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Abstract #3661

Discriminant Analysis & Prediction of AMCI Subjects and Normal Controls using Encoding & Recognition fMRI Tasks

Dietmar Cordes1, Mingwu Jin1, Tim Curran2, Victoria Pelak3, Rajesh Nandy4

1C-TRIC & Dept. of Radiology, University of Colorado-Denver, Aurora, CO, United States; 2Dept. of Psychology & Neuroscience, University of Colorado-Boulder, Boulder, CO, United States; 3Dept. of Neurology, University of Colorado-Denver, Aurora, CO, United States; 4Depts. of Biostatistic & Psychology, University of California-Los Angeles, Los Angeles, CA, United States

Focusing on activation in subregions of the medial temporal lobe (CA1, CA23DG, SUB, ERC, PRC, FUS, PHC) we used discriminant analysis applied to data from three different memory paradigms to investigate the degree of separation of the aMCI group from the normal control group as a function of the type of paradigm (outdoor pictures, faces-and-occupations, unrelated word pairs) and type of contrast (encoding-control, recognition-control, encoding-recognition, old-control, new-control, old-new). Results indicate optimum separation of groups for the face-and-occupation paradigm for contrast recognition-control. Prediction accuracy using the leave-one-out method is 75% using activations in left CA1, left SUB and left PHC.