The DOI matches its Crossref record; 331 of the 331 references it cites were found in a registry or an index.
Predicting while comprehending language: A theory and review.
Open accessAbstract
Researchers agree that comprehenders regularly predict upcoming language, but they do not always agree on what prediction is (and how to differentiate it from integration) or what constitutes evidence for it. After defining prediction, we show that it occurs at all linguistic levels from semantics to form, and then propose a theory of which mechanisms comprehenders use to predict. We argue that they most effectively predict using their production system (i.e., prediction-by-production): They covertly imitate the linguistic form of the speaker's utterance and construct a representation of the underlying communicative intention. Comprehenders can then run this intention through their own production system to prepare the predicted utterance. But doing so takes time and resources, and comprehenders vary in the extent of preparation, with many groups of comprehenders (non-native speakers, illiterates, children, and older adults) using it less than typical native young adults. We thus argue that prediction-by-production is an optional mechanism, which is augmented by mechanisms based on association. Support for our proposal comes from many areas of research (electrophysiological, eye-tracking, and behavioral studies of reading, spoken language processing in the context of visual environments, speech processing, and dialogue). (PsycINFO Database Record
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Gow, D. W., & Olson, B. B. (2015) · Journal of Memory and Language · doi:10.1016/j.jml.2015.03.004 · Cited by 24
Phonological typicality does not influence fixation durations in normal reading.
Staub, A., Grant, M. A., Clifton, C., & Rayner, K. (2009) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/a0015123 · Cited by 24
Structural prediction in aphasia: Evidence from either
Warren, T. C., Dickey, M. W., & Lei, C.-M. (2016) · Journal of Neurolinguistics · doi:10.1016/j.jneuroling.2016.01.001 · Cited by 23
Semantic retrieval of spoken words with an obliterated initial phoneme in a sentence context
Sivonen, P., Maeß, B., & Friederici, A. D. (2006) · Neuroscience Letters · doi:10.1016/j.neulet.2006.09.001 · Cited by 21
Neural Mechanisms of Rapid Sensitivity to Syntactic Anomaly
Kim, A. E., & Gilley, P. M. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00045 · Cited by 21
Multi-voxel pattern analysis of noun and verb differences in ventral temporal cortex
Boylan, C., Trueswell, J. C., & Thompson‐Schill, S. L. (2014) · Brain and Language · doi:10.1016/j.bandl.2014.07.009 · Cited by 14
The amount and structure of prior event experience affects anticipatory sentence interpretation
Borovsky, A. (2016) · Language Cognition and Neuroscience · doi:10.1080/23273798.2016.1238494 · Cited by 13
Form-to-expectation matching effects on first-pass eye movement measures during reading.
Farmer, T. A., Yan, S., Bicknell, K., & Tanenhaus, M. K. (2015) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/xhp0000054 · Cited by 12
Prediction and Production of Simple Mathematical Equations: Evidence from Visual World Eye-Tracking
Hintz, F., & Meyer, A. S. (2015) · PLoS ONE · doi:10.1371/journal.pone.0130766 · Cited by 10
McQueen, J. M., Eisner, F., & Norris, D. G. (2016) · Language Cognition and Neuroscience · doi:10.1080/23273798.2016.1154975 · Cited by 6
Predicting the unbeaten path through syntactic priming.
Arai, M., Nakamura, C., & Mazuka, R. (2014) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/a0038389 · Cited by 5
Beyond Associations: Sensitivity to structure in pre-schoolers' linguistic predictionsPreprint
Gambi, C. (2016) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/p2uux · Cited by 5
Self-citationBerkum, J. J. A. V. (2013) · Theoretical Linguistics · doi:10.1515/tl-2013-0004 · Cited by 5
Cited by
fMRI reveals language-specific predictive coding during naturalistic sentence comprehension
Shain, C., Blank, I. A., van Schijndel, M., Schuler, W., & Fedorenko, E. (2020) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2019.107307 · Cited by 215
Information flow across the cortical timescale hierarchy during narrative construction
Chang, C. H. C., Nastase, S. A., & Hasson, U. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2209307119 · Cited by 92
Does ChatGPT have semantic understanding? A problem with the statistics-of-occurrence strategy
Titus, L. M. (2024) · Cognitive Systems Research · doi:10.1016/j.cogsys.2023.101174 · Cited by 82
Developmental language disorder as syntactic prediction impairment
Hestvik, A., Epstein, B., Schwartz, R. G., & Shafer, V. L. (2022) · Frontiers in Communication · doi:10.3389/fcomm.2021.637585 · Cited by 11
“Prediction is increasingly recognized as a critical aspect of human cognition (Friston, 2005; Friston and Kiebel, 2009; Parr and Friston, 2018), and over the past decade, prediction has come to the forefront of psycholinguistic modeling and research (Levy, 2008; Rabagliati et al., 2016; Kuperberg and Jaeger, 2016; Gam…”
Background
Metadata
- Authors
- Pickering, M. J., & Gambi, C.
- Venue
- Psychological Bulletin
- Published
- 2018-10
- Volume
- 144
- Issue
- 10
- Pages
- 1002-1044
- ISSN
- 0033-2909 (ISSN-L)
- 1939-1455
- OpenAlex
- W2800516701
- Cited by
- 518
- References
- 331
- FWCI
- 15.35
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
