Understanding how attention modulates early sensory processing has become a high-priority research topic in visual neuroscience. Although much progress has recently been made in observing the conditions under which attention may affect sensation, the computational mechanism at the origin of attentional modulation remains largely unknown and controversial. This exploratory study seeks to develop new methodologies, combining human psychophysics, functional neuroimaging and computational modeling, to provide further quantitative understanding of how attention modulates early Visual processing. Psychophysical experiments will use a dual-task paradigm to split attention between a central and a near-peripheral visual discrimination task being performed simultaneously. This will allow the acquisition of psychophysical data under """"""""fully"""""""" and """"""""poorly"""""""" attended conditions, for 15 subjects and five different peripheral spatial pattern discrimination tasks . The central task will thus be used for the sole purpose of engaging attention away from the tasks of interest in the poorly attended condition. The five tasks will consist of discriminating contrast, orientation, spatial frequency, and contrast under two masking conditions, for simple visual patterns. A subset of 10 subjects will be selected, based on the stability of their psychophysical thresholds and on their ability to carry out dual tasks, for a subsequent high-field (4 Tesla) functional magnetic resonance imaging experiment( fMRI). This experiment will use an event-related paradigm to evaluate attentional modulation in primary visual cortex (area V1), for a performance-matched subset of the five pattern discrimination tasks. Using a control fMRI experiment consisting of viewing simple Gabor patches under full attention, the hemodynamic responses measured with fMRI will be calibrated against a detailed computational model of one hypercolumn in V1. This model will be further applied to test whether a single computational effect of attention, namely a strengthening of competition among the neurons within a V1 hypercolumn, can simultaneously explain the psychophysical and fMRI data. This exploratory study will, demonstrate how combining psychophysics, imaging and modeling may yield better quantitative and computational understanding of higher brain function.
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