Humans are ‘prediction machines’. We are exquisitely good at predicting future events and anticipating other agents. We owe this remarkable ability to the internal predictive models that we construct of ourselves and our environment, based on regularities in previous input. The tendency to seek and predict patterns in the environment is central to many aspects of human cognition.
Our internal predictive models are constantly evaluated and updated based on new, surprising input. Surprise (i.e. the distance between one’s prior and current beliefs) appears an essential ingredient in various cognitive faculties such as perception, learning, motivation and action and it strongly drives brain activity in both sub-cortical and cortical networks underlying goal-directed behavior.
The overall aim of this research proposal is to elucidate how surprise is computed within sensory circuits and how it influences information seeking behavior. To achieve this, I will: 1) test the theoretical proposition that surprise signals emerge from the discrepancy between prediction signals and input signals that are represented in distinct layers of the neocortex, using ultra-high field neuroimaging in human volunteers; 2) investigate how sensory surprise signals may be communicated to downstream areas to update the brain’s attentional sampling policies; and 3) investigate the relationship between sensory surprise and the explicit drive for information that we call curiosity.
Project SURPRISE has the broad general goal of understanding the neural generation and cognitive and behavioral consequences of sensory surprise signals. This is an ambitious goal, as it requires an integration from laminar circuit models that calculate sensory surprise to systems neuroscience and computational models of behavior, to investigate how agents utilitize surprise to influence information sampling. Thereby, the proposal bridges several levels of analysis (from circuit models to behavior) and several cognitive domains (perception, attention, motivation and curiosity). While this breadth is challenging, I hope that it will create exciting crosslinks between fields of research that are usually not connected, by studying a common principle - surprise - that may connect different levels of description and fields of cognition.
By embarking on a multi-scale investigation, from laminar circuit mechanisms to computational models of cognition and behavior, I hope to elucidate the basic mechanisms of surprise in the brain and its fundamental role in cognition. This may have important implications for understanding perception, learning and motivated cognition.
