Noise improves three-dimensional perception: Stochastic resonance and other impacts of noise to the perception of autostereograms

Abstract

Autostereograms can be perceived in different well-defined spatial levels. Therefore they are an excellent tool with which to examine spatiotemporal processes of multistable three-dimensional perception. We study properties of spatial ambiguity such as phase transitions between different spatial levels and hysteresis in perception with and without noise. We show that the perception of physical noise-which is added to the autostereograms in the form of a random dot pattern-is dependent on the perceived spatial level. We demonstrate that noise can be helpful for the perception of depth in some cases. We show that the signal-to-noise ratio of depth perception is enhanced at an intermediate level of noise strength that is the signature of stochastic resonance in depth perception.

Fluctuations in Neuronal Synchronization in Brain Activity Correlate with the Subjective Experience of Visual Recognition

“…Our measurements, using an effective diffusion coefficient, are related to those using the more common measure of SR, the signal-to-noise ratio [8,21]. Considering that, in noisy systems like the brain, synchronization can be defined only in a statistical sense, as widely discussed in many articles and books [14,16,24,26], it is important to think in terms of fluctuations in synchrony, in addition to the more usual determination of the strength of the synchronization between brain regions.…”

“…We did not evaluate instantaneous phases past 42 Hz due to the limitations imposed by the sampling acquisition of our equipment and the requirements for a reliable interpretation of the operation done by the Hilbert transform [24]. This frequency range encompasses the most important physiological frequency bands, theta (4-8), alpha (8)(9)(10)(11)(12)(13)(14), beta (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29) and gamma (>30 Hz). To summarize, the D eff calculation runs as follows: for a specific set of MEG signals, in the frontal lobe for example, (depicted in Fig.…”

“…This concept can be extended to what can be termed psychophysical stochastic resonance (PSR), when there is improved sensory discrimination for certain noise levels [5]. For example, noise-enhanced sensorimotor discrimination in human subjects has been shown in several modalities [3,[6][7][8][9][10][11]; indications of stochastic resonance in the mammalian nervous system have been obtained using other preparations [12,13]. It should be noted that it is one thing to determine stochastic resonance occurring in the brain and another to study how the brain (perception) responds to stimuli constructed according to the principles of SR.…”

Nonlinear Systems for Image Processing

“…Detection of subthreshold signal using noise has been proven in neural information process (Longtin, 1993;Nozaki et al, 1999;Stocks and Manella, 2001) and in data transmission fields (Barbay, 2001;Zozor and Amblard, 2003;Morfu et al, 2003;Comte and Morfu, 2003;Duan and Abbott, 2005) as well as information transmission in array of such coupled stochastic resonator (Lindner et al, 1998;Chapeau-Blondeau, 1999;Báscones et al, 2002;Morfu, 2003). Recent studies have also shown that noise can enhance image perception (Simonotto et al, 1997;Moss et al, 2004), autostereograms interpretation (Ditzinger et al, 2000), visual perception via eyes micro-saccade in retina (Hongler et al, (a) (b) (c)…”

Noise-Enhanced Propagation in a Dissipative Chain of Triggers

“…and then the signal detection ]. This effect known as Stochastic Resonance (SR), since its introduction to explain the periodic recurrence of ice ages in climate dynamics [Benzi et al, 1981;Benzi et al, 1983;Nicolis, 1982], has been investigated in many fields ] like visual perception [Simonotto et al, 1997;Ditzinger et al, 2000] or biology [Longtin, 1993;Gebeshuber, 2000;Zeng et al, 2000]. This phenomenon has been studied first in unicellular nonlinear systems, like the Schmitt trigger [Fauve & Heslot, 1983;Melnikov, 1993;Godivier & Chapeau-Blondeau, 1997;Gammaitoni et al, 1999], and more recently, considering lattices of coupled excitable cells [Lindner et al, 1995;Zhang et al, 1998;Locher et al, 1998;Lindner et al, 1998;Chapeau-Blondeau, 1999;ChapeauBlondeau & Rojas-Varela, 2000].…”