A postdoctoral position is available in
the laboratory of Dr.
Mark Goldman at the University
of California at Davis. The lab works on a
broad range of problems in
computational neuroscience ranging from neural coding to
dynamics and
plasticity of single neurons and networks. Immediate funding is
available for a range of
projects related to working memory, neural integration,
motor learning, and
decision-making as described below. The
postdoctoral candidate also would have flexibility to work
on a range of issues
of his or her choosing. Candidates
are
expected to have strong training in an analytically rigorous
discipline such as
theoretical neuroscience, physics, mathematics, computer
science, or
engineering. The
postdoctoral candidate
will have ample opportunity to interact within the vibrant
computational and
systems neuroscience communities at UC Davis and in the
greater San Francisco
Bay Area.
Candidates
should
send a CV, brief statement of previous research and future
research
interests, and email addresses and phone numbers of three
references to: Mark
Goldman, msgoldman@ucdavis.edu. I will also be at the
upcoming SFN meeting.
Recent topics of particular interest to
the laboratory are:
1) Dynamics of memory
and motor-related neural activity:
Challenging the
attractor picture of working
memory. In the
traditional attractor
picture of working memory, memory storage results from
positive feedback
processes that lead to the formation of self-sustained
attractors. In one
project, we are exploring how
functionally feedforward, rather than feedback, network
architectures can
generate flexible codes for storing memories and producing a
broad range of
input-output transformations.
In a
second project, we are utilizing methods from engineering
control theory to
show how balanced cortical networks can utilize negative
feedback to stabilize
persistent patterns of neural activity.
Multi-scale modeling of
neural integration. The
oculomotor neural integrator is a model system
for understanding the mathematical integration of inputs and
the maintenance of
persistent neural activity.
We seek to
determine the respective roles of cellular and circuit
mechanisms of memory
storage in this system. Multi-scale
models,
from ion channels to behavior, will be generated based upon
electrophysiological
and optical imaging recordings from the laboratories of
David Tank at Princeton
University and Emre Aksay at Weill Medical College of
Cornell University.
Role of the granule
cell layer in cerebellar
motor learning. The
eye movement
system provides a highly tractable setting for studying
motor learning because
it is well-characterized experimentally and has fewer
degrees of freedom than
more complicated movement systems. In
collaboration with the whole-circuit optical imaging
experiments of Emre Aksay’s
laboratory, we are modeling the neural dynamics and coding
of cerebellar
granule neurons. Particular
focus is
upon understanding the circuit basis for the transformations
underlying
plasticity in the gaze-holding system and oculomotor neural
integrator.
2) Collective
intelligence and decision-making in ant colonies: In collaboration with
Deborah Gordon’s
laboratory at Stanford University, we are using the foraging
behavior of desert
ants as a model system to quantitatively understand
social
decision-making. Desert
ants have strong
ecological pressure to make wise choices as to when to leave
the nest to forage
for food. We are
modeling how the decision-making
processes of individual ants result in adaptive whole-colony
behavior.
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