To help them in their work, scientists have created a computer model of the brain. Unsurprising as that might seem, their virtual model does something rather unique: it daydreams just like a human being. With their model, the scientists hope to explain why certain portions of the brain work together when a person is mentally idle. The ultimate aim of their work, which is funded in part by the Brain Network Recovery Group, is to help doctors better diagnose and treat brain injuries.

Synchronicity

In the late 1990s and early 2000s, scientists first recognized that the brain stays busy even when it's not engaged in mental tasks. What's more, the brain fluctuations when a person is at rest (daydreaming, for instance) are not random as one might expect; instead, the fluctuations are structured in spatial patterns of related activity across different brain areas. The fact is the activity levels rise and fall in sync.

To investigate how this resting-state functional connectivity emerges, the researchers wanted to create a less complex, though realistic description of the relevant brain dynamics. Working globally, they developed and tested a virtual model of the brain at Washington University School of Medicine in St. Louis, Universitat Pompeu Fabra in Barcelona, and several other European universities. The model they created helped them to see how the brain's anatomical structure contributes to the creation and maintenance of resting state networks.

"We can give our model lesions like those we see in stroke or brain cancer, disabling groups of virtual cells to see how brain function is affected," said senior author Maurizio Corbetta, M.D., of Washington University School of Medicine. "We can also test ways to push the patterns of activity back to normal."

Their early use of the virtual model took a whole cluster of computers a full 26 hours to simulate a mere 20 minutes of human brain activity. Eventually, the researchers simplified the mathematics to run the model on a single computer. "This simpler whole brain model allows us to test a number of different hypotheses on how the structural connections generate dynamics of brain function at rest and during tasks, and how brain damage affects brain dynamics and cognitive function," said Corbetta.

Such elaborate effort to understand the brain raises a key question: how have scientists studied the brain in the past? The complete answer might surprise you.

Machines

As with all areas of human research, scientists first learned about the brain by dissecting it. Ancient Egyptians thought the brain was a secondary organ, without as much significance as the heart, then considered to be the seat of intellect. By the Renaissance, though, physicians had begun to dissect the brain and name its parts. In so doing, their esteem for the previously disregarded organ grew.

Today, of course, scientists mainly study the living brain and they do so by using neuroimaging technologies. For example, an electroencephalogram (EEG) uses small, flat metal discs (electrodes) attached to the scalp to detect electrical activity in the brain. (The brain generates tiny electrical signals whenever it's active.) A painless procedure, an EEG records any brain activity as wavy lines. An EEG is one of the main diagnostic tools for epilepsy and often is the first test, followed by others, when diagnosing most brain disorders.

Positron emission tomography (PET) detects the radioactive energy given off during a scan, when a patient is injected with a dose of radioactive compound, which is carried to and absorbed by the brain. The PET scan generates data, which are converted into 3-D images. Doctors use PET scans to detect tumors, changes in the brain that may cause seizures, and disorders of the brain, such as Parkinson's disease.

Magnetic resonance imaging (MRI) detects shifts in the blood flow to and within the brain and so maps the activity of the brain. Commonly, an MRI is used to show which parts of the brain are active during thoughts or movement. It is frequently used to discover damage by a stroke or disease, such as Alzheimer's.

Magnetoencephalography (MEG) is another type of scan that relies on the same basic principle as EEG. During a MEG scan, a subject's head is placed within a "helmet" of SQUIDs (superconducting quantum interference devices); this helmet records magnetic fields produced by electrical currents occurring naturally in the brain. A MEG, then, does what few other technologies can: it allows researchers to see brain activity almost in real-time.

Along with neuroimaging, scientists also use the oldest tool of all: dumb luck.

Accidents

Every now and then someone has an injury that allows scientists to learn extensively about the brain. A famous case occurred in 1848 to Phineas Gage, 25, a supervisor for the Rutland and Burlington Railroad. While at work, an explosion occurred that drove a rod through his left check and out the top of his head. He survived the accident but records say his personality changed from pleasant to generally irritable. His accident led scientists to believe that various parts of the brain control different parts of who we are.

Both a neurologist and psychiatrist, Oliver Sacks worked with patients who contracted encephalitic lethargica or sleeping-sickness during the epidemic just after World War I. Frozen in a sleep that lasted decades, countless men and women were assumed to be hopeless until 1969, when Sacks gave them what was considered a 'miracle drug' at the time: L-DOPA. Able to cross the protective blood-brain barrier, L-DOPA acts as a metabolic precursor and is converted to dopamine in the brain. (Today, it is used to treat Parkinson's disease.) The drug had an astonishing, awakening effect for these individuals, and from this experiment, Sacks was able to derive an understanding of personality and brain function.

Possibly the most astonishing story of accident and experimentation comes from Jill Bolte Taylor. A neuroanatomist, Taylor had the unique misfortune — she describes it as an 'opportunity' — to study her own stroke as it happened. The video below explains everything.

Source: Deco G, Ponce-Alvarez A, Mantini D, Romani GL, Hagmann P, Corbetta M. Resting-State Functional Connectivity Emerges from Structurally and Dynamically Shaped Slow Linear Fluctuations. The Journal of Neuroscience. 2013.