Temporal patterns refer to the study and analysis of how data or events change over time. It involves identifying trends, cycles, and other patterns in time-series data to understand and predict future behavior. This research area is important in various fields such as economics, finance, biology, and social sciences, where understanding temporal patterns can help in forecasting, decision-making, and understanding underlying mechanisms. Techniques such as time series analysis, signal processing, and machine learning are commonly used to analyze temporal patterns in data.