Novel method for reliably measuring spontaneous postsynaptic potentials/currents in whole- cell patch clamp recordings in the central nervous system

Abstract

AbstractIn chemical synapses of the central nervous system (CNS) an information unit is transmitted via the presynaptic release of a neurotransmitter vesicle, a quantum, eliciting a postsynaptic membrane electric response of a certain amplitude, a quantal size. This key determinant of neural computation has not been reliably measured due to the nature of synaptic communication and technical limitations of electrophysiological recordings in the CNS. Measuring amplitudes of spontaneous postsynaptic currents (sPSCs) or potentials (sPSPs) at the cell soma potentially offers a technically straight forward way to estimate the quantal size as these miniature responses (minis) are ellicited by the spontaneous release of a single neurotransmitter vesicle. However, somatically recorded minis are massively attenuated and, for the most part, are indistinguishable from background noise fluctuations. For them to be accurately estimated, a revised method would have to isolate the noise component. As the first step in devising such a method, we developed and described a novel sPSP/sPSC detection algorithm as part of our quantal analysis software called ‘minis’. We tested the performance of the algorithm in detecting real and simulated minis in rat cortical slice whole-cell recordings and compared it to other most commonly used similar detection algorithms in the field of the synaptic function research. This benchmarking analysis revealed superior detection performance by our algorithm. The release version of the algorithm also offers great flexibility as it can be controlled through graphical and programming interfaces making it suitable for the needs of most individual researchers studying the central synapse function.Significance statementBeing able to measure accurately the electrical size of synapses in the brain is critical for understanding neural computations. Offering a novel algorithm for measuring properties of spontaneous synaptic signalling is an important first step in doing so. By its qualities of being transparent and objectively evaluated, this algorithm sets an important methodological standard for comparative assessment of other popular algorithms in the field of the synaptic function research. Because of its superior performance and flexibility, the algorithm also offers a technological improvement greatly useful to individual researchers in the field. Finally, its evaluation process highlighted common methodological pitfalls surrounding the spontaneous synaptic signalling research that hopefully could reduce their future impact.