Reminiscing can help boost mental performance

To solve a mental puzzle, the brain’s executive control network for externally focused, goal-oriented thinking must activate, while the network for internally directed thinking like daydreaming must be turned down to avoid interference – or so we thought.

New research led by Cornell University neuroscientist Nathan Spreng shows for the first time that engaging brain areas linked to so-called “off-task” mental activities (such as mind-wandering and reminiscing) can actually boost performance on some challenging mental tasks. The results advance our understanding of how externally and internally focused neural networks interact to facilitate complex thought, the authors say.

“The prevailing view is that activating brain regions referred to as the default network impairs performance on attention-demanding tasks because this network is associated with behaviors such as mind-wandering,” said Spreng. “Our study is the first to demonstrate the opposite – that engaging the default network can also improve performance.”

There are plenty of neuroimaging studies showing that default network activation interferes with complex mental tasks – but in most, Spreng explained, the mental processes associated with default network conflict with task goals. If you start thinking about what you did last weekend while taking notes during a lecture, for example, your note-taking and ability to keep up will suffer.

Spreng and his team developed a new approach in which off-task processes such as reminiscing can support rather than conflict with the aims of the experimental task. Their novel task, “famous faces n-back,” tests whether accessing long-term memory about famous people, which typically engages default network brain regions, can support short-term memory performance, which typically engages executive control regions.

While undergoing brain scanning, 36 young adults viewed sets of famous and anonymous faces in sequence and were asked to identify whether the current face matched the one presented two faces back. The team found participants were faster and more accurate when matching famous faces than when matching anonymous faces and that this better short-term memory performance was associated with greater activity in the default network. The results show that activity in the default brain regions can support performance on goal-directed tasks when task demands align with processes supported by the default network, the authors say.

“Outside the laboratory, pursuing goals involves processing information filled with personal meaning – knowledge about past experiences, motivations, future plans and social context,” Spreng said. “Our study suggests that the default network and executive control networks dynamically interact to facilitate an ongoing dialogue between the pursuit of external goals and internal meaning.”

(Image caption: This image shows the brain’s default mode network, where memory and sensory information are stored. Credit: Marcus Raichle, Washington University)

What happens to your brain when your mind is at rest?

For many years, the focus of brain mapping was to examine changes in the brain that occur when people are attentively engaged in an activity. No one spent much time thinking about what happens to the brain when people are doing very little.

But Marcus Raichle, a professor of radiology, neurology, neurobiology and biomedical engineering at Washington University in St. Louis, has done just that. In the 1990s, he and his colleagues made a pivotal discovery by revealing how a specific area of the brain responds to down time.

"A great deal of meaningful activity is occurring in the brain when a person is sitting back and doing nothing at all," says Raichle, who has been funded by the National Science Foundation (NSF) Division of Behavioral and Cognitive Sciences in the Directorate for Social, Behavioral and Economic Sciences. "It turns out that when your mind is at rest, dispersed brain areas are chattering away to one another."

The results of these discoveries now are integral to studies of brain function in health and disease worldwide. In fact, Raichle and his colleagues have found that these areas of rest in the brain—the ones that ultimately became the focus of their work—often are among the first affected by Alzheimer’s disease, a finding that ultimately could help in early detection of this disorder and a much greater understanding of the nature of the disease itself.

For his pioneering research, Raichle this year was among those chosen to receive the prestigious Kavli Prize, awarded by The Norwegian Academy of Science and Letters. It consists of a cash award of $1 million, which he will share with two other Kavli recipients in the field of neuroscience.

His discovery was a near accident, actually what he calls “pure serendipity.” Raichle, like others in the field at the time, was involved in brain imaging, looking for increases in brain activity associated with different tasks, for example language response.

In order to conduct such tests, scientists first needed to establish a baseline for comparison purposes which typically complements the task under study by including all aspects of the task, other than just the one of interest.

"For example, a control task for reading words aloud might be simply viewing them passively," he says.

In the Raichle laboratory, they routinely required subjects to look at a blank screen. When comparing this simple baseline to the task state, Raichle noticed something.

"We didn’t specify that you clear your mind, we just asked subjects to rest quietly and don’t fall asleep," he recalls. "I don’t remember the day I bothered to look at what was happening in the brain when subjects moved from this simple resting state to engagement in an attention demanding task that might be more involved than simply increases in brain activity associated with the task.

"When I did so, I observed that while brain activity in some parts of the brain increased as expected, there were other areas that actually decreased their activity as if they had been more active in the ‘resting state,"’ he adds. "Because these decreases in brain activity were so dramatic and unexpected, I got into the habit of looking for them in all of our experiments. Their consistency both in terms of where they occurred and the frequency of their occurrence—that is, almost always—really got my attention. I wasn’t sure what was going on at first but it was just too consistent to not be real."

These observations ultimately produced ground-breaking work that led to the concept of a default mode of brain function, including the discovery of a unique fronto-parietal network in the brain. It has come to be known as the default mode network, whose regions are more active when the brain is not actively engaged in a novel, attention-demanding task.

"Basically we described a core system of the brain never seen before," he says. "This core system within the brain’s two great hemispheres increasingly appears to be playing a central role in how the brain organizes its ongoing activities"

The discovery of the brain’s default mode caused Raichle and his colleagues to reconsider the idea that the brain uses more energy when engaged in an attention-demanding task. Measurements of brain metabolism with PET (positron emission tomography) and data culled from the literature led them to conclude that the brain is a very expensive organ, accounting for about 20 percent of the body’s energy consumption in an adult human, yet accounting for only 2 percent of the body weight.

"The changes in activity associated with the performance of virtually any type of task add little to the overall cost of brain function," he continues. "This has initiated a paradigm shift in brain research that has moved increasingly to studies of the brain’s intrinsic activity, that is, its default mode of functioning."

Raichle, whose work on the role of this intrinsic brain activity on facets of consciousness was supported by NSF, is also known for his research in developing and using imaging techniques, such as positron emission tomography, to identify specific areas of the brain involved in seeing, hearing, reading, memory and emotion.

In addition, his team studied chemical receptors in the brain, the physiology of major depression and anxiety, and has evaluated patients at risk for stroke. Currently, he is completing research studying what happens to the brain under anesthesia.

"The brain is capable of so many things, even when you are not conscious," Raichle says. "If you are unconscious, the organization of the brain is maintained, but it is not the same as being awake."

Selectively Rewiring the Brain’s Circuitry to Treat Depression

On Star Trek, it is easy to take for granted the incredible ability of futuristic doctors to wave small devices over the heads of both humans and aliens, diagnose their problems through evaluating changes in brain activity or chemistry, and then treat behavior problems by selectively stimulating relevant brain circuits.

While that day is a long way off, transcranial magnetic stimulation (TMS) of the left dorsolateral prefrontal cortex does treat symptoms of depression in humans by placing a relatively small device on a person’s scalp and stimulating brain circuits. However, relatively little is known about how, exactly, TMS produces these beneficial effects.

Some studies have suggested that TMS may modulate atypical interactions between two large-scale neuronal networks, the frontoparietal central executive network (CEN) and the medial prefrontal-medial parietal default mode network (DMN). These two functional networks play important roles in emotion regulation and cognition.

In order to advance our understanding of the underlying antidepressant mechanisms of TMS, Drs. Conor Liston, Marc Dubin, and their colleagues conducted a longitudinal study to test this hypothesis.

The researchers used functional magnetic resonance imaging in 17 currently depressed patients to measure connectivity in the CEN and DMN networks both before and after a 25-day course of TMS. They also compared the connectivity in the depressed patients with a group of 35 healthy volunteers.

TMS normalized depression-related hyperconnectivity between the subgenual cingulate and medial prefrontal areas of the DMN, but did not alter connectivity in the CEN.

Liston, an Assistant Professor at Weill Cornell Medical College, further details their findings, “We found that connectivity within the DMN and between nodes of the DMN and CEN was elevated in depressed individuals compared to healthy volunteers at baseline and normalized after TMS. Additionally, individuals with greater baseline connectivity with subgenual anterior cingulate cortex – an important target for other antidepressant modalities – were more likely to respond to TMS.”

These findings indicate that TMS may act, in part, by selectively regulating network-level connectivity.

Dr. John Krystal, Editor of Biological Psychiatry, comments, “We are a long way from Star Trek, but even the current ability to link brain stimulation treatments for depression to the activity of particular brain circuits strikes me as incredible progress.”

Dubin, also an Assistant Professor at Weill Cornell Medical College, adds, “Our findings may inform future efforts to develop personalized strategies for treating depression with TMS based on the connectivity of an individual’s default mode network. Further, they may help triage to TMS only those patients most likely to respond.”

(Image caption: These figures show lagged maturation of connections in ADHD between the default mode network, involved in internally-directed thought (i.e., daydreaming) and shown on the left of each figure, and two brain networks involved in externally-focused attention, shown on the right of each figure. The width of each arc represents the number of lagged connections between two regions within each network. Connections that normally increase with age and that are hypoconnected in ADHD are shown in blue; connections that normally decrease with age and that are hyperconnected in ADHD are shown in red.)

Slow to mature, quick to distract: ADHD brain study finds slower development of key connections

A peek inside the brains of more than 750 children and teens reveals a key difference in brain architecture between those with attention deficit hyperactivity disorder and those without.

Kids and teens with ADHD, a new study finds, lag behind others of the same age in how quickly their brains form connections within, and between, key brain networks.

The result: less-mature connections between a brain network that controls internally-directed thought (such as daydreaming) and networks that allow a person to focus on externally-directed tasks. That lag in connection development may help explain why people with ADHD get easily distracted or struggle to stay focused.

What’s more, the new findings, and the methods used to make them, may one day allow doctors to use brain scans to diagnose ADHD — and track how well someone responds to treatment. This kind of neuroimaging “biomarker” doesn’t yet exist for ADHD, or any psychiatric condition for that matter.

The new findings come from a team in the University of Michigan Medical School’s Department of Psychiatry. They used highly advanced computing techniques to analyze a large pool of detailed brain scans that were publicly shared for scientists to study. Their results are published in the Proceedings of the National Academy of Sciences.

Lead author Chandra Sripada, M.D., Ph.D., and colleagues looked at the brain scans of 275 kids and teens with ADHD, and 481 others without it, using “connectomic” methods that can map interconnectivity between networks in the brain.

The scans, made using function magnetic resonance imaging (fMRI) scanners, show brain activity during a resting state. This allows researchers to see how a number of different brain networks, each specialized for certain types of functions, were “talking” within and amongst themselves.

The researchers found lags in development of connection within the internally-focused network, called the default mode network or DMN, and in development of connections between DMN and two networks that process externally-focused tasks, often called task-positive networks, or TPNs. They could even see that the lags in connection development with the two task-related networks — the frontoparietal and ventral attention networks — were located primarily in two specific areas of the brain.

The new findings mesh well with what other researchers have found by examining the physical structure of the brains of people with and without ADHD in other ways.

Such research has already shown alterations in regions within DMN and TPNs. So, the new findings build on that understanding and add to it. 

The findings are also relevant to thinking about the longitudinal course of ADHD from childhood to adulthood. For instance, some children and teens “grow out” of the disorder, while for others the disorder persists throughout adulthood. Future studies of brain network maturation in ADHD could shed light into the neural basis for this difference.

“We and others are interested in understanding the neural mechanisms of ADHD in hopes that we can contribute to better diagnosis and treatment,” says Sripada, an assistant professor and psychiatrist who holds a joint appointment in the U-M Philosophy department and is a member of the U-M Center for Computational Medicine and Bioinformatics. “But without the database of fMRI images, and the spirit of collaboration that allowed them to be compiled and shared, we would never have reached this point.”  

Sripada explains that in the last decade, functional medical imaging has revealed that the human brain is functionally organized into large-scale connectivity networks. These networks, and the connections between them, mature throughout early childhood all the way to young adulthood. “It is particularly noteworthy that the networks we found to have lagging maturation in ADHD are linked to the very behaviors that are the symptoms of ADHD,” he says. 

Studying the vast array of connections in the brain, a field called connectomics, requires scientists to be able to parse through not just the one-to-one communications between two specific brain regions, but the patterns of communication among thousands of nodes within the brain. This requires major computing power and access to massive amounts of data – which makes the open sharing of fMRI images so important.

“The results of this study set the stage for the next phase of this research, which is to examine individual components of the networks that have the maturational lag,” he says. “This study provides a coarse-grained understanding, and now we want to examine this phenomenon in a more fine-grained way that might lead us to a true biological marker, or neuromarker, for ADHD.”

Sripada also notes that connectomics could be used to examine other disorders with roots in brain connectivity – including autism, which some evidence has suggested stems from over-maturation of some brain networks, and schizophrenia, which may arise from abnormal connections. Pooling more fMRI data from people with these conditions, and depression, anxiety, bipolar disorder and more could boost connectomics studies in those fields.

(Image caption: At left, the brains of adults who had ADHD as children but no longer have it show synchronous activity between the posterior cingulate cortex (the larger red region) and the medial prefrontal cortex (smaller red region). At right, the brains of adults who continue to experience ADHD do not show this synchronous activity. Illustration: Jose-Luis Olivares/MIT, based on images courtesy of the researchers)

Inside the adult ADHD brain

About 11 percent of school-age children in the United States have been diagnosed with attention deficit hyperactivity disorder (ADHD). While many of these children eventually “outgrow” the disorder, some carry their difficulties into adulthood: About 10 million American adults are currently diagnosed with ADHD.

In the first study to compare patterns of brain activity in adults who recovered from childhood ADHD and those who did not, MIT neuroscientists have discovered key differences in a brain communication network that is active when the brain is at wakeful rest and not focused on a particular task. The findings offer evidence of a biological basis for adult ADHD and should help to validate the criteria used to diagnose the disorder, according to the researchers.

Diagnoses of adult ADHD have risen dramatically in the past several years, with symptoms similar to those of childhood ADHD: a general inability to focus, reflected in difficulty completing tasks, listening to instructions, or remembering details.

“The psychiatric guidelines for whether a person’s ADHD is persistent or remitted are based on lots of clinical studies and impressions. This new study suggests that there is a real biological boundary between those two sets of patients,” says MIT’s John Gabrieli, the Grover M. Hermann Professor of Health Sciences and Technology, professor of brain and cognitive sciences, and an author of the study, which appears in the June 10 issue of the journal Brain.

Shifting brain patterns

This study focused on 35 adults who were diagnosed with ADHD as children; 13 of them still have the disorder, while the rest have recovered. “This sample really gave us a unique opportunity to ask questions about whether or not the brain basis of ADHD is similar in the remitted-ADHD and persistent-ADHD cohorts,” says Aaron Mattfeld, a postdoc at MIT’s McGovern Institute for Brain Research and the paper’s lead author.

The researchers used a technique called resting-state functional magnetic resonance imaging (fMRI) to study what the brain is doing when a person is not engaged in any particular activity. These patterns reveal which parts of the brain communicate with each other during this type of wakeful rest.

“It’s a different way of using functional brain imaging to investigate brain networks,” says Susan Whitfield-Gabrieli, a research scientist at the McGovern Institute and the senior author of the paper. “Here we have subjects just lying in the scanner. This method reveals the intrinsic functional architecture of the human brain without invoking any specific task.”

In people without ADHD, when the mind is unfocused, there is a distinctive synchrony of activity in brain regions known as the default mode network. Previous studies have shown that in children and adults with ADHD, two major hubs of this network — the posterior cingulate cortex and the medial prefrontal cortex — no longer synchronize.

In the new study, the MIT team showed for the first time that in adults who had been diagnosed with ADHD as children but no longer have it, this normal synchrony pattern is restored. “Their brains now look like those of people who never had ADHD,” Mattfeld says.

“This finding is quite intriguing,” says Francisco Xavier Castellanos, a professor of child and adolescent psychiatry at New York University who was not involved in the research. “If it can be confirmed, this pattern could become a target for potential modification to help patients learn to compensate for the disorder without changing their genetic makeup.”

Lingering problems

However, in another measure of brain synchrony, the researchers found much more similarity between both groups of ADHD patients.

In people without ADHD, when the default mode network is active, another network, called the task positive network, is suppressed. When the brain is performing tasks that require focus, the task positive network takes over and suppresses the default mode network. If this reciprocal relationship degrades, the ability to focus declines.

Both groups of adult ADHD patients, including those who had recovered, showed patterns of simultaneous activation of both networks. This is thought to be a sign of impairment in executive function — the management of cognitive tasks — that is separate from ADHD, but occurs in about half of ADHD patients. All of the ADHD patients in this study performed poorly on tests of executive function. “Once you have executive function problems, they seem to hang in there,” says Gabrieli, who is a member of the McGovern Institute.

The researchers now plan to investigate how ADHD medications influence the brain’s default mode network, in hopes that this might allow them to predict which drugs will work best for individual patients. Currently, about 60 percent of patients respond well to the first drug they receive.

“It’s unknown what’s different about the other 40 percent or so who don’t respond very much,” Gabrieli says. “We’re pretty excited about the possibility that some brain measurement would tell us which child or adult is most likely to benefit from a treatment.”

How your brain works during meditation

Mindfulness. Zen. Acem. Meditation drumming. Chakra. Buddhist and transcendental meditation. There are countless ways of meditating, but the purpose behind them all remains basically the same: more peace, less stress, better concentration, greater self-awareness and better processing of thoughts and feelings.

But which of these techniques should a poor stressed-out wretch choose? What does the research say? Very little – at least until now.

Nondirective or concentrative meditation?

A team of researchers at the Norwegian University of Science and Technology (NTNU), the University of Oslo and the University of Sydney is now working to determine how the brain works during different kinds of meditation.

Different meditation techniques can actually be divided into two main groups. One type is concentrative meditation, where the meditating person focuses attention on his or her breathing or on specific thoughts, and in doing so, suppresses other thoughts. The other type may be called nondirective meditation, where the person who is meditating effortlessly focuses on his or her breathing or on a meditation sound, but beyond that the mind is allowed to wander as it pleases. Some modern meditation methods are of this nondirective kind.

“No one knows how the brain works when you meditate. That is why I’d like to study it,” says Jian Xu, who is a physician at St. Olavs Hospital and a researcher at the Department of Circulation and Medical Imaging at NTNU.

Two different ways to meditate

Fourteen people who had extensive experience with the Norwegian technique Acem meditation were tested in an MRI machine. In addition to simple resting, they undertook two different mental meditation activities, nondirective meditation and a more concentrative meditation task. The research team wanted to test people who were used to meditation because it meant fewer misunderstandings about what the subjects should actually be doing while they lay in the MRI machine.

The results were recently published in the journal “Frontiers in Human Neuroscience”.

Nondirective meditation led to higher activity than during rest in the part of the brain dedicated to processing self-related thoughts and feelings. When test subjects performed concentrative meditation, the activity in this part of the brain was almost the same as when they were just resting.

A place for the mind to rest

“I was surprised that the activity of the brain was greatest when the person’s thoughts wandered freely on their own, rather than when the brain worked to be more strongly focused,” said Xu. “When the subjects stopped doing a specific task and were not really doing anything special, there was an increase in activity in the area of the brain where we process thoughts and feelings. It is described as a kind of resting network. And it was this area that was most active during nondirective meditation.”

Provides greater freedom for the brain

“The study indicates that nondirective meditation allows for more room to process memories and emotions than during concentrated meditation,” says Svend Davanger, a neuroscientist at the University of Oslo, and co-author of the study.

“This area of the brain has its highest activity when we rest. It represents a kind of basic operating system, a resting network that takes over when external tasks do not require our attention. It is remarkable that a mental task like nondirective meditation results in even higher activity in this network than regular rest,” says Davanger.

Meditating researchers

Most of the research team behind the study do not practice meditation, although three do: Professors Are Holen and Øyvind Ellingsen from NTNU and Professor Svend Davanger from the University of Oslo.

Acem meditation is a technique that falls under the category of nondirective meditation. Davanger believes that good research depends on having a team that can combine personal experience with meditation with a critical attitude towards results.

“Meditation is an activity that is practiced by millions of people. It is important that we find out how this really works. In recent years there has been a sharp increase in international research on meditation. Several prestigious universities in the US  spend a great deal of money to research in the field. So I think it is important that we are also active,” says Davanger.

Research in the News: Brain at rest yields clues to origins of mental illness

While at rest, multiple regions of the brain remain engaged in a highly heritable, stable pattern of activity called the default mode network. Researchers have found that this network is often disrupted in people with schizophrenia and bipolar disorder, which appear to share underlying genetic causes. This network is often abnormal in their unaffected close relatives, suggesting common genetic roots.

Now researchers at the Yale University School of Medicine and the Institute of Living in Hartford have devised a method to simultaneously identify many genes that play a role in disrupting this network. “Previous studies have identified small numbers of different genes which each contribute in a small way to schizophrenia and bipolar disorder but tell us little overall about the development of psychosis in an individual,” said Godfrey Pearlson, professor of psychiatry and neurobiology and senior author of the study. “Now we have begun to identify markers for these conditions that consist of hundreds of such genes acting simultaneously in recognized pathways that will eventually help in our designing novel ways to intervene in the disease process.”

The study was published April 28 in the Proceedings of the National Academy of Sciences.

Depression is detectable in the blood

Researchers at the MedUni Vienna have demonstrated the possibility of using a blood test to detect depression. While blood tests for mental illnesses have until recently been regarded as impossible, a recent study clearly indicates that, in principle, depression can in fact be diagnosed in this way and this could become reality in the not too distant future.

Serotonin transporter (SERT) is a protein in the cell membrane that facilitates the transport of the neurotransmitter serotonin (popularly known as the “happiness hormone”) into the cell. In the brain, serotonin transporter regulates neural depression networks. Depressive conditions can frequently be caused by a lack of serotonin. As a result, the serotonin transporter is also the point of action for the major antidepressant drugs.

The serotonin transporter, however, also occurs in large quantities in numerous other organs such as the intestines or blood. Recent studies have shown that the serotonin transporter in the blood works in exactly the same way as in the brain. In the blood, it ensures that blood platelets maintain the appropriate concentration of serotonin in the blood plasma.

Researchers at the MedUni Vienna have now used functional magnetic resonance imaging of the brain and pharmacological investigations to demonstrate that there is a close relationship between the speed of the serotonin uptake in blood platelets and the function of a depression network in the brain.

This network is termed the “default mode network” because it is primarily active at rest and processes content with strong self-reference. Findings from recent years have also demonstrated that it is actively suppressed during complex thought processes, which is essential for adequate levels of concentration. Interestingly, patients with depression find it difficult to suppress this network during thought processes, leading to negative thoughts and ruminations as well as poor concentration.

“This is the first study that has been able to predict the activity of a major depression network in the brain using a blood test. While blood tests for mental illnesses have until recently been regarded as impossible, this study clearly shows that a blood test is possible in principle for diagnosing depression and could become reality in the not too distant future,” explains study leader Lukas Pezawas from the Department of Biological Psychiatry at the University Department of Psychiatry and Psychotherapy within the MedUni Vienna. This result means that the diagnosis of depression through blood tests could become reality in the not too distant future.