Download Forea Wang

Forea Wang, [email protected]
Fall 2008
Postdoctoral Fellow: Dr. Nathan Wilson
Faculty Supervisor: Dr. Mriganka Sur
October 30, 2008
Patterned stimulation and adaptive neuronal responses in cortical circuits
CONTEXT AND SCOPE
Plasticity is the adaptive response of the brain to changes in inputs, and it is an
essential aspect of brain development and function. While work in this and other
laboratories strives to understand how neuronal responses come to be shaped by patterned
input from the environment, there remains no direct method for producing controlled
input patterns to a neuron and measuring its functional responses and adaptations.
Recently, a new system was developed in the Sur Laboratory that enables
multiple synaptic inputs to be stimulated in fine patterns by a computer while recording
synaptic responses and changes over time from neurons intracellularly. While the
hardware, software, and proof of principle experiments have been completed, it is now
necessary to carry out the controlled experiments to optimize stimulation and recording
parameters (verify that the pattern as envisioned reliably reaches the neuron), and
complete the second-order framework for routinely and comfortably exploring properties
of synaptic integration (make the system more fluid for designing and delivering new
The goal of this project is therefore to implement a multi-electrode array (MEA)
and integrated patch system for directly manipulating activity across multiple inputs in
order to examine 1) neuronal responses to patterned input, 2) adaptations of those
responses after repeated input, and 3) the dependence of those adaptations and responses
on specific molecular pathways. We are also interested in understanding how
anatomically-specified coordination of plasticity changes across multiple inputs emerges
to facilitate cortical processing and systems-level cortical plasticity.
In order to study the effects of patterned interplay, where changes to the strength
of one synapse influences the strength of another, we must be able to measure the
strength across multiple synaptic inputs to a neuron, and stimulate those inputs in
controlled patterns to induce adaptive responses. Several labs have recently been
working towards systems to do just this, such as patching a neuron while stimulating
neighboring neurons with the focal delivery of glutamate, or patching a neuron while
stimulating neighboring neurons with a depolarizing channel that is activated by laser
light.
In the Sur Lab, the development of an analogous system is underway, in which we
use patch clamp intracellular recording along with micro-electrodes deposited in finescale patterned arrays to stimulate neurons across a mouse brain cortical slice. However
our system features two key advantages: first, the computer interacts with the tissue
directly through the common currency of electricity and the robust communication
channels of electrical wires, which do not require additional heterologous expression of
molecules, viral packaging and delivery of constructs, a reliance on finicky optics, or the
perfusion of excitable compounds. Second and more importantly, our system can
stimulate multiple sites simultaneously, in contrast to the laser-guided systems which
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would require multiple beams to stimulate more than one site reliably. As such our
system offers to fulfill the promise of controlled, multi-site stimulation in patterns that
have not only a temporal component, but also a spatial one, and the integration of inputs
from multiple cells in tandem can be investigated.
Part of the UROP will involve dynamic discussions on how to design highly controlled
experiments for validating the system step-wise and logically. First, a cell will be patch
clamped and the system used to drive a nearby electrode until that cell is induced to fire
an action potential, thus verifying the efficacy of the system to stimulate single neurons.
We will collect data of both random and periodic stimulation, demonstrated in a graph of
voltage vs. time over a period of 5 seconds. In order to confirm the threshold effect of
action potentials, the nearby electrode will be driven at increasing voltages to induce an
action potential. Probability of response vs. voltage will demonstrate the “all or none”
aspect of action potentials.
Then, another neuron will be patched and other electrodes stimulated until an
electrode succeeds in driving synaptic activity to the patched postsynaptic neuron. If
activity is synaptic, we should be able to measure a constant Δt between stimulation and
response. Meanwhile, other electrodes will be stimulated to elicit interplay of other
synapses onto the same neuron. Once synaptic drive has been achieved in this manner,
with synapses of different strengths coming from different cortical locations, mapping
software will depict the anatomical location of these inputs and map their strengths.
Once the locations and strengths of these excitatory and inhibitory inputs have
been mapped and recorded stably, we can first test multi-site stimulation with two sites of
stimulation to synapse at the same neuron, alternately as well as in summation. We will
also test the effects of summation of an excitatory and inhibitory synapse in comparison
to two excitatory synapses. Since the MEA is in fact a 64-pin system, we can then expand
to large summations.
Preliminary patterns will include quick alternation between groups of excitatory
and/or inhibitory synapses, summations of groups, a “moving bar” across all electrodes,
and a study on pattern completion. A more developed plasticity paradigm can then be
applied during these recordings, and changes to the strengths of the inputs as a result can
be assessed – this would allow us to not only measure the strengths of multiple synapses
onto a neuron, but change the strengths of some of those synapses and see what it does to
the strengths of the remaining synapses.
SPECIFIC AIMS: data collection – figures
A. Verify efficacy of the system to stimulate single neurons
1. (graph) voltage vs. time: show AP spikes; mark times of stimulation (Xmax =
5sec);
 random & periodic stimulation
2. demonstrate threshold effect (stimulate with different voltages)
 (graph) probability of AP fired vs. voltage
 (graph) probability vs. normalized voltage
3. drugs (TTX): if no response detected, can confirm that former responses were
induced action potentials
 (graph) voltage vs. time; mark times of stimulation (Xmax = 5sec)
4. (graphs) stability over time: show results do not change as time passes
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same graphs after time lapse, Δt = 20 min.
B. Drive synaptic activity to patched postsynaptic neuron
1. If activity is synaptic, Δt (stimulation to response) should be constant
 voltage vs. time; mark time of stimulation; mark constant Δt
 bar graph: Δt for different synapses; error bar to show effectively const. Δt
2. (graph) histogram for one synapse
3. drugs: NBQX (AMPA receptor blocker): if no response detected, can confirm that
former responses were synaptic activity
 voltage vs. time: mark times stimulation (Xmax = 1sec, 200msec sweep)
4. Recording different synapses: strong, weak, blank
 (graph) voltage vs. time; mark times of stimulation
5. (graphs) stability over time: show results do not change as time passes
 same graphs after time lapse, Δt = 20 min.
C. Drive multi-site synaptic activity to patched postsynaptic neuron (synapses A, B, C,
etc. to neuron N)
1. (image) color-coded mapping of strong and weak synapses (static)
2. (graph) A to N and B to N (slow alternating) voltage vs. time
 plot two lines
3. (graph) [A+B] to N (summation response) voltage vs. time
 plot [A+B] observed and [A+B] predicted based on individual response
4. (graph) weak synapse C to N, voltage vs. time
 plot one line
5. (graph) [A+B+C] vs. [A+B] (summation of strong and weak) voltage vs. time.
 plot [A+B+C] observed, compared to [A+B] and individual C
 shows influence of weak synapse C on stronger synapses A and B
6. (graph) [A+B+C+D+….] (summation of multiple sites) voltage vs. time
D. Preliminary patterns (on a time scale) (synapses A, B, C, etc. to neuron N)
1. fast alternation
 A to N, B to N
 teams (clusters of strong synapses in alternation)
2. fast summation
 [A+B] to N
 teams of strong synapses to N
3. moving bar across all 64 electrodes (horizontally and vertically)
4. novelty
 team 1 (high frequency, steady stimulation, strong synapses) vs. team 2
(low frequency, inconsistent stimulation, weak synapses)
5. pattern completion
 How many synapses of the “team” are needed? Stimulate only a portion
of a team
 Competition: Stimulate portions of both teams (which response pathway
does neuron take?)

SKILLS AND TECHNIQUES
 Implementing MEA
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o Whole-cell patch recordings in MEA environment
o Utilize new MATLAB program to drive electrodes according to plasticity
paradigm
 Acute slice physiology
o Continued improvement of slice preparation
 Solution preparation
 Dissection
 Vibratome Slicing
 Whole-cell recording
o Adapt single-site stimulation patch techniques to MEA
 Pharmacology
o Prepare aliquots of drugs
o Introduce drugs to perfusion
o Record results in MATLAB
 Animal Facility
o Update Mouse Census
o Maintain healthy mouse cages (overcrowding, etc.)
RESPONSIBILITIES
 Acute slice physiology
o Prepare solution
 Cutting solution
 Artificial cerebrospinal fluid solution (ACSF)
o Dissection
 Sacrifice mouse
 Remove brain
o Vibratome slicing
 300µm coronal sections
 Whole-cell patch recording
o Rig setup
 Establish perfusion with ACSF
 Software/hardware setup (Prism MATLAB program, MEA chip,
manipulator, amplifier, MultiClamp Commander program, optics)
 Slice placement
 Pipette preparation using pipette puller
 Prepare intracellular solution for pipette
o Patching on MEA chip
 MEA stimulation
o Utilize Prism MATLAB program
 to drive electrodes in patterned stimulation
 record results, develop maps
o Help develop & implement plasticity paradigm
o Translate raw data into practical figures
LOCATION
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Research will be carried out through the Department of Brain and Cognitive
Sciences, in the laboratory of Mriganka Sur in the Picower Institute for Learning and
Memory.
WORK PLAN
I plan to devote 12 hours/week to this UROP project.
PERSONAL
This project is the continuation of a UROP that I started in the 2007-2008 school
year under Dr. Nathan Wilson. During that time, I gained the technical skills necessary
to be comfortable preparing acute slices from the cortex of the mouse. My hope for this
semester is to develop my research skills as we further develop our new MEA system and
begin to collect data. I am excited to conduct relevant research that could potentially have
a profound effect in the neuroscience field.
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