Biomedical subjects

John G Taylor

Publications and source records attributed to John G Taylor.

7 recordsLinked to original sources

PubMed2005

A neurodynamic model of the attentional blink.

A brain-based neural model of attention is used to simulate results for the 'attentional blink', observed when a subject is exposed to a rapid stream of stimuli and required to monitor for two successive targets in the stream. The 'blink' occurs when the time between the first and second targets is 200-500 ms, when there is reduced accuracy for report of the second target. The model gives a qualitative explanation of the phenomenon, especially of how attention is bolstered, during the processing to report of a given stimulus, in order to defend reportable information from attack by distracters.

Attention↗

PubMed2005

The interaction of attention and emotion.

We analyse emotions from the viewpoint of how emotion and attention interact in the brain. Much has been learnt about the brain structures involved in attention, especially in vision. In particular the manner in which attention functions as a high-level control system, able to make cognitive processing so effective, has been studied both at a global level by brain imaging (fMRI, PET, MEG and EEG), at a local single cell level in monkeys and lower animals, and computationally by a variety of models. The manner in which emotions impinge on this attention control system is not so well analysed, although numerous new results are now emerging from using the same tools. Here we use an engineering control approach to attention to model it in a global manner but with relatively sure local foundations at singe neuron level. The manner in which emotional value (as coded in amygdale and orbito-frontal cortex) can interact with the attention control circuitry is analysed using results of various experimental paradigms. A general model of this interaction is first developed and tested against a list of paradigms, and then more detailed computations are performed using more specific features of the attention control system and the limbic value coding. These computations are completed by a simulation of the emotional attentional blink, a demanding paradigm for any model of attention alone, but made more so by the presence of emotional value codes for stimuli. We conclude the paper with a general discussion of further avenues of research.

Animals↗

PubMed2004

A general framework for learning rules from data.

With the aim of getting understandable symbolic rules to explain a given phenomenon, we split the task of learning these rules from sensory data in two phases: a multilayer perceptron maps features into propositional variables and a set of subsequent layers operated by a PAC-like algorithm learns Boolean expressions on these variables. The special features of this procedure are that: i) the neural network is trained to produce a Boolean output having the principal task of discriminating between classes of inputs; ii) the symbolic part is directed to compute rules within a family that is not known a priori; iii) the welding point between the two learning systems is represented by a feedback based on a suitability evaluation of the computed rules. The procedure we propose is based on a computational learning paradigm set up recently in some papers in the fields of theoretical computer science, artificial intelligence and cognitive systems. The present article focuses on information management aspects of the procedure. We deal with the lack of prior information about the rules through learning strategies that affect both the meaning of the variables and the description length of the rules into which they combine. The paper uses the task of learning to formally discriminate among several emotional states as both a working example and a test bench for a comparison with previous symbolic and subsymbolic methods in the field.

Algorithms↗

PubMed2003

Paying attention to consciousness.

An engineering control approach is developed for the movement of attention, based on several features: experimental data indicating separate sites for attention modulation and for the creation of that modulation; the resulting analogy with motor control, to which an engineering approach has been applied; simulation and qualitative results supporting the presence of several of the necessary modules. These features are reviewed in the paper and a control model developed for the movement of attention. The engineering control framework is extended to the attended learning of motor control, again with description of support arising from simulations and qualitative analysis of several paradigms. The framework is even further extended to analyze how consciousness could arise during attentive processing, using the COrollary Discharge of Attention Movement (CODAM) model. This model is extended to encompass the temporal development of activity in various brain sites. Particular signals of the CODAM model are described and related to paradigms such as the attentional blink (AB) and features of simultaneous experience in neglect. A program of future explorations of the CODAM model and a set of open questions conclude the paper.

Animals↗

PubMed2003

Bubbles in the brain?

How does the brain learn to control motor actions? 'Bubbles' of activity might exist in the cortex, as implied by a simplified model of the cortical sheet. New results show how these bubbles could enable motor actions to be especially efficient, and that they can be used with little difficulty in decoding them.

Journal Article↗

PubMed2002

Trends and random fluctuations in athletics.

Improvements in the results of athletic competitions are often considered to stem from better training and equipment, but elements of chance are always present in athletics and these also contribute. Here we distinguish between these two effects by estimating the range into which athletic records would have fallen in the absence of systematic progress and then comparing this with actual performance results. We find that only 4 out of 22 disciplines have shown a systematic improvement, and that annual best results worldwide show saturation in some disciplines.

Germany↗

PubMedDate not supplied

A model of visual backward masking.

When two successive stimuli are presented within 0-200 ms intervals, the recognition of the first stimulus (the target) can be impaired by the second (the mask). This backward masking phenomenon has a form called metacontrast masking where the target and the mask are in close spatial proximity but not overlapping. In that case, the masking effect is strongest for interval of 60-100 ms. To understand this behaviour, activity propagation in a feedforward network of leaky integrate and fire neurons is investigated. It is found that, if neurons have a selectivity similar to that of V1 simple cells, activity decays layer after layer and ceases to propagate. To combat this, a local amplification mechanism is included in the model, using excitatory lateral connections, which turn out to support prolonged self-sustained activity. Masking is assumed to arise from local competition between representations recruited by the target and the mask. This tends to interrupt sustained firing, while prolonged retinal input tends to re-initiate it. Thus, masking causes a maximal reduction of the duration of the cortical response to the target towards the end of the retinal response. This duration exhibits the typical U-shape of the masking curve. In this model, masking does not alter the propagation of the onset of the response to the target, thus preserving response reaction times and enabling unconscious priming phenomena.

Models, Neurological↗