Decoding rapid object representations

Humans are extremely fast at recognising objects, and can do this very reliably. Information about objects and object categories emerges within 200 milliseconds in the human visual system, even under difficult conditions such as occlusion or low visibility. These neural representations can be highly complex and multidimensional, despite relying on limited visual information. Understanding emerging object representations necessitates time-resolved neuroimaging methods with millisecond precision, such as EEG and MEG. Recent time-resolved neuroimaging work has used decoding methods in rapid serial visual presentation designs to show that relevant object-information about multiple sequentially presented objects is robustly encoded by the brain. This talk will highlight recent research on the time course of object representations in rapid image sequences, focusing on three key findings: (1) object representations are highly automatic, with robust representations emerging even with fast-changing visual input. (2) emerging object representations are highly robust to changes in context and task, suggesting strong reliance on feedforward processes. (3) object representational structures are highly consistent across individuals, to the extent that neural representations are predictive of independent behavioural judgments on a variety of tasks. Together, these findings suggest that the first sweep of information through the visual system contains highly robust information that is readily available for read-out in behavioural decisions.