Intrinsic variability of latency to first-spike

Area of Science:

• Computational neuroscience
• Theoretical neuroscience
• Ion channel biophysics

Background:

• Neuronal spike timing variability is crucial for understanding neural coding mechanisms.
• Latency coding, a proposed neural code, relies on the precise timing of neuronal action potentials.
• The influence of biophysical noise, particularly from ion channels, on spike timing variability remains a key research question.

Purpose of the Study:

• To theoretically investigate the impact of channel noise on neuronal latency variability.
• To derive mathematical expressions for latency distribution and variance under noisy conditions.
• To explore the consequences of this variability for neural information processing using a specific model.

Main Methods:

• Utilizing recent mathematical results to analyze latency variability.
• Deriving asymptotic distributions for latency in systems with a large number of ion channels.
• Calculating the explicit expression for latency variance.
• Applying Fisher information analysis within the Morris-Lecar neuron model.

Main Results:

• Derived the asymptotic distribution of neuronal latency influenced by channel noise.
• Provided an explicit mathematical expression for the variance of latency.
• Identified a trade-off between input sensitivity and timing precision.
• Demonstrated that this competition leads to two distinct latency regimes in the Morris-Lecar model.

Conclusions:

• Channel noise significantly impacts neuronal latency variability and information processing.
• The derived mathematical framework quantifies the effect of noise on latency precision.
• Two distinct operational regimes for neuronal latency emerge due to competing factors of sensitivity and precision.