Semantic control regions actively generate rule-based semantic predictions

Automatic predictions based on past statistical regularities, as is seen during semantic priming, facilitate the processing of future events. However, prediction may be further enhanced through active predictions flexibly generated from statistical regularities specific to the current context. In this fMRI study, we employed a novel design to isolate the neural bases of these active predictions. Participants (N=20) read sentences describing a protagonist interacting with an item. Critically, the trial structure followed a rule that enabled strategic prediction for half of the trials. Active prediction recruited a left-lateralized network composed of lateral-prefrontal, temporal, and parietal areas - which we termed the active prediction network (APN). This network partially overlaps with the semantic control system, suggesting that flexible prediction of upcoming events relies, in part, on systems used for the flexible retrieval of semantic information. As a consequence, predictable sentences produced lower activity within semantic representational areas (precuneus and left angular gyrus), consistent with facilitated processing of semantic content. Collectively, these results show a flexible interaction between the APN and semantic representational areas, where the APN supports the processing of incoming semantic content when the current context necessitates unstereotypical predictions.

Authors

Institutions

Publication Details

Journal
NeuroImage
Published
2025-07-16
DOI
https://doi.org/10.1016/j.neuroimage.2025.121379
Citations
1
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
2.48

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Semantic control regions actively generate rule-based semantic predictions

Scott L. Fairhall, Andrea Belluzzi
1 citations
NeuroImage
Topic Modeling
2.48
article

Semantic control regions actively generate rule-based semantic predictions

Scott L. Fairhall, Andrea Belluzzi
article en
1 citations

Abstract

Automatic predictions based on past statistical regularities, as is seen during semantic priming, facilitate the processing of future events. However, prediction may be further enhanced through active predictions flexibly generated from statistical regularities specific to the current context. In this fMRI study, we employed a novel design to isolate the neural bases of these active predictions. Participants (N=20) read sentences describing a protagonist interacting with an item. Critically, the trial structure followed a rule that enabled strategic prediction for half of the trials. Active prediction recruited a left-lateralized network composed of lateral-prefrontal, temporal, and parietal areas - which we termed the active prediction network (APN). This network partially overlaps with the semantic control system, suggesting that flexible prediction of upcoming events relies, in part, on systems used for the flexible retrieval of semantic information. As a consequence, predictable sentences produced lower activity within semantic representational areas (precuneus and left angular gyrus), consistent with facilitated processing of semantic content. Collectively, these results show a flexible interaction between the APN and semantic representational areas, where the APN supports the processing of incoming semantic content when the current context necessitates unstereotypical predictions.

NeuroImageVol. 317
University of Trento (IT)
Università degli Studi di Trento, Fondazione Cassa Di Risparmio Di Trento E Rovereto, Provincia Autonoma di Trento
Reduced inequalities
Openalex Percentile: Top 9%
Topic Modeling
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Semantic control regions actively generate rule-based semantic predictions — Scott L. Fairhall, Andrea Belluzzi · NeuroImage (2025) | TGRS Research Map | TGRS