Period doubling behavior in human steady state visual evoked potentials

Abstract

Objective. Previous human steady state visual evoked potential (SSVEP) experiments have yielded different results regarding the range of stimulus frequencies in which period doubling (PD) behavior is observed. This study aims at obtaining experimental and statistical data regarding the frequency range of PD generation and also investigates other characteristics of PD. Approach. In two sets of experiments, seven subjects were presented a sinusoidal flickering light stimulus with frequencies varying from 15 to 42 Hz. To observe the short term variations in PD generation, another set of 5 successive experiments were performed on five subjects with 10 min breaks in between. To obtain the SSVEP responses, filtering, signal averaging and power spectral density (PSD) estimation were applied to the recorded electroencephalogram. From the PSD estimates, subharmonic occurrence rates were calculated for each experiment and were used along with ANOVA for interpreting the outcomes of the short term repeatability experiments. Main results. Although fundamental (excitation frequency) and second harmonic components appear in almost all SSVEP spectra, there is considerable inter-subject and intra-subject variability regarding PD occurrence. PD occurs for all stimulus frequencies from 15 to 42 Hz when all subjects are considered together. Furthermore, the statistical analyses of short term repeatability experiments suggest that in the short term, PD generation is consistent when all frequencies are considered together but for a single frequency significant short term differences occur. There also is considerable variation in the ratio of subharmonic amplitude to fundamental amplitude across different frequencies for a given subject. Significance. Important results and statistical data are obtained regarding PD generation. Our results indicate that modeling studies should attempt to generate PD for a broader range of stimulus frequencies. It is argued that SSVEP based brain–computer interface applications would likely benefit from the utilization of subharmonics in classification.