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Introducing HiBoP: a Unity-based visualization software for large iEEG datasets.
Del Vecchio, Maria; Bontemps, Benjamin; Lance, Florian; Gannerie, Adrien; Sipp, Florian; Albertini, Davide; Cassani, Chiara Maria; Chatard, Benoit; Dupin, Maryne; Lachaux, Jean-Philippe.
Afiliação
  • Del Vecchio M; Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, Parma 43125, Italy.
  • Bontemps B; Lyon Neuroscience Research Center, EDUWELL team, INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon F-69000, France.
  • Lance F; Lyon Neuroscience Research Center, EDUWELL team, INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon F-69000, France.
  • Gannerie A; Lyon Neuroscience Research Center, EDUWELL team, INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon F-69000, France.
  • Sipp F; Lyon Neuroscience Research Center, EDUWELL team, INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon F-69000, France.
  • Albertini D; Dipartimento di Medicina e Chirurgia, Università di Parma, Via Volturno 39, Parma 43125, Italy.
  • Cassani CM; Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, Parma 43125, Italy; Department of School of Advanced Studies, University of Camerino, Italy.
  • Chatard B; Lyon Neuroscience Research Center, EDUWELL team, INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon F-69000, France.
  • Dupin M; Lyon Neuroscience Research Center, EDUWELL team, INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon F-69000, France.
  • Lachaux JP; Lyon Neuroscience Research Center, EDUWELL team, INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon F-69000, France. Electronic address: Jp.lachaux@inserm.fr.
J Neurosci Methods ; 409: 110179, 2024 Sep.
Article em En | MEDLINE | ID: mdl-38823595
ABSTRACT

BACKGROUND:

Intracranial EEG data offer a unique spatio-temporal precision to investigate human brain functions. Large datasets have become recently accessible thanks to new iEEG data-sharing practices and tighter collaboration with clinicians. Yet, the complexity of such datasets poses new challenges, especially regarding the visualization and anatomical display of iEEG. NEW

METHOD:

We introduce HiBoP, a multi-modal visualization software specifically designed for large groups of patients and multiple experiments. Its main features include the dynamic display of iEEG responses induced by tasks/stimulations, the definition of Regions and electrodes Of Interest, and the shift between group-level and individual-level 3D anatomo-functional data.

RESULTS:

We provide a use-case with data from 36 patients to reveal the global cortical dynamics following tactile stimulation. We used HiBoP to visualize high-gamma responses [50-150 Hz], and define three major response components in primary somatosensory and premotor cortices and parietal operculum. COMPARISON WITH EXISTING METHODS(S) Several iEEG softwares are now publicly available with outstanding analysis features. Yet, most were developed in languages (Python/Matlab) chosen to facilitate the inclusion of new analysis by users, rather than the quality of the visualization. HiBoP represents a visualization tool developed with videogame standards (Unity/C#), and performs detailed anatomical analysis rapidly, across multiple conditions, patients, and modalities with an easy export toward third-party softwares.

CONCLUSION:

HiBoP provides a user-friendly environment that greatly facilitates the exploration of large iEEG datasets, and helps users decipher subtle structure/function relationships.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software Limite: Adult / Female / Humans / Male Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software Limite: Adult / Female / Humans / Male Idioma: En Ano de publicação: 2024 Tipo de documento: Article