PhD Scientific Days 2021

Budapest, 7-8 July 2021

NE_I_P: Neurosciences I. Posters

Dataset of cortical activity recorded with high spatial resolution from anesthetized rats

Dr. István Ulbert-Research Centre for Natural Sciences
Mr. Csaba Horváth-Research Centre for Natural Sciences
Ms. Lili Fanni Tóth-MSc Student
Dr. Richárd Fiáth-Research Centre for Natural Sciences

Text of the abstract

Publicly available neural recordings obtained with high spatial resolution are scarce. Here, we present an electrophysiological dataset recorded from the neocortex of twenty rats anesthetized with ketamine/xylazine. The wideband, spontaneous recordings were acquired with a single-shank silicon-based probe having 128 densely-packed recording sites arranged in a 32x4 array. The dataset contains the activity of a total of 7126 sorted single units extracted from all layers of the cortex. Here, we share raw neural recordings, as well as spike times, extracellular spike waveforms and several properties of units packaged in a standardized electrophysiological data format. For technical validation of our dataset, we provide the distributions of derived single unit properties along with various spike sorting quality metrics. This large collection of in vivo data enables the investigation of the high-resolution electrical footprint of cortical neurons which in turn may aid their electrophysiology-based classification. Furthermore, the dataset might be used to study the laminar-specific neuronal activity during slow oscillation, a brain rhythm strongly involved in neural mechanisms underlying memory consolidation and sleep.

Hungarian Brain Research Program Grant: 2017-1.2.1-NKP-2017-00002, Hungarian National Research, Development and Innovation Office: TUDFO/51757-1/2019-ITM [Ulbert]
Hungarian Brain Research Program Grant: 2017-1.2.1-NKP-2017-00002, Hungarian National Research, Development and Innovation Office: PD124175, PD134196, TUDFO/51757-1/2019-ITM [Fiáth]

University and Doctoral School

Semmelweis University, János Szentágothai Doctoral School of Neurosciences