Predicting Individual Impulsivity Based on Neural Architecture Captured by Different Neuroimaging Modalities
Impulsive buying is a clear violation of Homo economicus' assumptions. There are several perspectives on impulse buying presented, including those from consumer, economic, social, and clinical psychology. Heuristic information processing, time-inconsistent preferences, personality traits and values, emotions, conscious self-control, and compulsive buying are all examples of Impulsive buying.
These viewpoints can sometimes produce contradictory results. Impulse buying, for example, is often associated with happiness and pleasure, but it has also been linked to negative emotions and low self-esteem.
The objective of this paper is understanding and predicting individual impulsivity based on neural architecture captured by different neuroimaging modalities.
This work aim to use deep learning approach that combines diffusion, functional, structural MRI data and impulsivity test from the Human Connectome Project (N = 1105) to understanding and provide prediction models of impulsivity.
Keywords - Impulsivity; Neuromarketing; Impulsive buying; emotion recognition; machine learning; deep learning.