Estimating the influence of attention on population codes in human visual cortex using voxel-based tuning functions.

In order to form stable perceptual representations, populations of sensory neurons must pool their output to overcome physiological noise; selective attention is then required to ensure that behaviorally relevant stimuli dominate these 'population codes' to gain access to awareness. However, the role that attention plays in shaping population response profiles has received little direct investigation, in part because most traditional neurophysiological methods cannot simultaneously assess changes in activity across large populations of sensory neurons. Based on single-unit recording studies, current theories hold that attending to a relevant feature sharpens the population response profile and improves the signal-to-noise ratio of the resulting perceptual representation. Here, we test this hypothesis using fMRI and an analysis approach that is able to estimate the influence of feature-based attentional modulations on population response profiles. We first derive orientation tuning functions for single voxels in human primary visual cortex, and then use these tuning functions to sort voxels according to their orientation preference. We then show that selective attention systematically biases population response profiles so that behaviorally relevant stimuli are represented in the visual system at the expense of behaviorally irrelevant stimuli. Collectively, the present results (1) provide a new approach for precisely characterizing feature-selective responses in human sensory cortices and (2) reveal how behavioral goals can shape population response profiles to support the formation of coherent perceptual representations.