Negative Body Image Associated with Changes in the Visual Body Appearance Increases Pain Perception

Changing the visual body appearance by use of as virtual reality system, funny mirror, or binocular glasses has been reported to be helpful in rehabilitation of pain. However, there are interindividual differences in the analgesic effect of changing the visual body image. We hypothesized that a negative body image associated with changing the visual body appearance causes interindividual differences in the analgesic effect although the relationship between the visual body appearance and analgesic effect has not been clarified. We investigated whether a negative body image associated with changes in the visual body appearance increased pain. Twenty-five healthy individuals participated in this study. To evoke a negative body image, we applied the method of rubber hand illusion. We created an “injured rubber hand” to evoke unpleasantness associated with pain, a “hairy rubber hand” to evoke unpleasantness associated with embarrassment, and a “twisted rubber hand” to evoke unpleasantness associated with deviation from the concept of normality. We also created a “normal rubber hand” as a control. The pain threshold was measured while the participant observed the rubber hand using a device that measured pain caused by thermal stimuli. Body ownership experiences were elicited by observation of the injured rubber hand and hairy rubber hand as well as the normal rubber hand. Participants felt more unpleasantness by observing the injured rubber hand and hairy rubber hand than the normal rubber hand and twisted rubber hand (p<0.001). The pain threshold was lower under the injured rubber hand condition than with the other conditions (p<0.001). We conclude that a negative body appearance associated with pain can increase pain sensitivity.     

Does General Motivation Energize Financial Reward-Seeking Behavior? Evidence from an Effort Task

We aimed to predict how hard subjects work for financial rewards from their general trait and state reward-motivation. We specifically asked 1) whether individuals high in general trait “reward responsiveness” work harder 2) whether task-irrelevant cues can make people work harder, by increasing general motivation. Each trial of our task contained a 1 second earning interval in which male subjects earned money for each button press. This was preceded by one of three predictive cues: an erotic picture of a woman, a man, or a geometric figure. We found that individuals high in trait “reward responsiveness” worked harder and earned more, irrespective of the predictive cue. Because female predictive cues are more rewarding, we expected them to increase general motivation in our male subjects and invigorate work, but found a more complex pattern.     

The Route to an Integrative Associative Memory Is Influenced by Emotion

Though the hippocampus typically has been implicated in processes related to associative binding, special types of associations – such as those created by integrative mental imagery – may be supported by processes implemented in other medial temporal-lobe or sensory processing regions. Here, we investigated what neural mechanisms underlie the formation and subsequent retrieval of integrated mental images, and whether those mechanisms differ based on the emotionality of the integration (i.e., whether it contains an emotional item or not). Participants viewed pairs of words while undergoing a functional MRI scan. They were instructed to imagine the two items separately from one another (“non-integrative” study) or as a single, integrated mental image (“integrative” study). They provided ratings of how successful they were at generating vivid images that fit the instructions. They were then given a surprise associative recognition test, also while undergoing an fMRI scan. The cuneus showed parametric correspondence to increasing imagery success selectively during encoding and retrieval of emotional integrations, while the parahippocampal gyri and prefrontal cortices showed parametric correspondence during the encoding and retrieval of non-emotional integrations. Connectivity analysis revealed that selectively during negative integration, left amygdala activity was negatively correlated with frontal and hippocampal activity. These data indicate that individuals utilize two different neural routes for forming and retrieving integrations depending on their emotional content, and they suggest a potentially disruptive role for the amygdala on frontal and medial-temporal regions during negative integration.     

The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics

It has been a long-standing goal in systems biology to find relations between the topological properties and functional features of protein networks. However, most of the focus in network studies has been on highly connected proteins (“hubs”). As a complementary notion, it is possible to define bottlenecks as proteins with a high betweenness centrality (i.e., network nodes that have many “shortest paths” going through them, analogous to major bridges and tunnels on a highway map). Bottlenecks are, in fact, key connector proteins with surprising functional and dynamic properties. In particular, they are more likely to be essential proteins. In fact, in regulatory and other directed networks, betweenness (i.e., “bottleneck-ness”) is a much more significant indicator of essentiality than degree (i.e., “hub-ness”). Furthermore, bottlenecks correspond to the dynamic components of the interaction network—they are significantly less well coexpressed with their neighbors than nonbottlenecks, implying that expression dynamics is wired into the network topology.     

Horizontal Gene Transfer and the History of Life

Microbes acquire DNA from a variety of sources. The last decades, which have seen the development of genome sequencing, have revealed that horizontal gene transfer has been a major evolutionary force that has constantly reshaped genomes throughout evolution. However, because the history of life must ultimately be deduced from gene phylogenies, the lack of methods to account for horizontal gene transfer has thrown into confusion the very concept of the tree of life. As a result, many questions remain open, but emerging methodological developments promise to use information conveyed by horizontal gene transfer that remains unexploited today.The discovery of the existence of prokaryotic microbes dates back more than 300 years. Since then, our picture of our distant microscopic relatives has undergone several revolutions: from being the living “proofs” of the existence of spontaneous generation, they became later the “archaic” representatives of our distant ancestors, to finally be legitimately recognized as exceptionally diverse organisms, keystone to any ecosystem, including the most familiar and the most hostile environments on Earth. Similarly, although they were first seen as elementary and unbreakable bricks of life, they are now seen as genetically composite bodies, heavyweight champions of “gene robbery.” The most recent of these revolutions has indeed been the realization of their unparalleled ability to integrate genetic material coming from more or less evolutionarily distant organisms. This mechanism is called “horizontal gene transfer” as opposed to vertical transmission from mother to daughter cell.     

Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual Categorization

Observers can rapidly perform a variety of visual tasks such as categorizing a scene as open, as outdoor, or as a beach. Although we know that different tasks are typically associated with systematic differences in behavioral responses, to date, little is known about the underlying mechanisms. Here, we implemented a single integrated paradigm that links perceptual processes with categorization processes. Using a large image database of natural scenes, we trained machine-learning classifiers to derive quantitative measures of task-specific perceptual discriminability based on the distance between individual images and different categorization boundaries. We showed that the resulting discriminability measure accurately predicts variations in behavioral responses across categorization tasks and stimulus sets. We further used the model to design an experiment, which challenged previous interpretations of the so-called “superordinate advantage.” Overall, our study suggests that observed differences in behavioral responses across rapid categorization tasks reflect natural variations in perceptual discriminability.     

Epithelial cell plasticity: breaking boundaries and changing landscapes

Epithelial tissues respond to a wide variety of environmental and genotoxic stresses. As an adaptive mechanism, cells can deviate from their natural paths to acquire new identities, both within and across lineages. Under extreme conditions, epithelial tissues can utilize “shape‐shifting” mechanisms whereby they alter their form and function at a tissue‐wide scale. Mounting evidence suggests that in order to acquire these alternate tissue identities, cells follow a core set of “tissue logic” principles based on developmental paradigms. Here, we review the terminology and the concepts that have been put forward to describe cell plasticity. We also provide insights into various cell intrinsic and extrinsic factors, including genetic mutations, inflammation, microbiota, and therapeutic agents that contribute to cell plasticity. Additionally, we discuss recent studies that have sought to decode the “syntax” of plasticity—i.e., the cellular and molecular principles through which cells acquire new identities in both homeostatic and malignant epithelial tissues—and how these processes can be manipulated for developing novel cancer therapeutics.     

Untangling the oxidative cost of reproduction: An analysis in wild banded mongooses

The cost of reproduction plays a central role in evolutionary theory, but the identity of the underlying mechanisms remains a puzzle. Oxidative stress has been hypothesized to be a proximate mechanism that may explain the cost of reproduction. We examine three pathways by which oxidative stress could shape reproduction. The “oxidative cost” hypothesis proposes that reproductive effort generates oxidative stress, while the “oxidative constraint” and “oxidative shielding” hypotheses suggest that mothers mitigate such costs through reducing reproductive effort or by pre‐emptively decreasing damage levels, respectively. We tested these three mechanisms using data from a long‐term food provisioning experiment on wild female banded mongooses (Mungos mungo). Our results show that maternal supplementation did not influence oxidative stress levels, or the production and survival of offspring. However, we found that two of the oxidative mechanisms co‐occur during reproduction. There was evidence of an oxidative challenge associated with reproduction that mothers attempted to mitigate by reducing damage levels during breeding. This mitigation is likely to be of crucial importance, as long‐term offspring survival was negatively impacted by maternal oxidative stress. This study demonstrates the value of longitudinal studies of wild animals in order to highlight the interconnected oxidative mechanisms that shape the cost of reproduction.     

Why is Real-World Visual Object Recognition Hard?

Progress in understanding the brain mechanisms underlying vision requires the construction of computational models that not only emulate the brain's anatomy and physiology, but ultimately match its performance on visual tasks. In recent years, “natural” images have become popular in the study of vision and have been used to show apparently impressive progress in building such models. Here, we challenge the use of uncontrolled “natural” images in guiding that progress. In particular, we show that a simple V1-like model—a neuroscientist's “null” model, which should perform poorly at real-world visual object recognition tasks—outperforms state-of-the-art object recognition systems (biologically inspired and otherwise) on a standard, ostensibly natural image recognition test. As a counterpoint, we designed a “simpler” recognition test to better span the real-world variation in object pose, position, and scale, and we show that this test correctly exposes the inadequacy of the V1-like model. Taken together, these results demonstrate that tests based on uncontrolled natural images can be seriously misleading, potentially guiding progress in the wrong direction. Instead, we reexamine what it means for images to be natural and argue for a renewed focus on the core problem of object recognition—real-world image variation.     

Driver Gaze Behavior Is Different in Normal Curve Driving and when Looking at the Tangent Point

Several steering models in the visual science literature attempt to capture the visual strategies in curve driving. Some of them are based on steering points on the future path (FP), others on tangent points (TP). It is, however, challenging to differentiate between the models’ predictions in real–world contexts. Analysis of optokinetic nystagmus (OKN) parameters is one useful measure, as the different strategies predict measurably different OKN patterns. Here, we directly test this prediction by asking drivers to either a) “drive as they normally would” or b) to “look at the TP”. The design of the experiment is similar to a previous study by Kandil et al., but uses more sophisticated methods of eye–movement analysis. We find that the eye-movement patterns in the “normal” condition are indeed markedly different from the “tp” condition, and consistent with drivers looking at waypoints on the future path. This is the case for both overall fixation distribution, as well as the more informative fixation–by–fixation analysis of OKN. We find that the horizontal gaze speed during OKN corresponds well to the quantitative prediction of the future path models. The results also definitively rule out the alternative explanation that the OKN is produced by an involuntary reflex even while the driver is “trying” to look at the TP. The results are discussed in terms of the sequential organization of curve driving.     

Desire and Dread from the Nucleus Accumbens: Cortical Glutamate and Subcortical GABA Differentially Generate Motivation and Hedonic Impact in the Rat

Background

GABAergic signals to the nucleus accumbens (NAc) shell arise from predominantly subcortical sources whereas glutamatergic signals arise mainly from cortical-related sources. Here we contrasted GABAergic and glutamatergic generation of hedonics versus motivation processes, as a proxy for comparing subcortical and cortical controls of emotion. Local disruptions of either signals in medial shell of NAc generate intense motivated behaviors corresponding to desire and/or dread, along a rostrocaudal gradient. GABA or glutamate disruptions in rostral shell generate appetitive motivation whereas disruptions in caudal shell elicit fearful motivation. However, GABA and glutamate signals in NAc differ in important ways, despite the similarity of their rostrocaudal motivation gradients.

Methodology/Principal Findings

Microinjections of a GABA_A agonist (muscimol), or of a glutamate AMPA antagonist (DNQX) in medial shell of rats were assessed for generation of hedonic “liking” or “disliking” by measuring orofacial affective reactions to sucrose-quinine taste. Motivation generation was independently assessed measuring effects on eating versus natural defensive behaviors. For GABAergic microinjections, we found that the desire-dread motivation gradient was mirrored by an equivalent hedonic gradient that amplified affective taste “liking” (at rostral sites) versus “disliking” (at caudal sites). However, manipulation of glutamatergic signals completely failed to alter pleasure-displeasure reactions to sensory hedonic impact, despite producing a strong rostrocaudal gradient of motivation.

Conclusions/Significance

We conclude that the nucleus accumbens contains two functional affective keyboards for amino-acid signals: a motivation-generating keyboard and a hedonic-generating keyboard. Corticolimbic glutamate signals and subcortical GABA signals equivalently engage the motivation keyboard to generate desire and-or dread. Only subcortical GABA signals additionally engage the hedonic keyboard to amplify affective “liking” and “disliking” reactions. We thus suggest that top-down cortical glutamate signals powerfully regulate motivation components, but are relatively unable to penetrate core hedonic components of emotion. That may carry implications of limits to therapeutic regulation of pathological emotions.     

Temperament and Impulsivity Predictors of Smoking Cessation Outcomes

Aims

Temperament and impulsivity are powerful predictors of addiction treatment outcomes. However, a comprehensive assessment of these features has not been examined in relation to smoking cessation outcomes.

Methods

Naturalistic prospective study. Treatment-seeking smokers (n = 140) were recruited as they engaged in an occupational health clinic providing smoking cessation treatment between 2009 and 2013. Participants were assessed at baseline with measures of temperament (Temperament and Character Inventory), trait impulsivity (Barratt Impulsivity Scale), and cognitive impulsivity (Go/No Go, Delay Discounting and Iowa Gambling Task). The outcome measure was treatment status, coded as “dropout” versus “relapse” versus “abstinence” at 3, 6, and 12 months endpoints. Participants were telephonically contacted and reminded of follow-up face to face assessments at each endpoint. The participants that failed to answer the phone calls or self-reported discontinuation of treatment and failed to attend the upcoming follow-up session were coded as dropouts. The participants that self-reported continuing treatment, and successfully attended the upcoming follow-up session were coded as either “relapse” or “abstinence”, based on the results of smoking behavior self-reports cross-validated with co-oximetry hemoglobin levels. Multinomial regression models were conducted to test whether temperament and impulsivity measures predicted dropout and relapse relative to abstinence outcomes.

Results

Higher scores on temperament dimensions of novelty seeking and reward dependence predicted poorer retention across endpoints, whereas only higher scores on persistence predicted greater relapse. Higher scores on the trait dimension of non-planning impulsivity but not performance on cognitive impulsivity predicted poorer retention. Higher non-planning impulsivity and poorer performance in the Iowa Gambling Task predicted greater relapse at 3 and 6 months and 6 months respectively.

Conclusion

Temperament measures, and specifically novelty seeking and reward dependence, predict smoking cessation treatment retention, whereas persistence, non-planning impulsivity and poor decision-making predict smoking relapse.     

The Natural History of Biocatalytic Mechanisms

Phylogenomic analysis of the occurrence and abundance of protein domains in proteomes has recently showed that the α/β architecture is probably the oldest fold design. This holds important implications for the origins of biochemistry. Here we explore structure-function relationships addressing the use of chemical mechanisms by ancestral enzymes. We test the hypothesis that the oldest folds used the most mechanisms. We start by tracing biocatalytic mechanisms operating in metabolic enzymes along a phylogenetic timeline of the first appearance of homologous superfamilies of protein domain structures from CATH. A total of 335 enzyme reactions were retrieved from MACiE and were mapped over fold age. We define a mechanistic step type as one of the 51 mechanistic annotations given in MACiE, and each step of each of the 335 mechanisms was described using one or more of these annotations. We find that the first two folds, the P-loop containing nucleotide triphosphate hydrolase and the NAD(P)-binding Rossmann-like homologous superfamilies, were α/β architectures responsible for introducing 35% (18/51) of the known mechanistic step types. We find that these two oldest structures in the phylogenomic analysis of protein domains introduced many mechanistic step types that were later combinatorially spread in catalytic history. The most common mechanistic step types included fundamental building blocks of enzyme chemistry: “Proton transfer,” “Bimolecular nucleophilic addition,” “Bimolecular nucleophilic substitution,” and “Unimolecular elimination by the conjugate base.” They were associated with the most ancestral fold structure typical of P-loop containing nucleotide triphosphate hydrolases. Over half of the mechanistic step types were introduced in the evolutionary timeline before the appearance of structures specific to diversified organisms, during a period of architectural diversification. The other half unfolded gradually after organismal diversification and during a period that spanned ∼2 billion years of evolutionary history.     

Distinct Dynamin-dependent and -independent Mechanisms Target Structurally Homologous Dopamine Receptors to Different Endocytic Membranes

D1 and D2 dopamine receptors are structurally homologous G protein–coupled receptors that serve distinct physiological functions both in neurons and nonneural cell types. We have observed that these receptors are selectively endocytosed in HEK293 cells by distinct dynamin-dependent and -independent mechanisms. Although these endocytic mechanisms operate with similarly rapid kinetics, they differ in their regulation by agonist and deliver D1 and D2 receptors specifically to different primary endocytic vesicles. After this segregation into different endocytic membranes, both D1 and D2 receptors recycle to the plasma membrane. Similar results are observed in Neuro2A neuroblastoma cells coexpressing both receptors at high levels. These findings establish that “classical” dynamin-dependent and “alternative” dynamin-independent endocytic mechanisms differ in their physiological regulation, sort structurally homologous signaling receptors in the plasma membrane, and mediate distinct early endocytic pathways leading to recycling endosomes. Our results also refute the previous hypothesis that dynamin-independent endocytosis targets G protein–coupled receptors selectively to lysosomes, and they suggest a new role of endocytic sorting mechanisms in physically segregating structurally homologous signaling receptors at the cell surface.     

Contrasting roles of dynamics in protein allostery: NMR and structural studies of CheY and the third PDZ domain from PSD-95

Allosteric regulation is a ubiquitous phenomenon exploited in biological processes to control cells in a myriad of ways. It is also of emerging interest in the design of functional proteins and therapeutics. Even though allostery was proposed over 50 years ago and has been studied intensively from a structural perspective, many key details of allosteric mechanisms remain mysterious. Over the last decade significant attention has been paid to the “dynamic component” of allostery, as opposed to the analysis of rigid structures. Nuclear magnetic resonance spectroscopy and its ability to detect conformationally dynamic processes at atomic resolution have played an important role in expanding our understanding of allosteric mechanisms and opening up new questions. This article focuses on work that highlights how protein dynamics can factor into allosteric processes in distinct ways. Two cases are contrasted. The first considers the “traditionally allosteric” protein CheY, which undergoes a conformational change as a key element of its allostery. The second considers the more rarely observed “dynamic allostery” in a PDZ domain, in which allosteric behavior arises from changes in internal structural dynamics. Interestingly, the dynamic processes in these two contrasting examples occur on different timescales. In the case of the PDZ domain, subsequent experimental and computational work is reviewed to reveal a more complete picture of this interesting case of allostery.     

The Effectiveness of a ‘Train the Trainer’ Model of Resuscitation Education for Rural Peripheral Hospital Doctors in Sri Lanka

Background

Sri Lankan rural doctors based in isolated peripheral hospitals routinely resuscitate critically ill patients but have difficulty accessing training. We tested a train-the-trainer model that could be utilised in isolated rural hospitals.

Methods

Eight selected rural hospital non-specialist doctors attended a 2-day instructor course. These “trained trainers” educated their colleagues in advanced cardiac life support at peripheral hospital workshops and we tested their students in resuscitation knowledge and skills pre and post training, and at 6- and 12-weeks. Knowledge was assessed through 30 multiple choice questions (MCQ), and resuscitation skills were assessed by performance in a video recorded simulated scenario of a cardiac arrest using a Resuci Anne Skill Trainer mannequin.

Results/Discussion/Conclusion

Fifty seven doctors were trained. Pre and post training assessment was possible in 51 participants, and 6-week and 12-week follow up was possible for 43, and 38 participants respectively. Mean MCQ scores significantly improved over time (p<0.001), and a significant improvement was noted in “average ventilation volume”, “compression count”, and “compressions with no error”, “adequate depth”, “average depth”, and “compression rate” (p<0.01). The proportion of participants with compression depth ≥40mm increased post intervention (p<0.05) and at 12-week follow up (p<0.05), and proportion of ventilation volumes between 400-1000mls increased post intervention (p<0.001). A significant increase in the proportion of participants who “checked for responsiveness”, “opened the airway”, “performed a breathing check”, who used the “correct compression ratio”, and who used an “appropriate facemask technique” was also noted (p<0.001). A train-the-trainer model of resuscitation education was effective in improving resuscitation knowledge and skills in Sri Lankan rural peripheral hospital doctors. Improvement was sustained to 12 weeks for most components of resuscitation knowledge and skills. Further research is needed to identify which components of training are most effective in leading to sustained improvement in resuscitation.     

Good Exemplars of Natural Scene Categories Elicit Clearer Patterns than Bad Exemplars but Not Greater BOLD Activity

Within the range of images that we might categorize as a “beach”, for example, some will be more representative of that category than others. Here we first confirmed that humans could categorize “good” exemplars better than “bad” exemplars of six scene categories and then explored whether brain regions previously implicated in natural scene categorization showed a similar sensitivity to how well an image exemplifies a category. In a behavioral experiment participants were more accurate and faster at categorizing good than bad exemplars of natural scenes. In an fMRI experiment participants passively viewed blocks of good or bad exemplars from the same six categories. A multi-voxel pattern classifier trained to discriminate among category blocks showed higher decoding accuracy for good than bad exemplars in the PPA, RSC and V1. This difference in decoding accuracy cannot be explained by differences in overall BOLD signal, as average BOLD activity was either equivalent or higher for bad than good scenes in these areas. These results provide further evidence that V1, RSC and the PPA not only contain information relevant for natural scene categorization, but their activity patterns mirror the fundamentally graded nature of human categories. Analysis of the image statistics of our good and bad exemplars shows that variability in low-level features and image structure is higher among bad than good exemplars. A simulation of our neuroimaging experiment suggests that such a difference in variance could account for the observed differences in decoding accuracy. These results are consistent with both low-level models of scene categorization and models that build categories around a prototype.     

Creativity as an antidote to research becoming too predictable

In this commentary, Sonne‐Hansen and colleagues argue that research leaders and organizations should encourage more “theory‐guessing” by budding young scientists, rather than incentivizing safe mainstream research. Subject Categories: History & Philosophy of Science, Science Policy & Publishing

Most living things do not like extreme heat. Case in point—in 2021, French winemakers recorded the smallest harvest since 1957 due to rising temperatures. Unlike the grapes that give birth to dry whites and luscious reds, some organisms flourish in extremely hot environments, however. In the late 1960s, Thomas Brock, a microbiologist from Cleveland, and his undergraduate student Hudson Freeze conducted research in Yellowstone National Park. What drew their interest was that some organisms seem to thrive in the hot springs sprinkled throughout the park. From a sample of pink bacteria collected from Mushroom Spring, Brock and his student isolated a prokaryotic organism thriving at 70°C, which they named Thermus aquaticus—after the Greek word for “hot” and the Latin for “water.” The ability of an enzyme (DNA polymerase) from Thermus aquaticus to tolerate high temperatures would later spur the invention of the polymerase chain reaction or PCR, which won biochemist Kary Mullis a share of the 1993 Nobel Prize in Chemistry and revolutionized biomedicine.When it was published in the Journal of Bacteriology, the work by Brock and Freeze went largely undetected. It generated a few citations but did not manage to attract the attention of the wider community of biologists (Bhattacharya & Packalen, 2020). Of course, this is not uncommon for novel findings—their true value may remain unknown for a while, even if the work later spurs new ideas and scientific breakthroughs. Precisely, because it constitutes a venture into the unknown, pursuing novel ideas requires a special set of circumstances. Without the National Science Foundation''s financial support and without Brock being able to spend a decade exploring the hot springs of Yellowstone National Park, satisfying his curiosity about things that thrive in extreme heat (but undoubtedly offending his nose in the process—those thermal pools can be quite pungent), the world likely would have had to wait longer for the advent of PCR.Our core argument is that the conditions that allow and encourage scientists to engage in the relentless, creative exploration of the unknown are becoming harder and harder to find. There are several reasons for this. For one, finding new ideas appears increasingly difficult. Data from the United States, for instance, suggest that research productivity (defined as ratio of the output of ideas to the inputs used to make them) in a number of fields, including medical research, is declining over time. To offset the difficulty in finding new ideas, the United States would have to double its research effort every 13 years (Bloom et al, 2020).One of the consequences of this increase in research activity is that the number of papers published each year has increased over time (Chu & Evans, 2021). This growth has some undesirable side effects. Scientists focus their attention on work that is already well‐cited rather than on new ideas or on ideas on the fringes of the scientific mainstream (Chu & Evans, 2021). Sifting through a deluge of ideas—published in an actual Mount Kilimanjaro of papers (Van Noorden et al, 2014)—to find a nugget of wisdom is hard. This leads to a calcification of the intellectual structure of a field, slowing down progress over time.Funding agencies further exacerbate this trend. There is a tendency to minimize risk—it has become the norm that grant proposals have to already provide substantial amounts of data supporting the proposed theories/hypotheses (incidentally, something that Thomas Brock would not have been able to do)—and to reward work on topics that are more established. As recently as the 1990s, however, research that explored more current ideas was not at a disadvantage when it came to funding (Packalen & Bhattacharya, 2020). Going back to these “old ways” of maintaining a balance between funding work that builds on more established ideas and work that builds on more recent advances may be something that the biomedical sciences could aspire to. Small steps are being undertaken. For instance, some foundations in Denmark are now providing opportunities for (modest) funding of applicants whose ideas would likely get shunned by the traditional funding schemes.As obtaining external funding is the lifeblood for many research programs, investigators are responding to these pressures by “playing it safe,” pursuing ideas that, from the outset, are likely to be publishable to ensure a constant stream of papers. Long gone are the days that biologists could explore the hot springs of Yellowstone National Park without knowing what all that exploring would amount to (other than a nice tan). A journey into the exploration of the unknown has been replaced with a ticket on the Shinkansen “bullet train”—“destination: known” and always on time.Contemporary academic training practices have not been able to fight back these developments. Quite the contrary—one of the consequences of the “pressure to produce” is that budding researchers are often recruited onto preexisting projects with already defined milestones and deliverables, all the while having to develop a range of other skills. Naturally, this leaves little room and time for engaging in more exploratory aspects of the scientific process. The result is that we are turning the next generation of scientists into excellent experimentalists and “research managers,” rather than into bold scientific thinkers.We are at a point at which a systematic focus on training and injecting creativity into the research process in the life sciences is imperative. When hearing the word “creativity,” many people think of the tortured artist, toiling away in isolation in a village in the south of France (but who would not want a sip of a French Cabernet Sauvignon at the end of a hard day''s work—before it runs out). As enticing as this image of radiant colors and crystalline light might be, it is by no means the sole context in which creativity can flourish. Creativity is defined as the generation of ideas that are new and have potential value by addressing a problem or capitalizing on an opportunity. There is no mention of artistic endeavors in this definition! In fact, creativity is fundamental to the human condition and, as such, can be found anywhere, anytime, given the right circumstances.Creativity may be most pressingly needed during the early stages of the knowledge production process—when we have to make what physicist Richard Feynman has called “educated guesses” as to how the world may work. This is the opaquer part of the scientific process; the part that benefits from the use of intuition and of a language that is permissible of it—what Itai Yanai and Martin Lercher refer to as night science language (Yanai & Lercher, 2020; check out also their podcast series entitled, “Night Science”). While the part of the process that deals with testing existing ideas is highly visible and more easily describable, the guessing, theory‐generating part often gets far less systematic attention. Yet, it is the part of the scientific process that is becoming ever more important. We are not so much in need of more data, but of educated guesses (i.e., a theory) about what to look for in the first place. This call for ideas is echoed by Paul Nurse, quoting the famous words of the late biologist Sydney Brenner, “we are drowning in a sea of data and starving for knowledge” (Nurse, 2021).To understand the value of creativity for making educated guesses, it is helpful to dissect it into its components. According to Teresa Amabile, one of the pioneers of the study of creativity, there are three components to creativity—domain expertise, intrinsic motivation, and creativity‐relevant skills (Amabile, 1996). To put it simply: creativity flourishes when people have the wit (knowledge of the domain), the will (intrinsic motivation), and the necessary creative tools to tackle interesting and challenging problems (Fig 1).Open in a separate windowFigure 1Three components of creativityDomain expertise refers to a high level of domain‐specific knowledge acquired though experience. Without expertise, it is impossible to know where on the scientific frontier to look for new and interesting problems. However, there is a downside to becoming an expert. The more we know about a domain and the longer we have studied it, the more we lose flexibility in seeing new problems and devising novel solutions to them (Dane, 2010). Edward Tufte, for instance, describes how experts are likely to glance past unexpected findings in their datasets, whereas outsiders are more likely to pay attention to these surprises, as they see the world through what he calls “vacation eyes” (Tufte, 2020). While the loss of flexibility may not be of immediate concern to budding scientists, the benefits of learning ever more about the very same domain start to evaporate rather quickly over one''s career. Luckily, there is an antidote—investing in becoming well‐versed in new and different domains, that is, developing knowledge breadth rather than (further) depth. Research suggests that there are immediate benefits from knowledge breadth for creativity—even scientists just at the beginning of their academic journey should benefit from developing expertise in additional domains (Mannucci & Yong, 2018).How can we accomplish this? One strategy is to allow and encourage early‐stage scientists to immerse themselves in analogous problems domains and the solutions they may inspire. An example might serve to illustrate this principle: Some years ago, the already mentioned Shinkansen “bullet train” needed redesign. The train''s speed created a sonic boom that was heard for hundreds of meters when exiting tunnels. So, a group of engineers was charged with making the train quieter. One of the lead engineers, Eiji Nakatsu, was a bird watcher. He realized that birds diving into water to catch pray face the same challenge as the train trying to cut through air while going through a tunnel. The new design of the train''s front was based on the shape of the Kingfisher''s beak—a bird diving at high speed from one medium (air) into another (water) with barely a splash. To emulate Eiji Nakatsu, it will be necessary to allow scientists to not only spend time studying topics other than the ones they are actively investigating, but also to allow them to join research collaborations with scientists from other domains and even disciplines investigating analogous problems.Creativity requires a certain type of motivation—intrinsic motivation. People are intrinsically motivated to the extent that they derive pleasure from the work itself and from the opportunity to acquire new skills. Extrinsic motivation is just the opposite—it is the drive that comes from incentives, such as financial compensation and recognition. The reason why intrinsic motivation is so important to the creative process is that it provides perseverance—in the face of setbacks, obstacles, and naysayers. Intrinsic motivation is largely a function of the nature of the work—how challenging it is and how much autonomy it affords. Whenever we have the freedom to explore new lines of inquiry, to satisfy our curiosity, and, perhaps most importantly, to make mistakes, intrinsic motivation ensues. However, the knowledge production process that has become dominant in the life sciences is antithetical to budding scientists experiencing autonomy. Predefined (externally funded) research projects that are too rigidly managed (be it by funders or by principal investigators) with their milestones and deliverables offer little room to exercise autonomy.If we want research to flourish, it will be imperative for us to take responsibility and rethink the knowledge production process in our laboratories to allow for the occasional detours, setbacks, and dead ends. Case in point—Richard Feynman, who won the Nobel Prize in Physics for his contributions to quantum electrodynamics, developed his ideas based on an observation that many would consider a major intellectual detour—a cafeteria worker throwing a plate into the air. Feynman observed that the “Cornell” logo on the plate was going around much faster than the plate''s wobble. Armed with this observation and allowed the freedom to explore the dynamics of the motion of the plate, he developed the basis for the Feynman diagrams (Feynman et al, 1985). Naturally, this more autonomous and playful approach may decrease the efficiency of the knowledge production process. However, efficiency is not the primary criterion by which to evaluate research quality. The novelty and utility of our ideas should be the primary criteria. Research leaders may thus want to embrace the values of autonomy and novelty more courageously and embolden early‐stage researchers to do just the same. Similarly, academic institutions need to take a good, hard look at themselves, increasing the “breathing space and time” for scientist to engage in exploration of new ideas and research avenues.The final component contributing to our creativity is a set of creative skills that allow people to take greater advantage of their drive and of what they know. One skill that is imperative here is the ability to tolerate uncertainty. The uncertainty of not knowing, of taking guesses in the absence of a firmly established knowledge base, and of trying out things without knowing exactly what the outcome will be. The systems biologist Uri Alon refers to this as staying in the “research cloud,” highlighting the value of transitioning from the “known” to the “unknown” (i.e., the research cloud) and temporarily residing in this state of uncertainty despite the discomfort and frustration that are bound to arise (Alon, 2013). The notion of the “research cloud” may seem to conflict with the prevailing scientific culture, in which there is little room for speculations or intuitions. To combat this, we need to re‐imagine the ways in which research leaders interact with their teams, so as to encourage budding scientists to become more comfortable stepping outside the scientific path they learned as students. Case in point—critical thinking is highly priced in the training of university students. However, the inquisitive and evaluative processes that critical analysis relies upon can be antithetical to the generative processes required for creativity—it is difficult to develop new insights while at the same time having to defend them from others'' critical examination. This calls for supervisors and mentors to create what we call “creative oases”—spaces in which critical analysis is dispensed with and risk‐taking and speculation are encouraged.Another lesson from creativity research is that it is impacted heavily by the work environment in which people operate. Creative teams thrive in high‐trust environments, and whenever their members practice a “yes and” rather than a “no because” approach that encourages young researchers to engage and contribute toward new solutions to long‐standing scientific questions. Thus, it is crucial that administrative and research leaders are engaged in building a supportive and inclusive culture. To illustrate—at four biomedical research centers at the University of Copenhagen, we held in autumn 2021 a four‐session workshop for research group leaders on how to nurture a culture that fosters creativity. The sessions focused on how to guide teams through the different phases of the creative process, and introduced tools for divergent and convergent thinking. The underlying principle was that creativity thrives when leaders build an environment that allows the team to capitalize on the collective knowledge of individual members—an environment built on the principles of diversity of thought, autonomy, and a high degree of psychological safety (e.g., deferring judgment in order to promote idea sharing and interpersonal risk‐taking).In conclusion, we believe that research organizations should not dwell too much on the structural barriers to creativity (funding agencies and politicians need to dismantle these barriers) but rather take action to encourage more “theory‐guessing” and nurture the ability for budding scientist to find delight in staying in the “research cloud”—at least for some time. Also, research communities and academic institutions should take greater responsibility for embracing a truly team‐based approach to creativity (rather than the “lone genius” model), in which scientists are granted the freedom to take the occasional intellectual detour or flight of fancy—without repercussions or fear of failure. These efforts will be needed if we are to make lasting changes to the way in which we engage the scientific process and venture into the unknown in the pursuit of transformational research.     

When Do Short-Wave Cones Signal Blue or Red? A Solution Introducing the Concept of Primary and Secondary Cone Outputs

A recent paper by Oh and Sakata investigates the “incompletely solved mystery” of how the three cone responses map onto perceived hue, and particularly the S cone’s well-known problematic contribution to blueness and redness. Citing previous workers, they argue the twentieth century traditional multistage model does not satisfactorily account for color appearance. In their experiment, increasing S cone excitation with shortening wavelength from about 480–460 nm increased perceived blueness up to the unique Blue point at 470 nm, when (a) it began decreasing and (b) redness perception began increasing. The authors asked, What mechanism can be responsible for such functions? I demonstrate a solution. First, it is shown the problem does not lie in the traditional opponent color chromatic responses yellow-blue, red-green (y-b, r-g, which accurately predict the above functions), but in the traditional multistage model of mapping cone responses to chromatic response functions. Arguably, this is due to the S cone’s hypothetically signaling both blueness and redness by the same mechanism rather than by different, independent, mechanisms. Hence a new distinction or mechanism is proposed for a more accurate model, that introduces the new terms primary and secondary cone outputs. However, this distinction requires that the cones S, M, L each directly produce one of the three spectral chromatic responses b, g, y. Such a model was recently published, based on extremely high correlation of SML cone responsivities with the three spectral (bgy) chromatic responses. This model encodes the former directly onto the latter one-to-one as cone primary outputs, whilst S and L cones have a further or secondary function where each produces one of the two spectral lobes of r chromatic response. The proposed distinction between primary and secondary cone outputs is a new concept and useful tool in detailing cone outputs to chromatic channels, and provides a solution to the above “incompletely solved mystery.” Thus the S cone has a primary output producing the total b chromatic response and a secondary output that shares with the L cone the production of r chromatic response, thus aligning with Oh and Sokata’s results. The model similarly maps L cone to yellowness as primary output and to redness as secondary output.     

Distributed representations accelerate evolution of adaptive behaviours

Animals with rudimentary innate abilities require substantial learning to transform those abilities into useful skills, where a skill can be considered as a set of sensory–motor associations. Using linear neural network models, it is proved that if skills are stored as distributed representations, then within-lifetime learning of part of a skill can induce automatic learning of the remaining parts of that skill. More importantly, it is shown that this “free-lunch” learning (FLL) is responsible for accelerated evolution of skills, when compared with networks which either 1) cannot benefit from FLL or 2) cannot learn. Specifically, it is shown that FLL accelerates the appearance of adaptive behaviour, both in its innate form and as FLL-induced behaviour, and that FLL can accelerate the rate at which learned behaviours become innate.