Connectionists: Computational Neuroscience Graduate Program at UCSD

[Terry Sejnowski]

       UCSD GRADUATE PROGRAM IN COMPUTATIONAL NEUROSCIENCE

https://healthsciences.ucsd.edu/education/neurograd/computational/Pages/default.aspx

Application deadline: Thursday, December 1, 2016:
http://neurograd.ucsd.edu/2page.php?id=gradadm

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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 theories for brain function and behavior.  

Candidates from a wide range of backgrounds are invited to apply,
including Biology, Psychology, Computer Science, Engineering, 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
optogenetics, two-photon laser scanning microscopy, diffusion tensor
imaging and  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 differential
covariance and delay-differential analysis.

3. Dynamics and Control of Neurons and Neural Circuits:
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 are used to explore the collective properties and nonlinear
dynamics of neuronal systems, as well as issues in sensory coding and
motor control.

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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. 
* Kenta Asahina (Salk Institute):  Neural circuits for aggression and escape
 behavior in flies
* Eimen Azim (Salk Institute):  Neural circuits underlying motor planning, 
 execution and learning.
* Sharona Ben-Haim (Neurosurgery): Mechanisms for seizures propagation
 in humans and monkeys.
* Ed Callaway (Salk Institute):  Neural circuits, visual perception, visual cortex,
 and 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 Institute):  C. elegans: genes, networks and behavior
 Optical recording of olfactory processing.
* Andrea Chiba (Cognitive Science): Spatial attention, associative learning, 
 cholinergic neuromodulation of behavior, amygdala recordings
* 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
* Ralph Greenspan (Neurobiology): Molecular and neurobiological studies 
 of innate and learned behaviors in the fruit fly
* Xin Jin (Salk Institute):  How the brains learn and generate actions.
* 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.
* Scott Makeig (Institute for Neural Computation): Analysis of cognitive
 event-related brain dynamics and fMRI using time-frequency and Independent
 Component Analysis
* 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
 neuroscience; neuroanatomical scaling.
* Massimo Vergassola (Physics): Modeling, dynamics, orientation, 
 sensory systems, biological physics 
* 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.

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On-line applications: http://neurograd.ucsd.edu/2page.php?id=gradadm

The deadline for completed application materials, including letters of
recommendation, is Thursday, December 1, 2016. 

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