Abstract: Systems and methods are described for computing a quantitative index that characterizes Alzheimer's disease (“AD”) risk events based on a temporally ordered sequence of biomarker events. In general, the systems and methods described here implement a modified event-based probabilistic (“EBP”) model to calculate the risk index from biomarker data.

Abstract: Systems and methods obtain functional connectivity data in the whole brain to detect and predict brain disorders. This whole brain data is regionalized and then manipulated to derive functional connectivity data sets that can be used to show measured functional connectivity changes. This whole brain data may also be analyzed to determine changes in functional activity in both increased and decreased neural network connectivity. By identifying and then quantifying the functional connectivity differences between healthy and diseased subjects, a classification for individual subjects can be made.

Abstract: Systems and methods are described for computing a quantitative index that characterizes Alzheimer's disease (“AD”) risk events based on a temporally ordered sequence of biomarker events. In general, the systems and methods described here implement a modified event-based probabilistic (“EBP”) model to calculate the risk index from biomarker data.

Abstract: A method for reconstructing a plurality of images depicting a subject from image data that is simultaneously acquired from a corresponding plurality of slice locations with a magnetic resonance imaging (MRI] system is provided. Image data is acquired following the application of radio frequency (RF] energy to the plurality of slice locations. The RF energy is tailored to provide a different phase to each of the plurality of slice locations. Reference image data is also acquired for each slice location following the application of RF energy that has the same phase as is used to excite the respective slice location for the acquisition of the image data. Aliased images are reconstructed from the image data, and reference images are reconstructed from the reference image data. Using both of these image sets, an unaliased image is produced for each of the plurality of slice locations.

Abstract: Systems and methods obtain functional connectivity data in the whole brain to detect and predict brain disorders. This whole brain data is regionalized and then manipulated to derive functional connectivity data sets that can be used to show measured functional connectivity changes. This whole brain data may also be analyzed to determine changes in functional activity in both increased and decreased neural network connectivity. By identifying and then quantifying the functional connectivity differences between healthy and diseased subjects, a classification for individual subjects can be made.

Abstract: A method for reconstructing a plurality of images depicting a subject from image data that is simultaneously acquired from a corresponding plurality of slice locations with a magnetic resonance imaging (MRI] system is provided. Image data is acquired following the application of radio frequency (RF] energy to the plurality of slice locations. The RF energy is tailored to provide a different phase to each of the plurality of slice locations. Reference image data is also acquired for each slice location following the application of RF energy that has the same phase as is used to excite the respective slice location for the acquisition of the image data. Aliased images are reconstructed from the image data, and reference images are reconstructed from the reference image data. Using both of these image sets, an unaliased image is produced for each of the plurality of slice locations.

Abstract: Time course MRI data is acquired from the hippocampal region of the brain and processed to produce two indices that are a measure of the functional connectivity between locations therein. The MRI data is acquired while the brain is substantially at rest and the spontaneous low frequency component of the time course data at each location in the hippocampus is extracted and compared in a cross-correlation process. Also acquired is fMRI data which indicates those locations in the brain that should be included in the index calculations.

Abstract: Time course MRI data is acquired from the hippocampal region of the brain and processed to produce two indices that are a measure of the functional connectivity between locations therein. The MRI data is acquired while the brain is substantially at rest and the spontaneous low frequency component of the time course data at each location in the hippocampus is extracted and compared in a cross-correlation process. Also acquired is fMRI data which indicates those locations in the brain that should be included in the index calculations.

Abstract: Time course MRI data is acquired from the hippocampal region of the brain and processed to produce an index which is a measure of the functional connectivity between locations therein. The MRI data is acquired while the brain is substantially at rest and the spontaneous low frequency component of the time course data at each location in the hippocampus is extracted and compared in a cross-correlation process.