Introduction
Contents
Introduction#
Personality plays a pivotal role in shaping human behavior and decision-making processes. To better comprehend the intricate relationship between personality traits and brain function, this project employs advanced neuroimaging techniques, particularly functional Magnetic Resonance Imaging (fMRI). The objective is to investigate how individual differences in task performance can serve as predictive indicators of personality traits.
The primary goals of this project are:
Decode Neural Activity: Utilizing cutting-edge machine learning classifiers, this study seeks to decode neural activity patterns captured by fMRI during various cognitive tasks. The aim is to uncover correlations between these brain network activations and personality traits.
Predict Task Performance: By analyzing individual differences in task performance scores, the project aims to establish predictive models linking task performance to specific personality traits. This predictive approach offers a unique perspective compared to traditional brain-wide association studies reliant on resting-state fMRI data.
Differentiated Understanding: The research findings aim to emphasize that a “one-size-fits-all” approach cannot be applied when linking human traits to brain activation patterns. Instead, it highlights the significance of considering task-related brain activity for a more nuanced understanding of the interplay between neural processes and human traits.
Key Research Questions#
Can fMRI data effectively predict personality traits based on cognitive task performance?
Does fMRI data provide more comprehensive insights into cognition and personality than task performance scores alone?