Classification Accuracies for Selected Brain Regions.

NIAID Data Ecosystem2026-03-07 收录

脑区分类评估

神经影像模式识别

数据链接：

https://figshare.com/articles/dataset/_Classification_Accuracies_for_Selected_Brain_Regions_/725935 数据链接链接失效反馈

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资源简介：

Classification Accuracies for Selected Brain Regions.

创建时间：

2013-06-19

Sonobe et al.: The raw t-value maps of the searchlight analysis

神经影像模式识别

多感官整合

The raw t-value maps of the searchlight analysis: 1) Cross-classification between visuotactile and visuomotor trials. 2) Within-classification of visuotactile trials. 3) Within-classification of visuo

Figshare2022-02-24 更新60

CROSS-VALIDATION OF FUNCTIONAL MRI and PARANOID-DEPRESSIVE SCALE: BRAIN SIGNATURES FROM MULTIVARIATE ANALYSIS

精神疾病脑影像诊断

神经影像模式识别

Brain signatures identified by bottom-up unsupervised machine learning: three principal components based on activations yielded from the three kinds of diagnostically relevant stimuli are used in orde

NIAID Data Ecosystem40

MRI Pattern Recognition in Multiple Sclerosis Normal-Appearing Brain Areas

多发性硬化症诊断

神经影像模式识别

ObjectiveHere, we use pattern-classification to investigate diagnostic information for multiple sclerosis (MS; relapsingremitting type) in lesioned areas, areas of normalappearing grey matter (NAGM)

NIAID Data Ecosystem30

Appendix S1 - Decoding Semi-Constrained Brain Activity from fMRI Using Support Vector Machines and Gaussian Processes

fMRI脑活动解码

神经影像模式识别

Outputs of SVM and GP classifiers (second and third lines respectively) applied on one example data point. (DOCX)

NIAID Data Ecosystem50

Comparison of discriminative performance of different MVPA methods on TRD versus TSD and TRD or TSD versus controls.

抑郁症亚型研究

神经影像模式识别

PCA, Principal component analysis; RFE, recursive feature elimination; LLE, locally linear embedding; TRD, treatment-resistant depression; TSD, treatment-sensitive depression; HC, healthy control.

Figshare2015-12-02 更新30

Classification Accuracies for Selected Brain Regions.

资源简介：

相关数据集