COMPUTER-BASED COGNITIVE TRAINING
RESEARCH BACKGROUND
This project seeks to identify neural changes that occur in adults with mild cognitive impairment (MCI) after engagement in computerized cognitive training. Individuals with MCI are at high risk for Alzheimer’s disease (AD). Understanding how cognitive training can protect cognitive function in MCI can contribute to the development of effective interventions to delay AD in individuals at risk, thereby reducing the significant morbidity and health care costs associated with AD.
TRAINING PARADIGMS
Below are several examples of computerized cognitive training paradigms we use to better understand changes in brain and cognitive aging across older adulthood. All of these training paradigms target speed of processing of visual stimuli.
UFOV
(P. Ren, 2015)
RSVP
(K. Fhinger, 2015)
MOT
(K. Schneider, 2002)
NEUROPLASTICIY AND BRAIN NETWORKS
Assessing brain changes is important to determine whether computerized cognitive training can produce a sustainable positive effect on older adults' cognitive function.
The central executive network (CEN) and default mode network (DMN) are two neural networks critical for maintaining different aspects of cognitive function and susceptible to both normal and abnormal aging processes, including MCI (Figure 1). In our training project, we are not only interested in the improvements of cognitive performance, but also the underlying mechanism (i.e. neuroplasticity) of the training effect that may recover or enhance these brain functions. We use different magnetic resonance imaging (MRI) techniques to assess the function and structure of these neural networks, thereby evaluating whether our cognitive training paradigms promote neuroplasticity.
CEN
DMN
Figure 1. Brain "glass plots" of functional connectivity associated with the central executive network (CEN, top) and default mode network (DMN, bottom).