An algorithm for high-resolution detection of postsynaptic quantal events in extracellular records

Area of Science:

• Neuroscience
• Computational Biology
• Biophysics

Background:

• Extracellular recordings capture postsynaptic quantal events, crucial for understanding neurotransmission.
• Quantal analysis requires precise detection of asynchronous neurotransmitter release.
• Existing methods may lack accuracy or resolution for individual quanta.

Purpose of the Study:

• To develop and validate a software package for detecting and measuring extracellularly recorded postsynaptic quantal events.
• To assess the accuracy and resolution of the developed algorithm for analyzing neurotransmitter release.

Main Methods:

• Development of a software algorithm based on identifying monotonic regions in differentiated current signals.
• Utilizing recorded and simulated postsynaptic responses for algorithm verification.
• Testing the algorithm's ability to detect individual neurotransmitter quanta.

Main Results:

• The algorithm accurately detects up to six individual quanta within a 20 ms timeframe.
• Achieved a high temporal resolution of 0.5-1.0 ms for quantal event detection.
• Demonstrated accuracy in identifying small inflections and peaks corresponding to postsynaptic responses.

Conclusions:

• The developed software package provides a reliable tool for the quantitative analysis of postsynaptic quantal events.
• This advancement facilitates more precise investigations into the dynamics of asynchronous neurotransmitter release.
• The algorithm's resolution supports detailed studies of synaptic transmission mechanisms.