New X-ray microscopy technique enables comprehensive imaging of dense
neural circuits

Date:
September 14, 2020
Source:
Harvard Medical School
Summary:
A new x-ray microscopy technique could help accelerate efforts to
map neural circuits and ultimately the brain itself. Combined with
artificial intelligence-driven image analysis, researchers used
XNH to reconstruct dense neural circuits in 3D, comprehensively
cataloging neurons and even tracing individual neurons from muscles
to the central nervous system in fruit flies.



FULL STORY ==========================================================================
One of the grand quests in neuroscience is to build a precise map of the
brain, charting all its neurons and the connections between them. Such
a wiring diagram, called a connectome, promises to help shed light on
how a collection of cells can together give rise to thoughts, memories, behaviors and myriad other functions.


==========================================================================
Now, researchers at Harvard Medical School, Boston Children's Hospital
and the European Synchrotron Radiation Facility (ESRF) have demonstrated
that a new x- ray microscopy technique could help accelerate efforts to
map neural circuits and ultimately the brain itself.

Reporting in Nature Neuroscience on Sept. 14, the team describes how x-ray holographic nano-tomography (XNH) can be used to image relatively large
volumes of mouse brain and fruit fly nervous tissue at high resolutions.

Combined with artificial intelligence-driven image analysis, they
reconstructed dense neural circuits in 3D, comprehensively cataloging
neurons and even tracing individual neurons from muscles to the central
nervous system in fruit flies.

"We think this is going to open new avenues for understanding the brain,
both in how it's organized and the circuitry that underlies its function,"
said co- corresponding author Wei-Chung Allen Lee, HMS assistant
professor of neurology at Boston Children's. "This type of knowledge
can give us foundational insights into neurological disorders, diseases
that affect the structure of the brain and much more." For biological questions like neural circuit discovery, x-ray microscopy holds several advantages over current approaches based on electron microscopy (EM),
according to the authors.



==========================================================================
"We think XNH can bring a lot of value to neuroscience, because we can now access much larger volumes in shorter times," said co-corresponding author Alexandra Pacureanu, a scientist at the ESRF. "This is the beginning of
a new approach for efforts to map neural circuits." Near-light speed
Studying the connectome is a monumental challenge. The human brain,
for example, contains some 100 billion neurons with 100 trillion neural connections, roughly the number of stars within 1,000 galaxies.

In animal models, scientists have made remarkable progress, such as
imaging an entire fruit fly brain, primarily by taking serial slices of
a brain, each a thousand times thinner than a human hair, imaging the
slices with EM and stitching the images together for analysis.

The costs of this method can be prohibitive in terms of time and
resources, requiring large numbers of EM images, which have a narrow
field of view, and an intense effort to reconstruct even small neural
circuits. There is a need for new imaging modalities to accelerate such efforts, the study authors said.



==========================================================================
To do so, Lee's lab, which studies the organization and function of
neural circuits, collaborated with Pacureanu, who specializes in x-ray microscopy and neuroimaging. Spearheaded by co-first authors Aaron Kuan, research fellow in neurobiology at HMS, and Jasper Phelps, graduate
student in the Harvard Program in Neuroscience, the team focused on
applying XNH to neural tissue.

The technique works analogously to a CT scan, which uses a rotating
x-ray to create serial cross-sectional images of a body. In contrast,
XNH exposes a rotating tissue sample to high-energy x-rays at the ESRF's synchrotron, which accelerates electrons to near-light speed around an 844-meter ring.

Unlike standard x-ray imaging, which relies on differences in x-ray
attenuation as the beam passes through a tissue, XNH creates images
based on variations of subtle phase shifts of the beam induced by the
sample. This latter approach increases sensitivity and, combined with
imaging in cryogenic conditions, helps preserve and protect the specimen
from being damaged by x-ray energy.

Images generated by XNH must be interpreted to identify which structures
are neurons. The team tackled this by applying deep learning, an
artificial intelligence technique increasingly used for applications
such as face or object recognition.

As proof of principle, the researchers scanned millimeter-sized volumes of mouse and fruit fly neural tissue and reconstructed 3D images, achieving resolutions around 87 nanometers. This was enough to comprehensively
visualize neurons and trace individual neurites, the projections from
neurons that form the wiring of neural circuits.

Importantly, these reconstructions took a few days to achieve, compared
to the months to years it can take to reconstruct similar volumes using
serial EM sections.

Form to function In the mouse brain, the team looked at an area of
the cortex involved in integrating sensory stimuli and perceptual
decision making. Previous EM studies have noted interesting structural characteristics of so-called pyramidal neurons in this area, but have
been limited to sample sizes of around 20 neurons per dataset due to limitations in field of view.

Using XNH, the researchers scanned over 3,200 cells in this
area. Combined with aligned EM data, the team characterized the
structure and connectivity of hundreds of pyramidal neurons, which
revealed distinct structural properties - - such as strong and spatially compressed inhibitory inputs on certain neurite areas -- that suggest
unique and previously undescribed functional properties.

"Being able to visualize neurons helps us to understand the organizational principles of the brain and how different circuits or networks can
perform computations that are required for behavior," said Lee, who is an investigator at the Kirby Neurobiology Center at Boston Children's. "We
can then do further experiments to link structural data with functional experiments to try to address this question directly." They also imaged
the neurons contained within a fruit fly leg, a structure difficult to
section and study with EM. With XNH, they were able to map all of the
motor neurons extending from the fly equivalent of a spinal cord into
a leg, as well as the sensory neurons that relay signals to the central
nervous system.

"This technique has been applied to neural tissue before, but never with
this level of quality and resolution," said Pacureanu, who is a former
a visiting scientist in the Department of Neurobiology in the Blavatnik Institute at HMS.

"We've shown that we can achieve sufficient resolution to trace neurites
and move studies toward the direction of connectomes." The researchers
are now working to improve and further optimize XNH for imaging biological tissue.

The current resolution achieved by the technique is not yet high enough
to visualize synapses, which currently requires aligned EM data to
study. However, the physical limits of the technique are far from being reached, the authors said, and efforts to push the resolution will be
aided by a next-generation x- ray source recently operational at the ESRF.

"X-ray microscopy has particular strengths and one of our goals is to
apply it to larger networks of neural connections at higher resolutions,"
Lee said. "The hope is we could someday help address questions like can we understand neural circuits that underlie complex behaviors like decision making? Can we get inspiration for more efficient computer algorithms
and artificial intelligence? Can we reverse engineer the algorithms
of the brain?" Additional authors on the study include Logan Thomas,
Tri Nguyen, Julie Han, Chiao-Lin Chen, Anthony Azevedo, John Tuthill,
Jan Funke and Peter Cloetens.

The work was supported by the National Institutes of Health (grant R01NS108410), the Edward R. and Anne G. Lefler Center for the Study of Neurodegenerative Disorders and the Goldenson Family and the European
Research Council (grant 852455).


========================================================================== Story Source: Materials provided by Harvard_Medical_School. Original
written by Kevin Jiang.

Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Kuan, A.T., Phelps, J.S., Thomas, L.A. et al. Dense neuronal
reconstruction through X-ray holographic nano-tomography. Nat
Neurosci, 2020 DOI: 10.15151/ESRF-DC-217728238 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/09/200914114125.htm

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