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Abstract:
Many event related potential (ERP) correlates of attention
are well established. There is also growing evidence that attention
has correlates in electroencephalography (EEG) frequency
distributions. However, frequency representations of EEG obtained
with the Fourier transformation usually discard latency. Windowed
Fourier transforms preserve latency information, but only with the
temporal resolution of the window. Our goal was to use wavelet
transforms to investigate the frequency distribution of the EEG
with fine temporal resolution. The 128-channel EEG was recorded
during an alternating dichotic listening task. Within each ear,
high and low tones were presented according to a standard oddball
paradigm. Subjects were instructed to attend to the rare (high)
tones in only one ear. Wavelet transformations of single sweeps
were averaged over sweeps to produce an ERW, or event related
wavelet. Unlike the ERP, which displays signal amplitude as a
function of time, the ERW displays signal energy as a function of
time and scale. Because the scales map to frequency bands, the ERW
gives insight into the distribution of the EEG's energy in both
time and frequency. We compared the ERW to different stimuli types.
In summary, we found temporally-constrained components in several
of the EEG frequency bands that differ depending on stimulus type
and laterality. In conclusion, ERW differences suggest a more
comprehensive investigation of the temporal dynamics of the EEG's
frequency components in the presence and absence of selective
attention.
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