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Building a computational basis for the brain response in the left ventral occipito-temporal cortex: Understanding the Sparse Familiarity Model of visual word recognition

Objective

The left ventral occipito-temporal cortex (lvOT) is an integral part of the ventral visual processing stream and is consistently activated in response to visual words. Recently, I developed a computational implementation of the lvOT functioning during visual word recognition, the sparse familiarity model (SFM). The single assumption of the SFM is that the statistical patterns of letter string familiarity are the fundament of lvOT functioning. The SFM is able to simulate prominent lvOT benchmark contrasts and its simulations predict brain activation of the lvOT in multiple fMRI studies. The main aim of the present proposal is to use the model to systematically investigate hotly debated topics in word recognition research concerning current theoretical approaches for the lvOT: (1) The influence of learning and (2) domain specificity (i.e. for words) vs. generalization (i.e. to face and object recognition) of lvOT function and neuronal populations. In the course of these investigations, the SFM will be developed into a learning model and a generalized model for word, face, and object recognition. Central to this will be high-density electrophysiological measurements (MEG) that sample brain activation with high temporal resolution and reasonable spatial resolution, to allow connectivity analysis at different time points. The MEG measurement, in addition to fMRI measures, will be essential to test theoretical assumptions concerning the proposed two stages of the SFM that differ fundamentally in terms of neuronal and cognitive mechanisms. Critical will be the association of these stages to different time windows and assumptions about the brain networks involved. The host, Prof. Fiebach at Frankfurt University, has a strong focus on the neurocognitive basis of language and access to an MEG, which is essential for realizing this project. To summarize, the goal of the project is to establish the sparse familiarity model and extend its functioning to resolve current debates.

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Topic(s)

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MSCA-IF-EF-ST - Standard EF

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Call for proposal

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(opens in new window) H2020-MSCA-IF-2015

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Coordinator

JOHANN WOLFGANG GOETHE-UNIVERSITAET FRANKFURT AM MAIN
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 171 460,80
Address
THEODOR W ADORNO PLATZ 1
60323 FRANKFURT AM MAIN
Germany

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Region
Hessen Darmstadt Frankfurt am Main, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 171 460,80
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