Embodiments of the present systems and methods may relate to a non-invasive system with diagnostic and treatment capacities that use a unified code that is intrinsic to physiological brain function. For example, in an embodiment, a computer-implemented method for affecting living neural tissue may comprise receiving at least one signal from at least one read modality, the signal representing release of photons from mitochondria of the living neural tissue, computing at least one signal to effect alterations to the living neural tissue based on the received input signal, the computed signal adapted to cause transmission of photons to the living neural tissue, and delivering the photons to the living neural tissue to effect alterations to the living tissue.

Systems and methods for diagnosis of Parkinson's disease (PD) using machine learning are disclosed. In one embodiment, a method may include receiving, on at least one processor, data, comprising one or more Magnetic Resonance Images (MRI) from a human subject; preprocessing the one or more MRIs; applying one or more Convolutional Neural Networks (CNNs) to perform image analysis of the one or more MRIs; applying one or more Generative Adversarial Networks (GANs) to augment a dataset of artificial scans for classification training; outputting, using the at least one processor, a classification based on the one or more MRI images a diagnosis of the subject for PD.

A device for stimulating neurons that includes a non-invasive stimulation unit for generating stimuli in stimulation channels. A control unit controls the stimulation unit during first and second time intervals in different stimulation modes. The control unit controls the stimulation unit during 75% or more of the first time interval in the first stimulation mode to repeatedly generate sequences of stimuli and the order in which the stimulation channels generate stimuli is constant for not more than 5 successively generated sequences and then varied. The control unit controls the stimulation unit during 75% or more of the second time interval in a second stimulation mode such that the stimulation channels repeatedly generate sequences of stimuli and the order in which the stimulation channels generate stimuli is constant for at least 25 successively generated sequences and then varied.

In embodiments, devices, methods and systems to analyze the different mediums of brain function in a mathematically uniform manner may be provided. These devices, methods and systems may manifest at several levels and ways relating to brain physiology, including neuronal activity, molecular chirality and frequency oscillations. For example, in an embodiment, a computer-implemented method for determining structure of living neural tissue may comprise receiving at least one signal from at least one read modality, the signal representing at least one physical condition of the living neural tissue, determining action potentials based on the signals received from the read modalities, determining frequency oscillations based on the signals received from the read modalities and the action potentials, and determining neuron network structures based on the signals received from the read modalities, the action potentials, and the frequency oscillations.

In some embodiments, a display system comprising a head-mountable, augmented reality display is configured to perform a neurological analysis and to provide a perception aid based on an environmental trigger associated with the neurological condition. Performing the neurological analysis may include determining a reaction to a stimulus by receiving data from the one or more inwardly-directed sensors; and identifying a neurological condition associated with the reaction. In some embodiments, the perception aid may include a reminder, an alert, or virtual content that changes a property, e.g. a color, of a real object. The augmented reality display may be configured to display virtual content by outputting light with variable wavefront divergence, and to provide an accommodation-vergence mismatch of less than 0.5 diopters, including less than 0.25 diopters.

A training apparatus is capable of generating and presenting a suitable training menu for finger exercise to maintain or improve a cognitive function and/or an exercise function of a human and supporting training of the human. The training apparatus includes a measuring apparatus and a terminal device. Analysis evaluating data based on measurement of the finger exercise including finger tapping is obtained, and the analysis evaluating data contains an evaluation value of an index item related to an exercise function of a user. A training menu for the user is generated based on the analysis evaluating data and contains a training item for the finger exercise. The index item includes at least one of an amount of exercise, endurance, rhythmicity, cooperativeness of both sides, or marker trackability. The training item includes an exercise to carry out the finger tapping in accordance with teaching information, stimulation, or a marker.

The present invention relates to a system (10) for supporting an elderly, frail and/or diseased person (12), in particular a person suffering from Parkinson's disease, wherein the system (10) comprises: a detection unit (14) including (i) a brain activity sensor (20) for detecting a brain activity signal relating to the brain activity of the person (12) and (ii) a motion detection unit (22) for detecting a motion signal relating to a motion of one or more body parts of the person (12); an analysis unit (16) for determining, based on the detected brain activity signal and motion signal, an activity level of the person (12) which is indicative of the motoric and cognitive activity of the person (12); and a feedback unit (18) for providing a feedback to the person (12) if the activity level of the person (12) exceeds a predetermined threshold.

The present invention is directed to devices and methods for rhythmic therapy. A system streams a patient specific audio file to a patient for therapy or rehabilitation while the patient is performing an exercise, where the audio comprises a musical track selected from a library of musical tracks, and simultaneously playing a second audio file with a motivational message, for example, and further where the tempo of the track, or the selection of the tracks are changed based on data received from sensors and determining if the patient is improving or regressing.

The present disclosure discusses systems and methods for identifying biomarkers that can help with the diagnosis, prognosis, and treatment choices of patients with neurodegenerative diseases. Diffusion based magnetic resonance imaging can often fail for patients with a neurodegenerative disease because parameters fractional anisotropy, mean diffusivity, and radial diffusivity are based on simple models that can fail in the presence of neurodegeneration, such as demyelination. The present disclosure discusses systems and methods that enhance dMRI images and enable tractography to be performed on images of a damaged nervous system. The damaged tracks identified by the present system can be used as a biomarker for the assessment of patients. In some implementations, the biomarkers are converted into clinical scales that can be used to compare patients to one another or over time.

A system for analyzing eye movement on the basis of brain function and a device using the same, wherein the eye movement analysis system comprises: an eye movement behavior pattern and a plurality of eye movement data collection and data storage modules. The eye movement data collection is used to perform real time analysis on position data of the head and eyes, so as to compensate for the impact of head motion on eye position, thereby ensuring more accurate results. The device using this system is applicable to the diagnosis of neurodegenerative diseases.