Muckli Lab update
Published: 17 June 2021
New papers, new students and BBSRC grant news...
Prof Lars Muckli published a paper with Prof Frank Pollick and Greta Todorova, showing high precision prediction error processing in autistic individuals using an apparent motion paradigm. Todorova, G. K., Pollick, F. E., & Muckli, L. (2021). Special treatment of prediction errors in autism spectrum disorder. Neuropsychologia, 108070.
In another paper, Prof Muckli’s group investigated the processing of numerical magnitude in peripheral vision, finding that top-down factors impact how predictions are incorporated into perceptual decisions about numerosity in the periphery. Li, M.S., Abbatecola, C., Petro,L.S., Muckli, L. (2021). Numerosity perception in peripheral vision. Frontiers in Human Neuroscience.
In two other papers, the work of Dr Michele Svanera and Prof Lars Muckli provides a deep learning approach to segmenting whole MRI brain volumes at 7 Tesla at once, and compares a self-supervised deep neural network with human fMRI data in early visual cortex. Svanera, M. , Benini, S., Bontempi, D. and Muckli, L.(2021) CEREBRUM-7T: fast and fully volumetric brain segmentation of 7 Tesla MR volumes. Human Brain Mapping, (doi: 10.1002/hbm.25636)(PMID:34598307),
Svanera, M. , Morgan, A. T., Petro, L. S. and Muckli, L.(2021) A self-supervised deep neural network for image completion resembles early visual cortex fMRI activity patterns for occluded scenes. Journal of Vision, 21(7), 5. (doi: 10.1167/jov.21.7.5)(PMID:34259828)
Our new BBSRC grant has officially started, ‘Layer-specific cortical feedback dynamics’ in which we will test a novel conceptual model of early visual cortex multiplexing perceptual information with predictive information beyond our world view.
Lastly, welcome to our new PhD students, Belén Montabes de la Cruz and Zirui Zhang!
First published: 17 June 2021