Effects of the network structure and coupling strength on the noise-induced response delay of a neuronal network

Özer, Mahmut; Uzuntarla, Muhammet

doi:10.1016/j.physleta.2008.05.003

Cited by 32 publications

(25 citation statements)

References 46 publications

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“…Many recent theoretical and experimental studies have been concerned with the inhibitory effect of weak noise on neuronal spiking (Tuckwell 2005;Paydarfar et al 2006;Ozer and Graham 2008;Ozer and Uzuntarla 2008). Such observations are related to the general phenomena of stimulus-induced cessation of firing (Forger and Paydarfar 2004;Calitoiu et al 2008).…”

Section: Introductionmentioning

confidence: 99%

The effects of various spatial distributions of weak noise on rhythmic spiking

Tuckwell

Jost

2010

J Comput Neurosci

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We consider the response of the classical Hodgkin-Huxley (HH) spatial system in the weak to intermediate noise regime near the bifurcation to repetitive spiking. The deterministic component of the input (signal) is restricted to a small segment near the origin whereas noise, with parameter σ, occurs either only in the signal region or throughout the whole neuron. In both cases small noise inhibits the spiking and there is a minimum in the spike counts at σ ≈ 0.15. At the same value of σ, the variance of the spike counts undergoes a pronounced maximum. For spatially restricted noise, the spike count continues to increase beyond the minimum until σ=0.5, but in the case of spatially extended noise the spike count begins to decline around σ=0.35 to give a local maximum. For both spatial distributions of noise, the variance of the spike count is found to also have a local minimum at about σ=0.4. Examples are given of the probability distributions of the spike counts and the spatial distributions of spikes with varying noise level. The differences in behaviours of the spike counts as noise increases beyond 0.3 are attributable to noise-induced spiking outside the signal region, which has a larger probability of occurrence when the noise is over an extended region. This aspect is investigated by ascertaining the probability of noise-induced spiking as a function of noise level and examination of the corresponding latency distributions. These findings prompt a definition of weak noise in the standard HH model as that for which the probability of secondary phenomena is negligible, which occurs when σ is less than about 0.3. Finally, if signal and weak (σ<0.3) noise are applied on disjoint intervals, then the noise has no effect on the instigation or propagation of spikes, no matter how large its region of application. These results are expected to apply to type 2 neurons in general, including the majority of cortical pyramidal cells.

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Section: Introductionmentioning

confidence: 99%

The effects of various spatial distributions of weak noise on rhythmic spiking

Tuckwell

Jost

2010

J Comput Neurosci

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“…For the mechanism to work, however, the coupling strength has to be sufficiently strong, so that the faster response of the high-degree neurons can be detected back also by the low-degree neurons in a timely manner. Ozer and Uzuntarla [29] have arrived at qualitatively similar findings by using a different network topology, small-world neuronal network, indicating that strong coupling between neurons reduces the NDD effect regardless of the network topology. Increasing the average degree also has a positive impact, but its magnitude is only a fraction of that of the high coupling strengths.…”

mentioning

confidence: 68%

Can scale-freeness offset delayed signal detection in neuronal networks?

Uzun¹,

Özer²,

Perc³

2014

EPL

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-First spike latency following stimulus onset is of significant physiological relevance. Neurons transmit information about their inputs by transforming them into spike trains, and the timing of these spike trains is in turn crucial for effectively encoding that information. Random processes and uncertainty that underly neuronal dynamics have been shown to prolong the time towards the first response in a phenomenon dubbed noise-delayed decay. Here we study whether Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise might have shorter response times to external stimuli just above threshold if placed on a scale-free network. We show that the heterogeneity of the interaction network may indeed eradicate slow responsiveness, but only if the coupling between individual neurons is sufficiently strong. Increasing the average degree also favors a fast response, but it is less effective than increasing the coupling strength. We also show that noise-delayed decay can be offset further by adjusting the frequency of the external signal, as well as by blocking a fraction of voltage-gated sodium or potassium ion channels. For certain conditions, we observe a double peak in the response time depending on the intensity of intrinsic noise, indicating competition between local and global effects on the neuronal dynamics.

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“…Previous studies on noisy latencies have considered computations of the mean latency in the deterministic and large noise regime (Tuckwell and Wan 2005), the latter being characterized by an increase of mean latency, called "noise delay decay" (Pankratova et al 2005;Oser and Uzuntarla 2008). A detection enhancement of subthreshold pulses due to internal noise has been investigated in Chen et al (2008).…”

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confidence: 99%

Intrinsic variability of latency to first-spike

2010

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The assessment of the variability of neuronal spike timing is fundamental to gain understanding of latency coding. Based on recent mathematical results, we investigate theoretically the impact of channel noise on latency variability. For large numbers of ion channels, we derive the asymptotic distribution of latency, together with an explicit expression for its variance. Consequences in terms of information processing are studied with Fisher information in the Morris-Lecar model. A competition between sensitivity to input and precision is responsible for favoring two distinct regimes of latencies.

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Effects of the network structure and coupling strength on the noise-induced response delay of a neuronal network

Cited by 32 publications

References 46 publications

The effects of various spatial distributions of weak noise on rhythmic spiking

The effects of various spatial distributions of weak noise on rhythmic spiking

Can scale-freeness offset delayed signal detection in neuronal networks?

Intrinsic variability of latency to first-spike

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