Welcome to SFB 1528 - Cognition of Interaction
Nivedita Mani joins the Neuroscience and Beyond podcast
Nivi Mani, a member of SFB 1528, was recently interviewed on the "Neuroscience and Beyond" podcast. In this episode, she discusses the fascinating process of language acquisition in infants, shedding light on how babies learn to speak by engaging with their environment. Nivi explains the key roles that attention, motivation, and the social context play in language development. She also explores how different types of speech, such as infant-directed speech, influence language learning, and addresses the challenges adults face when learning new languages, particularly regarding accents. Additionally, Nivi talks about the impact of multilingual upbringing and how gender differences can shape early language development. You can listen to the full interview here
Final Panel Discussion: Empowering First Generation Academics
On March 12, we hosted our final panel discussion on how to increase diversity in Academia. The topic was “First Generation Academics – How the Family Background Influences the Career Paths of Young Female Scientists." Our expert panelists – Zurna Ahmed, Holmer Steinfath, Britta Korkowsky, Charlotte Prauß and Ann-Kristin Kolwes – openly discussed the challenges faced by young researchers from non-academic backgrounds. These challenges include not only financial barriers but also self-doubt, uncertainty in the academic environment, and lack of understanding from their own families. But the panel also talked about seemingly simple yet significant hurdles in academic life, such as: How do I find a supervisor? Can I approach professors directly? How do I become a student assistant?
Leopoldina policy paper on demographic change
SFB PI Julia Fischer co-authored a new discussion paper from the German National Academy of Sciences Leopoldina on demographic change and aging. The paper highlights the need for better policy coordination and proposes a government committee within the Federal Ministry of the Interior to ensure effective cross-departmental collaboration. It emphasizes the importance of focusing on social groups rather than just individuals when addressing workforce shortages and care dependency. The authors also call for strengthening demographic research through better data integration and interdisciplinary studies, particularly on healthy aging and medical-technological innovations.
To the policy paper
New Publication in PNAS: Understanding Local Learning in Neural Networks
How do individual elements in a neural network contribute to solving complex tasks? While both biological and artificial neural networks achieve remarkable performance, their local learning dynamics remain poorly understood. A new study by Michael Wibral, Viola Priesemann, and colleagues, published in PNAS, introduces a novel framework to describe local learning goals using principles from information theory. The researchers present infomorphic networks, which define learning objectives at the level of individual neurons through a parametric approach based on Partial Information Decomposition (PID). This allows them to unify different learning rules and tasks—including supervised, unsupervised, and memory learning—within a single theoretical framework. By making local learning dynamics more interpretable, infomorphic networks help bridge the gap between theoretical neuroscience and artificial intelligence.
Prof. Alexander Gail
Sensorimotor Neuroscience & Neuroprosthetics
University of Göttingen & German Primate Center Göttingen
Kellnerweg 4,
37077 Göttingen
Tel.: +49-551-3851-358 ContactDr. Christian Schloegl
Kellnerweg 4,
37077 Göttingen
Tel.: +49-551-3851-480
Contact