Behavioral Stochastic Resonance: How the Noise from a Daphnia Swarm Enhances Individual Prey Capture by Juvenile Paddlefish

Freund, Jan A.; Schimansky‐Geier, Lutz; Beisner, Beatrix E.; Neiman, Alexander; Russell, David F.; Yakusheva, Tatyana A.; Moss, Frank

doi:10.1006/jtbi.2001.2445

Cited by 74 publications

(62 citation statements)

References 59 publications

(53 reference statements)

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“…23,27,50 This boosts the signal-to-noise ratio at low frequencies, and consequently the SR coherence, and enhances the coding efficiency of a neuron. We note that the low frequency band of 0.5-2 Hz is indeed represented in the PSDs of naturalistic stimuli from zooplankton 26 and of moving DC electrical sources in water. 36 Although the gain of paddlefish ER afferents was low in this 0.5-2 Hz frequency range, the SR coherence showed high values, indicating effective stimulus encoding, and demonstrating the advantages of SR coherence for measuring frequency tuning.…”

Section: B Epithelial Oscillationsmentioning

confidence: 74%

“…2(b)). 26 These naturalistic stimuli were faithfully encoded into afferent spike trains, as indicated by high values of SR coherence for both types of stimuli (Fig. 4(b)).…”

Section: B Linear Encoding and Information Ratesmentioning

confidence: 92%

“…2(c)) recorded from a swarm of Daphnia zooplankton prey was Gaussian. 26 Two types of noise presentations were used: (a) as sequences of 180 s segments of different randomly chosen noise variances, or cutoff frequencies, separated by 10 s of no stimulus; or (b) as repeated identical 13.2 s segments of a noise realization, i.e., "frozen noise," separated by 5 s of no stimulus, to study cross-trial variability of afferent responses.…”

Section: A Experimentalmentioning

confidence: 99%

“…3(d)). While the signal from a Daphnia swarm could be represented as exponentially correlated noise, 26 the signal from a single Daphnia possessed essential periodicities due to 7 Hz beating of feeding legs, interrupted by large pulses due to antennal motions for swimming (Fig. 2(b)).…”

Section: B Linear Encoding and Information Ratesmentioning

confidence: 99%

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Sensory coding in oscillatory electroreceptors of paddlefish

Neiman

Russell²

2011

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Coherence and information theoretic analyses were applied to quantitate the response properties and the encoding of time-varying stimuli in paddlefish electroreceptors (ERs), studied in vivo. External electrical stimuli were Gaussian noise waveforms of varied frequency band and strength, including naturalistic waveforms derived from zooplankton prey. Our coherence analyses elucidated the role of internal oscillations and transduction processes in shaping the 0.5-20 Hz best frequency tuning of these electroreceptors, to match the electrical signals emitted by zooplankton prey. Stimulus-response coherence fell off above approximately 20 Hz, apparently due to intrinsic limits of transduction, but was detectable up to 40-50 Hz. Aligned with this upper fall off was a narrow band of intense internal noise at $25 Hz, due to prominent membrane potential oscillations in cells of sensory epithelia, which caused a narrow deadband of external insensitivity. Using coherence analysis, we showed that more than 76% of naturalistic stimuli of weak strength, $1 lV=cm, was linearly encoded into an afferent spike train, which transmitted information at a rate of $30 bits=s. Stimulus transfer to afferent spike timing became essentially nonlinear as the stimulus strength was increased to induce bursting firing. Strong stimuli, as from nearby zooplankton prey, acted to synchronize the bursting responses of afferents, including across populations of electroreceptors, providing a plausible mechanism for reliable information transfer to higher-order neurons through noisy synapses. Rhythmical activity underlies various complex physiological processes in central nervous systems. Peripheral sensory receptors, on the other hand, are often considered as "passive" systems with relatively simple and linear dynamics. Nevertheless, self-sustained oscillations have been observed in several types of peripheral sensory receptors. This paper reports on stimulus encoding in electroreceptors (ERs) of paddlefish, which use passive electrosense to feed on zooplankton. A single peripheral electroreceptor in paddlefish is a complex system comprised of several thousands of sensory epithelial cells innervated by a few primary sensory neurons (afferents). It embeds distinct oscillators: one resides in a population of epithelial cells, synaptically coupled to another oscillator in afferent terminals. In contrast to auditory receptors, which resonate to sound waves of certain frequency, neither epithelial nor afferent rhythms of electroreceptors match the low-frequency bioelectric signals emitted by zooplankton prey. We applied Gaussian noise stimuli to study how oscillators embedded in paddlefish electroreceptors shape the linear and nonlinear responses of electroreceptors, and to characterize quantitatively how external stimuli, including bioelectrical signals from zooplankton prey, are encoded into the timing of afferent firing.

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Section: B Epithelial Oscillationsmentioning

confidence: 74%

“…2(b)). 26 These naturalistic stimuli were faithfully encoded into afferent spike trains, as indicated by high values of SR coherence for both types of stimuli (Fig. 4(b)).…”

Section: B Linear Encoding and Information Ratesmentioning

confidence: 92%

Section: A Experimentalmentioning

confidence: 99%

Section: B Linear Encoding and Information Ratesmentioning

confidence: 99%

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Sensory coding in oscillatory electroreceptors of paddlefish

Neiman

Russell²

2011

Chaos: An Interdisciplinary Journal of Nonlinear Science

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“…SR and other cooperative noise effects so far have been extensively studied in very different fields reaching from protein switches and ion channels dynamics (Gardner et al, 2000;Hasty et al, 2000;Bezrukov and Vodyanoy, 1995;Astumian et al, 1997;Petracchi et al, 1994), to membrane currents and action potential generation (Douglass et al, 1993;Braun et al, 1980Braun et al, , 1994Huber et al, 1998;White et al, 1998;Longtin et al, 1991;Levin and Miller, 1996;Gluckman et al, 1996;Stacey and Durand, 2000;Rudolph and Destexhe, 2001), to cognitive functions and behavioral responses (Stemmler et al, 1995;Simonotto et al, 1997;Winterer et al, 1999;Russell et al, 1999;Freund et al, 2001Freund et al, , 2002, and also with regard to different aspects of psychiatric disorders (Huber et al, 1999(Huber et al, , 2000Winterer et al, 2000). Accordingly, psychiatrically relevant noise sources also appear at various levels.…”

Section: Introductionmentioning

confidence: 99%

On Episode Sensitization in Recurrent Affective Disorders: The Role of Noise

Huber

Braun

Krieg

2003

Neuropsychopharmacol

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Episode sensitization is postulated as a key mechanism underlying the long-term course of recurrent affective disorders. Functionally, episode sensitization represents positive feedback between a disease process and its disease episodes resulting in a transition from externally triggered to autonomous episode generation. Recently, we introduced computational approaches to elucidate the functional properties of sensitization. Specifically, we considered the dynamics of episode sensitization with a simple computational model. The present study extends this work by investigating how naturally occurring, internal or external, random influences ('noise') affect episode sensitization. Our simulations demonstrate that actions of noise differ qualitatively in dependence on both the model's activity state as well as the noise intensity. Thereby induction as well as suppression of sensitization can be observed. Most interestingly, externally triggered sensitization development can be minimized by tuning the noise to intermediate intensities. Our findings contribute to the conceptual understanding of the clinical kindling model for affective disorders and also indicate interesting roles for random fluctuations in kindling and sensitization at the neuronal level. Neuropsychopharmacology (2003) 28, S13-S20.

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Collective Coherence Resonance in Networks of Optical Neurons

Köster

Lingnau

Krimlowski

et al. 2021

Physica Status Solidi (b)

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The dynamical properties of an optical neuron formed by a quantum dot semiconductor laser model subjected to optical injection and optical feedback are analyzed. The parameter space spanned by the injection strength and frequency detuning of the optical injection is systematically scanned and modulations of the bifurcation boundaries that induce complex scenarios are found, which enable new opportunities to introduce the optical setup as an optical neuron. The counterintuitive behavior of coherence resonance for different setups of a single‐driven optical neuron under optical feedback is also found. Following the results, the microscopically motivated quantum dot laser rate equation model is reduced to the normal form of a saddle‐node infinite period (SNIPER) bifurcation for low injection strengths and a network of four such SNIPER systems in a globally coupled setup is studied. A new phenomenon is observed, which is called collective coherence resonance. This novel dynamical behavior is connected to the coexistence of a network‐wide SNIPER bifurcation and a change in stability for the synchronized manifold, analyzed via the master stability function.

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Behavioral Stochastic Resonance: How the Noise from a Daphnia Swarm Enhances Individual Prey Capture by Juvenile Paddlefish

Cited by 74 publications

References 59 publications

Sensory coding in oscillatory electroreceptors of paddlefish

Sensory coding in oscillatory electroreceptors of paddlefish

On Episode Sensitization in Recurrent Affective Disorders: The Role of Noise

Collective Coherence Resonance in Networks of Optical Neurons

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