Methods for phenotype and outcome prediction are largely based on inductive supervised models that use selected biomarkers to make predictions, without explicitly considering the functional relationships between individuals. We introduce a novel netw...
Previous work supports an age-specific impairment for recognition memory of pairs of words and other stimuli. The present study tested the generalization of an associative deficit across word, name, and nonword stimulus types in younger and older adu...
We evaluate the potential of connectionist models of developmental disorders to offer insights into the efficacy of interventions. Based on a range of computational simulation results, we assess factors that influence the effectiveness of interventio...
Psychological sciences have identified a wealth of cognitive processes and behavioral phenomena, yet struggle to produce cumulative knowledge. Progress is hamstrung by siloed scientific traditions and a focus on explanation over prediction, two issue...
Adequate reliability of measurement is a precondition for investigating individual differences and age-related changes in brain structure. One approach to improve reliability is to identify and control for variables that are predictive of within-pers...
Individuals show marked variability in determining to be honest or deceptive in daily life. A large number of studies have investigated the neural substrates of deception; however, the brain networks contributing to the individual differences in dece...
Understanding human personality has been a focus for philosophers and scientists for millennia. It is now widely accepted that there are about five major personality domains that describe the personality profile of an individual. In contrast to perso...
We present a new approach for handwritten signature classification and verification based on descriptors stemming from time causal information theory. The proposal uses the Shannon entropy, the statistical complexity, and the Fisher information evalu...
Several neurobiological factors have been found to correlate with functional recovery after brain lesions. However, predicting the individual potential of recovery remains difficult. Here we used multivariate support vector machine (SVM) classificati...
The interplay between individual differences and shared human characteristics significantly impacts electroencephalogram (EEG) emotion recognition models, yet remains underexplored. To address this, we propose a commonality and individuality-based EE...
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