The Oscillation Score: An Efficient Method for Estimating Oscillation Strength in Neuronal Activity

Abstract

We present a method that estimates the strength of neuronal oscillations at the cellular level, relying on autocorrelation histograms computed on spike trains. The method delivers a number, termed oscillation score, that estimates the degree to which a neuron is oscillating in a given frequency band. Moreover, it can also reliably identify the oscillation frequency and strength in the given band, independently of the oscillation in other frequency bands, and thus it can handle superimposed oscillations on multiple scales (theta, alpha, beta, gamma, etc.). The method is relatively simple and fast. It can cope with a low number of spikes, converging exponentially fast with the number of spikes, to a stable estimation of the oscillation strength. It thus lends itself to the analysis of spike-sorted single-unit activity from electrophysiological recordings. We show that the method performs well on experimental data recorded from cat visual cortex and also compares favorably to other methods. In addition, we provide a measure, termed confidence score, that determines the stability of the oscillation score estimate over trials.

Synchrony Makes Neurons Fire in Sequence, and Stimulus Properties Determine Who Is Ahead

“…Oscillation score. The oscillation strength in a data set was estimated by computing its oscillation score (OS) (Muresan et al, 2008). To this end, an autocorrelation histogram (ACH) was computed with 1 ms resolution for each unit and for each investigated stimulus condition.…”

“…Thus, the overall oscillation strength for a data set was estimated simply as the average OS for all individual ACHs. In accordance with the recommendations given by Muresan et al (2008), data sets with an average OS Ն 5 were classified as oscillatory, and data sets with an OS Ͻ 5 as nonoscillatory. For the responses to gratings drifting in different directions, seven data sets were classified as nonoscillatory (OS, 1.5-4.8; mean, 3.2; median, 3.5) and three as oscillatory (OS,6.0,6.3,and 7.2).…”

“…Oscillation strength was assessed by calculating the OS (Muresan et al, 2008) for each neuron, and the pMI-values of both firing times and rates covered a broader range in neurons with weak oscillations (OS Ͻ ϳ4) than in those with strong oscillations (OS Ͼ ϳ6) (Fig. 7 A, B) (oscillation strength and frequency of all neurons are shown in supplemental Fig.…”

The InfoPhase Method or How to Read Neurons with Neurons

“…In addition, autocorrelation analysis of the source spike trains (Fig. 5C) revealed oscillatory activity with an oscillation period around 25-27 ms (beta-high band [8]) suggesting that the oscillation cycles might play an important role in enabling the coding of fine-grained temporal information in the source neurons [6].…”

“…In this latter case, temporal phase patterns may even be expressed within a single gamma cycle, with more excited neurons firing earlier relative to the onset of the cycle than less excited ones. Furthermore, we now know that there is a tight interplay between the expression of neuronal oscillations and temporal coding in the cortex [7], with rhythms expressed in different frequency bands [8]. Even further, temporal codes could be defined beyond single-spike timing.…”