Evidence map›Paper›PMID 40800422›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2024

Context-dependent neural preparation for information relevance vs. probability.

José M G Peñalver, Carlos González-García, Ana F Palenciano, David López-García, María Ruz

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

José M G PeñalverMind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain.
Carlos González-GarcíaMind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain.
Ana F PalencianoMind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain.
David López-GarcíaData Science & Computational Intelligence Institute, Universidad de Granada, Granada, Spain.
María RuzMind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preparation is a top-down phenomenon known to improve performance across different situations. In light of recent electrophysiological findings that suggest that anticipatory neural preactivations linked to preparation are context-specific and do not generalize across domains, in the current study we used fMRI to investigate the brain regions involved in these differential patterns. We applied multivariate decoding to data obtained in a paradigm where, in different blocks, cues provided information about the relevance or probability of incoming target stimuli. Results showed that the anticipated stimulus category was preactivated in both conditions, mostly in different brain regions within the ventral visual cortex and with differential overlap with actual target perception. Crucially, there was scarce cross-classification across attention and expectation contexts except on a patch of the fusiform gyrus, indicating mostly differential neural coding of anticipated contents in relevance and probability scenarios. Finally, a model-based fMRI-EEG fusion showed that these regions differentially code for specific conditions during preparation, as well as specifically preparing for category anticipation in a ramping-up manner. Overall, our results stress the specificity of anticipatory neural processing depending on its informative role while highlighting a key hub of commonality in the fusiform gyrus.

Indexed as

attentionEEGexpectationfMRImodel-based fusionpreparation

Identifiers

PMID40800422
PMCPMC12290532

What OpenQuestion holds

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Registered trials

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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.