Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc.

Validation of computer-administered clinical rating scale: Hamilton Depression Rating Scale assessment with Interactive Voice Response technology--Japanese version.

AIM: The aim of this study was to examine the reliability and validity of the Interactive Voice Response (IVR) program to rate the 17-item Hamilton Rating Scale for Depression (HAM-D) score in Japanese depressive patients. METHODS: Depression severity was assessed in 60 patients by a clinician and psychologists using HAM-D. Scoring by the IVR program was conducted on the same and the following days. Test-retest reliability, internal consistency, and concurrent validity for total HAM-D scores were examined by calculating intraclass correlation coefficient, Cronbach's alpha, and Pearson's correlation coefficient. Inter-rater consistency for each HAM-D item was examined by Cohen's kappa. RESULTS: Test-retest reliability of the IVR program was high (intraclass correlation coefficient: 0.93). Internal consistency of each total score obtained by the clinician, psychologists, and IVR program was high (Cronbach's alpha: 0.77, 0.79, 0.78, and 0.83). Regarding concurrent validity, correlation coefficients between total scores obtained by the clinician versus IVR and that by the clinician versus psychologists were high (0.81 and 0.93). The HAM-D total score rated by the clinician was 3 points lower than that of IVR. Inter-rater consistency for each HAM-D item evaluated by the clinician versus IVR was estimated to be fair (Cohen's kappa coefficient: 0.02-0.50). CONCLUSION: Our results suggest that the Japanese IVR HAM-D program is reliable and valid to assess 17-item HAM-D total score in Japanese depressive patients. However, the current program tends to overestimate depression severity, and the score of each item did not always show high agreement with clinician's rating, which warrants further improvement in the program.