Heart Rate Variability (HRV) is a measure of the variation
in time between successive heartbeats, reflecting the influence of the au-
tonomic nervous system on the heart. It can provide insights into the bal-
ance between sympathetic and parasympathetic activity. The relation-
ship between autonomic nervous system function, specifically parasym-
pathetic activity, and certain learning disorders, including dyslexia, is
currently under study. In this paper, we propose the use of explain-
able techniques to explore the relationships between HRV markers and
local functional brain activity, estimated by cross-frequency coupling
(CFC) from electroencephalography (EEG) signals recorded while audi-
tory stimuli were applied to 7-year-old children. We analyze EEG data to
examine the phase-to-phase brainwave coupling and use machine learn-
ing tools such as XGBoost and Shapley values to reveal brain regions that
most contribute to different HRV features, with a focus on parasympa-
thetic activity. Our findings suggest that HRV features related to stress
can explain differential activations in the auditory cortex (Brodmann
areas 39 and 40) during auditory stimulation in dyslexic children.