UCSD GRADUATE PROGRAM IN COMPUTATIONAL NEUROSCIENCE
Application deadline: December 3, 2012
The goal of the Computational Neuroscience Specialization in the
Neurosciences 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
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
Participating Faculty include:
* Henry Abarbanel (Physics): Nonlinear and oscillatory dynamics;
modeling central pattern generators in the lobster stomatogastric ganglion.
* 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 (Bioengineering): Neuromorphic Engineering; analog VLSI
chips; wireless recording and nanoscale instrumentation for neural
systems; large-scale cortical modeling.
* Sreekanth Chalasani (Salk): C. elegans: genes, networks and behavior
Optical recording of olfactory processing.
* Andrea Chiba (Cognitive Science): Spatial attention, associative learning,
cholinergic neuromodulaiton of behavior, amygdala recordings
* EJ Chichilnisky (Salk Institute): Retinal multielectrode recording;
neural coding, visual perception.
* Todd Coleman (Bioengineering): Brain-Machine Interfaces (BMI)
* Garrison Cottrell (Computer Science and Engineering): Dynamical
neural network models and learning algorithms
* Virginia De Sa (Cognitive Science): Computational basis of perception
and learning; multi-sensory integration and contextual influences
* Mark Ellisman (Neurosciences, School of Medicine): High resolution
electron and light microscopy; anatomical reconstructions.
* Fred Gage (Salk Institute): Neurogenesis and models of the hippocampus;
neuronal diversity, neural stem cells.
* Timothy Gentner (Psychology): Birdsong learning. Neuroethology of vocal
communication and audition
* Robert Hecht-Nielsen (Electrical and Computer Engineering): Neural
computation and the functional organization of the cerebral cortex.
* Steve Hillyard (Neurosciences): EEG, perception, attention, memory,
Event related potentilas, SSVEP
* 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.
* Scott Makeig (Institute for Neural Computation): Analysis of cognitive
event-related brain dynamics and fMRI using time-frequency and Independent
* Javier Movellan (Institute for Neural Computation): Sensory fusion
and learning algorithms for continuous stochastic systems
* Howard Poizner (Institute for Neural Computation): Motor systems,
basal ganglia, reinforcment learning, Parkinson's disease.
* 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.
* John Reynolds (Salk): Visual attention, cortex, psychophysics,
neurophysiology, neural modeling
* Massimo Scanziani (Biology): Neural circuits in the somotosensory
cortex; physiology of synaptic transmission; inhibitory mechanisms.
* Terrence Sejnowski (Salk Institute/Neurobiology): Computational
models and physiological studies of synaptic, neuronal and network function.
* Tanya Sharpee (Salk): Statistical physics and information theory
approaches to sensory processing in natural auditory and visual environments.
* Gabe Silva (Bioengineering): Cellular neural engineering
* Nicholas Spitzer (Neurobiology): Regulation of ionic channels and
neurotransmitters in developing neurons and neural function.
* 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
* Jing Wang (Biology): Representation of olfactory information in
the nervous system of Drosophila
* Ruth Williams (Mathematics): Probabilistic analysis of stochastic
systems and continuous learning algorithms
* Angela Yu (Cognitive Science): Sensory processing, attentional selection,
perceptual decision-making, sensorimotor integration, learning, and adaptation.
On-line applications: http://neurograd.ucsd.edu/2page.php?id=gradadm
The deadline for completed application materials, including letters of
recommendation, is December 3, 2012.
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