AIM for the Brain
From artificial to natural intelligence: As machine learning systems become increasingly powerful at recognizing patterns and modeling complex dynamics, they are also being used more and more in cognitive neuroscience to investigate fundamental questions: How does the brain generate thoughts, memories, perception, and actions? And how can data-driven models help uncover the underlying principles of these processes? Ultimately, could artificial intelligence help us better understand natural intelligence?
AIM for … workshop series provides an interdisciplinary forum for researchers at the University of Münster who apply methods from artificial intelligence and machine learning, or whose research activities could potentially benefit from AI in the future. Each edition of “AIM for” focuses on a specific scientific field in which AI acts as a methodological driver for new research approaches. The first workshop of the series, AIM for the Brain, which centers on brain research, is jointly organized by the Center for Data Science and Complexity and the Otto Creutzfeldt Center for Cognitive and Behavioural Neuroscience.
The aim of the workshop series is to foster active networking and exchange within the University of Münster. At the same time, the workshops are enriched by contributions from external experts who provide insights into the current state of research and future developments of the respective field from different disciplinary and methodological perspectives. For the first edition of the series, we are pleased to welcome Daniel Durstewitz and Tim Kietzmann as guest speakers.
All researchers with an interest in the respective topic are explicitly invited to participate—even if they do not (yet) use AI in their research. Short and informal contributions may be used to present research approaches, ongoing projects, or ideas for potential collaborations. The goal is to encourage exchange across disciplinary boundaries, highlight shared research questions, and serve as a starting point for new scientific networks and collaborations.