Methods and systems for predicting treatment outcomes, patient selection and personalized therapy using patient response properties to sensory stimulation

A method of identifying a biomarker associated with a distinct clinical outcome, comprising:

• (a) training a machine learning algorithm to identify a statistical relationship between (i) a first dataset comprising a plurality of response measurements for a plurality of subjects, wherein the plurality of response measurements comprises a response to a gamma oscillation inducing non-invasive sensory stimulus for each subject in the plurality of subjects, and (ii) a second dataset comprising a plurality of clinical measurements for the plurality of subjects;
• and
• (b) identifying, using the machine learning algorithm, the biomarker associated with the distinct clinical outcome.

A method of predicting a response to a treatment for a subject diagnosed with or at a risk of developing a neurodegenerative disorder associated with cognitive decline, the computer-implemented method comprising:

• (a) providing a visual gamma oscillation inducing stimulus to the subject;
• and
• (b) performing an encephalogram on a brain region of the subject to measure a plurality of bioelectrical signals.

A method for selecting a patient population that will respond to gamma oscillation inducing sensory stimulation, the method comprising:

• (a) administering a gamma oscillation inducing non-invasive sensory stimulus to a subject of the patient population;
• (b) measuring a response from the subject;
• and (c) predicting, using a statistical algorithm, a machine learning algorithm, or a combination thereof, the expected treatment outcome of the patient population based at least partially on the measuring of (b), wherein the expected the treatment outcome comprises a slowing of neurodegeneration, an improvement in symptoms of neurodegeneration, or a combination thereof.

A method for identifying favorable parameter settings for gamma oscillation inducing non-invasive sensory stimulation therapy, the method comprising:

• (a) administering a gamma oscillation inducing non-invasive sensory stimulus to a subject of the patient population;
• (b) measuring a response from the subject;
• and (c) modifying a parameter of the gamma oscillation inducing non-invasive sensory stimulus, wherein the parameter of the gamma oscillation inducing non-invasive sensory stimulus is modified based at least partially on the measuring of (b), thereby identifying favorable parameter settings for gamma oscillation inducing non-invasive sensory stimulation therapy.

A method for selecting parameters to serve as a placebo for treatment using gamma oscillation inducing non-invasive sensory stimulus, the method comprising (a) administering a non-invasive sensory stimulus to a subject of the patient population;

• (b) measuring a response from the subject;
• (c) modifying a parameter of the stimulus to reduce the response from the subject;
• and (d) repeating (a) through (c) until the response from the subject is minimal, thereby selecting parameters to serve as a placebo for treatment using gamma oscillation inducing non-invasive sensory stimulus.

A method for selecting a brain region to target with treatment, the method comprising (a) administering a non-invasive sensory stimulus to a subject of the patient population;

• (b) performing an encephalogram on the brain of the subject to measure a plurality of bioelectrical signals;
• (c) selecting, based on the plurality of bioelectrical signals, the brain region to target with treatment.

A method for defining a unified clinical outcome for progression of a disease or disorder, the method comprising (a) administering a gamma oscillation inducing non-invasive sensory stimulus to a plurality of individuals;

• (b) measuring a biological response of the plurality of individuals to the gamma oscillation inducing non-invasive sensory stimulus, wherein the biological response is associated with progression of the disease or disorder;
• (c) normalizing values corresponding to the biological response, thereby generating normalized data points;
• and (d) determining, using the normalized data points, a principal component for the data points.