Lagged Functional Connectivity Reflects the Cognitive Impairment of MCI
Disciplines
Clinical Psychology | Cognitive Psychology
Abstract (300 words maximum)
The dorsolateral prefrontal cortex is an important part of the frontal cortex in mild cognitive impairment and Alzheimer’s disease. In our study, we measured the electroencephalogram and neuropsychological tests in 60 older adults with mild cognitive impairment and 63 age-matched controls. Functional connectivity was then estimated between Brodmann areas 9 and 46 and several other brain regions using Low Resolution Electromagnetic Tomography (LORETA). Functional connectivity was estimated between 10 brain regions, including hippocampus and dorsolateral prefrontal cortex. We then identified the 10 most promising measures of MCI status based on differences between groups and entered them into a logistic regression. Five of 10 were statistically significant predictors, with the strongest predictors being the lagged phase coherence between left and right hippocampus and the lagged connectivity between left visual area MT and right Brodmann Area 9, a region of the dorsolateral prefrontal cortex. The classification accuracy of the model was 75.6%.
Academic department under which the project should be listed
RCHSS - Psychological Science
Primary Investigator (PI) Name
Tim Martin
Additional Faculty
Voyko Kavcic, Wayne State University
Lagged Functional Connectivity Reflects the Cognitive Impairment of MCI
The dorsolateral prefrontal cortex is an important part of the frontal cortex in mild cognitive impairment and Alzheimer’s disease. In our study, we measured the electroencephalogram and neuropsychological tests in 60 older adults with mild cognitive impairment and 63 age-matched controls. Functional connectivity was then estimated between Brodmann areas 9 and 46 and several other brain regions using Low Resolution Electromagnetic Tomography (LORETA). Functional connectivity was estimated between 10 brain regions, including hippocampus and dorsolateral prefrontal cortex. We then identified the 10 most promising measures of MCI status based on differences between groups and entered them into a logistic regression. Five of 10 were statistically significant predictors, with the strongest predictors being the lagged phase coherence between left and right hippocampus and the lagged connectivity between left visual area MT and right Brodmann Area 9, a region of the dorsolateral prefrontal cortex. The classification accuracy of the model was 75.6%.