We discuss the relationship of endogenous neural noise (ENN) to performance of behavioral tasks and to information
processing in the brain. Spontaneous neural activity is closely linked to development and perception, and is correlated
with behavior. Some of this activity is probably related to internal processing of task- and goal-relevant information, but
some is simply noise. Two previous studies have reported correlations between performance on behavioral tasks and
measures of neural noise and have characterized these relationships as intrinsic stochastic resonance (SR). We argue that
neither of these studies demonstrated intrinsic SR, and discuss several alternative ways of measuring ENN in humans
from EEG or MEG records. Using one of these, random-phase power in the 30-50 Hz range 1 sec before the onset of the
signal, we demonstrate a kind of intrinsic SR that optimizes detection of weak visual signals. Minimum response time
was obtained when this EEG measure of ENN was in a middle decile. No other measure of ENN was related either to
response time or to an unbiased measure of detection accuracy (e.g., d'). A discussion of the implications of these
findings for the study of intrinsic SR concludes the paper.
We demonstrate experimentally that the human brain can make use of externally added noise to modulate attention switching between spatial locations. To do this we implemented a psychophysical task. Subjects were asked to respond to a weak gray-level target presented inside a marker box either in the left or right visual field while they fixated a central cross. Signal detection performance was improved by presenting a low level of randomly flickering gray-level noise between and outside the two possible target locations, and worsened by higher levels of noise. Our results suggest that noise can optimize switching behavior between multistable attentional states of the human brain via the mechanism of stochastic resonance.
We demonstrate experimentally that enhanced detection of weak visual signals by addition of visual noise is accompanied by an increase in phase synchronization of EEG signals across widely-separated areas of the human brain. In our sensorimotor integration task, observers responded to a weak rectangular gray-level signal presented to their right eyes by pressing and releasing a button whenever they detected an increment followed by a decrement in brightness. Signal detection performance was optimized by presenting randomly-changing-gray-level noise separately to observers' left eyes using a mirror stereoscope. We measured brain electrical activity at the scalp by electroencephalograph (EEG), calculated the instantaneous phase for each EEG signal, and evaluated the degree of large-scale phase synchronization between pairs of EEG signals. Dynamic synchronization-desynchronization patterns were observed and we found evidence of noise-enhanced large-scale synchronization associated with detection of the brightness changes under conditions of noise-enhanced performance. Our results suggest that behavioral stochastic resonance might arise from noise-enhanced synchronization of neural activities across widespread brain regions.
We report the results of two psychophysics experiments showing that the human brain can make use of externally added noise for behavioral responses. Subjects were instructed to respond to changing gray level signals presented to their right eye. The behavioral responses were optimized by presenting randomly changing gray level noise to their left eye. The results indicate that the behavioral stochastic resonance occurs at the cortical level where information from both eyes merges together.