Scientists Detect A Particle That Could Be A New Form Of Matter (the Tetraquark)

This was posted on io9 this morning, and it comes originally from Universe Today. Researchers at the

Large Hadron Collider have discovered a new particle that may be the theoretical tetraquark, and its discovery would mean that of a new form of matter. It also the raises a lot of new possibilities, including the "quark star," for both physics and cosmology.

"Very simply, the traditional model of a neutron star is that it is made of neutrons. Neutrons consist of three quarks (two down and one up), but it is generally thought that particle interactions within a neutron star are interactions between neutrons. With the existence of tetraquarks, it is possible for neutrons within the core to interact strongly enough to create tetraquarks. This could even lead to the production of pentaquarks and hexaquarks, or even that quarks could interact individually without being bound into color neutral particles. This would produce a hypothetical object known as a quark star."

Very cool stuff.

Scientists Detect A Particle That Could Be A New Form Of Matter

Brian Koberlein — Universe Today

Physicists working at the Large Hadron Collider have spotted a long sought-after exotic particle that's the strongest evidence yet for a new form of matter called a tetraquark. Here's what the discovery could mean to astrophysics.

Above: A neutron star. Credit: Casey Reed/Penn State University.

You may have heard that CERN announced the discovery of a strange particle known as Z(4430). A paper summarizing the results has been published on the physics arxiv, which is a repository for preprint (not yet peer reviewed) physics papers.

The new particle is about four times more massive than a proton, has a negative charge, and appears to be a theoretical particle known as a tetraquark. The results are still young, but if this discovery holds up it could have implications for our understanding of neutron stars.

Image: Chandra.

A Horse Of A Different Color

The building blocks of matter are made of leptons (such as the electron and neutrinos) and quarks (which make up protons, neutrons, and other particles). Quarks are very different from other particles in that they have an electric charge that is 1/3 or 2/3 that of the electron and proton. They also possess a different kind of "charge" known as color. Just as electric charges interact through an electromagnetic force, color charges interact through the strong nuclear force. It is the color charge of quarks that works to hold the nuclei of atoms together. Color charge is much more complex than electric charge. With electric charge there is simply positive (+) and its opposite, negative (-). With color, there are three types (red, green, and blue) and their opposites (anti-red, anti-green, and anti-blue).

Because of the way the strong force works, we can never observe a free quark. The strong force requires that quarks always group together to form a particle that is color neutral. For example, a proton consists of three quarks (two up and one down), where each quark is a different color. With visible light, adding red, green and blue light gives you white light, which is colorless. In the same way, combining a red, green and blue quark gives you a particle which is color neutral. This similarity to the color properties of light is why quark charge is named after colors.
The Tetraquark

Combining a quark of each color into groups of three is one way to create a color neutral particle, and these are known as baryons. Protons and neutrons are the most common baryons. Another way to combine quarks is to pair a quark of a particular color with a quark of its anti-color. For example, a green quark and an anti-green quark could combine to form a color neutral particle. These two-quark particles are known as mesons, and were first discovered in 1947. For example, the positively charged pion consists of an up quark and an antiparticle down quark.

Under the rules of the strong force, there are other ways quarks could combine to form a neutral particle. One of these, the tetraquark, combines four quarks, where two particles have a particular color and the other two have the corresponding anti-colors. Others, such as the pentaquark (3 colors + a color anti-color pair) and the hexaquark (3 colors + 3 anti-colors) have been proposed. But so far all of these have been hypothetical. While such particles would be color neutral, it is also possible that they aren't stable and would simply decay into baryons and mesons.

The Quark Star

There has been some experimental hints of tetraquarks, but this latest result is the strongest evidence of four quarks forming a color neutral particle. This means that quarks can combine in much more complex ways than we originally expected, and this has implications for the internal structure of neutron stars.

ESO/Luís Calçada.

Very simply, the traditional model of a neutron star is that it is made of neutrons. Neutrons consist of three quarks (two down and one up), but it is generally thought that particle interactions within a neutron star are interactions between neutrons. With the existence of tetraquarks, it is possible for neutrons within the core to interact strongly enough to create tetraquarks. This could even lead to the production of pentaquarks and hexaquarks, or even that quarks could interact individually without being bound into color neutral particles. This would produce a hypothetical object known as a quark star.

This is all hypothetical at this point, but verified evidence of tetraquarks will force astrophysicists to reexamine some the assumptions we have about the interiors of neutron stars.

This article originally appeared at Universe Today.

Omnivore - Philosophy for the Public

 

From Bookforum's Omnivore blog, another collection of philosophy links to drag us down the rabbit hole. Included is a review of Mary Midgley's Are You an Illusion? and an article on Midgley's efforts to defend human consciousness against the likes of Richard Dawkins.

There is also a good interview with John Searle, one of the current elder statesmen of philosophy and consciousness.

Philosophy for the public

Apr 10 2014  

9:00AM

• Achille C. Varzi (Columbia): The Magic of Holes. 
• Jeremy Wisnewski (Hartwick): The Misgivings of a Pop Culture Enthusiast: On the Intersection of Philosophy and Entertainment. 
• From Essays in Philosophy, a special issue on Public Philosophy, including Greg Littmann (Southern Illinois): Writing Philosophy for the Public is a Moral Obligation; and Matt Chick (WUSTL) and Matthew LaVine (Buffalo): The Relevance of Analytic Philosophy to Personal, Public, and Democratic Life. 
• Postmodern philosophy and truth on the go: Tim Crane reviews Truth: Philosophy in Transit by John D. Caputo. 
• Stephen Cave reviews Are You an Illusion? by Mary Midgley. 
• Andrew Anthony on Mary Midgley: A late stand for a philosopher with soul. 
• Zan Boag interviews John Searle: “It upsets me when I read the nonsense written by my contemporaries”. 
• Is philosophy stupid? Richard Carrier investigates. 
• Playing with Plato: Philosophers eager to write for popular audiences are finding readers who want answers science can’t offer. 
• Why study philosophy? Hope Reese interviews Rebecca Newberger Goldstein, author of Plato at the Googleplex (and more and more and more and more). 
• Carolyn Gregoire on the unexpected way philosophy majors are changing the world of business. 
• The introduction to The Moral Background: An Inquiry into the History of Business Ethics by Gabriel Abend. 
• Helen Douglas on philosophical counseling as a practice of emancipation. 
• From Existential Comics, a look at the publication of Dungeons & Dragons and Philosophers; and how the Germans play monopoly.

Rick Hanson, PhD, The Effect of Relationships on the Evolution of the Brain

This is a brief but cool little article from Rick Hanson's blog - and this may be preaching to the choir, but it felt worth sharing.

The Effect of Relationships on the Evolution of the Brain

posted on: April 10th, 2014

Your brain is the product of 3.5 billion years of intense evolutionary pressure, including 2.7 million years as tool-using hominids and over 100,000 years as homo sapiens.

Human DNA is about 98-99% identical to chimpanzee DNA. But that crucial 1-2% difference is mainly the genetic factors affecting the brain – especially for its relationship functions. In fact, the latest science suggests that the evolution of the brain was driven in two steps having to do with the survival benefits of strong relationships.

First, among vertebrates, many bird and mammal species developed pair bonding as a way to raise children who survived. (Remember that fish and reptiles generally do not raise their young and may in fact eat them if they happen upon them soon after they hatch.)

The “computational requirements” of choosing a good mate, working things out together, and then raising young to survive – hey, it’s just sparrow and squirrel couples, but anyone who has raised kids knows what I’m talking about – required larger brains than those of reptiles or fish that dealt with similar environmental challenges but made their way in life on their own.

By the way, it may be a source of satisfaction to some that polygamous species usually have the smallest brains.

Second, building on this initial jump in brain size, among primate species, the larger the social group, the bigger the brain. (And the key word here is social , since group size alone doesn’t create a big brain; if it did, cattle would be geniuses.)

In other words, the “computational requirements” of dealing with lots of individuals – the alliances, the adversaries, all the politics! – in a baboon or ape troupe pushed the evolution of the brain.

In sum: More than learning how to use tools, more than being successful at violence, more than adapting to moving out of the forest into the grasslands of Africa, it was learning how to love and live with each other that drove human evolution!

This is wonderful to see, finally - even if it is less than honest about the existing evidence for lifestyle interventions to affect depression levels. Drugs for depression are not treating the depression, they are creating an effect of feeling better through making people, for lack of a better word, stoned.

I have seen, firsthand, a client start walking 3-5 days a week (exercise and nature/environment), begin practicing contemplative prayer (meditation), spend more time with her dog (animal therapy - goes on the walk, then fetch in the park), and start spending less time at home by joining church activities and spending time with her kids and granddaughter (socializing). These synergy of these simple changes have been more effective than years of medications and various attempts at therapy.

Lifestyle medicine for depression

Jerome Sarris, Adrienne O'Neil, Carolyn E Coulson, Isaac Schweitzer, and Michael Berk
Author Affiliations | For all author emails, please log on.

Published: 10 April 2014

Abstract (provisional)

The prevalence of depression appears to have increased over the past three decades. While this may be an artefact of diagnostic practices, it is likely that there are factors about modernity that are contributing to this rise. There is now compelling evidence that a range of lifestyle factors are involved in the pathogenesis of depression. Many of these factors can potentially be modified, yet they receive little consideration in the contemporary treatment of depression, where medication and psychological intervention remain the first line treatments. "Lifestyle Medicine" provides a nexus between public health promotion and clinical treatments, involving the application of environmental, behavioural, and psychological principles to enhance physical and mental wellbeing. This may also provide opportunities for general health promotion and potential prevention of depression. In this paper we provide a narrative discussion of the major components of Lifestyle Medicine, consisting of the evidence-based adoption of physical activity or exercise, dietary modification, adequate relaxation/sleep and social interaction, use of mindfulness-based meditation techniques, and the reduction of recreational substances such as nicotine, drugs, and alcohol. We also discuss other potential lifestyle factors that have a more nascent evidence base, such as environmental issues (e.g. urbanisation, and exposure to air, water, noise, and chemical pollution), and the increasing human interface with technology. Clinical considerations are also outlined. While data supports that some of these individual elements are modifiers of overall mental health, and in many cases depression, rigorous research needs to address the long-term application of Lifestyle Medicine for depression prevention and management. Critically, studies exploring lifestyle modification involving multiple lifestyle elements are needed. While the judicious use of medication and psychological techniques are still advocated, due to the complexity of human illness/wellbeing, the emerging evidence encourages a more integrative approach for depression, and an acknowledgment that lifestyle modification should be a routine part of treatment and preventative efforts.

The complete article is available as a provisional PDF. The fully formatted PDF and HTML versions are in production.

Full Citation:
Sarris, J, O'Neil, A, Coulson, CE, Schweitzer, I, and Berk, M. (2014, Apr 10). Lifestyle medicine for depression. BMC Psychiatry, 14:107 doi:10.1186/1471-244X-14-107

Introduction

While modernity has provided multiple technological and medical advances including increased life-expectancy, it has come at a cost, in that a range of lifestyle issues are now negatively affecting our mental health [1]. As Hidaka [1] and Walsh [2] comment, in Western society people are increasingly becoming more sedentary and eating a poorer diet than previous generations. This, in combination with sleep/wake cycle pressures, substance misuse, and psychosocial factors such as more competition and time pressure, social isolation and less intimate engagement with the family unit, may exert a cost on mental health. Further, the combination of stress, fatigue, inactivity, and sleep deficiency in people who are “timepoor”, may advance obesity, and this in turn may promote a sedentary life with potential for resultant depression.

Due to the afore-mentioned challenges of modern urbanity, there is now the need to consider a “Lifestyle Medicine” approach for the potential prevention, promotion and management of depression. While medication and psychological interventions are first-line treatments for depression, Lifestyle Medicine offers a potentially safe and low-cost option for augmenting the management of the condition. While the evidence base remains patchy, many lifestyle or environmental factors are mutable and can provide the basis of practical interventions for the management of depression (summarised in Table 1). Lifestyle Medicine involves the application of environmental, behavioural, and psychological principles to enhance physical and mental wellbeing, adding a therapeutic and potentially preventative approach to illness [3]. This may involve modification of: diet; physical activity and exercise; relaxation and sleep-wake cycles; recreation and work-rest balance; and minimisation/avoidance of smoking, alcohol or illicit substances, in addition to the use of mindfulness-based meditation techniques [2]. Although the evidence base remains in its infancy, environmental issues are also considerations, such as reducing exposure to pollution (air, water, noise, and chemicals) and increasing time spent in nature, and are areas of current investigation. Activity scheduling such as encouraging engagement in meaningful activities and adequate social contact [1] is additionally of value. Further, Lifestyle Medicine may involve the application of clinical psychological techniques, insofar as motivational and behavioural factors are intrinsic to people trying to embrace lifestyle changes [3].

Table 1 Lifestyle Medicine for Depression

Lifestyle element................Evidence level....................Cost
Diet............................................CS, LO.................Moderate expense 
PA/Exercise..........................CS*, LO*, CTs ...............Inexpensive 
Recreation.................................OB, CTs..................Variable expense 
Relaxation/Meditation.................CTs..........................Inexpensive
Sleep......................................CS, LO, CTs...................No expense 
Environment..........................CS, LO, CTs...........Potentially not adjustable 
Socialization..............................CS, LO.........................No expense 
Animal/Pet therapy....................CS, CTs.....................Moderate expense 
Vices (smoking/alcohol)............CS, LO.................Potential to save money

CS = Cross-sectional, OB = Observational Study, LO = Longitudinal, CTs - Clinical Trials, NAT = Nature-Assisted Therapy, PA = Physical Activity. 
*Data assessing the relationship between exercise and depression has revealed mixed outcomes.

Comments on each Lifestyle Element:

Diet - Relationship found between dietary quality and depression; RCTs now required to validate
PA/Exercise - Strong evidence of efficacy for improving mood
Recreation - No studies exploring recreational activities for depression (aside from music therapy)
Relaxation & Meditation - Evidence supports relaxation techniques (especially with a mindfulness component) in improving mood
Sleep - Strong causal link between sleep amount and quality, and depression risk
Environment - Association between reduction of pollution and mood; CTs showing NAT improves mood
Socialization - Strong association between social support/networks and mental health
Animal/Pet therapy - Studies support the psychological benefits of animals and pets
Vices (smoking, alcohol) - Association between smoking and alcohol, and depressed mood

While lifestyle modification has been recognised by practitioners for centuries as a means by which to improve health outcomes, the field of “Lifestyle Medicine,” particularly in the context of mental health, is a relatively new field. While papers have discussed its broader application on health and in particular prevention of chronic disease and cardiovascular/metabolic conditions, little attention has been given to its application for mental health, and in particular depression, which is predicted to be the predominant cause of disability in the developed world [4], and is being argued as one of the prevalent noncommunicable disorders [5]. Some studies show that patients with sub-threshold depression rate lifestyle or psychosocial approaches as strategies that are most helpful in improving their mood [6], while patients with clinical depression have rated exercise as the most effective intervention [7].

There is a heuristic theoretical framework explaining why the modern lifestyle may be impacting mental health. Obesity [8], poor diet [9], poor/decreased sleep [10], exposure to chemicals and pollutants [11], and high stress levels [12], may potentially disrupt the hypothalamic pituitary adrenal axis, increase cortisol and increase low-grade systemic inflammation and oxidative stress. Both neuroendocrine disruption and inflammation have been linked to the aetiology of depression [13,14]. Specifically, increased levels of proinflammatory cytokines, interferon gamma and neopterin, reactive oxygen and nitrogen species and damage by oxidative and nitrosative stress, in combination with lowered levels of antioxidants, may potentially damage mitochondria and mitochondrial DNA; this may result in neurodegeneration and reduced neurogenesis [14].

This opinion paper aims to provide a context for Lifestyle Medicine by providing an overview of the lifestyle factors that are linked with depression risk before exploring the evidence and clinical application of modifying these elements. The paper firstly explores data for which there is sound evidentiary support (diet, physical activity and exercise, mindfulness meditation, management of recreational substance misuse, sleep, and social interaction), and then touches on lifestyle and environmental elements that have nascent data and are subject to confirmatory investigation (greenspace and pollutant exposure, hobbies and relaxation, and animal/pet therapy).

Read the whole article.

Omnivore - Psychologists Search

From Bookforum's Omnivore blog, this is a new collection of links related to psychology, research, and the state of the field.

In another piece of research not included below, Researchers Identify 15 more Facial Emotions:

The traditional six basic human emotions are happy, sad, fearful, angry, surprised and disgusted. For years, researchers have focused on these six categories, which are often depicted via specific facial muscles, when they assess people's moods. Now, according to a new study headed by associate professor Aleix Martinez from Ohio State University, the researchers have identified 15 more facial expressions, which they called "compound emotions." 

Interesting.

Psychologists search

Apr 8 2014 | 9:00AM

• The latest issue of the Annual Review of Critical Psychology is devoted to critical work around the world. 
• Augustine Brannigan (Calgary): Stanley Milgram’s Obedience Experiments: A Report Card 50 Years Later. 
• Eyal Zamir (HUJ): Loss Aversion: An Overview. 
• Rachael A. Carmen, Glenn Geher, Daniel J. Glass, Amanda E. Guitar, Terry L. Grandis, Laura Johnsen, Melvin M. Philip, Rebecca L. Newmark, Grant T. Trouton, and Briana R. Tauber (SUNY-New Paltz): Evolution Integrated Across All Islands of the Human Behavioral Archipelago: All Psychology as Evolutionary Psychology. 
• Research suggests it's easier than you think to get people to commit bad deeds. 
• Daniel Tutt reviews Enjoying What We Don’t Have: The Political Project of Psychoanalysis by Todd McGowan. 
• Psychologists’ effort to end aid to military interrogations falls short: APA failed to ban interrogation aiding, but gathered enough support to bolster efforts further. 
• From TNR, your self is located in your chest: Psychologists search for the subjective location of the self — some say it's in the torso, others say it's in the eyes; a little narcissism is good for you: Alice Robb interviews Elizabeth Lunbeck, author of The Americanization of Narcissism; and you probably think the most important historic event of your lifetime happened when you were in your twenties. 
• At what moment do you finally become yourself? New psychological research considers whether you are ever really comfortable with your own taste. 
• Chelsea Whyte on how a face map of mixed feelings could help AIs understand us. 
• Don’t worry be happy: Jeremy Safran on the dark underside of positive psychology.

Early Childhood Stress and Adult Mental Illness - New Research

The title above is closely related to a project I have been working on for the past several weeks, whenever I have a little bit of free time. Nearly ALL mental illness can be traced to environmental stress and relational traumas. Finally, researchers are beginning to look into these relationships.

Below are pieces of four recent studies on the impact of chronic stress in children that have made it into the press. These articles are mostly looking at the physical health outcomes, but we know beyond a doubt that a whole spectrum of adverse childhood events leads to physical health issues as well as mental health issues.

As always, follow the links to read the whole article.

Chronic stress in early life causes anxiety, aggression in adulthood, neurobiologists find

Date: March 27, 2014
Source: Cold Spring Harbor Laboratory

Summary:
In experiments to assess the impacts of social stress upon adolescent mice, both at the time they are experienced and during adulthood, a laboratory team conducted many different kinds of stress tests and means of measuring their impacts. The research indicates that a 'hostile environment in adolescence disturbs psychoemotional state and social behaviors of animals in adult life,' the team says.

Full Citation:
Irina L. Kovalenko, Anna G. Galyamina, Dmitry A. Smagin, Tatyana V. Michurina, Natalia N. Kudryavtseva, Grigori Enikolopov. Extended Effect of Chronic Social Defeat Stress in Childhood on Behaviors in Adulthood. PLoS ONE, 2014; 9 (3): e91762 DOI: 10.1371/journal.pone.0091762

The above article is open access.

* * * * *

Stress alters children's genomes

Poverty and unstable family environments shorten chromosome-protecting telomeres in nine-year-olds.

Jyoti Madhusoodanan
07 April 2014


Telomeres (shown in red) protect the ends of chromosomes from fraying over time. Pasieka/Science Photo Library

Growing up in a stressful social environment leaves lasting marks on young chromosomes, a study of African American boys has revealed. Telomeres, repetitive DNA sequences that protect the ends of chromosomes from fraying over time, are shorter in children from poor and unstable homes than in children from more nurturing families.

When researchers examined the DNA of 40 boys from major US cities at age 9, they found that the telomeres of children from harsh home environments were 19% shorter than those of children from advantaged backgrounds. The length of telomeres is often considered to be a biomarker of chronic stress.

The study, published today in the Proceedings of the National Academy of Sciences1, brings researchers closer to understanding how social conditions in childhood can influence long-term health, says Elissa Epel, a health psychologist at the University of California, San Francisco, who was not involved in the research.

Full Citation:
Mitchell, C. et al. (2014). Social disadvantage, genetic sensitivity, and children’s telomere length. Proc. Natl. Acad. Sci. USA. http://dx.doi.org/10.1073/pnas.1404293111

* * * * *

This number was 25% a couple of decades ago, and now it is 40%? What is happening with parenting that so many children lack secure parental bonds?

Four in 10 infants lack strong parental attachments

Date: March 27, 2014
Source: Princeton University, Woodrow Wilson School of Public and International Affairs

Summary:
In a study of 14,000 US children, 40 percent lack strong emotional bonds -- what psychologists call 'secure attachment' -- with their parents that are crucial to success later in life, according to a new report. The researchers found that these children are more likely to face educational and behavioral problems.

Full Citation:
The above story is based on materials provided by Princeton University, Woodrow Wilson School of Public and International Affairs. Note: Materials may be edited for content and length.

* * * * *

This article is basically a review of the current research, although not an in-depth one, but it offers another glimpse into the ways environment impacts children - from Live Science.

The Truth About How Mom's Stress Affects Baby's Brain

By Stephanie Pappas, Senior Writer | February 24, 2014


A dancing robot is used to test babies' temperaments at the University of Denver lab of Elysia Poggi Davis. Credit: Stephanie Pappas for LiveScience

DENVER — My daughter is sitting in a high chair, watching a black-and-white robot almost as big as she is bust a move.

A Vegas floor show this is not, but for a 7-month-old, a dancing robot is either fascinating or terrifying. How my daughter (or any baby) responds to such a display can reveal the child's temperament. And that, among other things, is what brought us here to this cheerful neurodevelopment lab decorated with cartoons of zebras and giraffes.

Here at the University of Denver, psychologists are working to understand how the early environment affects a child's life course — but the environment that researchers Elysia Poggi Davis and Pilyoung Kim are interested in isn't just the home or the neighborhood, but also the womb.

Stress hormones (and medications that mimic them) may have long-lasting effects on infants, Davis and Kim have found. And exposure in the womb is where it all begins.

If you are a fan of the late Johnny Cash, this is a cool little animated video. As always, this is courtesy of Open Culture, the curators of cool on the interwebs.

Animated Video: Johnny Cash Explains Why Music Became a Religious Calling

April 9th, 2014


Blank on Blank is back with another animated video. This one animates a long lost interview with the great Johnny Cash. Interviewed by Barney Hoskyns back in 1996, Cash talked about music as a religious calling. Playing music was akin to preaching the gospel, and he knew he’d continue making music until his final days. Should we be surprised then, that seven years later, Cash completed more than 60 songs during the last four months of his life? He died with his boots on indeed.

Below we’ve highlighted for you some great Johnny Cash material from our archive.

Related Content:

• The First Episode of The Johnny Cash Show, Featuring Bob Dylan & Joni Mitchell (1969)
• The 1969 Bob Dylan-Johnny Cash Sessions: Twelve Rare Recordings
• Johnny Cash Sings “Man in Black” for the First Time, 1971
• Two Prison Concerts That Defined an Outlaw Singer: Johnny Cash at San Quentin and Folsom (1968-69)

Physicist Per Bak's Sand Pile Model of Mind Is Growing in Popularity

Back in the 1980s, a physicist, Per Bak, proposed that the human mind may operate on some of the same principle as a sand pile - avalanches of various sizes help keep the entire system stable overall, a process Bak named “self-organized criticality.”


More precisely, "the brain’s ordered complexity and thinking ability arise spontaneously from the disordered electrical activity of neurons."

Interesting idea - and this article does well in explaining where the idea came from and how it has become more widely accepted.

Sand Pile Model of Mind Grows in Popularity

Support is growing for a decades-old physics idea suggesting that localized episodes of disordered brain activity help keep the overall system in healthy balance

Apr 7, 2014 | By Jennifer Ouellette and Quanta Magazine


Mounting evidence suggests that localized episodes of disordered brain activity, like avalanches in a sand pile, help keep the overall system in healthy balance.  Credit: James O'Brien for Quanta Magazine
From Quanta Magazine (find original story here).

In 1999, the Danish physicist Per Bak proclaimed to a group of neuroscientists that it had taken him only 10 minutes to determine where the field had gone wrong. Perhaps the brain was less complicated than they thought, he said. Perhaps, he said, the brain worked on the same fundamental principles as a simple sand pile, in which avalanches of various sizes help keep the entire system stable overall — a process he dubbed “self-organized criticality.”

As much as scientists in other fields adore outspoken, know-it-all physicists, Bak’s audacious idea — that the brain’s ordered complexity and thinking ability arise spontaneously from the disordered electrical activity of neurons — did not meet with immediate acceptance.

But over time, in fits and starts, Bak’s radical argument has grown into a legitimate scientific discipline. Now, about 150 scientists worldwide investigate so-called “critical” phenomena in the brain, the topic of at least three focused workshops in 2013 alone. Add the ongoing efforts to found a journal devoted to such studies, and you have all the hallmarks of a field moving from the fringes of disciplinary boundaries to the mainstream.

In the 1980s, Bak first wondered how the exquisite order seen in nature arises out of the disordered mix of particles that constitute the building blocks of matter. He found an answer in phase transition, the process by which a material transforms from one phase of matter to another. The change can be sudden, like water evaporating into steam, or gradual, like a material becoming superconductive. The precise moment of transition — when the system is halfway between one phase and the other — is called the critical point, or, more colloquially, the “tipping point.”

Classical phase transitions require what is known as precise tuning: in the case of water evaporating into vapor, the critical point can only be reached if the temperature and pressure are just right. But Bak proposed a means by which simple, local interactions between the elements of a system could spontaneously reach that critical point — hence the term self-organized criticality.

Think of sand running from the top of an hourglass to the bottom. Grain by grain, the sand accumulates. Eventually, the growing pile reaches a point where it is so unstable that the next grain to fall may cause it to collapse in an avalanche. When a collapse occurs, the base widens, and the sand starts to pile up again — until the mound once again hits the critical point and founders. It is through this series of avalanches of various sizes that the sand pile — a complex system of millions of tiny elements — maintains overall stability.

While these small instabilities paradoxically keep the sand pile stable, once the pile reaches the critical point, there is no way to tell whether the next grain to drop will cause an avalanche — or just how big any given avalanche will be. All one can say for sure is that smaller avalanches will occur more frequently than larger ones, following what is known as a power law.

Bak introduced self-organized criticality in a landmark 1987 paper — one of the most highly cited physics papers of the last 30 years. Bak began to see the stabilizing role of frequent smaller collapses wherever he looked. His 1996 book, “How Nature Works,” extended the concept beyond simple sand piles to other complex systems: earthquakes, financial markets, traffic jams, biological evolution, the distribution of galaxies in the universe — and the brain. Bak’s hypothesis implies that most of the time, the brain teeters on the edge of a phase transition, hovering between order and disorder.

The brain is an incredibly complex machine. Each of its tens of billions of neurons is connected to thousands of others, and their interactions give rise to the emergent process we call “thinking.” According to Bak, the electrical activity of brain cells shift back and forth between calm periods and avalanches — just like the grains of sand in his sand pile — so that the brain is always balanced precariously right at that the critical point.

A better understanding of these critical dynamics could shed light on what happens when the brain malfunctions. Self-organized criticality also holds promise as a unifying theoretical framework. According to the neurophysiologist Dante Chialvo, most of the current models in neuroscience apply only to single experiments; to replicate the results from other experiments, scientists must change the parameters — tune the system — or use a different model entirely.

Self-organized criticality has a certain intuitive appeal. But a good scientific theory must be more than elegant and beautiful. Bak’s notion has had its share of critics, in part because his approach strikes many as ridiculously broad: He saw nothing strange about leaping across disciplinary boundaries and using self-organized criticality to link the dynamics of forest fires, measles and the large-scale structure of the universe — often in a single talk. Nor was he one to mince words. His abrasive personality did not endear him to his critics, although Lee Smolin, a physicist at the Perimeter Institute for Theoretical Physics, in Canada, has chalked this up to “childlike simplicity,” rather than arrogance. “It would not have occurred to him that there was any other way to be,” Smolin wrote in a remembrance after Bak’s death in 2002. “Science is hard, and we have to say what we think.”

Nonetheless, Bak’s ideas found fertile ground in a handful of like-minded scientists. Chialvo, now with the University of California, Los Angeles, and with the National Scientific and Technical Research Council in Argentina, met Bak at Brookhaven National Laboratory around 1990 and became convinced that self-organized criticality could explain brain activity. He, too, encountered considerable resistance. “I had to put up with a number of critics because we didn’t have enough data,” Chialvo said. Dietmar Plenz, a neuroscientist with the National Institute of Mental Health, recalled that it was impossible to win a grant in neuroscience to work on self-organized criticality at the time, given the lack of experimental evidence.

Since 2003, however, the body of evidence showing that the brain exhibits key properties of criticality has grown, from examinations of slices of cortical tissue and electroencephalography (EEG) recordings of the interactions between individual neurons to large-scale studies comparing the predictions of computer models with data from functional magnetic resonance (fMRI) imaging. “Now the field is mature enough to stand up to any fair criticism,” Chialvo said.

One of the first empirical tests of Bak’s sand pile model took place in 1992, in the physics department of the University of Oslo. The physicists confined piles of rice between glass plates and added grains one at a time, capturing the resulting avalanche dynamics on camera. They found that the piles of elongated grains of rice behaved much like Bak’s simplified model.

Most notably, the smaller avalanches were more frequent than the larger ones, following the expected power law distribution. That is, if there were 100 small avalanches involving only 10 grains during a given time frame, there would be 10 avalanches involving 100 grains in the same period, but only a single large avalanche involving 1,000 grains. (The same pattern had been observed in earthquakes and their aftershocks. If there are 100 quakes measuring 6.0 on the Gutenberg-Richter scale in a given year, there will be 10 7.0 quakes and one 8.0 quake.)

Ten years later, Plenz and a colleague, John Beggs, now a biophysicist at Indiana University, observed the same pattern of avalanches in the electrical activity of neurons in cortical slices — the first key piece of evidence that the brain functions at criticality. “It was something that no one believed the brain would do,” Plenz said. “The surprise is that is exactly what happens.” Studies using magnetoencephalography (MEG) and Chialvo’s own work comparing computer simulations with fMRI imaging data of the brain’s resting state have since added to the evidence that the brain exhibits these key avalanche dynamics.

But perhaps it is not so surprising. There can be no phase transitions without a critical point, and without transitions, a complex system — like Bak’s sand pile, or the brain — cannot adapt. That is why avalanches only show up at criticality, a “sweet spot” where a system is perfectly balanced between order and disorder, according to Plenz. They typically occur when the brain is in its normal resting state. Avalanches are a mechanism by which a complex system avoids becoming trapped, or “phase-locked,” in one of two extreme cases. At one extreme, there is too much order, such as during an epileptic seizure; the interactions among elements are too strong and rigid, so the system cannot adapt to changing conditions. At the other, there is too much disorder; the neurons aren’t communicating as much, or aren’t as broadly interconnected throughout the brain, so information can’t spread as efficiently and, once again, the system is unable to adapt.

A complex system that hovers between “boring randomness and boring regularity” is surprisingly stable overall, said Olaf Sporns, a cognitive neuroscientist at Indiana University. “Boring is bad,” he said, at least for a critical system. In fact, “if you try to avoid ever sparking an avalanche, eventually when one does occur, it is likely to be really large,” said Raissa D’Souza, a complex systems scientist at the University of California, Davis, who simulated just such a generic system last year. “If you spark avalanches all the time, you’ve used up all the fuel, so to speak, and so there is no opportunity for large avalanches.”

D’Souza’s research applies these dynamics to better understand power outages across the electrical grid. The brain, too, needs sufficient order to function properly, but also enough flexibility to adapt to changing conditions; otherwise, the organism could not survive. This could be one reason that the brain exhibits hallmarks of self-organized criticality: It confers an evolutionary advantage. “A brain that is not critical is a brain that does exactly the same thing every minute, or, in the other extreme, is so chaotic that it does a completely random thing, no matter what the circumstances,” Chialvo said. “That is the brain of an idiot.”

When the brain veers away from criticality, information can no longer percolate through the system as efficiently. One study (not yet published) examined sleep deprivation; subjects remained awake for 36 hours and then took a reaction time test while an EEG monitored their brain activity. The more sleep-deprived the subject, the more the person’s brain activity veered away from the critical balance point and the worse the performance on the test.

Another study collected data from epileptic subjects during seizures. The EEG recordings revealed that mid-seizure, the telltale avalanches of criticality vanished. There was too much synchronization among neurons, and then, Plenz said, “information processing breaks down, people lose consciousness, and they don’t remember what happened until they recover.”

Chialvo envisions self-organized criticality providing a broader, more fundamental theory for neuroscientists, like those found in physics. He believes it could be used to model the mind in all its possible states: awake, asleep, under anesthesia, suffering a seizure, and under the influence of a psychedelic drug, among many others.

This is especially relevant as neuroscience moves deeper into the realm of big data. The latest advanced imaging techniques are capable of mapping synapses and monitoring brain activity at unprecedented resolutions, with a corresponding explosion in the size of data sets. Billions of dollars in research funding has launched the Human Connectome Project — which aims to build a “network map” of neural pathways in the brain — and the Brain Research Through Advancing Innovative Neurotechnologies (BRAIN), dedicated to developing new technological tools for recording signals from cells. There is also Europe’s Human Brain Project, working to simulate the complete human brain on a supercomputer, and China’s Brainnetome project to integrate data collected from every level of the brain’s hierarchy of complex networks.

But without an underlying theory, it will be difficult to glean all the potential insights hidden in the data. “It is fine to build maps and it is fine to catalog pieces and how they are related, so long as you don’t lose track of the fact that when the system you map actually functions, it is in an integrated system and it is dynamic,” Sporns said.

“The structure of the brain — the precise map of who connects with whom — is almost irrelevant by itself,” Chialvo said — or rather, it is necessary but not sufficient to decipher how cognition and behavior are generated in the brain. “What is relevant is the dynamics,” Chialvo said. He then compared the brain with a street map of Los Angeles containing details of all the connections at every scale, from private driveways to public freeways. The map tells us only about the structural connections; it does not help predict how traffic moves along those connections or where (and when) a traffic jam is likely to form. The map is static; traffic is dynamic. So, too, is the activity of the brain. In recent work, Chialvo said, researchers have demonstrated that both traffic dynamics and brain dynamics exhibit criticality.

Sporns emphasizes that it remains to be seen just how robust this phenomenon might be in the brain, pointing out that more evidence is needed beyond the observation of power laws in brain dynamics. In particular, the theory still lacks a clear description for how criticality arises from neurobiological mechanisms — the signaling of neurons in local and distributed circuits. But he admits that he is rooting for the theory to succeed. “It makes so much sense,” he said. “If you were to design a brain, you would probably want criticality in the mix. But ultimately, it is an empirical question.”

~ Reprinted with permission from Quanta Magazine, an editorially independent division of SimonsFoundation.org whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

 

Sonja Lyubomirsky, Ph.D., is professor of psychology at the University of California, Riverside. She received her B.A., summa cum laude, from Harvard University and her Ph.D. in social psychology from Stanford University. Her research - on the possibility of permanently increasing happiness -- has been honored with a Science of Generosity grant, a John Templeton Foundation grant, a Templeton Positive Psychology Prize, and a million-dollar grant from NIMH.

Lyubomirsky's 2008 book, The How of Happiness: A New Approach to Getting the Life You Want (Penguin Press) has been translated into 19 languages, and her most recent book, The Myths of Happiness: What Should Make You Happy, but Doesn't, What Shouldn't Make You Happy, but Does, was released in January, 2013.

She gave this talk at UC San Diego a few days ago.

The Science and Practice of Happiness Across the Lifespan - Research on Aging

Published on Apr 4, 2014


What makes people happy? Is happiness a good thing? How can we make people happier still? Sonja Lyubomirsky, PhD, examines happiness and how we can use our minds as well as coping tools better handle life's challenges. Series: "Stein Institute for Research on Aging" [4/2014]

William G Dever is the author of Did God Have a Wife?: Archaeology and Folk Religion in Ancient Israel (2005), as well as, more recently, The Lives of Ordinary People in Ancient Israel: When Archaeology and the Bible Intersect (2012).

In the Old Testament, the goddesses Asherah is quite possibly linked to the "Queen of Heaven" in the Book of the Prophet Jeremiah (circa 628 BC). Dever is not alone in making that connection. In 1967, Raphael Patai was the first historian to mention that the ancient Israelites worshiped both Yahweh and Asherah. The theory has gained new prominence due to the research of Francesca Stavrakopoulou (a senior lecturer in the department of Theology and Religion at the University of Exeter) - see more at Discovery News.

Dever spoke recently at Emory University, where he is Distinguished Visiting Professor, Lycoming College, and Professor Emeritus of Near Eastern Studies, Arizona State University. He spoke on the topic of his, Did God Have a Wife? Here is a synopsis of the book from Amazon.

Following up on his two recent, widely acclaimed studies of ancient Israelite history and society, William Dever here reconstructs the practice of religion in ancient Israel from the bottom up. Archaeological excavations reveal numerous local and family shrines where sacrifices and other rituals were carried out. Intrigued by this folk religion in all its variety and vitality, Dever writes about ordinary people in ancient Israel and their everyday religious lives. Did God Have a Wife? shines new light on the presence and influence of women's cults in early Israel and their implications for our understanding of Israels official Book religion. Dever pays particular attention to the goddess Asherah, reviled by the authors of the Hebrew Bible as a foreign deity but, in the view of many modern scholars, popularly envisioned in early Israel as the consort of biblical Yahweh. His work also gives new prominence to women as the custodians of Israels folk religion. The first book by an archaeologist on ancient Israelite religion, this fascinating study critically reviews virtually all of the archaeological literature of the past generation, while also bringing fresh evidence to the table. Though Dever digs deep into the past, his discussion is extensively illustrated, unencumbered by footnotes, and vivid with colorful insights. Meant for professional and general audiences alike, Did God Have a Wife? is sure to spur wide and passionate debate.

Did God Have a Wife?: Archaeology and Folk Religion in Ancient Israel

Published on Apr 1, 2014


William G. Dever, Distinguished Visiting Professor, Lycoming College, and Professor Emeritus of Near Eastern Studies, Arizona State University, presents the 2014 Tenenbaum Lecture (February 3, 2014). His illustrated lecture showcases recent archaeological evidence that reveals the differences in beliefs and practices of ordinary people in ancient Israel compared to the elitist, idealist portrait in the Bible, particularly the ongoing veneration of the Canaanite Goddess Asherah.

~ The Tenenbaum Family Lectureship in Judaic Studies salutes the family of the late Meyer W. Tenenbaum '31C-'32L of Savannah, Georgia. Past lectures can found here.

I'm not as hopeful as Lessig about the progress of political reform (I suspect hell will freeze over before there is any REAL political reform). But Lessig knows things I don't know - lots of them - and he makes some interesting arguments. I hope he is correct.

Lawrence Lessig: The unstoppable walk to political reform

March 2014

Seven years ago, Internet activist Aaron Swartz convinced Lawrence Lessig to take up the fight for political reform. A year after Swartz's tragic death, Lessig continues his campaign to free US politics from the stranglehold of corruption. In this fiery, deeply personal talk, he calls for all citizens to engage, and offers a heartfelt reminder to never give up hope.


This talk was presented at an official TED Conference. TED's editors featured it among our daily selections on the home page.



Lawrence Lessig - Legal activist Lawrence Lessig has already transformed intellectual-property law with his Creative Commons innovation. Now he's focused on an even bigger problem: The US' broken political system.

This comes from the U of Arizona via the UA News blog. Shaun Nichols, a professor in the U of A’s Department of Philosophy, conducted a meta-study (looked at five other studies to find patterns) of how morality and sense of self are connected and found that personal morality is the most important part of defining individual identity.

Interesting.

They also found, in another study, that people's beliefs about whether or not the self changes over time affects their actions.

Also interesting.

Searching for the Self: Morality Makes You Who You Are

Personal moral traits are considered the most important part of individual identity, according to a new study co-authored by a UA philosophy professor.

By Shelley Littin, University Communications | April 4, 2014



What makes you who you are? Your experiences? Your memories? Your favorite foods?

None of these truly define us. What people believe really make us individuals are our personal moral traits, according to a new study co-authored by Shaun Nichols, a professor in the University of Arizona’s Department of Philosophy.

The research moves beyond the tradition in philosophy, which has focused on memory as the most important factor in defining the individual self, and introduces a broader perspective on the question of what makes you who you are.

“The philosophical tradition has emphasized the importance of memory - that you need to have the same memories to be the same person,” said Nichols, who co-authored the study with Nina Strohminger, a psychologist at Duke University.

“Previous studies had focused on the presence versus absence of memory,” Nichols said. “This paper looks at a variety of different dimensions, including morality, personality and intelligence, and every result came out with morality as the most important factor in defining the self. We found that memory was second place to morality by far.”

Morality, in this case, refers to personal moral traits such as the tendency to be kind or the tendency to be selfish, Nichols said.

“When you imagine yourself losing all of your memories that seems terrible,” he said. “But we found that for most people, the idea that somebody who used to be nice is now cruel would be considered a much more profound influence on their behavior than just forgetting various things.”

The paper, published in March in the journal Cognition, documents the results of five independent studies involving over 800 U.S. participants, all showing overwhelmingly that personal morality is considered the most important trait in defining the self.

The researchers compared moral personality traits, such as the tendency to be kind, with non-moral personality traits, such as the tendency to be shy.

“We found that the moral personality traits really were much more important to the way that people thought about the true self,” Nichols said.

“If you’re shy or artistic or a slow learner and those traits change, people don’t think that’s as much of a change in who you are,” Nichols said. “But if you go from being callous to being kind, people think that’s a big change.”

Nichols and Strohminger did not investigate whether an individual’s personal morality is likely to change over the course of their lifetime, but they did find that people’s belief about whether they will change affects their actions.

In an earlier study, also published in the journal Cognition, Nichols, along with Daniel Bartels of the University of Chicago and then UA graduate student Trevor Kvaran, investigated how perceptions of whether the self changes over time influences people’s actions. They found that people were more likely to give money to charity in the long term if they believed the self would change over time.

This is predicted by Buddhism, Nichols said. If people come to appreciate that they won’t be the same person over time, then they may be less concerned about how their life turns out in the end.

Now Nichols is gearing up for a new investigation into whether individual beliefs about whether or not the self will change over time affect attitudes about death in Christian, Hindu and Buddhist populations. That investigation is being supported by a $249,000 grant from the John Templeton Foundation. Nichols is leading one of 10 research teams selected for the Immortality Project, based at the University of California, Riverside.

Contacts

UANews Contact:
Shelley Littin
319-541-1482
littin@email.arizona.edu

Researcher Contact:
Shaun Nichols
520-626-0616
sbn@email.arizona.edu

Does social fear (of being judged or evaluated) look different in the brain than physical fear (of being hurt or attacked)? The study of the similarities and differences is based on the psychological construction approach that views as emotions as situated, i.e., defined by the situation.

Based on this model, the researchers speculated that socially situated fear situations would have a high correlation with the physical fear scenarios in how the brain responds, as well as there being some differences. According to the authors:

We hypothesized that distributed neural patterns would underlie immersion in social evaluation and physical danger situations, with shared activity patterns across both situations in multiple sensory modalities and in circuitry involved in integrating salient sensory information, and with unique activity patterns for each situation type in coordinated large-scale networks that reflect situated responding. More specifically, we predicted that networks underlying the social inference and mentalizing involved in responding to a social threat (in regions that make up the “default mode” network) would be reliably more active during social evaluation situations. In contrast, networks underlying the visuospatial attention and action planning involved in responding to a physical threat would be reliably more active during physical danger situations. The results supported these hypotheses.

Interesting stuff.

Full Citation: 
Wilson-Mendenhall, CD, Barrett, LF, and Barsalou, LW. (2013, Nov 26). Situating emotional experience. Frontiers in Human Neuroscience; 7:764. doi: 10.3389/fnhum.2013.00764

Situating emotional experience

Christine D. Wilson-Mendenhall [1], Lisa Feldman Barrett [1] and Lawrence W. Barsalou [2]

1. Department of Psychology, Northeastern University, Boston, MA, USA
2. Department of Psychology, Emory University, Atlanta, GA, USA

Psychological construction approaches to emotion suggest that emotional experience is situated and dynamic. Fear, for example, is typically studied in a physical danger context (e.g., threatening snake), but in the real world, it often occurs in social contexts, especially those involving social evaluation (e.g., public speaking). Understanding situated emotional experience is critical because adaptive responding is guided by situational context (e.g., inferring the intention of another in a social evaluation situation vs. monitoring the environment in a physical danger situation). In an fMRI study, we assessed situated emotional experience using a newly developed paradigm in which participants vividly imagine different scenarios from a first-person perspective, in this case scenarios involving either social evaluation or physical danger. We hypothesized that distributed neural patterns would underlie immersion in social evaluation and physical danger situations, with shared activity patterns across both situations in multiple sensory modalities and in circuitry involved in integrating salient sensory information, and with unique activity patterns for each situation type in coordinated large-scale networks that reflect situated responding. More specifically, we predicted that networks underlying the social inference and mentalizing involved in responding to a social threat (in regions that make up the “default mode” network) would be reliably more active during social evaluation situations. In contrast, networks underlying the visuospatial attention and action planning involved in responding to a physical threat would be reliably more active during physical danger situations. The results supported these hypotheses. In line with emerging psychological construction approaches, the findings suggest that coordinated brain networks offer a systematic way to interpret the distributed patterns that underlie the diverse situational contexts characterizing emotional life.

Introduction

Darwin’s The Expression of the Emotions in Man and Animals is often used to motivate emotion research that focuses on identifying the biological signatures for five or so emotion categories (Ekman, 2009; Hess and Thibault, 2009). Interestingly, though, the evolution paradigm shift initiated by Darwin and other scientists heavily emphasized variability: species are biopopulations in which individuals within a population are unique and in which individual variation within a species is meaningfully tied to variation in the environment (and they are not physical types defined by essential features; Barrett, 2013). In other words, an individual organism is best understood by the situational context in which it operates. It is not a great leap, then, to hypothesize that “situatedness” is also a basic principle by which the human mind operates, during emotions and during many other mental phenomena (Barrett, 2013).

Situated approaches to the mind typically view the brain as a coordinated system designed to use information captured during prior situations (and stored in memory) to flexibly interpret and infer what is happening in the current situation – dynamically shaping moment-to-moment responding in the form of perceiving, coordinating action, regulating the body, and organizing thoughts (Glenberg, 1997; Barsalou, 2003, 2009; Aydede and Robbins, 2009; Mesquita et al., 2010; Barrett, 2013). “Cognitive” research domains (e.g., episodic and semantic memory, visual object recognition, language comprehension) are increasingly adopting a situated view of the mind (for empirical reviews, see Zwaan and Radvansky, 1998; Barsalou, 2003; Bar, 2004; Yeh and Barsalou, 2006; Mesquita et al., 2010). In contrast, emotion research largely remains entrenched in a “stimulus-response” reflexive approach to brain function, which typically views the brain as reacting to the demands of the environment, often in a simple, stereotyped way (cf. Raichle, 2010). Traditional “basic” emotion views often assume that an event (i.e., a stimulus) triggers one of several stereotyped responses in the brain and body that can be classified as either fear, disgust, anger, sadness, happiness, etc. (for a review of basic emotion models, see Tracy and Randles, 2011). Decades of research have revealed substantial variability in the neural, physiological, and behavioral patterns associated with these emotion categories (cf. Barrett, 2006; Lindquist et al., 2012). Whereas basic emotion approaches now focus on trying to identify primitive “core” (and often narrowly defined) instances of these emotions, alternative theoretical approaches to emotion, such as psychological construction, propose taking a situated approach to explaining the variability that exists in the experiences people refer to using words like fear, disgust, anger, sadness, happiness (and using many other emotion terms; Barrett, 2009b, 2013).

In the psychological construction view that we have developed, emotions are not fundamentally different from other kinds of brain states (Barrett, 2009a, 2012; Wilson-Mendenhall et al., 2011). During emotional experiences and during other kinds of experiences, the brain is using prior experience to dynamically interpret ongoing neural activity, which guides an individual’s responding in the situation. We refer to this process, which often occurs without awareness (i.e., it is a fundamental process for making sense of one’s relation to the world at any given moment), as situated conceptualization. The term situated takes on a broad meaning in our view, referring to the distributed neural activity across the modal systems of the brain involved in constructing situations, not just to perception of the external environment or to what might be considered the background. More specifically, situated neural activity reflects the dynamic actions that individuals engage in, and the events, internal bodily sensations, and mentalizing that they experience, as well as the perceptions of the external environmental setting and the physical entities and individuals it contains (Wilson-Mendenhall et al., 2011).

Emotions, like other classes of mental experiences, operate in this situation-specific way because rich, cross-modal knowledge is critical for interpreting, inferring, and responding when similar situations occur in the future. On this view, situational knowledge develops for emotion categories like fear, anger, etc., as it does for other abstract categories of experiences (e.g., situations that involve the abstract categories gossip, modesty, or ambition). Experiences categorized as fear, for example, can occur when delivering a speech to a respected audience or when losing control while driving a car. A situated, psychological construction perspective suggests that it is more adaptive to respond differently in these situations, guided by knowledge of the situation, than to respond in a stereotyped way. Whereas responding in the social speech situation involves inferring what audience members are thinking, responding in the physical car situation involves rapid action and attention to the environment. Stereotyped responding in the form of preparing the body to flee or fight does not address the immediate threat present in either of these situations. A psychological construction approach highlights the importance of studying the situations commonly categorized as emotions like fear or anger, not because these situations merely describe emotions, but because emotions would not exist without them.

A significant challenge in taking a situated approach to studying emotional experience is maintaining a balance between the rich, multimodal nature of situated experiences and experimental control. Immersion in emotional situations through vividly imagined imagery is recognized as a powerful emotion induction method for evoking physiological responses (Lang et al., 1980; Lench et al., 2011). Imagery paradigms were initially developed to study situations thought to be central to various forms of psychopathology (Lang, 1979; Pitman et al., 1987), and remain a focus in clinical psychology (for a review, see Holmes and Mathews, 2010). In contrast, a small proportion of neuroimaging studies investigating emotion in typical populations use these methods. Figure 1 illustrates the methods used across 397 studies in a database constructed for neuroimaging meta-analyses of affect and emotion (Kober et al., 2008; Lindquist et al., 2012)1. Visual methods dominate (70% of studies), with the majority of these studies using faces (42% of visual methods) and pictures (36% of visual methods) like the International Affective Picture System (IAPS; Lang et al., 2008). In contrast, only 6% of studies have used imagery methods2. Imagery methods appear to be used more frequently when studying complex socio-emotional experiences that would be difficult to induce with an unfamiliar face or picture and that are often clinically oriented, including angry rumination (Denson et al., 2009), personal anxiety (Bystritsky et al., 2001), competition and aggression (Rauch et al., 1999; Pietrini et al., 2000), social rejection and insult (Kim et al., 2008; Kross et al., 2011), romantic love (Aron et al., 2005), moral disgust (Moll et al., 2005; Schaich Borg et al., 2008), and empathy (Perry et al., 2012).

FIGURE 1


FIGURE 1. Methods used to study emotion and affect. Visual methods typically involved viewing faces, pictures, films, words, sentences, and/or bodies. Auditory methods typically involved listening to voices, sounds, music, words, and/or sentences. Imagery methods typically involved generating imagery using personal memories, sentences, faces, and/or pictures (and are described further in the main text). Recall methods typically involved recalling personal events, words, films, or pictures. Tactile methods involved touch or thermal stimulation, olfaction methods involved smelling odors, and taste methods involved tasting food. Multiple modalities refers to studies that involved two or more of the aforementioned methods in the same study, with visual and auditory methods being the most frequent combination.

Imagery-based neuroimaging studies of emotional experience typically take one of two approaches. The most frequent approach is to draw on the personal experiences of the participant, cueing specific, vivid memories in the scanner. Often participants’ personal narratives are scripted and vividly imagined (guided by the experimenter) outside the scanner, and then a version of this script is used to induce these memory-based emotional experiences during neuroimaging (e.g., Bystritsky et al., 2001; Marci et al., 2007; Gillihan et al., 2010). Less often, a specific visual stimulus is potent enough to easily evoke personal, emotional imagery in the scanner (e.g., face of a romantic partner; Aron et al., 2005; Kross et al., 2011). The second approach is to present standard prompts (e.g., a sentence) that participants use to generate imagery underlying emotional experiences (e.g., Colibazzi et al., 2010; Costa et al., 2010). A key strength of the first approach is that emotional experiences are tightly tied to situated, real-life memories, whereas a key strength of the second approach is the experimental control afforded by presenting the same prompts to all participants. In both cases, though, the situational context of the emotional experiences is typically lost, either because the situational details are specific to the individual (and thus lost in group-level analyses) or because standard prompts are not designed to cultivate and/or systematically manipulate the situational context of the emotional experience.

Building on the strengths of existing imagery-based approaches, we developed a neuroimaging procedure that would allow us to examine participants’ immersion in rich, situated emotional experiences while maximizing experimental control and rigor. In our paradigm, participants first received training outside the scanner on how to immerse themselves in richly detailed, full paragraph-long versions of emotional scenarios from a first-person perspective. The scenarios reflected two ecologically important situation types in which emotional experiences are often grounded: social evaluation and physical danger. Every scenario was constructed using written templates to induce a social evaluation emotional experience or a physical danger emotional experience (see Table 1 for examples). Participants listened to audio recordings of the scenarios, which facilitated immersion by allowing participants to close their eyes. In the scanner, participants were prompted with shorter, core (audio) versions of the scenarios in the scanner, so that a statistically powerful neuroimaging design could be implemented.

TABLE 1


TABLE 1. Examples of physical danger and social evaluation scenarios used in the experiment.

We hypothesized that immersion across both social evaluation and physical danger situations would be characterized by distributed neural patterns across multiple sensory modalities and across regions involved in detecting and integrating salient sensory information. Much previous research has demonstrated neural overlap between sensorimotor perception/action and sensorimotor imagery (for a review, see Kosslyn et al., 2001). If our scenario immersion method induces richly situated emotional experiences, then the vivid mental imagery generated should be grounded in brain regions underlying sensory perception and action. Perhaps surprisingly, studies using imagery paradigms to investigate emotional experiences do not typically examine sensorimotor activity, because the goal is often to isolate a category of experience (e.g., anger, disgust) or other “emotion” components. In contrast, our approach is designed to examine the distributed neural patterns that underlie emotional experiences.

Our second, primary hypothesis was motivated by a situated approach to studying the varieties of emotional experience. We hypothesized that unique activity patterns for each situation type would occur in coordinated large-scale networks that reflect situated responding. Whereas networks underlying the social inference and mentalizing involved in responding to a social threat (in regions that make up the “default mode” network) would be reliably more active during social evaluation situations (for reviews of default mode network functions, see Buckner et al., 2008; Barrett and Satpute, 2013)3, networks underlying the visuospatial attention and action planning involved in responding to a physical threat would be reliably more active during physical danger situations (for reviews of attention networks, see Chun et al., 2011; Petersen and Posner, 2012; Posner, 2012). These large-scale, distributed networks largely consist of heteromodal regions that engage in the multimodal integration necessary for coordinated interpretation and responding (Sepulcre et al., 2012; Spreng et al., 2013).

As a further test of our second hypothesis, we examined whether participants’ trial-by-trial ratings of immersion during the training session correlated with neural activity, across social evaluation scenarios and across physical danger scenarios. If emotional experience is situated, then feeling immersed in a situation should be realized by neural circuitry that underlies engaging in the specific situation. Whereas immersion in social evaluation situations should occur when affect is grounded in mentalizing about others, immersion in physical danger situations should occur when affect is grounded in taking action in the environment.

Materials and Methods

Participants

Twenty right-handed, native-English speakers from the Emory community, ranging in age from 20 to 33 (10 female), participated in the experiment. Six additional participants were dropped due to problems with audio equipment (three participants) or excessive head motion in the scanner. Participants had no history of psychiatric illness and were not currently taking any psychotropic medication. They received $100 in compensation, along with anatomical images of their brain.

Materials

A full and core form of each scenario was constructed, the latter being a subset of the former (see Table 1). The full form served to provide a rich, detailed, and affectively compelling scenario. The core form served to minimize presentation time in the scanner, so that the number of necessary trials could be completed in the time available. Each full and core scenario described an emotional situation from a first-person perspective, such that the participant could immerse him- or herself in it. As described shortly, participants practiced enriching the core form of the scenario during the training sessions using details from the full form, so that they would be prepared to immerse in the rich situational detail of the full forms during the scanning session when they received the core forms.

Both situation types were designed so the threat described could be experienced as any number of high arousal, negative emotions like fear or anger (and participants’ ratings of the ease of experiencing negative emotions in the two situation types validated this approach; see Wilson-Mendenhall et al., 2011 for details). In social evaluation situations, another person put the immersed participant in a socially threatening situation that involved damage to his or her social reputation/ego. In physical danger situations, the immersed participant put him- or herself in a physically threatening situation that involved impending or actual bodily harm.

Templates were used to systematically construct different scenarios in each situation type (social evaluation and physical danger). Table 1 provides examples of the social evaluation and physical danger scenarios. Each template for the full scenarios specified a sequence of six sentences: three primary sentences (Pi) also used in the related core scenario, and three secondary sentences (Si) not used in the core scenario that provided additional relevant detail. The two sentences in each core scenario were created using P1 as the first sentence and a conjunction of P2A and P2C as the second sentence.

For the social evaluation scenarios, the template specified the following six sentences in order: P1 described a setting and activity performed by the immersed participant in the setting, along with relevant personal attributes; S1 provided auditory detail about the setting; P2A described an action (A) of the immersed participant; P2C described the consequence (C) of that action; S2 described another person’s action in response to the consequence; S3 described the participant’s resulting internal bodily experience. The templates for the physical danger scenarios were similar, except that S1 provided visual detail about the setting (instead of auditory), S2 described the participant’s action in response to the consequence (instead of another person’s action), and S3 described the participant’s resulting external somatosensory experience (on the body surface).

A broad range of real-world situations served as the content of the experimental situations. The physical danger scenarios were drawn from situations that involved vehicles, pedestrians, water, eating, wildlife, fire, power tools, and theft. The social evaluation scenarios were drawn from situations that involved friends, family, neighbors, love, work, classes, public events, and service.

During the training sessions and the critical scan session, 30 social evaluation scenarios and 30 physical danger scenarios were presented. An additional three scenarios of each type were included in the training sessions so participants could practice the scanner task prior to the scan session.

Imaging Design

The event-related neuroimaging design involved two critical events: (1) immersing in an emotional scenario (either a social evaluation or physical danger scenario) and (2) experiencing the immersed state in one of four ways upon hearing an auditory categorization cue (as emotional: fearful or angry, or as another active state: planning or observing). We will refer to the first event as “immersion” and the second event as “categorization.” Because all neural patterns described here reflect activity during the first immersion event, we focus on this element of the design (for the categorization results and related methodological details, please see Wilson-Mendenhall et al., 2011). This design afforded a unique opportunity to examine the situations in which emotions emerge before the emotional state was explicitly categorized. As will be described later, the participant could not predict which categorization cue would follow the scenario, so the immersion period reflects situated activity that is not tied to a specific emotion category.

In order to separate neural activity during the immersion events from neural activity during the categorization events, we implemented a catch trial design (Ollinger et al., 2001a, b). Participants received 240 complete trials that each contained a social evaluation scenario or a physical danger scenario followed immediately by one of the four categorization cues. Participants also received 120 partial “catch” trials containing only a scenario (with no subsequent categorization cue), which enabled separation of the first scenario immersion event from the second categorization event. The partial trials constituted 33% of the total trials, a proportion in the recommended range for an effective catch trial design. Each of the 30 social evaluation scenarios and the 30 physical danger scenarios was followed once by each categorization cue, for a total of 240 complete trials (60 scenarios followed by 4 categorizations). Each of the 60 scenarios also occurred twice as a partial trial, for a total of 120 catch trials.

During each of 10 fMRI runs, participants received 24 complete trials and 12 partial trials. The complete and partial trials were intermixed with no-sound baseline periods that ranged from 0 to 12 s in increments of 3 s (average 4.5 s) in a pseudo-random order optimized by optseq2 (Greve, 2002). On a given trial, participants could not predict whether a complete or partial trial was coming, a necessary condition for an effective catch trial design (Ollinger et al., 2001a, b). Participants also could not predict the type of situation or the categorization cue they would hear. Across trials in a run, social evaluation and physical danger situations each occurred 18 times, and each of the 4 categorization cues (anger, fear, observe, plan) occurred 6 times, equally often with social evaluation and physical danger scenarios. A given scenario was never repeated within a run.

Procedure

The experiment contained two training sessions and an fMRI scan session. The first training session occurred 24–48 h before the second training session, followed immediately by the scan. During the training sessions, participants were encouraged to immerse themselves in all scenarios from a first-person perspective, to imagine the scenario in as much vivid detail as possible, and to construct mental imagery as if the scenario events were actually happening to them. The relation of the full to the core scenarios was also described, and participants were encouraged to reinstate the full scenario whenever they heard a core scenario.

During the first training session, participants listened over computer headphones to the full versions of the 66 scenarios that they would later receive on the practice trials and in the critical scan 24–48 h later, with the social evaluation and physical danger scenarios randomly intermixed. After hearing each full scenario, participants provided three judgments about familiarity and prior experiences, prompted by questions and response scales on the screen. After taking a break, participants listened to the 66 core versions of the scenarios, again over computer headphones and randomly intermixed. While listening to each core scenario, participants were instructed to reinstate the full version that they listened to earlier, immersing themselves fully into the respective scenario as it became enriched and developed from memory. After hearing each core scenario over the headphones, participants rated the vividness of the imagery that they experienced while immersed in the scenario. This task encouraged the participants to develop rich imagery upon hearing the core version. A detailed account of the first training session can be found in Wilson-Mendenhall et al. (2011).

During the second training session directly before the scan, participants first listened to the 66 full scenarios to be used in the practice and critical scans, and rated how much they were able to immerse themselves in each scenario, again hearing the scenarios over computer headphones and in a random order. After listening to each full scenario, the computer script presented the question, “How much did you experience ‘being there’ in the situation?” Participants responded on the computer keyboard, using a 1–7 scale, where one meant not experiencing being there in the situation at all, four meant experiencing being there a moderate amount, and seven meant experiencing being there very much, as if it was actually happening to them. The full scenarios were presented again at this point to ensure that participants were reacquainted with all the details before hearing the core versions later in the scanner. This first phase of the second training session lasted about an hour.

Participants were then instructed on the task that they would perform in the scanner and performed a run of practice trials. During the practice and during the scans, audio events were presented and responses collected using E-prime software (Schneider et al., 2002). On each complete trial, participants were told to immerse in the core version of a scenario as they listened to it, and that they would receive one of four words (anger, fear, observe, plan) afterward. The participant’s task was to judge how easy it was to experience what the word described in the context of the situation. The core scenario was presented auditorily at the onset of a 9 s period, lasting no more than 8 s. The word was then presented auditorily at the onset of a 3 s period, and participants responded as soon as ready. To make their judgments, participants pressed one of three buttons on a button box for not easy, somewhat easy, and very easy. During the practice trials, participants used an E-Prime button box to practice making responses. In the scanner, participants used a Current Designs fiber optic button box designed for high magnetic field environments. Participants were also told that there would be partial trials containing scenarios and no word cues, and that they were not to respond on these trials.

At the beginning of the practice trials, participants heard the same short instruction that they would hear before every run in the scanner: “Please close your eyes. Listen to each scenario and experience being there vividly. If a word follows, rate how easy it was to have that experience in the situation.” Participants performed a practice run equal in length to the runs that they would perform in the scanner. Following the practice run, the experimenter and the participant walked 5 min across campus to the scanner. Once settled safely and comfortably in the scanner, an initial anatomical scan was performed, followed by the 10 critical functional runs, and finally a second anatomical scan. Prior to beginning each functional run, participants heard the same short instruction from the practice run over noise-muffling headphones. Participants took a short break between each of the 8 min 3 s runs. Total time in the scanner was a little over 1.5 h.

Image Acquisition

The neuroimaging data were collected in the Biomedical Imaging Technology Center at Emory University on a research-dedicated 3T Siemens Trio scanner. In each functional run, 163 T2*-weighted echo planar image volumes depicting BOLD contrast were collected using a Siemens 12-channel head coil and parallel imaging with an iPAT acceleration factor of 2. Each volume was collected using a scan sequence that had the following parameters: 56 contiguous 2 mm slices in the axial plane, interleaved slice acquisition, TR = 3000 ms, TE = 30 ms, flip angle = 90°, bandwidth = 2442 Hz/Px, FOV = 220 mm, matrix = 64, voxel size = 3.44 mm × 3.44 mm × 2 mm. This scanning sequence was selected after testing a variety of sequences for susceptibility artifacts in orbitofrontal cortex, amygdala, and the temporal poles. We selected this sequence not only because it minimized susceptibility artifacts by using thin slices and parallel imaging, but also because using 3.44 mm in the X–Y dimensions yielded a voxel volume large enough to produce a satisfactory temporal signal-to-noise ratio. In each of the two anatomical runs, 176 T1-weighted volumes were collected using a high resolution MPRAGE scan sequence that had the following parameters: 192 contiguous slices in the sagittal plane, single-shot acquisition, TR = 2300 ms, TE = 4 ms, flip angle = 8°, FOV = 256 mm, matrix = 256, bandwidth = 130 Hz/Px, voxel size = 1 mm × 1 mm × 1 mm.

Image Preprocessing and Analysis

Image preprocessing and statistical analysis were conducted in AFNI (Cox, 1996). The first anatomical scan was registered to the second, and the average of the two scans computed to create a single high-quality anatomical scan. Initial preprocessing of the functional data included slice time correction and motion correction in which all volumes were registered spatially to a volume within the last functional run. A volume in the last run was selected as the registration base because it was collected closest in time to the second anatomical scan, which facilitated later alignment of the functional and anatomical data. The functional data were then smoothed using an isotropic 6 mm full-width half-maximum Gaussian kernel. Voxels outside the brain were removed from further analysis at this point, as were high-variability low-intensity voxels likely to be shifting in and out of the brain due to minor head motion. Finally, the signal intensities in each volume were divided by the mean signal value for the respective run and multiplied by 100 to produce percent signal change from the run mean. All later analyses were performed on these percent signal change data.

The averaged anatomical scan was corrected for non-uniformity in image intensity, skull-stripped, and then aligned with the functional data. The resulting aligned anatomical dataset was warped to Talairach space using an automated procedure employing the TT_N27 template (also known as the Colin brain, an averaged dataset from one person scanned 27 times).

Regression analyses were performed on each individual’s preprocessed functional data using a canonical, fixed-shape Gamma function to model the hemodynamic response. In the first regression analysis, betas were estimated using the event onsets for 10 conditions: 2 situation immersion conditions (social, physical) and 8 categorization conditions that resulted from crossing the situation with the categorization cue (social-anger, physical-anger, social-fear, physical-fear, social-observe, physical-observe, social-plan, physical-plan). Again, we only present results for the two situation immersion conditions here (see Wilson-Mendenhall et al., 2011 for the categorization results). The two situation immersion conditions were modeled by creating regressors that included scenario immersion events from both the complete trials and the partial trials. Including scenario immersion events from both trial types in one regressor made it possible to mathematically separate the situation immersion conditions from the subsequent categorization conditions (Ollinger et al., 2001a, b). Because scenario immersion events were 9 s in duration, the Gamma function was convolved with a boxcar function for the entire duration to model the situation immersion conditions. Six regressors obtained from volume registration during preprocessing were also included to remove any residual signal changes correlated with movement (translation in the X, Y, and Z planes; rotation around the X, Y, and Z axes). Scanner drift was removed by finding the best-fitting polynomial function correlated with time in the preprocessed time course data.

At the group level, the betas resulting from the each individual’s regression analysis were then entered into a second-level, random-effects ANOVA. Two key analyses were computed at this level of analysis using a voxel-wise threshold of p < 0.005 in conjunction with the 41-voxel extent threshold determined by AFNI ClustSim to produce an overall corrected threshold of p < 0.05. In the first analysis (that assessed our first hypothesis), we extracted clusters that were more active during immersion in social evaluation situations than in the no-sound baseline and clusters that were more active during immersion in physical danger situations than in the no-sound baseline (using the voxel-wise and extent thresholds specified above). We then entered the results of these two contrasts (social evaluation > baseline; physical danger > baseline) into a conjunction analysis to determine clusters shared by the two situation types (i.e., overlapping regions of activity). In the second analysis (that assessed our second hypothesis), we computed a standard contrast to directly compare immersion during social evaluation situations to immersion during physical danger situations using t tests (social evaluation > physical danger; physical danger > social evaluation).

A second individual-level regression was computed to examine the relationship between neural activity and the scenario immersion ratings collected during the training session just prior to the scan session, providing an additional test of our second hypothesis. This regression model paralleled the first regression model with the following exceptions. In this regression analysis, each participant’s “being there” ratings were specified trial-by-trial for each scenario in the social evaluation immersion condition and in the physical danger immersion condition. For the two situation immersion conditions (social evaluation and physical danger), both the onset times and ratings were then entered into the regression using the amplitude modulation option in AFNI. This option specified two regressors for each situation immersion condition, which were used to detect: (1) voxels in which activity was correlated with the ratings (also known as a parametric regressor); (2) voxels in which activity was constant for the condition and was not correlated with the ratings.

At the group level, each participant’s betas produced from the first parametric regressor for each situation immersion condition (i.e., indicating the strength of the correlation between neural activity and “being there” immersion ratings) were next entered into a second-level analysis. In this analysis, the critical statistic for each condition was a t test indicating if the mean across individuals differed significantly from zero (zero indicating no correlation between neural activity and the ratings). In these analyses, a slightly smaller cluster size of 15 contiguous voxels was used in conjunction with the voxel-wise threshold of p < 0.005.

In summary, this analysis is examining whether scenarios rated as easier to immerse in during the training are associated with greater neural activity in any region of the brain (the individual-level analysis), and whether this relationship between immersion ratings and neural activity is consistent across participants (group-level analysis). We computed this analysis separately for social evaluation and for physical danger situation types to test our hypothesis. This analysis is not examining between-subject individual differences in immersion (i.e., whether participants who generally experience greater immersion across all scenarios also show greater neural activity in specific regions), which is a different question that is not of interest here.

Results

Common Neural Activity during Immersion Across Situations

Our first hypothesis was that neural activity during both situations would be reliably greater than baseline across multiple sensory modalities and across regions involved in detecting and integrating salient sensory information (see Table 2 for the baseline contrasts). As shown in Figure 2A, neural activity was reliably greater than baseline in bilateral primary somatomotor and visual cortex, as well as premotor cortex, SMA, and extrastriate visual cortex, suggesting that participants easily immersed in the situations. The self-reported rating data from the training session confirmed that participants found the social evaluation and physical danger situations relatively easy to immerse in (see Figure 2B), with no significant differences in “being there” ratings between situation types [repeated measures t test; t(19) = 1.64, p > 0.05]. Because participants listened to the scenarios with their eyes closed and because participants did not make responses while immersing in the scenarios, it is significant that these sensorimotor regions were significantly more active than the no-sound baseline. As would be expected with an auditory, language-based immersion procedure, we observed activity in bilateral auditory cortex and in superior temporal and inferior frontal regions associated with language processing, with more extensive activity in the left frontal regions.

FIGURE 2


FIGURE 2. (A) shared neural activity during social evaluation and physical danger situations in sensorimotor cortex (revealed by the conjunction analysis in which each situation was compared to the “no sound” baseline) (B) self- reported immersion ratings from the training session (error bars depict SEM across participant condition means) (C) shared neural activity revealed by the conjunction analysis in the amygdala and hippocampus.

TABLE 2


TABLE 2. Social evaluation > baseline and physical danger > baseline contrasts.

Consistent with the hypothesis that immersion would also generally involve selection, encoding, and integration of salient sensory and other information, we observed activity in bilateral hippocampus and in right amygdala (see Figure 2C). Extensive evidence implicates the hippocampus in mnemonic functions (Squire and Zola-Morgan, 1991; Tulving, 2002; Squire, 2004), especially the integration and binding of the multimodal information involved in constructing (and reconstructing) situated memories (Addis and McAndrews, 2006; Kroes and Fernandez, 2012). More recent evidence establishes a central role for this structure in simulating future, imagined situations (Addis et al., 2007; Hassabis et al., 2007; Schacter et al., 2007, 2012), which is similar in nature to our immersion paradigm, and which requires similar integration and binding of concepts established in memory (from prior experience). The amygdala plays a central role in emotional experiences by efficiently integrating multisensory information to direct attention and guide encoding (Costafreda et al., 2008; Bliss-Moreau et al., 2011; Klasen et al., 2012; Lindquist et al., 2012), especially during situations that involve threat (Adolphs, 2008; Miskovic and Schmidt, 2012). As we will see, no differences emerged in the amygdala or in the hippocampus during the social evaluation and physical danger situations, suggesting these structures played a similar role in both types of experiences.

Unique Neural Patterns Emerge for Social Evaluation and Physical Danger Situations

Our second hypothesis was that networks underlying the social inference and mentalizing involved in responding to a social threat would be reliably more active during social evaluation situations, whereas networks underlying visuospatial attention and action planning involved in responding to a physical threat would be reliably more active during physical danger situations. As Table 3, together with Figures 3–5, illustrate, the neural patterns that emerged when we compared social evaluation situations to physical danger situations are consistent with these predictions. Figure 3 shows these results on representative 2D slices, with regions showing reliably greater activity during social evaluation in orange, and regions showing reliably greater activity during physical danger in green. Figures 4 and 5 display these maps projected onto the surface of the brain4, and directly compare the maps from this study with the large-scale networks that have been defined using resting state connectivity techniques across large samples (Yeo et al., 2011).

FIGURE 3


FIGURE 3. Social evaluation vs. physical danger contrast, with regions reliably more active during social evaluation in orange and regions reliably more active during physical danger in green.

FIGURE 4


FIGURE 4. Comparison of the social evaluation map from this study with the default mode network defined by Yeo et al. (2011)

FIGURE 5


FIGURE 5. Comparison of the physical danger map from this study with the attention networks defined by Yeo et al. (2011)

Heightened activity in the default mode network during social evaluation

As displayed in Figure 3 and Table 3, robust activity was observed during immersion in social evaluation situations (vs. physical danger situations) in midline medial prefrontal and posterior cingulate regions, as well as lateral temporal regions, in which activity spanned from the temporal pole to the posterior superior temporal sulcus/temporoparietal junction bilaterally, and on the left, extended in to inferior frontal gyrus. This pattern of activity maps onto a network that is often referred to as the “default mode” network (Gusnard and Raichle, 2001; Raichle et al., 2001; Buckner et al., 2008). Figure 4 illustrates the overlap between the default mode network and the pattern of neural activity that underlies immersing in social evaluation situations here (Yeo et al., 2011). The default mode network has been implicated in mentalizing and social inference (i.e., inferring what others’ are thinking/feeling and how they will act), as well as other socially motivated tasks, including autobiographical memory retrieval, envisioning the future, and moral reasoning (for reviews, see Buckner et al., 2008; Van Overwalle and Baetens, 2009; Barrett and Satpute, 2013). Consistent with the idea of situated emotional experience, participants engaged in the social inference and mentalizing that would be adaptive in responding to a social threat when immersed in social evaluation situations.

TABLE 3


TABLE 3. Brain regions that emerged in the social evaluation vs. physical danger contrast.

Heightened activity in fronto-parietal attention networks during physical danger

Figure 3 and Table 3 show the fronto-parietal patterns of activity observed during immersion in physical danger situations (vs. social evaluation situations). In addition to lateral frontal and parietal regions (including bilateral middle frontal gyrus, bilateral inferior frontal gyrus extending into pars orbitalis, bilateral inferior parietal lobule, and bilateral superior parietal/precuneus), neural activity was also reliably greater in right anterior insula, mid cingulate cortex, and bilateral premotor cortex during immersion in physical danger situations. Figure 5 illustrates the overlap between this pattern of activity and three networks that have been implicated in attention5 (Chun et al., 2011; Petersen and Posner, 2012; Posner, 2012). The most significant overlap was observed in the lateral fronto-parietal executive network and the dorsal attention network. These networks are thought to allocate attentional resources to prioritize specific sensory inputs (what is often referred to as “orienting” to the external environment) and to guide flexible shifts in behavior (Dosenbach et al., 2007; Petersen and Posner, 2012). The operations they carry out are critical for maintaining a vigilant state (Tang et al., 2012), which is important during threat. Less overlap was evident in the ventral attention network that is thought to interrupt top-down operations through bottom-up “salience” detection (Corbetta et al., 2008), although robust activity was observed in the mid cingulate regions shown in Figure 5 that support the action monitoring that occurs, especially, in situations involving physical pain (Morecraft and Van Hoesen, 1992; Vogt, 2005). Taken together, this pattern of results suggests, strikingly, that immersion in the physical danger situations (from a first-person perspective with eyes closed) engaged attention networks that are studied almost exclusively using external visual cues. Consistent with the idea of situated emotional experience, participants engaged in the monitoring of the environment and preparation for flexible action that would be adaptive in action to a physical threat when immersed in physical danger situations.

Immersion ratings correlate with activity in different regions during social evaluation vs. physical danger situations

To provide another test of our second hypothesis, we examined whether self-reported immersion ratings of “being there” in the situation (from the training session) were associated with brain activity during the two situation types. If emotional experience is situated, then feeling immersed in a situation should be realized by neural circuitry that underlies engaging in the specific situation. Whereas immersion in social evaluation situations should occur when affect is grounded in mentalizing about others, immersion in physical danger situations should occur when affect is grounded in taking action in the environment. The results displayed in Figure 6 support this prediction.

FIGURE 6

FIGURE 6. Regions in which neural activity was significantly correlated with participants’ “being there” ratings of immersion collected during the training session just prior to scanning, for the social evaluation situations and for the physical danger situations.

During social evaluation situations, participants’ immersion ratings correlated with activity in anterior medial prefrontal cortex (frontal pole area; peak voxel -6 51 0; 23 voxels) and in superior temporal gyrus/sulcus (peak voxel -47 -49 14; 24 voxels; see Figure 6). As described above, these regions are part of the default mode network and are central to social perception and mentalizing (Allison et al., 2000; Buckner et al., 2008; Adolphs, 2009; Van Overwalle, 2009). The anterior, frontal pole region of medial prefrontal cortex is considered the anterior hub of the default mode network (Andrews-Hanna et al., 2010) that integrates affective information from the body with social event knowledge (including inferences about others’ thoughts) originating in ventral and dorsal aspects of medial prefrontal cortex, respectively (Mitchell et al., 2005; Krueger et al., 2009). This integration may underlie the experience of “personal significance” (Andrews-Hanna et al., 2010) that appears important for immersing in social evaluation situations.

In contrast, during physical danger situations, participants’ immersion ratings correlated with activity in dorsal anterior cingulate/mid cingulate (extending into SMA; peak -1 17 40; 40 voxels) and in left inferior parietal cortex (peak -36 -46 39; 15 voxels; see Figure 6). The robust cluster of activity that emerged in the cingulate is part of the ventral attention “salience” network, and it is anterior to the mid cingulate activity observed in the initial whole-brain contrasts reported above. Because this region has been implicated across studies of emotion, pain, and cognitive control, and because it is anatomically positioned at the intersection of insular-limbic and fronto-parietal sub-networks within the attention system, it may play an especially important role in specifying goal-directed action based on affective signals originating in the body (Shackman et al., 2011; Touroutoglou et al., 2012). This integration may underlie the experience of action-oriented agency (Craig, 2009) that appears important for immersing in physical danger situations. The significant correlation with activity in left inferior parietal cortex, which supports planning action in egocentric space (e.g., Fogassi and Luppino, 2005), further suggests that immersion in physical danger situations is driven by preparing to act in the environment.

Discussion

Our novel scenario immersion paradigm revealed robust patterns of neural activity when participants immersed themselves in social evaluation scenarios and in physical danger scenarios. Consistent with participants’ high self-reported immersion ratings, neural activity across multiple sensory regions, and across limbic regions involved in the multisensory integration underlying the selection, encoding, and interpretation that influences what is salient and remembered (e.g., amygdala, hippocampus), occurred during both situation types. In addition to this shared activity, distributed patterns unique to each situation type reflected situated responding, with regions involved in mentalizing and social cognition more active during social evaluation and with regions involved in attention and action planning more active during physical danger.

Taken together, these findings suggest that our method produced vivid, engaging experiences during neuroimaging scans and that it could be used to study a variety of emotional experiences. One reason this immersion paradigm may be so powerful is that people often find themselves immersed in imagined situations in day-to-day life. Large-scale experience sampling studies have revealed that people spend much of their time imagining experiences that are unrelated to the external world around them (e.g., Killingsworth and Gilbert, 2010). An important direction for future research will be to understand if, consistent with other imagery-based paradigms, physiological changes occur during our scenario immersion paradigm and if these physiological changes are associated with subjective experiences of immersion.

The scenarios we developed for this study represent a small subset of the situations that people experience in real life (see also Wilson-Mendenhall et al., 2013). Because emotional experiences vary tremendously, it is adaptive to develop situated knowledge that guides inference and responding when similar situations arise in the future (Barsalou, 2003, 2008, 2009; Barrett, 2013). Here, we focused on immersion in emotion-inducing situations before they were explicitly categorized as an emotion (or another state). From our perspective, the situation plays a critical role in the emergence of an emotion, and it should not be considered a separate phenomenon from it (Barrett, 2009b, 2012; Wilson-Mendenhall et al., 2011). For example, it would be impossible to experience fear upon delivering a public speech without inferring others’ thoughts. Instead of viewing mentalizing as a “cold” cognitive process that interacts with a primitive “hot” emotion, we view mentalizing as an essential part of the situation in which the emotion emerges. Likewise, it would be impossible to experience fear upon getting lost in the woods without focusing attention on the environment (in other words, if one was instead lost in internal thought while traversing the same environment, it is unlikely that this fear would occur). We propose that it will be more productive to study emotional experience as dynamic situated conceptualizations that the brain continually generates to interpret one’s current state (based on prior experience), as opposed to temporally constrained cognition-emotion frameworks that often strip away much of the dynamically changing situated context. A situated approach also offers new insights into studying dynamic emotion regulation and dysregulation (Barrett et al., in press).

Network approaches to brain function provide functional frameworks for interpreting the distributed patterns that characterize situated experiences (Cabral et al., 2011; Deco et al., 2011; Lindquist and Barrett, 2012; Barrett and Satpute, 2013). As shown in Figures 4 and 5, the patterns unique to each situation type in this study can be differentiated by the anatomically constrained resting state networks6 identified in previous work (Raichle et al., 2001; Fox et al., 2005; Vincent et al., 2006; Dosenbach et al., 2007; Fair et al., 2007; Seeley et al., 2007; Yeo et al., 2011; Touroutoglou et al., 2012). Whereas the neural patterns underlying social threat situations primarily map onto the default mode network that supports social inference and mentalizing, the neural patterns underlying physical threat situations primarily map onto attention networks underlying monitoring of the environment and action planning. The neural pattern unique to each situation type reflects adaptive, situated responding. Furthermore, regions traditionally associated with emotion diverged in line with these networks (e.g., ventromedial prefrontal cortex as part of the default mode network; lateral orbitofrontal cortex and cingulate regions as part of the attention networks). Interestingly, these regions appear to be central to immersion in each type of situation, with the anterior medial prefrontal cortex (which is often considered part of ventromedial prefrontal cortex) associated with immersion during social evaluation situations and dorsal anterior cingulate associated with immersion during physical danger situations. These results suggest, strikingly, that the brain realizes immersion differently depending on the situation.

Resting state networks provide a starting point for examining how networks underlie situated experiences, but recent evidence suggests that coordination between regions in these networks dynamically changes during different psychological states (e.g., van Marle et al., 2010; Raz et al., 2012; Wang et al., 2012). In this study, for example, the neural patterns underlying physical danger experiences recruited various aspects of several different attention networks. Attention is primarily studied using simple visual detection tasks that examine external stimuli vs. internal goal dichotomies. Recent reviews emphasize the need for research that examines how attention systems operate during experiences guided by memory (e.g., Hutchinson and Turk-Browne, 2012), which arguably constitute much of our experience. Because inferior parietal cortex and cingulate regions figured prominently in the pattern observed across the attention networks in this study, this particular configuration may reflect the attention operations involved in coordinating bodily actions in space. It is also important to consider that these patterns reflect relative differences between the social and physical threat situations. As we showed initially, the situation types also share patterns of activity that contribute to the overall pattern of situated activity. In our view, it is useful to think about situated neural activity as dynamically changing patterns that are distributed across structurally and functionally distinct networks (see also Barrett and Satpute, 2013). Even within a structurally defined network, different distributed patterns of neural activity may reflect unique functional motifs that underlie different experiences and behaviors (Sporns and Kotter, 2004).

In closing, a psychological construction approach to studying situated emotion motivates different questions than traditional approaches to studying emotion. It invites shifting research agendas from defining five or so emotion categories to studying the rich situations that characterize emotional experiences.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Preparation of this manuscript was supported by an NIH Director’s Pioneer Award DPI OD003312 to Lisa Feldman Barrett at Northeastern University with a sub-contract to Lawrence Barsalou at Emory University. We thank A. Satpute and K. Lindquist for the meta-analysis codes indicating study methods/tasks.

Footnotes

^ This meta-analytic database has recently been updated to include articles through 2011. The proportions reported here reflect the updated database.
^ Lindquist etal. (2012) distinguished between “emotion perception” (defined as perception of emotion in others) and “emotion experience” (defined as experience of emotion in oneself) in their meta-analysis. When restricting our analysis of study methods to studies that involved emotion experience (as coded in the database), the use of imagery methods was still minimal (10% of 233 studies). Although emotional imagery is typically thought of as an induction of emotion experience, it seems likely that imagined situations, especially if they are social in nature, involve dynamic emotion perception as well.
^ There is substantial evidence that default mode network (DMN) regions are active during tasks that involve social inference and mentalizing (for reviews, see Barrett and Satpute, 2013; Buckner and Carroll, 2007; Van Overwalle and Baetens, 2009) and that the DMN is disrupted in disorders involving social deficits (for reviews, see Menon, 2011; Whitfield-Gabrieli and Ford, 2012). Recent work has directly demonstrated that neural activity during social/mentalizing tasks occurs in the DMN as it is defined using resting state analyses (e.g., Andrews-Hanna etal., 2010) and that resting state connectivity in the DMN predicts individual differences in social processing (e.g., Yang etal., 2012).
^ It is important to note that each individual’s data were not analyzed on the surface. We are using a standardized (Talairach) surface space for illustration of the group results in comparison to the resting state network maps from a large sample that have been made freely available (Yeo etal., 2011).
^ These networks are sometimes referred to by different names, and can take somewhat different forms depending on the methods used to define them (with core nodes remaining the same). Because the network maps we present here are taken from Yeo etal. (2011), we use their terminology. They note (and thus so do we) that the ventral attention network, especially, is similar to what has been described as the salience network (Seeley etal., 2007) and the cingulo-opercular network (Dosenbach etal., 2007).
^ The term “resting state” is often misinterpreted to mean the resting brain. It should not be assumed that the brain is actually “at rest” during these scans, but simply that there is no externally orienting task.

References are available at the Frontiers site.