Assessing the effects of cocaine dependence and pathological gambling using group-wise sparse representation of natural stimulus FMRI data.

Assessing functional brain activation patterns in neuropsychiatric disorders such as cocaine dependence (CD) or pathological gambling (PG) under naturalistic stimuli has received rising interest in recent years. In this paper, we propose and apply a novel group-wise sparse representation framework t...

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Publicado en:Brain Imaging & Behavior Vol. 11; no. 4; pp. 1179 - 1192
Autores principales: Ren, Yudan, Fang, Jun, Lv, Jinglei, Hu, Xintao, Guo, Cong, Guo, Lei, Xu, Jiansong, Potenza, Marc, Liu, Tianming, Guo, Cong Christine, Potenza, Marc N
Formato: research Journal Article
Publicado: Springer Nature Aug2017
Acceso en línea:Ver este registro en EBSCOhost
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          Ren, Yudan
          Fang, Jun
          Lv, Jinglei
          Hu, Xintao
          Guo, Cong
          Guo, Lei
          Xu, Jiansong
          Potenza, Marc
          Liu, Tianming
          Guo, Cong Christine
          Potenza, Marc N
        affil: School of Automation , Northwestern Polytechnical University , Xi'an China
      sug:
        subj:
          Substance Use Disorders Physiopathology
          Gambling Physiopathology
          Substance Use Disorders
          Brain Physiopathology
          Brain
          Gambling
          Human
          Visual Perception Physiology
          Male
          Magnetic Resonance Imaging
          Emotions
          Female
          Brain Mapping Methods
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Clinical Assessment Tools
          Male
          Female
      ab: Assessing functional brain activation patterns in neuropsychiatric disorders such as cocaine dependence (CD) or pathological gambling (PG) under naturalistic stimuli has received rising interest in recent years. In this paper, we propose and apply a novel group-wise sparse representation framework to assess differences in neural responses to naturalistic stimuli across multiple groups of participants (healthy control, cocaine dependence, pathological gambling). Specifically, natural stimulus fMRI (N-fMRI) signals from all three groups of subjects are aggregated into a big data matrix, which is then decomposed into a common signal basis dictionary and associated weight coefficient matrices via an effective online dictionary learning and sparse coding method. The coefficient matrices associated with each common dictionary atom are statistically assessed for each group separately. With the inter-group comparisons based on the group-wise correspondence established by the common dictionary, our experimental results demonstrated that the group-wise sparse coding and representation strategy can effectively and specifically detect brain networks/regions affected by different pathological conditions of the brain under naturalistic stimuli.
      pubtype: Academic Journal
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        Journal Article
      ougenre: Article
    language: English
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