Designing optimal stimuli to control neuronal spike timing
by
Yashar Ahmadian(Columbia U.)
→
Europe/Stockholm
122:026
122:026
Description
Recent advances in experimental stimulation methods have raised the
following important computational question: how can we choose a
stimulus that will drive a neuron to output a target spike train with
optimal precision, given physiological constraints?
I will present my work on this problem, where we adopt an
approach based on models which describe how a stimulating agent (such
as an injected electrical current, or a laser light interacting with
caged neurotransmitters or photosensitive ion channels) affect the
spiking activity of neurons. Based on these models, we solve the
reverse problem of finding the best time-dependent modulation of the
input, subject to hardware limitations as well as physiologically
inspired safety measures, that causes the neuron to emit a spike train
which with highest probability will be close to a target spike train.
We adopt fast convex constrained optimization methods to solve this
problem.
I will explain how we can carry out the optimization in computational time that scales linearly
with the temporal duration of the spike train, allowing for implementation in real time.
I will also explain how in certain situations we can use approximate optimization algorithms whose computational time scales
linearly also with the number of controlled cells. These properties make the method suitable for neural prosthesis applications.
I will also present simualted and experimental tests of the method.
