Structural plasticity controlled by calcium based correlation detection. helias@bccn.uni-freiburg.de.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Synaptic Plasticity

Background:

• Hebbian learning requires detecting correlations between pre- and postsynaptic neuronal firing.
• Spine calcium concentration is a promising candidate for this correlation detection mechanism.
• NMDA receptors are implicated in mediating calcium signals sensitive to spike timing.

Purpose of the Study:

• To develop a quantitative model of synaptic correlation detection.
• To investigate the role of NMDA receptor calcium influx under realistic neural activity.
• To analyze how correlation detection influences synapse dynamics and network structure.

Main Methods:

• Developed a quantitative model of synaptic calcium influx through NMDA receptors.
• Analyzed the model under conditions of irregular, correlated pre- and postsynaptic spiking.
• Investigated the impact of a thresholding mechanism on correlation detection and synapse plasticity.

Main Results:

• A simple thresholding mechanism reliably detects correlated neural activity at physiological firing rates.
• This mechanism is sensitive to correlations across multiple afferent synapses through cooperation and competition.
• The model demonstrates control of synapse formation and elimination, leading to firing rate homeostasis.

Conclusions:

• Synaptic calcium influx via NMDA receptors provides a robust mechanism for detecting neural correlations.
• Correlation detection regulates synapse plasticity, contributing to network stability and homeostasis.
• The model explains how correlated inputs shape synaptic connectivity and neuronal network structure.