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.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Small Research Grants (R03)
Project #
5R03EY013791-02
Application #
6525364
Study Section
Special Emphasis Panel (ZEY1-VSN (04))
Program Officer
Oberdorfer, Michael
Project Start
2001-09-10
Project End
2004-08-31
Budget Start
2002-09-20
Budget End
2003-08-31
Support Year
2
Fiscal Year
2002
Total Cost
$128,125
Indirect Cost
Name
University of Southern California
Department
Biostatistics & Other Math Sci
Type
Schools of Engineering
DUNS #
041544081
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
Carmi, Ran; Itti, Laurent (2006) Visual causes versus correlates of attentional selection in dynamic scenes. Vision Res 46:4333-45
Carmi, Ran; Itti, Laurent (2006) The role of memory in guiding attention during natural vision. J Vis 6:898-914
Mundhenk, T Nathan; Itti, Laurent (2005) Computational modeling and exploration of contour integration for visual saliency. Biol Cybern 93:188-212
Lu, Jianwei; Itti, Laurent (2005) Perceptual consequences of feature-based attention. J Vis 5:622-31
Navalpakkam, Vidhya; Itti, Laurent (2005) Modeling the influence of task on attention. Vision Res 45:205-31
Itti, Laurent (2004) Automatic foveation for video compression using a neurobiological model of visual attention. IEEE Trans Image Process 13:1304-18