Hierarchical nonlinear dynamics of human attention. (August 2015)

• Record Type: Journal Article
• Authors: Rabinovich, Mikhail I.; Tristan, Irma; Varona, Pablo
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 55(2015:Aug.)
• Page Start: 18
• Page End: 35
• Publication Date: 2015-08
• Subjects: Attention sharing -- Perception binding -- Stable heteroclinic channel -- Transient dynamics -- Robust sequence generation -- Working memory capacity -- Temporal coordination and creativity; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2015.04.001
• Languages: English
• ISSNs: 0149-7634

Abstract

Graphical abstract: Highlights: Attention can be described by multimode hierarchical sequential dynamics. Nonlinear dynamics is effective for building a theory of attention. We analyze attentional control stability and the time cost of attention switching. We address the finite capacity of informational resources in the brain. We discuss normal and pathological bifurcations of attention sequential dynamics. Abstract: Attention is the process of focusing mental resources on a specific cognitive/behavioral task. Such brain dynamics involves different partially overlapping brain functional networks whose interconnections change in time according to the performance stage, and can be stimulus-driven or induced by an intrinsically generated goal. The corresponding activity can be described by different families of spatiotemporal discrete patterns or sequential dynamic modes. Since mental resources are finite, attention modalities compete with each other at all levels of the hierarchy, from perception to decision making and behavior. Cognitive activity is a dynamical process and attention possesses some universal dynamical characteristics. Thus, it is time to apply nonlinear dynamical theory for the description and prediction of hierarchical attentional tasks. Such theory has to include the analyses of attentional control stability, the time cost of attention switching, the finite capacity of informational resources in the brain, and the normal and pathological bifurcations of attention sequential dynamics. In this paper we have integrated today's knowledge, models and results in these directions.