Adaptation Modulates Spike-Phase Coupling Tuning Curve in the Rat Primary Auditory Cortex

Abstract

Adaptation is an important mechanism that causes a decrease in the neural response both in terms of local field potentials (LFP) and spiking activity. We previously showed this reduction effect in the tuning curve of the primary auditory cortex. Moreover, we revealed that a repeated stimulus reduces the neural response in terms of spike-phase coupling (SPC). In the current study, we examined the effect of adaptation on the SPC tuning curve. To this end, employing the phase-locking value (PLV) method, we estimated the spike-LFP coupling. The data was obtained by a simultaneous recording from four single-electrodes in the primary auditory cortex of 15 rats. We first investigated whether the neural system may use spike-LFP phase coupling in the primary auditory cortex to encode sensory information. Secondly, we investigated the effect of adaptation on this potential SPC tuning. Our data showed that the coupling between spikes' times and the LFP phase in beta oscillations represents sensory information (different stimulus frequencies), with an inverted bell-shaped tuning curve. Furthermore, we showed that adaptation to a specific frequency modulates SPC tuning curve of the adapter and its neighboring frequencies. These findings could be useful for interpretation of feature representation in terms of SPC and the underlying neural mechanism of adaptation.

Measuring Synchronization between Spikes and Local Field Potential Based on the Kullback–Leibler Divergence

“…where U is the uniform distribution, P is the data distribution, and N is the total number of bins. H(P) is the Shannon entropy mentioned in equation (6), and log N is the maximum possible entropy value, which represents a uniform distribution (when P(j) � 1/N, applicable to all bins). erefore, we define the MI by dividing the KL divergence of the observed spike distribution (P) and the uniform distribution (U) by log N, and the final MI is given by…”

“…where KL(U, P) is the KL divergence according to equation (6) and N is the total number of bins [31,32]. If spikes are uniformly distributed over the phase of LFP (i.e., P � U, which means there is no synchronization between the spikes and LFP), then MI � 0.…”

“…is phenomenon has been widely studied in the extracellular records of conscious animals [5]. is record can capture the spike activity, which is a short-term high-frequency signal and reflects more individual activities [6].…”

“…e spikes encode the rate and temporal distribution of these binary events [5]. LFP is another component of the extracellular signal, namely, the low-frequency part of the neural signal that reflects the synaptic activity of neighbouring neurons [6][7][8]. Recently, LFP has attracted increasing attention in the fields of neuroscience and neural engineering.…”

“…It is considered to be the sum of thousands of synaptic potential fluctuations around the recording electrode [5]. Synchronization between spikes and LFP has been observed in different cognitive functions and different brain regions, such as the prefrontal cortex [5,9] and the hippocampus [6,10,11]. In recent years, many neurophysiological studies have shown that there is a close relationship between spikes and the gamma-band LFP [9,12], and it has been shown that the phase locking between the spikes and LFP reflects vital physiological information.…”