Extracting novel information from neuroimaging data using neural fields

被引：6

作者：

Pinotsis, Dimitris A. ^{[1
]}

Friston, Karl J. ^{[1
]}

机构：

[1] UCL, Wellcome Trust Ctr Neuroimaging, Queen Sq, London WC1N 3BG, England

来源：

EPJ NONLINEAR BIOMEDICAL PHYSICS | 2014年 / 2卷 / 01期

关键词：

Neural field theory; Dynamic causal modelling; Attention; Connectivity; Gamma oscillations; V1; Electrocorticography; Visual cortex; Electrophysiology;

D O I：

10.1140/epjnbp18

中图分类号：

Q6 [生物物理学];

学科分类号：

071011 ;

摘要：

We showcase three case studies that illustrate how neural fields can be useful in the analysis of neuroimaging data. In particular, we argue that neural fields allow one to: (i) compare evidences for alternative hypotheses regarding neurobiological determinants of stimulus-specific response variability; (ii) make inferences about between subject variability in cortical function and microstructure using non-invasive data and (iii) estimate spatial parameters describing cortical sources, even without spatially resolved data.

引用

页数：12

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