Details

Autor(en) / Beteiligte

• de Munck, J.C.
• Gonçalves, S.I.
• Faes, Th.J.C.
• Kuijer, J.P.A.
• Pouwels, P.J.W.
• Heethaar, R.M.
• Lopes da Silva, F.H.

Titel

A study of the brain's resting state based on alpha band power, heart rate and fMRI

Ist Teil von

• NeuroImage (Orlando, Fla.), 2008-08, Vol.42 (1), p.112-121

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2008

Quelle

MEDLINE

Beschreibungen/Notizen

• Considering that there are several theoretical reasons why fMRI data is correlated to variations in heart rate, these correlations are explored using experimental resting state data. In particular, the possibility is discussed that the “default network”, being a brain area that deactivates during non-specific general tasks, is a hemodynamic effect caused by heart rate variations. Of fifteen healthy controls ECG, EEG and fMRI were co-registered. Slice time dependent heart rate regressors were derived from the ECG data and correlated to fMRI using a linear correlation analysis where the impulse response is estimated from the data. It was found that in most subjects substantial correlations between heart rate variations and fMRI exist, both within the brain and at the ventricles. The brain areas with high correlation to heart rate are different from the “default network” and the response functions deviate from the canonical hemodynamic response function. Furthermore, a general negative correlation was found between heart beat intervals (reverse of heart rate) and alpha power. We interpret this finding by assuming that subject's state varies between drowsiness and wakefulness. Finally, given this large correlation, we re-examined the contribution of heart rate variations to earlier reported fMRI/alpha band correlations, by adding heart rate regressors as confounders. It was found that inclusion of these confounders most often had a negligible effect. From its strong correlation to alpha power, we conclude that the heart rate variations contain important physiological information about subject's resting state. However, it does not provide a full explanation of the behaviour of the “default network”. Its application as confounder in fMRI experiments is a relatively small computational effort, but may have a substantial impact in paradigms where heart rate is controlled by the stimulus.