Spatially Independent Components Derived from High-Density Diffuse Optical Tomography Data Show Differential Activity during Overt Motor Observation and Imitation

Sung Min Park, Tessa G. George, Chloe M. Sobolewski, Sophia R. McMorrow, Dalin Yang, Mary B. Nebel, Bahar Tunçgenç, René Vidal, Natasha Marrus, Stewart H. Mostofsky, Adam T. Eggebrecht

Research output: Contribution to conferencePaperpeer-review

Abstract

High-density diffuse optical tomography data was collected to assess neural activity during motor imitation. Independent component analysis revealed components exhibiting differential activity during observation and imitation. Changes in task-relatedness in components correlate with behavioral measures.

Original languageEnglish (US)
StatePublished - 2023
Event2023 Laser Science, LS 2023 - Tacoma, United States
Duration: Oct 9 2023Oct 12 2023

Conference

Conference2023 Laser Science, LS 2023
Country/TerritoryUnited States
CityTacoma
Period10/9/2310/12/23

ASJC Scopus subject areas

  • Nuclear Energy and Engineering
  • Electronic, Optical and Magnetic Materials
  • Nuclear and High Energy Physics
  • Atomic and Molecular Physics, and Optics

Fingerprint

Dive into the research topics of 'Spatially Independent Components Derived from High-Density Diffuse Optical Tomography Data Show Differential Activity during Overt Motor Observation and Imitation'. Together they form a unique fingerprint.

Cite this