Transcript Functional imaging of hippocampal palace cells at celluar resolution

Speaker: Li-xia Gao
Supervisor: Jufang He
Department of Rehabilitation Scienc,
Hong Kong Polytechnic University
06/12/2010
Author information
1. Measurement and analyses of the neural
circuit dynamics
2. To apply advanced electrophysiological,
imaging, and genetic techniques to study the
mechanisms of persistent neural activity in
experimental preparations in goldfish.
3. Two-photon laser scanning microscopy for the
study of calcium concentration dynamics in
dendrites and nerve terminals in intact neural
circuits
David Tank
Department of Molecular Biology and Princeton Neuroscience Institute,
Princeton University, Princeton, New Jersey, USA
Background
1. The location-specific firing of hippocampal place cells
during navigation represents a salient neural correlate of
spatial information in the mammalian brain.
2. Whether or not hippocampal neurons with similar place
fields are spatially organized within the hippocampus?
1. Electrophysiological methods
low spatial resolution
2. Optical imaging is unavailable in behavior mouse
Whether hippocampal neurons with similar place fields are
spatially organized within the hippocampus?
Three obstacles:
cellular resolution imaging in the brain of a mobile mouse
imaging more than a millimeter beneath the cortical surface
imaging that is compatible with navigation behavior
Method
1.Mouse virtual reality system
The limbs of a head-restrained mouse
rested on spherical treadmill. A toroidal
screen that subtended a mouse’s visual
field surrounded the treadmill and
displayed a computer-generated image of
a virtual environment.
Ball movements recorded with an optical
computer mouse provided information on
running speed and direction and this was
used by the computer program that
implemented the virtual environment to
update position and view angle.
Head-restrained mice were trained using
operant conditioning to run back and forth
along a 180 cm–long virtual linear track
Photograph of
experimental setup
2. Two-photon microscopy
They designed and constructed a twophoton microscope that could fit within
the geometric constraints of their
virtual reality apparatus without
obstructing the mouse’s view of the
display
The microscope was completely
shielded from the bright light of the
virtual reality projection display so
that the smaller number of photons
from the fluorescent probe could be
detected by the photomultiplier tubes
(PMTs) without contamination. They
then implemented additional lightblocking measures at the laser
input port and the hole for the
microscope objective
3. A window for chronic imaging of CA1 neurons in awake mice
They carefully removed the overlying
cortex by aspiration and replaced it
with a metal cannula with a coverslip
sealing one of the openings. This
created a chronic hippocampal window
that allowed direct imaging of the
hippocampus.
They used genetically encoded
calcium indicators to optically record
the activity of CA1 neurons.
In vivo two-photon images at
different depths through the
hippocampal window.
Experiment protocol
1. Mice were implanted with a metal headplate to allow their
heads to be restrained while they were on the spherical treadmill.
2. They were placed on water scheduling for several days and then
trained in the virtual reality apparatus.
3. Once the mice were proficient at the task (~2 rewards per minute,
~7−10 d of training), they injected the GCaMP3 virus, and the
next day they implanted the hippocampal window.
4. The mice were returned to behavioral training for ~5−7 d until the
GCaMP3 expression produced an acceptable signal-to-noise
ratio for imaging calcium transients.
5. Using the hippocampal imaging window and viral delivery of
GCaMP3, they could image activity in CA1 neurons repeatedly
over the course of about 3−4 weeks.
Results
1. Optical identification of CA1 place cells
(a) Two-photon image of neuron cell bodies in CA1 labeled with GCaMP3.
(b) The temporal activity patterns of four neurons from the example field of
view shown in a, along with mouse position.
(d) Mean Δ F/F versus linear track position for a subset of the cells labeled in a (right).
(e) A plot of mean ΔF/F versus linear track position for all of the cells labeled in a (right).
(f) Place cells are colored according to the location of their place fields along
the virtual linear track. Only place cells with significant place fields during running in the
positive direction are shown.
2. Place cells differ depending on the running direction in the linear track
1 means directionality,
0 means no directionality
(a) The place cells are colored according to the location of their place fields along the
virtual linear track. Example place cells with different place fields depending on the
running direction are highlighted with closed arrowheads (b) A plot of mean ΔF/F
versus linear track position for the positive direction place cells labeled in a (left) during
running in the positive (left) and negative (right) directions. (c) Histogram of
directionality index for all place fields.
3. Characterization of place cell calcium transients and place fields
4. Place cell activity variability in place fields.
(a) Temporal activity pattern against
linear track position traces for
neurons shown in Figure 2a (right)..
(b) Mean and s.d. of Δ F/F
(c) Histogram of the probability that a
place cell is active during traversals
through the place field. (d) Histogram
of the percentage of place field
traversal time for which the cell had a
significant calcium transient.
5. The anatomical organization of CA1 place cells
(a) Example images from different fields of view in which the place cells are colored
according to the location of their place fields along the virtual linear track. Each
image shows place cells with significant place fields during running in either the
positive or negative direction.
Summary
Optically identified place cells had different
place fields in the same environment depending
on the direction of running.
Imaging also reveals their exact relative
anatomical locations.
They optically identified populations of place
cells and determined the correlation between
the location of their place fields in the
virtual environment and their anatomical
location in the local circuit.
The combination of virtual reality and highresolution functional imaging should allow a
new generation of studies to investigate
neuronal circuit dynamics during behavior.
Thank you
for your attention!