Cited by 85Advanced Neuroimaging Techniques and ApplicationsNeural and Behavioral Psychology StudiesVisual perception and processing mechanisms

Metacognitive ability correlates with hippocampal and prefrontal microstructure

Open access
Allen, Micah, Glen, James C., Müllensiefen, Daniel, Schwarzkopf, Dietrich Samuel, Fardo, Francesca, Frank, Darya, Callaghan, Martina F., Rees, Geraint·2017·NeuroImage

Published version of a preprint

Abstract

Abstract The ability to introspectively evaluate our experiences to form accurate metacognitive beliefs, or insight, is an essential component of decision-making. Previous research suggests individuals vary substantially in their level of insight, and that this variation predicts brain volume and function, particularly in the anterior prefrontal cortex (aPFC). However, the neurobiological mechanisms underlying these effects are unclear, as qualitative, macroscopic measures such as brain volume can be related to a variety of microstructural features. Here we used a newly developed, high-resolution (800µm isotropic) multi-parameter mapping technique in 48 healthy individuals to delineate quantitative markers of in vivo histological features underlying metacognitive ability. Specifically, we examined how neuroimaging markers of local grey matter myelination, macromolecular and iron content relate to insight. Extending previous volumetric findings, we found that metacognitive ability, as determined by a signal-detection theoretic model, was positively related to the myelo-architectural integrity of aPFC grey matter. Interestingly, perceptual metacognition predicted decreased macromolecule content coupled with increased iron in the hippocampus and precuneus, areas previously implicated in meta-memory rather than meta-perception. Further, the relationship of hippocampal-precuneus and prefrontal microstructure to an auditory memory measure was respectively mediated or suppressed by metacognitive ability, suggesting a dynamic trade-off between participant’s memory and metacognition. These results point towards a novel understanding of the relationship between memory, brain microstructure, and metacognition. Significance Statement By combining a signal-theoretic model of individual metacognitive ability with state of the art quantitative neuroimaging, our results shed new light on the neurobiological mechanisms underlying introspective insight. Myelination and iron are core determinants of both healthy brain maturation and neurodegeneration; particularly in the hippocampus where iron accumulation is linked to oxidative stress and inflammation. Our results may thus indicate that metacognition depends upon the development and integrity of a memory-related brain network, potentially revealing novel biomarkers of neurodegeneration. These results highlight the power of quantitative mapping to reveal neurobiological correlates of behaviour.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.neuroimage.2017.02.008

Cites

88 of 88 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Individual differences in perceptual metacognitive sensitivity are linked to variation in the structure and function of human anterior prefrontal cortex.

    “Individual differences in perceptual metacognitive sensitivity have been similarly linked to variation in the structure and function of human anterior prefrontal cortex (Allen et al. 2017, Baird et al. 2013, Fleming et al. 2010, McCurdy et al. 2013).”

    From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Allen et al. 2017

  • Frontopolar cortex plays a role in metacognitive efficiency.

    “These findings are intriguing in light of other work emphasizing the role of frontopolar cortex in metacognitive efficiency (Allen et al. 2017, Baird et al. 2013, Fleming et al. 2010, McCurdy et al. 2013, Miyamoto et al. 2018).”

    From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Allen et al. 2017

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

3 of the 91 references couldn’t be matched to a known paper.

Research works printed but not linked: 3

  1. Fleming S.M. Weil R.S. Nagy Z. Dolan R.J. Rees G. Relating introspective accuracy to individual differences in brain structure Science 329 2010 1541 1543 20847276 PMC3173849
  2. Gelman N. Ewing J.R. Gorell J.M. Spickler E.M. Solomon E.G. Interregional variation of longitudinal relaxation rates in human brain at 3.0 T: relation to estimated iron and water contents Magn. Reson. Med. 45 2001 71 79 11146488
  3. Rooney W.D. Johnson G. Li X. Cohen E.R. Kim S.-G. Ugurbil K. Springer C.S. Magnetic field and tissue dependencies of human brain longitudinal 1H2O relaxation in vivo Magn. Reson. Med. 57 2007 308 318 17260370

Cited by

Sorted by citations

Authors
Allen, M., Glen, J. C., Müllensiefen, D., Schwarzkopf, D. S., Fardo, F., Frank, D., Callaghan, M. F., & Rees, G.
Affiliations
  • Wellcome Centre for Human Neuroimaging (GB)
  • University College London (GB)
  • Goldsmiths University of London (GB)
  • Aarhus University (DK)
  • University of Manchester (GB)
Corresponding author
Allen, Micah
Venue
NeuroImage
Publisher
Elsevier BV
Published
2017-04
Volume
149
Pages
415-423
ISSN
1053-8119 (ISSN-L)
OpenAlex
W2583951233
Cited by
85
References
91
Citations by year
2026: 5 · 2025: 7 · 2024: 6 · 2023: 13 · 2022: 13 · 2021: 10 · 2020: 7 · 2019: 8 · 2018: 10 · 2017: 5
FWCI
6.30
Type
journal article
Language
en
Open access
Locations
  • NeuroImage (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research Explorer (The University of Manchester) (publishedVersion, other-oa)
  • Goldsmiths (University of London) (acceptedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • ResearchSpace (University of Auckland) (submittedVersion)
Funders
  • Wellcome Trust (100227, 091593/Z/10/Z)
  • ERC Starting (310829)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
Keywords
metacognition, subjective confidence, anterior prefrontal cortex, hippocampus, myeloarchitecture, iron content, precuneus, visual cortex
MeSH terms
Metacognition, Adult, Brain Mapping, Female, Hippocampus, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Nerve Fibers, Myelinated, Prefrontal Cortex, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review