Realistically Coupled Neural Mass Models Can Generate EEG Rhythms

Article Properties
  • Language
    English
  • DOI (url)
    10.1162/neco.2007.19.2.478
  • Publication Date
    2007/02/01
  • Journal
    Neural Computation
  • Indian UGC (journal)
  • Refrences
    43
  • Citations
    102
  • Roberto C. Sotero
  • Nelson J. Trujillo-Barreto
  • Yasser Iturria-Medina Cuban Neuroscience Center, Brain Dynamics Department, Havana, Cuba,
  • Felix Carbonell
  • Juan C. Jimenez Instituto de Cibernética Matemática y Física, Departamento de Sistemas Adaptativos, Havana, Cuba,
Abstract
Cite
Sotero, Roberto C., et al. “Realistically Coupled Neural Mass Models Can Generate EEG Rhythms”. Neural Computation, vol. 19, no. 2, 2007, pp. 478-12, https://doi.org/10.1162/neco.2007.19.2.478.
Sotero, R. C., Trujillo-Barreto, N. J., Iturria-Medina, Y., Carbonell, F., & Jimenez, J. C. (2007). Realistically Coupled Neural Mass Models Can Generate EEG Rhythms. Neural Computation, 19(2), 478-512. https://doi.org/10.1162/neco.2007.19.2.478
Sotero, Roberto C., Nelson J. Trujillo-Barreto, Yasser Iturria-Medina, Felix Carbonell, and Juan C. Jimenez. “Realistically Coupled Neural Mass Models Can Generate EEG Rhythms”. Neural Computation 19, no. 2 (2007): 478-512. https://doi.org/10.1162/neco.2007.19.2.478.
Sotero RC, Trujillo-Barreto NJ, Iturria-Medina Y, Carbonell F, Jimenez JC. Realistically Coupled Neural Mass Models Can Generate EEG Rhythms. Neural Computation. 2007;19(2):478-512.
Journal Categories
Medicine
Internal medicine
Neurosciences
Biological psychiatry
Neuropsychiatry
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Technology
Electrical engineering
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Mechanical engineering and machinery
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Citations Analysis
Category Category Repetition
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry64
Medicine: Medicine (General): Medical physics. Medical radiology. Nuclear medicine30
Science: Biology (General)19
Medicine: Medicine (General): Computer applications to medicine. Medical informatics19
Science: Mathematics: Instruments and machines: Electronic computers. Computer science10
Science: Chemistry: Organic chemistry: Biochemistry10
Science: Science (General)9
Technology: Mechanical engineering and machinery8
Medicine8
Medicine: Medicine (General)8
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics7
Science7
Medicine: Medicine (General): Medical technology7
Science: Physics6
Science: Mathematics6
Technology: Technology (General): Industrial engineering. Management engineering: Applied mathematics. Quantitative methods5
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system4
Technology: Engineering (General). Civil engineering (General): Mechanics of engineering. Applied mechanics3
Medicine: Internal medicine: Special situations and conditions: Geriatrics2
Science: Physics: Electricity and magnetism: Electricity: Plasma physics. Ionized gases2
Science: Biology (General): Genetics2
Technology: Engineering (General). Civil engineering (General)1
Science: Human anatomy1
Philosophy. Psychology. Religion: Psychology1
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system: Psychiatry1
Science: Biology (General): Cytology1
Technology: Chemical technology: Biotechnology1
Science: Physiology: Neurophysiology and neuropsychology1
Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software1
The category Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry 64 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled MODELING ANALYSIS OF THE RELATIONSHIP BETWEEN EEG RHYTHMS AND CONNECTIVITY AMONG DIFFERENT NEURAL POPULATIONS and was published in 2007. The most recent citation comes from a 2024 study titled Solving large-scale MEG/EEG source localisation and functional connectivity problems simultaneously using state-space models. This article reached its peak citation in 2013, with 10 citations. It has been cited in 48 different journals, 35% of which are open access. Among related journals, the NeuroImage cited this research the most, with 26 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year