Dr Lucy S. Petro
I graduated from the University of Glasgow with a BSc Hons in Neuroscience, a Masters degree in Research Methods of Psychological Science and a PhD in Psychology completed in the lab of Prof Philippe Schyns using EEG and fMRI to study top-down effects during face processing. I then did postdoctoral research with Prof Winrich Freiwald at Rockefeller University in New York before returning to Glasgow to work with Prof Lars Muckli using fMRI to study predictive processing of sensory information in the visual system. I am also interested in how complex and flexible predictions govern behaviour and emotional responses, and how maladaptive higher-level internal models can be altered with psychotherapeutic intervention. I am a cognitive behavioural psychotherapist, working with integrative models of therapy.
Publications & Talks
Larkum, M.E., Petro, L.S., Sachdev, R.N.S., Muckli, L. (2018). A Perspective on Cortical Layering and Layer-Spanning Neuronal Elements. Frontiers in Neuroanatomy, 17;12:56.
Petro, L.S., Muckli, L. (2018). Forecasting Faces in the Cortex. Trends in Cognitive Sciences, 22, 95-97.
Edwards, G., Vetter, P., McGruer, F., Petro, L.S.*, Muckli, L.*. (2017). Predictive feedback to V1 dynamically updates with sensory input. Scientific Reports, 7(1):16538.
Revina, Y., Petro, L.S., Muckli, L. (2017). Cortical feedback signals generalise across different spatial frequencies of feedforward inputs. Neuroimage.
Muckli, L. & Petro, L.S. (2017). The significance of memory in sensory cortex. Trends in Neurosciences. 40(5):255-256.
Petro, L.S., Paton, A.T., Muckli, L. (2017). Contextual modulation of primary visual cortex by auditory signals. Philos Trans R Soc Lond B Biol Sci. 19;372(1714).
Petro L.S. & Muckli L. (2016). The brain's predictive prowess revealed in primary visual cortex. PNAS. 113(5):1124-5.
Petro L.S. & Muckli L. (2016). The laminar integration of sensory inputs with feedback signals in human cortex. Brain and Cognition. 112:54-57.
Morgan, A.T., Petro, L.S., Muckli, L. (2016). Cortical feedback to V1 and V2 contains unique information about high-level scene structure. bioRxiv
Muckli L., De Martino, F., Vizioli L., Petro L.S., Smith, F.W., Ugurbil, K., Goebel, R. & Yacoub, E. (2015). Contextual feedback to superficial layers of V1. Current Biology. 25(20):2690-5.
Petro L.S., Vizioli L. & Muckli L. (2014). Contributions of cortical feedback to sensory processing in primary visual cortex. Frontiers in Psychology, 5:1223.
Muckli L. & Petro L.S. (2013). Network interactions: non-geniculate input to V1. Current Opinion in Neurobiology, 23, 195–201.
Muckli L., Petro L.S. & Smith F.W. (2013). Backwards is the way forward:feedback in the cortical hierarchy predicts the expected future. Behavioural and Brain Sciences, 36:4.
Petro L.S., Smith F.W., Schyns P.G. & Muckli L. (2013). Decoding face categories in diagnostic sub-regions of primary visual cortex. European Journal of Neuroscience, 37, 1130-9.
Petro L.S., Smith F.W., Schyns P.G. & Muckli L. (2009). Early Visual Sensitivity to Diagnostic Information During the Processing of Facial Expressions. NeuroImage, 47, S191. Organization for Human Brain Mapping, San Francisco, CA.
Schyns P.G., Petro L.S. & Smith M.L. (2009). Transmission of Facial Expressions of Emotion Co-Evolved with Their Efficient Decoding in the Brain: Behavioral and Brain Evidence. PLoS ONE Vol.4(5)
Schyns P.G., Petro L.S. & Smith M.L. (2007). Dynamics of Visual Information Integration in the Brain for Categorizing Facial Expressions. Current Biology (17) pp 1580-1585
Room 513, Institute of Neuroscience and Psychology, 58 Hillhead Street, Glasgow, G12 8QB