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Mood variations decoded from multi-site intracranial human brain activity.
Sani, Omid G; Yang, Yuxiao; Lee, Morgan B; Dawes, Heather E; Chang, Edward F; Shanechi, Maryam M.
Afiliación
  • Sani OG; Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA.
  • Yang Y; Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA.
  • Lee MB; Department of Neurological Surgery, University of California, San Francisco, California, USA.
  • Dawes HE; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA.
  • Chang EF; Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, California, USA.
  • Shanechi MM; Department of Neurological Surgery, University of California, San Francisco, California, USA.
Nat Biotechnol ; 36(10): 954-961, 2018 11.
Article en En | MEDLINE | ID: mdl-30199076
The ability to decode mood state over time from neural activity could enable closed-loop systems to treat neuropsychiatric disorders. However, this decoding has not been demonstrated, partly owing to the difficulty of modeling distributed mood-relevant neural dynamics while dealing with the sparsity of mood state measurements. Here we develop a modeling framework to decode mood state variations from multi-site intracranial recordings in seven human subjects with epilepsy who self-reported their mood state intermittently over multiple days. We built dynamic neural encoding models of mood state and corresponding decoders for each individual and demonstrated that mood state variations over time can be decoded from neural activity. Across subjects, the decoders largely recruited neural signals from limbic regions, whose spectro-spatial features were tuned to mood variations. The dynamic models also provided an analytical tool to compute the timescales of the decoded mood state. These results provide an initial line of evidence indicating the feasibility of mood state decoding.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Encéfalo / Afecto Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Nat Biotechnol Asunto de la revista: BIOTECNOLOGIA Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Encéfalo / Afecto Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Nat Biotechnol Asunto de la revista: BIOTECNOLOGIA Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos