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Ubiquitous crossmodal Stochastic Resonance in humans: auditory noise facilitates tactile, visual and proprioceptive sensations.

Lugo E, Doti R, Faubert J - PLoS ONE (2008)

Bottom Line: Specifically, we show that the effective auditory noise significantly increased tactile sensations of the finger, decreased luminance and contrast visual thresholds and significantly changed EMG recordings of the leg muscles during posture maintenance.We conclude that crossmodal SR is a ubiquitous phenomenon in humans that can be interpreted within an energy and frequency model of multisensory neurons spontaneous activity.The result is an integrated activation that promotes sensitivity transitions and the signals are then perceived.

View Article: PubMed Central - PubMed

Affiliation: Visual Psychophysics and Perception Laboratory, School of Optometry, University of Montreal, Montreal, Quebec, Canada.

ABSTRACT

Background: Stochastic resonance is a nonlinear phenomenon whereby the addition of noise can improve the detection of weak stimuli. An optimal amount of added noise results in the maximum enhancement, whereas further increases in noise intensity only degrade detection or information content. The phenomenon does not occur in linear systems, where the addition of noise to either the system or the stimulus only degrades the signal quality. Stochastic Resonance (SR) has been extensively studied in different physical systems. It has been extended to human sensory systems where it can be classified as unimodal, central, behavioral and recently crossmodal. However what has not been explored is the extension of this crossmodal SR in humans. For instance, if under the same auditory noise conditions the crossmodal SR persists among different sensory systems.

Methodology/principal findings: Using physiological and psychophysical techniques we demonstrate that the same auditory noise can enhance the sensitivity of tactile, visual and propioceptive system responses to weak signals. Specifically, we show that the effective auditory noise significantly increased tactile sensations of the finger, decreased luminance and contrast visual thresholds and significantly changed EMG recordings of the leg muscles during posture maintenance.

Conclusions/significance: We conclude that crossmodal SR is a ubiquitous phenomenon in humans that can be interpreted within an energy and frequency model of multisensory neurons spontaneous activity. Initially the energy and frequency content of the multisensory neurons' activity (supplied by the weak signals) is not enough to be detected but when the auditory noise enters the brain, it generates a general activation among multisensory neurons of different regions, modifying their original activity. The result is an integrated activation that promotes sensitivity transitions and the signals are then perceived. A physiologically plausible model for crossmodal stochastic resonance is presented.

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Theoretical model results for unimodal SR.(Left column) shows the neurons' spectrum amplitude as a function of the noise intensity σ−. The insert (left column, middle row) shows the well-known SR inverted u-shape function. The maximum peak is found when P = 10 dB. Right column shows neuronal firing histograms with their corresponding time histories. T is the signal period and N means the probability to have certain neuronal activity levels.
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pone-0002860-g006: Theoretical model results for unimodal SR.(Left column) shows the neurons' spectrum amplitude as a function of the noise intensity σ−. The insert (left column, middle row) shows the well-known SR inverted u-shape function. The maximum peak is found when P = 10 dB. Right column shows neuronal firing histograms with their corresponding time histories. T is the signal period and N means the probability to have certain neuronal activity levels.

Mentions: For unimodal SR neurons, the signal (harmonic term in equation 1) and the noise are present in the same region x≤0. In this case the inherent system perturbation is defined by parameter values ε−>0 for x≤0 and ε+ = 0 for x>0. Hence, in order to calculate the neuron's firing necessary condition, we only have to take in account the homoclinic orbit Γ− and parameters associated with this region. Substituting equation (11) and equation (10), for Γ−, into equation (5) and then working out the integrals, the necessary condition for the escapes to take place is(14)where is known as the Melnikov scale factor, shown in figure 5 (bottom) where is clear that if we want to optimize the energy transfer from the stochastic process G(t) then its spectral density needs to contain frequencies around the Melnikov scale factor maximum. The necessary escape condition (equation 14) serves to calculate the required noise amplitude σ−, for neuron firings and the mean escape rate equation gives us the condition to observe the SR peak in neurons. Figure 6 shows some simulations for the behavior of neuronal activity with different noise amplitudes. The parameters we used are ε− = 1 γ− = 0.095, β− = 0.316, α+ = 49, α− = 1, ω0 = 0.6283 (0.1 Hz), N = 500, c = 0.02, and ωcut = 3. In all the simulations we have performed over 200 noise realizations approximated by equation G(t) and then averaged. The left column in figure 6 shows the neurons spectrum amplitude as a function of the noise intensity σ−. As it would be expected for low noise intensities the energy transfer from the noise to the signal is not enough to achieve the synchronization and as a result the spontaneous activity dominates and no firings occur. However as the noise intensity increases firings also increase up to a maximum peak, where the mean escape rate approximately equals the signal frequency. Beyond this point, random firings can occur at different frequencies meaning that the synchronized energy transfer from the noise to the signal is destroyed and the signal is embedded in the spontaneous activity. The insert (left column, middle row) shows the well known SR inverse u-shape function, the maximum peak is found when P = 10 dB. Right column in figure 6, shows neuron's firings histograms with their correspondent time histories.


Ubiquitous crossmodal Stochastic Resonance in humans: auditory noise facilitates tactile, visual and proprioceptive sensations.

Lugo E, Doti R, Faubert J - PLoS ONE (2008)

Theoretical model results for unimodal SR.(Left column) shows the neurons' spectrum amplitude as a function of the noise intensity σ−. The insert (left column, middle row) shows the well-known SR inverted u-shape function. The maximum peak is found when P = 10 dB. Right column shows neuronal firing histograms with their corresponding time histories. T is the signal period and N means the probability to have certain neuronal activity levels.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2481403&req=5

pone-0002860-g006: Theoretical model results for unimodal SR.(Left column) shows the neurons' spectrum amplitude as a function of the noise intensity σ−. The insert (left column, middle row) shows the well-known SR inverted u-shape function. The maximum peak is found when P = 10 dB. Right column shows neuronal firing histograms with their corresponding time histories. T is the signal period and N means the probability to have certain neuronal activity levels.
Mentions: For unimodal SR neurons, the signal (harmonic term in equation 1) and the noise are present in the same region x≤0. In this case the inherent system perturbation is defined by parameter values ε−>0 for x≤0 and ε+ = 0 for x>0. Hence, in order to calculate the neuron's firing necessary condition, we only have to take in account the homoclinic orbit Γ− and parameters associated with this region. Substituting equation (11) and equation (10), for Γ−, into equation (5) and then working out the integrals, the necessary condition for the escapes to take place is(14)where is known as the Melnikov scale factor, shown in figure 5 (bottom) where is clear that if we want to optimize the energy transfer from the stochastic process G(t) then its spectral density needs to contain frequencies around the Melnikov scale factor maximum. The necessary escape condition (equation 14) serves to calculate the required noise amplitude σ−, for neuron firings and the mean escape rate equation gives us the condition to observe the SR peak in neurons. Figure 6 shows some simulations for the behavior of neuronal activity with different noise amplitudes. The parameters we used are ε− = 1 γ− = 0.095, β− = 0.316, α+ = 49, α− = 1, ω0 = 0.6283 (0.1 Hz), N = 500, c = 0.02, and ωcut = 3. In all the simulations we have performed over 200 noise realizations approximated by equation G(t) and then averaged. The left column in figure 6 shows the neurons spectrum amplitude as a function of the noise intensity σ−. As it would be expected for low noise intensities the energy transfer from the noise to the signal is not enough to achieve the synchronization and as a result the spontaneous activity dominates and no firings occur. However as the noise intensity increases firings also increase up to a maximum peak, where the mean escape rate approximately equals the signal frequency. Beyond this point, random firings can occur at different frequencies meaning that the synchronized energy transfer from the noise to the signal is destroyed and the signal is embedded in the spontaneous activity. The insert (left column, middle row) shows the well known SR inverse u-shape function, the maximum peak is found when P = 10 dB. Right column in figure 6, shows neuron's firings histograms with their correspondent time histories.

Bottom Line: Specifically, we show that the effective auditory noise significantly increased tactile sensations of the finger, decreased luminance and contrast visual thresholds and significantly changed EMG recordings of the leg muscles during posture maintenance.We conclude that crossmodal SR is a ubiquitous phenomenon in humans that can be interpreted within an energy and frequency model of multisensory neurons spontaneous activity.The result is an integrated activation that promotes sensitivity transitions and the signals are then perceived.

View Article: PubMed Central - PubMed

Affiliation: Visual Psychophysics and Perception Laboratory, School of Optometry, University of Montreal, Montreal, Quebec, Canada.

ABSTRACT

Background: Stochastic resonance is a nonlinear phenomenon whereby the addition of noise can improve the detection of weak stimuli. An optimal amount of added noise results in the maximum enhancement, whereas further increases in noise intensity only degrade detection or information content. The phenomenon does not occur in linear systems, where the addition of noise to either the system or the stimulus only degrades the signal quality. Stochastic Resonance (SR) has been extensively studied in different physical systems. It has been extended to human sensory systems where it can be classified as unimodal, central, behavioral and recently crossmodal. However what has not been explored is the extension of this crossmodal SR in humans. For instance, if under the same auditory noise conditions the crossmodal SR persists among different sensory systems.

Methodology/principal findings: Using physiological and psychophysical techniques we demonstrate that the same auditory noise can enhance the sensitivity of tactile, visual and propioceptive system responses to weak signals. Specifically, we show that the effective auditory noise significantly increased tactile sensations of the finger, decreased luminance and contrast visual thresholds and significantly changed EMG recordings of the leg muscles during posture maintenance.

Conclusions/significance: We conclude that crossmodal SR is a ubiquitous phenomenon in humans that can be interpreted within an energy and frequency model of multisensory neurons spontaneous activity. Initially the energy and frequency content of the multisensory neurons' activity (supplied by the weak signals) is not enough to be detected but when the auditory noise enters the brain, it generates a general activation among multisensory neurons of different regions, modifying their original activity. The result is an integrated activation that promotes sensitivity transitions and the signals are then perceived. A physiologically plausible model for crossmodal stochastic resonance is presented.

Show MeSH
Related in: MedlinePlus