[Comp-neuro] PhD studentships: Computation in Brain and Mind at Brown University

Michael J Frank Michael_Frank at brown.edu
Tue Sep 10 02:26:00 CEST 2013

Announcing a new multidisciplinary initiative for Computation in Brain and
Mind <http://compneuro.clps.brown.edu> at Brown University, within the
Brown Institute for Brain Science.  PhD students are encouraged to apply to
any of the departments affiliated with the initiative, including
Neuroscience, Cognitive, Linguistic and Psychological Sciences, Applied
Mathematics, Computer Science and others.   The initiative includes a
seminar series focused on computation with distinguished lecturers, yearly
technical workshops and symposia,  and a yearly neural decoding
competition. The initiative will also have close links to parallel
initiatives at Brown in Human-Robot Interaction, Digital Society (big
data), and access to a high performance compute cluster with dedicated
cycles for Brain Science.

Brown neuroscientists and cognitive scientists rely on computational tools
for two core purposes: (i) to develop and refine theories about the
fundamental computations of mind and brain, used to guide and interpret
experiments; (ii) to develop sophisticated statistical analysis tools for
decoding neural data and predicting, for example, spike trains in a given
neuronal population based on their spike history and to leverage this
predictability for applications such as brain-machine interfaces. Other
applications include the use of computational tools to automate the
monitoring and analysis of behavioral neuroscience data.

Brown has particular expertise in computational approaches to higher order
brain function, from perception to cognition, spaning departments of
Neuroscience, Cognitive, Linguistic & Psychological Sciences, Applied
Mathematics, Computer Science, Neurosurgery, Biostatistics, and
Engineering. Most of these faculties cross theory and experiment, but
primary foci are listed here:

* Core level i*

* Computational perception: Theories about how the brain integrates sensory
information to give rise to percepts, constrained by biophysics and
computational objectives.

* Control over action: reinforcement learning, decision making, and
cognitive control; application to mental illnesses.

* Fundamental questions in neural computation: synaptic plasticity,
circuits, networks.

*Core level ii*

* Neurotechnology: brain-machine interface, advanced neural data analysis.

* Automated collection of neuroscience data, e.g. via computer vision and

* These core areas are supported by boundary-pushing development of
technical and analytic methods in Computer Science an Applied Mathematics.

Core faculty whose research and teaching focus centers around computation
in brain and mind include:

* James Anderson
* Joseph Austerweil
* Leon Cooper
* Michael Frank
* Stuart Geman
* Matthew Harrison
* James Hays
* Sorin Istrail
* Stephanie Jones
* Benjamin Kimia
* Michael Littman
* Xi Rossi Luo
* Thomas Serre
* Erik Sudderth
* Wilson Truccolo

In addition there are many affiliated faculty who rely on computation in
various aspects of their research. See
http://compneuro.clps.brown.edu/people/ for a full list.


Michael J Frank, PhD, Associate Professor
Laboratory for Neural Computation and Cognition
Brown University
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