Attention, uncertainty, and free-energy.
Attention, uncertainty, and free-energy.
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DOI：
10.3389/fnhum.2010.00215
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发表时间：
2010
影响因子：
2.9
通讯作者：
Friston KJ
中科院分区：
文献类型：
--
作者：
Feldman H;Friston KJ
我们最近提出，注意力可以被理解为在分层知觉过程中推断不确定性或精确度的水平。在这篇文章中，我们试图用定向空间注意和有偏见竞争的神经元模拟来证实这一说法。这些模拟假设神经元活动编码了以贝叶斯方式优化自由能的世界的概率表示。由于自由能边界给世界内部模型带来了惊喜或(负)对数证据，这种优化可以被视为证据积累或(广义)预测编码。至关重要的是，对产生感官数据的世界状态的预测和这些数据的精确度都必须优化。在这里，我们表明，如果精确度取决于状态，人们可以解释注意力的许多方面。我们在波斯纳范式的背景下说明了这一点，使用模拟来产生心理物理和电生理反应。这些模拟的反应与注意力偏向或门控、对注意力资源的竞争、注意力捕获以及相关的速度和准确性权衡是一致的。此外，如果我们同时呈现有注意和无注意的刺激，对神经元表征的有偏竞争就会成为贝叶斯最优知觉的一个原则性和直截了当的属性。
We suggested recently that attention can be understood as inferring the level of uncertainty or precision during hierarchical perception. In this paper, we try to substantiate this claim using neuronal simulations of directed spatial attention and biased competition. These simulations assume that neuronal activity encodes a probabilistic representation of the world that optimizes free-energy in a Bayesian fashion. Because free-energy bounds surprise or the (negative) log-evidence for internal models of the world, this optimization can be regarded as evidence accumulation or (generalized) predictive coding. Crucially, both predictions about the state of the world generating sensory data and the precision of those data have to be optimized. Here, we show that if the precision depends on the states, one can explain many aspects of attention. We illustrate this in the context of the Posner paradigm, using the simulations to generate both psychophysical and electrophysiological responses. These simulated responses are consistent with attentional bias or gating, competition for attentional resources, attentional capture and associated speed-accuracy trade-offs. Furthermore, if we present both attended and non-attended stimuli simultaneously, biased competition for neuronal representation emerges as a principled and straightforward property of Bayes-optimal perception.
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