Abstract
Functional Magnetic Resonance Imaging (fMRI) has proved to be a powerful technique for the analysis of the central autonomic control on the cardiovascular system. The carotid stimulation represents a viable non-invasive tool to investigate the brain areas involved in the central autonomic control. In this paper a resting-state fMRI protocol has been carried out on normal subjects, during bilateral carotid stimulation by neck suction using a custom MRI-compliant device. Two suction levels (60 mmHg and 10 mmHg) were applied in two consecutive sessions, using rectangular pulses with a duration of 8 s spaced by 4 s. To detect the brain region involved in processing the carotid baroreceptor efferent signals, a combined approach of independent component analysis (ICA) and spectral coherence (SC) has been used: ICs have been estimated from fMRI data using the GIFT toolbox, the SC between each IC and the neck stimulation signal has been computed, and finally we have identified the stimulus related ICs on the basis of the spectral coherence at the frequency of interest. SC greater than 0.5 were observed in all but one subjects, during the neck suction at 60 mmHg. The SC significantly dropped during the stimulation at 10 mmHg. Frequency analysis of the neck suction stimulation signal in conjunction with ICA of fMRI can identify the brain structures involved in the central processing and integration of afferent signals from the carotid baroreceptors in healthy human subjects.
Original language | English |
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Title of host publication | Computing in Cardiology |
Publisher | IEEE Computer Society |
Pages | 1005-1008 |
Number of pages | 4 |
Volume | 41 |
Edition | January |
Publication status | Published - 2014 |
Event | 41st Computing in Cardiology Conference, CinC 2014 - Cambridge, United States Duration: Sep 7 2014 → Sep 10 2014 |
Other
Other | 41st Computing in Cardiology Conference, CinC 2014 |
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Country/Territory | United States |
City | Cambridge |
Period | 9/7/14 → 9/10/14 |
ASJC Scopus subject areas
- Cardiology and Cardiovascular Medicine
- Computer Science(all)