Brain's 'Radio Stations' Have Much to Tell Scientists

Like listeners adjusting a high-tech radio, scientists at Washington University School of Medicine in St. Louis have tuned in to precise frequencies of brain activity to unleash new insights into how the brain works.

"Analysis of brain function normally focuses on where brain activity happens and when," says Eric C. Leuthardt, MD. "What we've found is that the wavelength of the activity provides a third major branch of understanding brain physiology."

Researchers used electrocorticography, a technique for monitoring the brain with a grid of electrodes temporarily implanted directly on the brain's surface. Clinically, Leuthardt and other neurosurgeons use this approach to identify the source of persistent, medication-resistant seizures in patients and to map those regions for surgical removal. With the patient's permission, scientists can also use the electrode grid to experimentally monitor a much larger spectrum of brain activity than they can via conventional brainwave monitoring.

Scientists normally measure brainwaves with a process called electroencephalography (EEG), which places electrodes on the scalp. Brainwaves are produced by many neurons firing at the same time; how often that firing occurs determines the activity's frequency or wavelength, which is measured in hertz, or cycles per second. Neurologists have used EEG to monitor consciousness in patients with traumatic injuries, and in studies of epilepsy and sleep.

In contrast to EEG, electrocorticography records brainwave data directly from the brain's surface.

"We get better signals and can much more precisely determine where those signals come from, down to about one centimeter," Leuthardt, assistant professor of neurosurgery, of neurobiology and of biomedical engineering, says. "Also, EEG can only monitor frequencies up to 40 hertz, but with electrocorticography we can monitor activity up to 500 hertz. That really gives us a unique opportunity to study the complete physiology of brain activity."

Leuthardt and his colleagues have used the grids to watch consciousness fade under surgical anesthesia and return when the anesthesia wears off. They found each frequency gave different information on how different circuits changed with the loss of consciousness, according to Leuthardt.

"Certain networks of brain activity at very slow frequencies did not change at all regardless of how deep under anesthesia the patient was," Leuthardt says. "Certain relationships between high and low frequencies of brain activity also did not change, and we speculate that may be related to some of the memory circuits."

Their results also showed a series of changes that occurred in a specific order during loss of consciousness and then repeated in reverse order as consciousness returned. Activity in a frequency region known as the gamma band, which is thought to be a manifestation of neurons sending messages to other nearby neurons, dropped and returned as patients lost and regained consciousness.

The results appeared in December in the Proceedings of the National Academy of Sciences.

In another paper that will publish Feb. 9 in The Journal of Neuroscience, Leuthardt and his colleagues have shown that the wavelength of brain signals in a particular region can be used to determine what function that region is performing at that time. They analyzed brain activity by focusing on data from a single electrode positioned over a number of different regions involved in speech. Researchers could use higher-frequency bands of activity in this brain area to tell whether patients:

• had heard a word or seen a word
• were preparing to say a word they had heard or a word they had seen
• were saying a word they had heard or a word they had seen.

"We've historically lumped the frequencies of brain activity that we used in this study into one phenomenon, but our findings show that there is true diversity and non-uniformity to these frequencies," he says. "We can obtain a much more powerful ability to decode brain activity and cognitive intention by using electrocorticography to analyze these frequencies."
Source: Daily Science

Same Face May Look Male or Female, Depending on Where It Appears in a Person's Field of View

Neuroscientists at MIT and Harvard have made the surprising discovery that the brain sees some faces as male when they appear in one area of a person's field of view, but female when they appear in a different location.

The findings challenge a longstanding tenet of neuroscience -- that how the brain sees an object should not depend on where the object is located relative to the observer, says Arash Afraz, a postdoctoral associate at MIT's McGovern Institute for Brain Research and lead author of a new paper on the work.

"It's the kind of thing you would not predict -- that you would look at two identical faces and think they look different," says Afraz. He and two colleagues from Harvard, Patrick Cavanagh and Maryam Vaziri Pashkam, described their findings in the Nov. 24 online edition of the journal Current Biology.

In the real world, the brain's inconsistency in assigning gender to faces isn't noticeable, because there are so many other clues: hair and clothing, for example. But when people view computer-generated faces, stripped of all other gender-identifying features, a pattern of biases, based on location of the face, emerges.

The researchers showed subjects a random series of faces, ranging along a spectrum of very male to very female, and asked them to classify the faces by gender. For the more androgynous faces, subjects rated the same faces as male or female, depending on where they appeared.

Study participants were told to fix their gaze at the center of the screen, as faces were flashed elsewhere on the screen for 50 milliseconds each. Assuming that the subjects sat about 22 inches from the monitor, the faces appeared to be about three-quarters of an inch tall.

The patterns of male and female biases were different for different people. That is, some people judged androgynous faces as female every time they appeared in the upper right corner, while others judged faces in that same location as male. Subjects also showed biases when judging the age of faces, but the pattern for age bias was independent from the pattern for gender bias in each individual.

Sample size

Afraz believes this inconsistency in identifying genders is due to a sampling bias, which can also be seen in statistical tools such as polls. For example, if you surveyed 1,000 Bostonians, asking if they were Democrats or Republicans, you would probably get a fairly accurate representation of these percentages in the city as a whole, because the sample size is so large. However, if you took a much smaller sample, perhaps five people who live across the street from you, you might get 100 percent Democrats, or 100 percent Republicans. "You wouldn't have any consistency, because your sample is too small," says Afraz.

He believes the same thing happens in the brain. In the visual cortex, where images are processed, cells are grouped by which part of the visual scene they analyze. Within each of those groups, there is probably a relatively small number of neurons devoted to interpreting gender of faces. The smaller the image, the fewer cells are activated, so cells that respond to female faces may dominate. In a different part of the visual cortex, cells that respond to male faces may dominate.

"It's all a matter of undersampling," says Afraz.

Michael Tarr, codirector of the Center for the Neural Basis of Cognition at Carnegie Mellon University, says the findings add to the growing evidence that the brain is not always consistent in how it perceives objects under different circumstances. He adds that the study leaves unanswered the question of why each person develops different bias patterns. "Is it just noise within the system, or is some other kind of learning occurring that they haven't figured out yet?" asks Tarr, who was not involved in the research. "That's really the fascinating question."