Differentiation between schizophrenia, bipolar disorder, and major depression using the prefrontal brain activity and the evaluation of ultra-high risk for psychosis: A large-sample functional near-infrared spectroscopy study
Poster B44, Tuesday, October 9, 11:30 am - 1:00 pm, Essex Ballroom
Shinsuke Koike1, Eisuke Sakakibara1, Yoshihiro Satomura1, Hanako Sakurada1, Mika Yamagishi1, Jun Matsuoka1, Naohiro Okada1, Kiyoto Kasai1; 1Univ of Tokyo
Background: A functional near-infrared spectroscopy (fNIRS) has an advantage of easy measurement of the activity in the surface of the cortex with a naturalistic position. In this study, we intend to explore the difference in fNIRS brain activity between three psychiatric diseases considering demographic variables. Then, we tested which disease spectrum the brain activity in ultra-high risk (UHR) individuals would be differentiated into. Methods: Of 1,838 measurements for 1,524 participants, 268 for 195 patients with schizophrenia, 181 for 177 patients with bipolar disorder, 516 for 405 patients with major depressive disorder, and 457 for 369 controls were included after considering the exclusion criteria. In addition, 50 UHR individuals participated. Intensity and timing of brain activity during the block-designed letter version of a verbal fluency task were tested on 20 brain area. Results: The intensity was smaller in patient groups over the brain area, but no difference was found between the patient groups. The timing in the bilateral superior and middle prefrontal cortex and the left pars orbitalis was later in schizophrenia group. The timing in the right superior medial prefrontal cortex and the left pars opercularis was later in depression group. We will show the results for UHR individuals in the conference. Discussion: This is the first study which investigated the characteristics of the brain activity in a variety of psychiatric disorders using a large sample set. In future, the clinical application to the fNIRS system may improve the differentiation rate and apply to other disease spectrums.
Topic Area: Neuroimaging