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traditional averaging was the poorest among tested
methods.
The paper touches practical issues the neuropsy-
chology researchers are faced with during EEG/ERP
data processing and analyzing. Namely, it points out
the bottlenecks of the traditional averaging technique
used for the time-locked brain responses denoising.
The roots of these bottlenecks are connected to the
violation of the assumptions underlying the averag-
ing in real applications and insufficiently powerful
’decoding’ of the relevant information ’encrypted’ in
the data. The weighted averaging method addresses
the bottlenecks, which arise due to the violation of
the assumptions underlying traditional averaging. We
have shown that this strategy for improving the per-
formance and the reliability of the traditional averag-
ing technique can be derived based on different crite-
ria and, in particular, SNR and mean-square error as it
has been shown in (Hoke et al., 1984). ERPSUB tries
to eliminate the second type of the bottlenecks, which
come from the disability of the traditional averaging
to effectively extract from data the overall available
information related to ERP and noise discrimination.
ERPSUB ’decrypts’ more effectively this information
hidden in data, since it operates through all time, trial,
and channel dimensions.
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