The goal of our research is to understand how prior knowledge and expectations influence how we perceive the world, and how this is realised by the brain.
Visual perception is not simply a product of the light that hits our eyes, but is instead strongly influenced by our prior knowledge and expectations. Perception can be seen as a process of inference, trying to arrive at the most likely explanation for our sensory inputs given our knowledge of the world. We use advanced neuroimaging methods to reveal the neural mechanisms whereby prior knowledge influences perception.
Ultimately, these insights may improve our understanding of disorders like psychosis and autism, which are characterised by aberrations in perception.
Revealing the fundamental computational architecture of visual cortex.
There is much we don’t know about how the visual cortex is organised. Our group uses groundbreaking ultra-high field (7T) functional magnetic resonance (fMRI) techniques to study neural signals in the different layers of human visual cortex (Kok et al., 2016). This allows us to study how neural representations in the different cortical layers are influenced by expectations, thereby revealing the computational architecture of visual cortex.
Establishing how the neural computations underlying perception unfold over time.
There is currently much debate on whether visual processing is biased by expectations from the moment they arrive in the cerebral cortex, or whether expectation only influences later decisionmaking processes. We are addressing these and other questions using magnetoencephalography (MEG), allowing us to study the unfolding of neural signals with millisecond precision (Kok et al., 2017).
Revealing the neural source of expectations.
In recent work, we revealed that an important memory region, the hippocampus, contains representations of expected visual stimuli (Kok & Turk-Browne, 2018). We are using highresolution fMRI to study the communication between visual cortex and specific subfields of the hippocampus, to reveal the neural networks by which the brain generates visual expectations from memory.
- Learning to Perceive and Perceiving to Learn Trends in Cognitive Sciences, 24 (4), 260-261 DOI: 10.1016/j.tics.2020.01.002
- Content-based Dissociation of Hippocampal Involvement in Prediction. Journal of Cognitive Neuroscience, 1-19 DOI: 10.1162/jocn_a_01509
- View all publications by the Visual Perception team