[Comp-neuro] UCSD Computational Neurobiolology Gradaute Training Program

Terry Sejnowski terry at salk.edu
Mon Oct 27 23:13:17 CET 2008

                    DEADLINE: DECEMBER 1, 2008

Neurosciences Graduate Training Program - University of California, San Diego

The goal of the Computational Neurobiology Graduate Program at UCSD
is to train researchers who are equally at home measuring large-scale brain
activity, analyzing the data with advanced computational techniques, and
developing new models for brain development and function.  

Candidates from a wide range of backgrounds are invited to apply,
including Biology, Psychology, Computer Science, Physics and
Mathematics. The three major themes in the training program are:

1. Neurobiology of Neural Systems: Anatomy, physiology and behavior
of systems of neurons.  Using modern neuroanatomical, behavioral,
neuropharmacological and electrophysiological techniques.  Lectures, wet
laboratories and computer simulations, as well as research rotations. Major
new imaging and recording techniques also will be taught, including
two-photon laser scanning microscopy and functional magnetic resonance
imaging (fMRI).

2. Algorithms and Realizations for the Analysis of Neuronal Data:
New algorithms and techniques for analyzing data obtained from physiological
recording, with an emphasis on recordings from large populations of
neurons with imaging and multielectrode recording techniques.  New
methods for the study of co-ordinated activity, such as multi-taper spectral
analysis and Independent Component Analysis (ICA).

3. Neuroinformatics, Dynamics and Control of Systems of Neurons:
Theoretical aspects of single cell function and emergent properties as
many neurons interact among themselves and react to sensory inputs. A
synthesis of approaches from mathematics and physical sciences as well as
biology will be used to explore the collective properties and nonlinear
dynamics of neuronal systems, as well as issues of sensory coding and
motor control.

Participating Faculty include:

* Henry Abarbanel (Physics): Nonlinear and oscillatory dynamics;
 modeling central pattern generators in the lobster stomatogastric
 ganglion.  Director, Institute for Nonlinear Systems at UCSD
* Thomas Albright (Salk Institute): Motion processing in primate visual
 cortex; linking single neurons to perception; fMRI in awake, behaving
 monkeys.  Director, Sloan Center for Theoretical Neurobiology
* Darwin Berg (Neurobiology): Regulation synaptic components, assembly
 and localization, function and long-term stability.
* Ed Callaway (Salk Institute):  Neural circuits, visual perception, visual cortex
Genetic tools for tracing neural pathways.
* Gert Cauwenberghs (Biology):  Neuromorphic Engineering; analog VLSI
 chips; wireless recording and nanoscale instrumentation for neural
 systems; large-scale cortical modeling.
* EJ Chichilnisky (Salk Institute):  Retinal multielectrode recording;
 neural coding, visual perception.
* Garrison Cottrell (Computer Science and Engineering): Dynamical
 neural network models and learning algorithms
* Virginia De Sa (Cognitive Science): Computational basis of perception
 and learning (both human and machine); multi-sensory integration and
 contextual influences
* Mark Ellisman (Neurosciences, School of Medicine): High resolution
 electron and light microscopy; anatomical reconstructions. Director,
 National Center for  Microscopy and Imaging Research
* Fred Gage (Salk Institute): Neurogenesis and models of the hippocampus;
neuronal diversity, neural stem cells.
* Robert Hecht-Nielsen (Electrical and Computer Engineering): Neural
 computation and the functional organization of the cerebral cortex.
 Founder of Hecht-Nielsen Corporation
* Harvey Karten (Neurosciences, School of Medicine): Anatomical,
 physiological and computational studies of the retina and optic tectum
 of birds and squirrels
* David Kleinfeld (Physics): Active sensation in rats; properties of
 neuronal assemblies; optical imaging of large-scale activity.
* William Kristan (Neurobiology):  Computational Neuroethology; functional
 and developmental studies of the leech nervous system, including
 studies of the bending reflex and locomotion.  Director, Neurosciences
 Graduate Program at UCSD
* Herbert Levine (Physics): Nonlinear dynamics and pattern formation
 in physical and biological systems, including cardiac dynamics and the
 growth and form of bacterial colonies
* Scott Makeig (Institute for Neural Computation): Analysis of cognitive
 event-related brain dynamics and fMRI using time-frequency and Independent
 Component Analysis
* Javier Movellan (Institute for Neural Computation): Sensory fusion
 and learning algorithms for continuous stochastic systems
* Mikhael Rabinovich (Institute for Nonlinear Science): Dynamical
 systems analysis of the stomatogastric ganglion of the lobster and the
 antenna lobe of insects
* Pamela Reinagel (Biology):  Sensory and neural coding; natural scene
 statistics; recordings from the visual system of cats and rodents.
* Massimo Scanziani (Biology):  Neural circuits in the somotosensory
 cortex; physiology of synaptic transmission; inhibitory mechanisms.
* Terrence Sejnowski (Salk Institute/Neurobiology): Computational
 neurobiology; physiological studies of neuronal reliability and
 synaptic mechanisms. Director, Institute for Neural Computation
* Tanya Sharpee (Salk):  Statistical physics and information theory 
approach to understanding sensory processing. Statistical properties 
of natural auditory and visual environments.
* Nicholas Spitzer (Neurobiology):  Regulation of ionic channels and
 neurotransmitters in neurons; effects of electrical activity in
 developing neurons on neural function. Chair of Neurobiology
* Charles Stevens (Salk Institute): Synaptic physiology; theoretical
 models of neuroanatomical scaling.
* Roger Tsien (Chemistry):  Second messenger systems in neurons;
 development of new optical and MRI probes of neuron function,
 including calcium indicators and caged neurotransmitters
* Ruth Williams (Mathematics): Probabilistic analysis of stochastic
 systems and continuous learning algorithms

On-line applications: http://neurograd.ucsd.edu/admissions/index.html

The deadline for completed application materials, including letters of
recommendation, is December 1, 2008.

More information about the Comp-neuro mailing list