This Feature Article is part of a series identified by the Editorial Board as reporting findings of exceptional significance.Edited by Terrence J. Sejnowski, Salk Institute for Biological Studies, La Jolla, CA, and approved August 8, 2014 (received for review February 22, 2014) Cognitive functions rely on the coordinated activity of neurons in many brain regions, but the interactions between cortical areas are not yet well understood. Here we investigated whether lowfrequency (α) and high-frequency (γ) oscillations characterize different directions of information flow in monkey visual cortex. We recorded from all layers of the primary visual cortex (V1) and found that γ-waves are initiated in input layer 4 and propagate to the deep and superficial layers of cortex, whereas α-waves propagate in the opposite direction. Simultaneous recordings from V1 and downstream area V4 confirmed that γ-and α-waves propagate in the feedforward and feedback direction, respectively. Microstimulation in V1 elicited γ-oscillations in V4, whereas microstimulation in V4 elicited α-oscillations in V1, thus providing causal evidence for the opposite propagation of these rhythms. Furthermore, blocking NMDA receptors, thought to be involved in feedback processing, suppressed α while boosting γ. These results provide new insights into the relation between brain rhythms and cognition.neuronal synchronization | attention | perceptual organization | phase coherence | Granger causality A reas of the visual cortex are arranged hierarchically, with low-level areas representing simple features and higher areas representing the more complex aspects of the visual world (1, 2). Neurons in many visual areas are coactive during the perception of a visual stimulus and it is difficult to disentangle the influences of lower areas onto higher areas from the effects that go in the opposite direction (3). Studies of visual cognition could benefit enormously from markers of cortical activity that distinguish between feedforward and feedback effects. One such putative marker is cortical oscillatory activity, because oscillations of different frequencies have been proposed to propagate either in feedforward or in the feedback direction (4, 5), but experimental evidence for this view is sparse (6).Low-frequency rhythms, like the α-rhythm-which is particularly pronounced in the visual cortex-have been proposed to characterize spontaneous activity (7,8) as the α-rhythm increases when the subject closes the eyes (9). More recent observations have also implicated α-oscillations in the active suppression of irrelevant, unattended information (10, 11). In contrast, the high-frequency γ-rhythm increases if visual stimuli are presented, and in particular if they are task-relevant (12, 13). One influential hypothesis has been that γ-oscillations play a role in feature binding (14), but later studies cast doubt on this proposal (15,16). A more recent hypothesis holds that γ-oscillations facilitate the communication between cortical areas (17), but both evidence in fa...

Stimuli associated with high rewards evoke stronger neuronal activity than stimuli associated with lower rewards in many brain regions. It is not well understood how these reward effects influence activity in sensory cortices that represent low-level stimulus features. Here, we investigated the effects of reward information in the primary visual cortex (area V1) of monkeys. We found that the reward value of a stimulus relative to the value of other stimuli is a good predictor of V1 activity. Relative value biases the competition between stimuli, just as has been shown for selective attention. The neuronal latency of this reward value effect in V1 was similar to the latency of attentional influences. Moreover, V1 neurons with a strong value effect also exhibited a strong attention effect, which implies that relative value and top-down attention engage overlapping, if not identical, neuronal selection mechanisms. Our findings demonstrate that the effects of reward value reach down to the earliest sensory processing levels of the cerebral cortex and imply that theories about the effects of reward coding and top-down attention on visual representations should be unified.object-based attention | reward expectancy R eward and punishment shape behavior. The representations of actual and anticipated rewards in the brain are widespread and multifaceted (1-4). There are many brain areas that code the value, taste, and other perceptual qualities of incentive stimuli (5-14). Furthermore, rewards are motivating. Motivational effects influence neuronal activity in brain structures responsible for goal-directed behavior in cortex, in the basal ganglia, and also at the level of the superior colliculus where neurons increase their activity if larger rewards can be obtained (1,3,9,(15)(16)(17)(18)(19). Finally, rewards influence the choice of an animal (20,21). If different stimuli are associated with distinct rewards, then it is optimal to choose the one with the highest expected value (22,23). Neurons in the parietal and orbitofrontal cortex and also in the basal ganglia increase their activity for those stimuli that predict rewards that are larger or more probable (21,22,(24)(25)(26).Intriguingly, reward value also influences neuronal activity in early visual cortex. Shuler and Bear (27) demonstrated that neurons in rat primary visual cortex predict the timing of reward delivery, even in a phase of the task when the cells are not driven by a visual stimulus. This result is remarkable because primary visual cortex (V1) neurons are usually thought to code low-level visual features rather than stimulus value. Moreover, a functional magnetic resonance imaging (fMRI) study by Serences (28) demonstrated that reward value also influences V1 activity in humans. Subjects chose between two stimuli, and the one that was more rewarding evoked more activity. Apparently, the effects of reward value can reach back to the earliest cortical processing levels, where they might influence the coding of low-level features. However, the precise me...

When stimulus information enters the visual cortex, it is rapidly processed for identification. However, sometimes the processing of the stimulus is inadequate and the subject fails to notice the stimulus. Human psychophysical studies show that this occurs during states of inattention or absent-mindedness. At a neurophysiological level, it remains unclear what these states are. To study the role of cortical state in perception, we analyzed neural activity in the monkey primary visual cortex before the appearance of a stimulus. We show that, before the appearance of a reported stimulus, neural activity was stronger and more correlated than for a not-reported stimulus. This indicates that the strength of neural activity and the functional connectivity between neurons in the primary visual cortex participate in the perceptual processing of stimulus information. Thus, to detect a stimulus, the visual cortex needs to be in an appropriate state.