Has artificial intelligence become alchemy?

Mathew Hutson describes Ali Rahimi's critique of current artificial intelligence (AI) learning algorithms at a recent AI meeting:

Rahimi charged that machine learning algorithms, in which computers learn through trial and error, have become a form of “alchemy.” Researchers, he said, do not know why some algorithms work and others don't, nor do they have rigorous criteria for choosing one AI architecture over another...Without deep understanding of the basic tools needed to build and train new algorithms, he says, researchers creating AIs resort to hearsay, like medieval alchemists. “People gravitate around cargo-cult practices,” relying on “folklore and magic spells,” adds François Chollet, a computer scientist at Google in Mountain View, California. For example, he says, they adopt pet methods to tune their AIs' “learning rates”—how much an algorithm corrects itself after each mistake—without understanding why one is better than others.

Rahimi offers several suggestions for learning which algorithms work best, and when. For starters, he says, researchers should conduct “ablation studies” like those done with the translation algorithm: deleting parts of an algorithm one at a time to see the function of each component. He calls for “sliced analysis,” in which an algorithm's performance is analyzed in detail to see how improvement in some areas might have a cost elsewhere.

Ben Recht, a computer scientist at the University of California, Berkeley, and coauthor of Rahimi's alchemy keynote talk, says AI needs to borrow from physics, where researchers often shrink a problem down to a smaller “toy problem.” “Physicists are amazing at devising simple experiments to root out explanations for phenomena,” he says.

Csaba Szepesvári, a computer scientist at DeepMind in London, says the field also needs to reduce its emphasis on competitive testing. At present, a paper is more likely to be published if the reported algorithm beats some benchmark than if the paper sheds light on the software's inner workings.

Not everyone agrees with Rahimi and Recht's critique. Yann LeCun, Facebook's chief AI scientist in New York City, worries that shifting too much effort away from bleeding-edge techniques toward core understanding could slow innovation and discourage AI's real-world adoption. “It's not alchemy, it's engineering,” he says. “Engineering is messy.”

Status threat explains 2016 presidential vote

Niraj Chokshi points to a PNAS article by Diana Mutz.  Mutz's abstract:

Significance

Support for Donald J. Trump in the 2016 election was widely attributed to citizens who were “left behind” economically. These claims were based on the strong cross-sectional relationship between Trump support and lacking a college education. Using a representative panel from 2012 to 2016, I find that change in financial wellbeing had little impact on candidate preference. Instead, changing preferences were related to changes in the party’s positions on issues related to American global dominance and the rise of a majority–minority America: issues that threaten white Americans’ sense of dominant group status. Results highlight the importance of looking beyond theories emphasizing changes in issue salience to better understand the meaning of election outcomes when public preferences and candidates’ positions are changing.

Abstract

This study evaluates evidence pertaining to popular narratives explaining the American public’s support for Donald J. Trump in the 2016 presidential election. First, using unique representative probability samples of the American public, tracking the same individuals from 2012 to 2016, I examine the “left behind” thesis (that is, the theory that those who lost jobs or experienced stagnant wages due to the loss of manufacturing jobs punished the incumbent party for their economic misfortunes). Second, I consider the possibility that status threat felt by the dwindling proportion of traditionally high-status Americans (i.e., whites, Christians, and men) as well as by those who perceive America’s global dominance as threatened combined to increase support for the candidate who emphasized reestablishing status hierarchies of the past. Results do not support an interpretation of the election based on pocketbook economic concerns. Instead, the shorter relative distance of people’s own views from the Republican candidate on trade and China corresponded to greater mass support for Trump in 2016 relative to Mitt Romney in 2012. Candidate preferences in 2016 reflected increasing anxiety among high-status groups rather than complaints about past treatment among low-status groups. Both growing domestic racial diversity and globalization contributed to a sense that white Americans are under siege by these engines of change.

The effort paradox - Effort is both costly and valued

Inzlicht et al. do an interesting review article on how we (as well as some other animals) associate effort with reward, sometimes pursuing objects and outcomes because of the effort they require rather than in spite of it. Effort can increase value retrospectively (as in the IKEA effect, valuing what you build more than what is ready-made), concurrently (as in Flow, enjoyment of energized focus), or prospective (as in effortful versus little effort pro-social work).

Their abstract and list of highlights:

According to prominent models in cognitive psychology, neuroscience, and economics, effort (be it physical or mental) is costly: when given a choice, humans and non-human animals alike tend to avoid effort. Here, we suggest that the opposite is also true and review extensive evidence that effort can also add value. Not only can the same outcomes be more rewarding if we apply more (not less) effort, sometimes we select options precisely because they require effort. Given the increasing recognition of effort’s role in motivation, cognitive control, and value-based decision-making, considering this neglected side of effort will not only improve formal computational models, but also provide clues about how to promote sustained mental effort across time.

Highlights

Prominent models in the cognitive sciences indicate that mental and physical effort is costly, and that we avoid it. Here, we suggest that this is only half of the story.

Humans and non-human animals alike tend to associate effort with reward and will sometimes select objects or activities precisely because they require effort (e.g., mountain climbing, ultra-marathons).

Effort adds value to the products of effort, but effort itself also has value.

Effort’s value can not only be accessed concurrently with or immediately following effort exertion, but also in anticipation of such expenditure, suggesting that we already have an intuitive understanding of effort’s potential positive value.

If effort is consistently rewarded, people might learn that effort is valuable and become more willing to exert it in general.

Transparency is the mother of 'fake news'

Stanley Fish, writing in the NYTimes "The Stone" series suggests that fake news is in large part a product of the enthusiasm for transparency and absolutely free speech. I suggest you read the whole piece. Below are a few clips.

The problem is..

...that information, data and the unbounded flow of more and more speech can be politicized — it can, that is, be woven into a narrative that constricts rather than expands the area of free, rational choice. When that happens — and it will happen often — transparency and the unbounded flow of speech become instruments in the production of the very inequalities (economic, political, educational) that the gospel of openness promises to remove. And the more this gospel is preached and believed, the more that the answer to everything is assumed to be data uncorrupted by interests and motives, the easier it will be for interest and motives to operate under transparency’s cover.

This is so because speech and data presented as if they were independent of any mechanism of selectivity will float free of the standards of judgment that are always the content of such mechanisms. Removing or denying the existence of gatekeeping procedures will result not in a fair and open field of transparency but in a field where manipulation and deception find no obstacles. Because it is an article of their faith that politics are bad and the unmediated encounter with data is good, internet prophets will fail to see the political implications of what they are trying to do, for in their eyes political implications are what they are doing away with.

...human difference is irreducible, and there is no “neutral observation language” (a term of the philosopher Thomas Kuhn’s in his 1962 book “The Structure of Scientific Revolutions”) that can bridge, soften, blur and even erase the differences. When people from opposing constituencies clash there is no common language to which they can refer their differences for mechanical resolution; there are only political negotiations that would involve not truth telling but propaganda, threats, insults, deceptions, exaggerations, insinuations, bluffs, posturings — all the forms of verbal manipulation that will supposedly disappear in the internet nirvana.

They won’t. Indeed, they will proliferate because the politically angled speech that is supposedly the source of our problems is in fact the only possible route to their (no doubt temporary) solution. Speech proceeding from a point of view can at least be recognized as such and then countered. You say, “I know where those guys are coming from, and here are my reasons for believing that we should be coming from some place else” — and dialogue begins. It is dialogue inflected by interests and agendas, but dialogue still. But when speech (or information or data) is just sitting there inert, unattached to any perspective, when there are no guidelines, monitors, gatekeepers or filters, what you have are innumerable bits (like Lego) available for assimilation into any project a clever verbal engineer might imagine; and what you don’t have is any mechanism that can stop or challenge the construction project or even assess it. What you have, in short, are the perfect conditions for the unchecked proliferation of what has come to be called “fake news.”

Industrial revolutions are political and social wrecking balls.

I want to point to yet another impressive bit of research and writing by Thomas Edsall, who gives one of the most clear pictures I have seen of current political and economic changes. Edsall begins with a few quotes from Klaus Schwab at Davos in January 2016 on the bright side of the 'fourth industrial revolution' (cf. my posts on Schwab and Davos on Jan. 28, Jan. 29, and Feb. 9, 2016.) and then the downside. Compared with previous industrial revolutions,

...the fourth is evolving at an exponential rather than a linear pace. Moreover, it is disrupting almost every industry in every country. And the breadth and depth of these changes herald the transformation of entire systems of production, management, and governance.

And, in a huge understatement:

As automation substitutes for labor across the entire economy, the net displacement of workers by machines might exacerbate the gap between returns to capital and returns to labor.

Edsall quotes from various authors:

On balance, near-term AI will have the greatest effect on blue collar work, clerical work and other mid-skilled occupations. Given globalization’s effect on the 2016 presidential election, it is worth noting that near-term AI and globalization replace many of the same jobs...Robots, autonomous vehicles, virtual reality, artificial intelligence, machine learning, drones and the Internet of Things are moving ahead rapidly and transforming the way businesses operate and how people earn their livelihoods. For millions who work in occupations like food service, retail sales and truck driving, machines are replacing their jobs.

AI’s near-term effect will not be mass unemployment but occupational polarization resulting in a slowly growing number of persons moving from mid-skilled jobs into lower wage work

The concern is not that robots will take human jobs and render humans unemployable. The traditional economic arguments against that are borne out by centuries of experience...the problem lies in the process of turnover, which could lead to sustained periods of time with a large fraction of people not working...not all workers will have the training or ability to find the new jobs created by AI. Moreover, this “short run” could last for decades and, in fact, the economy could be in a series of “short runs” for even longer.

A populist politician who campaigned on AI-induced job loss would start with ready-made definitions of the "people” and the “elite” based on national fault lines that were sharpened in the 2016 presidential election. This politician also would have a ready-made example of disrespect: the set of highly educated coastal “elites” who make a very good living developing robots to put “the people” out of work.

...both technology and trade seem to drive structural changes which are consequential for voting behavior...Job losses in manufacturing due to automation do create fertile territory for continued populist appeal...In fact, some of the places where Trump made the biggest gains relative to McCain or Romney are in the heartland of heavy manufacturing where robots did lead to losses of manufacturing jobs...David Autor, an economist at M.I.T., examined the political consequences in congressional districts hurt by increased trade with China and found a significant increase in the election of very conservative Republicans.

Rather than directly opposing free trade policies, individuals in import-exposed communities tend to target scapegoats such as immigrants and minorities. This drives support for right-wing candidates, as they compete electorally by targeting out-groups...in areas affected by trade, the scapegoating of immigrants takes place across the board and is not limited to manufacturing workers.

The hard core of Trump’s voters — more than half of all Republican voters don’t just approve of him, but strongly approve — have, in turn, demonstrated a willingness to deify the president no matter what he does or says — a deification dependent in no small part on Trump’s adoption of new communications technologies like Twitter.

The determination of the Trump wing of the Republican Party to profiteer on technologically driven economic and cultural upheaval — and the success of this strategy to date — suggests that the party will continue on its path. For this reason and many others, it is critically important that Democrats develop a more far-reaching understanding of the disruptive, technologically fueled economic and cultural forces that are now shaping American politics — if they intend to steer the country in a more constructive direction, that is.

How not to mind if someone is lying...

Daniel Effron describes the means by which Trump supporters, aware that many of his statements are falsehoods, manage to temper their potential anger.

Mr. Trump’s representatives have used a subtle psychological strategy to defend his falsehoods: They encourage people to reflect on how the falsehoods could have been true.

Effron's research has confirmed the effectiveness of this tactic. He asked

...2,783 Americans from across the political spectrum to read a series of claims that they were told (correctly) were false. Some claims, like the falsehood about the inauguration crowd, appealed to Mr. Trump’s supporters, and some appealed to his opponents: for instance, a false report (which circulated widely on the internet) that Mr. Trump had removed a bust of the Rev. Dr. Martin Luther King Jr. from the Oval Office.

All the participants were asked to rate how unethical it was to tell the falsehoods. But half the participants were first invited to imagine how the falsehood could have been true if circumstances had been different. For example, they were asked to consider whether the inauguration would have been bigger if the weather had been nicer, or whether Mr. Trump would have removed the bust if he could have gotten away with it.

The results of the experiments... show that reflecting on how a falsehood could have been true did cause people to rate it as less unethical to tell — but only when the falsehoods seemed to confirm their political views. Trump supporters and opponents both showed this effect.

Again, the problem wasn’t that people confused fact and fiction; virtually everyone recognized the claims as false. But when a falsehood resonated with people’s politics, asking them to imagine counterfactual situations in which it could have been true softened their moral judgments. A little imagination can apparently make a lie feel “truthy” enough to give the liar a bit of a pass.

These results reveal a subtle hypocrisy in how we maintain our political views. We use different standards of honesty to judge falsehoods we find politically appealing versus unappealing. When judging a falsehood that maligns a favored politician, we ask, “Was it true?” and then condemn it if the answer is no.

In this time of “fake news” and “alternative facts,”...Even when partisans agree on the facts, they can come to different moral conclusions about the dishonesty of deviating from those facts. The result is more disagreement in an already politically polarized world.

More on the vagaries of expertise

To follow up on yesterday's post on the illusion of having skills, I want to point to two other articles in this vein. Herrera notes work showing that:

...in group-work settings, instead of determining whether a given person has genuine expertise we sometimes focus on proxies of expertise — the traits and habits we associate, and often conflate, with expertise. That means qualities such as confidence, extroversion and how much someone talks can outweigh demonstrated knowledge when analyzing whether a person is an expert...In other words, your brain can instinctively trust people simply because they sound as if they know what they’re talking about.

And, Gibson reviews the work of Tom Nichols, reflected in his book "The Death of Expertise: The Campaign Against Expertise and Why It Matters." Nichols...

...had begun noticing what he perceived as a new and accelerating—and dangerous—hostility toward established knowledge. People were no longer merely uninformed, Nichols says, but “aggressively wrong” and unwilling to learn. They actively resisted facts that might alter their preexisting beliefs. They insisted that all opinions, however uninformed, be treated as equally serious. And they rejected professional know-how, he says, with such anger. That shook him.

Skepticism toward intellectual authority is bone-deep in the American character, as much a part of the nation’s origin story as the founders’ Enlightenment principles. Overall, that skepticism is a healthy impulse, Nichols believes. But what he was observing was something else, something malignant and deliberate, a collapse of functional citizenship. “Americans have reached a point where ignorance, especially of anything related to public policy, is an actual virtue...To reject the advice of experts is to assert autonomy, a way for Americans to insulate their increasingly fragile egos from ever being told they’re wrong about anything.”

Readers regularly approach Nichols with stories of their own disregarded expertise: doctors, lawyers, plumbers, electricians who’ve gotten used to being second-guessed by customers and clients and patients who know little or nothing about their work. “So many people over the past year have walked up to me and said, ‘You wrote what I was thinking,’” he says.

The illusion of skill acquisition.

Kardas and O'Brien document how watching others perform can foster an illusion of skill acquisition. Their abstract:

Modern technologies such as YouTube afford unprecedented access to the skilled performances of other people. Six experiments (N = 2,225) reveal that repeatedly watching others can foster an illusion of skill acquisition. The more people merely watch others perform (without actually practicing themselves), the more they nonetheless believe they could perform the skill, too (Experiment 1). However, people’s actual abilities—from throwing darts and doing the moonwalk to playing an online game—do not improve after merely watching others, despite predictions to the contrary (Experiments 2–4). What do viewers see that makes them think they are learning? We found that extensive viewing allows people to track what steps to take (Experiment 5) but not how those steps feel when taking them. Accordingly, experiencing a “taste” of performing attenuates the illusion: Watching others juggle but then holding the pins oneself tempers perceived change in one’s own ability (Experiment 6). These findings highlight unforeseen problems for self-assessment when watching other people.

Protein synthesis in brain tissue is much higher than previously thought.

Smeets et al. use stable isotope methodology during temporal lobe resection surgery to demonstrate protein synthesis rates exceeding 3% per day, suggesting that brain tissue plasticity is far greater than previously assumed.

All tissues undergo continuous reconditioning via the complex orchestration of changes in tissue protein synthesis and breakdown rates. Skeletal muscle tissue has been well studied in this regard, and has been shown to turnover at a rate of 1–2% per day in vivo in humans. Few data are available on protein synthesis rates of other tissues. Because of obvious limitations with regard to brain tissue sampling no study has ever measured brain protein synthesis rates in vivo in humans. Here, we applied stable isotope methodology to directly assess protein synthesis rates in neocortex and hippocampus tissue of six patients undergoing temporal lobectomy for drug-resistant temporal lobe epilepsy (Clinical trial registration: NTR5147). Protein synthesis rates of neocortex and hippocampus tissue averaged 0.17 ± 0.01 and 0.13 ± 0.01%/h, respectively. Brain tissue protein synthesis rates were 3–4-fold higher than skeletal muscle tissue protein synthesis rates (0.05 ± 0.01%/h; P < 0.001). In conclusion, the protein turnover rate of the human brain is much higher than previously assumed.

Electrical brain stimulation enhances visual memory performance

Kucewicz et al. study patients with epilepsy undergoing evaluation for resective surgery to show that stimulation of the lateral temporal cortex, but not the hippocampus, parahippocampal neocortex or prefrontal cortex, increases the number of words that patients can remember.:

Direct electrical stimulation of the human brain can elicit sensory and motor perceptions as well as recall of memories. Stimulating higher order association areas of the lateral temporal cortex in particular was reported to activate visual and auditory memory representations of past experiences (Penfield and Perot, 1963). We hypothesized that this effect could be used to modulate memory processing. Recent attempts at memory enhancement in the human brain have been focused on the hippocampus and other mesial temporal lobe structures, with a few reports of memory improvement in small studies of individual brain regions. Here, we investigated the effect of stimulation in four brain regions known to support declarative memory: hippocampus, parahippocampal neocortex, prefrontal cortex and temporal cortex. Intracranial electrode recordings with stimulation were used to assess verbal memory performance in a group of 22 patients (nine males). We show enhanced performance with electrical stimulation in the lateral temporal cortex (paired t-test, P = 0.0067), but not in the other brain regions tested. This selective enhancement was observed both on the group level, and for two of the four individual subjects stimulated in the temporal cortex. This study shows that electrical stimulation in specific brain areas can enhance verbal memory performance in humans.

A morning cortisol pulse is crucial for normal cognitive and emotional responses.

From Kalafatakis et. al.:

Significance

The hypothalamic-pituitary-adrenal axis is a critical neurohormonal network regulating homeostasis and coordinating stress responses. Here we demonstrate that an oscillating pattern of plasma cortisol is important for maintenance of healthy brain responses as measured by functional neuroimaging and behavioral testing. Our data highlight the crucial role of glucocorticoid rhythmicity in (i) modulating sleep behavior and working memory performance, and (ii) regulating the human brain’s responses under emotional stimulation. Current optimal cortisol replacement therapies for patients with primary or secondary adrenal insufficiently are associated with poor psychological status, and these results suggest that closer attention to aspects of chronotherapy will benefit these patients and may also have major implications for improved glucocorticoid dynamics in stress and psychiatric disease.

Abstract

Glucocorticoids (GCs) are secreted in an ultradian, pulsatile pattern that emerges from delays in the feedforward-feedback interaction between the anterior pituitary and adrenal glands. Dynamic oscillations of GCs are critical for normal cognitive and metabolic function in the rat and have been shown to modulate the pattern of GC-sensitive gene expression, modify synaptic activity, and maintain stress responsiveness. In man, current cortisol replacement therapy does not reproduce physiological hormone pulses and is associated with psychopathological symptoms, especially apathy and attenuated motivation in engaging with daily activities. In this work, we tested the hypothesis that the pattern of GC dynamics in the brain is of crucial importance for regulating cognitive and behavioral processes. We provide evidence that exactly the same dose of cortisol administered in different patterns alters the neural processing underlying the response to emotional stimulation, the accuracy in recognition and attentional bias toward/away from emotional faces, the quality of sleep, and the working memory performance of healthy male volunteers. These data indicate that the pattern of the GC rhythm differentially impacts human cognition and behavior under physiological, nonstressful conditions and has major implications for the improvement of cortisol replacement therapy.

Sitting is bad for your brain...

It is well known that sitting for long periods each day correlates with higher risk of heart disease, diabetes, and mortality rate. Siddarth et al. at UCLA now show a correlation of sedentary behavior with reduced thickness of the medial temporal lobe of our brains, which contains the hippocampus and is central to learning and memory. Their abstract:

Atrophy of the medial temporal lobe (MTL) occurs with aging, resulting in impaired episodic memory. Aerobic fitness is positively correlated with total hippocampal volume, a heavily studied memory-critical region within the MTL. However, research on associations between sedentary behavior and MTL subregion integrity is limited. Here we explore associations between thickness of the MTL and its subregions (namely CA1, CA23DG, fusiform gyrus, subiculum, parahippocampal, perirhinal and entorhinal cortex,), physical activity, and sedentary behavior. We assessed 35 non-demented middle-aged and older adults (25 women, 10 men; 45–75 years) using the International Physical Activity Questionnaire for older adults, which quantifies physical activity levels in MET-equivalent units and asks about the average number of hours spent sitting per day. All participants had high resolution MRI scans performed on a Siemens Allegra 3T MRI scanner, which allows for detailed investigation of the MTL. Controlling for age, total MTL thickness correlated inversely with hours of sitting/day (r = -0.37, p = 0.03). In MTL subregion analysis, parahippocampal (r = -0.45, p = 0.007), entorhinal (r = -0.33, p = 0.05) cortical and subiculum (r = -0.36, p = .04) thicknesses correlated inversely with hours of sitting/day. No significant correlations were observed between physical activity levels and MTL thickness. Though preliminary, our results suggest that more sedentary non-demented individuals have less MTL thickness. Future studies should include longitudinal analyses and explore mechanisms, as well as the efficacy of decreasing sedentary behaviors to reverse this association.

Brain signals predict who we will like in the future.

From Zerubavel et al.:

Significance

When joining a group, we may initially like some individuals more than others. Likewise, certain group members may be particularly drawn to us. Over months of interaction, these attractions inevitably change and typically become reciprocated. This study uses fMRI to predict such changes in liking. Specifically, we measure newly acquainted group members’ reward system responses to images of one another’s faces. We find that T1 neural responses predict whom one will like in the future. More strikingly, we find that others’ T1 neural responses to us predict whom we will like months later, at T2. This brain-based mechanism helps explain how group members’ initially unreciprocated liking sentiments become mutually reciprocated. This study reveals how our brains interdependently shape interpersonal relationships.

Abstract

Why do certain group members end up liking each other more than others? How does affective reciprocity arise in human groups? The prediction of interpersonal sentiment has been a long-standing pursuit in the social sciences. We combined fMRI and longitudinal social network data to test whether newly acquainted group members’ reward-related neural responses to images of one another’s faces predict their future interpersonal sentiment, even many months later. Specifically, we analyze associations between relationship-specific valuation activity and relationship-specific future liking. We found that one’s own future (T2) liking of a particular group member is predicted jointly by actor’s initial (T1) neural valuation of partner and by that partner’s initial (T1) neural valuation of actor. These actor and partner effects exhibited equivalent predictive strength and were robust when statistically controlling for each other, both individuals’ initial liking, and other potential drivers of liking. Behavioral findings indicated that liking was initially unreciprocated at T1 yet became strongly reciprocated by T2. The emergence of affective reciprocity was partly explained by the reciprocal pathways linking dyad members’ T1 neural data both to their own and to each other’s T2 liking outcomes. These findings elucidate interpersonal brain mechanisms that define how we ultimately end up liking particular interaction partners, how group members’ initially idiosyncratic sentiments become reciprocated, and more broadly, how dyads evolve. This study advances a flexible framework for researching the neural foundations of interpersonal sentiments and social relations that—conceptually, methodologically, and statistically—emphasizes group members’ neural interdependence.

You're as old as you feel...

The cliche continues to be backed up by data indicating that it is correct. Marlene Cimons does a piece pointing to recent work on attitude and aging. A well know paradox of old age is that as people's minds and bodies deline, instead of feeling worse about their lives, they feel better. A large internet survey by Chopik et al. of over half a million people showed that, consistently across age groups, people report themselves to feel about 20% younger than their current age. People who go against common negative view about aging to feel positive about aging are less likely to develop dementia. In a study of 4,765 dementia free subjects age 60 or older Levy et al. found that people with the  ε4 variant of the APOE gene (one of the strongest risk factors for dementia) who had positive age beliefs were 50% less likely to develop dementia.

A workshop on music and the brain.

I want to point to this open access article describing an NIH/Kennedy Center workshop on music and the brain, hosted by National Institutes of Health (NIH) Director Francis Collins, soprano Renée Fleming, and Kennedy Center (KC) President Deborah Rutter. Descriptions of the various workshops, in addition to waffling and hot air, include some useful links to basic research articles on music and the brain. Here is a clip from the introduction:

The workshop was organized around the three life stages—childhood, adulthood, and aging. In each session, a panel of 25 experts (listed in Table 1) discussed recent breakthroughs in research and their potential therapeutic applications. Over the course of a day and a half, the panelists recommended basic and applied research that will: (1) increase our understanding of how the brain processes music; (2) lead to scientifically based strategies to enhance normal brain development and function; and (3) result in evidence-based music interventions for brain diseases. In the sections that follow, we will review the discussions from the workshop and highlight the major recommendations that emerged. Finally, we will discuss how funding agencies, scientists, clinicians, and supporters of the arts can work together to catalyze further progress.

The article is worth a read for those (like myself) interested in music and the brain. The workshop on music and the adult brain discusses the effect of musical training on adult brain structure and function. Here are the topics:

“Building”: Music and the Child’s Brain

Music as a Therapeutic Intervention in Children

“Engaging”: Music and the Adult Brain

Music as a Therapeutic Intervention in Adults: Overlapping Circuits Suggest Potential Mechanisms

“Sustaining”: Music and the Aging Brain

Music as a Tool for Restoring Function in the Aging Brain

Risk tolerance is predicted by amygdala-prefrontal cortex connectivity

Hoon et al. show that more nerve connections between our amygdala and the rest of the brain increase our tolerance for risk.

Highlights

•Neural markers for risk tolerance were investigated with multimodal imaging data 

•Risk tolerance correlated with amygdala-medial prefrontal cortex connectivity 

•Risk tolerance correlated with amygdala structure

Summary

Risk tolerance, the degree to which an individual is willing to tolerate risk in order to achieve a greater expected return, influences a variety of financial choices and health behaviors. Here we identify intrinsic neural markers for risk tolerance in a large (n = 108) multimodal imaging dataset of healthy young adults, which includes anatomical and resting-state functional MRI and diffusion tensor imaging. Using a data-driven approach, we found that higher risk tolerance was most strongly associated with greater global functional connectivity (node strength) of and greater gray matter volume in bilateral amygdala. Further, risk tolerance was positively associated with functional connectivity between amygdala and medial prefrontal cortex and negatively associated with structural connectivity between these regions. These findings show how the intrinsic functional and structural architecture of the amygdala, and amygdala-medial prefrontal pathways, which have previously been implicated in anxiety, are linked to individual differences in risk tolerance during economic decision making.

Propagation of economic inequality through reciprocity and reputation.

Interesting work from Hackel and Zaki...an excerpt from their introduction, followed by their abstract:

Reciprocity and reputation are cornerstones of both evolutionary accounts of prosociality and evidence-based policy suggestions for amplifying cooperation on a large scale. For instance, people are more likely to vote, donate blood, and conserve energy when their actions are observable by others.

In studies of reciprocity, participants typically start out with an even distribution of wealth By contrast, the real world features enormous and rising economic inequality. We propose that when initial distributions of wealth are unequal, reciprocity and reputation might exacerbate economic inequality.

One possible mechanism is reward-based reinforcement learning, through which people associate actions with rewards Consider two “givers,” one of whom starts with a $100 endowment and the other of whom starts with a $20 endowment. If each giver shares half of his or her resources, each exhibits equal levels of generosity but provides differing levels of reward value, or raw capital, to beneficiaries. When people experience repeated pairings of a stimulus with reward, they are more likely to return to that stimulus . Similarly, we suggest that rewards build positive affect toward another person—even when those rewards do not reflect the giver’s generosity—and these positive associations can color later choices of people with whom to interact.

The abstract:

Reciprocity and reputation are powerful tools for encouraging cooperation on a broad scale. Here, we highlight a potential side effect of these social phenomena: exacerbating economic inequality. In two novel economic games, we manipulated the amount of money with which participants were endowed and then gave them the opportunity to share resources with others. We found that people reciprocated more toward higher-wealth givers, compared with lower-wealth givers, even when those givers were equally generous. Wealthier givers also achieved better reputations than less wealthy ones and therefore received more investments in a social marketplace. These discrepancies were well described by a formal model of reinforcement learning: Individuals who weighted monetary outcomes, rather than generosity, when learning about interlocutors also most strongly helped wealthier individuals. This work demonstrates that reciprocity and reputation—although globally increasing prosociality—can widen wealth gaps and provides a precise account of how inequality grows through social processes.

Seeing what you feel - unconscious affect drives perception

Siegle et al. provide yet another example of how it is impossible to separate emotions from cognition and perception:

Affective realism, the phenomenon whereby affect is integrated into an individual’s experience of the world, is a normal consequence of how the brain processes sensory information from the external world in the context of sensations from the body. In the present investigation, we provided compelling empirical evidence that affective realism involves changes in visual perception (i.e., affect changes how participants see neutral stimuli). In two studies, we used an interocular suppression technique, continuous flash suppression, to present affective images outside of participants’ conscious awareness. We demonstrated that seen neutral faces are perceived as more smiling when paired with unseen affectively positive stimuli. Study 2 also demonstrated that seen neutral faces are perceived as more scowling when paired with unseen affectively negative stimuli. These findings have implications for real-world situations and challenge beliefs that affect is a distinct psychological phenomenon that can be separated from cognition and perception.

Why exercise alone may not cause weight loss.

Gretchen Reynolds points to work by Lark et al. showing that mice given the opportunity to exercise on a running wheel then are more lazy the rest of the time than mice who don't exercise. Thus the effects of voluntary exercise can be countered by a reduction in nonexercise activity. This may explain why numerous studies in recent years examining exercise and weight loss in both humans and animals have concluded that exercise, by itself, is not an effective way to drop pounds.

How our "I" is like a virtual reality headset.

I pass on some clips from Joshua Rothman's article on the ideas of Metzinger, Blanke and others regarding the actual nature of our experienced selves, ideas that rise from virtual embodiment experiments in which subjects become convinced that they are someone else. The work challenges our understanding of who and what we are.

…reality, as we experience it, might be a mental stage set—a representation of the world, rather than the world itself. Having an O.B.E. (out of body experience) could be like visiting the set at night, when it wasn’t being used…Some internal mental system must function as an invisible, unconscious set dresser, making an itch feel like an itch, coloring the sky blue and the grass green.

It isn’t just that we live inside a model of the external world, Metzinger wrote. We also live inside models of our own bodies, minds, and selves. These “self-models” don’t always reflect reality, and they can be adjusted in illogical ways. They can, for example, portray a self that exists outside of the body—an O.B.E.

Metzinger and Blanke set about hacking the self-model. Along with the cognitive scientists Bigna Lenggenhager and Tej Tadi, they created a virtual-reality system designed to induce O.B.E.-like episodes. In 2005, Metzinger put on a virtual-reality head-mounted display—a headset containing a pair of screens, one for each eye, which together produce the illusion of a 3-D world. Inside, he saw his own body, facing away from him, standing in a room. (It was being filmed by a camera placed six feet behind him.) He watched as Lenggenhager stroked its back. Metzinger could feel the stroking, but the body to which it was happening seemed to be situated in front of him. He felt a strange sensation, as though he were drifting in space, or being stretched between the two bodies. He wanted to jump entirely into the body before him, but couldn’t. He seemed marooned outside of himself. It wasn’t quite an out-of-body experience, but it was proof that, using computer technology, the self-model could easily be manipulated. A new area of research had been created: virtual embodiment.

With a team of various collaborators, Slater and Sanchez-Vives have created many other-body simulations; they show how inhabiting a new virtual body can produce meaningful psychological shifts. In one study, participants are re-embodied as a little girl. Surrounded by a stuffed bear, a rocking horse, and other toys, they watch as their mother sternly demands a cleaner room. Afterward, on psychological tests, they associate themselves with more childlike characteristics. (When I tried it, under the supervision of the V.R. researcher Domna Banakou, I was astonished by my small size, and by the intimidating, Olympian height from which the mother addressed me.) In another, white participants spend around ten minutes in the body of a virtual black person, learning Tai Chi. Afterward, their scores on a test designed to reveal unconscious racial bias shift significantly. “These effects happen fast, and seem to last,” Slater said. A week later, the white participants still had less racist attitudes. (The racial-bias results have been replicated several times in Barcelona, and also by a second team, in London.) Embodied simulations seem to slip beneath the cognitive threshold, affecting the associative, unconscious parts of the mind. “It’s directly experiential,” Slater said. “It’s not ‘I know.’ It’s ‘I am.’ ”

 “I think that, in the human self-model, there are many layers. Some layers are transparent, like your bodily perceptions, which seem absolutely real. You just look”—he gestured toward a chair next to us—“and the chair is there. Others are opaque, like our cognitive layer. When we’re thinking, we know that our thoughts are internal mental constructs, which could be true or false.” As a philosopher, Metzinger’s method has been to see if the transparent can be made opaque. In books such as “Being No One” and “The Ego Tunnel,” he aims to show that aspects of our experience which we take to be real are actually “complex forms of virtual reality” created by our brains.

Imagine that you are sitting in the cockpit of an airplane, surrounded by instruments and controls. It’s a futuristic cockpit, with no windows; where the windshield would be, a computer displays the landscape. Using this cockpit, you can pilot your plane with ease. Still, there are questions you are unable to answer. Exactly what kind of plane are you flying? (It could be a Boeing 777 or an Airbus A380.) How accurate is the landscape on the screen? (Perhaps night-vision software has turned night to day.) When you throttle up the engines, you feel a rumbling and hear a roar. Does this mean the plane is accelerating—or could those effects have been simulated? Both scenarios might be true. You could be using a flight simulator to fly a real plane. This, in Metzinger’s view, is how we live our lives.

The instruments in an airplane cockpit report on pitch, yaw, speed, fuel, altitude, engine status, and so on. Our human instruments report on more complicated variables. They tell us about physical facts: the status of our bodies and limbs. But they also report on mental states: on what we are sensing, feeling, and thinking; on our intentions, knowledge, and memories; on where and who we are. You might wonder who is sitting in the cockpit, controlling everything. Metzinger thinks that no one is sitting there. “We” are the instruments, and our sense of selfhood is the sum of their readouts. On the instrument panel, there is a light with a label that says “Pilot Present.” When the light is on, we are self-conscious; we experience being in the cockpit and monitoring the instruments. It’s easy to assume that, while you’re awake, this light is always on. In fact, it’s frequently off—during daydreams, during much of our mental life, which is largely automatic and unconscious—and the plane still flies.

Two facts about the cockpit are of special importance. The first is that although the cockpit controls the airplane, it is not itself an airplane. It’s only a simulation—a model—of a larger, more complex, and very different machine. The implication of this fact is that the stories we tell about what happens in the cockpit—“I pulled up on the stick”; “I touched my jacket”—are very different from the reality of what is happening to the system as a whole. The second fact, harder to grasp, is that we cannot see the cockpit. Even as we consult its models of the outer and inner worlds, we don’t experience ourselves as doing so; we experience ourselves as simply existing. “You cannot recognize your self-model as a model,” Metzinger writes, in “Being No One.” “It is transparent: you look right through it. You don’t see it. But you see with it.” Our mental models of reality are like V.R. headsets that we don’t know we are wearing. Through them, we experience our own inner lives and have inner sensations that feel as solid as stone. But in truth:

Nobody ever was or had a self. All that ever existed were conscious self-models that could not be recognized as models. . . . You are such a system right now. . . . As you read these sentences, you constantly confuse yourself with the content of the self-model activated by your brain.

Do you know what an ‘illusion of control’ is?” he asked, mischievously. “If people are asked to throw dice, and their task is to throw a high number, they throw the dice harder!” He believes that many experiences of being in control are similarly illusory, including experiences in which we seem to control our own minds. Brain imaging, for example, shows that our thoughts begin before we’re aware of having them. But, Metzinger said, “if a thought crosses the boundary from unconsciousness to consciousness, we feel, ‘I caused this thought.’ ” The sensation of causing our own thoughts is also just another feature of the self-model—a phantom sensation conjured when a readout, labelled “thinking,” switches from “off” to “on.” If you suffer from schizophrenia, this readout may be deactivated inappropriately, and you may feel that someone else is causing your thoughts. “The mind has to explain to itself how it works,” he said, spreading his hands.

Lately, Metzinger has been thinking about his own experience as a meditator. At the center of the meditative experience is the exercise and cultivation of mental autonomy: when the meditator’s mind wanders, he notices and arrests that process, gently returning his mental focus to his breath. “The mind says, ‘I am now re-directing the flashlight of my attention to this,’ ” Metzinger said. “But the thought ‘I am redirecting my mind-wandering’ might itself be another inner story.” He leaned back in his chair and laughed. “It might be that the spiritual endeavor for liberation or detachment can lead to new illusions.”

…you are not the model. You are the whole system—the physical, biological organism in which the self-model is rendered, including its body, its social relationships, and its brain. The model is just a part of that system.” The “I” we experience is smaller than, and different from, the totality of who and what we are.

It turns out that we do, in this sense, possess subtle bodies; we also inhabit subtle selves. While a person exists, he feels that he knows the world and himself directly. In fact, he experiences a model of the world and inhabits a model of himself. These models are maintained by the mind in such a way that their constructed nature is invisible. But it can sometimes be made visible, and then—to a degree—the models can be changed. Something about this discovery is deflating: it turns out that we are less substantial than we thought. Yet it can also be invigorating to understand the constructed, provisional nature of experience. Our perceptions of the world and the self feel real—how could they feel otherwise?—but we can come to understand our own role in the creation of their apparent realness.