title: Hierarchical nonlinear dynamics of human attention.
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.
authors: BioCircuits Institute, University of California, San Diego, 9500 Gilman Drive #0328, La Jolla, CA 92093-0328, United States.
authors: Mikhail I
authors: MI
authors: Rabinovich
authors: BioCircuits Institute, University of California, San Diego, 9500 Gilman Drive #0328, La Jolla, CA 92093-0328, United States.
authors: Irma
authors: I
authors: Tristan
authors: Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, 28049 Madrid, Spain. Electronic address: pablo.varona@uam.es.
authors: Pablo
authors: P
authors: Varona
mesh_terms: D001288:Attention / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009434:Neural Pathways / Q000502:physiology; D017711:Nonlinear Dynamics
keywords: Attention sharing; Perception binding; Robust sequence generation; Stable heteroclinic channel; Temporal coordination and creativity; Transient dynamics; Working memory capacity