KEEP CALM AND SCAN ON

reposted from HBM - thanks Jen

BRAIN MAPPING

KEEP CALM AND SCAN ON  7/21/2016  3 Comments Detailed Summary:BY: JEANETTE MUMFORD, CYRIL PERNET, THOMAS YEO, LISA NICKERSON, NILS MUHLERT, NIKOLA STIKOV, RANDY GOLLUB, & OHBM COMMUNIATIONS COMMITTEE (IN CONSULTATION WITH THOMAS NICHOLS)   In recent weeks a lot of attention has been given to the paper “Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates”, by Eklund, Nichols and Knutsson, in the Proceedings of the National Academy of Sciences.  This work highlights an important concern; however, some of the media attention has been based on a misunderstanding and an ‘inflated’ interpretation of the results.  Specifically, too much weight has been given to the numbers “40,000 impacted studies” and “70% false positives”, an unfortunate side effect of reducing a study rich in information to a few soundbites.  We respect the views of this paper and the effort put forth by the authors who, like the leadership of OHBM, understand there is a growing concern for validity and reproducibility in our field. The purpose of this post is to put these numbers in context and clarify how these findings impact our view of past and future fMRI results.  Background: In task-based fMRI studies we are often interested in looking for systematic differences between experimental conditions or cognitive states across upwards of 100,000 voxels in the brain. It is widely known that this large number of statistical tests, typically one per voxel, requires correction for multiplicity. The most common approaches focus on control of the family-wise error (FWE), which is the probability that a given study will produce any false positives.  The most common approaches for FWE control are voxel-wise and cluster-wise thresholding. Voxel-wise thresholding draws conclusions about specific voxels and cluster-wise thresholding allows one to conclude whether a group (or cluster) of adjacent voxels show an effect based on a feature, most often its size (e.g. only groups of voxels bigger than size N are significant). Eklund et al. consider both voxel-wise and cluster-wise FWE control in an exercise that tests whether the thresholding methods and their implementation by various software packages control the FWE as advertised. The innovation in this work is that they used resting-state fMRI data rather than computer generated simulation data to estimate noise (see below for more on this); they analyzed this resting-state data as if it were actually task fMRI data.  Eklund et al. find voxel-wise results are always correct, i.e. control FWE below a requested 5% level, and are thus safe; we won't discuss these further. They also find that, depending on the exact methods and tools used, cluster-wise results can be invalid, i.e. have FWE in excess of the traditionally accepted 5% level.  Understanding the specifics of when these methods are invalid is the focus of the article. ​ Figure 1. Cartoon example of how cluster-based thresholding works. The orange line represents the uncorrected, voxelwise p-values over a row of voxels (space). First, the cluster-defining threshold, CDT, is used to define the clusters, which are indicated by the boxes on the x-axis. Second, using the cluster size as the statistic, a threshold of cluster size k is used to assess the two clusters, concluding only the red cluster is large enough to be significant. A cartoon example of the cluster-wise based strategy is illustrated in Figure 1. First, a primary threshold is required to define clusters (in Eklund et al. this is called a cluster-defining threshold, CDT). The CDT is typically based on the uncorrected voxelwise p-values.  SPM and FSL use random field theory to obtain FWE-corrected p-values, which requires an estimate of the spatial smoothness of the image that is being thresholded, typically a map of t-statistics that quantifies the effect size at each voxel. AFNI uses a simulation-based procedure that also relies on a smoothness estimate. In contrast, another choice is to use a permutation approach, which is based on randomly permuting data labels to generate a null distribution for cluster size that is used to compute a p-value. The approaches in the 3 widely used fMRI data analysis packages, SPM, FSL and AFNI, are variations of parametric methods, and are based on specific assumptions about the data, while the permutation method is nonparametric and requires minimal assumptions.  What is unique about this work? This paper is an example of a simulation study, an evaluation of a method based on ‘made up’ data. The reason simulations are used is because quantifying FWE can only be done if if the ground truth is known. Specifically, we must ensure there is no signal in the data. A simulation most useful when the simulated data reflect what we would find in real data as closely as possible. This has been a limitation of previous studies, which generated synthetic data with software and used this synthetic data to test the performance of the analysis algorithms (Friston et al. (1994) and Hayasaka and Nichols (2003) are examples). This work uses a large pool of real human resting state fMRI data as a source of null data, or data that do not contain any task-related signal. Fitting a model of a task to the data should not find any activation. The advantage of using actual fMRI data is that the spatial and temporal structure of the noise is real, in contrast to previous simulation studies that used computer-generated null data.  In the simulations in Eklund et al., random samples of subjects from the resting state data set are taken, and these samples are analyzed with a fake task design. The subject-specific task activation estimates are then entered into either a 1-sample test (to test the hypothesis that there is an effect of this task in this group) or a 2-sample test between two groups of subjects (to test the hypothesis that the effect of the task differs between the groups). Each result is assessed in the usual way, looking for FWE-corrected p-values that fall below p=0.05, and the occurrence of significant clusters (cluster-wise approach) is recorded. The authors repeat this a total of 1000 times and the FWE is computed as the number of simulated studies with any false positives divided by 1000. In theory, using p=0.05 should result in a FWE of 5%.  Primary Results Brief Summary: Four study designs, two blocked and two event related, were studied across multiple degrees of spatial smoothing, different cluster-forming thresholds and different software packages.  Specifically SPM, FLAME 1 from FSL, OLS from FSL, 3dttest from AFNI, 3dMEMA from AFNI, and a permutation-based approach implemented using the BROCCOLI software were studied. The main result, highlighted in the first figure of the paper, shows that when using a parametric approach, a cluster defining threshold of p=0.01 leads to poor control of FWE (FWE from approximately 4-50%).  However, FWE control is improved when a cluster defining threshold of p=0.001 is used instead, regardless of software package used (FWE ranges from approximately 0-25%).  The more conservative nonparametric approach controls FWE regardless of cluster defining threshold in most cases, although elevated FWE were observed for the one-sample t-test in some cases due to skewed data. The second result, which is the source of the 70% FWE that has appeared in many other blog posts, occurs when simply using a cluster size of 10 as an ad-hoc inference procedure.  In this case, a cluster defining threshold of p=0.001 was used and clusters with 10 or greater voxels are identified as significant. The high FWE of this approach indicates that it should not be thought of as controlling FWE. More details and the explanation of why FLAME1 appears conservative in both of these results are in the next section. The general conclusion is that when using cluster-based thresholding, a cluster-defining threshold of p=0.001 has better control of FWE than p=0.01 for SPM, FSL and AFNI. The nonparametric-based approach has better controlled FWE in the scenarios tested here. Detailed Summary: AFNI problem identified.  The results presented in this manuscript include the use of a pre May 2015 version of AFNI, specifically the 3dClustSim function used to implement the parametric FWE control. One of the discoveries made during this project was the smoothness estimate used in this older version of 3dClustSim had a flaw that increased the FWE. This was fixed by the AFNI developers in versions after May 2015.  Although the new version reduces FWE, it is still inflated above the target of 5%; the p=0.01 and p=0.001 cluster defining thresholds’ FWE with 3dClustSim changed from 31.0% to 27.1% and 11.5% to 8.6%, respectively.   Is FLAME1 superior? Some results appear to support the claim that FLAME1 option in FSL has better FWE control, even in the ad-hoc case, but this is due to a known problem where FLAME1 sometimes overestimates the variance. To clarify, FLAME1 differentially weights the contribution of each subject according to the subject-specific mixed effects variance, which is a sum of within- and between-subject variances. The result is that more variable subjects contribute less to the statistic estimate. In comparison, the OLS option in FSL treats all subjects equally (also true for SPM, AFNI’s 3dttest and permutation tests). When the true between-subject variance is small, FLAME1 overestimates it, causing an increase in p-values, which reduces the FWE. When the true between subject variance is not close to 0, FLAME1 results in a more accurate estimate of the variance but the FWE can then be inflated with results similar to FSL’s OLS. The resting state data have a low true between-subject variance, leading to lower FWE than we might see with task data where systematic differences in task performance might indeed yield the predicted large between-subject differences. This is supported by a secondary simulation using task fMRI data with randomly assigned groups that found FLAME1 to have error rates comparable to FSL’s OLS. Overall, this implies that the FWE will be controlled if the true between-subject variance is small and will be elevated similarly to OLS if the variance is larger than 0. Why do parametric methods fail? The assumptions of random field theory include that the spatial smoothness must be constant across the brain and the spatial autocorrelation follows a squared exponential distribution. The spatial autocorrelation distribution was not found to follow the squared exponential very well, instead the accuracy of the distribution varied according to distance. Simply put, if voxels were close together, there was a stronger agreement between the empirical and theoretical spatial correlation, but the two do not match for voxels that are far apart from each other. This explains why results improve for more stringent cluster forming thresholds, since clusters are smaller, hence the voxels involved are closer and the assumptions are more closely met. The Takeaways Should we all panic and give up on fMRI?  Are all 40,000 fMRI studies of the past worthless?  Of course not.   The blog post by Tom Nichols refines this estimate to a more reasonable number of studies from the past that may be impacted: closer to 3,500. (Note: PNAS has accepted an Erratum from the authors that revises the sentences that led to the sensationalized press articles.) The study shows that (a) FWE control does not work properly in the parametric tests using an ad hoc threshold of 10 voxels; (b) FWE is often controlled by permutation-based testing; (c) cluster inference for SPM, FSL, and AFNI using a cluster-defining threshold of 0.01 is likely problematic; (d) although improvements would be expected if a cluster forming threshold of 0.001 was used, FWE is still not controlled at the nominal level of 5% under all conditions.   How shall we proceed to analyze fMRI data?    Both parametric and nonparametric-based inference have pros and cons and work well when their assumptions are met. Prior work has highlighted the assumptions of the parametric cluster-based thresholding approach, including using a small p-value based cluster defining threshold (see Friston et al. (1994) and Hayasaka and Nichols (2003) for examples). Although it was clear the threshold needed to be low, without knowing the true spatial covariance structure, it wasn’t necessarily clear how low for real fMRI data. Since the Eklund et al. work used real fMRI data in the simulations we now know that p=0.01 is not low enough and p=0.001 is a better option.  Generally, the permutation test has fewer assumptions and tends to have better FWE control, but Eklund et al. did find some cases with the 1-sample t-test where the nonparametric approach had elevated FWE, due to skew in the data. Permutation-based options can be implemented on any NIfTI file using SnPM in SPM, randomise in FSL, PALM (also affiliated with FSL), Eklund’s BROCCOLI package and mri_glmfit-sim in FreeSurfer.   Importantly, AFNI users should update their versions to ensure use of either the repaired 3dClustSim (after May 2015), or the new3dFWHMx function which uses a more accurate spatial smoothness estimate and will improve FWER control.  Also, using the ad hoc cluster size of 10 voxels has the largest FWE and is not recommended as a method for controlling FWE. ​ The work of Eklund et al. supplies important information to those who choose to control the multiple comparison problem according to the FWE. In future work, researchers intending to use FWE correction can make better choices to ensure the true level of FWE is closer to the goal FWE. Although some previously published studies may have not used as stringent FWE control when they had intended to, the results can still be interpreted, but with more caution. Multiple comparison correction is just one element of neuroimaging practice, and there are countless choices in the design, acquisition, analysis and interpretation of any study. We encourage everyone to consult the OHBM Committee on Best Practice in Data Analysis and Sharing (COBIDAS) report on MRI, and review the detailed checklists for every stage of a study. The report is available directly on the OHBM websitehttp://www.humanbrainmapping.org/COBIDASreport and on bioRxiv.

Continuing to lead in cutting-edge research

I can not believe it is now 20-years since I have been using fMRI.  WOW!


reposted from RRI -

By Crystal Mackay, MA'05

When the Centre for Functional and Metabolic Mapping (CFMM) first opened its doors at Robarts Research Institute in 1996 you could stand beside the building and see the reflection of the hospital on one side and the University on the other. At the time, it was a revolutionary move; to have a cutting-edge Magnetic Resonance Imaging (MRI) research facility on the doorstep of patient care and academics.

“You need a facility with access to patients and doctors if you want to have clinical impact, and you need access to the academic side to answer the basic science questions,” said Ravi Menon, PhD, Professor at Schulich Medicine & Dentistry and the director and founder of the CFMM. “We are right in the middle of that, we are a bridge between the hospital and the university.”

Menon was recruited in 1994 from the University of Minnesota to establish the high-field imaging facility at Robarts with the aim of helping to answer some of the world’s most pressing medical questions.

During the past two decades, clinicians and researchers at Robarts have been using Functional Magnetic Resonance Imaging (fMRI) at CFMM to see high-resolution images of both anatomical structures inside the brain, but also metabolic features like blood-flow and pH. The technology has been used to explore the basis of diseases like Alzheimer’s, Parkinson’s and multiple sclerosis, and has provided a unique look into what exactly is happening inside the minds of patients in a vegetative state. 

In the spring of 1996, when fMRI was just starting to make its mark in the field of imaging, the first MRI system was delivered to Robarts. It was a 4 Tesla (4T), and at the time it was the highest magnetic field in Canada. “In the early days it was unique across the world,” said Joe Gati, PhD, who was hired by Menon in 1996 as CFMM’s Associate Director. “We garnered attention from a lot of other sites for not only our cutting-edge technology but the design and function of the facility. We led the way in a lot of aspects.”

Some of the early work at CFMM involved proving the viability of the technology and demonstrating how improving field strength could exponentially improve image quality. One of the first publications showed the benefits of using 4T MRI. “That paper really propelled the growth of high-field scanners,” said Menon. “At the time we were only the fourth scanner in the world at that field strength and now there are more than 4,000 worldwide.”

This spring, as CFMM celebrates its 20^th birthday, the facility continues to be on the leading-edge under Menon’s direction with a dedicated core staff of 14. In the time that he has been director of CFMM, he has watched the field of high-field imaging grow in unimaginable ways.

Currently inside the $35 million CFMM are Canada’s only large-bore 9.4 Tesla MRI for studying animal models of disease, Canada’s only 7 Tesla human MRI and Canada’s first 64-channel 3 Tesla MRI. That represents an increase in the strength of the scanners by almost 100-fold since Menon began his research more than two decades ago.

“With MRI, there is a combination of image processing, and image acquisition, and engineering. It’s just such a growing, innovative, seemingly limitless field for opportunity,” he said.

Part of CFMM’s mission is to advance the field of imaging through innovations in the technology, namely radio frequency coils. Like the lens of a camera, technology can be built for the scanners to focus down on specific areas with more detail for different applications.

“It’s absolutely amazing what we can see now,” he said. “When I go to the scanner here and look at something that we’ve built from scratch and see how it works, it's pretty incredible.”

While the structure of an organ is important, Menon and his colleagues at CFMM are spending much of their time these days focusing in on the functional information, exploring new imaging techniques that show exactly what those structures are doing. They are trying to answer questions about blood flow, tissue viability, oxygenation, pH and brain activity.

Menon says while there are thousands of labs around the world using functional MRI, there are only half a dozen or so concerned with advancing the technology and exploring exactly how it works.

“What's next is to be able to measure the electrical activity in the brain directly with MRI instead of going through the intermediate step of looking at blood flow,” said Menon. “To be able to do that would be phenomenal.”

TIMELINE

Spring 1996 – Establishment of Western’s Centre for Functional and Metabolic Mapping, and the first 4T MRI is delivered to Robarts

September 1996 – The official opening of the A.M. Cuddy Wing which houses CFMM

June 1999 – First major clinical finding comes out of CFMM showing that the mere threat of an injury can get the brain so worked up that you feel pain even if you aren’t injured.

2005 – Facility undergoes first major renovation for the addition of Canada’s only large-bore 9.4T scanner

2007 – The 4T is decommissioned to make way for the 3T and Canada’s first 7T human MRI scanner

2014 – $7 million in upgrades to 3T and 7T MRIs to improve software and imaging speed

reposted from http://neurosciencenews.com/violinist-music-fmri-3821/

How Music Affects The Brain: Using MRI to Study the Brain of a Virtuoso Violinist

NEUROSCIENCE NEWSMARCH 8, 2016

FEATUREDNEUROSCIENCENEUROSCIENCE VIDEOS

Until just a few years ago, violinist Jennifer Koh had no particular interest in the inner workings of the brain.

But then she suffered a concussion resulting in speech and memory loss. She couldn’t practice her violin for months; when she picked up the instrument again, she could play for no more than 20 minutes at a time.

Suddenly, Koh wanted all the knowledge she can muster about the brain. She read. She pestered friends who work in medical fields. And this week at Duke, she underwent a functional magnetic resonance imaging scan – known as an functional MRI – in the hope it can help explain how the brain of a professional musician works.

“I have a general curiosity about the relationship between human beings and music,” said Koh, a touring professional who has played the violin since she was 3 years old. “No matter what the culture, no matter what the country … music is a fundamental part of human beings.”

Koh’s fMRI this week was an unexpected offshoot of a visit to campus in January as an artist-in-residence sponsored by Duke Performances, during which time she gave a recital at Baldwin Auditorium and participated in some classes. One was “Music and the Brain,” which explores the intersection of music and neuroscience and is taught jointly by professors Scott Lindroth of the music department and Tobias Overath from the Duke Institute for Brain Sciences.

Koh is among the nation’s most well-regarded musicians. A Chicago native, she made her major symphony debut at age 11 with the Chicago Symphony Orchestra and has performed with dozens of professional symphonies around the world. She was recently named Instrumentalist of the Year by Musical America magazine, the oldest American magazine covering classical music. 

Knowing Koh was returning to campus this week to perform the Beethoven violin concerto with the Duke Symphony Orchestra, Overath reserved an MRI slot at the Duke-UNC Brain Imaging and Analysis Center (BIAC) – which funded the test — and set out to create a research study with the violinist’s brain as its subject.

Laying motionless on her back in the MRI machine while her brain activity was being measured, Koh was asked to imagine playing a series of classical works for solo violin by Paganini and Bach, to listen to them, or to read their musical scores. Overath then studied how Koh’s brain reacted to each.

The results, he said afterwards, showed a unique activation pattern for when she was listening, reading, and imagining playing music. However, there were also some common traits: For example, brain areas responsible for planning movements were active in all three tasks, even though Koh never lifted a finger.

Violinist Jennifer Koh used her visit to Duke to learn more about brain function. Credit: Duke University.

“The musician’s brain is exquisitely sensitive to all aspects of music, be it listening, reading or imagining playing music,” Overath said. “Therefore, you engage a whole range of areas of your brain – it’s quite literally a whole body experience. From a cognitive point of view, but also physically, it’s incredibly strenuous.”

Overath himself is a musician: he played violin for 16 years before transitioning to the viola, which he played for many years and still picks up from time to time. He studied musicology as a college undergraduate in Germany before realizing he was more interested in the brain chemistry of how us humans perceive music rather than the technical nitty-gritty of musical composition and theory. So he became a neuroscientist, one with the perfect background for Koh’s study.

Duke University professors conduct an experiment on a professional violinist that explains the science behind the brain’s ability to process music.

For Overath, the chance to study the working brain of a professional musician of Koh’s caliber was a rare opportunity, and his students will benefit as well. He and Lindroth will discuss the results derived from Koh’s scan in class.

“It certainly plays into the course content,” said Lindroth, a composer. “We’ll have a whole class on the ways the brain is engaged with the physical and auditory dimensions of musical performance. It’s especially wonderful that our students will have a personal connection to Jennifer from her visit to our class earlier in the semester.”

ABOUT THIS NEUROSCIENCE AND MUSIC RESEARCH

Funding: The study has received funding from Lund University, as well as the European Research Council (ERC), the Swedish Research Council (VR), the Marianne and Marcus Wallenberg Foundation and Region Skåne (through so-called ALF grants).

Source: Eric Ferreri – Duke University
Image Credit: The image is credited to Duke University.
Video Source: The video is credited to Duke University.

reposted from

Creation theory: Scientists are unlocking the biological secrets of creativity

KATE TAYLOR

The Globe and Mail

Published Wednesday, Oct. 01 2014, 11:50 AM EDT

Last updated Thursday, Oct. 02 2014, 12:27 PM EDT

Whether it’s playing Schubert or dancing the tango, artistic expression has a tangible effect on the brain. A burgeoning field of research seeks to measure how we produce and experience the arts – and may even explain why we create them in the first place. Kate Taylor reports

McMaster psychology PhD student Ye Yuan plays the piano in the university’s new LiveLAB with reflective markers for motion-capture attached to his hands. (Photos by Peter Power for The Globe and Mail)

Steven Brown must be the first person in the world to have danced the tango inside an MRI machine. Brown is an amateur dancer, but he is also a neuroscientist in the psychology department at McMaster University in Hamilton, Ont. He studies what goes on in the brain when it is engaged in the arts and, for his tango study, he wanted to see the differences between leading and following in partner dancing. He lay in the machine and danced with his arms, holding a partner’s hands outside it and leading her through her moves before they swapped roles. He found that the leading partner’s brain used more motor planning – the brain’s ability to plan and execute a physical task – while the following one showed more sensory activation, responding to the cues of touch and music.

His findings may not seem particularly surprising. They are, however, just one brick in an edifice of neurological, psychological and biological research that seeks to measure how humans produce and experience the arts – and may even explain why we create them in the first place.

“For me, all this leads to creativity. … I am trying to develop a neurological theory of the arts,” Brown said, explaining that he ultimately hopes to find common patterns of brain activity in different artistic disciplines. So far, he has done basic studies during dancing, drawing a picture, improvising a song and acting a role: His MRIs (magnetic resonance images) of actors, for example, showed less activity in the area of the brain believed to create personality when subjects were answering questions in character than when they were answering similar questions about their real selves. “It’s a loss of self,” he says of acting. “If you talk to an actor they often can’t put it into words. So, I look inside the box, and I’d say it’s like a possession.”

Does an actor, let alone a theatregoer, need to understand the brain activity associated with playing a role? It’s a tricky question as artistic communities become aware they are the subject of scientific scrutiny that might justify their existence as a biological imperative – or explain away their best inspirations as the convulsions of some overexcited neurons.

Theatre is pretty late to this party: The notion that the brain is doing all kinds of interesting gymnastics when listening to music is well established, popularized by McGill University professor Daniel Levitin and his best-selling 2006 book, This Is Your Brain on Music, in which he hypothesized music is a perceptual illusion in which the brain learns to impose structure on a sequence of sounds.

Levitin is the flag-bearer for a burgeoning field of research, much of it being done in Canada.

Those who do not come from artistic families often feel they have to justify what they do, especially if it doesn’t make much money, which is often the only measure of success. Here is a justification for their passion.

Daniel Levitin, McGill University professor and author of This Is Your Brain on Music

At McMaster, the psychology department’s Institute for Music and the Mind has just opened its LIVElab, a high-tech auditorium that can measure the brain waves, heart rate and sweat of performers and spectators. Brown hopes to study partner dancing there, using the same motion-capture technology that is used in animated films. Other researchers foresee using the lab to do everything from studying audience reaction in different acoustic environments to analyzing repetitive strain injuries in musicians, but nobody really expects the work to explain music itself. “The U.S. spends more on music than on pharmaceuticals,” says lab director Laurel Trainor. “To say it is a frill is a folly. How can it be if we invest so much in it?”

Since the 1990s, when Harvard psychologist Steven Pinker labelled music “auditory cheesecake,” a byproduct of other evolutionary developments that was fun but not necessary, researchers have debated its biological usefulness. Pinker’s critics believe music has precise evolutionary functions, arguing, for example, that music-making and rhythmic dancing might be signals to potential partners of sexual fitness, thus their particular importance to the adolescent male.

Meanwhile, a parallel debate about the purpose of fiction is being argued in literature and psychology departments. Rejecting the poststructuralist idea that the meaning of a text is not universal but determined by the individual reader, some English scholars such as the American Joseph Carroll and New Zealander Brian Boyd have argued that storytelling is an evolutionary refinement that helps people organize feelings and understand others. Similarly, psychologists such as Keith Oatley at the University of Toronto have argued fiction teaches empathy, and his colleagues are now setting out to test that premise. Raymond Mar, a neuroscientist and psychologist at York University, is working on studies that try to measure the impact of genre fiction on readers, testing their knowledge of authors’ names in various genres and then assessing their social awareness using tests first developed for autism. “Romance novels were the most robust predictor of interpersonal sensitivity,” Mar reports, cautioning the study only identifies a correlation, not a cause-and-effect.

Steven Brown studied partner dancing at McMaster University using motion-capture technology.

All of this work poses something of a conundrum for the people who actually produce art or literature.

A cap that can be worn to collect data at the LiveLab at McMaster University.

On the one hand, it offers a compelling explanation for artistic activity.

“Painters and musicians love seeing there is a rational and scientific explanation for what they do,” Levitin said. “Those who do not come from artistic families often feel they have to justify what they do, especially if it doesn’t make much money, which is often the only measure of success. Here is a justification for their passion.”

On the other hand, scientific studies of artistic activity inevitably reduce it, and rather miss the point that the mysteriousness of art can be central to both its creation and its enjoyment.

“It’s like telling someone who is madly in love: ‘This is what’s happening in your brain.’ What does it have to do with being in love?” asks pianist Andrew Burashko, artistic director of Toronto’s Art of Time Ensemble.

Both neuroscientists and humanities scholars are well aware of these dangers. Mar cautions against concluding that an activity with biological roots is necessarily ancient; he thinks fields such as sociology and anthropology, which would include archeological finds of prehistoric musical instruments, offer stronger evidence that the arts are fundamental to humans. In turn, others acknowledge how quickly the idea of the arts or literature as intrinsic can reduce them.

“We have uneasiness about universalism, reductivism, even biological determinism. Yes, these are dangers, but let’s not throw the baby out with the bathwater,” says Melba Cuddy-Keane, a professor emeritus of English at the University of Toronto. A Virginia Woolf scholar who studies how descriptions of physical space in fiction work on the reader’s mind, she follows neuroscience closely and is part of a new cross-disciplinary group at the Jackman Humanities Institute that is looking at the uncritical embrace of the “neuroculture” trend. She argues the danger doesn’t lie in applying science to literary criticism, but in drawing sweeping conclusions.

“We have to be cautious of falling into the bootstrap position: ‘Read [fiction] because it’s good for you,’” she says of the fiction-builds-empathy argument. “Read it because response is good for you, and your response is up to you.”

It’s like telling someone who is madly in love: ‘This is what’s happening in your brain.’ What does it have to do with being in love?

Andrew Burashko, artistic director of Toronto’s Art of Time Ensemble.

Still, the notion that music, painting and literature are fulfilling ancient functions that make us human – and that science can prove it – could be very attractive to those who have spent a lifetime arguing that the arts should get more respect, and often rely on job-creation arguments.

“The neurological argument has something to do with what it takes the species to survive in changing conditions,” said Robert Sirman, the recently retired director of the Canada Council for the Arts. “I don’t want to fall back on a single argument for the arts … but I think attaching them to humanity rather than to part of the economic system is the future.”

He cautions, however, against the dangers of just swapping social utility for economic utility. The English philosopher Alain de Botton has been criticized for presenting art as a kind of social work, an idea articulated in his current show Art as Therapy at Toronto’s Art Gallery of Ontario, where paintings are analyzed for their ability to make us feel less lonely, escape our money worries or give us a break from our cynicism. Here, the idea that visual art should be immediately and obviously improving seems reductionist in the extreme.

On the other hand, the argument that artistic activity builds your brain has taken hold in the music world: In Toronto, the Royal Conservatory of Music (RCM) now advertises its services with research that shows how music improves cognitive abilities. Some of that research is being done in-house at the RCM where neuroscientist Sean Hutchins is testing preschoolers to see if their abilities to distinguish shapes, compare amounts and make out sounds are improved by music classes.

At McMaster, meanwhile, Brown is hoping to get Toronto’s Coleman Lemieux & Compagnie dance troupe into the LIVElab and wonders if he will see differences between the brain patterns of amateurs like himself and the pros. Still, no MRI or EEG (electroencephalograph) will have the last word: “The paradigms we can look at in the lab are simple compared to the richness of the arts.”

Follow Kate Taylor on Twitter: @thatkatetaylor

A review of the use of magnetic resonance imaging in Parkinson's disease.

reposted from

A review of the use of magnetic resonance imaging in Parkinson's disease.
Ther Adv Neurol Disord. 2014 Jul;7(4):206-20. doi: 10.1177/1756285613511507.
Pyatigorskaya N, Gallea C, Garcia-Lorenzo D, Vidailhet M, Lehericy S.

Abstract

To date, the most frequently used Parkinson's disease (PD) biomarkers are the brain imaging measures of dopaminergic dysfunction using positron emission tomography and single photon emission computed tomography. However, major advances have occurred in the development of magnetic resonance imaging (MRI) biomarkers for PD in the past decade. Although conventional structural imaging remains normal in PD, advanced techniques have shown changes in the substantia nigra and the cortex. The most well-developed MRI markers in PD include diffusion imaging and iron load using T2/T2* relaxometry techniques. Other quantitative biomarkers such as susceptibility-weighted imaging for iron load, magnetization transfer and ultra-high-field MRI have shown great potential. More sophisticated techniques such as tractography and resting state functional connectivity give access to anatomical and functional connectivity changes in the brain, respectively. Brain perfusion can be assessed using non-contrast-agent techniques such as arterial spin labelling and spectroscopy gives access to metabolites concentrations. However, to date these techniques are not yet fully validated and standardized quantitative metrics for PD are still lacking. This review presents an overview of new structural, perfusion, metabolic and anatomo-functional connectivity biomarkers, their use in PD and their potential applications to improve the clinical diagnosis of Parkinsonian syndromes and the quality of clinical trials.

New evidence that chronic stress predisposes brain to mental illness

By Robert Sanders, Media Relations | February 11, 2014

BERKELEY —

University of California, Berkeley, researchers have shown that chronic stress generates long-term changes in the brain that may explain why people suffering chronic stress are prone to mental problems such as anxiety and mood disorders later in life.

Myelin is stained blue in this cross section of a rat hippocampus. Myelin, which speeds electrical signals flowing through axons, is produced by oligodendrocytes, which increase in number as a result of chronic stress. New oligodendrocytes are shown in yellow. Image by Aaron Friedman and Daniela Kaufer.

Their findings could lead to new therapies to reduce the risk of developing mental illness after stressful events.

Doctors know that people with stress-related illnesses, such as post-traumatic stress disorder (PTSD), have abnormalities in the brain, including differences in the amount of gray matter versus white matter. Gray matter consists mostly of cells – neurons, which store and process information, and support cells called glia – while white matter is comprised of axons, which create a network of fibers that interconnect neurons. White matter gets its name from the white, fatty myelin sheath that surrounds the axons and speeds the flow of electrical signals from cell to cell.

How chronic stress creates these long-lasting changes in brain structure is a mystery that researchers are only now beginning to unravel.

In a series of experiments, Daniela Kaufer, UC Berkeley associate professor of integrative biology, and her colleagues, including graduate students Sundari Chetty and Aaron Freidman, discovered that chronic stress generates more myelin-producing cells and fewer neurons than normal. This results in an excess of myelin – and thus, white matter – in some areas of the brain, which disrupts the delicate balance and timing of communication within the brain.

“We studied only one part of the brain, the hippocampus, but our findings could provide insight into how white matter is changing in conditions such as schizophrenia, autism, depression, suicide, ADHD and PTSD,” she said.

The hippocampus regulates memory and emotions, and plays a role in various emotional disorders.

Kaufer and her colleagues published their findings in the Feb. 11 issue of the journal Molecular Psychiatry.

Does stress affect brain connectivity?
Kaufer’s findings suggest a mechanism that may explain some changes in brain connectivity in people with PTSD, for example. One can imagine, she said, that PTSD patients could develop a stronger connectivity between the hippocampus and the amygdala – the seat of the brain’s fight or flight response – and lower than normal connectivity between the hippocampus and prefrontal cortex, which moderates our responses.

“You can imagine that if your amygdala and hippocampus are better connected, that could mean that your fear responses are much quicker, which is something you see in stress survivors,” she said. “On the other hand, if your connections are not so good to the prefrontal cortex, your ability to shut down responses is impaired. So, when you are in a stressful situation, the inhibitory pathways from the prefrontal cortex telling you not to get stressed don’t work as well as the amygdala shouting to the hippocampus, ‘This is terrible!’ You have a much bigger response than you should.”

White matter fiber architecture of the brain. Human Connectome Project.

She is involved in a study to test this hypothesis in PTSD patients, and continues to study brain changes in rodents subjected to chronic stress or to adverse environments in early life.

Stress tweaks stem cells
Kaufer’s lab, which conducts research on the molecular and cellular effects of acute and chronic stress, focused in this study on neural stem cells in the hippocampus of the brains of adult rats. These stem cells were previously thought to mature only into neurons or a type of glial cell called an astrocyte. The researchers found, however, that chronic stress also made stem cells in the hippocampus mature into another type of glial cell called an oligodendrocyte, which produces the myelin that sheaths nerve cells.

The finding, which they demonstrated in rats and cultured rat brain cells, suggests a key role for oligodendrocytes in long-term and perhaps permanent changes in the brain that could set the stage for later mental problems. Oligodendrocytes also help form synapses – sites where one cell talks to another – and help control the growth pathway of axons, which make those synapse connections.

The fact that chronic stress also decreases the number of stem cells that mature into neurons could provide an explanation for how chronic stress also affects learning and memory, she said.

Kaufer is now conducting experiments to determine how stress in infancy affects the brain’s white matter, and whether chronic early-life stress decreases resilience later in life. She also is looking at the effects of therapies, ranging from exercise to antidepressant drugs, that reduce the impact of stress and stress hormones.

Kaufer’s coauthors include Chetty, formerly from UC Berkeley’s Helen Wills Neuroscience Institute and now at Harvard University; Friedman and K. Taravosh-Lahn at UC Berkeley’s Department of Integrative Biology; additional colleagues from UC Berkeley and others from Stanford University and UC Davis.

The work was supported by a BRAINS (Biobehavioral Research Awards for Innovative New Scientists) award from the National Institute of Mental Health of the National Institutes of Health (R01 MH087495), a Berkeley Stem Cell Center Seed Grant, the Hellman Family Foundation and the National Alliance for Research on Schizophrenia and Depression.

RELATED INFORMATION

• Stress and glucocorticoids promote oligodendrogenesis in the adult hippocampus (2/11/14 Molecular Psychiatry)
• Daniela Kaufer’s web site
• Researchers find out why some stress is good for you (4/16/13 press release)

Categories: Health & medicine, News, Press Release, Science
Tags: ADHD, anxiety, depression, integrative biology, mental illness, mood disorders, PTSD, stress