Evidence map›Paper›PMID 31920635›Full record

ReviewFrontiers in pharmacology2019

The Pharmacology of Visual Hallucinations in Synucleinopathies.

Mirella Russo, Claudia Carrarini, Fedele Dono, Marianna Gabriella Rispoli, Martina Di Pietro, Vincenzo Di Stefano, Laura Ferri, Laura Bonanni, Stefano Luca Sensi, Marco Onofrj

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% of its field
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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
  8. Review
  9. Sertraline-induced visual hallucination in an adolescent girl.Dusunen adam : Bakirkoy Ruh ve Sinir Hastaliklari Hastanesi yayin organi · 2024
    Article
  10. Review
  11. Review
  12. Review
  13. Review
  14. Improving Psychiatry Services with Artificial Intelligence: Opportunities and Challenges.Turk psikiyatri dergisi = Turkish journal of psychiatry · 2024
    Review
  15. Review
  16. Review
  17. Article
  18. Article
  19. Review
  20. Review
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

10 authors at 2 institutions in 2 countries.

Mirella RussoDepartment of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
Claudia CarrariniDepartment of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
Fedele DonoDepartment of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
Marianna Gabriella RispoliDepartment of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
Martina Di PietroDepartment of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
Vincenzo Di StefanoDepartment of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
Laura FerriDepartment of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
Laura BonanniDepartment of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
Stefano Luca SensiDepartment of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
Marco OnofrjDepartment of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy.
University of Chieti-Pescara · ITUniversity of California, Irvine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visual hallucinations (VH) are commonly found in the course of synucleinopathies like Parkinson's disease and dementia with Lewy bodies. The incidence of VH in these conditions is so high that the absence of VH in the course of the disease should raise questions about the diagnosis. VH may take the form of early and simple phenomena or appear with late and complex presentations that include hallucinatory production and delusions. VH are an unmet treatment need. The review analyzes the past and recent hypotheses that are related to the underlying mechanisms of VH and then discusses their pharmacological modulation. Recent models for VH have been centered on the role played by the decoupling of the default mode network (DMN) when is released from the control of the fronto-parietal and salience networks. According to the proposed model, the process results in the perception of priors that are stored in the unconscious memory and the uncontrolled emergence of intrinsic narrative produced by the DMN. This DMN activity is triggered by the altered functioning of the thalamus and involves the dysregulated activity of the brain neurotransmitters. Historically, dopamine has been indicated as a major driver for the production of VH in synucleinopathies. In that context, nigrostriatal dysfunctions have been associated with the VH onset. The efficacy of antipsychotic compounds in VH treatment has further supported the notion of major involvement of dopamine in the production of the hallucinatory phenomena. However, more recent studies and growing evidence are also pointing toward an important role played by serotonergic and cholinergic dysfunctions. In that respect,

Indexed as

default mode networkdementia with Lewy bodiesParkinson's diseasesynucleinopathyvisual hallucination

Identifiers

PMID31920635
PMCPMC6913661
OpenAlexW2996042692

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.