Noise-induced properties of active dendrites

Area of Science:

• Neuroscience
• Computational Neuroscience
• Biophysics

Background:

• Dendrites are critical for neuronal input integration in vivo.
• Active dendrites with calcium channels exhibit complex dynamics.
• Studying dendrites with sparse inputs may miss in vivo-like dynamic behaviors.

Purpose of the Study:

• To investigate the dynamics of active dendritic compartments under in vivo-like fluctuating input.
• To understand the role of synaptic noise in dendritic integration.
• To explore noise-induced phenomena like nonmonotonicity and bistability.

Main Methods:

• Utilized a single-compartment model of an active dendrite with fast and slow calcium channel activation.
• Introduced in vivo-like fluctuating input to the model.
• Analyzed input-output relationships under both noisy and noiseless conditions.
• Employed numerical simulations for a multicompartment model neuron.

Main Results:

• Noise induced nonmonotonic input-output relationships in models with fast calcium activation.
• Noise induced bistability in the input-output relation for models with slow calcium activation.
• Stochastic switching extended the timescales of bistable dynamics significantly beyond deterministic predictions.
• Bistability persisted in a multicompartment model with realistic synaptic input.

Conclusions:

• Realistic synaptic input drives sustained nonlinear dendritic integration.
• Synaptic noise is a fundamental factor in dendritic input processing.
• Active dendrites exhibit complex, noise-dependent dynamics crucial for neural function.