Dynamic similarity of brain activity in humans: from single areas to functional networks

Abstract

What makes us similar and different? The intriguing problem has been studied throughout the centuries by philosophers and scientists and affects the way we live our lives in relationship to the people around us. The brain can process the external world in a similar way across people and even across animal species, but the boundary between similar/different is a dynamic one that changes in space – "where" in the brain we are similar – and in time – "when" brain activity is similar between us. It has been possible to show how localized brain regions show varying levels of intersubject similarity during controlled and naturalistic experiments using functional magnetic resonance imaging. However, the temporal dimension – "when" brain activity is similar between two brains – has remained poorly explored. Furthermore, the brain is a network and the concept of network-level intersubject similarity poses novel challenges especially when considering inter-individual differences both between and within healthy and clinical populations. Here we studied how intersubject similarity of brain activity is modulated in time due to the content of the stimuli or to the psychological perspective that subjects take. These novel problems led to the development of new methods to quantify instantaneous similarity between brains. In addition, moving emphasis from local neuronal activity to distributed network activity, we addressed the challenge of defining the similarity between brain subnetworks to identify their intersubject similarity in relation to behavioural measures. In the first study we used videoclips to induce strong emotions during fMRI scanning and computed how time-varying intersubject correlation of brain activity was modulated by the emotional experience. Feeling similar emotions makes the brains tick in sync. In the second study we introduced novel measures for instantaneous brain similarity for local activity and for dynamic functional connectivity. In the third study we considered how taking different psychological perspectives is reflected in brain activity. Finally, in the fourth study we isolated functional brain networks of high functioning individuals with autism spectrum disorder and healthy controls while watching a feature film, and proposed a method to correlate the autism quotient and the configuration of brain subnetworks. The work presented here reflects recent developments in human non-invasive neuroscience, by stressing the importance of the temporal dimension from local activity dynamics to time-varying networks and the individuality of each brain in relationship to others. Mutual understanding and similarity of behaviour between individuals might be related to similarity of brain function and structure. Although the causality of such relationships might be difficult to disentangle, the current work proposes tools to quantify them.