Stochastic resonance.

Stochastic resonance sounded odd in combination with consciousness, in a recent discussion. I was going to dismiss it, but maybe I can learn something instead.

History: Stochastic resonance was first discovered in a study of the periodic recurrence of earth’s ice ages. The theory developed out of an effort to understand how the earth's climate oscillates periodically between two relatively stable global temperature states, one "normal" and the other an "ice age" state. The conventional explanation was that variations in the eccentricity of earth's orbital path occurred with a period of about 100,000 years and caused the average temperature to shift dramatically. The measured variation in the eccentricity had a relatively small amplitude compared to the dramatic temperature change, however, and stochastic resonance was developed to show that the temperature change due to the weak eccentricity oscillation and added stochastic variation due to the unpredictable energy output of the sun (known as the solar constant) could cause the temperature to move in a nonlinear fashion between two stable dynamic states.

Wikipedia: Stochastic resonance is observed when noise added to a system changes the system's behaviour in some fashion. More technically, SR occurs if the signal-to-noise ratio of a nonlinear system or device increases for moderate values of noise intensity [or reversely?] It often occurs in bistable systems or in systems with a sensory threshold and when the input signal to the system is "sub-threshold". For lower noise intensities, the signal does not cause the device to cross threshold, so little signal is passed through it. For large noise intensities, the output is dominated by the noise, also leading to a low signal-to-noise ratio. For moderate intensities, the noise allows the signal to reach threshold, but the noise intensity is not so large as to swamp it. Thus, a plot of signal-to-noise ratio as a function of noise intensity shows a '∩' shape.

Typical curve of output performance versus input noise magnitude, for systems capable of stochastic resonance.

For small and large noise, the performance metric (e.g., SNR, mutual information, Fisher information, correlation, discrimination index) is very small, while some intermediate nonzero noise level provides optimal performance.

The word resonance in the term stochastic resonance was originally used because the signature feature of SR is that a plot of a performance measure—such as output signal-to-noise ratio (SNR)—against input noise “intensity” has a single maximum at a nonzero value. Such a plot, as shown in Figure, has a similar appearance to frequency-dependent systems that have a maximum SNR, or output response, for some resonant frequency. However, in the case of SR, the resonance is “noise-induced” rather than at a particular frequency.

Stochastic resonance occurs in bistable systems, when a small periodic (sinusoidal) force is applied together with a large wide band stochastic force (noise). The system response is driven by the combination of the two forces that compete/cooperate to make the system switch between the two stable states. The degree of order is related to the amount of periodic function that it shows in the system response. When the periodic force is chosen small enough in order to not make the system response switch, the presence of a non-negligible noise is required for it to happen. When the noise is small very few switches occur, mainly at random with no significant periodicity in the system response. When the noise is very strong a large number of switches occur for each period of the sinusoid and the system response does not show remarkable periodicity. Between these two conditions, there exists an optimal value of the noise that cooperatively concurs with the periodic forcing in order to make almost exactly one switch per period (a maximum in the signal-to-noise ratio).

Such a favorable condition is quantitatively determined by the matching of two time scales: the period of the sinusoid (the deterministic time scale) and the Kramers rate (i.e., the inverse of the average switch rate induced by the sole noise: the stochastic time scale). Thus the term "stochastic resonance".

• Weisstein, Eric W. "Kramers Rate." From MathWorld-A Wolfram Web Resource. http://mathworld.wolfram.com/KramersRate.html The charachteristic escape rate from a stable state of a potential in the absence of signal.
  
• Benzi, R.; Sutera, A.; and Vulpiani, A. "The Mechanism of Stochastic Resonance." J. Phys. A 14, L453-L457, 1981.
• Gammaitoni, L. "Stochastic Resonance E-Print Server." http://www.umbrars.com/sr/.
• Bulsara, A. R. and Gammaitoni, L. "Tuning in to Noise." Phys. Today 49, 39-45, March 1996. A stochastic resonance is a phenomenon in which a nonlinear system is subjected to a periodic modulated signal so weak as to be normally undetectable, but it becomes detectable due to resonance between the weak deterministic signal and stochastic noise. The earliest definition of stochastic resonance was the maximum of the output signal strength as a function of noise.

Stochastic resonance was discovered and proposed for the first time in 1981 to explain the periodic recurrence of ice ages. Since then the same principle has been applied in a wide variety of systems. Nowadays stochastic resonance is commonly invoked when noise and nonlinearity concur to determine an increase of order in the system response.

Peter Hänggi, et al.1990. Reaction-rate theory: fifty years after Kramers

The calculation of rate coefficients is a discipline of nonlinear science of importance to much of physics, chemistry, engineering, and biology. Fifty years after Kramers' seminal paper on thermally activated barrier crossing, the authors report, extend, and interpret much of our current understanding relating to theories of noise-activated escape, for which many of the notable contributions are originating from the communities both of physics and of physical chemistry. Theoretical as well as numerical approaches are discussed for single- and many-dimensional metastable systems (including fields) in gases and condensed phases. The role of many-dimensional transition-state theory is contrasted with Kramers' reaction-rate theory for moderate-to-strong friction; the authors emphasize the physical situation and the close connection between unimolecular rate theory and Kramers' work for weakly damped systems. The rate theory accounting for memory friction is presented, together with a unifying theoretical approach which covers the whole regime of weak-to-moderate-to-strong friction on the same basis (turnover theory). The peculiarities of noise-activated escape in a variety of physically different metastable potential configurations is elucidated in terms of the mean-first-passage-time technique. Moreover, the role and the complexity of escape in driven systems exhibiting possibly multiple, metastable stationary nonequilibrium states is identified. At lower temperatures, quantum tunneling effects start to dominate the rate mechanism. The early quantum approaches as well as the latest quantum versions of Kramers' theory are discussed, thereby providing a description of dissipative escape events at all temperatures. In addition, an attempt is made to discuss prominent experimental work as it relates to Kramers' reaction-rate theory and to indicate the most important areas for future research in theory and experiment.

The classical Kramers problem (the dissociation problem): The rate of escape of a classical particle over an energy barrier is a well-posed problem as long as the potential energy features a barrier or transition-state that has to be crossed. The escape-rate problem is known to be ill-defined when the particle is trapped in a potential well which is the only point of minimum in the potential profile (which then either diverges or reaches asymptotes along the coordinated axis), see a 'brandnew', Kramers rate theory of ionization and dissociation of bound states, Alessio Zaccone, Eugene M. Terentjev,

Calculating the microscopic dissociation rate of a bound state, such as a classical diatomic molecule, has been difficult so far. The problem was that standard theories require an energy barrier over which the bound particle (or state) escapes into the preferred low-energy state. This is not the case when the long-range repulsion responsible for the barrier is either absent or screened (as in Cooper pairs, ionized plasma, or biomolecular complexes). We solve this classical problem by accounting for entropic memory at the microscopic level. The theory predicts dissociation rates for arbitrary potentials and is successfully tested on the example of plasma, where it yields an estimate of ionization in the core of Sun in excellent agreement with experiments. In biology, the new theory accounts for crowding in receptor-ligand kinetics and protein aggregation.

Potential wells are important in biology, see memory-drag in Rakovic as instance. Popp talked much of potential versus kinetics. GABA-inhibition is known to create coherence etc.

Wikipedia: Suprathreshold stochastic resonance is a particular form of stochastic resonance. It is the phenomenon where random fluctuations, or noise, provide a signal processing benefit in a nonlinear system. Unlike most of the nonlinear systems where stochastic resonance occurs, suprathreshold stochastic resonance occurs not only when the strength of the fluctuations is small relative to that of an input signal, but occurs even for the smallest amount of random noise. Furthermore, it is not restricted to a subthreshold signal, hence the qualifier, suprathreshold, in suprathreshold stochastic resonance.

Standing waves as amplifiers? Review of Suprathreshold Stochastic Resonance
M. D. McDonnell, N. G. Stocks, C. E. M. Pearce, D. Abbott, Stochastic Resonance: From Suprathreshold Stochastic Resonance to Stochastic Signal Quantization, Cambridge University Press, 2008.

Stochastic resonance has been observed in the neural tissue of the sensory systems of several organisms. Computationally, neurons exhibit SR because of non-linearities in their processing. SR has yet to be fully explained in biological systems, but neural synchrony in the brain (specifically in the gamma wave frequency) has been suggested as a possible neural mechanism for SR by researchers who have investigated the perception of "subconscious" visual sensation.

This ethernal gamma wave! The neurobiological phallos? But interesting!

SR-based techniques has been used to create a novel class of medical devices (such as vibrating insoles) for enhancing sensory and motor function in the elderly, patients with diabetic neuropathy, and patients with stroke.

Vibrating molecules did we earlier discuss in smell perception as instance. Evidence for stochastic resonance in a sensory system was first found in nerve signals from the mechanoreceptors located on the tail fan of the crayfish (Procambarus clarkii). Also for other mechanoreceptors and tiny passive electroreceptors in the paddlefish (Polyodon spathula) rostrum.

The procedure.
Two separate measurements were used to estimate the signal-to-noise ratio of the neural response. The first was based on the Fourier power spectrum of the spike time series response. The power spectra from the averaged spike data for three different noise intensities all showed a clear peak at the 55.2 Hz component with different average levels of broadband noise. The relatively low- and mid-level added noise conditions also show a second harmonic component at about 110 Hz. The mid-level noise condition clearly shows a stronger component at the signal of interest than either low- or high-level noise, and the harmonic component is greatly reduced at mid-level noise and not present in the high-level noise. A standard measure of the SNR as a function of noise variance shows a clear peak at the mid-level noise condition. The other measure used for SNR was based on the inter-spike interval histogram instead of the power spectrum. A similar peak was found on a plot of SNR as a function of noise variance for mid-level noise, although it was slightly different from that found using the power spectrum measurement. These data support the claim that noise can enhance detection at the single neuron level, but not more.

If the stimuli are generally of a certain magnitude, it seems that it would be more evolutionarily advantageous for the threshold of the neuron to match that of the stimuli. In systems with noise, however, tuning thresholds for taking advantage of stochastic resonance may be the best strategy.

A theoretical account of how a large model network (up to 1000) of summed FitzHugh-Nagumo neurons could adjust the threshold of the system based on the noise level present in the environment was devised. This can be equivalently conceived of as the system lowering its threshold, and this is accomplished such that the ability to detect suprathreshold signals is not degraded.

Enhancing the synchrony and complexity?

Hänggi P (Mar 2002). "Stochastic resonance in biology. How noise can enhance detection of weak signals and help improve biological information processing" An interesting article.

Life's necessities; food, water, shelter, - noise - to enhance detection of weak signals and help improve biological information processing. A symmetric bistable potential well is periodically rocked by a weak signal.

Neural synchrony in stochastic resonance, attention, and consciousness. Ward et. al., 2006:

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.

Also between switched perceptions, as exemplified by a Necker cube. McDonnell MD, and Abbott D (2009). "What is Stochastic Resonance? Definitions, misconceptions, debates, and its relevance to biology"one of the central arguments for dismissing SR, i.e., the conclusion that optimal signal detection is incompatible with the fact that SR is observed when detection performance is non-monotonically decreasing with increasing input SNR. This difficulty has been discussed several times in the literature. Of particular relevance to biologists are the opposing viewpoints of Tougaard and Ward et. al.
In one variant of SR, which relies on a parallel population of “sensors” or neurons collectively encoding a common stimulus—noise benefits do disappear if the overall population is optimized. [- Note, evolutional factor?] The goal could be information transmission, signal classification, or signal compression, suboptimal detectors.

If it can be established that SR plays an important role in the encoding and processing of information in the brain, and that it somehow provides part of the brain's superior performance to computers and artificial intelligence in some areas, then using this knowledge in engineering systems may revolutionize the way we design computers, sensors, and communications systems.

For biological science, rather than view SR as a specifically defined phenomenon of limited scope, we advocate thinking about SR in terms of the broad idea of “noise benefits”, and as a reminder that ideal systems often cannot be engineered in practice. When this is the case, it is necessary to make the best of a suboptimal situation, such as exploiting noise to advantage. This principle holds for evolution as well. If there are nonlinearities involved, then it is easy to imagine that organisms evolved to make the best possible use of noise and fluctuations that are unavoidably present.

Melloni L, Molina C, Pena M, Torres D, Singer W, Rodriguez E (Mar 2007). "Synchronization of neural activity across cortical areas correlates with conscious perception"

Subliminal stimuli can be deeply processed and activate similar brain areas as consciously perceived stimuli. This raises the question which signatures of neural activity critically differentiate conscious from unconscious processing. Transient synchronization of neural activity has been proposed as a neural correlate of conscious perception. Here we test this proposal by comparing the electrophysiological responses related to the processing of visible and invisible words in a delayed matching to sample task. Both perceived and nonperceived words caused a similar increase of local (gamma) oscillations in the EEG, but only perceived words induced a transient long-distance synchronization of gamma oscillations across widely separated regions of the brain. After this transient period of temporal coordination, the electrographic signatures of conscious and unconscious processes continue to diverge. Only words reported as perceived induced (1) enhanced theta oscillations over frontal regions during the maintenance interval, (2) an increase of the P300 component of the event-related potential, and (3) an increase in power and phase synchrony of gamma oscillations before the anticipated presentation of the test word. We propose that the critical process mediating the access to conscious perception is the early transient global increase of phase synchrony of oscillatory activity in the gamma frequency range.

Note the oscillatory and temporal peaks giving the synchrony.

Long-range synchronization, conscious perception, and the depth of processing

It can be argued that the electrophysiological signatures associated with conscious perception are simply a reflection of more extensive processing rather than reflecting mechanisms specifically associated with awareness. We consider this as unlikely for several reasons. The finding that visible and invisible words induced gamma oscillations of similar power and distribution suggests that invisible words were thoroughly processed. In addition, in the control experiment with the subliminal priming task, we evaluated the depth of processing of the unperceived word using the same protocol as in the main experiment. Prime words, although not perceived, had a clear behavioral effect indicating that the unconsciously perceived words are processed. Therefore, we consider it likely that the key event mediating access to consciousness is the early long-distance synchronization of neural assemblies, rather than the mere depth of processing in the various cortical areas involved in written word processing.

But the emotional arousal??? We need to know more! Dejan Rakovic had memory functions linked to a potential well too. See Schrödingers cat. Dead and alive, body and mind. The cat is a complex system, and TGD and D.Rakovic. The quantum field body, a comprision.

A related phenomenon is dithering applied to analog signals before analog-to-digital conversion. Stochastic resonance can be used to measure transmittance amplitudes below an instrument's detection limit. If Gaussian noise is added to a subthreshold (i.e., immeasurable) signal, then it can be brought into a detectable region. After detection, the noise is removed. A fourfold improvement in the detection limit can be obtained.

Wave-interference?

Newsweek Being messy, both at home and in foreign policy, may have its own advantages Retrieved 3 Jan 2011

Quantum computer build inside a diamond: Noise brushes off particles that got decoherent.

Hänggi link this to relativistic thermodynamicity?
Physics News Update, 2007:

Einstein’s special theory of relativity has formulas, called Lorentz transformations, that convert time or distance intervals from a resting frame of reference to a frame zooming by at nearly the speed of light. But how about temperature? That is, if a speeding observer, carrying her thermometer with her, tries to measure the temperature of a gas in a stationary bottle,what temperature will she measure? A new look at this contentious subject suggests that the temperature will be the same as that measured in the rest frame. In other words, moving bodies will not appear hotter or colder... Some astrophysical systems might eventually offer a chance to experimentally judge the issue. In general the effort to marry thermodynamics with special relativity is still at an early stage. It is not exactly known how several thermodynamic parameters change at high speeds. Absolute zero, Dunkel says, will always be absolute zero, even for quickly-moving observers. But producing proper Lorentz transformations for other quantities such as entropy will be trickier to do.

Defining quantities with respect to the observer's past lightcone ? The concept of negative energy and Zero Energy Ontology of TGD? WAU!

(Maybe my german readers high peak will get an explanation?)

Interesting. This has potential to be something?