ArticleAPL bioengineering2025
Cerebellar contribution to multisensory integration: A computational modeling exploration.
Article in APL bioengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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.
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Who cites it
3 citing papers in PubMed.
- Brain morphometric alterations associated with degenerative scoliosis: a structural MRI study.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Modeling framework disentangles cerebellar mechanisms in speech feedback control, revealing trade-offs reshaped by degeneration.bioRxiv : the preprint server for biology · 2026Article
- Optic Flow Simulating Self-Motion Does Not Modulate the Hoffmann Reflex in the Soleus During Upright Standing in Healthy Young Adults.Brain sciences · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The remarkable ability of the human brain to create a coherent perception of reality relies heavily on multisensory integration-the complex process of combining inputs from different senses. While this mechanism is fundamental to our understanding of the world, its underlying neural architecture remains partially unknown. This study investigates the role of the cerebellum in multisensory integration through a novel computational approach inspired by clinical observations of a patient with cerebellar agenesis. With reference to the clinical data comparing an acerebellar patient with age-matched control subjects, we exploited biologically realistic spiking neural networks to model both conditions. Our computational framework enables testing multiple network configurations and parameters, effectively replicating and extending the clinical experiments
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Registered trials
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.