Human Processing of Short Temporal Intervals as Revealed by an ERP Waveform Analysis

To clarify the time course over which the human brain processes information about durations up to ∼300 ms, we reanalyzed the data that were previously reported by Mitsudo et al. (2009) using a multivariate analysis method. Event-related potentials were recorded from 19 scalp electrodes on 11 (nine original and two additional) participants while they judged whether two neighboring empty time intervals – called t1 and t2 and marked by three tone bursts – had equal durations. There was also a control condition in which the participants were presented the same temporal patterns but without a judgment task. In the present reanalysis, we sought to visualize how the temporal patterns were represented in the brain over time. A correlation matrix across channels was calculated for each temporal pattern. Geometric separations between the correlation matrices were calculated, and subjected to multidimensional scaling. We performed such analyses for a moving 100-ms time window after the t1 presentations. In the windows centered at <100 ms after the t2 presentation, the analyses revealed the local maxima of categorical separation between temporal patterns of perceptually equal durations versus perceptually unequal durations, both in the judgment condition and in the control condition. Such categorization of the temporal patterns was prominent only in narrow temporal regions. The analysis indicated that the participants determined whether the two neighboring time intervals were of equal duration mostly within 100 ms after the presentation of the temporal patterns. A very fast brain activity was related to the perception of elementary temporal patterns without explicit judgments. This is consistent with the findings of Mitsudo et al. and it is in line with the processing time hypothesis proposed by Nakajima et al. (2004). The validity of the correlation matrix analyses turned out to be an effective tool to grasp the overall responses of the brain to temporal patterns.