Thursday, 25 June 2026, 15:00-16:00

Prof. Claus Hilgetag

Register via: https://cam-ac-uk.zoom.us/meeting/register/n1P34QeQS_axP3tqjr636Q#/registration

Networks as the foundation of human and artificial cognition

Cognitive systems, whether biological or artificial, are fundamentally shaped by their underlying network organization.  Here, I compare evolutionary and developmental trajectories of biological neural networks (BNNs) and artificial neural networks (ANNs), highlighting shared trends such as increasing network depth, sparsity, and (hierarchical) modularity. Key connectomic principles of the mammalian brain provide fundamental constraints for understanding cognition and offer underexploited design principles for artificial systems. Combining empirical connectomes and neuro-inspired models, particularly in the context of  reservoir computing approaches, we find that biologically grounded network topologies can match or exceed the performance of random or engineered architectures on working memory-related tasks. Moreover, moving from designed to developmentally grown network architectures may be a crucial step toward more scalable, robust, and cognitively plausible artificial intelligence.