A quantitative framework of attentional selection

Attentional selection is an essential prerequisite for adaptive behaviour. The brain receives a vast amount of information from our sensory organs. Fully processing all of this information would exceed the capacity of the human brain, therefore attention selects only some of this information for in-depth processing at the expense of other, less relevant information. Attention is a key concept in the understanding of mental abilities: it critically influences perception, memory, cognition, emotion and consciousness, so that what we see, remember, think, feel and experience is, to a large extent, a function of selective attention.

Selectively attending to a stimulus enhances its processing in visual cortex and increases accuracy and speed of motor responses. While the connection between these findings seems obvious, our understanding of this connection is surprisingly vague: we know that, in the average of many trials, measures of cortical processing and behavioural performance are enhanced when the eliciting stimulus is attended, but we have very limited understanding of how these attentional effects are quantitatively related.

The proposed project aims to develop a quantitative model of visual attention that directly links electrophysiological measures of stimulus processing in visual cortex with behavioural outcomes. This will be achieved in a sequence of three connected objectives:

First, we will examine how concurrent attentional selection of different dimensions (e.g. location, colour, orientation or motion) affects stimulus processing. This will allow us to better understand attentional selection in complex realistic situations and facilitates quantitative modelling in the subsequent experiments by restricting model parameters.

Second, we will conduct a series of three EEG experiments in order to uncover the quantitative connections between attentional modulation of stimulus processing in visual cortex and behavioural measures. This will significantly enhance our understanding of how attention supports adaptive behaviour.

Third, we will investigate how monitoring of behavioural performance is used to readjust attentional model parameters over time in order to optimise subsequent performance. This will help us understand why performance on the same task fluctuates over time. It also provides important information on why attentional model parameters take on specific values.

The answers to these questions fundamentally contribute to our understanding of visual attention and perception. This research may have implications for research in special populations (e.g. children and older participants, patients with attentional disorders) as the experimental protocols and modelling approaches of the present project could be applied to gain a better understanding of group differences. Additionally, this work may facilitate the further development of Brain Computer Interfaces (BCIs), which allow subjects to convey their intentions by shifting attention and which commonly employ similar technical approaches as the present project.

The brain's capacity for visual processing is limited. Hence, selective attention directs processing resources to relevant stimuli in order to allow for adaptive behaviour. Previous research has documented attentional effects on measures of neuronal activity and behavioural performance, however these different types of measures have rarely been linked quantitatively.
Existing quantitative models of visual attention currently do not allow us to make direct connections between behavioural and neuronal measures. Although Bundesen's Theory of Visual Attention (TVA) has recently been reinterpreted in the context of neuroscientific models of attention, its empirical foundations still remain behavioural. The biased competition, feature-similarity gain and normalization models on the other hand provide quantitative descriptions of attentional effects on individual neurons, however they do not offer a direct quantitative link to behavioural data.
The proposed project aims to develop a quantitative model of visual attention that directly links electrophysiological recordings of 'frequency-tagged' steady-state visual evoked potentials (SSVEPs) with behavioural outcomes. This will be achieved through three connected objectives:
First, we will examine how concurrent attentional selection of different dimensions (e.g. location and colour) affects stimulus processing. This will facilitate modelling in the subsequent experiments and helps understand attentional selection in complex realistic situations.
Second, we will conduct three EEG experiments in order to uncover quantitatively how attentional modulation of stimulus processing in visual cortex affects behavioural measures.
Third, we will investigate how performance monitoring leads to readjustment of attentional model parameters. This helps us understand the basis of fluctuations in performance and also yields information on why attentional model parameters take on specific values.

The primary impact of the proposed research will be an increased understanding of fundamental aspects of human selective visual attention. Selective processing of sensory inputs plays a critical role in how we experience the world around us; understanding it is intrinsically valuable.
Due to the fundamental nature of this research, the most immediate beneficiaries will be other researchers of three types: (a) researchers who are interested in integrating the results with other findings in order to develop a more complete functional understanding of the human brain (b) researchers who are interested in applying the 'frequency tagging' technique to investigate other cognitive phenomena and (c) researchers who may apply the results to investigate attentional disorders or cognitive ageing or to further the development of Brain Computer Interfaces (BCIs), which allow subjects to convey their intentions to a computer by shifting attention between stimuli (e.g. letters or digits) in a visual display. In order to reach these researchers, the work will be submitted to high-impact journals with a large readership and presented at various national and international conferences with wide audiences. Particular care will be taken to present the findings and possible implications in nontechnical language to the media to make them accessible to non-specialist audiences.
This project will also provide rigorous scientific research training to a post-doctoral research assistant, who will develop specialized skills such as the utilization of psychophysical and electrophysiological techniques, time-frequency analysis of biological signals and more general skills such as programming and scientific writing.
Finally, the United Kingdom's reputation as a leading country for fundamental research with highly influential contributions in the fields of cognitive and visual neurosciences will be reinforced through the advances afforded by the proposed research. Publishing the results in top journals will attract more excellent researchers to work at UK institutions and thereby advance the scientific community here.