Although many studies have shown that the activity of individual neurons in a variety of visual areas is modulated by attention, a fundamental question remains unresolved: can attention alter the visual representations of individual neurons? One set of studies, primarily relying on the attentional modulations observed when a single stimulus is presented within the receptive field of a neuron, suggests that neuronal selectivities, such as orientation or direction tuning, are not fundamentally altered by attention (Salinas and Abbott, 1997; McAdams and Maunsell, 1999; Treue and Martinez Trujillo, 1999). Another set of studies, relying on modulations observed when multiple stimuli are presented within a receptive field, suggests that attention can alter the weighting of sensory inputs (Moran and Desimone, 1985; Luck et al., 1997; Reynolds et al., 1999; Chelazzi et al., 2001). In these studies, when preferred and nonpreferred stimuli are simultaneously presented, responses are much stronger when attention is directed to the preferred stimulus than when it is directed to the nonpreferred stimulus. In this study, we recorded neuronal responses from individual neurons in visual cortical area V4 to both single and paired stimuli with a variety of attentional allocations and stimulus combinations. For each neuron studied, we constructed a quantitative model of input summation and then tested various models of attention. In many neurons, we are able to explain neuronal responses across the entire range of stimuli and attentional allocations tested. Specifically, we are able to reconcile seemingly inconsistent observations of single and paired stimuli attentional modulation with a new model in which attention can facilitate or suppress specific inputs to a neuron but does not fundamentally alter the integration of these inputs.

We investigated whether synchrony between neuronal spike trains is affected by the animal's attentional state. Cross-correlation functions between pairs of spike trains in the second somatosensory cortex (SII) of three macaque monkeys trained to switch attention between a visual task and a tactile task were computed. We previously showed that the majority of recorded neuron pairs (66%) in SII cortex fire synchronously while the animals performed either task and that in a subset of neuron pairs (17%), the degree of synchrony was affected by the animal's attentional state. Of the neuron pairs that showed changes in synchrony with attention, about 80% showed increased synchrony when the animal attended to the tactile stimulus. Here, we show that peak correlation typically occurred at a delay <25 ms; most commonly the delay was close to zero. Half-widths of the correlation peaks were distributed between a few milliseconds and hundreds of milliseconds, with the majority lying <100 ms and the mode of the distribution around 20–30 ms. Maximal change in synchrony occurred mainly during the periods when the stimulus was present, and synchrony usually increased when attention was on the tactile stimulus. If periods of elevated firing rates around the motor response times were removed from the analysis, the percentage of pairs that changed the degree of synchrony with attention more than doubled (from 35 to 72%). The observed effects did not depend on details of the statistical criteria or of the time window used in the analysis.

Attention can selectively enhance neuronal responses and exclude external noise, but the neuronal computations that underlie these effects remain unknown. At the neuronal level, noise exclusion might result in altered spatial integration properties. We tested this proposal by recording neuronal activity and length tuning in neurons of the primary visual cortex of the macaque when attention was directed toward or away from stimuli presented in each neuron's classical receptive field. For cells with central-parafoveal receptive fields, attention reduced spatial integration, as demonstrated by a reduction in preferred stimulus length and in the size of the spatial summation area. Conversely, in cells that represented more peripheral locations, attention increased spatial integration by increasing the cell's summation area. This previously unknown dichotomy between central and peripheral vision could support accurate analysis of attended foveal objects and target selection for impending eye movements to peripheral objects.

Attention depends on figure-ground organization: figures draw attention, whereas shapes of the ground tend to be ignored. Recent research has revealed mechanisms for figure-ground organization in the visual cortex, but how these mechanisms relate to the attention process remains unclear. Here we show that the influences of figure-ground organization and volitional (top-down) attention converge in single neurons of area V2 in Macaca mulatta. Although we found assignment of border ownership for attended and for ignored figures, attentional modulation was stronger when the attended figure was located on the neuron's preferred side of border ownership. When the border between two overlapping figures was placed in the receptive field, responses depended on the side of attention, and enhancement was generally found on the neuron's preferred side of border ownership. This correlation suggests that the neural network that creates figure-ground organization also provides the interface for the top-down selection process.

The human brain is not a passive organ simply waiting to be activated by external stimuli. Instead, we propose that the brain continuously employs memory of past experiences to interpret sensory information and predict the immediately relevant future. The basic elements of this proposal include analogical mapping, associative representations and the generation of predictions. This review concentrates on visual recognition as the model system for developing and testing ideas about the role and mechanisms of top-down predictions in the brain. We cover relevant behavioral, computational and neural aspects, explore links to emotion and action preparation, and consider clinical implications for schizophrenia and dyslexia. We then discuss the extension of the general principles of this proposal to other cognitive domains.

The effects of attention on neuronal responses in visual cortex have been likened to a change in stimulus contrast. Attention and stimulus contrast both modulate the magnitude of neuronal responses. However, changes in stimulus contrast also affect the latency of visual responses. Although many neurophysiological studies have examined how attention affects the strength of neuronal responses, few have considered whether attention affects neuronal latencies. To compare directly the effects of stimulus contrast and attention, we recorded responses from individual neurons in area V4 of macaque monkeys while they performed a task that independently controlled spatial attention and stimulus contrast. As expected, changes in stimulus contrast affected both the magnitude and latency of neuronal responses. Although attention had the expected effects on the magnitudes of neuronal responses, we did not detect statistically reliable changes in neuronal latency. A direct comparison of the effects of contrast and attention revealed a reliable difference. When a shift in spatial attention decreased response magnitude, response latency increased much less than when the same magnitude change was caused by reducing stimulus contrast. Thus, attention is distinct from contrast in the way it affects the relationship between neuronal response magnitude and latency.

A mechanistic understanding of attention is necessary for the elucidation of the neurobiological basis of conscious experience. This chapter presents a framework for thinking about attention that facilitates the analysis of this cognitive process in terms of underlying neural mechanisms. Four processes are fundamental to attention: working memory, top-down sensitivity control, competitive selection, and automatic bottom-up filtering for salient stimuli. Each process makes a distinct and essential contribution to attention. Voluntary control of attention involves the first three processes (working memory, top-down sensitivity control, and competitive selection) operating in a recurrent loop. Recent results from neurobiological research on attention are discussed within this framework.

How does feature-based attention modulate neural responses? We used adaptation to quantify the effect of feature-based attention on orientation-selective responses in human visual cortex. Observers were adapted to two superimposed oblique gratings while attending to one grating only. We measured the magnitude of attention-induced orientation-selective adaptation both psychophysically, by the behavioral tilt aftereffect, and physiologically, using fMRI response adaptation. We found evidence for orientation-selective attentional modulation of neuronal responses-a lower fMRI response for the attended than the unattended orientation-in multiple visual areas, and a significant correlation between the magnitude of the tilt aftereffect and that of fMRI response adaptation in V1, the earliest site of orientation coding. These results show that feature-based attention can selectively increase the response of neuronal subpopulations that prefer the attended feature, even when the attended and unattended features are coded in the same visual areas and share the same retinotopic location.

During binocular rivalry, physical stimulation is dissociated from conscious visual awareness. Human brain imaging reveals a tight linkage between the neural events in human primary visual cortex (V1) and the dynamics of perceptual waves during transitions in dominance during binocular rivalry. Here, we report results from experiments in which observers' attention was diverted from the rival stimuli, implying that: competition between two rival stimuli involves neural circuits in V1, and attention is crucial for the consequences of this neural competition to advance to higher visual areas and promote perceptual waves.

Attention helps us process potentially important objects by selectively increasing the activity of sensory neurons that represent the relevant locations and features of our environment. This selection process requires top-down feedback about what is important in our environment. We investigated how parietal cortical output influences neural activity in early sensory areas. Neural recordings were made simultaneously from the posterior parietal cortex and an earlier area in the visual pathway, the medial temporal area, of macaques performing a visual matching task. When the monkey selectively attended to a location, the timing of activities in the two regions became synchronized, with the parietal cortex leading the medial temporal area. Parietal neurons may thus selectively increase activity in earlier sensory areas to enable focused spatial attention.