Statistical limitations in functional neuroimaging II. Signal detection and statistical inference
نویسندگان
چکیده
منابع مشابه
Statistical limitations in functional neuroimaging. II. Signal detection and statistical inference.
The field of functional neuroimaging (FNI) methodology has developed into a mature but evolving area of knowledge and its applications have been extensive. A general problem in the analysis of FNI data is finding a signal embedded in noise. This is sometimes called signal detection. Signal detection theory focuses in general on issues relating to the optimization of conditions for separating th...
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Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse...
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چکیده ندارد.
15 صفحه اولWavelet-Based Statistical Analysis in Functional Neuroimaging
Wavelet-based analysis versus Gaussian smoothing in statistical parametric mapping (SPM) for detecting and analyzing brain activity from functional magnetic resonance imaging (fMRI) data is presented. Detection of activation in fMRI data can be performed in the wavelet domain by a coefficient-wise statistical t-test. The link between the wavelet analysis and SPM is based on two observations: (i...
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ژورنال
عنوان ژورنال: Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences
سال: 1999
ISSN: 0962-8436,1471-2970
DOI: 10.1098/rstb.1999.0478