It is well known that aging is accompanied by the death of specific cell types that function as sensors of outside signals and that this cell death leads to deficits in our ability to detect these signals. For example, age-associated loss of sensory hair cells and/or spiral ganglia neurons in the inner ear leads to progressive hearing loss, particularly of high frequencies. Similarly, death of photoreceptors in the retina of the eye is a key aspect of the pathogenesis of age-related macular degeneration, the leading cause of vision impairment in individuals older than 60 years of age. Feng et al. now identify an unusual link between age-related loss of a sensory cell type and aberrant sensory processing: During aging, the loss of specialized skin cells called Merkel cells results in alloknesis, the pathological sensation of itch in response to innocuous mechanical stimuli...
The finding that Merkel cells normally protect against mechanical itch is notable because it is initially counterintuitive. Whereas in other sensory modalities (for example, vision and hearing), a reduction in sensory cell number as a result of cell death leads to a detrimental reduction in sensation, here, death of Merkel cells leads to an increase in unwanted sensation; that is, an otherwise nonaversive stimulus is perceived as potentially harmful.
The somatosensory system relays many signals ranging from light touch to pain and itch. Touch is critical to spatial awareness and communication. However, in disease states, innocuous mechanical stimuli can provoke pathologic sensations such as mechanical itch (alloknesis). The molecular and cellular mechanisms that govern this conversion remain unknown. We found that in mice, alloknesis in aging and dry skin is associated with a loss of Merkel cells, the touch receptors in the skin. Targeted genetic deletion of Merkel cells and associated mechanosensitive Piezo2 channels in the skin was sufficient to produce alloknesis. Chemogenetic activation of Merkel cells protected against alloknesis in dry skin. This study reveals a previously unknown function of the cutaneous touch receptors and may provide insight into the development of alloknesis.
Hoban et al. show interaction between the gut microbes and expression of anxiety and fear regulated by the amygdala. Their technical abstract:
The amygdala is a key brain region that is critically involved in the processing and expression of anxiety and fear-related signals. In parallel, a growing number of preclinical and human studies have implicated the microbiome–gut–brain in regulating anxiety and stress-related responses. However, the role of the microbiome in fear-related behaviours is unclear. To this end we investigated the importance of the host microbiome on amygdala-dependent behavioural readouts using the cued fear conditioning paradigm. We also assessed changes in neuronal transcription and post-transcriptional regulation in the amygdala of naive and stimulated germ-free (GF) mice, using a genome-wide transcriptome profiling approach. Our results reveal that GF mice display reduced freezing during the cued memory retention test. Moreover, we demonstrate that under baseline conditions, GF mice display altered transcriptional profile with a marked increase in immediate-early genes (for example, Fos, Egr2, Fosb, Arc) as well as genes implicated in neural activity, synaptic transmission and nervous system development. We also found a predicted interaction between mRNA and specific microRNAs that are differentially regulated in GF mice. Interestingly, colonized GF mice (ex-GF) were behaviourally comparable to conventionally raised (CON) mice. Together, our data demonstrates a unique transcriptional response in GF animals, likely because of already elevated levels of immediate-early gene expression and the potentially underlying neuronal hyperactivity that in turn primes the amygdala for a different transcriptional response. Thus, we demonstrate for what is to our knowledge the first time that the presence of the host microbiome is crucial for the appropriate behavioural response during amygdala-dependent memory retention.
Given the drum beat of daily negative news we all face, it is useful to be open to facts about longer term trends showing improvement in different areas of life (cf. my series of posts - starting on 4/1/18 - on Pinker's new book, "Enlightenment Now.") In this vein I pass on an open source review article from Nature Human Behavior by Diener et al. describing recent research on subjective well-being. The abstract:
The empirical science of subjective well-being, popularly referred to as happiness or satisfaction, has grown enormously in the past decade. In this Review, we selectively highlight and summarize key researched areas that continue to develop. We describe the validity of measures and their potential biases, as well as the scientific methods used in this field. We describe some of the predictors of subjective well-being such as temperament, income and supportive social relationships. Higher subjective well-being has been associated with good health and longevity, better social relationships, work performance and creativity. At the community and societal levels, cultures differ not only in their levels of well-being but also to some extent in the types of subjective well-being they most value. Furthermore, there are both universal and unique predictors of subjective well-being in various societies. National accounts of subjective well-being to help inform policy decisions at the community and societal levels are now being considered and adopted. Finally we discuss the unknowns in the science and needed future research.
Belief in rigid distinctions between the nationalistic ingroup and outgroup has been a motivating force in citizens’ voting behavior, as evident in the United Kingdom’s 2016 EU referendum. We found that individuals with strongly nationalistic attitudes tend to process information in a more categorical manner, even when tested on neutral cognitive tasks that are unrelated to their political beliefs. The relationship between these psychological characteristics and strong nationalistic attitudes was mediated by a tendency to support authoritarian, nationalistic, conservative, and system-justifying ideologies. This suggests flexible cognitive styles are related to less nationalistic identities and attitudes.
Nationalistic identities often play an influential role in citizens’ voting behavior and political engagement. Nationalistic ideologies tend to have firm categories and rules for what belongs to and represents the national culture. In a sample of 332 UK citizens, we tested whether strict categorization of stimuli and rules in objective cognitive tasks would be evident in strongly nationalistic individuals. Using voting behavior and attitudes from the United Kingdom’s 2016 EU referendum, we found that a flexible representation of national identity and culture was linked to cognitive flexibility in the ideologically neutral Wisconsin Card Sorting Test and Remote Associates Test, and to self-reported flexibility under uncertainty. Path analysis revealed that subjective and objective cognitive inflexibility predicted heightened authoritarianism, nationalism, conservatism, and system justification, and these in turn were predictive of support for Brexit and opposition to immigration, the European Union, and free movement of labor. This model accounted for 47.6% of the variance in support for Brexit. Path analysis models were also predictive of participants’ sense of personal attachment to the United Kingdom, signifying that individual differences in cognitive flexibility may contribute toward ideological thinking styles that shape both nationalistic attitudes and personal sense of nationalistic identity. These findings further suggest that emotionally neutral “cold” cognitive information processing—and not just “hot” emotional cognition—may play a key role in ideological behavior and identity.
Kundu et al. have used a new fMRI imaging technique to look at shifts in functional brain organization in subjects ranging from 8 to 46 years old, finding that localized networks characteristic of youth meld into larger and more functionally distinct networks with maturity. The number of blood oxygenation level-dependent (BOLD) components is halved from adolescence to the fifth decade of life, stabilizing in middle adulthood. The regions driving this change are dorsolateral prefrontal cortices, parietal cortex, and cerebellum. More dynamic regions correlate with skills that are works in progress during adolescence - developing a sense of self, monitoring one's performance, and estimating others' intentions.
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.”
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.
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.
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.
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.
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.”
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.
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