Methods for the diagnosis, prognosis, patient stratification and prediction of pharmacological response in patients afflicted by psychiatric disorders based on electroretinography (ERG) parameters are described.

There is provided a system for determining the state of dementia by using an image differentiation technique and a cognitive test score together with each other.

A system includes: a first input module configured to acquire a first evaluation index based on data regarding the physical state of a brain of a subject; a second input module configured to acquire a second evaluation index based on data regarding the function of the brain of the subject; and an estimation module configured to estimate the state of dementia of the subject based on an evaluation value obtained by a first evaluation function having the first evaluation index and the second evaluation index as its variables.

In an aspect of the invention, a method of identifying sensory inputs affecting working memory load of an individual is provided. The method comprises monitoring (S101) working memory load of the individual using a sensor device, detecting (S102) an increase in the working memory load of the individual, and identifying (S103), in response to the detected increase, at least one sensory input affecting the working memory load of the individual.

Method and apparatus for non-invasive condition detection using an all fiber portable terahertz imaging system. An imaging system of the present disclosure may comprise a control module comprising a femtosecond pulsed laser configured to generate an output light beam, a dispersion compensation unit configured to receive the output light beam and transmit a laser light beam generated based upon the output light beam, a beam splitter configured to receive the laser light beam and divide the laser light beam into a pump light beam and a reference light beam; and a rapid scanning optical delay line configured to receive the pump light beam and transmit an exit light beam generated based upon the pump light beam, a patch probe comprising a transmitter module, an optics lens, and a detector module.

A system includes a plurality of test elements and a processor. The test elements are configured for execution of a motor task by an individual and generation of test data from trials of the motor task. The processor is configured to compute a motor test score from the test data to assess a potential neurological concern.

Systems and methods of the present invention provide for generating a first, second, and third series of interface objects comprising a first and second sequence respectively, displayed on a graphical user interface (GUI). At least one visual indicator display object is also displayed that requires a switch between the first and second series of user interface objects. A user navigates through the first and second series of interface objects, including the visual indicator display object(s), and a score for the user is calculated according to a user input matching, or failing to match, a correct response associated with a task data defining a function skill demonstrating a cognitive ability of the user.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a mental health prediction for a patient. One of the methods includes obtaining brain data captured by one or more sensors characterizing a brain of a patient; determining a network graph from the brain data, wherein: a node of the network graph corresponds to a parcellation in the brain of the patient, and a subset of nodes of the network graph corresponds to a particular functional area of the brain; generating, for each of a plurality of nodes in the network graph, a measure of centrality of the node; generating, for the particular functional area of the brain and using the generated measures of centrality, a health score representing a measure of health of the functional area of the brain; generating a mental health prediction for the patient using the health score.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a mental health prediction for a patient using a centrality ranking of the brain of the patient. One of the methods includes obtaining brain data of a patient, wherein the brain data comprises, for each of a plurality of pairs of parcellations formed from a set of parcellations where each pair comprises a first parcellation and a second parcellation, data characterizing a number of tracts connecting the first parcellation and the second parcellation; determining a network graph from the brain data; generating, for each of a plurality of nodes in the network graph, a measure of centrality of the node; determining a centrality ranking of the plurality of nodes of the network graph according to the respective measures of centrality; generating a mental health prediction for the patient using the determined centrality ranking.

Disclosed is a method for scoring in real time neural signals of a subject with respect to a reference state characterized by k=1 . . . K reference covariance matrices, the method including the following steps: (i) obtaining neural signals from the subject; (ii) computing a covariance matrix of the neural signals; (iii) computing the Riemannian distances between the covariance matrix and k=1 . . . K reference covariance matrices; (iv) computing a continuous score s in real time based on at least one of the distances computed in step (iii). Also disclosed is a system and method for self-paced modulation or external modulation of neural activity of a subject.

Systems and methods are disclosed for detecting tremors in a subject. One method comprises receiving data from a digital device, the data comprising a plurality of digital device positions and a plurality of timestamps, each timestamp in the plurality of timestamps being associated with a digital device position in the plurality of digital device positions. The method further comprises determining a plurality of frequencies of hand movements of the subject based on the plurality of digital device positions and plurality of timestamps. The method further comprises determining a subportion of the data corresponding to frequencies of hand movements above a low tremor threshold, and determining a magnitude of tremors of the subject's hand based, at least in part, on the subportion of the data.