Humans constantly make perceptual decisions on human faces and voices. These regularly come with the challenge of receiving only uncertain sensory evidence, resulting from noisy input and noisy neural processes. Efficiently adapting one’s internal decision system including prior expectations and subsequent metacognitive assessments to these challenges is crucial in everyday life. However, the exact decision mechanisms and whether these represent modifiable states remain unknown in the general population and clinical patients with psychosis. Using data from a laboratory-based sample of healthy controls and patients with psychosis as well as a complementary, large online sample of healthy controls, I will demonstrate how a combination of perceptual face and voice recognition decision fidelity, metacognitive ratings, and Bayesian computational modelling may be used as indicators to differentiate between non-clinical and clinical states in the future.

The brain makes decisions by accumulating evidence until there is enough to stop and choose. Neural mechanisms of evidence accumulation are well established in association cortex, but the site and mechanism of termination is unknown. Here, we elucidate a mechanism for termination by neurons in the primate superior colliculus. We recorded simultaneously from neurons in lateral intraparietal cortex (LIP) and the superior colliculus (SC) while monkeys made perceptual decisions, reported by eye-movements. Single-trial analyses revealed distinct dynamics: LIP tracked the accumulation of evidence on each decision, and SC generated one burst at the end of the decision, occasionally preceded by smaller bursts. We hypothesized that the bursts manifest a threshold mechanism applied to LIP activity to terminate the decision. Focal inactivation of SC produced behavioral effects diagnostic of an impaired threshold sensor, requiring a stronger LIP signal to terminate a decision. The results reveal the transformation from deliberation to commitment.

The neurobiology of decision-making is informed by neurons capable of representing information over time scales of seconds. Such neurons were initially characterized in studies of spatial working memory, motor planning (e.g., Richard Andersen lab) and spatial attention. For decision-making, such neurons emit graded spike rates, that represent the accumulated evidence for or against a choice. They establish the conduit between the formation of the decision and its completion, usually in the form of a commitment to an action, even if provisional. Indeed, many decisions appear to arise through an accumulation of noisy samples of evidence to a terminating threshold, or bound. Previous studies show that single neurons in the lateral intraparietal area (LIP) represent the accumulation of evidence when monkeys make decisions about the direction of random dot motion (RDM) and express their decision with a saccade to the neuron’s preferred target. The mechanism of termination (the bound) is elusive. LIP is interconnected with other brain regions that also display decision-related activity. Whether these areas play roles in the decision process that are similar to or fundamentally different from that of LIP is unclear. I will present new unpublished experiments that begin to resolve these issues by recording from populations of neurons simultaneously in LIP and one of its primary targets, the superior colliculus (SC), while monkeys make difficult perceptual decisions.

Whether we are deciding about Covid-related restrictions, estimating a ball’s trajectory when playing tennis, or interpreting radiological images – most any choice we make is based on uncertain evidence. How do we infer that information is more or less reliable when making these decisions? How does the brain represent knowledge of this uncertainty? In this talk, I will present recent neuroimaging data combined with novel analysis tools to address these questions. Our results indicate that sensory uncertainty can reliably be estimated from the human visual cortex on a trial-by-trial basis, and moreover that observers appear to rely on this uncertainty when making perceptual decisions.