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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 Hits 1 – 20 of 47 1 Language Models Explain Word Reading Times Better Than Empirical Predictability ... Hofmann, Markus J.; Remus, Steffen; Biemann, Chris. - : arXiv, 2022 BASE Show details 2 Language Models Explain Word Reading Times Better Than Empirical Predictability Hofmann, Markus J.; Remus, Steffen; Biemann, Chris... In: Front Artif Intell (2022) BASE Show details 3 Meditation affects word recognition of meditation novices Lusnig, Larissa; Radach, Ralph; Hofmann, Markus J. In: Psychol Res (2021) Abstract: This work represents one of the first attempts to examine the effects of meditation on the processing of written single words. In the present longitudinal study, participants conducted a lexical decision task and rated the affective valence of nouns before and after a 7-week class in mindfulness meditation, loving-kindness meditation, or a control intervention. Both meditation groups rated the emotional valence of nouns more neutral after the interventions, suggesting a general down-regulation of emotions. In the loving-kindness group, positive words were rated more positively after the intervention, suggesting a specific intensification of positive feelings. After both meditation interventions, response times in the lexical decision task accelerated significantly, with the largest facilitation occurring in the loving-kindness group. We assume that meditation might have led to increased attention, better visual discrimination, a broadened attentional focus, and reduced mind-wandering, which in turn enabled accelerated word recognition. These results extend findings from a previous study with expert Zen meditators, in which we found that one session of advanced meditation can affect word recognition in a very similar way. Keyword: Original Article URL: http://www.ncbi.nlm.nih.gov/pubmed/33966104 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8942899/ https://doi.org/10.1007/s00426-021-01522-5 BASE Hide details 4 Zen meditation neutralizes emotional evaluation, but not implicit affective processing of words ... Lusnig, Larissa; Radach, Ralph; Mueller, Christina. - : figshare, 2020 BASE Show details 5 Zen meditation neutralizes emotional evaluation, but not implicit affective processing of words ... Lusnig, Larissa; Radach, Ralph; Mueller, Christina. - : figshare, 2020 BASE Show details 6 Individual corpora predict fast memory retrieval during reading ... The 28th International Conference on Computational Linguistics 2020; Biemann, Chris; Hofmann, Markus J.. - : Underline Science Inc., 2020 BASE Show details 7 Individual corpora predict fast memory retrieval during reading ... Hofmann, Markus J.; Müller, Lara; Rölke, Andre. - : arXiv, 2020 BASE Show details 8 A Lexical Frequency Analysis of Irish Sign Language Hofmann, Markus; Smith, Robert G In: Other Resources (2020) BASE Show details 9 A Lexical Frequency Analysis of Irish Sign Language Smith, Robert G.; Hofmann, Markus In: Articles (2020) BASE Show details 10 Zen meditation neutralizes emotional evaluation, but not implicit affective processing of words Lusnig, Larissa; Radach, Ralph; Mueller, Christina J.. - : Public Library of Science, 2020 BASE Show details 11 Decomposing predictability: Semantic feature overlap between words and the dynamics of reading for meaning ... Hofmann, Markus J.; Kleemann, Mareike A.; Roelke, Andre. - : arXiv, 2019 BASE Show details 12 Sampling Techniques to Overcome Class Imbalance in a Cyberbullying Context Hofmann, Markus; Colton, David. - : Universitat Politècnica de València, 2019 BASE Show details 13 A qualitative analysis of the Wikipedia N-Substate Algorithm's Enhancement Terms Goslin, Kyle; Hofmann, Markus. - : Universitat Politècnica de València, 2019 BASE Show details 14 Non-Manual Articulators in Irish Sign Language Verbs: An Analysis with Data Mining Association Rules Smith, Robert G; Hofmann, Markus In: Conference Papers (2018) BASE Show details 15 Typography and individual experience in digital reading: Do readers’ eye movements adapt to poor justification? Jarosch, Julian [Verfasser]; Schlesewsky, Matthias [Verfasser]; Füssel, Stephan [Verfasser]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2017 DNB Subject Category Language Show details 16 Taking typography to experimental testing: On the influence of serifs, fonts and justification on eye movements in text reading Jarosch, Julian [Verfasser]; Schlesewsky, Matthias [Verfasser]; Füssel, Stephan [Verfasser]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2017 DNB Subject Category Language Show details 17 The two sides of prediction error in reading: on the relationship between eye movements and the N400 in sentence processing Kretzschmar, Franziska [Verfasser]; Alday, Phillip M. [Verfasser]; Radach, Ralph [Herausgeber]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2017 DNB Subject Category Language Show details 18 When readers pay attention to the left: A concurrent eyetracking-fMRI investigation on the neuronal correlates of regressive eye movements during reading Weiß, Anna Fiona [Verfasser]; Kretzschmar, Franziska [Verfasser]; Nagels, Arne [Verfasser]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2017 DNB Subject Category Language Show details 19 Sentiment Analysis: Comparative Analysis Of Multilingual Sentiment And Opinion Classification Techniques ... Sannikumar Patel; Nolan, Brian; Hofmann, Markus. - : Zenodo, 2017 BASE Show details 20 Sentiment Analysis: Comparative Analysis Of Multilingual Sentiment And Opinion Classification Techniques ... Sannikumar Patel; Nolan, Brian; Hofmann, Markus. - : Zenodo, 2017 BASE Show details Page: 1 2 3

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