Brain Map Technology Reveals unprecedented details of neural connections

Scientists have developed a powerful new technology that can change our understanding of the brain’s intricate wiring systems. The breakthrough approach, known as light micromirror-based connectomics (LICONN), enables researchers to map complex neural networks of the brain at the nanoscale while identifying specific molecules in these connections. This innovative approach, detailed in a new study published in nature, takes scientists one step closer to a comprehensive understanding of how brain cells communicate and function.

Blinking the gap between structure and function

Until now, researchers studying brain connectivity have faced a challenging trade-off: They can use electron microscopes (EMs) to see the detailed physical structure of neural connections, or use optical microscopes to identify specific molecules, but not simultaneously at the resolution required to track a single connection.

Liconn overcomes this limitation by combining innovative organizational preparation with artificial intelligence. The technology expands approximately 16 times the brain tissue sample while retaining structural integrity, and then uses machine learning to analyze the extended samples and reconstruct its complex cellular structure.

“The brain consists of dense, complex and fine-grained arrangements of neurons with support cells that together form a functional network that enables the brain to function,” the researchers explained in their study. This new approach allows scientists to visualize this arrangement with unprecedented clarity and molecular environment.

How Liconn works

The technique is based on a method called an expansion microscope that physically enlarges tissue samples to reveal that the details are too small to be seen using a conventional microscope. The LaConn method can greatly improve this process through a series of chemical innovations:

• Brain tissue is embedded in a specially designed scalable hydrogel that retains cellular structure
• The hybrid of tissue mixed gel is about 16 times, bringing nanoscale features into the field of view
• Standard fluorescence microscope captures enlarged structures at high resolution
• Deep learning algorithm reconstructs neural networks with 92.8% accuracy
• Molecular tags identify specific proteins at synapses and other cellular structures

This combination allows researchers to visualize details at 20nm using standard microscopes, a resolution that was previously only achieved using more complex and expensive specialized equipment.

See brain connections in new eyes

In recent years, the traditional method of mapping brain circuits with electron microscopes has made great progress, but it has important limitations, especially in extracting molecular information. By contrast, Liconn directly visualizes structural connections and molecular details in the same sample.

The researchers demonstrated Liconn’s ability by mapping about 1 million cubic microns from the mouse cerebral cortex. In this volume, they identify individual neurons, their connections, and the molecular composition of these connections.

The technology reveals amazing details of brain architecture, including the precise arrangement of synaptic proteins less than 100 nanometers apart, i.e. 1/1000 of the width of human hair. It also determines the periodic pattern of proteins along the axons, i.e. the long projection used by neurons to send signals, with intervals of about 89 nanometers.

Making advanced brain mapping easier to access

Perhaps most importantly, Liconn gives more researchers access to high-resolution brain mappings. Although electron microscopy requires specialized equipment and expertise, Liconn works with standard laboratory microscopy and technology.

“Liconn is highly accessible,” the researchers noted. “The acquisition is powered by the widely available conventional light micromirror hardware… Although Liconn sample preparation introduces new strategies to enable high-fidelity tissue expansion, the protocol is fundamentally no more complex than the scaling techniques that have been widely adopted before.”

This accessibility can greatly accelerate research on the brain structure and function of the neuroscience community.

Beyond basic connections

The molecular information provided by Liconn opens up new research avenues instead of mapping basic connections. In their study, the researchers demonstrated several applications, including:

Identify excitatory synapses and inhibitory synapses based on their molecular composition, thereby gaining insight into the balance of nerve activation and inhibition. The team found that about 90% of dendritic inputs (branch expansion of nerve cells) were excitatory, while 10% were inhibitory, consistent with previous observations.

Visualizing electrical connections called gap junctions is difficult to identify with electron microscopy, but is crucial to understand how neurons synchronize their activity.

Examine the characteristics of specialized cellular structures, such as the characteristics of primary cilia (cells used for signaling) and compare their characteristics between normal mice and those of people with gene mutations associated with epilepsy and intellectual disabilities.

Finding the future of brain mapping

While the amount of plotted by the current liconn implementation is similar to that of electron microscopy studies, the researchers envision scaling the technology to map larger brain regions. They suggest that combining licon with a technique that measures gene expression directly in tissues can provide a more comprehensive brain function map.

“By combining connectivity with in situ molecular information from a single cell, Liconn proposes feasible pathways to multimodal descriptions of mammalian brain cells, including morphology, connectivity (including electrical connections), physiology, and gene expression,” the researchers concluded.

As neuroscientists continue to reveal unusually complex wiring in the brain, technologies like Liconn bridge the gap between physical connections and molecular functions, promise to speed up our understanding of how the brain works and potentially problems arise in neurological disorders.

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