Literature DB >> 7548470

Selected quantitative EEG (QEEG) and event-related potential (ERP) variables as discriminators for positive and negative schizophrenia.

M Gerez1, A Tello.   

Abstract

Heterogeneity is a major obstacle in the search for biological substrates in schizophrenia. The positive and negative distinction, even if too simplistic, may improve our understanding of underlying processes. Frontostriatal deficits have been related to negative symptoms, while dysfunction of the dominant temporal lobe appears more relevant to the generation of positive symptoms. Despite interactions between the subsystems, different neurophysiological profiles could be expected for patients predominantly affected at each of those levels. We performed discriminant analysis on 10 neurophysiological variables (hypothesis-related) in schizophrenic patients grouped by positive or negative symptoms (PANSS), obtaining a discriminant that correctly classified the sample. The function was then tested in a new sample of patients with schizophrenia, affective psychoses, and controls, classifying subjects with 78% sensitivity and 85% specificity. Our findings suggest that predominantly negative and positive schizophrenics have different neurophysiological profiles, which are consistent with the hypotheses of hypofrontality and temporal lobe dysfunction, respectively. A linear relation between discriminant scores and PANSS ratings might reflect coexisting pathologies or compensatory interactions in the mixed subgroup.

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Year:  1995        PMID: 7548470     DOI: 10.1016/0006-3223(94)00205-H

Source DB:  PubMed          Journal:  Biol Psychiatry        ISSN: 0006-3223            Impact factor:   13.382


  7 in total

Review 1.  Biomarkers for the effects of antipsychotic drugs in healthy volunteers.

Authors:  S J de Visser; J van der Post; M S Pieters; A F Cohen; J M van Gerven
Journal:  Br J Clin Pharmacol       Date:  2001-02       Impact factor: 4.335

Review 2.  The status of spectral EEG abnormality as a diagnostic test for schizophrenia.

Authors:  Nash N Boutros; Cynthia Arfken; Silvana Galderisi; Joshua Warrick; Garrett Pratt; William Iacono
Journal:  Schizophr Res       Date:  2007-12-21       Impact factor: 4.939

Review 3.  Neuropsychiatric Disorders as Erratic Attention Regulation - Lessons from Electrophysiology.

Authors:  Goded Shahaf
Journal:  Psychiatr Q       Date:  2019-12

Review 4.  Identification of neural circuits underlying P300 abnormalities in schizophrenia.

Authors:  B F O'Donnell; R W McCarley; G F Potts; D F Salisbury; P G Nestor; Y Hirayasu; M A Niznikiewicz; J Barnard; Z J Shen; D M Weinstein; F L Bookstein; M E Shenton
Journal:  Psychophysiology       Date:  1999-05       Impact factor: 4.016

5.  Differentiation of schizophrenia patients from healthy subjects by mismatch negativity and neuropsychological tests.

Authors:  Yi-Ting Lin; Chih-Min Liu; Ming-Jang Chiu; Chen-Chung Liu; Yi-Ling Chien; Tzung-Jeng Hwang; Fu-Shan Jaw; Jia-Chi Shan; Ming H Hsieh; Hai-Gwo Hwu
Journal:  PLoS One       Date:  2012-04-05       Impact factor: 3.240

6.  Sleep-Wake Rhythm and Oscillatory Pattern Analysis in a Multiple Hit Schizophrenia Rat Model (Wisket).

Authors:  Leatitia Gabriella Adlan; Mátyás Csordás-Nagy; Balázs Bodosi; György Kalmár; László G Nyúl; Attila Nagy; Gabriella Kekesi; Alexandra Büki; Gyongyi Horvath
Journal:  Front Behav Neurosci       Date:  2022-01-28       Impact factor: 3.558

7.  Accuracy of EEG Biomarkers in the Detection of Clinical Outcome in Disorders of Consciousness after Severe Acquired Brain Injury: Preliminary Results of a Pilot Study Using a Machine Learning Approach.

Authors:  Francesco Di Gregorio; Fabio La Porta; Valeria Petrone; Simone Battaglia; Silvia Orlandi; Giuseppe Ippolito; Vincenzo Romei; Roberto Piperno; Giada Lullini
Journal:  Biomedicines       Date:  2022-08-05
  7 in total

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