Speaker: Li-xia Gao Supervisor: Jufang He

Department of Rehabilitation Scienc, Hong Kong Polytechnic University

06/12/2010

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

Author information

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 inf

ormation in the mammalian brain.

2. Whether or not hippocampal neurons with similar place fiel

ds 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

1.Mouse virtual reality system

Method

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 two-photon 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 light-blocking 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.

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 ne

xt 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 rati

o for imaging calcium transients.

5. Using the hippocampal imaging window and viral delivery of GCa

MP3, they could image activity in CA1 neurons repeatedly over t

he course of about 3−4 weeks.

Experiment protocol

Results

(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.

1. Optical identification of CA1 place cells

(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 alongthe virtual linear track. Only place cells with significant place fields during running in the positive direction are shown.

(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.

2. Place cells differ depending on the running direction in the linear track

1 means directionality,0 means no directionality

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 pla

ce 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.

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.

Summary

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 loca

tion in the local circuit.

The combination of virtual reality and high-re

solution functional imaging should allow a n

ew generation of studies to investigate neuro

nal circuit dynamics during behavior.

Thank you

for your attention!