Dr. Alessandro Tavano
Hauptforschungsgebiete
I am interested in how time shapes perception and cognition.
For perception, I study how temporal noise and temporal expectations co-determine the encoding of stimulus sequences, in interaction with feature-based predictions.
For cognition, I exploit the temporal dimension of speech (amplitude modulation) to try and capture a signature of online access to abstract syntactic categories.
In my experiments, I rely on MEG/EEG, peripheral physiology (ECG, respiration), eyetracking and behavioral data collection. I have an extensive clinical experience, especially on the fuction of subcortical and subtentorial structures in cognition and language perception. One of my current goals is to bridge clinical and neurophysiological investigations.
Recently, I delved into the experience of complex naturalistic stimuli, such as watching a movie, asking how people’s neural states synch with each other, creating an audience that participate in a similar perceptual and aesthetic adventure.
Vita
Ausbildung
| 2014 | Habilitation in Italien als Associate Professor der Psychobiologie |
| 2010 | Master der Psychologie, Universität Triest |
| 2009 | Bachelor der Psychobiologie, Universität Triest |
| 2008–2009 | EEG Training, Universität Barcelona |
| 2003 | PhD in Philosophie, Universität Triest |
| 1999–2000 | Forschungsaufenthalte als Gast-PhD-Kandidat (UCL, London und McGill Universität, Montreal) |
| 1998–1999 | Auslandsstudium, individuelles Forschungsstipendium, Antwerpen |
| 1997–1998 | Training für Jugendleiter, Europäisches Jugendcenter, Straßburg |
| 1997 | Master of Arts in Sprachwissenschaften und Literatur, Universität Triest |
| 1994–1995 | 1-jähriger Auslandsaufenthalt, Erasmus Programm, Reading Universität |
Werdegang
| Seit 2018 | Dozent Differentialpsychologie, Goethe Universität |
| 2018–2019 | Dozent Experimentelle Psychologie, Goethe Universität |
| Seit 2014 | Wissenschaftlicher Mitarbeiter am Max-Planck-Institut für empirische Ästhetik, Frankfurt/Main |
| 2013–2014 | Dozent Biologische Psychologie und Kognitive Prozesse II, Universität Leipzig |
| 2009–2014 | Wissenschaftlicher Mitarbeiter in der Abteilung Kognitive und Biologische Psychologie, Universität Leipzig |
| 2009 | Dozent Neurolinguistik, Universität von Nova Gorica |
| 2008–2009 | Dozent Kommunikationspsychologie, Universität Mailand-Bicocca |
| 2006–2008 | Außerordentlicher Professor, Semiotik, Pragmatik und Sprachphilosophie, Universität von Triest |
| 2003–2009 | Hauptuntersuchungsleiter und Forschungsmitarbeiter, Forschungsinstitut “E. Medea”, San Vito al Tagliamento, Italien |
| 2002–2004 | Dozent Neuropsychologie der Sprache und Klinische Lingusitik, Universität Udine |
| 2002 | Forschungsassistent, Forschungsinstitut “E. Medea”, San Vito al Tagliamento, Italien |
Publikationen
Publikationen
Tavano, A., Rimmele, J., Michalareas, G., Poeppel, D. Neural oscillations in EEG and MEG (In preparation).
Kazanina, N., Tavano, A. What neural oscillations can(not) do for syntactic structure building (Submitted).
Sierra, F., Poeppel, D., Tavano, A. A bias generating temporal distortions in serial perception (Submitted).
Tavano, A., Kotz, S.A. Overt eye movements reveal covert temporal predictions (Under review)
Tavano, A., Nagels, A., Gagl, B., Muralikrishnan, R. Rapid neural encoding of the contrast between native and nonnative speech in the alpha band (Under review).
Tavano, A., Maess, B., Schroeger, E. Neural entrainment via perceptual inferences (Under review).
Gagl, B., Gregorova, K., Golch, J., Hawelka, S., Sassenhagen, J., Tavano, A., Poeppel, D., Fiebach, C.J. Reading at the speed of speech: Eye-movements sample text at the rate of speech production. (Under review).
Sierra, F., Poeppel, D., Tavano, A. How to minimize subjective time distortions. (Under review).
Tavano, A., Blohm, S., Knoop, C.A., Muralikrishnan, R, Scharinger, M., Wagner, V., Thiele, D., Ghitza, O., Ding, N., Menninghaus, W., Poeppel, P. (2020). Neural harmonics reflect grammaticality. Submitted. https://www.biorxiv.org/content/10.1101/2020.04.08.031575v1
Tavano, A., Schroger. E., Kotz, S.A. (2019). Beta power encodes contextual estimates of temporal event probability in the human brain. PLoS ONE 14(9): e0222420. https://doi.org/10.1371/journal.pone.0222420
Tavano, A., Poeppel, D. (2019). A division of labor between power and phase coherence in encoding attention to stimulus streams. NeuroImage 193; 146–156 doi.org/10.1016/j.neuroimage.2019.03.018. Caletti, E., Delvecchio, G., Andrella, A., Finos, L., Perlini, C., Tavano, A. et al. (2018). Prosody abilities in a large sample of affective and non-affective first episode psychosis patients. Comprehensive psychiatry, 86, 31-38. Scharinger, M., Steinberg, J., Tavano, A. (2017) Integrating speech in time depends on temporal expectations and attention. Cortex. doi: 10.1016/j.cortex.2017.05.001. Lorusso, M.L., Burigo, M., Tavano, A. et al. (2017). Learning and Using Abstract Words: Evidence from Clinical Populations. BioMed research international. doi.org/10.1155/2017/8627569 Kokinous, J., Tavano, A., Kotz, S. A., & Schröger, E. (2017). Perceptual Integration of Faces and Voices Depends on the Interaction of Emotional Content and Spatial Frequency. Biological Psychology, 123, 155-165. Tavano, A. & Scharinger, M. (2015). Prediction in speech and language processing. Cortex, 68(0), 1-7. doi:10.1016/j.cortex.2015.05.001. Kokinous, J., Kotz, S. A., Tavano, A., & Schröger, E. (2014) The role of emotion in dynamic audiovisual integration of faces and voices. Social Cognitive and Affective Neuroscience, DOI: 10.1093/scan/nsu105. Tavano, A., Pesarin, A., Drioli, C., Perina, A., Murino, V., & Cristani, M. (2014). Automatic conversational scene analysis. Low-level acoustic feature classification of speech activity in children with Asperger syndrome and typically developing peers. PLoS One, 9(1): e85819. Tavano, A., Widmann, A., Bendixen, A., Trujillo-Barreto, N. J., & Schröger, E. (2014). Temporal regularity facilitates higher-order sensory predictions in fast auditory sequences. European Journal of Neuroscience. DOI: 10.1111/ejn.12404. Tavano, A., Galbiati, S., Recla, M., Bardoni, A., & Strazzer, S. (2014). Cognitive recovery after Severe Traumatic Brain Injury in children and adults: similar outcome but different underlying pathways? Brain Injury, 28(7), 900-905. Recla, M., Bardoni, A., Galbiati, S., Pastore, V., Dominici, C., Tavano, A., Locatelli, F., & Strazzer, S. (2013). Cognitive and adaptive functioning after severe TBI in school-aged children. Brain Injury, 27(7-8), 862-871.
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Projekte
- Sensory Sharpening Effects of Attention and Expectation
Attention to sensory stimuli is never uniformly distributed. We tested whether time-based and feature-based aspects of sensory attention interact in facilitating the detection of new stimuli in a stream. We recorded behavioural and ...
- Neuronale Verarbeitung von Bewegungsverben in metaphorischer Bedeutung
Diese Studie untersucht mit Hilfe von EEG die neuronale Verarbeitung von Verben, die körperliche Bewegungen in metaphorischen und buchstäblichen Kontexten bezeichnen. Die rhetorische Theorie geht davon aus, dass bildhafte Sprache dazu dient, dem ...
- Cortical tracking of complex spoken sentences
Humans naturally tune in to the rhythm of speech (Giraud & Poeppel, 2012). Recent work has shown that low-frequency brain rhythms have been shown concurrently to track the main constituents in a linguistic hierarchy: phrases and sentences ...
- Linguistic competence in the frequency domain
Can rhythmic neural activity be driven to reveal purely internal linguistic competence? To answer this question, I record human electroencephalographic data as participants listen to isochronously delivered word stimuli composing chains of ...
- Brain on Screen
When we go to the cinema, we partake in a complex experience. How does a series of two-dimensional images and sounds blend into an immersive, sometimes lifelike narrative experience? And how do different individuals in the movie theater become ...
- Temporal expectations
In a series of auditory experiments using the roving standard paradigm, I manipulate both time-based (when) and feature-based (what) aspects of prediction to determine if and how they facilitate behavior. Electroencephalographic (EEG) data is ...