AIMC Journal:
Imaging neuroscience (Cambridge, Mass.)

Showing 1 to 3 of 3 articles

Improving respiratory and heart rate variation estimation from resting-state BOLD fMRI across the lifespan using a functionally informed, tissue-aware deep learning framework.

Imaging neuroscience (Cambridge, Mass.)
Accurate measurement of physiological signals such as respiration and cardiac activity is essential for modeling physiological confounds in BOLD-fMRI data. However, external monitoring devices such as respiratory belts and photoplethysmographs often ...

SUITPy: A Python-based toolbox for the analysis of cerebellar functional and anatomical imaging data across the human lifespan.

Imaging neuroscience (Cambridge, Mass.)
The human cerebellum plays a central role in motor, emotional, and cognitive functions, and is implicated in many brain disorders. To improve the analysis of functional and anatomical imaging from the cerebellum, we introduce SUITPy, an improved and ...

Distinct neural signatures in a sensorimotor synchronization-continuation task.

Imaging neuroscience (Cambridge, Mass.)
Optimal sensorimotor timing hinges on the generation, refinement, and employment of internal models to meet task demands. In finger tapping sensorimotor synchronization tasks, this occurs across and within tapping conditions that prompt externally-cu...