Using the past to estimate sensory uncertainty.
Using the past to estimate sensory uncertainty.
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DOI：
10.7554/elife.54172
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发表时间：
2020-12-15
期刊：
影响因子：
7.7
通讯作者：
Noppeney U
中科院分区：
文献类型：
--
作者：
Beierholm U;Rohe T;Ferrari A;Stegle O;Noppeney U
为了形成一个更可靠的环境感知，大脑需要估计自己的感官不确定性。当前的知觉推理理论假设大脑会即时且独立地计算每个刺激的感觉不确定性。我们在四个心理物理实验中评估了这一假设，在这些实验中，人类观察者定位了与空间上不同的视觉信号同步呈现的听觉信号。重要的是，视觉噪声随时间连续或间歇跳跃地动态变化。我们的研究结果表明，观察员整合视听输入加权感官不确定性估计，联合收割机信息从过去和当前的信号一致的最佳贝叶斯学习，可以近似指数折扣。我们的研究结果挑战了知觉推理的主要模型，其中感官不确定性估计仅取决于当前的刺激。他们证明，大脑利用外部世界的时间动态，并通过将过去的经验与新传入的感官信号相结合来估计感官的不确定性。
To form a more reliable percept of the environment, the brain needs to estimate its own sensory uncertainty. Current theories of perceptual inference assume that the brain computes sensory uncertainty instantaneously and independently for each stimulus. We evaluated this assumption in four psychophysical experiments, in which human observers localized auditory signals that were presented synchronously with spatially disparate visual signals. Critically, the visual noise changed dynamically over time continuously or with intermittent jumps. Our results show that observers integrate audiovisual inputs weighted by sensory uncertainty estimates that combine information from past and current signals consistent with an optimal Bayesian learner that can be approximated by exponential discounting. Our results challenge leading models of perceptual inference where sensory uncertainty estimates depend only on the current stimulus. They demonstrate that the brain capitalizes on the temporal dynamics of the external world and estimates sensory uncertainty by combining past experiences with new incoming sensory signals.