Abstract: A system for predicting a survival outcome of a brain tumor patient includes a computing device with at least one processor and a non-volatile computer-readable media. The non-volatile computer-readable media contains instructions executable on the processor to: transform a resting-state fMRI dataset obtained from the patient into a functional connectivity matrix comprising a plurality of matrix elements, each matrix element comprising a correlation of resting-state fMRI activities of a first and second region of interest from a plurality of pre-selected regions of interest within the patient's brain, transform the functional connectivity matrix into the predicted survival outcome using a machine learning model, and output the predicted survival outcome.

Abstract: A method for selecting a seed region for use in a seed-based cortical functional mapping method includes providing at least one RSN map of at least one subject, each of the at least one RSN maps comprising a plurality of functional voxels within a brain of each of the at least one subjects, each functional voxel of the plurality of functional voxels associated with a probability of membership in an RSN. A subset of the functional voxels characterizing a contiguous region is selected as the seed region, each functional voxel of the seed region having a probability of membership in the RSN above a threshold value.

Abstract: A biomarker predictive of a survival outcome of a brain tumor patient is disclosed. The biomarker includes a functional connectivity matrix that includes a plurality of matrix elements. Each matrix element includes a correlation of resting-state fMRI activities of a first and second region of interest from a plurality of regions of interest within the patient's brain. Computing device and systems are disclosed to transform a resting-state fMRI dataset obtained from the patient into the biomarker and to transform the biomarker into a predicted survival outcome using a machine learning model.

Abstract: A method for selecting a seed region for use in a seed-based cortical functional mapping method includes providing at least one RSN map of at least one subject, each of the at least one RSN maps comprising a plurality of functional voxels within a brain of each of the at least one subjects, each functional voxel of the plurality of functional voxels associated with a probability of membership in an RSN. A subset of the functional voxels characterizing a contiguous region is selected as the seed region, each functional voxel of the seed region having a probability of membership in the RSN above a threshold value.

Abstract: A target location for a therapeutic intervention is determined in a subject with a neurological disorder. The target location is selected within at least one resting state network (RSN) map according to a predetermined criterion for the neurological disorder. The at least one RSN map includes a plurality of functional voxels within a brain of the subject, and each functional voxel of the plurality of functional voxels is associated with a probability of membership in an RSN. Instructions are transmitted to a treatment system that cause operation to be performed on the selected target location.

Abstract: A biomarker predictive of a survival outcome of a brain tumor patient is disclosed. The biomarker includes a functional connectivity matrix that includes a plurality of matrix elements. Each matrix element includes a correlation of resting-state fMRI activities of a first and second region of interest from a plurality of regions of interest within the patient's brain. Computing device and systems are disclosed to transform a resting-state fMRI dataset obtained from the patient into the biomarker and to transform the biomarker into a predicted survival outcome using a machine learning model.

Abstract: A method for determining a target location for a therapeutic intervention in a subject with a neurological disorder is disclosed that includes selecting the target location within at least one resting state network (RSN) map according to a predetermined criterion for the neurological disorder. Each of the at least one RSN maps includes a plurality of functional voxels within a brain of the subject, and each functional voxel of the plurality of functional voxels is associated with a probability of membership in an RSN. A method for monitoring an efficacy of a therapeutic intervention in a subject with a neurological disorder is also disclosed that includes comparing at least a portion of at least one pre-treatment RSN map of the subject prior to the therapeutic intervention, at least one post-treatment RSN map of the subject after the therapeutic intervention to determine changes in the at least one post-treatment RSN map.