Visual selective attention enables perception and adaptive behaviour by focussing cortical processing resources on the most relevant information. How attention achieves this selection of information is a key question in both human and animal neuroscience that has far reaching implications for understanding perceptual and cognitive abilities. For example, our functionality in a variety of everyday situations such as driving a car, competitive team sports, or social interactions depends on attentional selection of sensory information.
Attentional modulation of sensory processing in visual cortex has been thoroughly studied using a variety of techniques ranging from primate single cell recordings to human imaging and electroencephalography (EEG). Despite this, the dynamic patterns of how attentional modulation spread across multiple brain areas are still poorly understood.
This project will investigate the dynamic interactions of attentional mechanisms in healthy human vision across different brain areas. This will be achieved by combining behavioural measures, scalp recordings of steady-state visual evoked potentials (SSVEPs), and structural fMRI scans. This goal cannot be achieved by either technique in isolation because EEG has a poor spatial resolution and fMRI has a poor temporal resolution. However, by utilising structural fMRI scans to constrain EEG source reconstruction it is possible to reliably separate SSVEP responses from different visual brain areas (Cottereau et al., 2012). Applying this analysis technique to established SSVEP attention paradigms (e.g. Andersen et al., 2012), will allow us to study the time-course of attentional modulation concurrently in different brain areas. This will, for example, enable us to directly test the hypothesis of a backward progression of attention effects from higher to lower areas of the visual processing hierarchy (Buffalo et al., 2010) noninvasively in human subjects for the first time.
The PhD candidate involved in this project will develop a thorough understanding of selective visual attention, state-of-the-art electrophysiological techniques and experimental design practices. In particular, this involves a high level of expertise in programming (Matlab), digital signal processing (e.g. time-frequency analysis of oscillatory brain responses) and advanced source reconstruction techniques using co-registered EEG and MRI data. These techniques easily lend themselves to more applied approaches. For instance, SSVEPs are a core technique for the development of brain-computer interfaces (BCIs), which are central to approaches to communicate with patients with locked-in syndrome or disorders of consciousness, such as minimally conscious states. These techniques also provide a strong grounding in statistical analysis, advanced mathematics, and computer programming, all of which are highly relevant skills in today’s world: both in the industry and in academia.
The project is interdisciplinary, bringing together behavioural biology, experimental psychology, and human neuroscience and the involved techniques require a good mathematical understanding. The project would thus suit candidates with backgrounds in psychology, neuroscience, behavioural biology or physical science/engineering eager to apply quantitative techniques to biological problems.
Andersen SK, Müller MM, Martinovic J (2012) Bottom-up biases in feature-selective attention. J Neurosci 32:16953-8.
Buffalo EA, Fries P, Landman R, Liang H, Desimone R (2010) A backward progression of attentional effects in the ventral stream. Proc Natl Acad Sci U S A 107:361-5.
Cottereau BR, Ales JM, Norcia AM (2012) Increasing the accuracy of electromagnetic inverses using functional area source correlation constraints. Hum Brain Mapp 33:2694-2713.
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