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https://www.um.edu.mt/library/oar/handle/123456789/86685
Title: | T-patterns in the study of movement and behavioral disorders |
Authors: | Aiello, Stefania Crescimanno, Giuseppe Di Giovanni, Giuseppe Casarrubea, Maurizio |
Keywords: | Nervous system -- Diseases Nervous system -- Analysis Behavioral assessment Movement disorders Mental disorders |
Issue Date: | 2020 |
Publisher: | Elsevier |
Citation: | Aiello, S., Crescimanno, G., Di Giovanni, G., & Casarrubea, M. (2020). T-patterns in the study of movement and behavioral disorders. Physiology & Behavior, 215, 112790. |
Abstract: | Aim of the present review is to offer an outline of the application of T-pattern analysis (TPA) in the study of neurological disorders characterized by anomalies of movement and, more in general, of behavior. TPA is a multivariate technique to detect real time patterns of behavior on the basis of statistically significant constraints among the events in sequence. TPA is particularly suitable to analyse the structure of behavior. The application of TPA to study movement and behavioral disorders is able to offer, with a high level of detail, hidden characteristics of behavior otherwise impossible to detect. For its intrinsic features, TPA is completely different not only from quantitative evaluations of behavior such as assessments of frequencies, durations, percent distributions etc. of individual behavioral components, but also from the largest extent of multivariate approaches based, for instance, on the analysis of transition matrices. Various applications of TPA in the study of behavior in human patients and in animal models of neurological disorders are discussed. TPA is a suitable tool to study the movement and behavioral disorders. This review represents a useful background for researchers, therapists, physicians etc. who intend to use this technique. |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/86685 |
Appears in Collections: | Scholarly Works - FacM&SPB |
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T_patterns_in_the_study_of_movement_and_behavioral_disorders_2020.pdf Restricted Access | 336.89 kB | Adobe PDF | View/Open Request a copy |
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