ArticleFrontiers in systems neuroscience2022
Dimensionality reduction and recurrence analysis reveal hidden structures of striatal pathological states.
Article in Frontiers in systems neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Recurrence quantification analysis of gait for computer-aided diagnosis of Parkinson's disease.Frontiers in aging neuroscience · 2026Article
- Integrative functional optical imaging approaches: Optics, microfluidics, and machine learning for neuroscience in organoids and small-animal models.Biophysical journal · 2025Review
- Intra-striatal dopaminergic inter-subject covariance in social drinkers and non-treatment-seeking alcohol use disorder participants.Addiction biology · 2024Article
- Pathological cell assembly dynamics in a striatal MSN network model.Frontiers in computational neuroscience · 2024Article
- MorphoGlia, an interactive method to identify and map microglia morphologies, demonstrates differences in hippocampal subregions of an Alzheimer's disease mouse model.Frontiers in cellular neuroscience · 2024Article
- Distributed dopaminergic signaling in the basal ganglia and its relationship to motor disability in Parkinson's disease.Current opinion in neurobiology · 2023Review
- Rethinking the network determinants of motor disability in Parkinson's disease.Frontiers in synaptic neuroscience · 2023Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A pipeline is proposed here to describe different features to study brain microcircuits on a histological scale using multi-scale analyses, including the uniform manifold approximation and projection (UMAP) dimensional reduction technique and modularity algorithm to identify neuronal ensembles, Runs tests to show significant ensembles activation, graph theory to show trajectories between ensembles, and recurrence analyses to describe how regular or chaotic ensembles dynamics are. The data set includes
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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.