Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.

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Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.

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2018 nî lūn-bûn

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2018年の論文

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年學術文章

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Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.

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Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.

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Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.

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Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.

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Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.

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Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.

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P1476

Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI

@en

P2093

Jain Mangalathu-Arumana

http://www.w3.org/2001/XMLSchema#string

P2860

What we can do and what we cannot do with fMRI

How to use fMRI functional localizers to improve EEG/MEG source estimation.

General overview on the merits of multimodal neuroimaging data fusion

Cortical Surface-Based Analysis

An information-maximization approach to blind separation and blind deconvolution

AFNI: software for analysis and visualization of functional magnetic resonance neuroimages

Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system

Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties

Within-subject joint independent component analysis of simultaneous fMRI/ERP in an auditory oddball paradigm.

Specialization along the left superior temporal sulcus for auditory categorization

P304

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P31

scholarly article

P356

10.3389/FNINS.2018.00013

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P478

http://www.w3.org/2001/XMLSchema#string

P50

Einat Liebenthal

Scott A Beardsley

P577

2018-01-23T00:00:00Z

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P698

29410611

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P932

5787094

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