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Biomedical subjects

Robert A M Gregson

Publications and source records attributed to Robert A M Gregson.

5 recordsLinked to original sources
PubMed2005

Identifying ill-behaved nonlinear processes without metrics: use of symbolic dynamics.

Given ill-behaved psychological data that are unlikely to satisfy metric axioms, the use of encoding in symbolic dynamics, and hence leading into Markov analyses, is explored. Various measures of entropy are calculated. The tractability of entropic measures for categorizing the trajectories of nonlinear dynamics that may be present and chaotic is considered, with a focus on the case where there are two attractors and at least one heteroclinic orbit between them. Fast/slow dynamics are treated as a special case. The problem of identification is in other contexts the problem of diagnosis in time-varying pathologies. Some real data, selected for their psychological relevance in clinical, forensic and psychophysical processes, that are apparently edge-of chaos and nonstationary, are for comparison analysed both as metric and discrete and in symbolic encoding.

Humans↗
PubMed2004

Transitions between two pictorial attractors.

Two experiments exploring similarity judgments on pairs and triplets of stimuli drawn from pictorial series are described. The stimuli are the Man-Woman and Gypsy-Girl pictures that slowly change from one prototype to the other as one progresses along the series. These have been used previously to demonstrate hysteresis of category judgments on ambiguous figures; the Man Woman series has been both modelled as a problem in neural network theory and mapped onto part of a cusp catastrophe surface. It. is shown that the transition process is complicated with a zone of uncertainty and prevalence of bimodality in many of the pairwise similarity judgments. The dynamics are interpreted in terms of transitions between two saddle-node attractors that are themselves not a discrete pair but have some overlap in their composition.

Humans↗
PubMed2003

Forcing function effects on nonlinear trajectories: identifying very local brain dynamics.

Effects of imposing a sinusoidal acoustic and visual forcing function at various frequencies onto an EEG process are examined in terms of various indices of the nonlinear dynamics. Conjoint use of four methods of data analysis; Lyapunov exponents, the entropic analogue of the Schwarzian derivative, surrogate distributions, and higher-order kernel analyses in the time domain, is illustrated. Local epochs with unstable dynamics are identifed on very short series.

Auditory Perception↗