Evidence map›Paper›PMID 39694345›Full record

ArticleNeuroImage2025

An implemented predictive coding model of lexico-semantic processing explains the dynamics of univariate and multivariate activity within the left ventromedial temporal lobe during reading comprehension.

Lin Wang, Samer Nour Eddine, Trevor Brothers, Ole Jensen, Gina R Kuperberg

Abstract read
In one paragraph

Article in NeuroImage, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lin WangDepartment of Psychiatry and the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA; Department of Psychology, Tufts University, Medford, MA, 02155, USA.
Samer Nour EddineDepartment of Psychology, Tufts University, Medford, MA, 02155, USA.
Trevor BrothersDepartment of Psychology, Tufts University, Medford, MA, 02155, USA; North Carolina Agricultural and Technical State University, North Carolina, NC, 27411, USA.
Ole JensenDepartment of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom.
Gina R KuperbergDepartment of Psychiatry and the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA; Department of Psychology, Tufts University, Medford, MA, 02155, USA. Electronic address: GKUPERBERG@mgh.harvard.edu.

Funding

The neural basis of language comprehension: Insights from spatiotemporal imagingR01HD082527 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI GINA R KUPERBERG · 2015 to 2026
$5.8M
NICHD NIH HHS R01 HD082527
6 · The paper itself

Abstract

During language comprehension, the larger neural response to unexpected versus expected inputs is often taken as evidence for predictive coding-a specific computational architecture and optimization algorithm proposed to approximate probabilistic inference in the brain. However, other predictive processing frameworks can also account for this effect, leaving the unique claims of predictive coding untested. In this study, we used MEG to examine both univariate and multivariate neural activity in response to expected and unexpected inputs during word-by-word reading comprehension. We further simulated this activity using an implemented predictive coding model that infers the meaning of words from their orthographic form. Consistent with previous findings, the univariate analysis showed that, between 300 and 500 ms, unexpected words produced a larger evoked response than expected words within a left ventromedial temporal region that supports the mapping of orthographic word-forms onto lexical and conceptual representations. Our model explained this larger evoked response as the enhanced lexico-semantic prediction error produced when prior top-down predictions failed to suppress activity within lexical and semantic "error units". Critically, our simulations showed that despite producing minimal prediction error, expected inputs nonetheless reinstated top-down predictions within the model's lexical and semantic "state" units. Two types of multivariate analyses provided evidence for this functional distinction between state and error units within the ventromedial temporal region. First, within each trial, the same individual voxels that produced a larger response to unexpected inputs between 300 and 500 ms produced unique temporal patterns to expected inputs that resembled the patterns produced within a pre-activation time window. Second, across trials, and again within the same 300-500 ms time window and left ventromedial temporal region, pairs of expected words produced spatial patterns that were more similar to one another than the spatial patterns produced by pairs of expected and unexpected words, regardless of specific item. Together, these findings provide compelling evidence that the left ventromedial temporal lobe employs predictive coding to infer the meaning of incoming words from their orthographic form during reading comprehension.

Indexed as

ComprehensionModels, NeurologicalReadingSemanticsTemporal LobeAdultBrain MappingFemaleHumansMagnetoencephalographyMaleYoung AdultLanguage comprehensionMEGModelingN400Predictive codingRSA

Identifiers

PMID39694345
PMCPMC11894502

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.