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Human Connectome Project: mapping the human brain

 

Uddip Talukdar

Assistant Professor, Department of Psychiatry, Fakhruddin Ali Ahmed Medical College Hospital, Barpeta, Assam, India

 

 

Abstract

The brain can be considered a collection of connected system of neurons, and a comprehensive map of neuronal connections in the brain is called a ‘connectome’. Tracing out the connectome of a brain is helpful to understand the working of a brain, and would help us to target new areas for drug action, to formulate new modalities of treatment. Scientists started constructing the complete human connectome under Human Connectome Project (HCP). One important aspect of HCP was to develop improved MRI system to trace neuronal connection. One of the ambitious goals of HCP is to incorporate genetic data to compare with connectomes. HCP plans to incorporate not only imaging studies but also behavioural and genetic data. Behavioural data to be obtained in HCP would assess a wide range of human functions, including cognition, emotion, motor and sensory processes, and personality. This will enable comparison of brain-behaviour relationships.

 

Talukdar U. Human Connectome Project: mapping the human brain. Dysphrenia. 2014;5:83-6.

Keywords: Neurons. Genotype. Behaviour.

Correspondence: uddiptalukar@rediffmail.com

Received on 13 June 2014. Accepted on 15 June 2014.

 

 

Psychiatrists are well-versed with the concept of neuronal connections. Neurons in one part of the brain form multiple connections with neurons in other parts, and thus form one working sub-system in the brain. We still don’t know very well how the brain functions, but based on the knowledge of connections between neurons, we can assume that the whole brain is full of such connecting systems communicating with one another. The brain hence can be considered a collection of connected system of neurons.

A comprehensive map of neuronal connections in the brain is called a ‘connectome’.[1] The term was suggested independently and simultaneously by Dr. Olaf Sporns at Indiana University and Dr. Patric Hagmann at Lausanne University Hospital in 2005. Tracing out the connectome of a brain is helpful to understand the working of a brain, as the ‘wiring diagram’ or connectome would give us great insight into how neurons are connected to each other. The diagram would help us to target new areas for drug action, to formulate new modalities of treatment. But, tracing out the connectome of any brain is a very difficult task, though not impossible even with the technology we have today.

Scientists have successfully constructed the full connectome of one animal until now. It is a roundworm called Caenorhabditis elegans.[2,3] There are other works where peripheral nervous system connectome has been constructed, such as mouse retina and mouse primary visual cortex.[4,5] However, as psychiatrists we are more interested in having connectome of the human brain, and that is the ultimate goal of connectomics.

Constructing connectome of human brain is a great challenge. The roundworm C. elegans has 302 nos. of neurons and 5000 nos. of synapses compared to the 85 million neurons and 1014 - 1015 synapses in the human brain. Size of data accumulated for C. elegans connectome is 12 Tera Byte (TB).[5] So, the enormous volume of data to be unearthed for constructing human brain connectome is easily understandable.

Tracing a single connectome is another challenge. There are various tools to find out connection between two neurons. But, the limitation of such process becomes evident when one has to repeat the procedure for the 85 million neurons. The process would not only be extremely time consuming, but expensive too.

In spite of all the hurdles and difficulties, scientists started constructing the complete human connectome under Human Connectome Project (HCP). The HCP is a five-year project sponsored by United States’ primary bio-medical research agency National Institutes of Health (NIH). The project is a split between two consortia of research institutions. One consortium is led by Washington Univ-ersity in Saint Louis and the University of Minnesota (WU Minn Consortium) and the other is led by Harvard University, Massachusetts General Hospital and the University of California Los Angeles (MGH/Harvard-UCLA consortium).[6]

Dozens of researchers from Oxford University, Saint Louis University, Indiana University, University d’Annunzio in Chieti, Ernst Strungmann Institute, Warwick University, Advanced MRI Technologies, and the University of California at Berkeley has joined the project.

WU Minn consortium is mapping human brain connections in healthy adults using noninvasive neuroimaging techniques. Their target is to map macro-scale connectomes in each of 1,200 healthy adults—twin pairs and their siblings from 300 families. A grant of 30 million over five years has been announced by NIH to WU Minn consortium for the purpose in September 2010.[7,8] This work will yield some important information about brain connectivity, and its relationship to behaviour. It will also throw light on contribution of genetic and environmental factors on brain circuitry and behaviour.

MGH/Harvard-UCLA consortium has been granted 8.5 million dollars over five years. Their main focus is to optimise magnetic resonance imaging (MRI) technology for imaging the brain’s structural connections using diffusion MRI (dMRI), to have better spatial resolution, quality, and speed.[6]

https://file1.hpage.com/004238/12/bilder/human_connectome_project.jpg

Data acquisition

Both consortia employ dMRI to map brain’s fibrous long distance connections by observing the diffusive motion of water protons. Water diffusion patterns in various types of cells allow the detection of different types of tissues. Using this imaging method, the connecting part of neurons (white matter) can be seen in sharp relief. Individual neurons are not mapped in these diffusion MRIs, but the connections can be mapped very well.

Neurons in the human brain are difficult to trace out, because they are too large and too small at the same time. They are so small that without microscope they cannot be seen. However, at the same time they are so long that one microscopic field includes only a fraction of the entire length of some neurons. So, it’s impossible to trace the neurons by microscopic examination. One way of seeing the neurons is to trace those using indirect ways. MRI, particularly dMRI, can be used to trace neurons. One important aspect of HCP was to develop improved MRI system to trace neuronal connection. The project involved developing a 3T human MRI scanner equipped with 300 mT/m gradients. This is the strongest gradient ever built for an in vivo human MRI scanner.[8]

HCP uses four imaging modalities, all in a notably high resolution: structural MRI, resting-state fMRI (rfMRI), task fMRI (tfMRI), dMRI. All 1200 subjects will be scanned with all four modalities on a customised 3T scanner at Washington University (WashU). Two hundred of the same subjects would undergo all four modalities of scanning on a 7T scanner at the University of Minnesota (UMinn). Beside these imaging modalities a subset of 100 subjects will be studied at St. Louis University (SLU) using combined magnetic encephalography (MEG)/electroencephalography (EEG) (resting-state and task-evoked).[9]

HCP in its first two years also worked on developing new 7T scanner, a customised 3T scanner, and improved MR pulse sequences.[10] The project would also incorporate EEG and MEG imaging of the brain along with behavioural and genetic data.

Genetic analyses

One of the ambitious goals of HCP is to incorporate genetic data to compare with connectomes. To acquire genetic data blood sample from the subjects will be sent to the Rutgers University Cell and DNA Repository (RUCDR). Genetic analysis will be carried out in early 2015, after all Phase II subjects have completed in-person testing. De-indentified genetic and demographic data will be entered into the dbGAP database in accordance with NIH data-sharing policies. ConnectomeDB will enable summary data look-up by genotype.[10]

Data distribution

One of the key aspects of HCP is its promise to make the acquired data available openly to researchers worldwide. HCP is expected to generate about 1 Peta Byte (=1024 TB) of data. Such big amount of data needs special means to distribute and also would need tremendous processing power to analyse. The open availability of the data would foster research works by individuals and other academic institutions processing need would be distributed worldwide, reducing the time needed for analyses. For open availability of data, the HCP is developing a comprehensive informatics platform which has two interoperable components. The data management system of HCP is called ConnectomeDB; and a software suite Connectome Workbench (CWB) would provide visualisation and discovery capabilities.[11]

The data providers and visualisation informatics of the HCP are important aspects of the project because HCP plans to incorporate not only imaging studies but also behavioural and genetic data.

Behavioural data to be obtained in HCP would assess a wide range of human functions, including cognition, emotion, motor and sensory processes, and personality. The NIH Toolbox for Assessment of Neurological and Behavioral function would be the core battery for assessment of these functions. This will enable comparison of brain-behaviour relationships.[12]

Results until now

The release results of HCP were started with the first quarterly (Q1) data release (March 2013). The dataset is available for download and use at the project website http://www.humanconnectome.org/. The first set included data from rfMRI, dMRI, tfMRI.

In March 2014, the first MEG data were released. The dataset included MEG scans from 14 healthy adults (all members of monozygotic twin pairs) collected at rest (rMEG) and during three tasks (tMEG) that measure sensory, motor, and cognitive task performance.[13]

A bug-fixed and updated dataset of Q1-Q3 HCP data were released in March 2014. This updated dataset includes the first release of volume-smoothed tfMRI analysis data besides the release of the data patch.[14]

In June 5, 2014, the third release included the 500 subjects data that consists of multimodal MRI data collected from healthy young adults scanned from the project inception to January 2014. Fourteen subjects have been released with anatomical, resting state and task MEG data. This set included behavioural and demographic data on 550 subjects.[15]

New data are being released regularly by the HCP, and available for research. But the question now arises how valuable are these data for gaining new knowledge? In other terms, do the vast amount of expenses and time given is fruitful enough? One thing is sure, when we go through the scanned images in the HCP images one feels awestruck at the wonderfully detailed images generated. The images also look wonderfully aesthetic. But, we all know our expectations do not demand merely pretty pictures, but some solid groundbreaking information. What until now HCP has shown pretty clearly is that brain connections run in a pretty organised fashion, similar to the way cloth is weaved. Bundles of fibres run perpendicular to each other —some going from front to back while other connections go from the inside out. But, is this enough for a $40 million project?

It’s too early to say what these data would yield in future. HCP is now working mainly on getting information. The analyses and insight about the data are yet to be obtained. Some researchers have already doubted the usability of these data, as according to them what until now HCP has released are not exactly new, but showing us in a ‘cool’ way what we already knew from post-mortem studies of the brain.[16,17] However, the doubts of these researchers seem short-sighted. The data released so far by HCP only includes fractions of the actual dataset. Moreover, the wisdom to be had from these data is not the data itself, but how we interpret and analyse them. It won’t be easy to interconnect all the information and come to meaningful insight.

The biggest positive aspect of HCP and the data acquired by them is not immediate results. That the HCP data would be there for us to refer to when we need them is the biggest advantage. It’s like having a roadmap of the street without knowing which road goes where, but since we would have the roadmap, later on we would be able to guide our way through these roads and eventually find out where all these road lead.

Source of support: Nil. Declaration of interest: None.

References

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12. Gershon RC, Cella D, Fox NA, Havlik RJ, Hendrie HC, Wagster MV. Assessment of neurological and behavioural function: the NIH Toolbox. Lancet Neurol. 2010;9:138-9.

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14. NIH Blueprint for Neuroscience Research: the Human Connectome Project. HCP Data Update: March 2014 Patch Release [Internet]. 2014 Mar 25 [cited 2014 Jun 13]. Available from:http://www.humanconnectome.org/documentation/updates/march-2014-patch-release.html

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