NEUROCIRCLE · Probing the neural processes underpinning perceptual decisions on a continuum

Probing the neural processes underpinning perceptual decisions on a continuum

The overarching goal of this project was to better understand the kinds of simple perceptual decisions that people make throughout the day. Sensorimotor decisions, in which we perceive a stimulus and respond with an appropriate action underlie many of our everyday interactions with the world. As fundamental building blocks of cognition, there can be serious consequences when these decision processes are impaired due to neurological disorders or ageing. There is a massive interdisciplinary research effort aimed at understanding the cognitive mechanisms underpinning perceptual decision making, but the vast majority of this research employs decision tasks with just two alternative outcomes. For example, a classic task in psychology and neuroscience involves looking at a cloud of moving dots and identifying whether they are moving more to the left or to the right. This work has facilitated the development of detailed computational models of cognitive processes that can explain people’s responses and response times. These models are used to estimate parameters corresponding to meaningful psychological constructs, such as the speed of information processing and response caution, which can then be compared across interesting task conditions or individuals. However, many of our everyday decisions cannot be boiled down to just two alternatives. When playing sports, cooking, or walking down the street, we face a constant stream of perceptual decisions for which the potential outcomes lie on a continuum. In this project we took advantage of a new cognitive model for perceptual decisions with continuous outcomes, to better understand these types of decisions. Decision neuroscience research shows that perceptual decision processing takes place simultaneously at multiple levels in the brain, suggesting a continuous flow of information from sensory to motor systems. With non-invasive brain recordings from electroencephalography (EEG), we can identify distinct signals representing sensory evidence encoding, the accumulation of evidence forming a decision, and motor signals related to preparing the response. Computational models that are designed solely to explain decision-making behaviour are not equipped to distinguish between processing at these different levels. Thus, the aim of this project was to use neural decision signals at multiple levels of processing in the human brain to more clearly parse the psychological effects identified by cognitive models. Furthermore, we wanted to use these decision signals to design more complex models that better reflect the hierarchical structure of decision processing. We found that incorporating neural signals into cognitive models of decision making allowed us to identify important decision process components that are missed by more traditional behavioural modelling.

Data: CORDIS, © European Union