Neuroscience meets AI: Fatma Deniz revolutionizes language understanding

Neuroscience meets AI: Fatma Deniz revolutionizes language understanding

At this year's #RP25, which took place on April 25, 2025, the leading neuroscientist and computer scientist Fatma Deniz presented findings on the representation of language in human brain. In her lecture, she illuminated the comparison between complex neuronal networks in the brain and large language models used in artificial intelligence (AI). Deniz, who works at the Technical University of Berlin as a professor of computer science and also acts as a vice president for digitization and sustainability, impressively brought up the bridge between neurow sciences and artificial intelligence. She explained that semantic processing takes place in similar brain regions as in large language models, which could result in new approaches to the treatment of language disorders and the development of human-like AI systems. Your research uses advanced techniques of machine learning and brain imaging to gain deeper insights into language processing. This shows how the combination of neuroscience, AI and data science can make decisive progress.

The neurocognition of language processing is a central field of research that researches dealing with language at a neurocognitive level. Current work, such as the developments of a neurocognitive model of auditory language comprehension, offer a comprehensive framework for the understanding of syntactic, semantic and lexical processes in different brain regions. The left hemisphere in particular plays a key role in these processes, while prosodic aspects are processed in the right hemisphere. These findings are based on the analysis of functional and structural relationships between language-related key regions of the brain and show how syntax, semantics and other linguistic and non-linguistic areas interact. These research approaches create an expanded understanding of the hierarchical processing structures of language, which are important for AI development. You can find more information about these developments at the Max Planck Society, which deals intensively with neuropsychology and neurocognition.

The role of AI in the humanities

artificial intelligence and machine learning have established themselves as central elements in the digital humanities. Your skills offer new ways of analysis, structuring and interpretation of complex data and combine traditional methods with powerful algorithms. AI systems are able to process natural language and images, adapt to new information and solve complex problems. In the humanities in particular, KI enables the analysis of large amounts of data, pattern recognition and semantic link.

One of the significant advantages of AI is automation. Routine tasks such as text recognition and image classification can be carried out efficiently. In addition, hidden learning processes can be discovered in large data sets by automated learning processes, which results in considerable progress in text analysis and cultural media research. Examples include automatic text recognition and style analysis in literary studies, which enable deeper insights into historical texts and their authors.

With the linking of these innovative technologies with the findings of the neuroscience, a promising basis for the development of progressive AI systems can be created. Fatma Deniz emphasizes how important it is to bring these two disciplines together to use the full potential of language processing. The integration of such findings can not only lead to efficient solutions for language disorders, but also improve the ability of machines to create and understand human -like language.

More details on these exciting topics can be found in the reports of the Max Planck Society and the Digital Humanities. A comprehensive analysis also offers the article by Re: Publica, which highlights Fatma Deniz's findings.