title: Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis.
abstract: To quantify the effect of absorption changes in the deep tissue (cerebral) and shallow tissue (scalp, skin) layers on functional near-infrared spectroscopy (fNIRS) signals, a method using multi-distance (MD) optodes and independent component analysis (ICA), referred to as the MD-ICA method, is proposed. In previous studies, when the signal from the shallow tissue layer (shallow signal) needs to be eliminated, it was often assumed that the shallow signal had no correlation with the signal from the deep tissue layer (deep signal). In this study, no relationship between the waveforms of deep and shallow signals is assumed, and instead, it is assumed that both signals are linear combinations of multiple signal sources, which allows the inclusion of a "shared component" (such as systemic signals) that is contained in both layers. The method also assumes that the partial optical path length of the shallow layer does not change, whereas that of the deep layer linearly increases along with the increase of the source-detector (S-D) distance. Deep- and shallow-layer contribution ratios of each independent component (IC) are calculated using the dependence of the weight of each IC on the S-D distance. Reconstruction of deep- and shallow-layer signals are performed by the sum of ICs weighted by the deep and shallow contribution ratio. Experimental validation of the principle of this technique was conducted using a dynamic phantom with two absorbing layers. Results showed that our method is effective for evaluating deep-layer contributions even if there are high correlations between deep and shallow signals. Next, we applied the method to fNIRS signals obtained on a human head with 5-, 15-, and 30-mm S-D distances during a verbal fluency task, a verbal working memory task (prefrontal area), a finger tapping task (motor area), and a tetrametric visual checker-board task (occipital area) and then estimated the deep-layer contribution ratio. To evaluate the signal separation performance of our method, we used the correlation coefficients of a laser-Doppler flowmetry (LDF) signal and a nearest 5-mm S-D distance channel signal with the shallow signal. We demonstrated that the shallow signals have a higher temporal correlation with the LDF signals and with the 5-mm S-D distance channel than the deep signals. These results show the MD-ICA method can discriminate between deep and shallow signals.
authors: Hitachi, Ltd., Central Research Laboratory, Hatoyama, Saitama 350-0395, Japan. Electronic address: tsukasa.funane.sb@hitachi.com.
authors: Tsukasa
authors: T
authors: Funane
authors: Hirokazu
authors: H
authors: Atsumori
authors: Takusige
authors: T
authors: Katura
authors: Akiko N
authors: AN
authors: Obata
authors: Hiroki
authors: H
authors: Sato
authors: Yukari
authors: Y
authors: Tanikawa
authors: Eiji
authors: E
authors: Okada
authors: Masashi
authors: M
authors: Kiguchi
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000502:physiology; D002560:Cerebrovascular Circulation / Q000502:physiology; D003627:Data Interpretation, Statistical; D004192:Discrimination, Psychological / Q000502:physiology; D004566:Electrodes; D059907:Functional Neuroimaging / Q000295:instrumentation / Q000379:methods / Q000706:statistics & numerical data*; D006257:Head / Q000033:anatomy & histology; D006454:Hemoglobins / Q000032:analysis / Q000378:metabolism; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008570:Memory, Short-Term / Q000502:physiology; D008875:Middle Aged; D019047:Phantoms, Imaging; D025341:Principal Component Analysis; D011597:Psychomotor Performance / Q000502:physiology; D012039:Regional Blood Flow / Q000502:physiology; D015203:Reproducibility of Results; D012535:Scalp / Q000098:blood supply; D019265:Spectroscopy, Near-Infrared / Q000295:instrumentation / Q000379:methods / Q000706:statistics & numerical data*; D014705:Verbal Behavior / Q000502:physiology
chemical_list: D006454:Hemoglobins
keywords: Brain activity measurement; Functional near-infrared spectroscopy (fNIRS); Independent component analysis (ICA); Multi-distance optodes; Scalp (skin) blood flow; Verbal fluency task (VFT)