Invited speakers

The language vision interface and its plasticity

Current research practices in NeuroAI do not support the many strong claims of ANN-Human Alignment

Artificial neural networks (ANNs) developed in computer science are successful in a range of vision, language, and reasoning tasks. They can also predict behavioural responses and brain activations of humans better than alternative models. This has led to the common claim that ANNs are the best models of biological intelligence. However, most prediction studies are correlational, and accordingly, do not support causal conclusions. Furthermore, researchers are incentivized to identify ANN-human similarities, as reviewers and editors are more likely to publish studies that report similarities rather than differences. Accordingly, researchers rarely carry out "severe" tests of their claims that are more likely to falsify their conclusions (if indeed the conclusions are false). I show when the relevant experiments are carried out, ANNs do a poor job in explaining human intelligence. The field of NeuroAI needs to change its methods to better characterize ANN-human alignment and build better models of minds.

Mapping the Social World: Interaction as a Core Dimension of Social Scene Perception

Humans are inherently social, and our understanding of the world is shaped from the very beginning by the social interactions we observe and engage in. Social interactions are multifaceted and subtle, yet we can almost instantaneously discern if two people are cooperating or competing, flirting or fighting. We swiftly learn a great deal about people from observing their interactions with others – even a brief interaction gives us important clues about their relationship, their personalities, their social abilities, and their current mood. As a consequence, we excel at extracting information from social scenes, using a small network of brain regions that are sensitive to social cues such as faces, bodies, and biological motion. This work has identified the posterior superior temporal sulcus (pSTS) as a key region for processing dynamic social interactions, but other regions in the “social brain” – particularly extrastriate body area (EBA) – also show sensitivity to specifically interactive information, depending on stimulus content and context. Here, I’ll primarily explore the brain basis of our remarkable ability to extract interactive information from complex social scenes, particularly looking at the role of various structures in the “social brain” across development.

Seeing and thinking: Interplay between externally and internally generated neural representations

Wasps know each other's faces: The development and evolution of face recognition in the Polistes