Meet the Expert: Stefania Bracci, PhD
The role of behavioural goals in shaping representations in the ventral visual pathway
- https://www.uni-giessen.de/de/fbz/ggn/events/mte-folder/mte_bracci
- Meet the Expert: Stefania Bracci, PhD
- 2024-06-05T10:00:00+02:00
- 2024-06-05T12:00:00+02:00
- The role of behavioural goals in shaping representations in the ventral visual pathway
Wann
05.06.2024 von 10:00 bis 12:00 (Europe/Berlin / UTC200)
Wo
Raum F005, Otto-Behaghel-Straße 10 F
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Stefania Bracci, PhD (Center for Mind/Brain Sciences - CIMeC) |
is an assistant professor at the Center for Mind/Brain Sciences (CIMeC) in Trento (Italy). She holds a Bachelor of Science in Psychology and a Master of Science in Neuropsychology and Cognitive Rehabilitation from the University of Bologna (Italy). Stefania Bracci received her PhD in 2011 at Northumbria University (UK) on the topic of "Neural Correlates of Hand-Tool Interaction". After a post-doctoral and research period at KU Leuven (Belgium), she worked as principal investigator of the Object Vision group at the CIMeC, where she became assistant professor in 2022.
Stefania Bracci's group investigates the basic dimensions underlying the organization of object representations in the visual cortex by combining behavioural experiments, neuroimaging and deep neural networks.
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The role of behavioral goals in shaping representations in the ventral visual pathway |
How does our brain represent the visual environment? Classic theories of object vision focus on object recognition, yet human object vision is far from being solved, and accumulating evidence points to the complexity of the multidimensional representational space that underlies visual representations. In this seminar, I suggest that to understand object vision, we need to move beyond object recognition, as considered the final goal of visual perception, and take into account the role of behavioural goals in shaping the organization of object space in the visual cortex. Understanding the core mechanisms behind this object space could inform the conception of computational models that perceive and represent the world as humans do.
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