Cargando…
Integrating Statistical and Machine Learning Approaches for Neural Classification
Neurons can code for multiple variables simultaneously and neuroscientists are often interested in classifying neurons based on their receptive field properties. Statistical models provide powerful tools for determining the factors influencing neural spiking activity and classifying individual neuro...
Autores principales: | SARMASHGHI, MEHRAD, JADHAV, SHANTANU P., EDEN, URI T. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205093/ https://www.ncbi.nlm.nih.gov/pubmed/37223667 http://dx.doi.org/10.1109/access.2022.3221436 |
Ejemplares similares
-
Efficient spline regression for neural spiking data
por: Sarmashghi, Mehrad, et al.
Publicado: (2021) -
Statistics for data science: leverage the power of statistics for data analysis, classification, regression, machine learning, and neural networks
por: Miller, James D
Publicado: (2017) -
Machine learning and statistical approaches for classification of risk of coronary artery disease using plasma cytokines
por: Saharan, Seema Singh, et al.
Publicado: (2021) -
Statistical reinforcement learning: modern machine learning approaches
por: Sugiyama, Masashi
Publicado: (2015) -
Statistical and machine learning approaches for network analysis
por: Dehmer, Matthias, et al.
Publicado: (2012)