Evidence map›Paper›PMID 42643197›Full record

ReviewFrontiers in neurology2026

Insight and executive functions in acquired brain injury: empirical evidence and theoretical frameworks.

Natasha Sigala, Melis Cobandag, Leigh Leppard, Nick Medford

Abstract readReview
In one paragraph

Review in Frontiers in neurology, 2026. 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
–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

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

4 authors.

Natasha SigalaDepartment of Clinical Neuroscience, Brighton and Sussex Medical School, University of Brighton, University of Sussex, Brighton, United Kingdom.
Melis CobandagDepartment of Clinical Neuroscience, Brighton and Sussex Medical School, University of Brighton, University of Sussex, Brighton, United Kingdom.
Leigh LeppardDepartment of Neuropsychiatry, South London and Maudsley NHS Foundation Trust, London, United Kingdom.
Nick MedfordDepartment of Neuropsychiatry, South London and Maudsley NHS Foundation Trust, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Impaired self-awareness affects 30-50% of patients with moderate to severe acquired brain injury (ABI) and represents one of the most clinically consequential obstacles to effective rehabilitation. Despite substantial evidence that self-awareness and executive functions share neural substrates in prefrontal cortex, the mechanisms linking these two functions remain incompletely specified. This paper reviews the empirical evidence for the relationship between executive functions and insight in ABI, and evaluates four theoretical frameworks: the Cognitive Awareness Model, the Dynamic Comprehensive Model of Awareness, Mograbi et al.'s predictive coding framework, and Duncan's adaptive coding model. It then proposes a novel integration of the latter two as a mechanistically grounded account of why executive dysfunction and impaired self-awareness co-occur following prefrontal damage. We argue that adaptive coding describes the representational flexibility of prefrontal neurons in coding self-relevant information, whilst predictive coding provides the computational logic, driven by precision-weighted prediction errors, through which this adaptive selection is updated. We conclude by discussing assessment and rehabilitation implications in ABI.

Indexed as

AwarenessBrain InjuriesExecutive FunctionPrefrontal CortexCognitive FlexibilityHumansacquired brain injuryadaptive codinganosognosiaexecutive functionsinsightmetacognitionpredictive codingprefrontal cortex

Identifiers

PMID42643197
PMCPMC13503201

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.