Synaptic modifications depend on synapse location and activity: a biophysical model of STDP

Area of Science:

• Computational Neuroscience
• Synaptic Plasticity

Background:

• Spike-timing-dependent plasticity (STDP) modifies synaptic strength based on the precise timing of pre- and post-synaptic neuronal signals.
• Existing models often focus solely on spike timing, potentially overlooking other crucial signal characteristics.

Purpose of the Study:

• To present a biophysical model of STDP that incorporates the influence of signal shapes on synaptic modifications.
• To investigate how signal morphology and neuronal activity patterns affect synaptic potentiation and depression.

Main Methods:

• Development of a Hebbian learning rule correlating NMDA synaptic conductance with post-synaptic signals.
• Simulation using real neuronal input signals and multi-spike patterns.
• Analysis of synaptic modifications based on signal shape and dendritic location.

Main Results:

• The model successfully reproduces the generic STDP weight change curve using realistic neuronal inputs and multi-spike combinations.
• The shape of the STDP curve is demonstrated to be highly dependent on the morphology of depolarizing membrane potentials.
• Synaptic changes are predicted to be location-dependent due to variations in membrane potentials across the dendritic tree.
• The STDP weight change curve is shown to be activity-dependent when considering complex spike patterns.

Conclusions:

• Synaptic plasticity is influenced not only by spike timing but also by the shapes of neuronal signals.
• Neuronal signal morphology and dendritic location play significant roles in shaping synaptic modifications.
• The developed biophysical model provides a more comprehensive understanding of STDP and its dependence on neuronal activity patterns.