ArticleCognitive neurodynamics2016
Combined nonlinear metrics to evaluate spontaneous EEG recordings from chronic spinal cord injury in a rat model: a pilot study.
Article in Cognitive neurodynamics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 8 citations in OpenAlex.
- In-ear EEG wearables for brain activity assessment and cognitive rehabilitation: the emerging role of multimodal embedded intelligence.Frontiers in human neuroscience · 2026Review
- Animal Models of Spinal Cord Injury.Biomedicines · 2025Review
- Prospects of Electrocorticography in Neuropharmacological Studies in Small Laboratory Animals.Brain sciences · 2024Review
- Music of brain and music on brain: a novel EEG sonification approach.Cognitive neurodynamics · 2019Article
- Analysis of heart rate signals during meditation using visibility graph complexity.Cognitive neurodynamics · 2019Article
- Analysis of long range dependence in the EEG signals of Alzheimer patients.Cognitive neurodynamics · 2018Article
- NDDN: A Cloud-Based Neuroinformation Database for Developing Neuronal Networks.Journal of healthcare engineering · 2018Article
- Long-range temporal correlations of broadband EEG oscillations for depressed subjects following different hemispheric cerebral infarction.Cognitive neurodynamics · 2017Article
- Combined nonlinear metrics to evaluate spontaneous EEG recordings from chronic spinal cord injury in a rat model: a pilot study.Cognitive neurodynamics · 2016Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spinal cord injury (SCI) is a high-cost disability and may cause permanent loss of movement and sensation below the injury location. The chance of cure in human after SCI is extremely limited. Instead, neural regeneration could have been seen in animals after SCI, and such regeneration could be retarded by blocking neural plasticity pathways, showing the importance of neural plasticity in functional recovery. As an indicator of nonlinear dynamics in the brain, sample entropy was used here in combination with detrended fluctuation analysis (DFA) and Kolmogorov complexity to quantify functional plasticity changes in spontaneous EEG recordings of rats before and after SCI. The results showed that the sample entropy values were decreased at the first day following injury then gradually increased during recovery. DFA and Kolmogorov complexity results were in consistent with sample entropy, showing the complexity of the EEG time series was lost after injury and partially regained in 1 week. The tendency to regain complexity is in line with the observation of behavioral rehabilitation. A critical time point was found during the recovery process after SCI. Our preliminary results suggested that the combined use of these nonlinear dynamical metrics could provide a quantitative and predictive way to assess the change of neural plasticity in a spinal cord injury rat model.
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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.