The lexical categorization model: A computational model of left-ventral occipito-temporal cortex activation in visual word recognition

Sassenhagen

Haan

et al. 2018

Preprint

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Most current models assume that the perceptual and cognitive processes of visual word recognition and reading operate upon neuronally coded domain-general low-level visual representations -typically oriented line representations. We here demonstrate, consistent with neurophysiological theories of Bayesian-like predictive neural computations, that prior visual knowledge of words is utilized to 'explain away' redundant and highly expected parts of the visual percept. Subsequent processing stages, accordingly, operate upon an optimized representation of the visual input, the orthographic prediction error, highlighting only information relevant for word identification. We show that this informationally optimized representation is related to orthographic word characteristics, accounts for word recognition behavior, and is processed early in the visual processing stream, i.e., in occipital cortex and before 200 ms after word-onset. Based on these findings, we propose that prior visual-orthographic knowledge is used to optimize the representation of visually presented words, which in turn allows for highly efficient reading processes.

Section: Discussionmentioning

confidence: 99%

An Orthographic Prediction Error as the basis for efficient Visual Word Recognition

Sassenhagen

Haan

et al. 2018

Preprint

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“…However, with this procedure we hardly found significant results for the letter string characteristics indicated as relevant in the behavioral analysis, with the exception of lexicality effects during prime processing. The absence of significant decodability of OLD20 and word frequency from MEG responses was unexpected (i) as both effects were found reliable in our behavioral data, and (ii) given that word frequency and orthographic similarity have in previous work been found to modulate EEG/MEG responses to words and pseudowords (e.g., Embick et al, 2001;Assadollahi and Pulvermüller, 2003;Vergara-Martínez and Swaab, 2012;Dufau et al, 2015;Gagl et al, 2016;Carrasco-Ortiz et al, 2017). Effects of OLD20 and word frequency should thus at least be found to reliably modulate brain activity during the presentation of the prime.…”

Section: Figurementioning

confidence: 43%

“…given that word frequency and orthographic similarity have in previous work been found to modulate M/EEG responses to words and pseudowords (e.g., Embick et al, 2001;Assadollahi and Pulvermüller, 2003;Vergara-Martínez and Swaab, 2012;Dufau et al, 2015;Gagl et al, 2016;Carrasco-Ortiz et al, 2017). Effects of OLD20 and word frequency should thus at least be found to reliably modulate brain activity during the presentation of the prime.…”

Section: Supporting Results 5 Multivariate Pattern Decoding Analysis and Resultsmentioning

confidence: 89%

Predictive pre-activation of orthographic and lexical-semantic representations facilitates visual word recognition

Eisenhauer

Fiebach

2020

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The efficiency of reading, to a crucial extent, results from the fact that visual word recognition is faster in predictive contexts (like sentences or texts). This observation is consistent with predictive coding models, but it is so far not sufficiently understood which aspects of the rich set of linguistic representations that is activated during reading contribute to this context-dependent facilitation. Candidate representations are visual, orthographic, phonological, and/or lexical-semantic in nature. Our study investigates which representations contribute to efficient word recognition in predictive context with a well-controlled repetition priming paradigm, including words and pseudowords (i.e., pronounceable nonwords), that was combined with magnetoencephalography (MEG) measurements in human participants (both sexes). We used high-powered linear mixed modeling to test the hypothesis that context-dependent facilitation relies on the pre-activation of linguistic representations prior to perceiving the expected stimulus. Behavioral data from 49 participants indicate that word predictability (i.e., context present vs. absent) facilitated orthographic and lexical-semantic, but not visual or phonological processes. MEG data from 38 participants show sustained activation of orthographic and lexical-semantic codes in the interval between prime and target, i.e., before processing the predicted stimulus. Also, we found a positive correlation between these pre-activation effects and brain responses elicited when processing the expected letter string. Pre-activation was more stable across time in words than in pseudowords. These results suggest that readers use orthographic and lexical-semantic representations to actively predict upcoming words and that this predictive process is modulated by the presence of prior knowledge (in words as opposed to pseudowords).

“…Prelexical familiarity is critical for the interpretation of our knowledge effects as we selected the letter strings such that prior to familiarization training, prelexical familiarity (i.e., OLD20; Yarkoni et al, 2008) and thus also prelexical processing, were comparable between the pseudowords and words. This match reflects that, a priori, orthographic processing difficulty was held constant across knowledge conditions and therefore should elicit similar activation strength in left posterior brain areas (as for example shown by Gagl et al, 2016or Vinckier et al, 2007 using a match with quadrigram frequency). Still, we expected (consistent with Glezer et al, 2015) that pseudoword familiarization, by mere repetition, facilitates prelexical processing of the learned pseudowords.…”

Section: Knowledge Effectsmentioning

confidence: 89%

Context-based facilitation in visual word recognition: Evidence for visual and lexical but not pre-lexical contributions

Eisenhauer

Fiebach

2018

Preprint

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Visual word recognition is facilitated by word knowledge (i.e., word familiarity) and predictive context, as reflected in faster reading times and reduced neuronal activation for highly familiar or predictable words. Previous studies could not dissociate whether knowledge-and context-based facilitation requires semantic knowledge or can also stem from prelexical sources of information.Here, we experimentally separate prelexical (i.e., orthographic/phonological) and semantic knowledge in two repetition priming experiments, to investigate their role for knowledge-and context-based facilitation. Experiment 1 investigates repetition suppression effects (i.e., reduced activation for predictable stimuli) in magnetoencephalographic brain responses of human participants (N=38) and Experiment 2 uses response times to investigate behavioral priming effects (N=24). To disentangle prelexical and semantic knowledge, we realized a pseudoword familiarization procedure in both experiments and contrasted familiarized pseudowords with novel pseudowords (unfamiliar, no semantic knowledge) and words (semantics available). In Experiment 2, one further set of pseudowords was additionally associated with semantic information (i.e., objects). We found, in both experiments, a general context effect for all letter strings, which was specifically enhanced when semantic information was available. A knowledge effect for pseudowords was found (familiarized vs. novel pseudowords) but prelexical (i.e., orthographic/phonological) knowledge alone did not enhance context effects. We conclude that knowledge-and context-based facilitation in visual word recognition can be achieved without semantic information processing, i.e., exclusively on the basis of prelexical perceptual knowledge. Semantic knowledge, however, drastically enhances context-based facilitation. Significance StatementThe goal of reading is the extraction of meaning from script. This highly automatized process relies on facilitation based on word familiarity and text context. Here we use repetition priming to show that context-based facilitation is increased when semantic knowledge is present. This was demonstrated by enhanced context effects for letter strings with semantic associations. Still, earlier context effects (~80 ms) and orthographic knowledge effects were found irrespective of semantic processing. Our findings highlight the stronger role of semantic knowledge for achieving facilitated visual word recognition in contrast to semantic-free knowledge. Our findings suggest predictive coding as a potential mechanism that underlies efficient visual word recognition.