title: [Ageing and arithmetic performance--electrophysiological complexity-, and graph theoretical characteristics].
abstract: During the course of ageing the decline of cognitive performance, including attention and working memory processes--essential for arithmetic procedures--is well known. For the investigation of the neuronal mechanisms of these processes the application of methods capable of taking into account the high complexity of the nervous system, the role of nonlinear processes and network-properties of its constituents are necessary. As for the latter the recently realized small world network characteristics representing optimal conditions for information processing may be of particular importance. In the present study the spectral, complexity-, and network characteristics of the EEG recorded during performing an arithmetic task in a group of young (n=32, mean age 22.0 yrs) and elderly (n=19, mean age: 66.7 yrs) was analyzed. Heart rate and behavioral measures (number of mistakes, reaction time) were also investigated. The alpha2 band decreased in the young, while the delta band increased in the elderly in the task condition. The increased Omega-complexity observed in the elderly is probably caused by reduced interneuronal connectivity. "Small-world" network characteristics were found in the beta and delta bands although in the elderly the topology was closer to a random pattern. In the task condition the network features of the elderly subjects shifted more towards the small world pattern than those seen in the young indicating that for the elderly the mobilized effort for task completion was higher. In spite of this, the level of performance and the heart rate change observed in the elderly was lower than that seen in the young. The application of complexity-, and graph theoretical analysis appears to be a promising tool for the investigation of diseases of the nervous system characterized by diffuse pathology as in the case of as various types of dementias.
authors.affiliation: MTA, Pszichológiai Kutatóintézet, Budapest. molnar@cogpsyphy.hu
authors.forename: Márk
authors.initials: M
authors.lastname: Molnár
authors.forename: Roland
authors.initials: R
authors.lastname: Boha
authors.forename: Máté
authors.initials: M
authors.lastname: Benyovszky
authors.forename: Zsófia Anna
authors.initials: ZA
authors.lastname: Gaál
authors.forename: Brigitta
authors.initials: B
authors.lastname: Tóth
mesh_terms: D000328:Adult; D000368:Aged; D000375:Aging; D001921:Brain / Q000502:physiology*; D003071:Cognition / Q000502:physiology*; D004562:Electrocardiography; D004569:Electroencephalography; D005260:Female; D006339:Heart Rate; D006801:Humans; D008297:Male; D008432:Mathematical Computing; D008875:Middle Aged; D008959:Models, Neurological; D017711:Nonlinear Dynamics