CoChat
Sign Up
Cited by 49Functional Brain Connectivity StudiesSchizophrenia research and treatmentNeural dynamics and brain function

The application of nonlinear dynamic causal modelling for fMRI in subjects at high genetic risk of schizophrenia

Dauvermann, Maria R., Whalley, Heather C., Romaniuk, Liana, Valton, Vincent, Owens, David G.C., Johnstone, Eve C., Lawrie, Stephen M., Moorhead, Thomas W.J.·2013·NeuroImage
DOI 10.1016/j.neuroimage.2013.01.063
Open this paper in CoChat — free account

Abstract

Nonlinear Dynamic Causal Modelling (DCM) for fMRI provides computational modelling of gating mechanisms at the neuronal population level. It allows for estimations of connection strengths with nonlinear modulation within task-dependent networks. This paper presents an application of nonlinear DCM in subjects at high familial risk of schizophrenia performing the Hayling Sentence Completion Task (HSCT). We analysed scans of 19 healthy controls and 46 subjects at high familial risk of schizophrenia, which included 26 high risk subjects without psychotic symptoms and 20 subjects with psychotic symptoms. The activity-dependent network consists of the intra parietal cortex (IPS), inferior frontal gyrus (IFG), middle temporal gyrus (MTG), anterior cingulate cortex (ACC) and the mediodorsal (MD) thalamus. The connections between the MD thalamus and the IFG were gated by the MD thalamus. We used DCM to investigate altered connection strength of these connections. Bayesian Model Selection (BMS) at the group and family level was used to compare the optimal bilinear and nonlinear models. Bayesian Model Averaging (BMA) was used to assess the connection strengths with the gating from the MD thalamus and the IFG. The nonlinear models provided the better explanation of the data. Furthermore, the BMA analysis showed significantly lower connection strength of the thalamocortical connection with nonlinear modulation from the MD thalamus in high risk subjects with psychotic symptoms and those who subsequently developed schizophrenia. These findings demonstrate that nonlinear DCM provides a method to investigate altered connectivity at the level of neural circuits. The reduced connection strength with thalamic gating may be a neurobiomarker implicated in the development of psychotic symptoms. This study suggests that nonlinear DCM could lead to new insights into functional and effective dysconnection at the network level in subjects at high familial risk.

Integrity signals

Registry

Crossref · 10.1016/j.neuroimage.2013.01.063

Cites

106 of 106 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

  • DCM studies in schizophrenia demonstrated differences in functional network architecture and effective connectivity compared to healthy controls across various tasks.

    “These studies demonstrated differences in functional network architecture and effective connectivity compared to healthy controls across various tasks.”

    From Can Bayesian Theories of Autism Spectrum Disorder Help Improve Clinical Practice? (2016) · cites this paper as [131]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Dauvermann, M. R., Whalley, H. C., Romaniuk, L., Valton, V., Owens, D. G. C., Johnstone, E. C., Lawrie, S. M., & Moorhead, T. W. J.
Affiliations
  • Royal Edinburgh Hospital (GB)
  • University of Edinburgh (GB)
Corresponding author
Dauvermann, Maria R.
ORCID
Venue
NeuroImage
Publisher
Elsevier BV
Published
2013-06
Volume
73
Pages
16-29
ISSN
1053-8119 (ISSN-L)
DOI
10.1016/j.neuroimage.2013.01.063
OpenAlex
W2043735337
Cited by
49
References
106
Citations by year
2025: 1 · 2024: 1 · 2023: 4 · 2022: 1 · 2021: 4 · 2020: 1 · 2019: 2 · 2018: 2 · 2017: 7 · 2016: 7 · 2015: 5 · 2014: 7 · 2013: 7
FWCI
4.73
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • NeuroImage (publishedVersion)
  • PubMed (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • Research Portal (King's College London) (submittedVersion)
  • University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
Funders
  • Dr Mortimer and Theresa Sackler Foundation
  • Dorothy Hodgkin Fellowship from the Royal Society (DH080018)
  • EPSRC
  • BBSRC
  • MRC
  • TMRC
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Keywords
schizophrenia, familial risk, high genetic risk, mediodorsal thalamus, inferior frontal gyrus, thalamocortical connections, nonlinear modulation, Bayesian model averaging, Bayesian model selection, psychotic symptoms, neurobiomarkers, effective connectivity
MeSH terms
Adolescent, Algorithms, Bayes Theorem, Brain, Delusions, Female, Hallucinations, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Models, Neurological, Neural Pathways, Neuronal Plasticity, Psychomotor Performance, Risk, Schizophrenia, Schizophrenic Psychology, Thalamus, Linear Models, Nonlinear Dynamics, Genetic Predisposition to Disease, 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