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STATISTICA SINICA
Call for submissions on
STATISTICAL CHALLENGES AND ADVANCES IN BRAIN SCIENCE
Statistics and probability theory play key roles in cutting edge brain
research. Leading examples include non-linear time series analysis for
studying brain dynamics using electro/magnetoencephalograms and random
field theory in analyzing 3D neuroimaging datasets. This special issue
will highlight statistical and probabilistic topics related to all aspects
of brain science, including but not limited to, computational
neuroscience, neuronal modeling, and structural and functional
neuroimaging.
Submissions preferably will provide either methodological or theoretical
advances in the statistical aspects of brain science or demonstrate
applications of techniques using statistics in neuroscience. Priority
will be given to papers that are assessed to be, statistically and
scientifically speaking, the most innovative, comprehensive, and of
interest to a wide readership.
Papers submitted to the special issue will be reviewed according to the
regular procedure of the journal. Accepted papers will appear in a single
issue of Statistica Sinica, scheduled for 2008. Please contact John Aston
(jaston at stat.sinica.edu.tw) for questions on the suitability of your
paper(s). Submissions must be made online through the journal site at
http://www3.stat.sinica.edu.tw/statistica/
Please use the LaTeX article template, also available at the above site,
for preparing your manuscript submission. The deadline for submission is
April 15, 2007. Authors wishing to receive email alerts as the deadline
approachs may contact the editorial assistant, Karen Li (Karen at
stat.sinica.edu.tw).
Guest Editors:
John Aston, Academia Sinica
Emery Brown, Harvard University
Keith Worsley, McGill University
Yingnian Wu, UCLA
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Statistica Sinica endeavors to meet the needs of statisticians faced with
a rapidly changing world. It publishes significant and original articles
that promote the principled use of statistics along with related theory
and methods in quantitative studies, essential to modern technologies and
sciences.
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