Tuesday, June 12, 2012 3:30 pm
-
5:30 pm
EDT (GMT -04:00)
Optimal Control of Neurons
June 12 2012 in MC 5158
Speaker: Ali Nabi
Department
of
Mechanical
Engineering
University
of
California
at
Santa
Barbara
Motivated
by
issues
related
to
treating
certain
neurological
diseases
such
as
Parkinson's
disease
by
a
method
called
electrical
deep
brain
stimulation,
we
consider
applying
optimal
control
methods
to
both
mathematical
models
of
neurons
and
in
vitro
neurons.
Patients
suffering
from
Parkinson's
disease
experience
involuntary
tremors
that
typically
affect
the
distal
portion
of
their
upper
limbs.
It
has
been
hypothesized
that
these
tremors
are
associated
with
simultaneous
spiking
of
a
cluster
of
neurons
in
the
thalamus
and
basal
ganglia
regions
of
the
brain.
In
a
healthy
situation,
the
periodic
ring
of
neurons
is
not
synchronized,
but
they
can
engage
in
a
pathological
synchrony
and
all
fire
at
the
same
time
which
results
in
release
of
strong
action
potentials
that
trigger
the
downstream
muscles
with
periodic
shocks,
manifested
as
tremors.
In
this
talk,
we
investigate
the
control
of
different
neuronal
systems
using
methods
of
optimal
control.
The
neuronal
systems
considered
range
from
simple
one-dimensional
phase
models
to
multi-dimensional
conductance-based
models,
both
on
a
single
neuron
level
and
on
a
population
level.
The
optimal
control
methods
considered
produce
event-based,
continuous-time,
typically
bounded
input
stimuli
that
can
optimally
achieve
the
desired
control
objective.
The
optimality
criterion
considered
is
minimum
energy.
The
control
objectives
of
interest
are
the
interspike
interval
for
single
neurons
and
desynchrony
for
populations
of
neurons.
The
applicability
of
the
interspike
interval
controller
is
shown
in
practice
by
testing
it
on
single
in
vitro
pyramidal
neurons
in
the
CA1
region
of
rat
hippocampus.