Abstract: There is provided a therapy selection support device that generates a discriminator (identifier) as a diagnostic marker or a classifier as a stratification marker through machine learning on the basis of measurement data on brain activities and that uses the discriminator or the classifier as a biomarker. A therapy selection support system 300a, 300b, 500 includes a clustering device 300b that executes stratification in which the results of measurement of brain functional connectivity correlation values acquired from a plurality of second subjects are divided into a plurality of clusters through a clustering process.

Abstract: A brain functional connectivity correlation value clustering device for clustering subjects having a prescribed attribute on the basis of brain measurement data obtained from a plurality of facilities, wherein a plurality of MRI devices capture resting state fMRI image data of a healthy cohort and a patient cohort; a computing system 300 performs generation of an identifier as ensemble learning of “supervised learning” between harmonized component values of correlation matrixes and disease labels of each of the subjects, selects, during the ensemble learning, features for clustering in accordance with importance from the features specified for generating an identifier for a disease label, and performs multiple co-clustering by “unsupervised learning.

Abstract: A harmonization system for a brain activity classifier harmonizing brain measurement data obtained at a plurality of sites to realize a discrimination process based on brain functional imaging: obtains data, for a plurality of traveling subjects as common objects of measurements at each of the plurality of measurement sites, resulting from measurements of brain activities of a predetermined plurality of brain regions of each of the traveling subjects; calculates, for each of the traveling subjects, prescribed elements of a brain functional connectivity matrix representing the temporal correlation of brain activities of a set of the plurality of brain regions; using a generalized linear mixed model, calculates measurement bias data 3108 for each element of the brain functional connectivity matrix, as a fixed effect at each measurement site with respect to an average of the corresponding element across the plurality of measurement sites and across the plurality of traveling subjects; and thereby executes a harm

Abstract: An optical sensor includes an irradiation system including at least one light irradiator to irradiate light onto an object under test; and a detection system detecting the light that is irradiated from the irradiation system and is propagated in the object under test. Further, the light irradiator irradiates non-parallel plural light beams on a same position of the object under test.

Abstract: An optical sensor includes an irradiation system including at least one light irradiator to irradiate light onto an object under test; and a detection system detecting the light that is irradiated from the irradiation system and is propagated in the object under test. Further, the light irradiator irradiates non-parallel plural light beams on a same position of the object under test.

Abstract: In order to solve a problem that a local optical characteristic-changed region inside an object cannot be accurately estimated, an object observing apparatus includes: a light intensity information acquiring unit that acquires light intensity information received by each light-receiving probe; a light intensity change information acquiring unit that acquires, for each probe set, light intensity change information, from reference light intensity information and light intensity information; an estimating unit that acquires three-dimensional optical characteristic-changed region information, using the light intensity change information; and an output unit that outputs the optical characteristic-changed region information; the estimating unit including a correcting part that performs correction according to sensitivity attenuation in accordance with a depth; and a sparseness applying part that introduces sparseness for improving a space resolution, thereby acquiring the optical characteristic-changed region infor

Abstract: In order to solve a problem that a local optical characteristic-changed region inside an object cannot be accurately estimated, an object observing apparatus includes: a light intensity information acquiring unit that acquires light intensity information received by each light-receiving probe; a light intensity change information acquiring unit that acquires, for each probe set, light intensity change information, from reference light intensity information and light intensity information; an estimating unit that acquires three-dimensional optical characteristic-changed region information, using the light intensity change information; and an output unit that outputs the optical characteristic-changed region information; wherein the estimating unit includes: a correcting part that performs correction according to sensitivity attenuation in accordance with a depth; and a sparseness applying part that introduces sparseness for improving a space resolution, thereby acquiring the optical characteristic-changed regi

Abstract: A brain information output apparatus includes an intention determination information storage unit in which two or more pieces of intention determination information can be stored, with each intention determination information including a pair of an intention identifier, and a learning feature amount group including one or more feature amounts extracted from second learning data that is obtained by converting first learning data into intracerebral brain activity data, the first leaning data being acquired from the outside of the cranium of a user when the user performs a trial according to one intention; a first brain activity data acquiring unit that acquires first brain activity data from the outside of the cranium of a user; a second brain activity data acquiring unit that converts the first brain activity data to intracerebral brain activity data, and acquires second brain activity data; a feature amount group acquiring unit that acquires, from the second brain activity data, an input feature amount group

Abstract: A brain information output apparatus includes an intention determination information storage unit in which two or more pieces of intention determination information can be stored, with each intention determination information including a pair of an intention identifier, and a learning feature amount group including one or more feature amounts extracted from second learning data that is obtained by converting first learning data into intracerebral brain activity data, the first leaning data being acquired from the outside of the cranium of a user when the user performs a trial according to one intention; a first brain activity data acquiring unit that acquires first brain activity data from the outside of the cranium of a user; a second brain activity data acquiring unit that converts the first brain activity data to intracerebral brain activity data, and acquires second brain activity data; a feature amount group acquiring unit that acquires, from the second brain activity data, an input feature amount group