Topic: stimulus identity

Neural activity in visual cortex is well described by models composed of a deterministic tuning function, a stochastic gain, and a point process. Recent work has shown that in the responses of neurons in the visual cortex of nonhuman primates, variability in the gain is tuned to the statistics of the sensory input. This suggests that gain variability may reflect signal rather than noise. Some theories of neural coding suggest that perceptual uncertainty may be encoded in neural response variability, and that, specifically, gain variability appears well suited to inform downstream uncertainty e

Neural representations of statistical probability and uncertainty are critical for brain function and behavior (Ma and Jazayeri 2014), and it is particularly important that the brain learn temporal relationships since they can infer causation and allow predictions about future events. Influential models assume this information is available in the brain, but many details are speculative and direct evidence remains elusive. Multiple labs (Bear, Berry, Buonomano, Buschman, Carandini, Fiser, Gavornik, Hawkins, Keller, Mrsic-Flogel, Hussain Shuler, Shouval) have demonstrated that primary visual c

The brain’s limited information processing capacity leads to competition among concurrent inputs at the neuronal level. Selective attention is a cognitive process that resolves this competition by filtering out irrelevant sensory information while enhancing the neural representation of relevant stimuli. This phenomenon is well-explained by the theory of biased competition, which posits that attention biases neural processing towards behaviorally relevant stimuli when multiple objects are present. However, the mechanism of attention remains under debate. We show how biased competition can be so

The brain’s limited information processing capacity leads to competition among concurrent inputs at the neuronal level. Selective attention is a cognitive process that resolves this competition by filtering out irrelevant sensory information while enhancing the neural representation of relevant stimuli. This phenomenon is well-explained by the theory of biased competition, which posits that attention biases neural processing towards relevant stimuli when multiple objects are present. However, the mechanism of attention remains under debate. We show how biased competition can be solved in a bio