The Role Of Coincidence-Detector Neuron In Subthreshold Signal Detection In Noise

Neurons transmit information by complex spike sequences that reflect both the in-trinsic dynamics and the features of stimulus. However, the coding scheme used in this process is not fully understood, and is often a highly argued issue. One view considers the cortical neurons as an integrate-and-fire device. In this simple scheme, how neurons encode and process the stable propagation of spiking in cortical neural networks is in-dicated by their average firing rate; others suggested that neurons in the cortex work es-sentially as coincidence detectors, and relay preferentially synchronized synaptic inputs and the exact timing of spikes, which has been shown to potentially provide information in addition to the spike rate as the coding scheme.Here, we propose that coincidence detection, one of the ways to describe the func-tionality of a single neural cell, can improve the reliability and the precision of signal detection through detection of presynaptic input synchrony. Using a simplified neu-ronal network model composed of dozens of integrate-and-fire neurons and a single coincidence-detector neuron, we show how the network reads out the subthreshold noisy signals reliably and precisely. We find suitable pairing parameters, the threshold and the detection time window of the coincidence-detector neuron, that optimize the precision and reliability of the neuron.Furthermore, it is observed that the refractory period induces an oscillation in the spontaneous firing, but the neuron can inhibit this activity and improve the reliability and precision further. In the case of intermediate intrinsic states of the input neuron, the network responds to the input more efficiently. These results present the critical link between spiking synchrony and noisy signal transfer, which is utilized in coincidence detection, resulting in enhancement of temporally sensitive coding scheme.Multicell electrophysiological searches have shown that the synchronous discharge of neurons distributed in different structures of the cerebral cortex, hippocampal forma-tion, and thalamus. However, Latencies, resulting from the infinite conduction velocity of axons. can amount to several tens of milliseconds between the firing in a presynap-tic cell and the elicitation of a postsynaptic potential. Athough such temporal delays, the connection between neurons can leads to zero time lag synchrony, how the neurons adapt to such synchrony?Here, we constructe a neuron network, each of which including a self-feedback synapse (autaptic), and study the mechanism of zero time lag neuronal synchrony. In general, synapses is a connection of signal transformation between different neurons. However, autapse is a self-feedback loop to the same neuron. Why the neuron relay the information to itsself? Experiments results have shown that autapses might play important roles in brain function, for examples, it can adapt the firing times of a neuron and thereby paces other neruonal circuit, and it may allow a kind of regional self-control.Our researches show that the neruons coupled by the excitory synapse could reach to the zero time synchrony, thought in the long time delay, and stabilize in this state.This mechanism is based on the adapt ability of the postsynaptic neuron to the firing latency of the neuron. And it also depends on the firing neuron to relay the action potentials not only to the postsynaptic neuron but also to itsself symmetrically. But the effects of postsynaptic potential on the coupling neuron are different from itself. The self-feedback compensate the initial phase difference, and both neurons end up firing isochronously, a stable state.On the other hand, because of the refractory period, the synchronous index shows periodic changes. To gain the full synchronization the critical coupling strength must be large enough if the self-feedbacd delay time is shorter the reh refractory period. This is due to the fact that during this time the neuron is rather insensitive to any stimuli. This resuls reveal that the autapse can adapt the neuronal activites and the accumulation of such mechanism to the interspike intervals of the neurons in the network lead the zero time lag synchrony.