Evidence map›Paper›PMID 36601626›Full record

ArticleBrain communications2023

Changes in both top-down and bottom-up effective connectivity drive visual hallucinations in Parkinson's disease.

George E C Thomas, Peter Zeidman, Tajwar Sultana, Angeliki Zarkali, Adeel Razi, Rimona S Weil

Abstract read
In one paragraph

Article in Brain communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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  7. Article
  8. Redefining Non-Motor Symptoms in Parkinson's Disease.Journal of personalized medicine · 2025
    Review
  9. Review
  10. Review
  11. Neuropsychiatric disorders in Parkinson's disease.Therapeutic advances in neurological disorders · 2025
    Review
  12. Article
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  15. Article
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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

6 authors.

George E C ThomasDementia Research Centre, UCL Institute of Neurology, WC1N 3AR London, UK.ORCID https://orcid.org/0000-0001-6107-0326
Peter ZeidmanWellcome Centre for Human Neuroimaging, UCL Institute of Neurology, WC1N 3AR London, UK.
Tajwar SultanaDepartment of Computer and Information Systems Engineering, NED University of Engineering & Technology, Karachi 75270, Pakistan.
Angeliki ZarkaliDementia Research Centre, UCL Institute of Neurology, WC1N 3AR London, UK.ORCID https://orcid.org/0000-0003-2808-072X
Adeel RaziWellcome Centre for Human Neuroimaging, UCL Institute of Neurology, WC1N 3AR London, UK.
Rimona S WeilDementia Research Centre, UCL Institute of Neurology, WC1N 3AR London, UK.ORCID https://orcid.org/0000-0002-5092-6325

Funding

Wellcome Trust 205167/Z/16/Z
6 · The paper itself

Abstract

Visual hallucinations are common in Parkinson's disease and are associated with a poorer quality of life and a higher risk of dementia. An important and influential model that is widely accepted as an explanation for the mechanism of visual hallucinations in Parkinson's disease and other Lewy body diseases is that these arise due to aberrant hierarchical processing, with impaired bottom-up integration of sensory information and overweighting of top-down perceptual priors within the visual system. This hypothesis has been driven by behavioural data and supported indirectly by observations derived from regional activation and correlational measures using neuroimaging. However, until now, there was no evidence from neuroimaging for differences in causal influences between brain regions measured in patients with Parkinson's hallucinations. This is in part because previous resting-state studies focused on functional connectivity, which is inherently undirected in nature and cannot test hypotheses about the directionality of connectivity. Spectral dynamic causal modelling is a Bayesian framework that allows the inference of effective connectivity-defined as the directed (causal) influence that one region exerts on another region-from resting-state functional MRI data. In the current study, we utilize spectral dynamic causal modelling to estimate effective connectivity within the resting-state visual network in our cohort of 15 Parkinson's disease visual hallucinators and 75 Parkinson's disease non-visual hallucinators. We find that visual hallucinators display decreased bottom-up effective connectivity from the lateral geniculate nucleus to primary visual cortex and increased top-down effective connectivity from the left prefrontal cortex to primary visual cortex and the medial thalamus, as compared with non-visual hallucinators. Importantly, we find that the pattern of effective connectivity is predictive of the presence of visual hallucinations and associated with their severity within the hallucinating group. This is the first study to provide evidence, using resting-state effective connectivity, to support a model of aberrant hierarchical predictive processing as the mechanism for visual hallucinations in Parkinson's disease.

Indexed as

effective connectivityParkinson’s diseaseresting-state functional MRIspectral dynamic causal modellingvisual hallucinations

Identifiers

PMID36601626
PMCPMC9798302

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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.