TY  - INPR
A1  - Gagl, Benjamin
A1  - Richlan, Fabio
A1  - Ludersdorfer, Philipp
A1  - Sassenhagen, Jona
A1  - Eisenhauer, Susanne
A1  - Gregorova, Klara
A1  - Fiebach, Christian
T1  - The lexical categorization model: A computational model of left-ventral occipito-temporal cortex activation in visual word recognition
T2  - bioRxiv
N2  - To characterize the left-ventral occipito-temporal cortex (lvOT) role during reading in a quantitatively explicit and testable manner, we propose the lexical categorization model (LCM). The LCM assumes that lvOT optimizes linguistic processing by allowing fast meaning access when words are familiar and filter out orthographic strings without meaning. The LCM successfully simulates benchmark results from functional brain imaging. Empirically, using functional magnetic resonance imaging, we demonstrate that quantitative LCM simulations predict lvOT activation across three studies better than alternative models. Besides, we found that word-likeness, which is assumed as input to LCM, is represented posterior to lvOT. In contrast, a dichotomous word/non-word contrast, which is assumed as the LCM’s output, could be localized to upstream frontal brain regions. Finally, we found that training lexical categorization results in more efficient reading. Thus, we propose a ventral-visual-stream processing framework for reading involving word-likeness extraction followed by lexical categorization, before meaning extraction.
Y1  - 2020
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/72419
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-724195
IS  - 085332
ER  -