Bistable perception modeled as competing stochastic integrations at two levels.
Bistable perception modeled as competing stochastic integrations at two levels.
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DOI：
10.1371/journal.pcbi.1000430
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发表时间：
2009-07
影响因子：
4.3
通讯作者：
Del Giudice P
中科院分区：
文献类型：
--
作者：
Gigante G;Mattia M;Braun J;Del Giudice P
我们对双稳态知觉提出了一种新的解释，即多个神经元群体的集体动力学是单独亚稳态的。在这些群体中，感觉输入和知觉状态的分布式表征通过噪声驱动的转换逐渐建立，直到替代表征之间的竞争通过阈值机制解决。这种集体竞相达到门槛的无休止重复，使得人们的看法变得双稳。这种集体动力--在很大程度上与支配个体群体或神经元的时间尺度无关--解释了许多迄今令人费解的关于双稳知觉的观察：双稳现象表现出的平均更改率的广泛范围，连续主导期的一致可变性，以及过去知觉状态的稳定效应。它还预测了表征双稳知觉的可观测量之间的一些以前未被怀疑的关系。我们的结论是，双稳态知觉反映了神经决策的集体性质，而不是单个群体或神经元的属性。知觉的不稳定性是神经科学中最古老的谜题之一。当视觉刺激甚至是轻微的模棱两可时，知觉体验就不能稳定下来，在不同的状态之间永远交替。这种“双稳感知”的细节已经被广泛研究了几十年。在这里，我们提出双稳态知觉在两个神经表征水平上反映了许多亚稳态群体上的随机积分。虽然以前对双稳感知的描述依赖于振荡动力学，但我们的模型本质上是随机的。我们认为，波动驱动的过程自然解释了几十年来一直令人困惑的双稳态认知的关键特征。例如，我们的模型首次解释了为什么连续主导期的统计变异性基本保持不变，而双稳现象的平均交替率在两个数量级以上。通过假设分别由刺激和知觉状态驱动的两个水平的表征，我们的模型进一步解释了过去知觉状态的稳定影响，这在间歇性显示中尤为明显。一般而言，波动驱动的过程将双稳态感知的集体动力学与单个神经元的属性分离，并预测了行为可观察测量之间迄今未被怀疑的一些关系。
We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics – which is largely uncoupled from the time-scales that govern individual populations or neurons – explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons. The instability of perception is one of the oldest puzzles in neuroscience. When visual stimulation is even slightly ambiguous, perceptual experience fails to stabilize and alternates perpetually between distinct states. The details of this ‘bistable perception’ have been studied extensively for decades. Here we propose that bistable perception reflects the stochastic integration over many meta-stable populations at two levels of neural representation. While previous accounts of bistable perception rely on an oscillatory dynamic, our model is inherently stochastic. We argue that a fluctuation-driven process accounts naturally for key characteristics of bistable perception that have remained puzzling for decades. For example, our model is the first to explain why the statistical variability of successive dominance periods remains essentially the same, while the mean alternation rates of bistable phenomena range over two orders of magnitude. By postulating two levels of representation that are driven by stimulation and by perceptual state, respectively, our model further accounts for the stabilizing influence of past perceptual states, which are particularly evident in intermittent displays. In general, a fluctuation-driven process decouples the collective dynamics of bistable perception from single-neuron properties and predicts a number of hitherto unsuspected relations between behaviorally observable measures.
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DOI：
10.1007/bf00290512
发表时间：
1972-01-01
期刊：
KYBERNETIK
影响因子：
--
作者：
BORSELLINO, A;ALLAZETTA, A;DEMARCO, A
通讯作者：
DEMARCO, A
影响因子：
1.8
作者：
Kim, YJ;Grabowecky, M;Suzuki, S
通讯作者：
Suzuki, S
影响因子：
2.9
作者：
Dayan, P
通讯作者：
Dayan, P
影响因子：
1.3
作者：
Kang, David C.
通讯作者：
Kang, David C.
影响因子：
2.5
作者：
Freeman, AW
通讯作者：
Freeman, AW