The benefits of noise in neural systems: bridging theory and experiment

McDonnell, Mark D.; Ward, Lawrence M.

doi:10.1038/nrn3061

Cited by 656 publications

(484 citation statements)

References 99 publications

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“…Alternatively, it has been more recently postulated that neural variability instead forms a key element of the neural code by promoting increased information transmission (1). Indeed, theoretical studies posit that trial-to-trial variability in the neural response can effectively increase information transmission (38). Our results showing that correlated activity can optimally transmit information about the envelope for a nonzero level of variability provide a novel beneficial role for neural variability in sensory coding.…”

Section: Discussionmentioning

confidence: 57%

Coding of envelopes by correlated but not single-neuron activity requires neural variability

Metzen

Jamali

Carriot

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Understanding how the brain processes sensory information is often complicated by the fact that neurons exhibit trial-to-trial variability in their responses to stimuli. Indeed, the role of variability in sensory coding is still highly debated. Here, we examined how variability influences neural responses to naturalistic stimuli consisting of a fast time-varying waveform (i.e., carrier or first order) whose amplitude (i.e., envelope or second order) varies more slowly. Recordings were made from fish electrosensory and monkey vestibular sensory neurons. In both systems, we show that correlated but not single-neuron activity can provide detailed information about second-order stimulus features. Using a simple mathematical model, we made the strong prediction that such correlation-based coding of envelopes requires neural variability. Strikingly, the performance of correlated activity at predicting the envelope was similarly optimally tuned to a nonzero level of variability in both systems, thereby confirming this prediction. Finally, we show that second-order sensory information can only be decoded if one takes into account joint statistics when combining neural activities. Our results thus show that correlated but not single-neural activity can transmit information about the envelope, that such transmission requires neural variability, and that this information can be decoded. We suggest that envelope coding by correlated activity is a general feature of sensory processing that will be found across species and systems. correlation | envelope | electrosensory | vestibular | neural coding A lthough correlated activity and neural variability are both observed ubiquitously in the brain, their functional roles have been the focus of much debate (1, 2). Indeed, the conventional wisdom that both are detrimental to coding by introducing redundancy and noise, respectively, has been recently challenged (3, 4). Here, we investigated the effects of variability on the coding by correlated activity of naturalistic sensory stimuli that often have rich spatiotemporal structure characterized by firstand second-order attributes. Specifically, we considered how neural populations within the electrosensory system of weakly electric fish and the vestibular system of monkeys respond to stimuli consisting of a fast time-varying carrier waveform (i.e., first-order attribute) whose amplitude or envelope (i.e., secondorder attribute) varies independently on a longer timescale. Envelopes are critical for perception (5, 6), yet their neural encoding continues to pose a challenge to investigators because they are nonlinearly related to the stimulus waveform (7). Previous studies have shown that single neurons can transmit envelope information through changes in firing rate (8, 9) when the relationship between the stimulus input and the output firing rate is nonlinear. In contrast, here, we focused on neuronal responses that were linearly related to the stimulus waveform.Weakly electric fish generate an electric field around their body throug...

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Section: Discussionmentioning

confidence: 57%

Coding of envelopes by correlated but not single-neuron activity requires neural variability

Metzen

Jamali

Carriot

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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“…In classical systems theory, random fluctuations in signals are referred to as "noise" and are nearly always considered detrimental, and so great efforts are made to eliminate this noise. However, in physiological systems, such as neural systems, while "noise" is ubiquitous, it is, in fact, widely considered to be essential in facilitating information processing in the body [11]. Stochastic Resonance (SR) is a phenomenon where the presence of "noise" in non-linear systems can be used to enhance the detection of sub-threshold stimuli.…”

Section: Discussionmentioning

confidence: 99%

Rectification of RF Fields in Load Dependent Coupled Systems: Application to Non-Invasive Electroceuticals

Koneru¹,

Westgate²,

McLeod³

2016

JBiSE

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Electroceuticals are medical devices that employ electric signals to alter the activity of specific nerve fibers to achieve therapeutic effects. The rapid growth of RF microelectronics has resulted in the development of very small, portable, and inexpensive shortwave and microwave radio frequency (RF) amplifiers, raising the possibility of utilizing these new RF technologies to develop non-contact electroceutical devices. However, the bio-electromagnetics literature suggests that beyond 10 MHz, RF fields cannot influence biological tissue, beyond simple heating, because effective demodulation mechanisms at these frequencies do not exist in the body. However, RF amplifiers operating at or near saturation have non-linear interactions with complex loads, and if body tissue creates a complex loading condition, the opportunity exists for the coupled system to produce non-linear effects, that is, the equivalent of demodulation may occur. Correspondingly, exposure of tissue to pulsed RF energy could result in the creation of low frequency demodulation components capable of influencing tissue activity. Here, we develop a one-dimensional, numerical simulation to investigate the complex loading conditions under which such demodulation could arise. Applying these results in a physical prototype device, we show that up to7.5% demodulation can be obtained for a 40 MHz RF field pulsed at 1 KHz. Implications for this research include the possibility of developing wearable, electromagnetic electroceutical devices.

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“…The diameter of a typical human axon, 0.1 micrometres, is so small that the signals it contains are susceptible to thermal noise and hence to random fluctuations 6 . Although such noise is often considered to hinder the operation of the nervous system, in some circumstances it might offer an advantage 7 .…”

Section: Wider Benefitsmentioning

confidence: 99%

Modelling: Build imprecise supercomputers

Palmer

2015

Nature

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Energy-optimized hybrid computers with a range of processor accuracies will advance modelling in fields from climate change to neuroscience, says Tim Palmer.T oday's supercomputers lack the power to model accurately many aspects of the real world, from the impact of cloud systems on Earth's climate to the processing ability of the human brain. Rather than wait decades for sufficiently powerful supercomputers -with their potentially unsustainable energy demands -it is time for researchers to reconsider the basic concept of the computer. We must move beyond the idea of a computer as a fast but otherwise traditional 'Turing machine' , churning through calculations bit by bit in a sequential, precise and reproducible manner.In particular, we should question whether all scientific computations need to be performed deterministically -that is, always producing the same output given the same input -and with the same high level of precision. I argue that for many applications they do not.Energy-efficient hybrid supercomputers with a range of processor accuracies need to be developed. These would combine conventional energy-intensive processors with low-energy, non-deterministic processors, able to analyse data at variable levels of precision. The demand for such machines could be substantial, across diverse sectors of the scientific community. MORE WITH LESSTake climate change, for example. Estimates of Earth's future climate are based on solving nonlinear (partial differential) equations for fluid flow in the atmosphere and oceans. Current climate simulators -typically with grid cells of 100 kilometres in width -can resolve the large, low-pressure weather systems typical of mid-latitudes, but not individual clouds. Yet modelling cloud systems accurately is crucial for reliable estimates of the impact of anthropogenic emissions on global temperature 1 .The resolution of this computational grid is determined by the available computing power. Current petaflop computers can perform up to 10 15 additions or multiplications -floating-point operationsper second (flops). By the early 2020s, next-generation exaflop supercomputers, capable of 10 18 operations per second, will be able to resolve the largest and most vigorous types of thunderstorm 2 . But cloud physics on scales smaller than a grid cell will still have to be approximated, or

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The benefits of noise in neural systems: bridging theory and experiment

Cited by 656 publications

References 99 publications

Coding of envelopes by correlated but not single-neuron activity requires neural variability

Coding of envelopes by correlated but not single-neuron activity requires neural variability

Rectification of RF Fields in Load Dependent Coupled Systems: Application to Non-Invasive Electroceuticals

Modelling: Build imprecise supercomputers

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