Neural synchrony in stochastic resonance, attention, and consciousness.

We describe briefly three of our lab's ongoing projects studying the role of neural synchrony in human perception and cognition. These projects arise from two main interests: the role of noise both in human perception and in neural synchrony, and neural synchrony as a basis for integration of functional modules in the brain. Our experimental work on these topics began with a study of the possibility that noise-influenced neural synchrony might be responsible for the fact that small amounts of noise added to weak signals can enhance their detectability (stochastic resonance). We are also studying the role of neural synchrony in attention and consciousness in several paradigms. On the basis of our own and related work by others, we conclude that (1) neural synchrony plays an important role in the integration of functional modules in the brain and (2) neural synchrony is profoundly affected and possibly regulated, in part, by the "noisiness" of the brain. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于周期势系统随机共振的轴承故障诊断

提出基于普通变尺度和周期势自适应随机共振理论,检测噪声背景下轴承滚动体的故障特征.在具体实施过程中,首先用普通变尺度的方法满足随机共振中小参数的条件,然后用随机权重粒子群优化算法作为自适应随机共振参数寻优的优化算法,同时用改进的信噪比作为评价指标.噪声背景下含轴承滚动体故障的实验信号经过普通变尺度下的自适应随机共振处理和优化后,微弱的故障特征可以有效的提取出来.将普通变尺度下的双稳态自适应随机共振和周期势自适应随机共振进行了对比,结果表明周期势自适应随机共振比双稳态自适应随机共振能进一步提高信噪比,并且比双稳态自适应随机共振迭代次数少,用时短.这说明提出的基于普通变尺度和周期势系统自适应随机共振的轴承滚动体故障诊断方法具有优越性,尤其是在工程实际中,故障监测所需的数据量大,计算时间长,如能较早的预警,可以提高诊断效率并减少不必要的损失.因此,这种轴承滚动体故障诊断方法对提高机械设备故障诊断效率具有参考价值.     

Noise-enhanced information transmission in rat SA1 cutaneous mechanoreceptors via aperiodic stochastic resonance

1. Aperiodic stochastic resonance (ASR) is a phenomenon wherein the response of a nonlinear system to a weak aperiodic input signal is optimized by the presence of a particular, nonzero level of noise. Our objective was to demonstrate ASR experimentally in mammalian cutaneous mechanoreceptors. 2. Experiments were performed on rat slowly adapting type 1 (SA1) afferents. Each neuron was subjected to a perithreshold aperiodic stimulus plus noise. The variance of the noise was varied between trials. The coherence between the aperiodic input stimulus and the response of each SA1 afferent was computed. 3. Of the 12 neurons tested, 11 showed clear ASR behavior: as input noise variance was increased, the stimulus-response coherence rapidly increased to a peak and then slowly decreased. These findings were in contrast with those for the average firing rate, which increased monotonically as a function of input noise variance. 4. This work shows that noise can serve to enhance the response of a sensory neuron to a perithreshold aperiodic input signal. These results suggest a possible functional role for input noise in sensory systems. These findings also indicate that it may be possible to introduce noise artificially into sensory neurons to improve their abilities to detect arbitrary weak signals.