2.4 Data Preprocessing and Analysis
Hemodynamic data was preprocessed with a combination of nirsLAB (an
analysis software that comes with the NIRSport system), Homer2 (Huppert
et al., 2009) and custom scripts in MATLAB R2017B. The raw data was
converted into optical densities. The channels that fell outside the
80-140 dB optical density range were excluded from further analysis.
Motion artefacts were corrected via the wavelet method (Cooper et al.,
2012). Subsequently, data was band-pass filtered with a third-order
Butterworth filter with cut-off frequencies of 0.05 and 0.2 Hz. Since
the system did not feature short-channel separation, a PCA filter was
also used to remove non-cortical signals that remained within the
band-pass filter frequency range. Lastly, preprocessed optical densities
were converted into oxy-hemoglobin (HBO) and deoxy-hemoglobin (HBR)
concentrations. Only HBO data was used in further analysis as it was
claimed that cortical activation is better reflected by HBO (Dravida et
al., 2017; Watanabe et al., 2002).
Accuracy and reaction times were computed for each condition and
subject. For trials in which subjects did not give an answer within
3-second long response window, reaction time was set as 3
seconds. A paired sample t-test was used to analyze the
accuracy and reaction time data.
To analyze hemodynamic activity, fourteen seconds long segments were
generated by using the two seconds pre-stimulus baseline window and
twelve seconds post-stimulus activity windows for each trial. Then, the
segments were detrended and classified as either SRC or ORC.
Subsequently, the average across trials was computed to generate single
SRC and single ORC timeseries in each fNIRS channel of each subject.
Lastly, the hemodynamic activity induced by conditions was measured by
computing the hemodynamic activity strength (HAS) (Mutlu et al., 2020)
with the following equation:
\begin{equation}
HAS=\frac{\text{mean}_{\text{act}}-\text{mean}_{\text{base}}}{\text{std}_{\text{base}}}\nonumber \\
\end{equation}where meanact denotes the average HBO
concentration of a three seconds long window created around the peak HBO
value found within the post-stimulus 2 and 8 seconds window;meanbase and stdbasedenote the average and standard deviation of two seconds long
pre-stimulus baseline HBO concentration, respectively. As a result, each
subject had a 22 x 2 (channel x condition ) matrix consisting of
respective HAS values.
Two levels of analysis were performed on HAS parameter: within-condition
and between-conditions. For within-condition analysis, a channel-based
one-sample t-test was used to identify the brain regions showing
significant hemodynamic activity for each condition, while a
channel-based paired sample t-test was used to compare the brain
activity between conditions. Channel-based analysis was preferred, as it
was claimed that different brain regions have different optical
properties which can lead to systematic bias and may cause
non-comparable signal quality and/or intensity across different channels
(Kujach et al., 2018; Yanagisawa et al., 2010). All statistical analyses
were conducted in MATLAB R2017B.