Artificial neural network analysis of Prefrontal fNIRS Blood Oxygenation Recordings
Research Square (Research Square)(2023)
Abstract
Abstract Noninvasive functional near infra-red spectroscopy (fNIRS) measuring brain oxygenated (O 2 Hb) and deoxygenated hemoglobin (HHb) is a promising technique for studying dementia diseases. fNIRS signals are determined by cerebral and extracerebral factors as for instance neuronal activity, degree of neurovascular coupling (NVC), blood flow dependency on heart rate (HR), ventilation controlling blood oxygenation (SaO 2 ) or autonomic nerve activity (ANA). These factors regulate different body functions such as vascular resistance in coordination with the brain. The simultaneous measurement of as many as possible anatomical and physiological factors during fNIRS of the brain is a prerequisite to interpret fNIRS signals with respect to the degree of brain tissue oxygenation. We measured brain O 2 Hb-HHb relation by fNIRS and four bipolar EEG recordings simultaneously with HR, blood volume changes, SaO 2 and galvanic skin resistance as ANA marker. We analyzed the EEG recordings by a Fourier power analysis (delta, theta, alpha, beta, gamma frequencies). All modalities together resulted finally in 24 parameters. We investigated their probable influence on the fNIRS brain O 2 Hb-HHb signal. The importance of each parameter for the fNIRS signal was assessed by nonlinear regression using an artificial neural network (ANN) analysis as a new tool of fNIRS signal interpretation. We applied fNIRS to 5 healthy control patients and to 5 patients with brain disorders (BD) known to have a disturbed NVC as for instance described for Alzheimer disease. The fNIRS recordings of brain O 2 Hb and HHb of control patients responding to different task challenges like breath holding, odor presentation, skin touching or listening to music is mainly influenced by SaO 2 and HR changes masking NVC signals due to low EEG power frequency activities as assessed by ANN. The fNIRS recordings of brain O 2 Hb and HHb changes of BD patients responding to the different task challenges, however, is mainly influenced by high gamma and low theta EEG power frequencies as expression of high NVC activity. Brain O 2 Hb-HHb relation in response to different task challenges is significantly reduced in BD patients hinting to a disturbed brain blood microcirculation. These strategies might be useful to follow up the therapeutic success cognition deficiencies in general medicine ambulance.
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Key words
neural network,artificial neural network analysis,artificial neural network
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