Abstract: A computer system and method for providing functional magnetic resonance imaging (MRI) distortion correction. A processor of the computer system is caused to: receive multi-echo functional MRI (ME-fMRI) data obtained from a magnetic resonance acquisition; measure a difference between two or more echoes of a plurality of echoes associated with the at least one magnetic resonance acquisition; sample distortion across a plurality of image frames included in the ME-fMRI data; estimate a frame-by-frame magnetic field inhomogeneity for each of the plurality of image frames; perform dynamic frame-wise distortion correction for each of the plurality of image frames to generate corrected data; and generate one or more field maps based on the corrected data.

Abstract: A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.

Abstract: Systems and methods are provided for managing the acquisition of MRI k-space data to reduce artifacts caused by degraded data quality and scan times required to acquire all necessary data at the requisite data quality. MRI k-space data may include any form of raw MR data acquired with an MRI system, including functional MRI (fMRI) data, resting state fMRI (rs-fMRI) data, per-fusion-weighted data, and other MRI data. Real-time monitoring and prediction of degraded data quality may be used, such as monitoring patient motion during scanning.

Abstract: A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.

Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan. One method includes receiving a data frame from the MRI system performing the MRI scan of the patient, comparing the data frame to a reference image to assess motion of a body part of the patient during the MRI scan, generating stimulus to be communicated to the patient during the MRI scan based on a task of the MRI scan and the motion of the body part of the patient during the MRI scan, adjusting the stimulus during the MRI scan to adjust the task and as the motion of the body part of the patient changes, and communicating the stimulus to the patient during the MRI scan, wherein the sensory feedback includes at least one of a game, a movie, a cartoon, a shape, or an auditory signal.

Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.

Abstract: Systems and methods are provided for producing resting-state functional magnetic resonance imaging (rs-fMRI) images. The method may include receiving functional magnetic resonance imaging (fMRI) data acquired from a subject as the subject is subjected to at least one of performing a task or experiencing a stimulus and reconstructing the fMRI data acquired as the subject is subjected to at least one of performing a task or experiencing a stimulus using a resting-state fMRI (rs-fMRI) reconstruction process without accounting for the at least one of performing the task or experiencing the stimulus to generating rs-fMRI images. The method may also include displaying the rs-fMRI images and/or using the rs-fMRI images to determine motion of the subject during the acquisition of the fMRI data.

Abstract: A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.

Abstract: A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.

Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.

Abstract: A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.

Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.

Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.

Abstract: Systems and methods for monitoring neuroplasticity within at least one region of interest of a brain of a subject are disclosed. The method includes transforming at least one time sequence of signals indicative of neural activity into a summary parameter indicative of plasticity pulses. The method further includes evaluating the summary parameter with respect to one or more threshold values to obtain a determination of neuroplasticity within at least one region of interest of the subject. The method may be used to evaluate the efficacy of a neuroactive therapy, such as a neuroactive medication, a physical therapy, an occupational therapy or a speech therapy. The summary parameter obtained using the disclosed method may be displayed to a subject as a biofeedback during a neurotherapy.

Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.

Abstract: A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.

Abstract: A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.

Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.