Machine Learning for Neuroimaging: applications and theoretical challenges
Neuroimaging techniques produce large amounts of
brain images of different natures, allowing researchers and clinicians
to gain insights of unprecedented quality on the cerebral anatomy, its
connectivity structure and its functions. On the one hand,
the development of these techniques provides neuroscientists with a
growing amount and variety of data, and thus, a potentially improved
understanding of the brain, and on the other hand, it precisely poses
the challenge of devising automated methods for a high-level
understanding of neuroimages. These methods would be of importance to
decode mental thoughts, understand cortical representations, categorize
and classify brain responses, detect abnormalities in the brain, remove
noise, take advantage of correlated prior information, help the
diagnosis, and so on. Machine learning is probably one of the most
promising field of research that would bring new approaches and
procedures for automated neuroimaging interpretation.
main goal of this workshop is precisely to bring together people from
the machine learning community and people from the neuroimaging
community that are keen to discuss their expertises. Potential outcomes
to this workshop are for instance: the formal/machine learning setting
of common problems in neuroimaging, the identification of new problems
that can be readily tackled using machine learning techniques, the
creation of new collaborations. It is also expected that discussions
will build around important challenges of machine learning posed by
neuroimaging data such as feature selection in presence of few data,
transfer learning, structured prediction...
the various themes that are of primary interest for the workshop, time
will be devoted to sparsity based methods, feature selection,
graph-based representation of image and kernel methods, exploitation of
prior and heterogeneous knowledge to build predictive models.
Dates of the workshop: Nov. 8 and 9, 2011.
Location: Marseille, at Institut de Neurosciences de la Timone (see venue)
Thanks to our sponsors, registration is free -- though mandatory.