCV) score 0.79 and identified an average of 22 clusters across the data sets, with a high mean data retention rate of 96.88%. The mean spike shape from every channel was then presented in two forms: a line plot providing a view of the mean spike shape, and a heatmap showcasing the amplitude variations and spike delays across channels (Figure 1). The minimum (largest negative) amplitudes, which denote the peak of the spike waveform, were displayed in the MEA layout for selected clusters (Figure 2).

Conclusions: Spatiotemporal spike sorting revealed distinct clusters - neuronal subgroups with asynchronous firing rates and phases (delays). This observation supports the hypothesis that VHFO may be generated by such neuronal mechanisms.

Funding: This project was funded by project n. NU22-08-00278 of the Ministry of Health of the Czech Republic and LX22NPO5107 (MEYS): Financed by European Union – Next Generation EU.

Basic Mechanisms