ERP-Lab 台大醫院精神部 神經生理研究室

ERP, MMN, P50, schizophrenia, prodrome, MEG

Archive for the ‘Classification分類’


P50/N1/P3 amplitudes as classifiers的機器學習machine learning

Critical Evaluation of Auditory Event-Related Potential Deficits in Schizophrenia: Evidence From Large-Scale Single-Subject Pattern Classification 柏林研究團隊刊登於  Schizophrenia Bulletin vol. 40 no. 5 pp. 1062–1071, 2014之文章

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螢幕快照 2015-01-07 下午6.05.29

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Boutros與Gjini研究團隊的分類法則

A statistical methodology to improve accuracy in differentiating schizophrenia patients from healthy controls    Psychiatry Research 21 February-27 February 2014

Rosalind M. Peters, Klevest Gjini, Thomas N. Templin, Nash N. Boutros

untitled

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精神疾病Biomarker的挑戰:從分類到預測

 

有沒有辦法:從某一生理指標推論受試者是control 抑或 Proband//Converter抑或Non-Converter

Early Recognition and Disease Prediction in the At-Risk Mental States for Psychosis Using Neurocognitive Pattern Classification. Schizophrenia Bulletin 2012;38(6)Pp. 1200-1215

這一篇有MRI的Machine Learning Disease Prediction in the At-Risk Mental State for Psychosis Using Neuroanatomical Biomarkers: Results From the FePsy Study Schizophrenia Bulletin 2012;38(6)Pp. 1234-1246

ARMS與發病

英國研究團隊於2012年January出版在Schizophrenia Research; 134(1)Pages 42–48的Reduced mismatch negativity predates the onset of psychosis

  1. 41 cases meeting PACE criteria for the At Risk Mental State (ARMS) and 50 controls performed a duration-deviant MMN. The amplitude of the MMN wave was compared between groups using linear regression. The ARMS subjects were then followed for 2 years to determine their clinical outcome.
  2. The MMN amplitude was significantly reduced in the ARMS group compared to controls. (繼續閱讀…)

早期發現與Disease Prediction in At-Risk Subjects

張文和教授的老朋友John Davis研究團隊之作品Proton Magnetic Resonance Spectroscopy and Illness Stage in Schizophrenia—A Systematic Review and Meta-Analysis 2011, Biological Psychiatry ; 69(5)Pages 495-503Stefan Brugger, John M. Davis, Stefan Leucht, James M. Stone

    Results Significant reductions in NAA levels were found in frontal lobe, temporal lobe, and thalamus in both patient groups (effect size > .3; p < .01). In individuals at high risk of schizophrenia (of whom approximately 20% would be expected to undergo transition to psychosis), significant NAA reductions were present in thalamus (effect size = .78; p < .05), with reductions at trend level only in temporal lobe (effect size = .32; p < .1), and no reductions in frontal lobe (effect size = .05; p = .5).

    Conclusions  These data suggest that schizophrenia is associated with loss of neuronal integrity in frontal and temporal cortices and in the thalamus and suggest that these changes in the frontal and temporal lobe might occur in the transition between the at-risk phase and the first episode.

    另一篇Early Recognition and Disease Prediction in the At-Risk Mental States for Psychosis Using Neurocognitive Pattern Classification.  Schizophr Bull published 16 May 2011, 10.1093/schbul/sbr037

      http://schizophreniabulletin.oxfordjournals.org/cgi/content/abstract/sbr037v1?papetoc

      Different ARMS and their clinical outcomes may be reliably identified on an individual basis by evaluating neurocognitive test batteries using multivariate pattern recognition. These patterns may have the potential to substantially improve the early recognition of psychosis.


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