Google Maps and the road to simpler images of the human brain

Google Maps. Most people know this web-mapping application in its traditional form, giving Internet users around the world access to street maps, route planners and, more recently, Street View. But at Brown University, USA, a team of researchers, funded by the National Institutes of Health, have put Google Maps to a very interesting and very unusual use: creating an Internet-based platform to access 2D images of the neural circuitry in the human brain.

Mapping the brain

The human brain is the centre of the nervous system, containing 100 billion neurons, all passing messages to one another via up to 1000 trillion synaptic connections. Brain mapping, a set of neuroscience techniques used to gain a better understanding of all these neurons and connections, sets out to create a spatial representation of the brain by collecting images (neuroimaging) from a number of different sources. These images are then transformed into data and analysed to gain a better understanding of the brain.

A wealth of information is constantly being gathered on the structure, anatomy, physiology, perfusion, function and phenotypes of both healthy and diseased brains, which can be used in a number of different ways. Some researchers and professionals use it to watch what the brain does as it performs certain tasks, e.g. being able to identify an object, or understanding what someone is saying. Others use it to understand the impact of environmental factors on the brain as a whole, for example, the effects of various drugs, aging and learning. This research also contributes to the understanding of the brain when it is affected by illness or disease, for example, autism, clinical depression or schizophrenia.

A large part of the process of mapping the brain is neuroimaging, a group of techniques used to provide structural imaging and functional imaging of the brain. Structural imaging is used to show large-scale intracranial disease such as tumours or brain injury. Functional imaging works on a finer scale, diagnosing metabolic diseases and lesions. Functional imaging is also used for neurological and clinical psychological research, as well as for building brain-computer interfaces. A number of these techniques (PET scans, SPECT scans and MRIs) enable researchers and scientists to build a 3D computer model of the brain, allowing for better study, diagnosis and therapy.

The growth of an industry

3D medical imaging (including neuroimaging) has been around since the 1970s, and is a huge industry. Global Industry Analysts, Inc. estimates that spending in this market will reach USD3.5 billion by 2015, fuelled by an ageing population, a rise in the incidence of critical diseases, increasing applications and technological advancements, as well as a rise in demand from developing countries.

3D medical imaging now has a wide reach within the healthcare industry, shaping a number of different disciplines, including:

• research and development within biomedical engineering (instrumentation, image acquisition, modelling and quantification)
• research within medical physics into the application and interpretation of images
• Various relevant medical sub-disciplines (cardiology, neuroscience, etc.)

These techniques, initially developed for use in healthcare, are also now reaching into other industries. For example, tools developed for medical imaging are now being used in airport security for passenger screening and within the food and pharmaceutical industries for non-invasive, high quality checks of products.

3D and 2D: detail v. simplicity

In an industry that seems to be moving away from 2D images at an ever-increasing rate, what then are the benefits of going back to them? Going from an intricate, detailed, sophisticated model of the brain (in this example), to an image akin to something you would find on your Internet browser? Brown University’s reasoning is that the 3D version is too complex; there is simply too much information to make the model useful. They are not, however, discounting the 3D image. In fact, users of their software can toggle between the 2D and 3D images of the brain to see both views. What they are saying is that, sometimes, “there can be too much detail; important elements can go unnoticed.”

In developing a 2D image, the researchers’ aim is, first and foremost, simplicity: to take all the information of the 3D model and make it easy to use. The bundles of nerve cells that link each other in the brain are so intricate and interwoven that users often cannot follow them. Transforming the 3D image into the 2D image allows for a simplified representation of the neural pathways. In particular, researchers were interested in tracking myelin, an insulating layer surrounding the part of neurons that transmits signals and is essential for the proper functioning of the brain and the rest of the nervous system. A lack of myelin (through loss or imperfect growth), is known to cause diseases such as multiple sclerosis and leukodystrophy. Brown University are hoping that along with a better understanding of these diseases through their simplified images, they will also help identify pathologies such as autism, which is being increasingly linked to myelin by neuroscientists.

The benefits of a simple, collaborative tool

2D images of the brain are useful in a number of ways. What has made 2D images more useful is the ability to view them on the Internet, via the Google Maps platform. Researchers found that the use of this web-interface allowed for easy collaboration, as well as allowing easy access and quick exploration of the data. Being able to work with colleagues at a distance, using an interface that adopts a “geographical digital-maps framework with associated labels, metrics and statistics”, while still linking to a more in-depth 3D model, can only lead to improvements in the way the brain (and other parts of the body) is understood, as well as improving the diagnosis and treatment of a number of illnesses and diseases.

While 3D imaging will more than likely remain the most used and most useful tool for the majority of the medical community, 2D imaging should not be completely written off. In fact, in a number of cases, this new form of 2D image may be the better option. This is particularly true where a 3D model is also available for comparison, and there is a platform available that allows for collaboration and ease of use. Companies that research and develop hardware and software for medical imaging should take note. It may be that they can gain a market edge by working with researchers and scientists to develop simplified, collaborative, user-friendly versions of complicated models, especially where an illness or disease is only beginning to be understood.