Synaptic Information Transmission in a Two-State Model of Short-Term Facilitation

Area of Science:

• Neuroscience
• Computational Neuroscience
• Information Theory

Background:

• Synaptic transmission involves neurotransmitter release, which is probabilistic and influenced by action potentials.
• Synaptic plasticity, including short-term facilitation, dynamically alters release probability based on recent activity.
• Quantifying information transmission in facilitating synapses is crucial for understanding neural computation.

Purpose of the Study:

• To derive bounds for information transmission rates in a model of short-term synaptic facilitation.
• To investigate the relationship between facilitation, synchronous and asynchronous release, and information transfer.
• To determine the energy-information trade-off in facilitating synapses.

Main Methods:

• Modeling the synapse as a two-state binary asymmetric channel.
• Analyzing the impact of action potentials on synaptic state transitions (facilitated vs. baseline).
• Deriving rigorous lower and upper bounds for mutual information rate.

Main Results:

• Information transmission bounds depend on asynchronous and synchronous release parameters.
• Increased synchronous facilitation enhances mutual information rate, but high intrinsic synchronous release probability degrades it.
• The energy-normalized information rate is robust to changes in facilitation strength, unlike the raw information rate.

Conclusions:

• Short-term synaptic facilitation has a complex effect on information transmission, dependent on release parameters.
• Facilitating synapses exhibit an energy-information trade-off, with energy-normalized information being a stable measure.
• Findings provide insights into the energetic costs and information processing capabilities of neural synapses.