Cargando…

Sparse Ordinal Logistic Regression and Its Application to Brain Decoding

Brain decoding with multivariate classification and regression has provided a powerful framework for characterizing information encoded in population neural activity. Classification and regression models are respectively used to predict discrete and continuous variables of interest. However, cogniti...

Descripción completa

Detalles Bibliográficos
Autores principales:	Satake, Emi, Majima, Kei, Aoki, Shuntaro C., Kamitani, Yukiyasu
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2018
Materias:	Neuroscience
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6104194/ https://www.ncbi.nlm.nih.gov/pubmed/30158864 http://dx.doi.org/10.3389/fninf.2018.00051

Ejemplares similares

Brain hierarchy score: Which deep neural networks are hierarchically brain-like?
por: Nonaka, Soma, et al.
Publicado: (2021)

Reconstructing visual illusory experiences from human brain activity
por: Cheng, Fan L., et al.
Publicado: (2023)

BrainLiner: A Neuroinformatics Platform for Sharing Time-Aligned Brain-Behavior Data
por: Takemiya, Makoto, et al.
Publicado: (2016)

Characterization of deep neural network features by decodability from human brain activity
por: Horikawa, Tomoyasu, et al.
Publicado: (2019)

Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features
por: Horikawa, Tomoyasu, et al.
Publicado: (2017)

End-to-End Deep Image Reconstruction From Human Brain Activity
por: Shen, Guohua, et al.
Publicado: (2019)

Multivariate decoding of brain images using ordinal regression()
por: Doyle, O.M., et al.
Publicado: (2013)

Ordinal Logistic Regression in Medical Research
por: Bender, Ralf, et al.
Publicado: (1997)

Genomic-Enabled Prediction of Ordinal Data with Bayesian Logistic Ordinal Regression
por: Montesinos-López, Osval A., et al.
Publicado: (2015)

Regression modeling strategies: with applications to linear models, logistic and ordinal regression, and survival analysis
por: Harrell , Jr , Frank E
Publicado: (2015)

Sparse Logistic Regression With L(1/2) Penalty for Emotion Recognition in Electroencephalography Classification
por: Chen, Dong-Wei, et al.
Publicado: (2020)

Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model
por: Islam, Md. Akhtarul, et al.
Publicado: (2022)

How Are BMI, Nutrition, and Physical Exercise Related? An Application of Ordinal Logistic Regression
por: Wang, Hongwei, et al.
Publicado: (2022)

Deep image reconstruction from human brain activity
por: Shen, Guohua, et al.
Publicado: (2019)

Leukemia Prediction Using Sparse Logistic Regression
por: Manninen, Tapio, et al.
Publicado: (2013)

Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh
por: Das, Sumonkanti, et al.
Publicado: (2011)

Training in Use of Brain–Machine Interface-Controlled Robotic Hand Improves Accuracy Decoding Two Types of Hand Movements
por: Fukuma, Ryohei, et al.
Publicado: (2018)

Sufficient Sample Size and Power in Multilevel Ordinal Logistic Regression Models
por: Ali, Sabz, et al.
Publicado: (2016)

Validation of in silico biomarkers for drug screening through ordinal logistic regression
por: Jeong, Da Un, et al.
Publicado: (2022)

Application of ordinal logistic regression analysis to identify the determinants of illness severity of COVID-19 in China
por: Xu, Kandi, et al.
Publicado: (2020)

Identification and evaluation of novel methods for the analysis of ordinal data in acute stroke trials in comparison to ordinal logistic regression
por: Nunn, Aimie, et al.
Publicado: (2015)

Multinomial and ordinal Logistic regression analyses with multi-categorical variables using R
por: Liang, Jiaqi, et al.
Publicado: (2020)

Predicting happiness levels of European immigrants and natives: An application of Artificial Neural Network and Ordinal Logistic Regression
por: Chen, Shaoming, et al.
Publicado: (2022)

Generic decoding of seen and imagined objects using hierarchical visual features
por: Horikawa, Tomoyasu, et al.
Publicado: (2017)

Determinants of nutritional status among primary school students in Dilla Town; Application of an ordinal logistic regression model
por: Berhanu, Getasew, et al.
Publicado: (2023)

Position Information Encoded by Population Activity in Hierarchical Visual Areas
por: Majima, Kei, et al.
Publicado: (2017)

Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time
por: Baker, Rose D, et al.
Publicado: (2009)

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes
por: Li, Baoyue, et al.
Publicado: (2011)

Mapping of the DLQI scores to EQ-5D utility values using ordinal logistic regression
por: Ali, Faraz Mahmood, et al.
Publicado: (2017)

Effect of Behavioral Factors on Severity of Female Pattern Hair Loss: An Ordinal Logistic Regression Analysis
por: Yi, Yanhua, et al.
Publicado: (2020)

Analysis of sparse data in logistic regression in medical research: A newer approach
por: Devika, S, et al.
Publicado: (2016)

Estimating Phred scores of Illumina base calls by logistic regression and sparse modeling
por: Zhang, Sheng, et al.
Publicado: (2017)

Bias in Odds Ratios From Logistic Regression Methods With Sparse Data Sets
por: Gosho, Masahiko, et al.
Publicado: (2023)

Factors associated with anaemia among women of reproductive age in Ethiopia: Multilevel ordinal logistic regression analysis
por: Tirore, Lire Lemma, et al.
Publicado: (2020)

Differential item functioning analysis on the Geriatric Depression Scale-15: An iterative hybrid ordinal logistic regression
por: Allahyari, Elahe
Publicado: (2021)

Assessing COVID-19 risk with temporal indices and geographically weighted ordinal logistic regression in US counties
por: Chen, Vivian Yi-Ju, et al.
Publicado: (2022)

Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation
por: Singh, Vishwajeet, et al.
Publicado: (2020)

Psychological Distress and Its Correlates among Newly Diagnosed People Living with HIV in Northwest Ethiopia: Ordinal Logistic Regression Analyses
por: Moges, Nurilign Abebe, et al.
Publicado: (2021)

Sparse Logistic Regression for Diagnosis of Liver Fibrosis in Rat by Using SCAD-Penalized Likelihood
por: Yan, Fang-Rong, et al.
Publicado: (2011)

To tune or not to tune, a case study of ridge logistic regression in small or sparse datasets
por: Šinkovec, Hana, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_cglnundcufsbnre82qtr6solrs