Our mind remains one of the greatest mysteries-far from linear, it thrives on synchronization and connectivity. In fact, much of what our brain accomplishes happens not in isolation, but through intricate, coordinated collaboration among its regions. Even more fascinating, our brain function reveals an unexpected quality: alongside its complex connectivity, it unfolds in discrete, temporal patterns. But why do we observe these remarkable dynamics in the brain?In this TEDx Talk, we’ll embark on an exploration of how these hidden brain patterns emerge and evolve. Leveraging advanced neuroimaging techniques and cutting-edge artificial intelligence, researchers are beginning to unravel the complex interactions that govern our mental processes. How can we measure the ebb and flow of connection and these discrete rhythms? And in what ways do these interactions and temporal patterns coalesce into the broader dynamics that define how we think, feel, and behave?Building on this foundation of discovery, we naturally turn our attention to what these insights enable us to do. Beyond mere observation, we will delve into the realm of neurofeedback- a revolutionary approach that translates the brain’s unconscious workings into sensory feedback, empowering us to shape our own neural activity. When we combine the complex temporal patterns of brain activity with neurofeedback, a crucial question emerges: can we harness our growing understanding of these dynamics to actively influence our own mental states?Looking ahead, we’ll speculate on the role of predictability in brain dynamics and explore how artificial intelligence might eventually help us decode our own “alphabet of thought.” Imagine a future where AI not only reads our brain patterns but also helps us shape them - this might indeed be a good thing - maybe. Markus Goldhacker studied Physics and Psychology at the University of Regensburg, focusing on neuroscience and artificial intelligence. In his PhD, he explored how the synchrony of brain activity changes over time, uncovering hidden patterns and developing new methods to analyze them. He then worked as a Data Scientist at the Neurosurgery Department of the University Hospital of Regensburg, analyzing functional brain scans of brain tumor patients. Later, he worked in the mechanical engineering industry, developing data-driven models for predictive maintenance. Since September 2020, he has been a Professor of Data Science at OTH Regensburg in the mechanical engineering department and the Regensburg School of Digital Sciences. His current research delves into Brain-Computer Interfaces and Neurofeedback, exploring how these technologies can enable people to self-regulate their brain function. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx