Covert attention can lead to improved performance in perceptual tasks. The neural and functional mechanisms of covert attention are still under investigation. Using both rapid event-related and mixed designs, we measured the blood oxygenation leveldependent functional MRI contrast response functions over the full range of contrast (0 -100%) in the retinotopically defined early visual areas (V1, V2, V3, V3A, and V4) in humans. Covert attention increased both the baseline activities and contrast gains in the five cortical areas. The effect on baseline can be decomposed into a transient trial-by-trial component and a component across an entire attention block. On average, increase in contrast gain accounted for Ϸ88.0%, 28.5%, 12.7%, 35.9%, and 25.2% of the trial-by-trial effects of attention in the five areas, respectively, and 22.2%, 12.8%, 7.4%, 19.7%, and 17.3% of the total effects of attention in those areas, consistent with single-unit findings in V4 and MT. The results provide strong evidence for a stimulus enhancement mechanism of attention as demonstrated in various behavioral studies.contrast gain ͉ increased baseline ͉ response gain ͉ stimulus enhancement C overt attention can lead to improved performance accuracy and response time (1, 2). Since the initial discovery that attention increases the blood oxygenation level-dependent (BOLD) responses in early visual areas (3-9), a large number of new studies have further documented many interesting effects of attention in the visual pathway, including attentional modulation of the BOLD responses in the lateral geniculate nucleus (10), increased BOLD activities in the visual cortical areas corresponding to the attended spatial location in the absence of visual stimulation (6,11,12), different effects of endogenous and exogenous attention (13,14), and topographic maps of visual spatial attention in parietal cortex (15). How attention enhances visual stimuli in early visual cortical areas, however, remains unclear. We attempt to address this fundamental question in this study.There are three potential mechanisms underlying the increased BOLD responses in early visual areas ( Fig. 1): increased contrast gain, increased response gain, and increased baseline activity. Formulated in terms of the impact of attention on contrast response functions (CRFs), these three mechanisms have distinct behavioral and functional significance. In the behavioral domain, a theoretical framework based on analyses of human observers distinguishes three mechanisms of attention: stimulus enhancement, external noise exclusion, and nonlinearity change (16,17). Whereas an increase in baseline activity need not contribute to improved discrimination and cannot be observed in psychophysical studies (18), increased contrast gain (18, 19) is related to behaviorally identified stimulus enhancement in a discrimination task, and response gain corresponds to nonlinearity changes observed behaviorally (20). Because most of the functional MRI (fMRI) attention studies used a single stimulus contrast, t...

Dosher and Lu (1998) [Perceptual learning reflects external noise filtering and internal noise reduction through channel reweighting. Proceedings of the National Academy of Sciences of the United States of America, 95 (23), 13988-13993.] proposed three mechanisms of perceptual learning: stimulus enhancement, external noise exclusion, and multiplicative noise reduction. In this study, we used pre-training as a manipulation to evaluate the separability of these mechanisms as a key test of the theoretical framework. Observers were trained in identifying the motion direction of a moving sine-wave grating in fovea with varying amount of superimposed external noise across trials, after receiving no pre-training, pre-training in high external noise, or pre-training in zero external noise in the same task. We found: (1) Without pre-training, perceptual learning significantly reduced contrast thresholds by about the same amount across all the external noise levels. (2) Both types of pre-training significantly reduced contrast thresholds in the corresponding conditions. (3) Pre-training in high external noise greatly reduced subsequent learning in high external noise, accounting for 64.6% of the total (pre-training + subsequent) improvements in that condition. On the other hand, the amount of subsequent learning in low external noise conditions was essentially the same as the total (pre-training + subsequent) amount of improvements in high external noise, suggesting that pre-training in high external noise had mostly only improved performance in noisy displays. (4) Pre-training in zero external noise practically eliminated or left very little additional learning in all the external noise conditions. We concluded that the two mechanisms of perceptual learning, stimulus enhancement, and external noise exclusion, can be trained independently in motion direction discrimination in fovea; training in low noise suffices to improve observer performance over all the external noise conditions.

On the basis of results from behavioral studies that spatial attention improves the exclusion of external noise in the target region, we predicted that attending to a spatial region would reduce the impact of external noise on the BOLD response in corresponding cortical areas, seen as reduced BOLD responses in conditions with large amounts of external noise but relatively low signal, and increased dynamic range of the BOLD response to variations in signal contrast. We found that, in the presence of external noise, covert attention reduced the trial-by-trial BOLD response by 15.5–18.9% in low signal contrast conditions in V1. It also increased the BOLD dynamic range in V1, V2, V3, V3A/B, and V4 by a factor of at least three. Overall, covert attention reduced the impact of external noise by about 73–85% in these early visual areas. It also increased the contrast gain by a factor of 2.6–3.8.

Eye-transfer tests, external noise manipulations, and observer models were used to systematically characterize learning mechanisms in judging motion direction of moving objects in visual periphery (Experiment 1) and fovea (Experiment 2) and to investigate the degree of transfer of the learning mechanisms from trained to untrained eyes. Perceptual learning in one eye was measured over 10 practice sessions. Subsequent learning in the untrained eye was assessed in five transfer sessions. We characterized the magnitude of transfer of each learning mechanism to the untrained eye by separately analyzing the magnitude of subsequent learning in low and high external noise conditions. In both experiments, we found that learning in the trained eye reduced contrast thresholds uniformly across all of the external noise levels: 47 ؎ 10% and 62 ؎ 8% in experiments 1 and 2, respectively. Two mechanisms, stimulus enhancement and template retuning, accounted for the observed performance improvements. The degree of transfer to the untrained eye depended on the amount of external noise added to the signal stimuli: In high external noise conditions, learning transferred completely to the untrained eye in both experiments. In low external noise conditions, there was only partial transfer of learning: 63% in experiment 1 and 54% in experiment 2. The results suggest that template retuning, which is effective in high external noise conditions, is mostly binocular, whereas stimulus enhancement, which is effective in low external noise displays, is largely monocular. The two independent mechanisms underlie perceptual learning of motion direction identification in monocular and binocular motion systems. interocular transfer ͉ stimulus enhancement ͉ external noise exclusion ͉ mechanisms of perceptual learning