ArticleScientific data2021
Dataset of cortical activity recorded with high spatial resolution from anesthetized rats.
Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Multi-Channel Neural Interface for Neural Recording and Neuromodulation.Small methods · 2026Review
- DREDge: robust motion correction for high-density extracellular recordings across species.Nature methods · 2025Article
- Article
- DREDge: robust motion correction for high-density extracellular recordings across species.bioRxiv : the preprint server for biology · 2023Article
- Ipsilateral Stimulus Encoding in Primary and Secondary Somatosensory Cortex of Awake Mice.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
- Subthreshold repetitive transcranial magnetic stimulation suppresses ketamine-induced poly population spikes in rat sensorimotor cortex.Frontiers in neuroscience · 2022Article
- From End to End: Gaining, Sorting, and Employing High-Density Neural Single Unit Recordings.Frontiers in neuroinformatics · 2022Review
- Dataset of cortical activity recorded with high spatial resolution from anesthetized rats.Scientific data · 2021Article
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4 authors.
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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 32 × 4 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.
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