title: Complexity of functional connectivity networks in mild cognitive impairment subjects during a working memory task.
abstract: OBJECTIVE
  The objective is to study the changes of brain activity in patients with mild cognitive impairment (MCI). Using magneto-encephalogram (MEG) signals, the authors investigate differences of complexity of functional connectivity network between MCI and normal elderly subjects during a working memory task.
  
  
  METHODS
  MEGs are obtained from 18 right handed patients with MCI and 19 age-matched elderly participants without cognitive impairment used as the control group. The brain networks' complexities are measured by Graph Index Complexity (C(r)) and Efficiency Complexity (C(e)).
  
  
  RESULTS
  The results obtained by both measurements show complexity of functional networks involved in the working memory function in MCI subjects is reduced at alpha and theta bands compared with subjects with control subjects, and at the theta band this reduction is more pronounced in the whole brain and intra left hemisphere.
  
  
  CONCLUSIONS
  C(e) would be a better measurement for showing the global differences between normal and MCI brains compared with C(r).
  
  
  CONCLUSIONS
  The high accuracy of the classification shows C(e) at theta band can be used as an index for assessing deficits associated with working memory, a good biomarker for diagnosis of MCI.
authors.affiliation: Netherlands Institute for Neuroscience, Meibergdreef 47, Amsterdam, The Netherlands.
authors.forename: Mehran
authors.initials: M
authors.lastname: Ahmadlou
authors.affiliation: Department of Neurology, The Ohio State University, 395 W 12th Ave, 7th Floor Columbus, OH 43210, United States.
authors.forename: Anahita
authors.initials: A
authors.lastname: Adeli
authors.affiliation: Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Campus de Montegancedo, 28223 Pozuelo de Alarcón, Madrid, Spain.
authors.forename: Ricardo
authors.initials: R
authors.lastname: Bajo
authors.affiliation: Department of Biomedical Engineering, The Ohio State University, Columbus, OH 43210, United States; Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, United States; Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, 470 Hitchcock Hall, 2070 Neil Avenue, Columbus, OH 43210, United States; Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, United States; Department of Neurological Surgery, The Ohio State University, Columbus, OH 43210, United States; Department of Neuroscience, The Ohio State University, Columbus, OH 43210, United States. Electronic address: adeli.1@osu.edu.
authors.forename: Hojjat
authors.initials: H
authors.lastname: Adeli
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers; D001921:Brain / Q000503:physiopathology*; D001931:Brain Mapping / Q000379:methods; D060825:Cognitive Dysfunction / Q000175:diagnosis / Q000503:physiopathology* / Q000523:psychology; D004569:Electroencephalography; D005260:Female; D006801:Humans; D015225:Magnetoencephalography; D008297:Male; D008570:Memory, Short-Term / Q000502:physiology*; D008875:Middle Aged; D009415:Nerve Net / Q000503:physiopathology*; D009483:Neuropsychological Tests
chemical_list: D015415:Biomarkers
keywords: Complexity of functional connectivity networks; Efficiency Complexity; Graph Index Complexity; Magneto encephalography; Mild cognitive impairment; Working memory