The content of visual experience depends on how selective attention is distributed in the visual field. We used functional magnetic resonance imaging (fMRI) in humans to test whether feature-based attention can globally influence visual cortical responses to stimuli outside the attended location. Attention to a stimulus feature (color or direction of motion) increased the response of cortical visual areas to a spatially distant, ignored stimulus that shared the same feature.

Although motion-sensitive neurons in macaque middle temporal (MT) area are conventionally characterized using stimuli whose velocity remains constant for 1-3 s, many ecologically relevant stimuli change on a shorter time scale (30-300 ms). We compared neuronal responses to conventional (constant-velocity) and time-varying stimuli in alert primates. The responses to both stimulus ensembles were well described as rate-modulated Poisson processes but with very high precision (approximately 3 ms) modulation functions underlying the time-varying responses. Information-theoretic analysis revealed that the responses encoded only approximately 1 bit/s about constant-velocity stimuli but up to 29 bits/s about the time-varying stimuli. Analysis of local field potentials revealed that part of the residual response variability arose from "noise" sources extrinsic to the neuron. Our results demonstrate that extrastriate neurons in alert primates can encode the fine temporal structure of visual stimuli.

Previous electrophysiology data suggests that the modulation of neuronal firing by spatial attention depends on stimulus contrast, which has been described using either a multiplicative gain or a contrast-gain model. Here we measured the effect of spatial attention on contrast responses in humans using functional MRI. To our surprise, we found that the modulation of blood oxygenation level-dependent (BOLD) responses by spatial attention does not greatly depend on stimulus contrast in visual cortical areas tested [V1, V2, V3, and MTϩ (middle temporal area)]. An additive model, rather than a multiplicative or contrast-gain model best describes the attentional modulations in V1. This inconsistency with previous single-unit electrophysiological data has implications for the population-based neuronal source of the BOLD signal.

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