Evidence map›Paper›PMID 38755514›Full record

ReviewCurrent topics in behavioral neurosciences2025

Predictive Processing and the Pathophysiology of Functional Neurological Disorder.

Johannes Jungilligens, David L Perez

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current topics in behavioral neurosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Neurofeedback for functional neurological disorders: future directions for research and clinical practice.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026
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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

2 authors.

Johannes JungilligensBehavioral Neurology Research Group, Department of Neurology, University Hospital Knappschaftskrankenhaus Bochum, Ruhr University Bochum, Bochum, Germany.
David L PerezDivision of Behavioral Neurology and Integrated Brain Medicine, Department of Neurology, Functional Neurological Disorder Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The contemporary neuroscience understanding of the brain as an active inference organ supports that our conscious experiences, including sensorimotor perceptions, depend on the integration of probabilistic predictions with incoming sensory input across hierarchically organized levels. As in other systems, these complex processes are prone to error under certain circumstances, which may lead to alterations in their outcomes (i.e., variations in sensations and movements). Such variations are an important aspect of functional neurological disorder, a complex disorder at the interface of brain-mind-body interactions. Thus, predictive processing frameworks offer fundamental mechanistic insights into the pathophysiology of functional neurological disorder. In recent years, many of the aspects relevant to the neurobiology of functional neurological disorder - e.g., aberrant motor and sensory processes, symptom expectation, self-agency, and illness beliefs, as well as interoception, allostasis, and emotion - have been investigated through the lens of predictive processing frameworks. Here, we provide an overview of the current state of research on predictive processing and the pathophysiology of functional neurological disorder.

Indexed as

BrainNervous System DiseasesHumansActive inferenceFunctional neurological disorderNeurobiologyNeuroimagingPathophysiologyPredictive processing

Identifiers

What OpenQuestion holds

Textmetadata
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.