How brains benefit from meditation

How brains benefit from meditation

  10:05:00 AM    Science Lover

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Experienced meditators seem to be able switch off areas of the brain associated with daydreaming as well as psychiatric disorders such as autism and schizophrenia, according to a new brain imaging study by Yale researchers.

Experienced meditators seem to switch off areas of the brain
associated with wandering thoughts, anxiety and some
psychiatric disorders such as schizophrenia. Researchers
used fMRI scans to determine how the brains of meditators
differed from subjects who were not meditating. The areas
shaded in blue highlight areas of decreased activity in the
brains of meditators. Credit: courtesy of yale

Meditation's ability to help people stay focused on the moment has been associated with increased happiness levels, said Judson A. Brewer, assistant professor of psychiatry and lead author of the study published the week of Nov. 21 in the Proceedings of the National Academy of Sciences. Understanding how meditation works will aid investigation into a host of diseases, he said.

"Meditation has been shown to help in variety of health problems, such as helping people quit smoking, cope with cancer, and even prevent psoriasis," Brewer said.

The Yale team conducted functional magnetic resonance imaging scans on both experienced and novice meditators as they practiced three different meditation techniques.

They found that experienced meditators had decreased activity in areas of the brain called the default mode network, which has been implicated in lapses of attention and disorders such as anxiety, attention deficit and hyperactivity disorder, and even the buildup of beta amyloid plaques in Alzheimer's disease. The decrease in activity in this network, consisting of the medial prefrontal and posterior cingulate cortex, was seen in experienced meditators regardless of the type of meditation they were doing.

The scans also showed that when the default mode network was active, brain regions associated with self-monitoring and cognitive control were co-activated in experienced meditators but not novices. This may indicate that meditators are constantly monitoring and suppressing the emergence of "me" thoughts, or mind-wandering. In pathological forms, these states are associated with diseases such as autism and schizophrenia.

The meditators did this both during meditation, and also when just resting — not being told to do anything in particular. This may indicate that meditators have developed a "new" default mode in which there is more present-centered awareness, and less "self"-centered, say the researchers. "Meditation's ability to help people stay in the moment has been part of philosophical and contemplative practices for thousands of years," Brewer said. "Conversely, the hallmarks of many forms of mental illness is a preoccupation with one's own thoughts, a condition meditation seems to affect. This gives us some nice cues as to the neural mechanisms of how it might be working clinically."

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Scientists Measure Dream Content for the First Time: Dreams Activate the Brain in a Similar Way to Real Actions

Scientists Measure Dream Content for the First Time: Dreams Activate the Brain in a Similar Way to Real Actions

  9:51:00 PM    Science Lover

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The ability to dream is a fascinating aspect of the human mind. However, how the images and emotions that we experience so intensively when we dream form in our heads remains a mystery. Up to now it has not been possible to measure dream content. Max Planck scientists working with colleagues from the Charité hospital in Berlin have now succeeded, for the first time, in analysing the activity of the brain during dreaming.

Top: Patient in a functional magnetic resonance imaging machine. Bottom: Activity in the motor cortex during the movement of the hands while awake (left) and during a dreamed movement (right). Blue areas indicate the activity during a movement of the right hand, which is clearly demonstrated in the left brain hemisphere, while red regions indicate the corresponding left-hand movements in the opposite brain hemisphere. (Credit: © MPI of Psychiatry)

They were able to do this with the help of lucid dreamers, i.e. people who become aware of their dreaming state and are able to alter the content of their dreams. The scientists measured that the brain activity during the dreamed motion matched the one observed during a real executed movement in a state of wakefulness.

The research is published in the journal Current Biology.

Methods like functional magnetic resonance imaging have enabled scientists to visualise and identify the precise spatial location of brain activity during sleep. However, up to now, researchers have not been able to analyse specific brain activity associated with dream content, as measured brain activity can only be traced back to a specific dream if the precise temporal coincidence of the dream content and measurement is known. Whether a person is dreaming is something that could only be reported by the individual himself.

Scientists from the Max Planck Institute of Psychiatry in Munich, the Charité hospital in Berlin and the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig availed of the ability of lucid dreamers to dream consciously for their research. Lucid dreamers were asked to become aware of their dream while sleeping in a magnetic resonance scanner and to report this "lucid" state to the researchers by means of eye movements. They were then asked to voluntarily "dream" that they were repeatedly clenching first their right fist and then their left one for ten seconds.



This enabled the scientists to measure the entry into REM sleep -- a phase in which dreams are perceived particularly intensively -- with the help of the subject's electroencephalogram (EEG) and to detect the beginning of a lucid phase. The brain activity measured from this time onwards corresponded with the arranged "dream" involving the fist clenching. A region in the sensorimotor cortex of the brain, which is responsible for the execution of movements, was actually activated during the dream. This is directly comparable with the brain activity that arises when the hand is moved while the person is awake. Even if the lucid dreamer just imagines the hand movement while awake, the sensorimotor cortex reacts in a similar way.

The coincidence of the brain activity measured during dreaming and the conscious action shows that dream content can be measured. "With this combination of sleep EEGs, imaging methods and lucid dreamers, we can measure not only simple movements during sleep but also the activity patterns in the brain during visual dream perceptions," says Martin Dresler, a researcher at the Max Planck Institute for Psychiatry.

The researchers were able to confirm the data obtained using MR imaging in another subject using a different technology. With the help of near-infrared spectroscopy, they also observed increased activity in a region of the brain that plays an important role in the planning of movements. "Our dreams are therefore not a 'sleep cinema' in which we merely observe an event passively, but involve activity in the regions of the brain that are relevant to the dream content," explains Michael Czisch, research group leader at the Max Planck Institute for Psychiatry.

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Word Association: Study Matches Brain Scans With Complex Thought

Word Association: Study Matches Brain Scans With Complex Thought

  4:16:00 PM    Science Lover

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In an effort to understand what happens in the brain when a person reads or considers such abstract ideas as love or justice, Princeton researchers have for the first time matched images of brain activity with categories of words related to the concepts a person is thinking about. The results could lead to a better understanding of how people consider meaning and context when reading or thinking.

Princeton researchers developed a method to determine the
probability of various words being associated with the object a person
thought about during a brain scan. They produced color-coded figures
that illustrate the probability of words within the Wikipedia article
about the object the participant saw during the scan actually being
associated with the object. The more red a word is, the more likely a
person is to associate it, in this case, with "cow." On the other hand,
bright blue suggests a strong correlation with "carrot." Black and grey
"neutral" words had no specific association or were not considered at
all. (Credit: Illustration courtesy of Francisco Pereira)

The researchers report in the journal Frontiers in Human Neuroscience that they used functional magnetic resonance imaging (fMRI) to identify areas of the brain activated when study participants thought about physical objects such as a carrot, a horse or a house. The researchers then generated a list of topics related to those objects and used the fMRI images to determine the brain activity that words within each topic shared. For instance, thoughts about "eye" and "foot" produced similar neural stirrings as other words related to body parts.

Once the researchers knew the brain activity a topic sparked, they were able to use fMRI images alone to predict the subjects and words a person likely thought about during the scan. This capability to put people's brain activity into words provides an initial step toward further exploring themes the human brain touches upon during complex thought.

"The basic idea is that 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 long-term goal is to translate that brain-activity pattern into the words that likely describe the original mental 'subject matter,'" Botvinick said. "One can imagine doing this with any mental content that can be verbalized, not only about objects, but also about people, actions and abstract concepts and relationships. This study is a first step toward that more general goal.

"If we give way to unbridled speculation, one can imagine years from now being able to 'translate' brain activity into written output for people who are unable to communicate otherwise, which is an exciting thing to consider. In the short term, our technique could be used to learn more about the way that concepts are represented at the neural level -- how ideas relate to one another and how they are engaged or activated."

The research, which was published Aug. 23, was funded by a grant from the National Institute of Neurological Disease and Stroke, part of the National Institutes of Health.

Depicting a person's thoughts through text is a "promising and innovative method" that the Princeton project introduces to the larger goal of correlating brain activity with mental content, said Marcel Just, a professor of psychology at Carnegie Mellon University. The Princeton researchers worked from brain scans Just had previously collected in his lab, but he had no active role in the project.

"The general goal for the future is to understand the neural coding of any thought and any combination of concepts," Just said. "The significance of this work is that it points to a method for interpreting brain activation patterns that correspond to complex thoughts."

Tracking the brain's 'semantic threads'

Largely designed and conducted in Botvinick's lab by lead author and Princeton postdoctoral researcher Francisco Pereira, the study takes a currently popular approach to neuroscience research in a new direction, Botvinick said. He, Pereira and coauthor Greg Detre, who earned his Ph.D. from Princeton in 2010, based their work on various research endeavors during the past decade that used brain-activity patterns captured by fMRI to reconstruct pictures that participants viewed during the scan.

"This 'generative' approach -- actually synthesizing something, an artifact, from the brain-imaging data -- is what inspired us in our study, but we generated words rather than pictures," Botvinick said.

"The thought is that there are many things that can be expressed with language that are more difficult to capture in a picture. Our study dealt with concrete objects, things that are easy to put into a picture, but even then there was an interesting difference between generating a picture of a chair and generating a list of words that a person associates with 'chair.'"

Those word associations, lead author Pereira explained, can be thought of as "semantic threads" that can lead people to think of objects and concepts far from the original subject matter yet strangely related.

"Someone will start thinking of a chair and their mind wanders to the chair of a corporation then to Chairman Mao -- you'd be surprised," Pereira said. "The brain tends to drift, with multiple processes taking place at the same time. If a person thinks about a table, then a lot of related words will come to mind, too. And we thought that if we want to understand what is in a person's mind when they think about anything concrete, we can follow those words."

Pereira and his co-authors worked from fMRI images of brain activity that a team led by Just and fellow Carnegie Mellon researcher Tom Mitchell, a professor of computer science, published in the journal Science in 2008. For those scans, nine people were presented with the word and picture of five concrete objects from 12 categories. The drawing and word for the 60 total objects were displayed in random order until each had been shown six times. Each time an image and word appeared, participants were asked to visualize the object and its properties for three seconds as the fMRI scanner recorded their brain activity.

Matching words and brain activity with related topics

Separately, Pereira and Detre constructed a list of topics with which to categorize the fMRI data. They used a computer program developed by Princeton Associate Professor of Computer Science David Blei to condense 3,500 articles about concrete objects from the online encyclopedia Wikipedia into all the topics the articles covered. The articles included a broad array of subjects, such as an airplane, heroin, birds and manual transmission. The program came up with 40 possible topics -- such as aviation, drugs, animals or machinery -- with which the articles could relate. Each topic was defined by the words most associated with it.

The computer ultimately created a database of topics and associated words that were free from the researchers' biases, Pereira said.

"We let the software discern the factors that make up meaning rather than stipulating it ourselves," he said. "There is always a danger that we could impose our preconceived notions of the meaning words have. Plus, I can identify and describe, for instance, a bird, but I don't think I can list all the characteristics that make a bird a bird. So instead of postulating, we let the computer find semantic threads in an unsupervised manner."




The topic database let the researchers objectively arrange the fMRI images by subject matter, Pereira said. To do so, the team searched the brain scans of related objects for similar activity to determine common brain patterns for an entire subject, Pereira said. The neural response for thinking about "furniture," for example, was determined by the common patterns found in the fMRI images for "table," "chair," "bed," "desk" and "dresser." At the same time, the team established all the words associated with "furniture" by matching each fMRI image with related words from the Wikipedia-based list.

Based on the similar brain activity and related words, Pereira, Botvinick and Detre concluded that the same neural response would appear whenever a person thought of any of the words related to furniture, Pereira said. And a scientist analyzing that brain activity would know that person was thinking of furniture. The same would follow for any topic.

Using images to predict the words on a person's mind
Finally, to ensure their method was accurate, the researchers conducted a blind comparison of each of the 60 fMRI images against each of the others. Without knowing the objects the pair of scans pertained to, Pereira and his colleagues estimated the presence of certain topics on a participant's mind based solely on the fMRI data. Knowing the applicable Wikipedia topics for a given brain image, and the keywords for each topic, they could predict the most likely set of words associated with the brain image.

The researchers found that they could confidently determine from an fMRI image the general topic on a participant's mind, but that deciphering specific objects was trickier, Pereira said. For example, they could compare the fMRI scan for "carrot" against that for "cow" and safely say that at the time the participant had thought about vegetables in the first example instead of animals. In turn, they could say that the person most likely thought of other words related to vegetables, as opposed to words related to animals.

On the other hand, when the scan for "carrot" was compared to that for "celery," Pereira and his colleagues knew the participant had thought of vegetables, but they could not identify related words unique to either object.

One aim going forward, Pereira said, is to fine-tune the group's method to be more sensitive to such detail. In addition, he and Botvinick have begun performing fMRI scans on people as they read in an effort to observe the various topics the mind accesses.

"Essentially," Pereira said, "we have found a way to generally identify mental content through the text related to it. We can now expand that capability to even further open the door to describing thoughts that are not amenable to being depicted with pictures."

Story Source:
The above story is reprinted (with editorial adaptations) from materials provided by Princeton University.

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Speaking and Understanding Speech Share the Same Parts of the Brain

Speaking and Understanding Speech Share the Same Parts of the Brain

  9:13:00 AM    Science Lover

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The brain has two big tasks related to speech: making it and understanding it. Psychologists and others who study the brain have debated whether these are really two separate tasks or whether they both use the same regions of the brain. Now, a new study, published in the August issue of Psychological Science, a journal of the Association for Psychological Science, finds that speaking and understanding speech share the same parts of the brain, with one difference: we don't need the brain regions that control the movements of lips, teeth, and so on to understand speech.

New research finds that speaking and understanding 
speech share the same parts of the brain. 
(Credit: © Artsem Martysiuk / Fotolia)

Most studies of how speech works in the brain focuses on comprehension. That's mostly because it's easier to image the brains of people who are listening quietly; talking makes the head move, which is a problem when you're measuring the brain. But now, the Donders Institute at the Radboud University Nijmegen, where the study was conducted, has developed technology that allows recording from a moving brain.

Laura Menenti, a Postdoctoral Research Associate at the University of Glasgow, co-wrote the paper along with Peter Hagoort of Radboud University Nijmegen and the Max Planck Institute for Psycholinguistics, Sarah Gierhan and Katrien Segaert. Menenti was initially interested in how the brain produces grammatical sentences and wanted to track the process of producing a sentence in its entirety; looking not only at its grammatical structure but also at its meaning. "What made this particularly exciting to us was that no one had managed to perform such a study before, meaning that we could explore an almost completely new topic," says Menenti.




The authors used functional MRI technology to measure brain activity in people who were either listening to sentences or speaking sentences. The other problem with measuring brain activity in people who are speaking is that you have to get them to say the right kind of sentence. The authors accomplished this with a picture of an action -- a man strangling a woman, say -- with one person colored green and one colored red to indicate their order in the sentence. This prompted people to say either "The man is strangling the woman" or "The woman is strangled by the man." (The experiments were all carried out in Dutch.)

From this, the researchers were able to tell where in the brain three different speech tasks (computing meaning, coming up with the words, and building a grammatical sentence) -- were taking place. They found that the same areas were activated for each of these tasks in people who were speaking and people who were listening to sentences. However, although some studies have suggested that while people are listening to speech, they silently articulate the words in order to understand them, the authors found no involvement of motor regions when people were listening.

According to Menenti, though the study was largely designed to answer a specific theoretical question, it also points towards some useful avenues for treatment of people with language-related problems. It suggests that while it sometimes seems that people with comprehension problems may have intact production, and vice versa, this may not necessarily be the case. According to Menenti, "Our data suggest that these problems would be expected to always at least partly coincide. On the other, our data confirm the idea that many different processes in the language system, such as understanding meaning or grammar, can at least partly, be damaged independently of each other."

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How Social Pressure Can Affect What We Remember: Scientists Track Brain Activity as False Memories Are Formed

How Social Pressure Can Affect What We Remember: Scientists Track Brain Activity as False Memories Are Formed

  10:02:00 AM    Science Lover

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How easy is it to falsify memory? New research at the Weizmann Institute shows that a bit of social pressure may be all that is needed. The study, which appears in the journal Science, reveals a unique pattern of brain activity when false memories are formed -- one that hints at a surprising connection between our social selves and memory.

New research reveals a unique pattern of brain 
activity when false memories are formed -- one 
that hints at a surprising connection between 
our social selves and memory. (Credit: Image 
courtesy of Weizmann Institute of Science)

The experiment, conducted by Prof. Yadin Dudai and research student Micah Edelson of the Institute's Neurobiology Department with Prof. Raymond Dolan and Dr. Tali Sharot of University College London, took place in four stages. In the first, volunteers watched a documentary film in small groups. Three days later, they returned to the lab individually to take a memory test, answering questions about the film. They were also asked how confident they were in their answers.

They were later invited back to the lab to retake the test while being scanned in a functional MRI (fMRI) that revealed their brain activity. This time, the subjects were also given a "lifeline": the supposed answers of the others in their film viewing group (along with social-media-style photos). Planted among these were false answers to questions the volunteers had previously answered correctly and confidently. The participants conformed to the group on these "planted" responses, giving incorrect answers nearly 70% of the time.

But were they simply conforming to perceived social demands, or had their memory of the film actually undergone a change? To find out, the researchers invited the subjects back to the lab to take the memory test once again, telling them that the answers they had previously been fed were not those of their fellow film watchers, but random computer generations. Some of the responses reverted back to the original, correct ones, but close to half remained erroneous, implying that the subjects were relying on false memories implanted in the earlier session.

An analysis of the fMRI data showed differences in brain activity between the persistent false memories and the temporary errors of social compliance. The most outstanding feature of the false memories was a strong co-activation and connectivity between two brain areas: the hippocampus and the amygdala. The hippocampus is known to play a role in long-term memory formation, while the amygdala, sometimes known as the emotion center of the brain, plays a role in social interaction. The scientists think that the amygdala may act as a gateway connecting the social and memory processing parts of our brain; its "stamp" may be needed for some types of memories, giving them approval to be uploaded to the memory banks. Thus social reinforcement could act on the amygdala to persuade our brains to replace a strong memory with a false one.

Prof. Yadin Dudai's research is supported by the Norman and Helen Asher Center for Human Brain Imaging, which he heads; the Nella and Leon Benoziyo Center for Neurological Diseases; the Carl and Micaela Einhorn-Dominic Institute of Brain Research, which he heads; the Marc Besen and the Pratt Foundation, Australia; Lisa Mierins Smith, Canada; Abe and Kathryn Selsky Memorial Research Project; and Miel de Botton, UK. Prof. Dudai is the incumbent of the Sara and Michael Sela Professorial Chair of Neurobiology.

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Researchers can predict future actions from human brain activity

Researchers can predict future actions from human brain activity

  2:42:00 AM    Science Lover

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Bringing the real world into the brain scanner, researchers at The University of Western Ontario from The Centre for Brain and Mind can now determine the action a person was planning, mere moments before that action is actually executed.

A volunteer completes tasks while in the functional magnetic
imaging (fMRI) machine. This research project focuses
on understanding how the human brain plans actions.

The findings were published this week in the prestigious Journal of Neuroscience, in the paper, "Decoding Action Intentions from Preparatory Brain Activity in Human Parieto-Frontal Networks."



"This is a considerable step forward in our understanding of how the human brain plans actions," says Jason Gallivan, a Western Neuroscience PhD student, who was the first author on the paper.

University of Western Ontario researchers Jody Culham and Jason Gallivan describe how they can use a fMRI to determine the action a person was planning, mere moments before that action is actually executed. Credit: The University of Western Ontario

Over the course of the one-year study, human subjects had their brain activity scanned using functional magnetic resonance imaging (fMRI) while they performed one of three hand movements: grasping the top of an object, grasping the bottom of the object, or simply reaching out and touching the object. The team found that by using the signals from many brain regions, they could predict, better than chance, which of the actions the volunteer was merely intending to do, seconds later.

"Neuroimaging allows us to look at how action planning unfolds within human brain areas without having to insert electrodes directly into the human brain. This is obviously far less intrusive," explains Western Psychology professor Jody Culham, who was the paper's senior author.

Gallivan says the new findings could also have important clinical implications: "Being able to predict a human's desired movements using brain signals takes us one step closer to using those signals to control prosthetic limbs in movement-impaired patient populations, like those who suffer from spinal cord injuries or locked-in syndrome."

                    Brain timecourse video of subject's fMRI image during experiment

Provided by University of Western Ontario

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Neurorobotics Reveals Brain Mechanisms of Self-Consciousness

Neurorobotics Reveals Brain Mechanisms of Self-Consciousness

  12:57:00 AM    Science Lover

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A new study uses creative engineering to unravel brain mechanisms associated with one of the most fundamental subjective human feelings: self-consciousness. The research, published in the April 28 issue of the journal Neuron, identifies a brain region called the temporo-parietal junction (TPJ) as being critical for the feeling of being an entity localized at a particular position in space and for perceiving the world from this position and perspective.

A new study uses creative engineering to unravel brain 
mechanisms associated with one of the most fundamental 
subjective human feelings: self-consciousness. The research 
identifies a brain region called the temporo-parietal junction 
(TPJ) as being critical for the feeling of being an entity 
localized at a particular position in space and for perceiving 
the world from this position and perspective. 
(Credit: © paul prescott / Fotolia)

Recent theories of self-consciousness highlight the importance of integrating many different sensory and motor signals, but it is not clear how this type of integration induces subjective states such as self-location ("Where am I in space?") and the first-person perspective ("From where do I perceive the world?"). Studies of neurological patients reporting out-of-body experiences have provided some evidence that brain damage interfering with the integration of multisensory body information may lead to pathological changes of the first-person perspective and self-location. However, it is still not known how to examine brain mechanisms associated with self-consciousness.

"Recent behavioral and physiological work, using video-projection and various visuo-tactile conflicts showed that self-location can be manipulated in healthy participants," explains senior study author, Dr. Olaf Blanke, from the Ecole Polytechnique Fédérale de Lausanne in Switzerland. "However, so far these experimental findings and techniques do not allow for the induction of changes in the first-person perspective and have not been integrated with neuroimaging, probably because the experimental set-ups require participants to sit, stand, or move. This makes it very difficult to apply and film the visuo-tactile conflicts on the participant's body during standard brain imaging techniques."

Making use of inventive neuroimaging-compatible robotic technology that was developed by Dr. Gassert's group at the Swiss Federal Institute of Technology in Zurich, Dr. Blanke and colleagues studied healthy subjects and employed specific bodily conflicts that induced changes in self-location and first-person perspective while simultaneously monitoring brain activity with functional magnetic resonance imaging. They observed that TPJ activity reflected experimental changes in self-location and first-person perspective. The researchers also completed a large study of neurological patients with out-of-body experiences and found that brain damage was localized to the TPJ.

"Our results illustrate the power of merging technologies from engineering with those of neuroimaging and cognitive science for the understanding of the nature of one of the greatest mysteries of the human mind: self-consciousness and its neural mechanisms," concludes Dr. Blanke. "Our findings on experimentally and pathologically induced altered states of self-consciousness present a powerful new research technology and reveal that TPJ activity reflects one of the most fundamental subjective feelings of humans: the feeling that 'I' am an entity that is localized at a position in space and that 'I' perceive the world from here."

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Emotional Signals Are Chemically Encoded in Tears, Researchers Find

Emotional Signals Are Chemically Encoded in Tears, Researchers Find

  9:47:00 AM    Science Lover

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Emotional crying is a universal, uniquely human behavior. When we cry, we clearly send all sorts of emotional signals. In a paper published online January 6 in Science Express, scientists at the Weizmann Institute have demonstrated that some of these signals are chemically encoded in the tears themselves. Specifically, they found that merely sniffing a woman's tears -- even when the crying woman is not present -- reduces sexual arousal in men.

Scientists have found that certain emotional signals are chemically encoded in tears. (Credit: iStockphoto/Arpad Nagy-Bagoly)

Humans, like most animals, expel various compounds in body fluids that give off subtle messages to other members of the species. A number of studies in recent years, for instance, have found that substances in human sweat can carry a surprising range of emotional and other signals to those who smell them.

But tears are odorless. In fact, in a first experiment led by Shani Gelstein, Yaara Yeshurun and their colleagues in the lab of Prof. Noam Sobel in the Weizmann Institute's Neurobiology Department, the researchers first obtained emotional tears from female volunteers watching sad movies in a secluded room and then tested whether men could discriminate the smell of these tears from that of saline. The men could not.

In a second experiment, male volunteers sniffed either tears or a control saline solution, and then had these applied under their nostrils on a pad while they made various judgments regarding images of women's faces on a computer screen. The next day, the test was repeated -- the men who were previously exposed to tears getting saline and vice versa. The tests were double blinded, meaning neither the men nor the researchers performing the trials knew what was on the pads. The researchers found that sniffing tears did not influence the men's estimates of sadness or empathy expressed in the faces. To their surprise, however, sniffing tears negatively affected the sex appeal attributed to the faces.

To further explore the finding, male volunteers watched emotional movies after similarly sniffing tears or saline. Throughout the movies, participants were asked to provide self-ratings of mood as they were being monitored for such physiological measures of arousal as skin temperature, heart rate, etc. Self-ratings showed that the subjects' emotional responses to sad movies were no more negative when exposed to women's tears, and the men "smelling" tears showed no more empathy. They did, however, rate their sexual arousal a bit lower. The physiological measures, however, told a clearer story. These revealed a pronounced tear-induced drop in physiological measures of arousal, including a significant dip in testosterone -- a hormone related to sexual arousal.

Finally, in a fourth trial, Sobel and his team repeated the previous experiment within an fMRI machine that allowed them to measure brain activity. The scans revealed a significant reduction in activity levels in brain areas associated with sexual arousal after the subjects had sniffed tears.

Sobel said, "This study raises many interesting questions. What is the chemical involved? Do different kinds of emotional situations send different tear-encoded signals? Are women's tears different from, say, men's tears? Children's tears? This study reinforces the idea that human chemical signals -- even ones we're not conscious of -- affect the behavior of others."

Human emotional crying was especially puzzling to Charles Darwin, who identified functional antecedents to most emotional displays -- for example, the tightening of the mouth in disgust, which he thought originated as a response to tasting spoiled food. But the original purpose of emotional tears eluded him. The current study has offered an answer to this riddle: Tears may serve as a chemosignal. Sobel points out that some rodent tears are known to contain such chemical signals. "The uniquely human behavior of emotional tearing may not be so uniquely human after all," he says.

The work was authored by Shani Gelstein, Yaara Yeshurun, Liron Rozenkrantz, Sagit Shushan, Idan Frumin, Yehudah Roth and Noam Sobel, was conducted in collaboration with the Edith Wolfson Medical Center, Holon.

Prof. Noam Sobel's research is supported by the James S. McDonnell Foundation 21st Century Science Scholar in Understanding Human Cognition Program; the Minerva Foundation; the European Research Council; and Regina Wachter, NY.

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Brain Regions Can Switch Functions in Young

Brain Regions Can Switch Functions in Young

  1:52:00 AM    Science Lover

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A new paper from MIT neuroscientists, in collaboration with Alvaro Pascual-Leone at Beth Israel Deaconess Medical Center, offers evidence that it is easier to rewire the brain early in life. The researchers found that a small part of the brain's visual cortex that processes motion became reorganized only in the brains of subjects who had been born blind, not those who became blind later in life.

Scientists offer evidence that it is easier to rewire the 
brain early in life. Researchers found that a small part 
of the brain's visual cortex that processes motion became
reorganized only in the brains of subjects who had been 
born blind, not those who became blind later in life.
(Credit: iStockphoto/Vasiliy Yakobchuk)

The new findings, described in the Oct. 14 issue of the journal Current Biology, shed light on how the brain wires itself during the first few years of life, and could help scientists understand how to optimize the brain's ability to be rewired later in life. That could become increasingly important as medical advances make it possible for congenitally blind people to have their sight restored, said MIT postdoctoral associate Marina Bedny, lead author of the paper.

In the 1950s and '60s, scientists began to think that certain brain functions develop normally only if an individual is exposed to relevant information, such as language or visual information, within a specific time period early in life. After that, they theorized, the brain loses the ability to change in response to new input.

Animal studies supported this theory. For example, cats blindfolded during the first months of life are unable to see normally after the blindfolds are removed. Similar periods of blindfolding in adulthood have no effect on vision.

However, there have been indications in recent years that there is more wiggle room than previously thought, said Bedny, who works in the laboratory of MIT assistant professor Rebecca Saxe, also an author of the Current Biology paper. Many neuroscientists now support the idea of a period early in life after which it is difficult, but not impossible, to rewire the brain.

Bedny, Saxe and their colleagues wanted to determine if a part of the brain known as the middle temporal complex (MT/MST) can be rewired at any time or only early in life. They chose to study MT/MST in part because it is one of the most studied visual areas. In sighted people, the MT region is specialized for motion vision.

In the few rare cases where patients have lost MT function in both hemispheres of the brain, they were unable to sense motion in a visual scene. For example, if someone poured water into a glass, they would see only a standing, frozen stream of water.

Previous studies have shown that in blind people, MT is taken over by sound processing, but those studies didn't distinguish between people who became blind early and late in life.

In the new MIT study, the researchers studied three groups of subjects -- sighted, congenitally blind, and those who became blind later in life (age nine or older). Using functional magnetic resonance imaging (fMRI), they tested whether MT in these subjects responded to moving sounds -- for example, approaching footsteps.

The results were clear, said Bedny. MT reacted to moving sounds in congenitally blind people, but not in sighted people or people who became blind at a later age.

This suggests that in late-blind individuals, the visual input they received in early years allowed the MT complex to develop its typical visual function, and it couldn't be remade to process sound after the person lost sight. Congenitally blind people never received any visual input, so the region was taken over by auditory input after birth.

"We need to think of early life as a window of opportunity to shape how the brain works," said Bedny. "That's not to say that later experience can't alter things, but it's easier to get organized early on."

Bedny believes that by better understanding how the brain is wired early in life, scientists may be able to learn how to rewire it later in life. There are now very few cases of sight restoration, but if it becomes more common, scientists will need to figure out how to retrain the patient's brain so it can process the new visual input.

"The unresolved question is whether the brain can relearn, and how that learning differs in an adult brain versus a child's brain," said Bedny.

Bedny hopes to study the behavioral consequences of the MT switch in future studies. Those would include whether blind people have an advantage over sighted people in auditory motion processing, and if they have a disadvantage if sight is restored.

Editor's Note: This article is not intended to provide medical advice, diagnosis or treatment.

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Turning Thoughts into Words A new approach allows more information to be extracted from the brain.

Turning Thoughts into Words A new approach allows more information to be extracted from the brain.

  2:23:00 AM    Science Lover

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Brain-computer interfaces could someday provide a lifeline to "locked-in" patients, who are unable to talk or move but are aware and awake. Many of these patients can communicate by blinking their eyes, but turning blinks into words is time-consuming and exhausting.

Scientists in Utah have now demonstrated a way to determine which of 10 distinct words a person is thinking by recording the electrical activity from the surface of the brain.

Brian interface: The micro electrodes
shown here were used to record brain
signals in order to decode ten words
from a patient’s thoughts.
Credit: Spencer Kellis, University of Utah

The new technique involves training algorithms to recognize specific brain signals picked up by an array of nonpenetrating electrodes placed over the language centers of the brain, says Spencer Kellis, one of the bioengineers who carried out the work at the University of Utah, in Salt Lake City. The approach used is known as electrocorticography (ECoG). The group was able to identify the words "yes," "no," "hot, "cold," "thirsty," "hungry," "hello," "goodbye," "more," and "less" with an accuracy of 48 percent.

"The accuracy definitely needs to be improved," says Kellis. "But we have shown the information is there."

Individual words have been decoded from brain signals in the past using functional magnetic resonance imaging (fMRI), says Eric Leuthardt, director of the Center for Innovation in Neuroscience and Technology at Washington University School of Medicine in St. Louis, Missouri. This is the first time that the feat has been performed using ECoG, a far more practical and portable approach than fMRI, he says.

Working with colleagues Bradley Greger and Paul House, Kellis placed 16 electrodes on the surface of the brain of a patient being treated for epilepsy. The electrodes recorded signals from the facial motor cortex--an area of the brain that controls face muscles during speech--and over the Wernicke's area, part of the cerebral cortex that is linked with language. To train the algorithm, signals were analyzed as the patient was asked to repeatedly utter the 10 words.

ECoG has long been used to locate the source of epileptic seizures in the brain. But electrodes used are typically several hundred microns in size and are positioned centimeters apart, says Kellis. "The brain is doing processing at a much finer spatial scale than is really detectable by these standard clinical electrodes," he says. The Utah team used a new type of microelectrode array developed by PMT Neurosurgical. The electrodes are much smaller--40 microns in size--and are separated by a couple of millimeters.

It's possible to use less invasive techniques, such as electroencephalography (EEG), which places electrodes on the scalp, to enable brain-to-computer communications. Adrian Owen, a senior scientist in the Cognition and Brain Sciences Unit at the University of Cambridge, UK, has shown that EEG signals can be used to allow people in a persistent vegetative state to communicate "yes" and "no."

But with EEG, many of the signals are filtered out by the skull, says Leuthardt. "What's really nice about ECoG is its potential to give us a lot more information," he says.

Decoding 10 words is "very cool," says Owen, but the accuracy will need to improve dramatically, given the patients the technology is aimed at. "I don't think even 60 percent or 70 percent accuracy is going to work for patients who cannot communicate in any other way and where there is no other margin for verification," he says.

Ultimately, the hope is that ECoG will enable much more sophisticated communication. Last year Leuthardt showed that ECoG could be used to decode vowel and consonant sounds--an approach that might eventually be used to reconstruct a much larger number of complete words.

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Brain Coprocessors The need for operating systems to help brains and machines work together.

Brain Coprocessors The need for operating systems to help brains and machines work together.

  9:50:00 AM    Science Lover

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The last few decades have seen a surge of invention of technologies that enable the observation or perturbation of information in the brain. Functional MRI, which measures blood flow changes associated with brain activity, is being explored for purposes as diverse as lie detection, prediction of human decision making, and assessment of language recovery after stroke.

Implanted electrical stimulators, which enable control of neural circuit activity, are borne by hundreds of thousands of people to treat conditions such as deafness, Parkinson's disease, and obsessive-compulsive disorder. And new methods, such as the use of light to activate or silence specific neurons in the brain, are being widely utilized by researchers to reveal insights into how to control neural circuits to achieve therapeutically useful changes in brain dynamics. We are entering a neurotechnology renaissance, in which the toolbox for understanding the brain and engineering its functions is expanding in both scope and power at an unprecedented rate.

This toolbox has grown to the point where the strategic utilization of multiple neurotechnologies in conjunction with one another, as a system, may yield fundamental new capabilities, both scientific and clinical, beyond what they can offer alone. For example, consider a system that reads out activity from a brain circuit, computes a strategy for controlling the circuit so it enters a desired state or performs a specific computation, and then delivers information into the brain to achieve this control strategy. Such a system would enable brain computations to be guided by predefined goals set by the patient or clinician, or adaptively steered in response to the circumstances of the patient's environment or the instantaneous state of the patient's brain.

Some examples of this kind of "brain coprocessor" technology are under active development, such as systems that perturb the epileptic brain when a seizure is electrically observed, and prosthetics for amputees that record nerves to control artificial limbs and stimulate nerves to provide sensory feedback. Looking down the line, such system architectures might be capable of very advanced functions--providing just-in-time information to the brain of a patient with dementia to augment cognition, or sculpting the risk-taking profile of an addiction patient in the presence of stimuli that prompt cravings.

Given the ever-increasing number of brain readout and control technologies available, a generalized brain coprocessor architecture could be enabled by defining common interfaces governing how component technologies talk to one another, as well as an "operating system" that defines how the overall system works as a unified whole--analogous to the way personal computers govern the interaction of their component hard drives, memories, processors, and displays. Such a brain coprocessor platform could facilitate innovation by enabling neuroengineers to focus on neural prosthetics at an algorithmic level, much as a computer programmer can work on a computer at a conceptual level without having to plan the fate of every individual bit. In addition, if new technologies come along, e.g., a new kind of neural recording technology, they could be incorporated into a system, and in principle rapidly coupled to existing computation and perturbation methods, without requiring the heavy readaptation of those other components.

Developing such brain coprocessor architectures would take some work--in particular, it would require technologies standardized enough, or perhaps open enough, to be interoperable in a variety of combinations. Nevertheless, much could be learned from developing relatively simple prototype systems. For example, recording technologies by themselves can report brain activity, but cannot fully attest to the causal contribution that the observed brain activity makes to a specific behavioral or clinical outcome; control technologies can input information into neural targets, but by themselves their outcomes might be difficult to interpret due to endogenous neural information and unobserved neural processing. These scientific issues can be disambiguated by rudimentary brain coprocessors, built with readily available off-the-shelf components, that use recording technologies to assess how a given neural circuit perturbation alters brain dynamics. Such explorations may begin to reveal principles governing how best to control a circuit--revealing the neural targets and control strategies that most efficaciously lead to a goal brain state or behavioral effect, and thus pointing the way to new therapeutic strategies. Miniature, implantable brain coprocessors might be able to support new kinds of personalized medicine, for example continuously adapting a neural control strategy to the goals, state, environment, and history of an individual patient--important powers, given the dynamic nature of many brain disorders.

In the future, the computational module of a brain coprocessor may be powerful enough to assist in high-level human cognition or complex decision making. Of course, the augmentation of human intelligence has been one of the key goals of computer engineers for well over half a century. Indeed, if we relax the definition of brain coprocessor just a bit, so as not to require direct physical access to the brain, many consumer technologies being developed today are converging upon brain coprocessor-like architectures. A large number of new technologies are attempting to discover information useful to a user and to deliver this information to the user in real time. Also, these discovery and delivery processes are increasingly shaped by the environment (e.g., location) and history (e.g., social interactions, searches) of the user. Thus we are seeing a departure from the classical view (as initially anticipated by early thinkers about human-machine symbiosis such as J. C. R. Licklider) in which computers receive goals from humans, perform defined computations, and then provide the results back to humans.

Of course, giving machines the authority to serve as proactive human coprocessors, and allowing them to capture our attention with their computed priorities, has to be considered carefully, as anyone who has lost hours due to interruption by a slew of social-network updates or search-engine alerts can attest. How can we give the human brain access to increasingly proactive coprocessing technologies without losing sight of our overarching goals? One idea is to develop and deploy metrics that allow us to evaluate the IQ of a human plus a coprocessor, working together--evaluating the performance of collaborating natural and artificial intelligences in a broad battery of problem-solving contexts. After all, humans with Internet-based brain coprocessors (e.g., laptops running Web browsers) may be more distractible if the goals include long, focused writing tasks, but they may be better at synthesizing data broadly from disparate sources; a given brain coprocessor configuration may be good for some problems but bad for others. Thinking of emerging computational technologies as brain coprocessors forces us to think about them in terms of the impacts they have on the brain, positive and negative, and importantly provides a framework for thoughtfully engineering their direct, as well as their emergent, effects.

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Gain and Loss in Optimistic Versus Pessimistic Brains

Gain and Loss in Optimistic Versus Pessimistic Brains

  9:28:00 PM    Science Lover

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Our belief as to whether we will likely succeed or fail at a given task -- and the consequences of winning or losing -- directly affects the levels of neural effort put forth in movement-planning circuits in the human cortex, according to a new brain-imaging study by neuroscientists at the California Institute of Technology (Caltech).

Subjects who reported they were "good" at the task 
(optimists) showed highest brain activity when they 
expected large gains; subjects who thought they 
performed "poorly" (pessimists) showed highest brain 
activity when they tried to avoid large losses. Yellow 
regions show brain areas with highest motor planning 
activity; green and red regions depict areas that 
exhibited the strongest modulation in activity 
relative to the subjective absolute value. 
(Credit: Igor Kagan/Caltech)

A paper about the research -- led by Richard A. Andersen, the James G. Boswell Professor of Neuroscience at Caltech -- appears in the August issue of PLoS Biology.

Research in Andersen's laboratory includes work to understand the neural mechanisms of action planning and decision-making. The lab is working toward the development of implanted neural prosthetic devices that would serve as an interface between severely paralyzed individuals' brain signals and artificial limbs -- allowing their planned actions to control the limbs' movements.

In particular, Andersen's group focuses on a high-level area of the brain called the posterior parietal cortex (PPC), where sensory stimuli are transformed into movement plans.

In the current study, Andersen and his colleagues used a functional magnetic resonance imaging scanner to monitor activity in the PPC and other brain areas in subjects who were asked to perform a complex task. Using a trackball, they had to move a cursor to a number of memorized locations on a computer screen, in a predetermined order.

"The subjects were given 1 second to memorize the sequence, 15 seconds to plan their movements in advance, and then only 10 seconds to finish the task," says Igor Kagan, a senior research fellow in biology in the Andersen lab, and a coauthor of the PLoS Biology paper. "We intentionally made the task hard -- I couldn't do it myself," he says.

The subjects received monetary compensation for participating in the experiment, with their earnings tied to their performance. The amount of money that would be gained (or lost) varied from trial to trial. In one trial, for example, success might net the participant $5, while failure would cause him to lose $1. In another trial, completing the task correctly would earn $1, while failure would cost $5. Alternatively, success and failure might produce an equivalent gain or loss (say, +$5 versus -$5). The subjects were told the stakes in advance of each trial.

Prior to receiving their earnings, the subjects reported -- in a post-test questionnaire -- how they perceived their performance. Interestingly, those perceptions did not correlate with their actual performance; individuals in the group who believed they had performed well were just as likely to have performed poorly, and vice versa for individuals in the group who believed they had done badly.

Furthermore, the researchers found that the pattern of brain activity in the PPC was linked to how well the subjects believed they had done on the tasks -- that is, their subjective perception of their performance, rather than their actual performance -- as well as by the monetary gain or loss they expected from success or failure.

How hard an individual subject's brain "worked" at the task was dependent upon their personal approach. For example, Andersen says, "subjects who are 'optimists' and believe they are doing well will put out the most effort -- and exhibit an increase in activity in their PPC -- when they expect to earn a larger reward for being successful." Conversely, those individuals who believe they are doing poorly -- the pessimists -- show the most brain activity when there is a higher price for failure.

"They're trying harder to avoid losses and seem to care less about potential gains," Kagan adds.

"This study demonstrates that the process of planning and action is influenced by our subjective, but often incorrect, idea of how well we are doing, as well as by the potential gain or loss," Andersen says. The results suggest that the cortical areas involved in planning actions are also likely to be involved in decision-making, and take into account higher-order cognitive as well as subjective factors when deciding among potential actions.

The paper was also coauthored by former Caltech graduate student Asha Iyer, the first author of the study, now a resident at Mount Sinai Medical School, and former Caltech postdoctoral fellow Axel Lindner, now a group leader at the University of Tübingen. The research was funded by the Gordon and Betty Moore Foundation, the James G. Boswell Foundation, and the National Eye Institute.

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