Postsynaptic Potential Energy as Determinant of Synaptic Plasticity

Area of Science:

• Neuroscience
• Computational Biology
• Biophysics

Background:

• Neuronal activity control by metabolic energy is established.
• The role of metabolic energy alone in determining synaptic plasticity outcomes is unclear.

Purpose of the Study:

• To propose a computational model of synaptic plasticity entirely governed by energy.
• To establish a quantitative relationship between synaptic plasticity and postsynaptic potential energy.

Main Methods:

• Developed a computational model where synaptic weight is proportional to the difference between baseline and suprathreshold potential energies.
• Incorporated maximum energy supply as a constraint on synaptic weight.

Main Results:

• The energy constraint enhances synaptic plasticity performance and eliminates hard boundaries for synaptic weights.
• The model successfully reproduces classical experiments in homosynaptic and heterosynaptic plasticity.
• The model elucidates the interaction between Hebbian and homeostatic plasticity at the cellular level.

Conclusions:

• Metabolic energy alone can determine synaptic plasticity outcomes.
• Homeostatic plasticity operates on multiple timescales, driven by heterosynaptic plasticity and energy supply constraints.
• The model provides a unified framework for understanding synaptic plasticity mechanisms.