Posts tagged "fmri"
New tools to answer timeless questions
After finishing his PhD in molecular biophysics, Alan Jasanoff decided to veer away from that field and try looking into some of the biggest questions in neuroscience: How do we perceive things? What happens in our brains when we make decisions?
After a few months, however, he realized that he didn’t have the tools he wanted to use — so he decided to start making his own.
Jasanoff, who recently earned tenure in MIT’s Department of Biological Engineering, now specializes in developing novel brain-imaging agents that can reveal information more detailed than other human brain-imaging techniques such as fMRI and PET, and more comprehensive than traditional neuroscience measurements such as microscopy and electrode recordings. With the new tools, he is also beginning to explore some of the fundamental questions that first drew him into neuroscience.
Neuroscientists commonly use fMRI, which measures blood flow in the brain, as a proxy for neural activity. In the past several years, Jasanoff has developed sensors that can be used with fMRI to image brain activity more directly, by measuring levels of neurotransmitters (the chemicals that carry messages between neurons) and calcium, which enters neurons when they fire.
Using those sensors, Jasanoff has started exploring how positive reinforcement influences behavior and decision making in animals. His work could also be applicable to fields outside of neuroscience, because intracellular signaling molecules such as calcium “are really ubiquitous — not just in neuronal signaling but signaling throughout the body, during development, immune-cell activity and so on,” says Jasanoff, who is an associate member of MIT’s McGovern Institute for Brain Research and an associate professor of biological engineering, nuclear science and engineering, and brain and cognitive sciences.
As a teenager, Jasanoff had a strong interest in science and two role models for a career in academia — his parents, both social scientists. Jasanoff spent his childhood first in Cambridge, Mass., where his father taught at Harvard University, then Ithaca, N.Y., where both parents were professors at Cornell University. His parents, Jay and Sheila Sen Jasanoff, have since returned to Harvard. “My sister Maya is also a professor at Harvard, so I’m the black sheep,” Jasanoff jokes.
While a senior in high school, Jasanoff got his start in science with a part-time job washing test tubes in a lab at Cornell. “That wasn’t a very technically sophisticated job, but I occasionally would hit up the local grad students and postdocs for slightly more scientific insight into what was going on,” he says.
As an undergraduate at Harvard, Jasanoff studied biochemical sciences and had a strong interest in structural biology, using the techniques of X-ray crystallography and nuclear magnetic resonance (NMR) to study molecules far too small to examine with the naked eye. “I like molecules,” he says, adding, “My mother always says it’s an outgrowth of my fascination with LEGO.”
He stayed at Harvard to get his PhD in biophysics, then went to MIT’s Whitehead Institute to begin independent research as a Whitehead Fellow. With a growing interest in some of the “timeless questions” of neuroscience, he began working on molecular-level neuroimaging — trading the relative predictability of structural biology for the complexity of a field “famous among many for its unanswerable questions,” he says.
Direct measurements
Functional MRI, or fMRI, currently one of the best ways to try to address those questions, provides an indirect view of what’s happening inside the brain, and can only reveal average activity in large regions. Meanwhile, traditional neuroscience techniques such as optical imaging provide a precise record of activity at the cellular level but cannot be done non-invasively over large areas of the brain.
Jasanoff wanted to find a way to have the best of both worlds — imaging large brain regions non-invasively, but with cellular precision.
He spent several years as a postdoc trying to achieve that in flies, until he realized that to be successful, he would have to develop his own molecular tools. “I tried one after another failed or weak experiments,” he recalls. “I sort of hoped there were off-the-shelf chemicals and reagents that could be useful for this, and that was probably foolhardy.”
Since joining the MIT faculty in 2004, Jasanoff has developed sensors that can be used with fMRI to monitor the neurotransmitters dopamine and serotonin, as well as calcium and other signaling molecules. The sensors, which currently can only be used in animals, include a section that binds to the target molecule, as well as a magnetic component that allows them to become visible with MRI.
Dopamine holds great interest for neuroscientists because of its role in reward, addiction and neurodegenerative disorders such as Parkinson’s disease. Jasanoff’s lab is now focusing on the role of rewards, or positive reinforcement of behavior, in decision making.
“This is one of the areas of neuroscience where I think we can make a difference relatively soon, just because we’ve got the tools for it,” Jasanoff says. “We’re also hard at work on sensors for a range of other molecular targets; our vision is to have a whole set of these probes available for ‘dissecting’ multiple aspects of neural function in living, intact brains.”

New tools to answer timeless questions

After finishing his PhD in molecular biophysics, Alan Jasanoff decided to veer away from that field and try looking into some of the biggest questions in neuroscience: How do we perceive things? What happens in our brains when we make decisions?

After a few months, however, he realized that he didn’t have the tools he wanted to use — so he decided to start making his own.

Jasanoff, who recently earned tenure in MIT’s Department of Biological Engineering, now specializes in developing novel brain-imaging agents that can reveal information more detailed than other human brain-imaging techniques such as fMRI and PET, and more comprehensive than traditional neuroscience measurements such as microscopy and electrode recordings. With the new tools, he is also beginning to explore some of the fundamental questions that first drew him into neuroscience.

Neuroscientists commonly use fMRI, which measures blood flow in the , as a proxy for neural activity. In the past several years, Jasanoff has developed sensors that can be used with fMRI to image brain activity more directly, by measuring levels of neurotransmitters (the chemicals that carry messages between neurons) and calcium, which enters neurons when they fire.

Using those sensors, Jasanoff has started exploring how positive reinforcement influences behavior and decision making in animals. His work could also be applicable to fields outside of neuroscience, because intracellular signaling molecules such as calcium “are really ubiquitous — not just in neuronal signaling but signaling throughout the body, during development, immune-cell activity and so on,” says Jasanoff, who is an associate member of MIT’s McGovern Institute for Brain Research and an associate professor of biological engineering, nuclear science and engineering, and brain and cognitive sciences.

As a teenager, Jasanoff had a strong interest in science and two role models for a career in academia — his parents, both social scientists. Jasanoff spent his childhood first in Cambridge, Mass., where his father taught at Harvard University, then Ithaca, N.Y., where both parents were professors at Cornell University. His parents, Jay and Sheila Sen Jasanoff, have since returned to Harvard. “My sister Maya is also a professor at Harvard, so I’m the black sheep,” Jasanoff jokes.

While a senior in high school, Jasanoff got his start in science with a part-time job washing test tubes in a lab at Cornell. “That wasn’t a very technically sophisticated job, but I occasionally would hit up the local grad students and postdocs for slightly more scientific insight into what was going on,” he says.

As an undergraduate at Harvard, Jasanoff studied biochemical sciences and had a strong interest in structural biology, using the techniques of X-ray crystallography and nuclear magnetic resonance (NMR) to study molecules far too small to examine with the naked eye. “I like molecules,” he says, adding, “My mother always says it’s an outgrowth of my fascination with LEGO.”

He stayed at Harvard to get his PhD in biophysics, then went to MIT’s Whitehead Institute to begin independent research as a Whitehead Fellow. With a growing interest in some of the “timeless questions” of neuroscience, he began working on molecular-level neuroimaging — trading the relative predictability of structural biology for the complexity of a field “famous among many for its unanswerable questions,” he says.

Direct measurements

Functional MRI, or fMRI, currently one of the best ways to try to address those questions, provides an indirect view of what’s happening inside the brain, and can only reveal average activity in large regions. Meanwhile, traditional neuroscience techniques such as optical imaging provide a precise record of activity at the cellular level but cannot be done non-invasively over large areas of the brain.

Jasanoff wanted to find a way to have the best of both worlds — imaging large brain regions non-invasively, but with cellular precision.

He spent several years as a postdoc trying to achieve that in flies, until he realized that to be successful, he would have to develop his own molecular tools. “I tried one after another failed or weak experiments,” he recalls. “I sort of hoped there were off-the-shelf chemicals and reagents that could be useful for this, and that was probably foolhardy.”

Since joining the MIT faculty in 2004, Jasanoff has developed sensors that can be used with fMRI to monitor the neurotransmitters dopamine and serotonin, as well as calcium and other signaling molecules. The sensors, which currently can only be used in animals, include a section that binds to the target molecule, as well as a magnetic component that allows them to become visible with MRI.

Dopamine holds great interest for neuroscientists because of its role in reward, addiction and neurodegenerative disorders such as Parkinson’s disease. Jasanoff’s lab is now focusing on the role of rewards, or positive reinforcement of behavior, in decision making.

“This is one of the areas of  where I think we can make a difference relatively soon, just because we’ve got the tools for it,” Jasanoff says. “We’re also hard at work on sensors for a range of other molecular targets; our vision is to have a whole set of these probes available for ‘dissecting’ multiple aspects of neural function in living, intact brains.”


Your brain on ‘shrooms: fMRI elucidates neural correlates of psilocybin psychedelic state

Psychedelic substances have long been used for healing, ceremonial, or mind-altering subjective experiences due to compounds that, when ingested or inhaled, generate hallucinations, perceptual distortions, or altered states of awareness. Of these, the psychedelic substance psilocybin, the prodrug (a precursor of a drug that must in vivo chemical conversion by metabolic processes before becoming an active pharmacological agent) of psilocin (4-hydroxy-dimethyltryptamine) and the key hallucinogen found in so-called magic mushrooms, is widely used not only in healing ceremonies, but, more recently, in psychotherapy as well – but little has been known about its specific activity in the brain.
Recently, however, scientists in the Neuropsychopharmacology Unit at Imperial College London used complementary blood-oxygen level dependent (BOLD) functional MRI, or fMRI, in conjunction with a technique for imaging the transition from normal waking consciousness to the psychedelic state. The study found decreased blood flow and BOLD in the thalamus, anterior and posterior cingulate cortex, and medial prefrontal cortex. The researchers concluded that the surprising results strongly suggest that the subjective effects of psychedelic drugs are caused by decreased activity and connectivity in the brain’s key connector hubs, enabling a state of unconstrained cognition.
Lead researcher Dr. Robin L. Carhart-Harris, working in the Neuropsychopharmacology Unit created by Prof. David J. Nutt, recounts the team’s main challenges in establishing an fMRI methodology that would be specific enough to highly correlate neurophysiological activity with the neuronal presence or absence of psilocybin. “There were a number of considerations,” Carhart-Harris tells Medical Xpress. “In terms of experimental design, we had to determine the precise dose and delivery protocol that would be appropriate for obtaining clear fMRI results. “For example,” he explains, “we had to consider temporal dynamics: If the drug was administered orally, the protracted period of time between ingestion, metabolism, and crossing of the blood-brain barrier would fall outside of the short scanning window needed to capture induced brain activity.” They therefore had to rely on intravenous administration.
“Another issue,” Carhart-Harris adds, “was methodological – specifically, isolating any placebo effect derived from changes not due to the injection itself, such as anticipatory anxiety.” The team also had to measure physiological parameters, including breathing and heart rate, in order to use these signals as weighting factors, correlate with baseline levels and remove them as a possible explanation of any observed brain changes.

To address these challenges, Carhart-Harris points to the pilot work the team performed in order to determine the optimal dose. “The original dose was too low in our mock scanner environment, in which subjects were asked to rate regular subjective or perceptual experiences< he recalls. “However, that simply wouldn’t work in a scanning environment, since their very response would interfere with fMRI measurement.”
Regarding next steps in their research, Carhart-Harris sees obtaining a grant to study psilocybin as a treatment for depression – scheduled to begin at the end of 2012 – as key. “Psilocybin decreases brain activity in regions such as the medial prefrontal cortex,” he explains, “that are overactive in depression.” The team may also perform the same investigations with alternative psychedelic compounds, such as MDMA (3,4-methylenedioxymethamphetamine) – a synthetic, psychoactive drug, commonly known as Ecstasy, that is chemically similar to the stimulant methamphetamine.
Carhart-Harris is also interested in the effects of psilocybin on memory. “When subjects are in the scanner,” he illustrates, “and are shown personal memory cues, then asked to close their eyes and remember the emotions at the time of the original event, the recalled emotions are more vivid – indicating elevated brain activation – when under the effects of psilocybin.” Moreover, Carhart-Harris notes that when administered psilocybin when undergoingpsychotherapy, there is an increased incidence of sudden personal insights. He speculates that this suggests that psilocybin-induced visual changes indicate that the visual pathways are more sensitive to signals from the hippocampus, which is involved in memory, when under psilocybin.
In addition to depression, Carhart-Harris observes, there are other research and applications that might benefit from the team’s findings. “Those suffering from cluster headaches,” he notes, “report excruciating pain that is difficult to treat, sometimes describing it as worse than the pain childbirth. During such headaches, they show an increase in hypothalamic activity to date has only been ameliorated by deep brain stimulation. However,” he concludes, “when administered psilocybin, they display a decrease in hypothalamic activity and a corresponding suspension of cluster headaches.”
More information: Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin, Published online before print January 23, 2012, doi: 10.1073/pnas.1119598109, PNAS February 7, 2012 vol. 109 no. 6 2138-2143.

Your brain on ‘shrooms: fMRI elucidates neural correlates of psilocybin psychedelic state

Psychedelic substances have long been used for healing, ceremonial, or mind-altering subjective experiences due to compounds that, when ingested or inhaled, generate hallucinations, perceptual distortions, or altered states of awareness. Of these, the psychedelic substance psilocybin, the prodrug (a precursor of a drug that must in vivo chemical conversion by metabolic processes before becoming an active pharmacological agent) of psilocin (4-hydroxy-dimethyltryptamine) and the key hallucinogen found in so-called magic mushrooms, is widely used not only in healing ceremonies, but, more recently, in psychotherapy as well – but little has been known about its specific activity in the brain.

Recently, however, scientists in the Neuropsychopharmacology Unit at Imperial College London used complementary blood-oxygen level dependent (BOLD) functional MRI, or fMRI, in conjunction with a technique for imaging the transition from normal waking consciousness to the psychedelic state. The study found decreased blood flow and BOLD in the thalamus, anterior and posterior cingulate cortex, and medial prefrontal cortex. The researchers concluded that the surprising results strongly suggest that the subjective effects of psychedelic drugs are caused by decreased activity and connectivity in the brain’s key connector hubs, enabling a state of unconstrained cognition.

Lead researcher Dr. Robin L. Carhart-Harris, working in the Neuropsychopharmacology Unit created by Prof. David J. Nutt, recounts the team’s main challenges in establishing an fMRI methodology that would be specific enough to highly correlate neurophysiological activity with the neuronal presence or absence of psilocybin. “There were a number of considerations,” Carhart-Harris tells Medical Xpress. “In terms of experimental design, we had to determine the precise dose and delivery protocol that would be appropriate for obtaining clear fMRI results. “For example,” he explains, “we had to consider temporal dynamics: If the drug was administered orally, the protracted period of time between ingestion, metabolism, and crossing of the blood-brain barrier would fall outside of the short scanning window needed to capture induced brain activity.” They therefore had to rely on intravenous administration.

“Another issue,” Carhart-Harris adds, “was methodological – specifically, isolating any placebo effect derived from changes not due to the injection itself, such as anticipatory anxiety.” The team also had to measure physiological parameters, including breathing and heart rate, in order to use these signals as weighting factors, correlate with baseline levels and remove them as a possible explanation of any observed brain changes.

To address these challenges, Carhart-Harris points to the pilot work the team performed in order to determine the optimal dose. “The original dose was too low in our mock scanner environment, in which subjects were asked to rate regular subjective or perceptual experiences< he recalls. “However, that simply wouldn’t work in a scanning environment, since their very response would interfere with fMRI measurement.”

Regarding next steps in their research, Carhart-Harris sees obtaining a grant to study psilocybin as a treatment for depression – scheduled to begin at the end of 2012 – as key. “Psilocybin decreases brain activity in regions such as the medial prefrontal cortex,” he explains, “that are overactive in depression.” The team may also perform the same investigations with alternative psychedelic , such as MDMA (3,4-methylenedioxymethamphetamine) – a synthetic, psychoactive drug, commonly known as Ecstasy, that is chemically similar to the stimulant methamphetamine.

Carhart-Harris is also interested in the effects of psilocybin on memory. “When subjects are in the scanner,” he illustrates, “and are shown personal memory cues, then asked to close their eyes and remember the emotions at the time of the original event, the recalled emotions are more vivid – indicating elevated brain activation – when under the effects of psilocybin.” Moreover, Carhart-Harris notes that when administered psilocybin when undergoing, there is an increased incidence of sudden personal insights. He speculates that this suggests that psilocybin-induced visual changes indicate that the visual pathways are more sensitive to signals from the hippocampus, which is involved in memory, when under psilocybin.

In addition to depression, Carhart-Harris observes, there are other research and applications that might benefit from the team’s findings. “Those suffering from cluster headaches,” he notes, “report excruciating pain that is difficult to treat, sometimes describing it as worse than the pain childbirth. During such headaches, they show an increase in hypothalamic activity to date has only been ameliorated by deep brain stimulation. However,” he concludes, “when administered psilocybin, they display a decrease in hypothalamic activity and a corresponding suspension of cluster headaches.”

More information: Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin, Published online before print January 23, 2012, doi: 10.1073/pnas.1119598109, PNAS February 7, 2012 vol. 109 no. 6 2138-2143.

fMRI brain imaging illuminates magic mushrooms’ psychedelic effects

Brain scans of people under the influence of the psilocybin, the active ingredient in magic mushrooms, have given scientists the most detailed picture to date of how psychedelic drugs work. The findings of two studies being published in scientific journals this week identify areas of the brain where activity is suppressed by psilocybin and suggest that it helps people to experience memories more vividly.

In the first study, published today in  (PNAS), 30 healthy volunteers had psilocybin infused into their blood while inside  (MRI) scanners, which measure changes in brain activity. The scans showed that activity decreased in “hub” regions of the brain – areas that are especially well-connected with other areas.

Professor David Nutt, from the Department of Medicine at Imperial College London, the senior author of both studies, said: “Psychedelics are thought of as ‘mind-expanding’ drugs so it has commonly been assumed that they work by increasing brain activity, but surprisingly, we found that psilocybin actually caused activity to decrease in areas that have the densest connections with other areas. These hubs constrain our experience of the world and keep it orderly. We now know that deactivating these regions leads to a state in which the world is experienced as strange.”

The second study, due to be published online by the British Journal of Psychiatry on Thursday, found that psilocybin enhanced volunteers’ recollections of personal memories, which the researchers suggest could make it useful as an adjunct to psychotherapy.

The intensity of the effects reported by the participants, including visions of geometric patterns, unusual bodily sensations and altered sense of space and time, correlated with a decrease in oxygenation and  in certain parts of the brain.

The function of these areas, the medial prefrontal cortex (mPFC) and the posterior cingulate cortex (PCC), is the subject of debate among neuroscientists, but the PCC is proposed to have a role in consciousness and self-identity. The mPFC is known to be hyperactive in depression, so psilocybin’s action on this area could be responsible for some antidepressant effects that have been reported. Similarly, psilocybin reduced blood flow in the hypothalamus, where blood flow is increased during cluster headaches, perhaps explaining why some sufferers have said symptoms improved under psilocybin.

In the British Journal of Psychiatry study 10 volunteers viewed written cues that prompted them to think about memories associated with strong positive emotions while inside the brain scanner. The participants rated their recollections as being more vivid after taking psilocybin compared with a placebo, and with psilocybin there was increased activity in areas of the brain that process vision and other sensory information.

Participants were also asked to rate changes in their emotional wellbeing two weeks after taking the psilocybin and placebo. Their ratings of vividness under the drug showed a significant positive correlation with their wellbeing two weeks afterwards. In a previous study of 12 people in 2011, researchers found that people with anxiety who were given a single psilocybin treatment had decreased depression scores six months later.

Dr Robin Carhart-Harris, from the Department of Medicine at Imperial College London, the first author of both papers, said: “Psilocybin was used extensively in psychotherapy in the 1950s, but the biological rationale for its use has not been properly investigated until now. Our findings support the idea that psilocybin facilitates access to personal memories and emotions.

"Previous studies have suggested that psilocybin can improve people’s sense of emotional wellbeing and even reduce depression in people with anxiety. This is consistent with our finding that psilocybin decreases mPFC activity, as many effective depression treatments do. The effects need to be investigated further, and ours was only a small study, but we are interested in exploring psilocybin’s potential as a therapeutic tool."

The researchers acknowledged that because the participants in this study had volunteered after having previous experience of psychedelics, they may have held prior assumptions about the drugs which could have contributed to the positive memory rating and the reports of improved wellbeing in the follow-up.

Functional MRI measures  indirectly by mapping blood flow or the oxygen levels in the blood. When an area becomes more active, it uses more glucose, but generates energy in rapid chemical reactions that do not use oxygen. Consequently, blood flow increases but oxygen consumption does not, resulting in a higher concentration of oxygen in blood in the local veins.

In the PNAS study, the volunteers were split into two groups, each studied using a different type of fMRI: 15 were scanned using arterial spin labelling (ASL) perfusion fMRI, which measures blood flow, and 15 using blood-oxygen level-dependent (BOLD) fMRI. The two modalities produced similar results, strongly suggesting that the observed effects were genuine.

More information: R Carhart-Harris et al. ‘Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin.’Proceedings of the National Academy of Sciences, published online 23 January 2012.

(http://medicalxpress.com/news/2012-01-fmri-brain-imaging-illuminates-magic.html)

Psychopaths&#8217; brains show differences in structure and function
 
Images of prisoners&#8217; brains show important differences between those who are diagnosed as psychopaths and those who aren&#8217;t, according to a new study led by University of Wisconsin-Madison researchers.

The results could help explain the callous and impulsive anti-social behavior exhibited by some psychopaths.
The study showed that psychopaths have reduced connections between the ventromedial prefrontal cortex (vmPFC), the part of the brain responsible for sentiments such as empathy and guilt, and the amygdala, which mediates fear and anxiety. Two types of brain images were collected. Diffusion tensor images (DTI) showed reduced structural integrity in the white matter fibers connecting the two areas, while a second type of image that maps brain activity, a functional magnetic resonance image (fMRI), showed less coordinated activity between the vmPFC and the amygdala.
"This is the first study to show both structural and functional differences in the brains of people diagnosed with psychopathy," says Michael Koenigs, assistant professor of psychiatry in the University of Wisconsin School of Medicine and Public Health. "Those two structures in the brain, which are believed to regulate emotion and social behavior, seem to not be communicating as they should."
The study, which took place in a medium-security prison in Wisconsin, is a unique collaborative between three laboratories.
UW-Madison psychology Professor Joseph Newman has had a long term interest in studying and diagnosing those with psychopathy and has worked extensively in the Wisconsin corrections system. Dr. Kent Kiehl, of the University of New Mexico and the MIND Research Network, has a mobile MRI scanner that he brought to the prison and used to scan the prisoners&#8217; brains. Koenigs and his graduate student, Julian Motzkin, led the analysis of the brain scans.
The study compared the brains of 20 prisoners with a diagnosis of psychopathy with the brains of 20 other prisoners who committed similar crimes but were not diagnosed with psychopathy.
"The combination of structural and functional abnormalities provides compelling evidence that the dysfunction observed in this crucial social-emotional circuitry is a stable characteristic of our psychopathic offenders,&#8221; Newman says. "I am optimistic that our ongoing collaborative work will shed more light on the source of this dysfunction and strategies for treating the problem."
Newman notes that none of this work would be possible without the extraordinary support provided by the Wisconsin Department of Corrections, which he called &#8220;the silent partner in this research.&#8221; He says the DOC has demonstrated an unprecedented commitment to supporting research designed to facilitate the differential diagnosis and treatment of prisoners.
The study, published in the most recent Journal of Neuroscience, builds on earlier work by Newman and Koenigs that showed that psychopaths&#8217; decision-making mirrors that of patients with known damage to their ventromedial prefrontal cortex(vmPFC). This bolsters evidence that problems in that part of the brain are connected to the disorder.
"The decision-making study showed indirectly what this study shows directly – that there is a specific brain abnormality associated with criminal psychopathy,&#8221; Koenigs adds.
(http://medicalxpress.com/news/2011-11-psychopaths-brains-differences-function.html)

Psychopaths’ brains show differences in structure and function

Images of prisoners’ brains show important differences between those who are diagnosed as psychopaths and those who aren’t, according to a new study led by University of Wisconsin-Madison researchers.

The results could help explain the callous and impulsive anti-social behavior exhibited by some psychopaths.

The study showed that psychopaths have reduced connections between the ventromedial prefrontal cortex (vmPFC), the part of the brain responsible for sentiments such as empathy and guilt, and the amygdala, which mediates fear and anxiety. Two types of  were collected. Diffusion tensor images (DTI) showed reduced structural integrity in the  fibers connecting the two areas, while a second type of image that maps , a functional  (fMRI), showed less coordinated activity between the vmPFC and the .

"This is the first study to show both structural and functional differences in the brains of people diagnosed with psychopathy," says Michael Koenigs, assistant professor of psychiatry in the University of Wisconsin School of Medicine and Public Health. "Those two structures in the brain, which are believed to regulate emotion and social behavior, seem to not be communicating as they should."

The study, which took place in a medium-security prison in Wisconsin, is a unique collaborative between three laboratories.

UW-Madison  Joseph Newman has had a long term interest in studying and diagnosing those with psychopathy and has worked extensively in the Wisconsin corrections system. Dr. Kent Kiehl, of the University of New Mexico and the MIND Research Network, has a mobile  that he brought to the prison and used to scan the prisoners’ brains. Koenigs and his graduate student, Julian Motzkin, led the analysis of the brain scans.

The study compared the brains of 20 prisoners with a diagnosis of psychopathy with the brains of 20 other prisoners who committed similar crimes but were not diagnosed with psychopathy.

"The combination of structural and functional abnormalities provides compelling evidence that the dysfunction observed in this crucial social-emotional circuitry is a stable characteristic of our psychopathic offenders,” Newman says. "I am optimistic that our ongoing collaborative work will shed more light on the source of this dysfunction and strategies for treating the problem."

Newman notes that none of this work would be possible without the extraordinary support provided by the Wisconsin Department of Corrections, which he called “the silent partner in this research.” He says the DOC has demonstrated an unprecedented commitment to supporting research designed to facilitate the differential diagnosis and treatment of prisoners.

The study, published in the most recent Journal of Neuroscience, builds on earlier work by Newman and Koenigs that showed that psychopaths’ decision-making mirrors that of patients with known damage to their (vmPFC). This bolsters evidence that problems in that part of the brain are connected to the disorder.

"The decision-making study showed indirectly what this study shows directly – that there is a specific brain abnormality associated with criminal ,” Koenigs adds.

(http://medicalxpress.com/news/2011-11-psychopaths-brains-differences-function.html)

 
What Psychology Tells Us About the Brain and Vice Versa Part I: An Intro to Cognitive Neuroscience 2.0
A new way to look at brain images&#8212;and brains.
 
Since the original invention of functional Magnetic Resonance Imaging (fMRI) in the early 1990s, the field&#8212;and the public&#8212;have become nearly obsessed with the technique.  The result has been literally tens of thousands of functional brain imaging studies, investigating the neural underpinnings of everything from addition to addiction.  Indeed, the beautiful pictures that fMRI produces have become so ubiquitous in both the public and the scientific imagination that we might fairly call the last 20 years of cognitive neuroscience &#8220;the age of the image&#8221;.

That was then, this is now.  While you shouldn&#8217;t expect to see any less brain imaging in the coming years, we are undergoing a sea change in the way those images are being interpreted.  Instead of reading these images individually, researchers over the past few years have begun pioneering efforts to interpret these images collectively.   Since no human being can hope to assimilate and make visual sense out of thousands of brain images, investigating all manner of psychological phenomena, these researchers use various computational methods to analyze and find hidden patterns in all of that data.
This movement&#8212;recently dubbed &#8220;Cognitive Neuroscience 2.0 " by Tal Yarkoni and colleagues&#8212;promises to radically alter our understanding both of the brain, and of brain science. In this post I&#8217;ll mention one of the ways it is changing our understanding of brain organization, and in Part II, I&#8217;ll talk about its promise to change the way we pursue psychology.
For a simple example of the sort of surprising insight that collective data interpretation can produce, consider the principle of selectivity.  A guiding ideal of brain science for at least 50 years, selectivity is the notion that individual neurons, as well as larger networks, respond to only a narrow class of stimuli-straight lines but not curved ones; faces but not houses; nouns but not verbs.  The principle of selectivity is what is behind the popular understanding of a brain composed of neural specialists clustered together like ethnic neighborhoods in New York-vision downtown, language over on the west side, executive control somewhere in midtown Manhattan.  Certainly individual fMRI studies can reinforce this impression; for any given investigation, the brain will &#8220;light up&#8221; in only a few places, apparently highlighting the specialists responsible for the task under investigation. 
But when you look at brain activity across many, many such individual studies, things don&#8217;t really look that way.  One early study  investigated 135 experiments in four different cognitive domains: language, vision, attention and memory, and color coded the regions that were activated by tasks in each using standard 4-color printing techniques.  Instead of seeing large regions of the brain painted in simple primary colors, indicating dedication to tasks in a single domain, each brain region took on its own mixed hue, reflecting its contribution to many different tasks across the four domains. This finding was recently confirmed by a much larger study  involving over 1,100 experiments across 11 different cognitive domains. Bottom line: the neighborhoods of the brain are highly integrated and functionally diverse.
The picture below represents those brain demographics on a cool-to-hot scale, in a way designed to emphasize the differences in diversity between regions.  It uses a scale of zero (black) to one (bright red), where zero means all activity restricted to a single domain, and one means a region that is equally likely to be active in all 11 domains, like a perfectly integrated neighborhood.  It turns out that the 78 standard anatomical regions of the brain have an average diversity of 0.70!  In fact, a typical brain region is active in tasks across nine of the eleven domains.

This probably comes as a surprise to many readers.  But when you think about it from an evolutionary perspective, it makes some sense.  If the brain were a collection of regionally segregated specialists, then that would mean that new cognitive abilities would emerge only via the development of new dedicated brain tissue, like adding a new specialized organ or appendage.  That&#8217;s one possible pathway, of course, but evolution is also known to repurpose existing resources to meet emerging challenges.  If that&#8217;s the way the brain evolved-and it does seem to be a more efficient use of metabolically expensive brain matter-then what we would expect to see is what we indeed see: regions used and reused for a variety of purposes in different circumstances.
One important upshot of this is that there typically isn&#8217;t a &#8220;brain area for X&#8221;. The brain doesn&#8217;t operate by differentially activating one or a few dedicated local regions to achieve some task.  Instead, the brain dynamically assembles different coalitions of partners.  Achieving a task is not a matter of finding a single neural specialist, but is rather about putting together the right neural team for the job.
(Michael Anderson | PT)

What Psychology Tells Us About the Brain and Vice Versa Part I: An Intro to Cognitive Neuroscience 2.0

A new way to look at brain images—and brains.

Since the original invention of functional Magnetic Resonance Imaging (fMRI) in the early 1990s, the field—and the public—have become nearly obsessed with the technique.  The result has been literally tens of thousands of functional brain imaging studies, investigating the neural underpinnings of everything from addition to addiction.  Indeed, the beautiful pictures that fMRI produces have become so ubiquitous in both the public and the scientific imagination that we might fairly call the last 20 years of cognitive neuroscience “the age of the image”.

That was then, this is now.  While you shouldn’t expect to see any less brain imaging in the coming years, we are undergoing a sea change in the way those images are being interpreted.  Instead of reading these images individually, researchers over the past few years have begun pioneering efforts to interpret these images collectively.   Since no human being can hope to assimilate and make visual sense out of thousands of brain images, investigating all manner of psychological phenomena, these researchers use various computational methods to analyze and find hidden patterns in all of that data.

This movement—recently dubbed “Cognitive Neuroscience 2.0 " by Tal Yarkoni and colleagues—promises to radically alter our understanding both of the brain, and of brain science. In this post I’ll mention one of the ways it is changing our understanding of brain organization, and in Part II, I’ll talk about its promise to change the way we pursue psychology.

For a simple example of the sort of surprising insight that collective data interpretation can produce, consider the principle of selectivity.  A guiding ideal of brain science for at least 50 years, selectivity is the notion that individual neurons, as well as larger networks, respond to only a narrow class of stimuli-straight lines but not curved ones; faces but not houses; nouns but not verbs.  The principle of selectivity is what is behind the popular understanding of a brain composed of neural specialists clustered together like ethnic neighborhoods in New York-vision downtown, language over on the west side, executive control somewhere in midtown Manhattan.  Certainly individual fMRI studies can reinforce this impression; for any given investigation, the brain will “light up” in only a few places, apparently highlighting the specialists responsible for the task under investigation. 

But when you look at brain activity across many, many such individual studies, things don’t really look that way.  One early study  investigated 135 experiments in four different cognitive domains: language, vision, attention and memory, and color coded the regions that were activated by tasks in each using standard 4-color printing techniques.  Instead of seeing large regions of the brain painted in simple primary colors, indicating dedication to tasks in a single domain, each brain region took on its own mixed hue, reflecting its contribution to many different tasks across the four domains. This finding was recently confirmed by a much larger study  involving over 1,100 experiments across 11 different cognitive domains. Bottom line: the neighborhoods of the brain are highly integrated and functionally diverse.

The picture below represents those brain demographics on a cool-to-hot scale, in a way designed to emphasize the differences in diversity between regions.  It uses a scale of zero (black) to one (bright red), where zero means all activity restricted to a single domain, and one means a region that is equally likely to be active in all 11 domains, like a perfectly integrated neighborhood.  It turns out that the 78 standard anatomical regions of the brain have an average diversity of 0.70!  In fact, a typical brain region is active in tasks across nine of the eleven domains.

This probably comes as a surprise to many readers.  But when you think about it from an evolutionary perspective, it makes some sense.  If the brain were a collection of regionally segregated specialists, then that would mean that new cognitive abilities would emerge only via the development of new dedicated brain tissue, like adding a new specialized organ or appendage.  That’s one possible pathway, of course, but evolution is also known to repurpose existing resources to meet emerging challenges.  If that’s the way the brain evolved-and it does seem to be a more efficient use of metabolically expensive brain matter-then what we would expect to see is what we indeed see: regions used and reused for a variety of purposes in different circumstances.

One important upshot of this is that there typically isn’t a “brain area for X”. The brain doesn’t operate by differentially activating one or a few dedicated local regions to achieve some task.  Instead, the brain dynamically assembles different coalitions of partners.  Achieving a task is not a matter of finding a single neural specialist, but is rather about putting together the right neural team for the job.

(Michael Anderson | PT)

 
Guilt, Cooperation Linked by Neural Network: Why People Choose to Cooperate Rather Than Act Selfishly
A team of researchers at the University of Arizona has brought an MRI to bear on the study of a familiar and age-old emotion &#8212; guild.
What makes the investigation unique is the use of fMRI scans to target the regions of the brain associated with guilt. It also opens a new avenue in understanding behavioral disorders associated with guilt, such as depression and anxiety.
The study is published by Cell Press in the journal Neuron.
The authors &#8212; Luke Chang, Alec Smith, Martin Dufwenberg and Alan Sanfey &#8212; also come from two seemingly disparate areas: cognitive neuroscience and economics.
Sanfey is a recognized neuroscientist who also has an appointment at the Donders Institute at Radboud University in The Netherlands, and Chang is a doctoral student in the UA psychology department.
Dufwenberg is a behavioral economist in the UA Eller College of Management. Smith, a former doctoral student in Eller&#8217;s economics department, is now a post-doctoral scholar in economics at the California Institute of Technology.
The collaboration began when Dufwenberg and Smith were &#8220;reaching out for people who would be interested&#8221; in cross-disciplinary partnerships when they met and teamed up with Sanfey and Chang.
Guilt, in this case the failure to live up to the expectations of others. It is an emotion that likely has its roots in the evolutionary history of humans. And the aversion to guilt is a factor in motivating cooperative behavior.
The thrust of the study, said Chang, is trying to understand why people cooperate.
"One idea is that most people cooperate because it feels good to do it. And there is some brain imaging data that shows activity in reward-related regions of the brain when people are cooperating.
"But there is a whole other world of motivation to do good because you don&#8217;t want to feel bad. That is the idea behind guilt aversion," Chang said.
To test this, 30 volunteers played a game appropriate for testing a mathematical theory of guilt aversion that Dufwenberg devised. In it, &#8220;investors&#8221; were asked to award a certain amount of money to a &#8220;trustee,&#8221; whose expectations regarding how much the investor expected to get back were elicited. The trustees were then scanned using fMRI while deciding how much money should be returned to their investors.
"The theory will then operate on the expectations the players have," said Dufwenberg. "I would feel guilt if I give you less than I believe that you expect that you will get. Then we measure expectations in the experimental situation. The theory predicts when people will experience guilt. Then we see how that correlates with brain activity."
The fMRI scans identified regions in the brain involved in guilt-motivated cooperation while test subjects made their decisions whether or not to honor a partner&#8217;s trust. Different areas of the brain became active during those decisions based on their choosing to cooperate, or to abuse the trust and maximize their own financial gain.
The report said the results show that &#8220;a neural system previously implicated in expectation processing plays a critical role in assessing moral sentiments that in turn can sustain human cooperation in the face of temptation.&#8221;
Civilized society is based on cooperation and trust, from behaviors a simple and informal as opening a door for someone carrying heavy packages or tipping a restaurant server to complex legal agreements between corporations or countries. Understanding the neural structures behind these behaviors promises to offer new insights into complex behaviors of trust and reciprocity.
Chang said the collaboration among economists, psychologists and neuroscientists is instrumental in understanding the biological mechanisms underlying complex social behavior, such as guilt, and has real world implications for understanding clinical disorders such as depression anxiety and psychopathy.
Alan Sanfey, the senior author of the study, said &#8220;the study demonstrates the potential in cross-disciplinary collaborations of this nature, for example, in developing more complete models of how people make decisions in complex social situations.&#8221;
As a behavioral economist, Dufwenberg argues that factors such as emotions may be important drivers of economic outcomes, and that the mathematical models that economists use can be augmented to include such psychological aspects.
"In the end, it&#8217;s a two-way exchange. Economists take inspiration from the richer concept of man usually considered in psychology, but at the same time they have something to offer psychologists through their analytical tools.
"Remember how guilt depends on beliefs about beliefs about outcomes? These are hard to observe, hard to test. I&#8217;m excited about the idea of using neuroscience tools to test economic theory."
(Original Summary in SD)
(Full Article in the journal Neuron)

Guilt, Cooperation Linked by Neural Network: Why People Choose to Cooperate Rather Than Act Selfishly

A team of researchers at the University of Arizona has brought an MRI to bear on the study of a familiar and age-old emotion — guild.

What makes the investigation unique is the use of fMRI scans to target the regions of the brain associated with guilt. It also opens a new avenue in understanding behavioral disorders associated with guilt, such as depression and anxiety.

The study is published by Cell Press in the journal Neuron.

The authors — Luke Chang, Alec Smith, Martin Dufwenberg and Alan Sanfey — also come from two seemingly disparate areas: cognitive neuroscience and economics.

Sanfey is a recognized neuroscientist who also has an appointment at the Donders Institute at Radboud University in The Netherlands, and Chang is a doctoral student in the UA psychology department.

Dufwenberg is a behavioral economist in the UA Eller College of Management. Smith, a former doctoral student in Eller’s economics department, is now a post-doctoral scholar in economics at the California Institute of Technology.

The collaboration began when Dufwenberg and Smith were “reaching out for people who would be interested” in cross-disciplinary partnerships when they met and teamed up with Sanfey and Chang.

Guilt, in this case the failure to live up to the expectations of others. It is an emotion that likely has its roots in the evolutionary history of humans. And the aversion to guilt is a factor in motivating cooperative behavior.

The thrust of the study, said Chang, is trying to understand why people cooperate.

"One idea is that most people cooperate because it feels good to do it. And there is some brain imaging data that shows activity in reward-related regions of the brain when people are cooperating.

"But there is a whole other world of motivation to do good because you don’t want to feel bad. That is the idea behind guilt aversion," Chang said.

To test this, 30 volunteers played a game appropriate for testing a mathematical theory of guilt aversion that Dufwenberg devised. In it, “investors” were asked to award a certain amount of money to a “trustee,” whose expectations regarding how much the investor expected to get back were elicited. The trustees were then scanned using fMRI while deciding how much money should be returned to their investors.

"The theory will then operate on the expectations the players have," said Dufwenberg. "I would feel guilt if I give you less than I believe that you expect that you will get. Then we measure expectations in the experimental situation. The theory predicts when people will experience guilt. Then we see how that correlates with brain activity."

The fMRI scans identified regions in the brain involved in guilt-motivated cooperation while test subjects made their decisions whether or not to honor a partner’s trust. Different areas of the brain became active during those decisions based on their choosing to cooperate, or to abuse the trust and maximize their own financial gain.

The report said the results show that “a neural system previously implicated in expectation processing plays a critical role in assessing moral sentiments that in turn can sustain human cooperation in the face of temptation.”

Civilized society is based on cooperation and trust, from behaviors a simple and informal as opening a door for someone carrying heavy packages or tipping a restaurant server to complex legal agreements between corporations or countries. Understanding the neural structures behind these behaviors promises to offer new insights into complex behaviors of trust and reciprocity.

Chang said the collaboration among economists, psychologists and neuroscientists is instrumental in understanding the biological mechanisms underlying complex social behavior, such as guilt, and has real world implications for understanding clinical disorders such as depression anxiety and psychopathy.

Alan Sanfey, the senior author of the study, said “the study demonstrates the potential in cross-disciplinary collaborations of this nature, for example, in developing more complete models of how people make decisions in complex social situations.”

As a behavioral economist, Dufwenberg argues that factors such as emotions may be important drivers of economic outcomes, and that the mathematical models that economists use can be augmented to include such psychological aspects.

"In the end, it’s a two-way exchange. Economists take inspiration from the richer concept of man usually considered in psychology, but at the same time they have something to offer psychologists through their analytical tools.

"Remember how guilt depends on beliefs about beliefs about outcomes? These are hard to observe, hard to test. I’m excited about the idea of using neuroscience tools to test economic theory."

(Original Summary in SD)

(Full Article in the journal Neuron)