Machine Learning Decomposition of the Anatomy of Neuropsychological Deficit in Alzheimer's Disease and Mild Cognitive Impairment.

Objective: Alzheimer's Disease (AD) is a progressive condition characterized by cognitive decline. AD is often preceded by mild cognitive impairment (MCI), though the diagnosis of both conditions remains a challenge. Early diagnosis of AD, and prediction of MCI progression require data-driven approaches to improve patient selection for treatment.

Pediatric Brain Development in Down Syndrome: A Field in Its Infancy.

Objectives: As surprisingly little is known about the developing brain studied in vivo in youth with Down syndrome (DS), the current review summarizes the small DS pediatric structural neuroimaging literature and begins to contextualize existing research within a developmental framework.

Methods: A systematic review of the literature was completed, effect sizes from published studies were reviewed, and results are presented with respect to the DS cognitive behavioral phenotype and typical brain development.

Results: The majority of DS structural neuroimaging studies describe gross differences in brain morphometry and do not use advanced neuroimaging methods to provide nuanced descriptions of the brain.

A conceptual framework for interpreting neuroimaging studies of brain neuroplasticity and cognitive recovery.

Functional neuroimaging technologies are increasingly being used to predict cognitive/behavioral outcomes after the initiation of clinical interventions such as resective surgery or cognitive rehabilitation. We provide a conceptual model and a case example to explain how the results from various neuroimaging techniques can be integrated to answer important questions about clinical recovery such as whether neural reorganization has occurred and, if so, the type of adaptive cognitive mechanism driving this reorganization. This proposed framework and its use in interpreting neuroimaging outcomes studies should help uncover the principles that govern neural reorganization, and be of use to any patient for whom the risk, or potential benefit, of brain-based interventions is unknown.