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Spike-interval triggered averaging reveals a quasi-periodic spiking alternative for stochastic resonance in catfish electroreceptors.

Lankheet MJ, Klink PC, Borghuis BG, Noest AJ - PLoS ONE (2012)

Bottom Line: Here we show that catfish electroreceptors have adopted a fundamentally different strategy.In this regime stimuli modulate the interval between successive spikes rather than the instantaneous probability for a spike.This alternative for stochastic resonance combines threshold-free sensitivity for weak stimuli with similar sensitivity for excitations and inhibitions based on single interspike intervals.

View Article: PubMed Central - PubMed

Affiliation: Experimental Zoology, Wageningen University, Wageningen, The Netherlands. martin.lankheet@wur.nl

ABSTRACT
Catfish detect and identify invisible prey by sensing their ultra-weak electric fields with electroreceptors. Any neuron that deals with small-amplitude input has to overcome sensitivity limitations arising from inherent threshold non-linearities in spike-generation mechanisms. Many sensory cells solve this issue with stochastic resonance, in which a moderate amount of intrinsic noise causes irregular spontaneous spiking activity with a probability that is modulated by the input signal. Here we show that catfish electroreceptors have adopted a fundamentally different strategy. Using a reverse correlation technique in which we take spike interval durations into account, we show that the electroreceptors generate a supra-threshold bias current that results in quasi-periodically produced spikes. In this regime stimuli modulate the interval between successive spikes rather than the instantaneous probability for a spike. This alternative for stochastic resonance combines threshold-free sensitivity for weak stimuli with similar sensitivity for excitations and inhibitions based on single interspike intervals.

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Spike interval triggered averaging (SITA).(A) The recording setup. Stimulation currents are applied locally through a stimulation ring, while spikes from afferent are recorded from within the lumen of the electroreceptor. (B) Example of the reverse correlation technique. For each recorded spike the stimulus shape is analyzed in a directly preceding time interval (-Δt). For each measurement about 75,000 spikes were grouped in 5 classes with equal numbers of spikes in each class, based on the cumulative distribution of interspike interval durations (intervals preceding spikes). (C) Interspike interval distribution (bottom panel) and cumulative interspike interval distribution (top panel). Spike-triggered averages were generated for each class separately. (D) Overview of spike interval triggered averages (SITAs) for 26 electroreceptors recorded in 20 catfish. Colors indicate the different interval classes as shown in (C). Confidence intervals for each class represent ±2*SEM. The overall STA is shown in black and the moment of the trigger spike is represented by the dashed line at T = 0 ms. (E) Left hand panel: Distributions of peak amplitude values, normalized to the amplitude for the shortest interval class. Right hand panel: distribution of peak latencies.
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pone-0032786-g001: Spike interval triggered averaging (SITA).(A) The recording setup. Stimulation currents are applied locally through a stimulation ring, while spikes from afferent are recorded from within the lumen of the electroreceptor. (B) Example of the reverse correlation technique. For each recorded spike the stimulus shape is analyzed in a directly preceding time interval (-Δt). For each measurement about 75,000 spikes were grouped in 5 classes with equal numbers of spikes in each class, based on the cumulative distribution of interspike interval durations (intervals preceding spikes). (C) Interspike interval distribution (bottom panel) and cumulative interspike interval distribution (top panel). Spike-triggered averages were generated for each class separately. (D) Overview of spike interval triggered averages (SITAs) for 26 electroreceptors recorded in 20 catfish. Colors indicate the different interval classes as shown in (C). Confidence intervals for each class represent ±2*SEM. The overall STA is shown in black and the moment of the trigger spike is represented by the dashed line at T = 0 ms. (E) Left hand panel: Distributions of peak amplitude values, normalized to the amplitude for the shortest interval class. Right hand panel: distribution of peak latencies.

Mentions: Figure 1 illustrates how SITAs are constructed in a reverse correlation experiment. We recorded spikes from electroreceptors in response to Gaussian white noise stimulation (Fig. 1A) and constructed STAs of the stimulus-shape preceding spikes (Fig. 1B) as a function of interval duration. To this end, recorded spikes were divided in five classes based on the duration of their preceding interspike interval (Fig. 1C). Since the total number of spikes was about 75,000 and we divided spikes in 5 equally sized classes, each class consisted of approximately 15,000 spikes. SITA analysis is a generalization of the standard STA (which is the average of all SITA curves), and reveals to what extent stimulus patterns correlate with interval durations, rather than spike timings. Differences between SITA curves for different spike-interval durations imply additional structure in the spike-triggered ensemble that is not picked up by conventional STA analysis.


Spike-interval triggered averaging reveals a quasi-periodic spiking alternative for stochastic resonance in catfish electroreceptors.

Lankheet MJ, Klink PC, Borghuis BG, Noest AJ - PLoS ONE (2012)

Spike interval triggered averaging (SITA).(A) The recording setup. Stimulation currents are applied locally through a stimulation ring, while spikes from afferent are recorded from within the lumen of the electroreceptor. (B) Example of the reverse correlation technique. For each recorded spike the stimulus shape is analyzed in a directly preceding time interval (-Δt). For each measurement about 75,000 spikes were grouped in 5 classes with equal numbers of spikes in each class, based on the cumulative distribution of interspike interval durations (intervals preceding spikes). (C) Interspike interval distribution (bottom panel) and cumulative interspike interval distribution (top panel). Spike-triggered averages were generated for each class separately. (D) Overview of spike interval triggered averages (SITAs) for 26 electroreceptors recorded in 20 catfish. Colors indicate the different interval classes as shown in (C). Confidence intervals for each class represent ±2*SEM. The overall STA is shown in black and the moment of the trigger spike is represented by the dashed line at T = 0 ms. (E) Left hand panel: Distributions of peak amplitude values, normalized to the amplitude for the shortest interval class. Right hand panel: distribution of peak latencies.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3293861&req=5

pone-0032786-g001: Spike interval triggered averaging (SITA).(A) The recording setup. Stimulation currents are applied locally through a stimulation ring, while spikes from afferent are recorded from within the lumen of the electroreceptor. (B) Example of the reverse correlation technique. For each recorded spike the stimulus shape is analyzed in a directly preceding time interval (-Δt). For each measurement about 75,000 spikes were grouped in 5 classes with equal numbers of spikes in each class, based on the cumulative distribution of interspike interval durations (intervals preceding spikes). (C) Interspike interval distribution (bottom panel) and cumulative interspike interval distribution (top panel). Spike-triggered averages were generated for each class separately. (D) Overview of spike interval triggered averages (SITAs) for 26 electroreceptors recorded in 20 catfish. Colors indicate the different interval classes as shown in (C). Confidence intervals for each class represent ±2*SEM. The overall STA is shown in black and the moment of the trigger spike is represented by the dashed line at T = 0 ms. (E) Left hand panel: Distributions of peak amplitude values, normalized to the amplitude for the shortest interval class. Right hand panel: distribution of peak latencies.
Mentions: Figure 1 illustrates how SITAs are constructed in a reverse correlation experiment. We recorded spikes from electroreceptors in response to Gaussian white noise stimulation (Fig. 1A) and constructed STAs of the stimulus-shape preceding spikes (Fig. 1B) as a function of interval duration. To this end, recorded spikes were divided in five classes based on the duration of their preceding interspike interval (Fig. 1C). Since the total number of spikes was about 75,000 and we divided spikes in 5 equally sized classes, each class consisted of approximately 15,000 spikes. SITA analysis is a generalization of the standard STA (which is the average of all SITA curves), and reveals to what extent stimulus patterns correlate with interval durations, rather than spike timings. Differences between SITA curves for different spike-interval durations imply additional structure in the spike-triggered ensemble that is not picked up by conventional STA analysis.

Bottom Line: Here we show that catfish electroreceptors have adopted a fundamentally different strategy.In this regime stimuli modulate the interval between successive spikes rather than the instantaneous probability for a spike.This alternative for stochastic resonance combines threshold-free sensitivity for weak stimuli with similar sensitivity for excitations and inhibitions based on single interspike intervals.

View Article: PubMed Central - PubMed

Affiliation: Experimental Zoology, Wageningen University, Wageningen, The Netherlands. martin.lankheet@wur.nl

ABSTRACT
Catfish detect and identify invisible prey by sensing their ultra-weak electric fields with electroreceptors. Any neuron that deals with small-amplitude input has to overcome sensitivity limitations arising from inherent threshold non-linearities in spike-generation mechanisms. Many sensory cells solve this issue with stochastic resonance, in which a moderate amount of intrinsic noise causes irregular spontaneous spiking activity with a probability that is modulated by the input signal. Here we show that catfish electroreceptors have adopted a fundamentally different strategy. Using a reverse correlation technique in which we take spike interval durations into account, we show that the electroreceptors generate a supra-threshold bias current that results in quasi-periodically produced spikes. In this regime stimuli modulate the interval between successive spikes rather than the instantaneous probability for a spike. This alternative for stochastic resonance combines threshold-free sensitivity for weak stimuli with similar sensitivity for excitations and inhibitions based on single interspike intervals.

Show MeSH