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Learning to see in noise.

research learningtoseeRecent behavioural studies have shown that learning can be a key facilitator in perceptual integration for the detection and recognition of objects in cluttered scenes. Further, neurophysiological studies suggest that learning enhances the sensitivity of neural processing. However, little is known about the role of learning in shaping perceptual integration and visual recognition processes across stages of visual analysis in the human brain. In this work, we use human psychophysics and brain imaging to understand the neural plasticity mechanisms that support behavioural improvement in perceptual integration and visual recognition. We ask: How does the human visual brain learn objects in natural cluttered scenes? Does the human visual brain take advantage of natural image regularities (e.g. grouping of elements with similar orientation) that determine the distinctiveness of targets when learning novel objects in cluttered scenes? Does learning facilitate perceptual integration and shape detection in the absence of regularities that usually mediate the grouping of shape contours in natural images? This work will provide a) significant insights into the role of learning in shaping brain functions that mediate key perceptual and cognitive abilities, and b) the foundation for studying the role of learning in visual or cognitive deficits that impair these functions.

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“Neurocomputation: from brains to machines” 25th November 2015, Corpus Christi College

Nov 09, 2015

You are invited to attend the next in the series of Cambridge Neuroscience Interdisciplinary Workshops on “Neurocomputation: from brains to machines”. This workshop is being hosted by Professor Zoe Kourtzi and is being run in association with the Big Data Strategic Research Initiative.

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