Abstract: Described herein are systems and methods for predicting response to treatment for a neurological or psychiatric disorder. The systems may include machine learning and run LDA and/or Lasso Regression methods that use psychometric inventories and other forms of patient data such as patient characteristics, treatment history, clinical history, biometric data, neuroimaging data, or a combination thereof, as inputs to generate a predictive model that separates responders from non-responders. The methods may include prediction of response to initial treatment by obtaining baseline, pretreatment data collected through psychometric inventories as well as other forms of patient data.

Abstract: Described herein are methods and systems for the identification and selection of a neurostimulation target for treating neurological or psychiatric disorders in a subject using functional connectivity networks. The methods and systems may analyze the connectivity or synchrony between deeper brain regions of interest that have been divided into parcels with surface regions of the brain. The methods and systems generally reduce the computational complexity of the targeting algorithm, which in turn may result in a more reliable determination of the neurostimulation targets. Additionally, the methods and systems may personalize the target for neurostimulation, which may improve the overall efficacy of the neurostimulation treatment. Methods and systems that use a decision algorithm to calculate a weight value for a plurality of seed-circuit pairs, and determine a neurostimulation target based on the seed-circuit pair having the greatest weight value are also described herein.

Abstract: Described herein are methods and systems for treatment of neurological conditions using aTBS. One variation includes a method for treating anxiety disorders, including generating a personalized accelerated theta burst stimulation (aTBS) target, placing a TMS device relative to the patient's brain such that the focus of the magnetic field is over the aTBS target, applying TMS to the aTBS target according to an aTBS protocol to the brain using the TMS device to alleviate one or more symptoms of the anxiety disorder. Methods and systems for concurrently treating two or more disorders, e.g., depression and an anxiety disorder, are also described.

Abstract: Described herein are systems and methods for the automated prediction of relapse of a neurological or psychiatric disorder. The systems and methods may generally use patient data such as patient characteristics, treatment history, clinical history, biometric data, and/or neuroimaging data as inputs to a predictive model. Additionally, the systems and methods may be integrated with a treatment system so that neurostimulation may be automatically delivered when triggered by the predictive model. Systems and methods configured to propose a personalized treatment schedule for maintaining the effects of neurostimulation therapy are also described herein.