Single neurons can signal subtle changes in the sensory environment with surprising fidelity, often matching the perceptual sensitivity of trained psychophysical observers. This similarity poses an intriguing puzzle: why is psychophysical sensitivity not greater than that of single neurons? Pooling responses across neurons should average out noise in the activity of single cells, leading to substantially improved psychophysical performance. If, however, noise is correlated among these neurons, the beneficial effects of pooling would be diminished. To assess correlation within a pool, the responses of pairs of neurons were recorded simultaneously during repeated stimulus presentations. We report here that the observed covariation in spike count was relatively weak, the correlation coefficient averaging 0.12. A theoretical analysis revealed, however, that weak correlation can limit substantially the signalling capacity of the pool. In addition, theory suggests a relationship between neuronal responses and psychophysical decisions which may prove useful for identifying cell populations underlying specific perceptual capacities.

Natural scenes typically contain multiple objects that are unique in different stimulus dimensions so that an object with feature contrast to surrounding objects draws attention and pops out. Furthermore, if we have previous knowledge about the dimension in which a target object differs from the surrounding objects, we will attend to that dimension and more easily detect the target. Our aims here were to elucidate neural mechanisms underlying this type of attention by recording neuronal activities from area V4 and to investigate how visual signals encoding feature contrast between objects are modulated by attention specific to a particular dimension. To accomplish this, we trained monkeys to do a multidimensional visual search task in which two singleton stimuli, unique in the color or shape dimension, were presented with four other identical stimuli. The monkeys had to search for the singleton stimulus that was unique in the instructed dimension while the search dimension was switched between shape and color. We found that individual V4 neurons carry visual signals encoding feature contrast in either shape or color, and this signal is modulated depending on the search dimension. Population responses to the target singleton stimulus were significantly higher than to others, regardless of the search dimension. In most V4 neurons, however, significant response increases occurred only when one particular singleton stimulus was the target. These findings suggest that interaction between bottom-up signals encoding feature contrast between stimuli and top-down signals encoding search dimension occurs in V4 and facilitates adaptive selection of targets in a complex visual environment.

Several decades of psychophysical and neurophysiological studies have established that visual signals are enhanced at the locus of attention. What remains a mystery is the mechanism that initiates biases in the strength of visual representations. Recent evidence argues that, during spatial attention, these biases reflect nascent saccadic eye movement commands. We examined the functional interaction of saccade preparation and visual coding by electrically stimulating sites within the frontal eye fields (FEF) and measuring its effect on the activity of neurons in extrastriate visual cortex. Here we show that visual responses in area V4 could be enhanced after brief stimulation of retinotopically corresponding sites within the FEF using currents below that needed to evoke saccades. The magnitude of the enhancement depended on the effectiveness of receptive field stimuli as well as on the presence of competing stimuli outside the receptive field. Stimulation of non-corresponding FEF representations could suppress V4 responses. The results suggest that the gain of visual signals is modified according to the strength of spatially corresponding eye movement commands.

To find a target object in a crowded scene, a face in a crowd for example, the visual system might turn the neural representation of each object on and off in a serial fashion, testing each representation against a template of the target item. Alternatively, it might allow the processing of all objects in parallel but bias activity in favor of those neurons that represent critical features of the target, until the target emerges from the background. To test these possibilities, we recorded neurons in area V4 of monkeys freely scanning a complex array to find a target defined by color, shape, or both. Throughout the period of searching, neurons gave enhanced responses and synchronized their activity in the gamma range whenever a preferred stimulus in their receptive field matched a feature of the target, as predicted by parallel models. Neurons also gave enhanced responses to candidate targets that were selected for saccades, or foveation, reflecting a serial component of visual search. Thus, serial and parallel mechanisms of response enhancement and neural synchrony work together to identify objects in a scene. To find a target object in a crowded scene, a face in a crowd for example, the visual system might turn the neural representation of each object on and off in a serial fashion, testing each representation against a template of the target item. Alternatively, it might allow the processing of all objects in parallel but bias activity in favor of those neurons that represent critical features of the target, until the target emerges from the background. To test these possibilities, we recorded neurons in area V4 of monkeys freely scanning a complex array to find a target defined by color, shape, or both. Throughout the period of searching, neurons gave enhanced responses and synchronized their activity in the gamma range whenever a preferred stimulus in their receptive field matched a feature of the target, as predicted by parallel models. Neurons also gave enhanced responses to candidate targets that were selected for saccades, or foveation, reflecting a serial component of visual search. Thus, serial and parallel mechanisms of response enhancement and neural synchrony work together to identify objects in a scene.