A groundbreaking Harvard and Google project has created the most detailed map of the human brain’s connections to date, focusing on a cubic millimeter of cerebral cortex taken from a patient during epilepsy surgery in 2014. For more than a decade, a team of biologists and machine learning experts have painstakingly analyzed this tiny sample of tissue, which contains about 57,000 cells and 150 million synapses. Their work represents a significant advance in brain science, providing an unprecedented level of detail in understanding the wiring of the brain.
Advanced Mapping Techniques
The process began by staining brain tissue with heavy metals, which bind to lipid membranes in cells, making them visible under an electron microscope. The tissue was then embedded in resin and cut into incredibly thin sections, each just 34 nanometers thick. The technique transformed a complex 3D problem into a more manageable 2D problem, resulting in a colossal 1.4 petabytes of data. To assemble these 2D slices into a coherent 3D model, the team used machine-learning algorithms developed in partnership with Google. This involved aligning the images and automatically segmenting different cell types, although manual adjustments were required to refine the accuracy of these segments.
Conclusions and challenges
The resulting map reveals a wealth of information about the brain’s cellular structure. It identified neurons with more than 50 synapses, previously overlooked and potentially crucial to understanding cortical processing. But the project faces challenges, including manually reviewing the vast amount of data to correct segmentation errors. Some cells, such as unidentified ovoid structures and tangled cells, remain enigmatic. These abnormalities could provide new insights but require further study.
Implications for future research
The brain map is now publicly available, opening up new avenues for research. It promises to deepen our understanding of mental health disorders such as schizophrenia and could inspire improvements in artificial intelligence by mimicking brain function. Future projects include extending this research to whole mouse brains and additional human brain regions, potentially leading to further breakthroughs in neuroscience and related fields.
