Neuro and future exam 5 iclicker + notes

what is connectomics?

the study of how neurons connect and communicate within the brain

What is a big problem with light microscopy for studying connectomics?

it cant see fine enough details to trace individual connections

If there is a limit to light microscopy and super-resolution techniques are not practical, how can light microscopy be used to identify synapse connectivity?

expand the tissue by a known amount

What fills up the space in a hydrogel cube?

blood vessels, axons of passage, and dendrites from cells outside the plane

What is pan-protein fluorescence labeling?

compound/dye that targets entire classes of cellular structures

Why is pan-protein flourescence labeling used?

it allows for greater contrast between structures.

Clearing tissue

Brain tissue is naturally opaque due to the different refractive indices of its components, like lipids, proteins, and water. Clearing removes lipids and/or uses chemicals to align these refractive indices, making the tissue transparent.

What are the challenges of current microscopy?

they have massive data sizes and high data rates where time needed for image acquisition is immense for a whole a mammalian brain.

microscopic

at a nanoscale and electron microscopy is used to resolve tiny synaptic connections

mesoscopic

at a cellular level where there is mapping of long-range individual neurons across brain regions.

macroscopic

at a who brain level where it can map large fiber bundles and region to region connectivity

what are the challenges in image processing and analysis?

There are segmentation and reconstruction errors because there needs to be manual “proofreading” by humans and the structural connectome maps do not inherently reveal the function.

light microscopy

it holds considerable potential for unifying synapse-level circuit reconstruction with in-depth molecular characterization.

light microspcopy challenges

Its resolution is limited to about 200-300 nm, making it too coarse to distinguish densely labelled cellular structures

Electron microscopy

The only technology that allows dense connectivity analysis, and enormous strides have been made in using EM to map connectivity on organisms.

how does EM allow for connectivity?

Through chemical synapses to be inferred from structural features, but the synapses can’t be differentiated molecularly.

What is LICONN?

light-microscopy-based connectomics. A dense reconstruction of brain circuitry with light microscopy at synaptic resolution.

what is the dense connectomic capabilities of LICONN?

manual neuonal tracing and deep-learning cellular segmentation, traceability of axons and dendritic spines, and connectivity analysis at single-synapse resolution

What kind of molecular information comes from LICONN?

simultaneous molecular measurement, deep-learning prediction of molecular locations, and molecularly informed reconstruction of brain tissue.

What did the hydrogel-mediated tissue expansion (16x) with pan-protein staining and deep-learning segmentation show?

it shows the complex neuronal circuits within large tissue volumes and maintain high tracing accuracy

How did LICONN do in deep-learning based segmentation?

When they used various fluorescent markers to identify proteins associated with synaptic structures, they were able to match presynaptic and postsynaptic structures to identify connections.

what does segmenation mean?

separating an image into identifiable structures.

how did they use flood-filling networks?

to reconstruct neuronal structures from the microscopy data. they found that it had a 92.8% edge accuracy.

what did they find when they looked at how the neurons are connected?

they found that 90% of the identified synapses were located on dendritic spine heads. they also found that the inhibitory axons showed a different targeting pattern favoring dendritic shafts

what gap does LICONN close with light microscopy?

it can be used to trace individual neuronal structures and identify synapses using light microscopy.

What gap does LICONN close with structural and molecular information?

They can now examine the physical structure of neurons while simultaneously identifying specific proteins associated with their connections.

What gap does LICONN close with deep learning?

Deep learning models (artificial intelligence) can assist with neuronal segmentation and synapse identification.

What gap does LICONN close with examining different types of brain connections?

it can help identify excitatory chemical synapses, inhibitory chemical synapses, and electrical connections through gap junctions.