Evidence map›Paper›PMID 41664566›Full record

SynthesisBrain and behavior2026

The Neural Blueprint of Novelty: A Meta-Analytic Dissection of Active and Passive Novelty Processing Networks.

Ern Wong, Gianluca Sesso, Irene Sánchez Rodríguez, Jordi Manuello, Pietro Pietrini

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in Brain and behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

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.

Ern WongIMT School for Advanced Studies Lucca, Molecular Mind Lab, Lucca, Italy.
Gianluca SessoIMT School for Advanced Studies Lucca, Molecular Mind Lab, Lucca, Italy.
Irene Sánchez RodríguezIMT School for Advanced Studies Lucca, Molecular Mind Lab, Lucca, Italy.
Jordi ManuelloGCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy.
Pietro PietriniIMT School for Advanced Studies Lucca, Molecular Mind Lab, Lucca, Italy.

Funding

Next Generation EU, Ecosistema dell'Innovazione "the-Tuscany Health Ecosystem" ecS00000017
6 · The paper itself

Abstract

backgroundDetecting novel environmental events is a fundamental survival mechanism, enabling organisms to identify and respond to salient changes. This function can operate in at least two broad modes, differing in task demands: active and passive novelty processing. Active processing involves explicitly recognizing novel or deviant stimuli and engaging goal-directed, top-down attentional control and memory-related systems. In contrast, passive processing is driven primarily by bottom-up attentional reorienting and does not necessarily require an explicit response or conscious evaluation. The present study asked whether these two modes recruit a shared neural architecture across task demands.

methodsWe conducted a coordinate-based meta-analysis using Activation Likelihood Estimation (ALE) across fMRI studies of active and passive novelty processing. Conjunction and subtraction analyses were performed on the resulting ALE maps to identify common and distinct neural substrates associated with each mode of novelty processing.

resultsThe conjunction analysis revealed a core novelty-responsive network encompassing the bilateral medial temporal lobes (MTLs), inferior frontal gyrus (IFG), and medial frontal regions. Subtraction analyses further identified task-dependent specializations: studies of active novelty processing showed greater spatial convergence in the left precentral gyrus, left IFG, right MTL, and medial frontal areas, whereas studies of passive processing showed greater convergence in the left superior temporal gyrus, bilateral MTL, and right IFG.

conclusionThese findings suggest that active and passive conditions share a common novelty-responsive network but differentially weight its components, reflecting distinct cognitive and attentional demands imposed by the explicit versus incidental processing of novel events.

Indexed as

AttentionBrainNerve NetBrain MappingHumansLikelihood FunctionsMagnetic Resonance ImagingActivation Likelihood Estimation (ALE)fMRImedial temporal lobemeta‐analysismeta‐analytic connectivity modeling (MACM)novelty detection

Identifiers

PMID41664566
PMCPMC12887445

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.