Open AccessUse of machine learning to predict cognitive performance based on brain metabolism in Neurofibromatosis type 1
Author(s) -
Manuel Schütze,
Danielle de Souza Costa,
Jonas Jardim de Paula,
Leandro Fernandes Malloy-Diniz,
Carlos Malamut,
Marcelo Mamede,
Débora Marques de Miranda,
Michael Brammer,
Marco Aurélio Romano-Silva
Publication year - 2018
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0203520
Subject(s) - neuropsychology , cognition , wechsler adult intelligence scale , verbal fluency test , neuropsychological assessment , principal component analysis , psychology , artificial intelligence , machine learning , audiology , neuroscience , computer science , medicine
Neurofibromatosis Type 1 (NF1) can cause a wide range of cognitive deficits, but its underlying nature is still unknown. We investigated the correlation between cognitive performance and specific patterns of resting-state brain metabolism in a NF1 sample. Sixteen individuals diagnosed with NF1 underwent 18F-FDG PET/CT brain imaging followed by a neuropsychological assessment. Principal component analysis was performed on 17 measures of cognitive function and a machine learning approach based on Gaussian Process Regression was used to individually predict the components that represented most of the variance in the neuropsychological data. The accuracy of the method was estimated using leave-one-out cross-validation and its significance through permutation testing. We found that only the first component could be accurately predicted from resting state metabolism ( r = 0.926, p<0.001). Multiple and heterogeneous measures contribute to the first component, mainly WISC/WAIS Procedure and Verbal IQ, verbal memory and fluency. Considering the accurate prediction of measures of neuropsychological performance based on brain metabolism in NF1 patients, this suggests an underlying metabolic pattern that relates to cognitive performance in this group.