The Influence of Peripheral Physiological Parameters on the Functional Connectivity Analysis of the Lateral Prefrontal Cortex Using Functional Near- Infrared Spectroscopy
Functional near-infrared spectroscopy (fNIRS) is a non-invasive method to measure changes in the blood oxygenation level of the brain and therewith detect neural activity. Since near-infrared light has to traverse superficial layers before reaching the cortex, the fNIRS signal also contains extracerebral signal components and is therefore dependent on peripheral physiological processes, such as the arterial blood pressure, breathing, and heartbeat.
In this master’s thesis functional connectivity analysis with partial directed coherence (PDC) has been used to study the influence of peripheral physiology on the fNIRS signal in the lateral prefrontal cortex (lPFC) in two separate studies. They were based on the finding that the lPFC is hierarchically organized along a rostro-caudal axis. The first study was carried out using data from patients with a stenosis of the internal carotid artery (ICA) and changes of the resting state functional connectivity (RSFC) in the affected and unaffected hemisphere were analyzed. In the second study fNIRS with resolution in depth was used to differentiate hemodynamic processes in the extra- and intracerebral tissues by comparing the resting state-like functional connectivity.
Functional connectivity analysis of fNIRS signals with PDC appeared to be robust against physiological noise, since neither the exclusion of the influence of aBP nor the induction of blood pressure oscillations through deep breathing could affect the predominant direction of RSFC. Moreover, ICA stenosis did not cause strong changes in the pattern of interaction between the sub-regions, which shows that PDC analysis reliably pictures functional connectivity independent of vascular changes. The finding that the strength of the directed interaction was stronger in signals from the cortex gave further evidence for the validity of the connectivity analysis.
With this master’s thesis it could be shown that using fNIRS and PDC is a valid and sensitive method to assess RSFC of the lPFC and robust against influences from peripheral physiological parameters.
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