Address book


Staff Structures


Back to the list


Professore Ordinario






Office hours

  • Wednesday from 10:30 to 12:15
    at Dipartimento di Psicologia Generale, sede di Via Venezia 12 (piano terra edificio PSICO 2)
    Prendere un appuntamento sul calendario online (copiare l'indizzo qui sotto):




Zorzi, M, & Testolin, A. (2018). An emergentist perspective on the origin of number sense. Phil. Trans. R. Soc. B, 373, 20170043.

Testolin, A., Stoianov, I., & Zorzi, M. (2017). Letter perception emerges from unsupervised learning and recycling of natural image features. Nature Human Behaviour, 1, 657–664.

Sella, F., Berteletti, I., Lucangeli, D., & Zorzi, M. (2017). Preschool children use space, rather than counting, to infer the numerical magnitude of digits: Evidence for a spatial mapping principle. Cognition, 158, 56-67.

Blini, E., Romeo, Z., Spironelli, C., Pitteri, M., Meneghello, F., Bonato, M., & Zorzi, M. (2016). Multi-tasking uncovers right spatial neglect and extinction in chronic left-hemisphere stroke patients. Neuropsychologia, 92, 147-157.

Sella, F., Berteletti, I., Lucangeli, D., & ZORZI, M. (2016). Spontaneous non-verbal counting in toddlers. Developmental Science, 19, 329-337.

Testolin, A., Stoianov, I., Sperduti, A., & Zorzi, M. (2016). Learning orthographic structure with sequential generative neural networks. Cognitive Science, 40, 579–606.

Lisi, M., Bonato, M., & Zorzi, M. (2015). Pupil dilation reveals top-down attentional load during spatial monitoring. Biological Psychology, 112, 39–45.

Cutini, S., Scarpa, F., Scatturin, P., Dell’Acqua, R. & Zorzi, M. (2014). Number-space interactions in the human parietal cortex: Enlightening the SNARC effect with functional Near-Infrared Spectroscopy. Cerebral Cortex, 24(2), 444-451.

Ziegler, JC., Perry, C., & Zorzi M. (2014). Modelling reading development through phonological decoding and self-teaching: implications for dyslexia. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1634), 20120397.

Zorzi, M., Barbiero, C., Facoetti, A., Lonciari, I., Carrozzi, M., Montico, M., Bravar, L., et al. (2012). Extra-large letter spacing improves reading in dyslexia. Proceedings of the National Academy of Sciences of the United States of America, 109(28), 11455-9.

Stoianov, I., & Zorzi, M. (2012). Emergence of a “visual number sense” in hierarchical generative models. Nature neuroscience, 15(2), 194-6.

Casarotti, M., Lisi, M., Umiltà, C., & Zorzi, M. (2012). Paying attention throgh eye movements: A computational investigation of the premotor theory of spatial attention. Journal of Cognitive Neuroscience, 14, 1519-1531.

Piazza, M., Facoetti, A., Trussardi, A. N., Berteletti, I., Conte, S., Lucangeli, D., Dehaene, S., & Zorzi, M. (2010). Developmental trajectory of number acuity reveals a severe impairment in developmental dyscalculia. Cognition, 116(1), 33-41.

Bonato, M., Priftis, K., Marenzi, R., Umiltà, C., & Zorzi, M. (2010). Increased attentional demands impair contralesional space awareness following stroke. Neuropsychologia, 48, 3934-3940.

Perry, C., Ziegler, J.C., & Zorzi, M. (2007). Nested incremental modeling in the development of computational theories: The CDP+ model of reading aloud. Psychological Review, 114, 273-315.

Zorzi M., Priftis, K., & Umilta` C. (2002). Neglect disrupts the mental number line. Nature, 417,138-139.

Research Area

Research in my laboratory (Computational Cognitive Neuroscience Lab, is focused on the study of the computational bases of cognition, from development to skilled performance and to breakdowns of processing in atypical development or after brain damage. To address these issues we use a cognitive neuroscience approach that combines several methodologies, including computational modeling, behavioral studies (reaction times and psychophysics), neuropsychology, and functional neuroimaging (fMRI, fNIRS, EEG). Main themes: 1) numerical cognition and dyscalculia; 2) attention, space coding, neglect; 3) reading and dyslexia; 4) neural networks (deep learning) and computational neuroscience.

Thesis proposals

Topics for theses:
- Artificial intelligence (neural networks, deep learning, machine learning)
- Numerical cognition (numerosity perception, numbers and space, dyscalculia)
- Spatial attention (attention and cognition, multitasking, neuropsychology of attention)
- Reading (letter and word perception, dyslexia)
- Computational neuroimaging (connectomics, brain-behavior mapping)

- Experimental cognitive psychology
- Computational modeling (only Master or PhD students)
- Neuropsychology (neurological patients or children with learning disabilities) (only Master or PhD students)
- Neuroimaging (fMRI, EEG, fNIRS) (only Master or PhD students)

See lab website for more info:
Computational Cognitive Neuroscience Lab (

Supervision of PhD thesis: see section "Notice and additional information"