In bioFAME, the learned frequency filters can be interpreted to understand the specific frequency bands and types of information that are most relevant for different downstream biosignal tasks by analyzing the attention weights and patterns within the frequency space. By visualizing the attention weights across different frequency components, researchers can gain insights into which frequency bands are most activated or relevant for specific biosignal tasks. This analysis can help identify the key frequency components that contribute to the classification or understanding of different physiological states or activities. Additionally, researchers can explore techniques such as frequency band analysis, power spectral density estimation, and frequency domain feature extraction to further interpret and extract meaningful information from the learned frequency filters. By correlating the frequency components with the specific physiological activities or patterns in the biosignals, researchers can enhance their understanding of how different frequency bands contribute to the overall representation and classification of biosignals in various tasks.