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Andrew P. Holmes
Researcher at AstraZeneca
Publications - 60
Citations - 31087
Andrew P. Holmes is an academic researcher from AstraZeneca. The author has contributed to research in topics: Parametric statistics & Population. The author has an hindex of 35, co-authored 59 publications receiving 29643 citations. Previous affiliations of Andrew P. Holmes include Hammersmith Hospital & University College London.
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Journal ArticleDOI
Multisubject fMRI studies and conjunction analyses.
TL;DR: It is suggested that activations common to all subjects reflect aspects of functional anatomy that may be "typical" of the population from which that group was sampled, and these commonalities can be identified by a conjunction analysis of the activation effects.
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A functional neuroanatomy of hallucinations in schizophrenia
David Silbersweig,David Silbersweig,Emily Stern,Emily Stern,Chris D. Frith,C. Cahill,Andrew P. Holmes,S. Grootoonk,J. Seaward,P. McKenna,S. E. Chua,L. Schnorr,Terry Jones,R. S. J. Frackowiak,R. S. J. Frackowiak +14 more
TL;DR: A group study of five patients with classic auditory verbal hallucinations despite medication, demonstrating activations in subcortical nuclei (thalamic, stri-atal), limbic structures (especially hippocampus), and paralimbic regions (parahippocampal and cingulate gyri, as well as orbito-frontal cortex).
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How many subjects constitute a study
TL;DR: In fMRI there are two classes of inference: one aims to make a comment about the "typical" characteristics of a population, and the other about "average" characteristics, which applies to studies of normal subjects that try to identify some qualitative aspect of normal functional anatomy.
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Nonparametric analysis of statistic images from functional mapping experiments
TL;DR: In this article, a nonparametric approach to significance testing for statistic images from activation studies is presented, which is based on a simple rest-activation study, and relies only on minimal assumptions about the design of the experiment, with Type I error (almost) exactly that specified, and hence is always valid.
Journal ArticleDOI
Generalisability, Random Effects & Population Inference
Andrew P. Holmes,Karl J. Friston +1 more
TL;DR: The generalisability of inferences drawn from multi-subject functional neuroimaging experiments is concerned, and a hierarchical model an inter-subject level model on the parameters of the standard intra- subject level model presented above is presented.