Tag Archives: fMRI

MRI study shows how Beatboxing really works — and it’s crazy

Beatboxing is an art form in which performers create percussive sounds using nothing but their vocal tract. Now, a team of scientists is using a real-time MRI machine to see how beatboxers create their magic.

Beatboxing techniques have been used as early as the 19th century, but true beatboxing is derived from the mimicry of early drum machines. Nowadays, beatboxing is mostly associated with hip-hop, though it is not limited to it.

Several studies have been carried out on beatboxers, but in the past, they’ve consisted of only one beatboxer with a particular native language. The new study looked at several beatboxers of different ages and genders and with different native languages.

The team used real-time MRI to observe the vocal tracts of beatboxers just before they make a sound to see how those movements differ from the movements associated with speech. Using real-time data offers a dynamic view of the entire vocal tract, at a high enough resolution to observe the movement and coordination of the different biological elements.

“Beatboxers may learn something different in preparing to make a sound than they do when they’re talking,” said Timothy Greer, a doctoral candidate at the University of Southern California. “Using real-time MRI allows us to investigate the difference in the production of music and language and to see how the mind parses these different modalities.”

Three different snare drum effects were demonstrated by the subject, each produced with different articulatory and airstream mechanisms. The technical names are: a click, an ejective affricate, and a pulmonic egressive dorsal stop-fricative sequence. Image credits: Timothy Greer.

The results surprised even Greer: beatboxers use movements not present in any known languages to produce a wide variety of sounds. Essentially, it’s a completely different way of moving the vocal tract.

“We found that beatboxers can create sounds that are not seen in any language. They have an acrobatic ability to put together all these different sounds,” said Greer. “They can hear a sound like a snare drum and they can figure out what they need to do with their mouth to recreate it.”

“As far as we know, some of the articulations that beatboxers can use are not attested in any language,” He added for ZME Science.

However, this type of study remains challenging, because existing algorithms to analyze the vocal tract movement are based on existing languages — and since beatboxing doesn’t seem to resemble any of them, different and new algorithms are needed.

“The vocal tract is amazing but it’s also incredibly complex. We need to keep creating better computer algorithms to understand how it all works together,” said Greer.

This is only the start, however — the group that acquired the data is already working on algorithms to analyze beatboxing is already working on ways to analyze and better understand this unusual form of art.

“The same group that collected the real-time MRI beatboxing videos–the Speech Production and kNowledge (SPAN) group at USC–has developed a set of region-of-interest (ROI) and segmentation algorithms that can be used on rtMRI data to determine how the different components of the vocal tract move in relation to each other. We are using these tools on our rtMRI data now to get more quantitative observations about beatboxing.”

However, this field of research is not only about beatboxing itself (though it will be a valuable resource for the community) — it can teach us a lot about speech patterns, and even shed some light on our vocal tract anatomy.

“This research has practical and theoretical benefits. Practically, this is one of the first looks at how the vocal tract moves during beatboxing; these videos offer the beatboxing community a tool to use in their art for teaching, exploration, and innovation. This work also benefits linguistic theory because it shows what the vocal tract can do when stretched to its limits. It addresses questions like “why do some sounds exist in speech, but not others?” and “which speech patterns exist only in language, and which speech patterns are grounded in broader cognitive capacities?”.”

Greer will present his findings at the Acoustical Society of America’s 176th Meeting.

MRI successfully predicts suicidality 9 out of 10 times

It’s an impressive success for the algorithm, but it’s not exactly clear how to best apply these findings. Researchers successfully identified people with suicidal tendencies with 91% success, using only 6 words: Death, Cruelty, Trouble, Carefree, Good, Praise.

Credits: Adam et al, 2017.

Tackling suicide is never easy and straightforward. When it comes to identifying these tendencies, researchers and medics typically ask patients. But studies have shown that 80% of patients who committed suicide deny these ideas up until the last moment.

With that in mind, researchers devised a test to objectively assess suicidal plans. They carried out a trial with 17 adults with suicidal ideation and 17 control subjects. The participants had their brain scanned with an fMRI while they listened to words like ‘death’ and ‘cruelty’. Researchers then employed a machine-learning algorithm to identify patterns in the participants’ brains as they heard the words. The scientists were able to successfully detect 15 of the 17 suicidal brains and 16 of the 17 controls.

However, there are significant caveats to this study, and we shouldn’t expect it in hospitals anytime soon, said lead researchers  Dr. Marcel Just told Perry Wilson at The Methods Man. The first problem is money — fMRIs are expensive and there’s usually a huge queue for them. Having stressed and potentially suicidal people lie still in a small, dark and noisy machine is certainly less than ideal.

“It would be nice to see if we could possibly do this using EEG, if we could assess the thought alterations with EEG. It would be enormously cheaper. More widely used.”

Secondly, the algorithm was able to perform so well is because patients were open about their tendencies in the first place. If they wanted to hide these thoughts, as you’d expect in a real-life scenario, they could almost certainly do so.

“If somebody didn’t want others to know what they are thinking, they can certainly block that method. They can not coorperate. I don’t think we have a way to get at people’s thoughts against their will.”

However, as pointed out by Wilson, today’s expensive fMRI is tomorrow’s EEG, and next year’s iPhone app. At the rate at which technology continues to develop, a similar approach could soon be incorporated into some sort of precision medicine, and it gives us another glimpse into how our thoughts cluster around words and ideas.

Journal Reference: Marcel Adam Just, Lisa Pan, Vladimir L. Cherkassky, Dana L. McMakin, Christine Cha, Matthew K. Nock & David Brent. Machine learning of neural representations of suicide and emotion concepts identifies suicidal youth. doi:10.1038/s41562-017-0234-y

Baby brain scans and machine learning algorithm can predict autism

Scientists have developed a surprisingly accurate mechanism of predicting autism — using a single brain scan.

The findings indicate that autism has a biological component. Image credits: Carolina Institute for Developmental Disabilities.

Predicting the unpredictable

There’s still a lot of disagreement and debate regarding the nature and causes of autism. We do know that it is a spectrum disorder, with all autistic people suffering from some level of problems, but the severity and nature of these problems differ greatly. Autism is caused by a combination of genetic and environmental factors, with some instances being associated with certain pregnancy infections or drug abuse, and others having no clear source. The diagnosis of autism is difficult because it is based on behavior, not a certain cause or a mechanism. Considering that autism affects an estimated 1 in 68 children (1 in 42 boys and 1 in 189 girls), having a possibility to not only diagnose it but predict it, through a simple brain scan, is truly exciting.

“We have been trying to identify autism as early as possible, most importantly before the actual behavioural symptoms of autism appear,” says team member Robert Emerson of the University of North Carolina at Chapel Hill.

He and his colleagues have developed an algorithm that analyzed brain scans of 6-month-old children and predicted, with almost perfect accuracy, which of them will develop autism.

For the study, they focused on babies with autism suffering siblings, which put them at a higher risk of developing the condition themselves; they settled for 59 infants aged approximately 6 months. They carried out a single brain scan (also a significant reduction from previous studies, and can be carried while the babies are sleeping) which gathered data from 230 brain regions, showing the 26,335 connections between them. Out of all these connections, researchers identified 974 regions possibly connected with autism, and put those into a machine learning algorithm. The results were impressive.

“When the classifier determined a child had autism, it was always right. But it missed two children. They developed autism but the computer program did not predict it correctly, according to the data we obtained at six months of age,” said Emerson.

The algorithm predicted that 9 of them were developing autism, and they did. Still, two more also developed the condition, which it didn’t catch. But the fact that it has no false positives is extremely encouraging, and could pave a new way for autism treatment and management. If parents know from 6 months that a child is highly likely to develop an autistic condition, they can start preparing accordingly and develop a proper environment and suitable therapies.

Vaccines don’t cause autism

This study also carries another interesting conclusion: if autism can be detected through a brain scan, it means that it has a biological component and is not fully environmental. Also, since the test was done before any vaccines were done, it invalidates (once more) the theory that vaccines cause autism. This had already been debunked several times, but for some reason, many people seem to still believe that.

“The study confirms that autism has a biological basis, manifest in the brain before behavioural symptoms appear, and that autism is not due to environmental effects that occur after 6 months, for example, vaccinations,” says Uta Frith of University College London. “This still needs pointing out.”

Of course, although results are encouraging, this is still a relatively small sample size, and it’s not clear how the algorithm would fare for different types of babies (with different brains). They will try to replicate the new findings on a broader sample size. The study comes on the heels of an earlier study that used two scans, at ages of 6 and 12 months, and had similar results in terms of accuracy.

“The more we understand about the brain before symptoms appear, the better prepared we will be to help children and their families,” said researcher Joseph Piven, also from the University of Carolina.

Journal Reference: Robert W. Emerson et al — Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age. DOI: 10.1126/scitranslmed.aag2882

Scientists find brain’s generosity center

Neuroscientists have zoomed into the part of the brain responsible for one of humanity’s purest emotions: generosity.

Photo by digital Battuta.

It’s pretty much accepted in sociology that generosity is a beneficial behavior. Ironically, looking away from your best interest and helping someone else can work out to your advantage in the long run – it can make you more desirable and can do wonders for your brain. Scientists wanted to see where exactly the generosity is ‘located’ in your brain, looking at positive empathy and other psychosocial behaviors.

Dr Patricia Lockwood from Oxford University, who led the study, said:

‘Prosocial behaviours are social behaviours that benefit other people. They are a fundamental aspect of human interactions, essential for social bonding and cohesion, but very little is currently known about how and why people do things to help others.’

She and her team had an fMRI look at volunteers’ brain while they were deciding on giving rewards to other volunteers. Interestingly, they found that generosity can also be a learned behavior, though it takes a bit longer to learn it than those which benefit yourself. In the end, they were able to identify a particular brain area involved in giving the best result for other people.

‘A specific part of the brain called the subgenual anterior cingulate cortex was the only part of the brain that was activated when learning to help other people. Put another way, the subgenual anterior cingulate seems to be especially tuned to benefiting other people.

‘However, this region of the brain was not equally active in every person. People who rated themselves as having higher levels of empathy learnt to benefit others faster than those who reported having lower levels of empathy. They also showed increased signalling in their subgenual anterior cingulate cortex when benefitting others.’

As it turns out, not everyone is generous in the same way. The ability to understand other people’s emotions and feelings are a key part of generosity, but the link is complex and difficult to understand for now.

The immediate application for this study would be understanding psychopathy or other anti- or asocial behaviors. Psychopathy is generally characterized by persistent antisocial behavior and impaired or non-existent empathy. The consequence is often a bold and egotistical behavior. In the log run, however, this could help us understand what motivates people to behave the way they do, and how we can encourage members of society to be more generous.

Journal Reference: Patricia L. Lockwood, Matthew A. J. Apps, Vincent Valton, Essi Viding, and Jonathan P. Roiser. Neurocomputational mechanisms of prosocial learning and links to empathy. PNAS, 2016 DOI:10.1073/pnas.1603198113

A software bug could render the last 15 years of brain research meaningless

A new study suggests that our fMRI technology might be relying on faulty algorithms — a bug the researchers found in fMRI-specific software could invalidate the past 15 years of research into human brain activity.

Image credits Kai Stachowiak/Publicdomainpictures

The best tool we have to measure brain activity today is functional magnetic resonance imaging (fMRI.) It’s so good in fact that we’ve come to rely on it heavily — which isn’t a bad thing, as long as the method is sound and provides accurate readings. But if the method is flawed, the results of years of research about what our brains look like during exercise, gaming, love, drug usage and more would be put under question. Researchers from Linköping University in Sweden have performed a study of unprecedented scale to test the efficiency of fMRI, and their results are not encouraging.

“Despite the popularity of fMRI as a tool for studying brain function, the statistical methods used have rarely been validated using real data,” the researchers write.

The team lead by Anders Eklund gathered rest-state fMRI data from 499 healthy individuals from databases around the world and split them intro 20 groups. They then measured them against each other, resulting in a staggering 3 million random comparisons. They used these pairs to test the three most popular software packages for fMRI analysis – SPM, FSL, and AFNI.

While the team expected to see some differences between the packages (of around 5 percent), the findings stunned them: the software resulted in false-positive rates of up to 70 percent. This suggests that some of the results are so inaccurate that they might be showing brain activity where there is none — in other words, the activity they show is the product of the software’s algorithm, not of the brain being studied.

“These results question the validity of some 40,000 fMRI studies and may have a large impact on the interpretation of neuroimaging results,” the paper reads.

One of the bugs they identified has been in the systems for the past 15 years. It was finally corrected in May 2015, at the time the team started writing their paper, but the findings still call into question the findings of papers relying on fMRI before this point.

So what is actually wrong with the method? Well, fMRI relies on a massive magnetic field pulsating through a subject’s body that can pick up on changes of blood flow in areas of the brain. These minute changes signal that certain brain regions have increased or decreased their activity, and the software interprets them as such. The issue is that when scientists are looking at the data they’re not looking at the actual brain — what they’re seeing at is an image of the brain divided into tiny ‘voxels’, then interpreted by a computer program, said Richard Chirgwin for The Register.

“Software, rather than humans … scans the voxels looking for clusters,” says Chirgwin. “When you see a claim that ‘Scientists know when you’re about to move an arm: these images prove it,’ they’re interpreting what they’re told by the statistical software.”

Because fMRI machines are expensive to use — around US$600 per hour — studies usually employ small sample sizes and there are very few (if any) replication experiments done to confirm the findings. Validation technology has also been pretty limited up to now.

Since fMRI machines became available in the early ’90s, neuroscientists and psychologists have been faced with a whole lot of challenges when it comes to validating their results. But Eklund is confident that as fMRI results are being made freely available online and validation technology is finally picking up, more replication experiments can be done and bugs in the software identified much more quickly.

“It could have taken a single computer maybe 10 or 15 years to run this analysis,” Eklund told Motherboard. “But today, it’s possible to use a graphics card”, to lower the processing time “from 10 years to 20 days”.

So what the nearly 40,000 papers that could now be in question? All we can do is try to replicate their findings, and see which work and which don’t.

The full paper, titled “Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates,” has been published online in the journal PNAS.


What separates the wolves from the sheep in the stock market?

“Be fearful when others are greedy and be greedy only when others are fearful,” said Warren Buffet, arguably the most astute contemporary investor in the world. Research by Caltech and Virginia Tech backs this sound advice, after delving deep into the investor mind and framework by analyzing stock market behavior at the neurolevel. Apparently, some parts of the brains of wise traders light up differently when they receive a signal that it’s time to maybe back down and sell, even though the market is rising and far from its peak.


Known as “the Oracle of Omaha”, Buffett is Chairman of Berkshire Hathaway and arguably the greatest investor of all time. His wealth fluctuates with the performance of the market. For instance, in 2008 he was the richest man in the world; today he’s classed at #3. Credit: Wikimedia Commons

Buy low, sell high

The hallmark of the work is the discovery of two key brain mechanisms that describe distinct types of activity in the brains of participants. One such type of brain activity was observed in a tiny fraction of the study participants. It made them nervous, twitchy and prompted them to sell their stocks even though the prices were on the rise. The other mechanism was far more common and was shared by most participants, prompting them to behave greedily and buy shares aggressively  during the bubble and sometimes even after it collapsed.

The lucky few who received the early warning signal got out of the market early and earned the most money. The others displayed what former Federal Reserve chairman Alan Greenspan called “irrational exuberance” and lost their proverbial shirts.

The researchers organized 16 trading sessions, each attended by 20 participants or so. Each participant was instructed how a screen trading market worked and was given 100 units of an experimental currency and six shares of a risky asset. Then, over the course of 50 trading periods, the traders indicated by pressing keyboard buttons whether they wanted to buy, sell, or hold shares at various prices.

The fundamental price of the risky asset was set by the researchers at 14 credits, but what’s interesting is that in many of the sessions the traded price of the asset rose far more than this. In fact, in some situations, the trading price was five times higher. Of course, this gave rise to bubble markets that eventually crashed.

“The first thing we saw was that even in an environment where you don’t have squawking heads and all kinds of other information being fed to people, you can get bubbles just through pricing dynamics that occur naturally,” says Camerer. This finding is at odds with what some economists have held—that bubbles are rare or are caused by misinformation or hype.

Throughout the experiment, the participants had their brains scanned by a functional magnetic resonance imaging (fMRI) machine. In fMRI, blood flow is monitored and used as a proxy for brain activation. If a brain region shows a relatively high level of blood oxygenation during a task, that region is thought to be particularly active.

Based on their performance over 50 trading periods, participants were divided into three main categories: the low, medium and high earners. People in the middle ground didn’t take many risks and as a result neither made nor lost money in the process. The traders who were on the low margin tended to be impulse buyers that traded on momentum. The high earners, on average, bought early and sold when the stocks were on the rise.

“The high-earning traders are the most interesting people to us,” Camerer says. “Emotionally, they have to do something really hard: sell into a rising market. We thought that something must be going on in their brains that gives them an early warning signal.”

Irrational investors are clouded by emotions

When the outcomes of the trading sessions were shared with the participants, fMRI scans revealed how a region called the nucleus accumbens (NAcc) lit up.

This region is associated with reward processing—it lights up when people are given expected rewards such as money or a paid off gamble, like in the trading business. A very interesting finding was that poor earners – those who’ve basically lost their shirts – were very sensitive to activity in the NAcc: when they experienced the most activity in the NAcc, they bought a lot of the risky asset.

“That is a correlation we can call irrational exuberance,” Camerer says. “Exuberance is the brain signal, and the irrational part is buying so many shares. The people who make the most money have low sensitivity to the same brain signal. Even though they’re having the same mental reaction, they’re not translating it into buying as aggressively.”

History is written by the victor, however. What makes the high earners better? The researchers hypothesize that a part of the brain called the insular cortex, or insula, is key.

Previous studies have linked the insula to financial uncertainty and risk aversion. It is also known to reflect negative emotions associated with bodily sensations such as being shocked or smelling something disgusting, or even with feelings of social discomfort like those that come with being treated unfairly or being excluded.

“The scans showed that the insula activity shortly before the traders switched from buying to selling. And again, Camerer notes, “The prices were still going up at that time, so they couldn’t be making pessimistic predictions just based on the recent price trend. We think this is a real warning signal.”

Meanwhile, in the low earners, insula activity actually decreased, perhaps allowing their irrational exuberance to continue unchecked.

“Individual human brains are indeed powerful alone, but in groups we know they can build bridges, spacecraft, microscopes, and even economic systems,” says Read Montague, director of the Human Neuroimaging Laboratory at the Virginia Tech Carilion Research Institute and one of the paper’s senior authors. “This is one of the next frontiers in neuroscience—understanding the social mind.”

The findings of the paper were reported in the Proceedings of the National Academy of Sciences.

Humans are not unique in understanding the basics of language

A paper published recently in Nature Communications details how a team led by Dr. Ben Wilson and Professor Chris Petkov used a brain imaging technique to identify the neuronal evolutionary origins of language. Their findings help us understand how we learn to speak, and could allow new treatments for those who lost this ability from aphasia following a stroke or dementia.

Image via wikimedia

By scanning the brains of macaque monkeys, the researchers identified an area in the front of the brain that, in both humans and macaques, recognizes a sequence of sounds as speech, and is responsible for analyzing if the sounds are in legal order or in an unexpected, illegal order.

“Young children learn the rules of language as they develop, even before they are able to produce language. So, we used a ‘made up’ language first developed to study infants, which our lab has shown the monkeys can also learn. We then determined how the human and monkey brain evaluates the sequences of sounds from this made up language,” said Professor Petkov.

Human and monkey subjects were played an example sequence from the made-up language, to hear the correct order in the sequence of sounds. After this they were played new sequences, some of which were in an incorrect order, and the team scanned their brains using fMRI. In both species, there was neuronal response in the same region of the brain — the ventral frontal and opercular cortex — when the sounds were correctly ordered.

The findings suggest that this region’s functionality is shared between humans and macaques, revealing a common cerebral evolutionary source. This brain region seems to monitor the orderliness or organization of sounds and words, which is an important cognitive function, at the core of the more complex language abilities of humans. The findings are the first scientific evidence that other animals share with us at least some of the functions this area serves, which include understanding language in humans.

“Identifying this similarity between the monkey and human brain is also key to understanding the brain regions that support language but are not unique to us and can be studied in animal models using state-of-the-art neuroscientific technologies,” Professor Petkov explains.

“This will help us answer questions on how we learn language and on what goes wrong when we lose language, for example after a brain injury, stroke or dementia.”

Building on these developments, the Newcastle University team, with their neurology collaborators in Cambridge and Reading Universities have begun a project to study the function of this brain region and its role in language impairment in aphasic patients with stroke, which might lead to better diagnosis and prognosis of language impairment.


Brain fMRI study predicts efficiency of anti-smoking Ads

Using functional magnetic resonance imaging, scientists from the universities of Michigan and Pennsylvania scanned the brains of 50 smokers while they viewed anti-smoking ads. They recorded their neural activity spikes as they watched the sample of 40 images one at a time, looking for increase activity in the medial prefrontal cortex, the area that handles decision making processes.

The paper, titled “Functional brain imaging predicts public health campaign success,” is published in the journal Cognitive and Affective Neuroscience.

Then the images were sent via e-mail to New York smokers in a campaign named “Stop smoking. Start living,” with a link embedded under the ads to sources with help on quitting smoking. The team believed that the ads which stimulated the MPFC the most during the Michigan fMRI study would achieve the best results in the campaign, which they estimated by the number of clicks each ad would receive.

The researchers predicted the ads which showed the most brain activity in the MPFC area would achieve the best results in e-mail campaigns.

And indeed, during the test campaign, Michigan trial data correlated well with the results: ads that caused intense spikes in activity achieved the highest Click-Through Rate — with only opened e-mails counted, CTR ranged from 10 percent for the least successful images to 26 percent for the ones that caused the most significant spikes.

This means that, just by looking at brain activity, researchers were able to predict which images were the best suited for the ad campaign. Emily Falk, a professor at Pennsylvania’s Annenberg School for Communication, commented:

“If you ask people what they plan to do or how they feel about a message, you get one set of answers. Often the brain gives a different set of answers, which may help make public health campaigns more successful. My hope is that moving forward, we might be able to use what we learned from this study and from other studies to design messages that are going to help people quit smoking and make them healthier and happier in the long run.”

Most of the successful images used a negative tone, contradicting research which shows that negative messages que the participant to take a more defensive approach to the message.




Gamers have more grey matter and better brain connectivity, new research suggests

All those hours of leveling up your character have finally paid off – a new study conducted by Australian and Chinese researchers suggests that playing computer games not only increases the amount of grey matter in your brain, but also promotes better connectivity between different areas of the brain.

The former Dota2 squad of Evil Geniuses, one of the most successful teams.

Even after all these years, people who often play computer games still get a lot of bad rep in many circles of society – but that’s likely to change in the near future, as more and more studies showed that not only does it not hurt you (except for wasting copious amounts of time), it might actually help you. Gaming has been linked to brain thickening (which is a good thing), it improves spatial orientation, it improves eyesight and reflexes, and despite what many people think, it might actually make you more social and polite. Also, it should come as no surprise that gaming improves brain connectivity – after all, most of today’s computer games require active participation and a mixture of very different types of thinking.

A team led by researchers from the University of Electronic Science and Technology of China and Macquarie University in Sydney, used functional MRI (fMRI) scans to analyse the brains of 27 gamers who have achieved professional, or ‘expert’, levels of playing action video games (AVG), having won regional and national championships in League of Legends or DOTA2.

The team, led by researchers from researchers from the University of Electronic Science and Technology of China and Macquarie University in Sydney, used functional MRI (fMRI) scans to analyse the brains of 27 gamers who achieved professional status or at least had an ‘expert’ status. The team then compared the results with those from people who don’t typically play games and noted the results.

The results showed increased activity for gamers in an area called the insular cortex – typically associated with ‘higher’ cognitive functions such as empathy and compassion, but also with the ability to focus. The image below below reveals what they found; the anterior (green), transitional (yellow) and posterior (red) regions of the brain showed greater connectivity in gamers.

This really shouldn’t shock anyone – competitive computer gaming is… well, competitive, especially with the huge money influx in games like Dota2 or League of Legends (they already have multi-million tournaments) – so you’d expect players to be really good at it, and have a better ability to concentrate, reason and make quick decisions that most people.

“By comparing AVG experts and amateurs, we found that AVG experts had enhanced functional connectivity and grey matter volume in insular subregions,” the team writes in Scientific Reports. “Furthermore, AVG experts exhibited increased functional connectivity between the attentional and sensorimotor networks, and the experience-related enhancement was predominantly evident in the left insula, an understudied brain area. Thus, AVG playing may enhance functional integration of insular subregions and the pertinent networks therein.”

Journal Reference: Diankun Gong, Hui He, Dongbo Liu, Weiyi Ma, Li Dong, Cheng Luo & Dezhong Yao, Enhanced functional connectivity and increased gray matter volume of insula related to action video game playing. Scientific Reports, doi:10.1038/srep09763

No two autistic brains are alike – each has unique connections

For most people, brains are pretty similar – our connections follow the same pattern, and while there are certainly exceptions, you could say that our brains are connected in pretty much the same way. But for autistic people, things are very different. A new study has found that each autistic brain has unique, highly idiosyncratic connections.

Image: The networks in your brain. Credit: NIH

We’re only starting to scratch the surface when it comes to understanding autism. Autism is a neurodevelopmental disorder with various characteristics. The most usual are impaired social interaction as well as verbal and non-verbal communication. Autism is often accompanied by repetitive or compulsive behavior. An estimated 60%–80% of autistic people have motor signs that include poor muscle tone, poor motor planning, and toe walking.

However, we still don’t know what’s causing it and what can be done to treat it. For these reasons, studies such as this one are very important, because they show what happens inside the brains of people suffering from autistic spectrum disorder (ASD). What this study revealed is that unlike the relative monotony of non-autistic humans, people with ASD come in stark contrast – each brain is different.

Avital Hahamy and Prof. Rafi Malach of the Weizmann Institute’s Neurobiology Department, and Prof. Marlene Behrmann of Carnegie Mellon University, Pittsburgh analyzed data from fMRI studies from a large number of resting volunteers.

“Resting-state brain studies are important,” says Hahamy, “because that is when patterns emerge spontaneously, allowing us to see how various brain areas naturally connect and synchronize their activity.” A number of previous studies in Malach’s group and others suggest that these spontaneous patterns may provide a window into individual behavioral traits, including those that stray from the norm and are associated with ASD.

[Also read: Child prodigies and autism are linked, study finds]

In people without the disorder, they found very similar patterns. In other words, if you would superimpose one scan on top of the other, the levels of connectivity would be basically the same across the various regions of the brain. But when they did the same thing with the brains of people with ASD, they couldn’t find similarities between any two participants. They couldn’t even split the brains up into sub-groups because the way the networks were arranged was so individualised! This study not only shows a remarkable particularity of ASD brains, but may shed some light on the very nature of the disorder.

“Our results reveal a new and robust abnormality in the ASD connectivity, which relates to the topographical nature of the functional connectivity patterns rather than to their overall strength,” the team reports in the journal Nature Neuroscience.“Specifically, we found that the canonical pattern of functional connectivity seen in typical controls showed significant and individually distinct (idiosyncratic) distortions in participants with ASD.”

The team is not certain what causes ASD brains to be so different, but judging by the fMRIs, they believe it has something to do with how people interact with the environment which surrounds them.

“From a young age, the average, typical person’s brain networks get moulded by intensive interaction with people and the mutual environmental factors,” says Hahamy in the press release. “Such shared experiences could tend to make the synchronisation patterns in the control group’s resting brains more similar to each other. It is possible that in ASD, as interactions with the environment are disrupted, each one develops a more uniquely individualistic brain organisation pattern.”


Scientists scan a woman’s brain during out of body experience

It’s a little out of this world – a psychology graduate student at the University of Ottawa says she can voluntarily enter an out-of-body experience. While scientists are generally skeptical when it comes to this kind of claims, they were thrilled by the possibility to scan her brain during the experience – and the results were indeed spectacular.

An unusual experience

Usually, outer body experiences accompany extreme situations – for example a life threatening accident, where one “floats” above his/her body as the doctors are working, it’s usually something along these lines. The experience is also usually attributed to the drugs in a patient’s system, or the hormones released into their system by trauma.

This study passed the peer review and was published in Frontiers of Neuroscience, so it’s not just some shenanigans. Andra M. Smith and Claude Messier from the University of Ottawa talk about how this went:

“She was able to see herself rotating in the air above her body, lying flat, and rolling along with the horizontal plane. She reported sometimes watching herself move from above but remained aware of her unmoving “real” body… “

… and an unusual participant

The participant, whose name was not disclosed, is a right-handed woman, age 24, who was a psychology graduate student at the time of testing. She signed an informed consent approved by the University of Ottawa Research Ethics Board. Her story is a very interesting one: she was in an undergraduate class that presented data on body representation hallucinations in patients that report experiences of their body outside their physical body (Blanke and Arzy, 2005). She spontaneously reported after class that she could have a similar “out of body” experience. She appeared surprised that not everyone could experience this – describing that she developed the technique in kindergarten, trying to find something to do while she was asked to nap. She claimed she believed that everyone can do this, and was surprised to learn that this is not nearly the case.

“I feel myself moving, or, more accurately, can make myself feel as if I am moving. I know perfectly well that I am not actually moving. There is no duality of body and mind when this happens, not really. In fact, I am hyper-sensitive to my body at that point, because I am concentrating so hard on the sensation of moving. I am the one moving – me – my body. For example, if I ‘spin’ for long enough, I get dizzy. I do not see myself above my body. Rather, my whole body has moved up. I feel it as being above where I know it actually is. I usually also picture myself as moving up in my mind’s eye, but the mind is not substantive. It does not move unless the body does.”

The brain, out of the body

So what did the results actually show? Researchers did a fMRI before and after asking her to enter her out-of-body state to find out what that looked like in the brain. They compared these to when she was imagining, but not actually entering, the state. Interestingly enough, the pathway that seemed to be activated during her out-of-body experience is also involved in the mental representation of movements. So basically, when she was “out of her body” and simply imagining this, some of the same pathways were activated – but there were also clear differences.

fmri out of body 2

From a neurological and psychological perspective, this whole thing seems to be a sort of hallucination that she can turn on and off, at will – and researchers are pretty sure about one thing: she’s not faking it. There’s obviously something happening in her brain that is making her experience the world in a different way, stimulating the supplementary motor area, the cerebellum, the supramarginal gyrus, the inferior temporal gyrus, the middle and superior orbitofrontal gyri. Some parts were actually turned down, which is expected with this kind of experience, as shown below:

fmri out of body

So what does this mean?

First of all, we shouldn’t be jumping to conclusions. This doesn’t, in an way, imply a paranormal experience. Furthermore, it doesn’t necessarily mean that there is a “soul” which can leave the body at will. So then… what does it mean?

Well, anyone can imagine themselves flying around their body and claim they have an out of body experience. What the researchers went for is figuring out, first of all, if this experience is real and not simulated, and second of all, what happens in the brain during this experience. By comparing her brain activity in all of these conditions they tried to see whether her out-of-body experiences produced detectably different patterns of brain activity than her imaginary movements – and as it turns out, there are major differences.

But this is only one woman’s experience – we need to study more before we draw any definite conclusions. The fMRI revealed changes which are comparable to meditation, so that’s definitely interesting. Is this something more common than previously thought, is it something which can be trained, like meditation? Science – and time – will tell.

Dogs’ Brains Respond to People’s Voices the Same Way We Do, MRI study shows

If you’ve ever had a nice fuzzy feeling whenever you heard the voice of a loved one, then, you’re not alone. If somebody’s ever told you that ‘we need to talk’ and out of their tone  you understood that something’s bad, then again, you’re not alone. A new study has shown that dogs have an uncanny ability of picking up our emotions only from our speech – seeming to sense our emotional currents through changes in the tone of our voice. Ask any dog owner, and they’ll confirm it; but for the first time, the science has been done to confirm this theory.


It took a while to get there  though, and kudos to the researchers for getting conscious dogs to stay still enough during the MRIs – I have no idea how they managed to do this. Scanning other animals is normally very difficult, as they need to be both conscious and very still. Thankfully, dogs are very trainable and Attila Andics, a researcher in the MTA-ELTE Comparative Ethology Research Group in Budapest and his team, managed to train 11 dogs (golden retrievers and border collies) to rest in an MRI machine. That allowed them to observe the patterns in the dogs’ brains when they heard any of 200 different sounds and compare those responses to humans’. This is the first study which creates a neurological comparison between humans and non-primate animals.

However, we shouldn’t take these findings too far. It’s tempting to draw the conclusion that dogs and humans received their vocal-perception strategies from a common ancestor – but that’s pretty much impossible. If this were the case, then more mammals would also exhibit this – which isn’t happening. Evolutionary biologists are pretty clear on this one.

Andics argues that it’s possible that other mammals do have such a system, since recognition of emotional cues through vocalizations would have been beneficial to all of them. But the other camp claims that this is another simple case of convergent evolution – the same characteristic independently occurring in different animal groups.

Via PBS.




Highly controversial brain scan predicts whether criminals are likely to reoffend

As the writers on Nature depict it, it evokes the dystopian worlds of science fiction writer Philip K. Dick – if you’ve read his works or seen Minority Report, you’ll understand it. Neuroscientists have developed a brain scan that shows how likely are convicted felons to commit crimes again.

Brain scanning felons

brain felon

Kent Kiehl, a neuroscientist at the non-profit Mind Research Network in Albuquerque, New Mexico, and his collaborators studied a group of 96 male prisoners just before their release. They used their functional magnetic resonance imaging (fMRI) to scan the prisoners’ brains during computer tasks in which the prisoners had to make rash decisions and inhibit impulsive behavior. They especially focused on a section of the anterior cingulate cortex (ACC), a small region in the front of the brain involved in motor control and executive functioning. After these tests, they followed their subjects for 4 years, to see how they do.

Subjects who had lower ACC activity during the quick-decision tasks were more likely to be arrested again after getting out of prison, even after researchers eliminated disturbing factors, such as age, sex, drug and alcohol abuse and psychopathic traits – bare in mind however, that the elimination of these parameters is never perfect, and always subject to either under or overestimation. en who were in the lower half of the ACC activity ranking had a 2.6-fold higher rate of rearrest for all crimes and a 4.3-fold higher rate for nonviolent crimes.

Treading on thin ice

minority report

First of all, even the researchers themselves agree that this is just an initial study, and much more data has to be gathered before this method can be considered even remotely viable.

“This isn’t ready for prime time,” says Kiehl.

Also, they underline that only high risk subjects should be taken into consideration, and not lower risk ones. But even so… Philip K. Dick raised the very thorny ethical issues of arresting people for crimes they didn’t commit. Of course, brain scans are much, much different than the psychic powers described in Minority Report, but let’s take a moment to ponder a case. Say you have a subject with a moderately to high risk; what do you do? You can’t arrest him for something he hasn’t committed, and you can’t say, keep some surveillance on him, because that may very well be the trigger that makes him snap and commit crimes again. If you ask me, this kind of technology, if available at some point, should be used to make low stake decisions, like which rehabilitation treatment to assign a prisoner or more often visits when on parole, rather than high stake ones, like actually giving parole or a bigger sentence.

“A treatment of [these clinical neuroimaging studies] that is either too glibly enthusiastic or over-critical,” says Tor Wager, a neuroscientist at the University of Colorado in Boulder “will be damaging for this emerging science in the long run.”

Vegetative patients can now communicate with the outside world through fMRI and EEG

As amazing as it sounds, communicating with a person in a vegetative state is no longer something we see in sci-fi movies, it is beginning to become a reality.

A vegetative state occurs when some patients come out of a come and wake up, but not with their minds, just their bodies. While they are able to breathe on their own and exhibit some reflexive behaviors, they are thought to be in a state where they cannot have any brain activity whatsoever: no thoughts or emotions. At least that’s what is currently believed to be true of the people in this condition.

An fMRI machine. [Via singularityhub.com]

Recent studies using EEG or fMRIhave lead some scientists to conclude that in some of the patients they studied, awareness was detected. And not only that, what is even more amazing is that the doctors succeeded in establishing a form of communication with these people – showing how they can answer yes or no questions.

fMRI from http://www.bbc.co.uk/news/health-20268044

Patient having an fMRI scan performed. (c) BBC.co.uk

Prof. Adrian Owen, a neuroscientist at the Brain and Mind Institute at the University of Western Ontario used fMRI to read the brain activity in several patients in this condition. How did he manage to instruct them to communicate back ?

Through technologies such as the fMRI, scientists are able to distinguish from different types of thoughts. In the case of these studies they used the ability to distinguish from what is referred to as spatial movement from the body movement-type brain activity. As such, for the first case, the patients were instructed to think of travelling through the streets of a familiar city or through their home and for the second type of activity they were told to think about playing tennis and hitting the ball back to an instructor.

[RELATED] Science brings mind-reading tech a step closer 

By telling them to assign the first type of activity to a “no” answer and the second type to a “yes” – they were able to answer questions and thus capable of establishing a basic type of communication. This is an incredible breakthrough for the people in this condition and for their loved ones.

Besides the fMRI, Dr Owen managed to use the same strategy for communication by using EEG – a technology that is much more cheap and easy to use in comparison with the fMRI, thus potentially enabling a wide scale use of this method.

Undergoing an EGG scan. (c) BBC.co.uk

It’s true that this is not a miracle method yet – only 5 of the 54 patients that participated in this study were able to modulate their brain activity willfully at least as far as the fMRI could detect, but it still opens up an amazing opportunity.

Professor Julian Savulescu, the director of the Oxford Centre for Neuroethics stated that “This important scientific study raises more ethical questions than it answers. People who are deeply unconscious don’t suffer.

“But are these patients suffering? How bad is their life? Do they want to continue in that state? If they could express a desire, should it be respected?

“The important ethical question is not: are they conscious? It is: in what way are they conscious? Ethically, we need answers to that.”

[Via singularityhub.com, and BBC News]

Decreased cerebral blood flow (CBF) after psilocybin imaged by fMRI

fMRI scans reveals how ‘magic mushrooms’ inflict psychedelic effect on the brain

Psychedelic mushrooms have been used for medical, ceremonial and spiritual purposes for thousands of years, due their mind-alterating properties which induce hallucinations, perception disorders or altered states of awareness. It’s been found that the active ingredient responsible for the psychedelic state, which many associated with a religious experience, is a substance called psilocybin. Though a lot is known about the substance, chemically-wise, how exactly it affects the brain remained unclear until now, but a recent studying involving fMRI brain scans changed all that.

Scientists at the  Neuropsychopharmacology Unit at Imperial College London, used blood-oxygen level dependent (BOLD) functional MRI (fMRI), in conjunction with a technique that images the transition from normal, conscious state to psychedelic state, to scan the brains of volunteers. These were separated into two groups, the ones which were administrated with active psilocybin, and those who were given a placebo.

Decreased cerebral blood flow (CBF) after psilocybin imaged by fMRI

Decreased cerebral blood flow (CBF) after psilocybin imaged by fMRI

What the researchers found was a decreased blood flow and BOLD in the thalamus, anterior and posterior cingulate cortex, and medial prefrontal cortex. These areas of the brain are key connector hubs, which when faced with a decreased activity, enable a state of unconstrained cognition, which would explain the psychedelic effect.

The study, though highly successful, wasn’t without hardship. Lead researcher Dr. Robin L. Carhart-Harris recalls how a number of impediments made their research one big tough nut to crack. For instance, an exact dosage and delivery protocol was necessary for accurate fMRI imaging, insulating placebo effects like pre-administration anxiety, and a number of other issues, which were fortunately resolved by the scientists.

Now that the exact regions of the brain where the psychedelic substance is active have been pinpointed, research which might lead to beneficial psychedelic drug therapy will not only commence soon, but will be taken more seriously by the rest of the community, as hard evidence of key receptors and their interaction with substances are presented. Psilocybin therapy might help a great deal people suffering from depression.

 “Psilocybin decreases brain activity in regions such as the medial prefrontal cortex,” Dr. Carhart explains, “that are overactive in depression.”

In addition to depression, Carhart-Harris observes, there are other research and applications that might benefit from the team’s findings.

“Those suffering from cluster headaches,” he notes, “report excruciating pain that is difficult to treat, sometimes describing it as worse than the pain childbirth. During such headaches, they show an increase in hypothalamic activity to date has only been ameliorated by deep brain stimulation. However,” he concludes, “when administered psilocybin, they display a decrease in hypothalamic activity and a corresponding suspension of cluster headaches.”

The findings were reported in the journal PNAS.


Brain Movie

Brain imaging reveals the movies inside our mind

Brain Movie

Mixing in a typical fMRI brain scanner with advanced computer modeling simulations, scientists at the University of California have managed to achieve the the unthinkable – render the visual expressions triggered inside the brain and play them like a movie. This is the forefront technology which will one day allow us to tap inside the mind of coma patients or be able to watch the dream you had last night and still vaguely remember, just like a plain movie. Quite possibly one of the most fascinating SciFi ideas might become a matter of reality in the future.

“This is a major leap toward reconstructing internal imagery,” said Professor Jack Gallant, a UC Berkeley neuroscientist and coauthor of the study published online today (Sept. 22) in the journal Current Biology. “We are opening a window into the movies in our minds.”

This comes right on the heels of a recent, comparatively amazing study, from Princeton University who’ve managed to tell what study participants were thinking about, using a fMRI and a lexical algorithm. The neuroscientists from University of California have taken this one big step farther by visually representing what goes on inside the cortex.

A Sci-Fi dream come true that might show your dreams, in return

They first started out with a pictures experiment, showing participants black and white photos. After a while the researchers’ system allowed them to pick with absolute accuracy  which picture the subject was looking at. For this latest one, however, scientists had to surrmount various difficult challenges which come with actually decoding brain signals generated by moving pictures.

“Our natural visual experience is like watching a movie,” said Shinji Nishimoto, lead author of the study and a post-doctoral researcher in Gallant’s lab. “In order for this technology to have wide applicability, we must understand how the brain processes these dynamic visual experiences.”

Nishimoto and two other research team members served as subjects for the experiment, as they stepped inside the fMRI for the experiments which requires them to sit still for hours at a time. During their enclosed space inside the fMRI, the scientists were presented with a few sets of Hollywood trailers, while blood flow through the visual cortex, the part of the brain that processes visual information, was measured. The brain activity recorded while subjects viewed the first set of clips was fed into a computer program that learned, second by second, to associate visual patterns in the movie with the corresponding brain activity.

A movie of the movie inside your head. Limbo!

The second phase of the experiment is where it all becomes very interesting, as it implies the movie reconstruction algorithm. Scientists fed 18 million seconds of random YouTube videos into the computer program so that it could predict the brain activity that each film clip would most likely evoke in each subject. Then based on the brain imaging delivered by the fMRI, the computer program would morph various frames it had already learn into what it believed best describes the brain pattern. The result was nothing short of amazing. Just watch the video below.

This doesn’t mean that this new technology developed by UC scientists is able to read minds or the likes and visually tape ones memories on a display. Such technology, according to the researchers, is decades away, but their studies will help pave the way for future such developments. As yet, the technology can only reconstruct movie clips people have already viewed.

“We need to know how the brain works in naturalistic conditions,” he said. “For that, we need to first understand how the brain works while we are watching movies.”


The three stage approach neuroscientists followed in the published study: creating a model of how stimuli will be represented in the brain, learning how to predict fMRI data in response to the stimuli, given the model, and inverting the process to make a prediction for fMRI data not used to fit the model.

Science brings mind reading tech a step closer

Researchers from Princeton University recently published a study in which they show how they’ve been able to use functional magnetic resonance imaging and a computer program that condensed 3,500 Wikipedia articles to associate words to particular brain activity patterns. Basically, they were able to read thoughts.

To reach this remarkable correlation, researchers first did some fMRI scans while participants were asked to think of a given word and then visualize it for at least three seconds. This way, they were able to identify regions of the brain which turned active when the subject was thinking about a certain word, like “carrot” or “house”. Repeating this with various subjects, they were able to map a brain pattern that corresponds to a certain family of words or topic. For instance, thoughts about the idea of “furniture” shared similar patterns with words like “table,” “desk” and “chair.”

The three stage approach neuroscientists followed in the published study: creating a model of how stimuli will be represented in the brain, learning how to predict fMRI data in response to the stimuli, given the model, and inverting the process to make a prediction for fMRI data not used to fit the model.

The three stage approach neuroscientists followed in the published study: creating a model of how stimuli will be represented in the brain, learning how to predict fMRI data in response to the stimuli, given the model, and inverting the process to make a prediction for fMRI data not used to fit the model.

Extrapolating from this data, neuroscientists were able to read fMRI scans which allowed them to tell what topic a person was thinking about, without  the researchers having any idea beforehand. Going back to the previous example, if the fMRI scan showed a brain activity corresponding to “chair”, scientists could assert that the subject was thinking about furniture.

“Whatever subject matter is on someone’s mind — not just topics or concepts, but also emotions, plans or socially oriented thoughts — is ultimately reflected in the pattern of activity across all areas of his or her brain,” said the team’s senior researcher, Matthew Botvinick, an associate professor in Princeton’s Department of Psychology and in the Princeton Neuroscience Institute.

The researchers picked up their work based on a previous 2008 word-association study, in which participants were shown a picture and a word of five objects in 12 categories.

Neural activity was recorded using fMRIs, but the topic range wasn’t broad enough so they used 3,500 Wikipedia articles about objects — like an airplane, heroin, birds and manual transmission – which were inputted in a software that returned 40 topics to which these things could relate — i.e. aviation, drugs, animals or machinery.

Scientists arranged the fMRIs and were ultimately able to tell the general idea inside a subjects head. Particular thoughts have been next to impossible to pick up, Princeton scientists explain, however the progress made thus far can be considered remarkable without a doubt. Eventually, scientists hope that they’ll be able to translate brain activity patterns into words which could actually accurately describe one’s train of thought.

Applications would be numerous for this SciFi concept. People of neural disabilities which renders them unable to communicate might benefit enormously from something like this, as well as, of course, intelligence agencies. Who wouldn’t love a mind reading device?