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connectomics

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google

A new light on neural connections (opens in new tab)

Google and the Institute of Science and Technology Austria (ISTA) have developed LICONN, the first light-microscopy-based method capable of comprehensively mapping neurons and their connections in brain tissue. This approach overcomes the traditional reliance on expensive electron microscopy by utilizing physical tissue expansion and advanced machine learning to achieve comparable resolution and accuracy. The researchers successfully validated the technique by reconstructing nearly one million cubic microns of mouse cortex, demonstrating that light microscopy can now achieve "dense" connectomics at scale. ## Overcoming Resolution and Cost Barriers * Connectomics has traditionally relied on electron microscopy (EM) because it offers nanometer-scale resolution, whereas standard light microscopy is limited by the diffraction limit of visible light. * Electron microscopes cost millions of dollars and require specialized training, restricting high-level neuroscience research to wealthy, large-scale institutions. * LICONN provides a more accessible alternative by utilizing standard light microscopy equipment already found in most life science laboratories. ## Advanced Tissue Expansion and Labeling * The project uses a specialized expansion microscopy protocol where brain tissue is embedded in hydrogels that absorb water and physically swell. * The technique employs three different hydrogels to create interweaving polymer networks that expand the tissue by 16 times in each dimension while preserving structural integrity. * A whole-protein labeling process is used to provide the necessary image contrast, allowing for the tracing of densely packed neurites and the detection of synapses. ## Automated Reconstruction and Validation * Google applied its established suite of machine learning and image analysis tools to automate the reconstruction of the expanded tissue samples. * The team verified the accuracy of the method by tracing approximately 0.5 meters of neurites within mouse hippocampus tissue, confirming results comparable to electron microscopy. * In a large-scale validation, the researchers provided an automated reconstruction of a volume of mouse cortex totaling nearly one million cubic microns. ## Integration of Molecular and Structural Data * One of LICONN’s primary advantages over electron microscopy is its ability to capture multiple light wavelengths simultaneously. * Researchers can use fluorescent markers to visualize specific proteins, neurotransmitters, and other molecules within the structural map. * This dual-layered approach allows scientists to align molecular information with physical neuronal pathways, offering new insights into how brain circuits drive behavior and cognition. LICONN represents a significant shift in neuroscience by democratizing high-resolution brain mapping. By replacing expensive hardware requirements with sophisticated chemical protocols and machine learning, this method enables a wider range of laboratories to contribute to the global effort of mapping the brain’s intricate wiring.

connectomicsaimachine-learningexpansion-microscopy+3
google

Improving brain models with ZAPBench (opens in new tab)

Google Research, in collaboration with HHMI Janelia and Harvard, has introduced ZAPBench, a first-of-its-kind whole-brain activity dataset and benchmark designed to improve the accuracy of brain activity models. Using the larval zebrafish as a model organism, the project provides single-cell resolution recordings of approximately 70,000 neurons, capturing nearly the entire vertebrate brain in action. This resource allows researchers to bridge the gap between structural connectomics and dynamic functional activity to better understand how neural wiring generates complex behavior. ## Whole-Brain Activity in Larval Zebrafish * The dataset focuses on the six-day-old larval zebrafish because it is small, transparent, and capable of complex behaviors like motor learning, hunting, and memory. * Researchers used light-sheet microscopy to scan the brain in 3D slices, recording two hours of continuous activity. * The fish were engineered with GCaMP, a genetically encoded calcium indicator that emits light when neurons fire, allowing for the visualization of real-time neural impulses. * To correlate neural activity with behavior, the fish were placed in a virtual reality environment where stimuli—such as shifting water currents and light changes—were projected around them while tail muscle activity was recorded via electrodes. ## The ZAPBench Framework * ZAPBench standardizes the evaluation of machine learning models in neuroscience, following the tradition of benchmarks in fields like computer vision and language modeling. * The benchmark provides a high-quality dataset of 70,000 neurons, whereas previous efforts in other species often covered less than 0.1% of the brain. * It challenges models to predict how neurons will respond to specific visual stimuli and behavioral patterns. * Initial results presented at ICLR 2025 demonstrate that while simple linear models provide a baseline, advanced architectures like Transformers and Convolutional Neural Networks (CNNs) significantly improve prediction accuracy. ## Integrating Structure and Function * While previous connectomics projects mapped physical neural connections, ZAPBench adds the "dynamic" layer of how those connections are used over time. * The team is currently generating a comprehensive structural connectome for the exact same specimen used in the activity recordings. * This dual approach will eventually allow scientists to investigate the direct relationship between precise physical wiring and the resulting patterns of neural activity across an entire vertebrate brain. By providing an open-source dataset and standardized benchmark, ZAPBench enables the global research community to develop and compare more sophisticated models of neural dynamics, potentially leading to breakthroughs in how we simulate and understand vertebrate cognition.

connectomicsaimachine-learningbenchmarking+5