Topic: sex classification

Since the brain operates as a scale-free network, the frequency-power plot of fMRI BOLD signals follows a power-law distribution. However, conventional deep neural network models that fail to account for this characteristic tend to underperform, lacking a proper model structure to capture the brain signal as a complex system adequately. In this paper, we propose DivfreqBERT, an end-to-end timeseries data model that leverages the features of scale-free networks to encode biological characteristics better. We employed Lorentzian and multi-fractal functions to partition the whole-brain dynamics i