Meeting At The Middle Eight.
Like jazz music, the human brain improvises while its rhythm section keeps up a steady beat. But when it comes to taking on intellectually challenging tasks, groups of neurons tune in to one another for a fraction of a second and harmonise, then go back to improvising, according to new research led by UC Berkeley.
These findings, reported in the journal Nature Neuroscience, could pave the way for more targeted treatments for people with brain disorders marked by fast, slow or chaotic brain waves, also known as neural oscillations.
Tracking the changing rhythms of the healthy human brain at work advances our understanding of such disorders as Parkinson’s disease, schizophrenia and even autism, which are characterized in part by offbeat brain rhythms. In jazz lingo, for example, bands of neurons in certain mental illnesses may be malfunctioning because they’re tuning in to blue notes, or playing double time or half time.
“The human brain has 86 billion or so neurons all trying to talk to each other in this incredibly messy, noisy and electro-chemical soup,” said study lead author Bradley Voytek. “Our results help explain the mechanism for how brain networks quickly come together and break apart as needed.”
Voytek and fellow researchers at UC Berkeley’s Helen Wills Neuroscience Institute measured electrical activity in the brains of cognitively healthy epilepsy patients. They found that, as the mental exercises became more demanding, theta waves at 4-8 Hertz or cycles per second synchronized within the brain’s frontal lobe, enabling it to connect with other brain regions, such as the motor cortex.
“In these brief moments of synchronization, quick communication occurs as the neurons between brain regions lock into these frequencies, and this measure is critical in a variety of disorders,” said Voytek, an assistant professor of cognitive science at UC San Diego who conducted the study as a postdoctoral fellow in neuroscience at UC Berkeley.
Previous experiments on animals have shown how brain waves control brain activity. This latest study is among the first to use electro-corticography, which places electrodes directly on the exposed surface of the brain to measure neural oscillations as people perform cognitively challenging tasks and show how these rhythms control communication between brain regions.
There are five types of brain wave frequencies, Gamma, Beta, Alpha, Theta and Delta and each are thought to play a different role. For example, Theta waves help coordinate neurons as we move around our environment and thus are key to processing spatial information.
In people with autism, the connection between Alpha waves and neural activity has been found to weaken when they process emotional images. Meanwhile, people with Parkinson’s disease show abnormally strong Beta waves in the motor cortex. This locks neurons into the wrong groove and inhibits movement. Fortunately, electrical deep brain stimulation can disrupt abnormally strong Beta waves in Parkinson’s and alleviate symptoms, Voytek said.
For the study, epilepsy patients viewed shapes of increasing complexity on a computer screen and were tasked with using different fingers (index or middle) to push a button depending on the shape, colour or texture of the shape. The exercise started out simply with participants hitting the button with, say, an index finger each time a square flashed on the screen. But it grew progressively more difficult as the shapes became more layered with colours and textures, and their fingers had to keep up.
As the tasks became more demanding, the oscillations kept up, coordinating more parts of the frontal lobe and synchronizing the information passing between those brain regions.
“The results revealed a delicate coordination in the brain’s code,” Voytek said. “Our neural orchestra may need no conductor, just brain waves sweeping through to briefly excite neurons, like millions of fans in a stadium doing ‘The Wave.'”
Not Smarter, Just More Efficient.
Elsbeth Stern, Professor for Research on Learning and Instruction at ETH (Eidgenössische Technische Hochschule) Zurich, states “when a more and a less intelligent person are given the same task, the more intelligent person requires less cortical activation to solve the task.”
Referred to as the neural efficiency hypothesis, experts consider that it ceased being a hypothesis some time ago and that there is ample evidence to support it.
While working on her doctoral thesis in Stern’s work group, Daniela Nussbaumer also found evidence of this effect for the first time in a group of people possessing above-average intelligence for tasks involving what is referred to as working memory. “We measured the electrical activity in the brains of university students, enabling us to identify differences in brain activity between people with slightly above-average and considerably above-average IQs,” explained Nussbaumer. Past studies conducted to identify the effect of neural efficiency have generally used groups of people that exhibit extreme variations in intelligence.
Psychologists define working intelligence as a person’s ability to associate memories with new information as well as to adapt to changing objectives by filtering out information that has become irrelevant. The frontal lobe plays a pivotal role in these processes. In order to test these abilities, the ETH researchers asked 80 student volunteers to solve tasks of varying complexity on a computer.
One task, for example, was to determine whether individual letters or faces were part of a selection of letters or faces that had been shown to the subjects immediately beforehand. An especially difficult task involved identifying letters and faces shown to the subjects during past runs of the test within a time limit. While the students were completing the tests, the researchers used electroencephalography (EEG) to measure their brain activity. For the results analysis, the researchers had the subjects take a conventional IQ test and then split them into two groups: one with slightly above-average IQs and another with well above-average IQs.
The researchers found no differences in brain activity in either group of subjects when they performed very easy or very difficult tasks. They did, however, see clear differences in the case of moderately difficult tasks. Stern attributes this to the fact that none of the subjects had any trouble whatsoever with the simple tasks and that the difficult tasks were cognitively demanding even for the highly intelligent subjects. In contrast, all subjects succeeded in solving the moderately difficult tasks, but the highly intelligent subjects required fewer resources to do so.
Stern uses the analogy of a more and less efficient car: “When both cars are travelling slowly, neither car consumes very much fuel. If the efficient car travels at maximum speed, it also consumes a lot of fuel. At moderate speeds, however, the differences in fuel consumption become significant.”
So is it possible to use EEG measurements to draw any direct conclusions about intelligence? Stern qualifies the findings: “If you want to learn something about intelligence, you have to perform a conventional IQ test, because these tests still provide the most reliable results,” she says. EEG and other brain activity readings are not precise enough to assess the intelligence of an individual. Still, using these methods may be an interesting way to study how different levels of intelligence are manifested in the brain.
The ETH researchers’ intelligence study also suggests that it is impossible to “exercise” working memory. This has been a controversial issue among scientists in recent years because of contradictory findings in different studies. If subjects practise a certain task for a prolonged period, they improve with time. As Stern and her peers have now shown in their study, people who have practiced certain tasks do not have any advantage over their unpracticed counterparts when confronted with new, yet similar tasks.