I am a cognitive neuroscientist interested in how context and prediction guide processing at neuronal and cognitive levels. I work as a Research Fellow with Prof Lars Muckli using high-field functional brain imaging to study contextual and predictive processing in the visual system. I previously worked with Prof Philippe Schyns using EEG and fMRI to study top-down effects during face processing, and Prof Winrich Freiwald at Rockefeller University in New York using electrophysiology and fMRI. 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. In addition, I am a cognitive behavioural psychotherapist, working with integrative models of therapy.

Publications & Talks:

Bergmann, J., Petro, L. S., Abbatecola, C., Li, M. S., Morgan, A. T., & Muckli, L. (2024). Cortical depth profiles in primary visual cortex for illusory and imaginary experiences. Nature Communications, 15(1), 1002.

Muckli*, L., Petro*, L. S., Abbatecola, C., Adeel, A., Bergmann, J., Deperrois, N., Destexhe, A., Kriegeskorte, N., Levelt, C. N., Maass, W., Morgan, A. T., Papale, P., Pennartz. Cyriel M. A., Peters, B., Petrovici, M. A., Phillips, W. A., Roelfsema, P. R., Sachdev, R. N. S., Seignette, K., … Larkum*, M. E. (2023). The cortical microcircuitry of predictions and context – a multi-scale perspective (v_0.1). Zenodo. https://doi.org/10.5281/zenodo.8380094

Petro, L.S., Smith, F.W., Abbatecola, C., Muckli, L. (2023). The Spatial Precision of Contextual Feedback Signals in Human V1. Biology 12, 1022.

Papale, P., Wang, F., Morgan, A.T., Chen, X., Gilhuis, A., Petro, L.S., Muckli, L., Roelfsema, P.R., Self, M.W. (2022). Feedback brings scene information to the representation of occluded image regions in area V1 of monkeys and humans. bioRxiv.

Li*, M.S.,  Abbatecola*, C., Petro, L.S., Muckli, L. (2021). Numerosity Perception in Peripheral VisionFrontiers in Human Neuroscience.

Svanera, M., Morgan, A.T., Petro, L.S., 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, 5.

Revina, Y., Petro, L.S., Denk-Florea, C.B., Rao, I.S., Muckli. L. (2021). Increased region of surround stimulation enhances contextual feedback and feedforward processing in human V1. bioRxiv

Petro, L.S. Muckli, L. (2020). Neuronal codes for predictive processing in cortical layers. Behavioural and brain sciences, 43, e142.

Svanera, M., Morgan, A.T., Petro, L.S., Muckli, L. (2020). An unsupervised deep neural network for image completion resembles early visual cortex fMRI activity patterns for occluded scenes. bioRxiv. 

Vizioli, L., De Martino, F., Petro, L.S., Kersten, D., Ugurbil, K., Yacoub, E., Muckli, L. Multivoxel Pattern of Blood Oxygen Level Dependent Activity can be sensitive to stimulus specific fine scale responses. Scientific Reports, 10, 7565.

Morgan, A.T., Petro, L.S., Muckli L. (2019). Scene representations conveyed by cortical feedback to early visual cortex can be described by line drawings. Journal of Neuroscience, pii: 0852-19.

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 cortexFrontiers in Psychology, 5:1223.

Muckli L. & Petro L.S. (2013). Network interactions: non-geniculate input to V1Current 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 ExpressionsCurrent Biology (17) pp 1580-1585


Lucy.Petro@glasgow.ac.uk, +44 (0)141 330 1607

Room 625, Institute of Neuroscience and Psychology, 62 Hillhead Street, Glasgow, G12 8QB