Department of Neuroscience,University of Pittsburgh, Pittsburgh, United States.
Center for the Neural Basis of Cognition, Pittsburgh, United States.
Elife. 2022 Jun 6;11:e67258. doi: 10.7554/eLife.67258.
Improvements in perception are frequently accompanied by decreases in correlated variability in sensory cortex. This relationship is puzzling because overall changes in correlated variability should minimally affect optimal information coding. We hypothesize that this relationship arises because instead of using optimal strategies for decoding the specific stimuli at hand, observers prioritize : a single set of neuronal weights to decode any stimuli. We tested this using a combination of multineuron recordings in the visual cortex of behaving rhesus monkeys and a cortical circuit model. We found that general decoders optimized for broad rather than narrow sets of visual stimuli better matched the animals' decoding strategy, and that their performance was more related to the magnitude of correlated variability. In conclusion, the inverse relationship between perceptual performance and correlated variability can be explained by observers using a general decoding strategy, capable of decoding neuronal responses to the variety of stimuli encountered in natural vision.
感知能力的提高通常伴随着感觉皮层中相关变异性的降低。这种关系令人费解，因为相关变异性的总体变化应该最小化地影响最优信息编码。我们假设这种关系的出现是因为观察者不是使用最优策略来解码手头的特定刺激，而是优先选择：一组神经元权重来解码任何刺激。我们使用行为恒河猴视觉皮层中的多神经元记录和皮质电路模型对此进行了测试。我们发现，针对广泛而非狭窄的视觉刺激进行优化的通用解码器更符合动物的解码策略，并且其性能与相关变异性的大小更相关。总之，感知表现和相关变异性之间的反比关系可以通过观察者使用通用解码策略来解释，该策略能够解码神经元对自然视觉中遇到的各种刺激的反应。
