Archive for the ‘Neuroscience’ Category
nope – looking just below the eyes is optimal for face recognition tasks http://www.pnas.org/content/early/2012/11/07/1214269109.abstract …
Ever since ancient times, scholars have puzzled over the reasons that some musical note combinations sound so sweet while others are just downright dreadful. The Greeks believed that simple ratios in the string lengths of musical instruments were the key, maintaining that the precise mathematical relationships endowed certain chords with a special, even divine, quality. Twentieth-century composers, on the other hand, have leaned toward the notion that musical tastes are really all in what you are used to hearing.
Now, researchers think they may have gotten closer to the truth by studying the preferences of more than 250 college students from Minnesota to a variety of musical and nonmusical sounds. “The question is, what makes certain combinations of musical notes pleasant or unpleasant?” asks Josh McDermott, who conducted the studies at the University of Minnesota before moving to New York University. “There have been a lot of claims. It might be one of the oldest questions in perception.”
The University of Minnesota team, including collaborators Andriana Lehr and Andrew Oxenham, was able to independently manipulate both the harmonic frequency relations of the sounds and another quality known as beating. (Harmonic frequencies are all multiples of the same fundamental frequency, McDermott explains. For example, notes at frequencies of 200, 300, and 400 hertz are all multiples of 100. Beating occurs when two sounds are close but not identical in frequency. Over time, the frequencies shift in and out of phase with each other, causing the sound to wax and wane in amplitude and producing an audible “wobbling” quality.)
The researchers’ results show that musical chords sound good or bad mostly depending on whether the notes being played produce frequencies that are harmonically related or not. Beating didn’t turn out to be as important. Surprisingly, the preference for harmonic frequencies was stronger in people with experience playing musical instruments. In other words, learning plays a role — perhaps even a primary one, McDermott argues.
Whether you would get the same result in people from other parts of the world remains to be seen, McDermott says, but the effect of musical experience on the results suggests otherwise. “It suggests that Westerners learn to like the sound of harmonic frequencies because of their importance in Western music. Listeners with different experience might well have different preferences.” The diversity of music from other cultures is consistent with this. “Intervals and chords that are dissonant by Western standards are fairly common in some cultures,” he says. “Diversity is the rule, not the exception.”
That’s something that is increasingly easy to lose sight of as Western music has come to dominate radio waves all across the globe. “When all the kids in Indonesia are listening to Eminem,” McDermott says, “it becomes hard to get a true sense.”
Individual Differences Reveal the Basis of Consonance
Josh H. McDermott1,Andriana J. Lehr2 and Andrew J. Oxenham2
1 Center for Neural Science, New York University, New York, NY 10003, USA
2 Department of Psychology, University of Minnesota, Minneapolis, MN 55455, USA
Received 5 March 2010; revised 7 April 2010; accepted 8 April 2010. Published online: May 20, 2010. Available online 20 May 2010.
Summary Some combinations of musical notes are consonant (pleasant), whereas others are dissonant (unpleasant), a distinction central to music. Explanations of consonance in terms of acoustics, auditory neuroscience, and enculturation have been debated for centuries. We utilized individual differences to distinguish the candidate theories. We measured preferences for musical chords as well as nonmusical sounds that isolated particular acoustic factors—specifically, the beating and the harmonic relationships between frequency components, two factors that have long been thought to potentially underlie consonance . Listeners preferred stimuli without beats and with harmonic spectra, but across more than 250 subjects, only the preference for harmonic spectra was consistently correlated with preferences for consonant over dissonant chords. Harmonicity preferences were also correlated with the number of years subjects had spent playing a musical instrument, suggesting that exposure to music amplifies preferences for harmonic frequencies because of their musical importance. Harmonic spectra are prominent features of natural sounds, and our results indicate that they also underlie the perception of consonance.
Highlights ► Sounds with harmonic frequencies, and that lack beats, are preferred by listeners ► Only preference for harmonic spectra predicts preference for consonant chords ► Preferences for harmonic spectra, consonant chords correlate with musical experience ► Suggests harmonic frequency relations underlie perception of consonance
Language is a defining aspect of what makes us human. Although some brain regions are known to be associated with language, neuroscientists have had a surprisingly difficult time using brain imaging technology to understand exactly what these ‘language areas’ are doing. In a new study published in the Journal of Neurophysiology, MIT neuroscientists report on a new method to analyze brain imaging data — one that may paint a clearer picture of how our brain produces and understands language.
Sample brain activations of a left frontal language area in three subjects. Activations vary substantially in their precise locations, plausibly due to brain anatomy differences between subjects. Traditional group analyses would only capture a small proportion of each subject’s activations and would underestimate the functional selectivity of these regions. (Credit: Evalina Fedorenko / MIT)
Research with patients who developed specific language deficits (such as the inability to comprehend passive sentences) following brain injury suggest that different aspects of language may reside in different parts of the brain. But attempts to find these functionally specific regions of the brain with current neuroimaging technologies have been inconsistent and controversial.
One reason for this inconsistency may be due to the fact that most previous studies relied on group analyses in which brain imaging data were averaged across multiple subjects — a computation that could introduce statistical noise and bias into the analyses.
“Because brains differ in their folding patterns and in how functional areas map onto these folds, activations obtained in functional MRI studies often do not precisely ‘line up’ across brains,” explained Evelina Fedorenko, first author of the study and a postdoctoral associate in Nancy Kanwisher’s lab at the McGovern Institute for Brain Research at MIT. ” Some regions of the brain thought to be involved in language are also geographically close to regions that support other cognitive processes like music, arithmetic, or general working memory. By spatially averaging brain data across subjects you may see an activation ‘blob’ that looks like it supports both language and, say, arithmetic, even in cases where in every single subject these two processes are supported by non-overlapping nearby bits of cortex.”
The only way to get around this problem, according to Fedorenko, is to first define “regions of interest” in each individual subject and then investigate those regions by examining their responses to various new tasks. To do this, they developed a “localizer” task where subjects read either sentences or sequences of pronounceable nonwords.
Sample sentence: THE DOG CHASED THE CAT ALL DAY LONG
Sample nonword sequence: BOKER DESH HE THE DRILES LER CICE FRISTY’S
By subtracting the nonword-activated regions from the sentence-activated regions, the researchers found a number of language regions that were quickly and reliably identified in individual brains. Their new method revealed higher selectivity for sentences compared to nonwords than a traditional group analysis applied to the same data.
“This new, more sensitive method allows us now to investigate questions of functional specificity between language and other cognitive functions, as well as between different aspects of language,” Fedorenko concludes. “We’re more likely to discover which patches of cortex are specialized for language and which also support other cognitive functions like music and working memory. Understanding the relationship between language and the rest of condition is one of key questions in cognitive neuroscience.”
Next Steps: Fedorenko published the tools used in this study on her website: http://web.mit.edu/evelina9/www/funcloc.html. The goal for the future, she argues, is to adopt a common standard for identifying language-sensitive areas so that knowledge about their functions can be accumulated across studies and across labs. “The eventual goal is of course to understand the precise nature of the computations each brain region performs,” Fedorenko says, “but that’s a tall order.”
J Neurophysiol (April 21, 2010). doi:10.1152/jn.00032.2010
A new method for fMRI investigations of language: Defining ROIs functionally in individual subjects
Evelina Fedorenko1,*, Po-Jang Hsieh2, Alfonso Nieto Castanon3, Susan Whitfield-Gabrieli3 and Nancy Kanwisher4
2 Massachusetts Institute of Technology
3 4 Dept. of Brain and Cognitive Sciences, MIT
Submitted 13 January 2010; Revision received 29 March 2010. accepted in final form 15 April 2010
Abstract: Previous neuroimaging research has identified a number of brain regions sensitive to different aspects of linguistic processing, but precise functional characterization of these regions has proven challenging. We hypothesize that clearer functional specificity may emerge if candidate language-sensitive regions are identified functionally within each subject individually, a method that has revealed striking functional specificity in visual cortex but that has rarely been applied to neuroimaging studies of language. This method enables pooling of data from corresponding functional regions across subjects, rather than from corresponding locations in stereotaxic space (which may differ functionally because of the anatomical variability across subjects). However, it is far from obvious a priori that this method will work, as it requires that multiple stringent conditions be met. Specifically, candidate language-sensitive brain regions i) must be identifiable functionally within individual subjects in a short scan, ii) must be replicable within subjects and have clear correspondence across subjects, and iii) must manifest key signatures of language processing (e.g., a higher response to sentences than nonword strings, whether visual or auditory). We show here that this method does indeed work: we identify 13 candidate language-sensitive regions that meet these criteria, each present in at least 80 percent of subjects individually. The selectivity of these regions is stronger using our method than when standard group analyses are conducted on the same data, suggesting that the future application of this method may reveal clearer functional specificity than has been evident in prior neuroimaging research on language.
Key Words: fmri • language • individual subject analyses • functional specificity
Forget about crystals and candles, and about sitting and breathing in awkward ways. Meditation research explores how the brain works when we refrain from concentration, rumination and intentional thinking. Electrical brain waves suggest that mental activity during meditation is wakeful and relaxed.
“Given the popularity and effectiveness of meditation as a means of alleviating stress and maintaining good health, there is a pressing need for a rigorous investigation of how it affects brain function,” says Professor Jim Lagopoulos of Sydney University, Australia. Lagopoulos is the principal investigator of a joint study between his university and researchers from the Norwegian University of Science and Technology (NTNU) on changes in electrical brain activity during nondirective meditation.
Constant brain waves
Whether we are mentally active, resting or asleep, the brain always has some level of electrical activity. The study monitored the frequency and location of electrical brain waves through the use of EEG (electroencephalography). EEG electrodes were placed in standard locations of the scalp using a custom-made hat
Participants were experienced practitioners of Acem Meditation, a nondirective method developed in Norway. They were asked to rest, eyes closed, for 20 minutes, and to meditate for another 20 minutes, in random order. The abundance and location of slow to fast electrical brain waves (delta, theta, alpha, beta) provide a good indication of brain activity.
Relaxed attention with theta
During meditation, theta waves were most abundant in the frontal and middle parts of the brain.
“These types of waves likely originate from a relaxed attention that monitors our inner experiences. Here lies a significant difference between meditation and relaxing without any specific technique,” emphasizes Lagopoulos.
“Previous studies have shown that theta waves indicate deep relaxation and occur more frequently in highly experienced meditation practitioners. The source is probably frontal parts of the brain, which are associated with monitoring of other mental processes.”
“When we measure mental calm, these regions signal to lower parts of the brain, inducing the physical relaxation response that occurs during meditation.”
Silent experiences with alpha
Alpha waves were more abundant in the posterior parts of the brain during meditation than during simple relaxation. They are characteristic of wakeful rest.
“This wave type has been used as a universal sign of relaxation during meditation and other types of rest,” comments Professor Øyvind Ellingsen from NTNU. “The amount of alpha waves increases when the brain relaxes from intentional, goal-oriented tasks.This is a sign of deep relaxation, — but it does not mean that the mind is void.”
Neuroimaging studies by Malia F. Mason and co-workers at Dartmouth College NH suggest that the normal resting state of the brain is a silent current of thoughts, images and memories that is not induced by sensory input or intentional reasoning, but emerges spontaneously “from within.”
“Spontaneous wandering of the mind is something you become more aware of and familiar with when you meditate,” continues Ellingsen, who is an experienced practitioner. “This default activity of the brain is often underestimated. It probably represents a kind of mental processing that connects various experiences and emotional residues, puts them into perspective and lays them to rest.”
Different from sleep
Delta waves are characteristic of sleep. There was little delta during the relaxing and meditative tasks, confirming that nondirective meditation is different from sleep.
Beta waves occur when the brain is working on goal-oriented tasks, such as planning a date or reflecting actively over a particular issue. EEG showed few beta waves during meditation and resting.
“These findings indicate that you step away from problem solving both when relaxing and during meditation,” says Ellingsen.
Nondirective versus concentration
Several studies indicate better relaxation and stress management by meditation techniques where you refrain from trying to control the content of the mind.
“These methods are often described as nondirective, because practitioners do not actively pursue a particular experience or state of mind. They cultivate the ability to tolerate the spontaneous wandering of the mind without getting too much involved. Instead of concentrating on getting away from stressful thought and emotions, you simple let them pass in an effortless way.”
Take home message
Nondirective meditation yields more marked changes in electrical brain wave activity associated with wakeful, relaxed attention, than just resting without any specific mental technique.
he Journal of Alternative and Complementary Medicine. November 2009, 15(11): 1187-1192. doi:10.1089/acm.2009.0113.
Increased Theta and Alpha EEG Activity During Nondirective Meditation.
Jim Lagopoulos, Jian Xu, Inge Rasmussen, Alexandra Vik, Gin S. Malhi, Carl F. Eliassen, Ingrid E. Arntsen, Jardar G. Sæther, Stig Hollup, Are Holen, Svend Davanger, Øyvind Ellingsen
Abstract Objectives: In recent years, there has been significant uptake of meditation and related relaxation techniques, as a means of alleviating stress and maintaining good health. Despite its popularity, little is known about the neural mechanisms by which meditation works, and there is a need for more rigorous investigations of the underlying neurobiology. Several electroencephalogram (EEG) studies have reported changes in spectral band frequencies during meditation inspired by techniques that focus on concentration, and in comparison much less has been reported on mindfulness and nondirective techniques that are proving to be just as popular. Design: The present study examined EEG changes during nondirective meditation. The investigational paradigm involved 20 minutes of acem meditation, where the subjects were asked to close their eyes and adopt their normal meditation technique, as well as a separate 20-minute quiet rest condition where the subjects were asked to close their eyes and sit quietly in a state of rest. Both conditions were completed in the same experimental session with a 15-minute break in between. Results: Significantly increased theta power was found for the meditation condition when averaged across all brain regions. On closer examination, it was found that theta was significantly greater in the frontal and temporal–central regions as compared to the posterior region. There was also a significant increase in alpha power in the meditation condition compared to the rest condition, when averaged across all brain regions, and it was found that alpha was significantly greater in the posterior region as compared to the frontal region. Conclusions: These findings from this study suggest that nondirective meditation techniques alter theta and alpha EEG patterns significantly more than regular relaxation, in a manner that is perhaps similar to methods based on mindfulness or concentration.
The brains of psychopaths appear to be wired to keep seeking a reward at any cost, new research from Vanderbilt University finds. However suspicious I find research that administers volunteers a dose of amphetamine, or speed, and then scannes their brains using PET, the research uncovers the role of the brain’s reward system in psychopathy and opens a new area of study for understanding what drives these individuals. Let us just hope, that the faint light this study casts in the darkness of our understanding psychopathy is not a psychopath with a torch seeking his rewards after this study.
“This study underscores the importance of neurological research as it relates to behavior,” Dr. Francis S. Collins, director of the National Institutes of Health, said. “The findings may help us find new ways to intervene before a personality trait becomes antisocial behavior.”
The results were published March 14, 2010, in Nature Neuroscience.
“Psychopaths are often thought of as cold-blooded criminals who take what they want without thinking about consequences,” Joshua Buckholtz, a graduate student in the Department of Psychology and lead author of the new study, said. “We found that a hyper-reactive dopamine reward system may be the foundation for some of the most problematic behaviors associated with psychopathy, such as violent crime, recidivism and substance abuse.”
Previous research on psychopathy has focused on what these individuals lack — fear, empathy and interpersonal skills. The new research, however, examines what they have in abundance — impulsivity, heightened attraction to rewards and risk taking. Importantly, it is these latter traits that are most closely linked with the violent and criminal aspects of psychopathy.
“There has been a long tradition of research on psychopathy that has focused on the lack of sensitivity to punishment and a lack of fear, but those traits are not particularly good predictors of violence or criminal behavior,” David Zald, associate professor of psychology and of psychiatry and co-author of the study, said. “Our data is suggesting that something might be happening on the other side of things. These individuals appear to have such a strong draw to reward — to the carrot — that it overwhelms the sense of risk or concern about the stick.”
To examine the relationship between dopamine and psychopathy, the researchers used positron emission tomography, or PET, imaging of the brain to measure dopamine release, in concert with a functional magnetic imaging, or fMRI, probe of the brain’s reward system.
“The really striking thing is with these two very different techniques we saw a very similar pattern — both were heightened in individuals with psychopathic traits,” Zald said.
Study volunteers were given a personality test to determine their level of psychopathic traits. These traits exist on a spectrum, with violent criminals falling at the extreme end of the spectrum. However, a normally functioning person can also have the traits, which include manipulativeness, egocentricity, aggression and risk taking.
In the first portion of the experiment, the researchers gave the volunteers a dose of amphetamine, or speed, and then scanned their brains using PET to view dopamine release in response to the stimulant. Substance abuse has been shown in the past to be associated with alterations in dopamine responses. Psychopathy is strongly associated with substance abuse.
“Our hypothesis was that psychopathic traits are also linked to dysfunction in dopamine reward circuitry,” Buckholtz said. “Consistent with what we thought, we found people with high levels of psychopathic traits had almost four times the amount of dopamine released in response to amphetamine.”
In the second portion of the experiment, the research subjects were told they would receive a monetary reward for completing a simple task. Their brains were scanned with fMRI while they were performing the task. The researchers found in those individuals with elevated psychopathic traits the dopamine reward area of the brain, the nucleus accumbens, was much more active while they were anticipating the monetary reward than in the other volunteers.
“It may be that because of these exaggerated dopamine responses, once they focus on the chance to get a reward, psychopaths are unable to alter their attention until they get what they’re after,” Buckholtz said. Added Zald, “It’s not just that they don’t appreciate the potential threat, but that the anticipation or motivation for reward overwhelms those concerns.”
Nature Neuroscience, 2010; DOI: 10.1038/nn.2510
Mesolimbic dopamine reward system hypersensitivity in individuals with psychopathic traits.
Joshua W Buckholtz, Michael T Treadway, Ronald L Cowan, Neil D Woodward, Stephen D Benning, Rui Li, M Sib Ansari, Ronald M Baldwin, Ashley N Schwartzman, Evan S Shelby, Clarence E Smith, David Cole, Robert M Kessler & David H Zald.
Psychopathy is a personality disorder that is strongly linked to criminal behavior. Using fallypride positron emission tomography and blood oxygen level–dependent functional magnetic resonance imaging, we found that impulsive-antisocial psychopathic traits selectively predicted nucleus accumbens dopamine release and reward anticipation-related neural activity in response to pharmacological and monetary reinforcers, respectively. These findings suggest that neurochemical and neurophysiological hyper-reactivity of the dopaminergic reward system may comprise a neural substrate for impulsive-antisocial behavior and substance abuse in psychopathy.