Visual Neuroscience Lab
We study how we see what we see, using behavioural and neurophysiological techniques.
How an object is perceived depends on the temporal context in which it is encountered. Sensory signals in the brain also depend on temporal context, often called adaptation. We are studying how adaptation alters signals in neurones and humans, and how adaptation might have an impact on the efficiency of brain processing. Our observations also provide a way in which to non-invasively ‘knock-out’ populations of nerve-cells in normal humans and animals.
The receptive fields of nerve cells early in the visual pathway are usually thought to be small and simple. We have shown that many of them are sensitive to a larger fraction of visual space than usually thought. This makes the signals of these nerve cells sensitive to the global spatial structure of images, and we are currently studying how this sensitivity to global structure may be differentially expressed in pathways that subserve conscious and unconscious vision.
Non-sensory, intrinsically generated signals like attention are integrated into sensory pathways at multiple stages, but we know little about how this integration is done, or how particular aspects of the world are selected for attention in the first place. We are recording neural activity in the context of different tasks to try to understand the interrelationship of sensation and cognition.
MOTION SIGNALS IN THE CEREBRAL CORTEX
A small area of the cerebral cortex – area MT – is thought to hold a special role in motion vision and the control of eye movements. We have been making measurements of the motion signals carried by populations of nerve cells in area MT, to understand how their how signals might be used for surface segmentation (eg. transparency) and surface integration (eg. ‘pattern motion’).
- Visual motion discrimination by propagating patterns in primate cerebral cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience DOI: 10.1523/jneurosci.1538-17.2017
- Interpreting the dimensions of neural feature representations revealed by dimensionality reduction. NeuroImage DOI: 10.1016/j.neuroimage.2017.06.068
- Spectral signatures of feedforward and recurrent circuitry in monkey area MT Cerebral Cortex DOI: 10.1093/cercor/bhw124
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