Button to scroll to the top of the page.

News

From the College of Natural Sciences
Font size: +

Scientists Estimate Memory Capacity Based on Sizes of Brain Synapses

Scientists Estimate Memory Capacity Based on Sizes of Brain Synapses

Neuroscientists from The University of Texas at Austin and the Salk Institute have discovered that connections between brain cells, called synapses, can be grouped into more discrete sizes than was previously thought, and these discrete sizes are thought to predict different functional states.

Based on the new insights, they estimate that a single human brain might potentially store a petabyte of information, roughly the size of the entire World Wide Web. The new study appeared in the journal eLife.

To create the data set, Kristen Harris, co-senior author of the study and professor of neuroscience at UT Austin and her colleagues, prepared tissue from a rat hippocampus, a brain region associated with learning and memory as it is in humans. They sectioned it very thinly to visualize serial sections in the electron microscope. 

When scientists reconstructed structures in a piece of brain tissue from the hippocampus, they found that, rather than just 3 sizes of synapses, there are actually 26 discrete sizes that can change over a span of a few minutes, meaning that the brain might have a far greater capacity for storing information than previously thought. Click on the image to see a video about the research. Credit: Salk Institute.

"Then, over the course of several years, we used our computer software to reconstruct in 3D every structural process, and the roughly 500 synapses found in a tiny volume of this brain tissue the size of a single red blood cell," says Harris.

Synapses transmit signals between neurons. Larger synapses—with more surface area and vesicles of neurotransmitters—are stronger, making them more likely to activate their surrounding neurons (i.e., successfully transmit their signals from one neuron to the next) than smaller synapses. In this dataset, the researchers occasionally found places where two neurons were connected to each other through not just one synapse, but two. These synaptically coupled pairs of synapses provided a natural experiment to test whether synapses with the same activation histories have the same size.

Salk Institute scientists, led by professor of computational neurobiology Terry Sejnowski, analyzed the UT Austin data set using a computer algorithm they developed to quantify precisely the connectivity, shapes, volumes and surface area at the nanometer scale. Only 10 percent of synapses in the volume were found to be synaptically coupled.

"We were amazed to find that the difference in the sizes of the coupled pairs of synapses were very small, on average, only about eight percent different in size," notes Tom Bartol, a Salk scientist and first author on the paper. "No one thought it would be such a small difference."

Application of the findings to the whole synapse distribution resulted in 26 sizes of synapses. In computer terms, this value corresponds to about 4.7 "bits" of information per synapse.

"The implications of what we found are far-reaching," adds Sejnowski. "Hidden under the apparent chaos and messiness of the brain is an underlying precision to the size and shapes of synapses that was hidden from us."

Harris adds that the findings suggest more questions to explore, for example, whether similar rules apply for synapses in other regions of the brain and how those rules differ during development and as synapses change during the initial stages of learning.

In a computational reconstruction of brain tissue in the hippocampus, scientists found the unusual occurrence of two synapses from the axon of one neuron (translucent black strip) forming onto two spines on the same dendrite of a second neuron (yellow). Separate terminals from one neuron’s axon are shown in synaptic contact with two spines (arrows) on the same dendrite of a second neuron in the hippocampus. The spine head volumes, synaptic contact areas (red), neck diameters (gray) and number of presynaptic vesicles (white spheres) of these two synapses are almost identical. Credit: Salk Institute/University of Texas at Austin.

To reconstruct one whole human brain at this nanoscale with existing tools, scientists estimate it would take 8 trillion years of manual labor. From an engineering perspective, the data sets provide 'ground truth' for computer scientists to create automatic reconstruction tools, needed to test the new hypotheses in larger data sets. Hence, the original images and reconstructed data sets were recently published and shared in a format that is publically accessible at the Open Connectome Project website.

"This study, exemplary in its combination of experimental and theoretical approaches, shows that hidden in the jungle of neural connections there are striking regularities in the sizes that synapses assume," remarks Ila Fiete, associate professor of neuroscience at UT Austin. "Like any truly unexpected finding, it raises many more questions than it answers."

Synapses are still a mystery, though their dysfunction can cause a range of neurological diseases. Harris's group has expanded the data to include other brain regions and tissue from experiments where synapses have been exposed to a variety of conditions, mimicking what happens during learning. Students in her UT Austin classes are being engaged in cuttingedge research using these new data in search of answers about the generality of the underlying rules governing synapse structure and function, and how these rules may be disrupted by disease.

Other authors on the paper were Cailey Bromer of the Salk Institute; Justin Kinney of the McGovern Institute for Brain Research; and Michael A. Chirillo and Jennifer N. Bourne of UT Austin.

The work was supported by the National Institutes of Health and the Howard Hughes Medical Institute.

Save the Dates
Spring Events and Lectures Not to Miss

Comments

 
No comments made yet. Be the first to submit a comment
Already Registered? Login Here
Guest
Wednesday, 25 December 2024

Captcha Image