A unified selection signal for attention and reward in primary visual cortex

Abstract

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...

Motivational Salience Modulates Early Visual Cortex Responses across Task Sets

“…Indeed, our data demonstrate that punishment can induce sensitivity for low-level stimulus features in early sensory cortex, as previously shown for high rewards (Stanisor et al, 2013) in a way that new stimuli that share those features will also benefit from enhanced sensory processing in V1. However, Our data do not allow to specify the exact stimulus feature(s) for which this plasticity occurred.…”

“…First, the task parameters could account for this unexpected finding, which might be partly due to the presentation of stimuli in isolation (i.e., neutral and rewarded stimuli are not presented simultaneously), while most effects of reward on sensory processing have been observed in competitive contexts (e.g., Serences, 2008), where prioritization effects are obviously maximized. Furthermore, given that the recognition task heavily depended on feature-based attention, the influence of reward might have been overshadowed by the effects of voluntary feature-based attention allocation on early visual processing (Lee and Shomstein, 2013;Stanisor et al, 2013), that was presumably set to perform the task. Second, it is also possible that the use of monetary reinforcers might have played a role in the divergence between learning speed and neural changes in early visual cortex.…”

Neuronal Reward and Decision Signals: From Theories to Data

“…Amygdala neurons initially detect a visual stimulus and may code its identity and then transition within 60 -300 ms to differential reward value coding (9,422,428). V1 and inferotemporal cortex responses show initial visual stimulus selectivity and only 50 -90 ms later distinguish reward values (371,557). Thus there is a sequence in the processing of external events that advances from initial detection via identification to valuation.…”

How motivation and reward learning modulate selective attention

“…One study in monkeys found that V1 neurons with a strong value effect also exhibited a strong attention effect, suggesting overlap between relative value and top-down attention (Stanisor et al, 2013). Interestingly, Baruni and collaborators (2015) conducted a study in monkeys in order to differentiate reward expectation from attentional source of modulation in visual area V4.…”