ArticleScientific data2025
Mesoscale insights in Epileptic Networks: A Multimodal Intracranial Dataset.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Inferring neural sources from electroencephalography: foundations and frontiers.Journal of neural engineering · 2026Review
- Single-neuron correlates of visual consciousness in human lateral occipital complex.Nature communications · 2025Article
- Mesoscale insights in Epileptic Networks: A Multimodal Intracranial Dataset.Scientific data · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Understanding the intricate dynamics of epileptic networks at the mesoscale is crucial for advancing our knowledge of epilepsy pathophysiology and developing targeted interventions. In this data descriptor, we present a comprehensive dataset encompassing intracranial electroencephalography (iEEG) recordings, Local Field Potentials (LFP), and Multiunit Activity (MUA) data obtained from Microelectrode arrays (MEA; Utah array; Blackrock). 12 seizures were recorded in 5 epilepsy patients with the MEA. Our dataset offers a unique opportunity to investigate the complex interactions between diverse neural signals across brain areas and to study the mesoscale networks in focal epilepsy. This dataset can be used to explore the modulations of LFP and MUA in conjunction with iEEG, offering potential insights into the spatiotemporal dynamics of epileptic networks. Additionally, the high temporal resolution of the data allows for the computation of High-Frequency Oscillations (HFOs) in both LFP and iEEG signals, facilitating the investigation of their potential relationship with MUA activity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.