Millions of different circuits and channels make up the complex organism known as our brain. The interconnecting bundle of tangles can be changed and modified through different chemical reactions, enzymes and even outside forces. These connections crawl among each other like a spider crawler doing a Google search, finding just the right connections to interpret the signals.
“Much like Google crawls web links, a combination of microscopic platforms allows researchers to crawl through the individual connections composing a neural network,” according to a Harvard Medical School’s Department of Neurobiology researchers. They believe they may have found a technique that can unravel these complex circuits.
“The questions that such a technique enables us to address are too numerous even to list,” said Clay Reid, HMS professor of neurobiology and senior author of a paper reported in the March 10 edition of Nature.
The Cerebral cortex is believed to be the most important part of the human brain. It processes sensory images, reasoning and some believe even free will. Although the physical structure of the cerebral cortex’s anatomy has been known for the last 100 years, it has only been within the past ten, when imaging technology has allowed us to watch the brain from the inside as to how it processes information and works within a cortical circuit.
These images are excellent for showing us what the circuits do, but it still is not able to show us how it works.
Researchers in Reid’s lab have been studying the cerebral cortex for years, modifying and adapting ways they can observe the brain at work. They have been successful in isolating the neural activity of individual cells, and can watch them fire up when responding to stimulus. The coupe-de-gras, however, would be to be able to get inside a single cortical circuit and figure out how it is wired. The problem is, each of these circuits contains between 10,000 to 100,000 neurons, and they form over 10,000 interconnections. That would total over a billion connections, and all of them within a single circuit. “This is a radically hard problem to address,” Reid said.
By studying the pint-sized portion of a mouse’s brain that processes vision, the team conducted an experiment using electron microscopy. A mouse was injected with dyes that flashed whenever a specific neuron was fired and the findings were recorded with a laser-scanning microscope. They then tried to conduct the experiment on a larger scale to view the same neurons, along with hundreds of others, with nanometer resolution.
The team was able to record more than 3 million high-resolution images, and then sent them on to the Pittsburgh Supercomputing Center at Carnegie Mellon University. Researchers there put these images into 3-D. They were then able to painstakingly take 10 individual neurons and trace their partial wiring diagram. It seems neurons believed to be assigned to suppress brain activity were randomly wired, suppressing local groups of neurons all at once rather than picking and choosing. These results are important because many conditions concerning the brain are the result of inhibitions gone awry – such as epilepsy.
“This is just the iceberg’s tip,” said Reid. “Within ten years I’m convinced we’ll be imaging the activity of thousands of neurons in a living brain. In a visual circuit, we’ll interpret the data to reconstruct what an animal actually sees. By that time, with the anatomical imaging, we’ll also know how it’s all wired together.”
“How the brain works is one of the greatest mysteries in nature,” he added, “and this research presents a new and powerful way for us to explore that mystery.”
About the author:
Ron White is a two-time U.S.A. Memory Champion and memory training expert. As a memory keynote speaker he travels the world to speak before large groups or small company seminars, demonstrating his memory skills and teaching others how to improve their memory, and how important a good memory is in all phases of your life.
Source:
Science Daily – Web-Crawling the Brain: 3-D Nanoscale Model of Neural Circuit Created:http://www.sciencedaily.com/releases/2011/03/110309131928.htm
