The goal of the Human Connectome Project is to understand the connections in the healthy human brain, so that doctors and researchers have a reference basis for identifying connection attacks that are related to brain diseases.
The Human Connectome Project (HCP) was launched in July 2009. It is part of a 5-year, 21.3 million euro NIH (National Institutes of Health) plan. The goal of the project is to:
- Provide a collection of neural data.
- Provide an interface that allows researchers to navigate data graphically.
- Discover new information about the human brain.
Hagmann, one of the project’s researchers, explains: “To understand a network, one must know its elements and their interconnections. The compound will increase our understanding of how functional brain states emerge from their underlying structural substrate, and provide new mechanical insights into how brain function is affected if this structural substrate is disrupted. ”
Before we continue, what is the human connectome? Simply put, it is a kind of map of the connections between the neurons of the brain. The aim of the project is thus to build a map that shows the brain’s network of connections at an anatomical and functional level.
In other words, to come to a detailed understanding of all brain circuits and their synapses.
The second goal of the project is to produce a dataset that will facilitate research on various brain diseases.
The goals of the Human Connectome Project
The National Institutes of Health Blueprint for Neuroscience Research is currently launching a $30 million project. It uses the latest neuroimaging technology to map the circuits of the healthy, human adult brain.
By systematically collecting neuroimaging data from hundreds of people, the Human Connectome Project will provide information about the brain connections that underlie brain function. It also opens up new avenues for neuroscience research.
Latest data and research
Currently, researchers have only identified one connectome: that of a nematode ( Caenorhabditis elegans ). The modest nervous system consists of 300 neurons. In the 1970s and 1980s, a team of researchers traced a map of its 7,000 internal connections.
The name of the card that we mentioned before is connectome. Clearly, humans are much more complex, with more than 100 billion neurons and 10,000 times more connections.
New research from the HCP team suggests that the organization of brain circuits is more like a Manhattan street map than the high-flying jumble of roads in London. In other words, the human neural network is also orderly and neat. It is not roundabout and tangled, as scientists used to think.
Various new findings based on neuroimaging data from HCP and psychological research show that differences in brain connections between individuals are a good predictor of behavior.
These researchers believe that these types of scans can be helpful in providing a more personal diagnosis and treatment to patients with mental illness.
Conclusions and observations on the Human Connectome Project
The brain continues to be a complex and mysterious organ. Although scientists are finding out more about the brain every day, there is still much we do not know. That is one of the reasons why HCP is so important.
The point is to use the best technology available to clarify brain function and neural connections. The hope is that this new information will help eradicate many mental illnesses.
Today, scientists know that many mental disorders, such as schizophrenia, are connectopathies. This means that the irregularity that causes the disorder is in the “wires” of the brain. If scientists can create a map of the human brain and understand its structural framework, they might be able to cure diseases like epilepsy.
If you are interested in learning more about HCP, visit this page to see an interactive viewer who interprets data from the connection matrix from the conference publication: Anatomical structural network analysis of human brain using partial correlations of gray matter volumes by Anand A. Joshi, Shantanu H. Joshi, Ivo D. Dinov, David W. Shattuck, Richard M. Leahy, and Arthur W. Toga.