Human Connectome Project: How does the nervous system communicate?
Neuroscientists have studied the anatomy and physiology of our body’s control center for generations. Neuroimaging for the longest time adopted a modular approach, believing one area of our brain is responsible for a specific function. However, recent research has begun exploring the communication that occurs between two or more individual regions of the brain to perform a given function. This understanding birthed the Human Connectome Project(HCP), which sought to map and visualize the multiple connections the neurons of the brain make through the central nervous system to communicate information, perform tasks, and navigate our complex world. Advancements in magnetic resonance imaging have allowed scientists to map macroscale connections of 1200+ healthy adults, laying the framework of underlying intricacies within the brain’s function to help in the future of rehabilitative medicine.
Cerebrum and Cerebellum pathways of the left hemisphere, achieved through HCP(Psychology Today)
T1 and T2 relaxation times(time between delivery of magnetic pulses and the image being taken) of fat and water and tissue proton densities were traditionally used as a cornerstone for mapping and imaging of brain tissue. After all, the comparable variation in concentration of fat and water within the brain’s regions(grey matter containing the most fat and cerebrospinal fluid containing the most water) made it extremely reliable. However, the problem came in the imaging of white matter. It was seen as a largely undifferentiated mass in most samples.
To combat the challenges posed by these original scanning methods, diffusion MRI(dMRI) began to be utilized as well as other scanning procedures such as MR spectroscopy and BOLD fMRI. These new methods have allowed scientists to utilize in vivo brain samples for imaging as water diffusion makes it possible to reconstruct neural fiber pathways. dMRI works by mapping and differentiating between the white matter regions of the brain by measuring the water diffused by direction. This estimation is conducted on a voxel(3D pixel) level followed by the use of tractography to measure the length of white matter fibers within voxels to map their connectivity. The most simple form of utilized tractography is deterministic streamline fiber tracking, which identifies white matter fibers of in vivo brains in a point by point fashion. However, this process purely provides a rough estimation of this connectivity because a voxel is measured on the scale of millimeters while neurons are measured on the scale of microns, oftentimes leading to inaccuracies in measured distances.
Once the brain structure has been mapped, graphs can be constructed, which define the nodes and connections said nodes make with one another, axonal bundles. These nodes make up the grey matter of the brain. These connections are analyzed for their clustering coefficient, C, which measures how connected the nodes are, and their path length, λ, which measures the distance between nodes and thus the overall efficiency of the network. For a long time, neural networks were often classed as having high C and high λ together(regular) or low C and low λ together(random). However, in 1998, a new network class was discovered; “small-world” networks were characterized with a high C and low λ value.
These network classes have many underlying implications. Results from two 2009 fMRI(detecting changes in cerebral blood flow) trials proved that brain cortex efficacy is directly correlated with one’s intelligence quota(IQ), in that a more efficient brain, or one with a shorter λ value, is one of a higher IQ. Furthermore, it was found that brain efficacy changes during development and overall decreases as one ages. fMRI trials additionally revealed that neural networks differed in patients with ADHD and those who were born blind. Carriers of the autism risk gene additionally showed having affected brain connectivity, which hints at the underlying disorder individuals with autism have neurologically.
Thus far, neuroscientists’ approach predominantly relies on mapping and collecting scans of many sampled brains. However, this is insufficient to fully understand the brain and its millions of networks. As the Human Connectome Project continues, scientists hope to gain a more comprehensive understanding of our brain’s white matter tracts as their functioning is paramount in the communication of information. So far, the project’s advancements have led to U.S. President Barack Obama launching the Brain Initiative, which allows for the application of our understanding of the brain’s network to develop reliable and more effective rehabilitative technologies. The neuroscience community hopes to gain more insight into the effect of neurological disorders such as autism, schizophrenia, and Alzheimer’s to develop more feasible therapeutic measures. The world of medicine will thrive through a better understanding of our brain’s white matter tracts through further advancements of the Human Connectome Project.
Sources:
Toga, A. W., Clark, K. A., Thompson, P. M., Shattuck, D. W., & Van Horn, J. D. (2012, July). Mapping the human connectome. Neurosurgery. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3555558/#R47
U.S. Department of Health and Human Services. (2022, November). Human Connectome Project (HCP). National Institute of Mental Health. https://www.nimh.nih.gov/research/research-funded-by-nimh/research-initiatives/human-connectome-project-hcp
