Uncovering the brain's biggest secret - Melanie E. Peffer

553,211 views ・ 2021-02-08

TED-Ed


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In the late 1860s, scientists believed they were on the verge
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of uncovering the brain’s biggest secret.
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They already knew the brain controlled the body through electrical impulses.
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The question was, how did these signals travel through the body
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without changing or degrading?
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It seemed that perfectly transmitting these impulses
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would require them to travel uninterrupted along some kind of tissue.
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This idea, called reticular theory,
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imagined the nervous system as a massive web of tissue
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that physically connected every nerve cell in the body.
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Reticular theory captivated the field with its elegant simplicity.
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But soon, a young artist would cut through this conjecture,
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and sketch a bold new vision of how our brains work.
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60 years before reticular theory was born,
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developments in microscope technology
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revealed cells to be the building blocks of organic tissue.
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This finding was revolutionary,
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but early microscopes struggled to provide additional details.
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The technology was especially challenging for researchers studying the brain.
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Soft nervous tissue was delicate and difficult to work with.
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And even when researchers were able to get it under the microscope,
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the tissue was so densely packed it was impossible to see much.
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To improve their view,
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scientists began experimenting with special staining techniques
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designed to provide clarity through contrast.
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The most effective came courtesy of Camillo Golgi in 1873.
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First, Golgi hardened the brain tissue with potassium bichromate
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to prevent cells from deforming during handling.
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Then he doused the tissue in silver nitrate,
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which visibly accumulated in nerve cells.
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Known as the “black reaction,”
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Golgi’s Method finally allowed researchers to see the entire cell body
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of what would later be named the neuron.
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The stain even highlighted the fibrous branches
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that shot off from the cell in different directions.
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Images of these branches became hazy at the ends,
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making it difficult to determine exactly how they fit into the larger network.
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But Golgi concluded that these branches connected,
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forming a web of tissue comprising the entire nervous system.
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14 years later, a young scientist and aspiring artist
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named Santiago Ramón y Cajal began to build on Golgi’s work.
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While writing a book about microscopic imaging,
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he came across a picture of a cell treated with Golgi’s stain.
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Cajal was in awe of its exquisite detail— both as a scientist and an artist.
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He soon set out to improve Golgi’s stain even further
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and create more detailed references for his artwork.
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By staining the tissue twice in a specific time frame,
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Cajal found he could stain a greater number of neurons with better resolution.
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And what these new slides revealed would upend reticular theory—
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the branches reaching out from each nerve cell
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were not physically connected to any other tissue.
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So how were these individual cells transmitting electrical signals?
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By studying and sketching them countless times,
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Cajal developed a bold, new hypothesis.
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Instead of electrical signals traveling uninterrupted across a network of fibers,
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he proposed that signals were somehow jumping from cell to cell
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in a linear chain of activation.
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The idea that electrical signals could travel this way was completely unheard of
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when Cajal proposed it in 1889.
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However his massive collection of drawings supported his hypothesis from every angle.
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And in the mid-1900s, electron microscopy further supported this idea
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by revealing a membrane around each nerve cell
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keeping it separate from its neighbors.
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This formed the basis of the “neuron doctrine,”
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which proposed the brain’s tissue was made up of many discrete cells,
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instead of one connected tissue.
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The neuron doctrine laid the foundation for modern neuroscience,
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and allowed later researchers to discover that electrical impulses
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are constantly converted between chemical and electrical signals
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as they travel from neuron to neuron.
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Both Golgi and Cajal received the Nobel Prize
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for their separate, but shared discoveries,
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and researchers still apply their theories and methods today.
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In this way, their legacies remain connected as discrete elements
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in a vast network of knowledge.
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