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 January 31, 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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