A Fundamental Trade-off in Covalent Switching and Its Circumvention by Enzyme Bifunctionality in Glucose Homeostasis

Covalent modification provides a mechanism for modulating molecular state and regulating physiology. A cycle of competing enzymes that add and remove a single modification can act as a molecular switch between “on” and “off” and has been widely studied as a core motif in systems biology. Here, we exploit the recently developed “linear framework” for time scale separation to determine the general principles of such switches. These methods are not limited to Michaelis-Menten assumptions, and our conclusions hold for enzymes whose mechanisms may be arbitrarily complicated. We show that switching efficiency improves with increasing irreversibility of the enzymes and that the on/off transition occurs when the ratio of enzyme levels reaches a value that depends only on the rate constants. Fluctuations in enzyme levels, which habitually occur due to cellular heterogeneity, can cause flipping back and forth between on and off, leading to incoherent mosaic behavior in tissues, that worsens as switching becomes sharper. This trade-off can be circumvented if enzyme levels are correlated. In particular, if the competing catalytic domains are on the same protein but do not influence each other, the resulting bifunctional enzyme can switch sharply while remaining coherent. In the mammalian liver, the switch between glycolysis and gluconeogenesis is regulated by the bifunctional 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase (PFK-2/FBPase-2). We suggest that bifunctionality of PFK-2/FBPase-2 complements the metabolic zonation of the liver by ensuring coherent switching in response to insulin and glucagon.     

Applying an Attentional Set to Perceived and Remembered Features

Previous research has examined our ability to attend selectively to particular features of perceptual objects, as well as our ability to switch from attending to one type of feature to another. This is usually done in the context of anticipatory attentional-set control, comparing the neural mechanisms involved as participants prepare to attend to the same stimulus feature as on the previous trial (“task-stay” trials) with those required as participants prepare to attend to a different stimulus feature to that previously attended (“task-switch” trials). We wanted to establish how participants maintain or switch attentional set retrospectively, as they attend to features of objects held in visual short-term memory (VSTM). We found that switching, relative to maintaining attentional set retrospectively, was associated with a performance cost, which can be reduced over time. This control process was mirrored by a large parietal and frontal amplitude difference in the event-related brain potentials (ERPs) and significant differences in global field power (GFP) between switch and stay trials. However, when taking into account the switch/stay GFP differences, thereby controlling for this difference in amplitude, we could not distinguish these trial types topographically. By contrast, we found clear topographic differences between preparing an anticipatory feature-based attentional set versus applying it retrospectively within VSTM. These complementary topographical and amplitude analyses suggested that anticipatory and retrospective set control recruited a qualitatively different configuration of underlying neural generators. In contrast, switch/stay differences were largely quantitative, with them differing primarily in terms of amplitude rather than topography.     

Modeling spatial–temporal operations with context-dependent associative memories

We organize our behavior and store structured information with many procedures that require the coding of spatial and temporal order in specific neural modules. In the simplest cases, spatial and temporal relations are condensed in prepositions like “below” and “above”, “behind” and “in front of”, or “before” and “after”, etc. Neural operators lie beneath these words, sharing some similarities with logical gates that compute spatial and temporal asymmetric relations. We show how these operators can be modeled by means of neural matrix memories acting on Kronecker tensor products of vectors. The complexity of these memories is further enhanced by their ability to store episodes unfolding in space and time. How does the brain scale up from the raw plasticity of contingent episodic memories to the apparent stable connectivity of large neural networks? We clarify this transition by analyzing a model that flexibly codes episodic spatial and temporal structures into contextual markers capable of linking different memory modules.     

A mathematical model for neutrophil gradient sensing and polarization

Directed cell migration in response to chemical cues, also known as chemotaxis, is an important physiological process involved in wound healing, foraging, and the immune response. Cell migration requires the simultaneous formation of actin polymers at the leading edge and actomyosin complexes at the sides and back of the cell. An unresolved question in eukaryotic chemotaxis is how the same chemoattractant signal determines both the cell's front and back. Recent experimental studies have begun to reveal the biochemical mechanisms necessary for this polarized cellular response. We propose a mathematical model of neutrophil gradient sensing and polarization based on experimentally characterized biochemical mechanisms. The model demonstrates that the known dynamics for Rho GTPase and phosphatidylinositol-3-kinase (PI3K) activation are sufficient for both gradient sensing and polarization. In particular, the model demonstrates that these mechanisms can correctly localize the “front” and “rear” pathways in response to both uniform concentrations and gradients of chemical attractants, including in actin-inhibited cells. Furthermore, the model predictions are robust to the values of many parameters. A key result of the model is the proposed coincidence circuit involving PI3K and Ras that obviates the need for the “global inhibitors” proposed, though never experimentally verified, in many previous mathematical models of eukaryotic chemotaxis. Finally, experiments are proposed to (in)validate this model and further our understanding of neutrophil chemotaxis.     

Discrimination of Complex Human Behavior by Pigeons (Columba livia) and Humans

The cognitive and neural mechanisms for recognizing and categorizing behavior are not well understood in non-human animals. In the current experiments, pigeons and humans learned to categorize two non-repeating, complex human behaviors (“martial arts” vs. “Indian dance”). Using multiple video exemplars of a digital human model, pigeons discriminated these behaviors in a go/no-go task and humans in a choice task. Experiment 1 found that pigeons already experienced with discriminating the locomotive actions of digital animals acquired the discrimination more rapidly when action information was available than when only pose information was available. Experiments 2 and 3 found this same dynamic superiority effect with naïve pigeons and human participants. Both species used the same combination of immediately available static pose information and more slowly perceived dynamic action cues to discriminate the behavioral categories. Theories based on generalized visual mechanisms, as opposed to embodied, species-specific action networks, offer a parsimonious account of how these different animals recognize behavior across and within species.     

On the proposed energy switch in photosynthesis

This paper analyzes the “energy switch” that has often been proposed to direct quanta absorbed by a given photosynthetic unit alternately to the site of one and then the other primary reaction. Such a device is essential to the Franck-Rosenberg theory, but not to the Duysens-Witt-Kok (DWK) model, which needs to assume only that the reactions occur in series. If there is no energy switch, an incident quantum absorbed at any time by any particular pigment molecule stands a chance of ending up in the reactive site of either primary reaction. The “separate packages” model is a special case of this general picture. Without an energy switch, a series model requires a storage device to insure that a quantum will not be wasted if it arrives at the site of one reaction while the photosynthetic unit is set up to perform the other. Such a storage device can be appended to the DWK model. Alternatively, this model can be augmented by an energy switch. This gives what is commonly known as the “spillover model,” a confusing name which we suggest be abandoned. As a clear-cut-though perhaps technically unfeasible-test of the energy switch hypothesis, we imagine a quantum injector, a hypothetical source of flashing light which delivers a single quantum to every photosynthetic unit with each flash. We aim this useful figment at an (equally hypothetical) photosynthetic system all of whose units are set up to perform the same primary reaction. If there is an energy switch, we can now prepare a “synchronous” photosynthetic apparatus in which each photosynthetic unit is undergoing the same reaction at the same time.     

Long-Stay Patients in Canadian Mental Hospitals, 1955-1963

Changes in the number and characteristics of patients in Canadian mental hospitals during 1955-1963 were studied in order to assess the future need for long-term hospital care.Despite marked increases in the number of first admissions and readmissions, the average number of patients in hospital decreased 6% from 49,537 in 1955 to 46,498 in 1963.Patients who were “long stay” in 1955 continued to leave hospital at the same rate during the years 1960-1963 as during 1955-1959. No “hard core” of long-stay patients with reduced potential for discharge seemed to have formed by 1963.Since 1955 the number of “admissions” remaining continuously hospitalized has progressively decreased for the elderly and for patients with psychoses. No build-up of new long-stay patients from patients with repeated short admissions was evident.The estimate of the Royal Commission on Health Services that the ratio of patients in mental hospitals could be reduced from 3.0 per 1000 in 1961 to 1.5 per 1000 by 1971 seems feasible.     

A Model for Responses to Activation by Axodendritic Synapses

A simple mathematical model of synaptic activation shows that the response to synaptic activation depends inversely on the size of the subsynaptic process. This provides a theoretical foundation for: the relationship between excitability and cell size; a possible source of plasticity in nerve cell behavior; and the hypothesis that postsynaptic responses to activation at axodendritic synapses are of large amplitude. The last-mentioned idea provides for flexible nonlinear interaction in dendritic regions because the diminution of postsynaptic potentials (PSPs) by prior potential becomes significant at high levels of depolarization. Digital-computer simulations of nerve cell input-output behavior for axodendritic activation based on these ideas reveal: frequency-transfer curves for axodendritic activation saturate; activations combined on different dendritic branches sum approximately linearly while those on the same branch occlude; simultaneous activation of several synapses on a previously inactive dendritic branch results in a large “peak” response at the onset of stimulation; and such an initial peak may be markedly mitigated by a prior depolarization of the branch. The third-mentioned finding may represent a widespread mode of hypersensitivity to stimulus onset in neural systems and in particular may contribute to the “on” responses of sensory channels, and the fourth suggests that depolarizing synapses at extreme peripheries of dendritic fibers might in some cases serve an inhibitory function.     

Division of Labor Regulates Precision Rescue Behavior in Sand-Dwelling Cataglyphis cursor Ants: To Give Is to Receive

Division of labor, an adaptation in which individuals specialize in performing tasks necessary to the colony, such as nest defense and foraging, is believed key to eusocial insects'' remarkable ecological success. Here we report, for the first time, a completely novel specialization in a eusocial insect, namely the ability of Cataglyphis cursor ants to rescue a trapped nestmate using precisely targeted behavior. Labeled “precision rescue”, this behavior involves the ability of rescuers not only to detect what, exactly, holds the victim in place, but also to direct specific actions to this obstacle. Individual ants, sampled from each of C. cursor''s three castes, namely foragers, nurses and inactives, were experimentally ensnared (the “victim”) and exposed to a caste-specific group of potential “rescuers.” The data reveal that foragers were able to administer, and obtain, the most help while members of the youngest, inactive caste not only failed to respond to victims, but also received virtually no help from potential rescuers, regardless of caste. Nurses performed intermediate levels of aid, mirroring their intermediate caste status. Our results demonstrate that division of labor, which controls foraging, defense and brood care in C. cursor, also regulates a newly discovered behavior in this species, namely a sophisticated form of rescue, a highly adaptive specialization that is finely tuned to a caste member''s probability of becoming, or encountering, a victim in need of rescue.     

Insights into short‐ and long‐term crop‐foraging strategies in a chacma baboon (Papio ursinus) from GPS and accelerometer data

Crop‐foraging by animals is a leading cause of human–wildlife “conflict” globally, affecting farmers and resulting in the death of many animals in retaliation, including primates. Despite significant research into crop‐foraging by primates, relatively little is understood about the behavior and movements of primates in and around crop fields, largely due to the limitations of traditional observational methods. Crop‐foraging by primates in large‐scale agriculture has also received little attention. We used GPS and accelerometer bio‐loggers, along with environmental data, to gain an understanding of the spatial and temporal patterns of activity for a female in a crop‐foraging baboon group in and around commercial farms in South Africa over one year. Crop fields were avoided for most of the year, suggesting that fields are perceived as a high‐risk habitat. When field visits did occur, this was generally when plant primary productivity was low, suggesting that crops were a “fallback food”. All recorded field visits were at or before 15:00. Activity was significantly higher in crop fields than in the landscape in general, evidence that crop‐foraging is an energetically costly strategy and that fields are perceived as a risky habitat. In contrast, activity was significantly lower within 100 m of the field edge than in the rest of the landscape, suggesting that baboons wait near the field edge to assess risks before crop‐foraging. Together, this understanding of the spatiotemporal dynamics of crop‐foraging can help to inform crop protection strategies and reduce conflict between humans and baboons in South Africa.     

Animal‐borne video systems provide insight into the reproductive behavior of the Asian black bear

Previous studies on the mating system of the Asian black bear (Ursus thibetanus) have been limited to observations of captive populations and estimations of multiple paternities. Hence, the mating system of wild bears remains poorly understood. Animal‐borne camera systems (i.e., cameras mounted on animals) provide novel tools to study the behavior of elusive animals. Here, we used an animal‐borne video system to record the activities of wild bears during the mating season. Video camera collars were attached to four adult Asian black bears (male “A” and “B,” and female “A” and “B”) captured in Tokyo, central Japan, in May and June 2018. The collars were retrieved in July 2018, after which the video data were downloaded and analyzed in terms of bear activity and mating behavior. All the bears were found to interact with other uniquely identifiable bears for some of the time (range 9–22 days) during the deployment period (range 36–45 days), and multiple mating in males was documented. Both males and females exhibited different behaviors on social days (i.e., days when the bear interacted with conspecifics) compared with solitary days (i.e., days with no observed interactions with conspecifics). Compared with solitary days, the bears spent a lower proportion of time on foraging activities and higher proportion of time on resting activities on social days. Our results suggest that Asian black bears have a polygamous mating system, as both sexes consort and potentially mate with multiple partners during a given mating season. Furthermore, bears appeared to reduce their foraging activities on social days and engaged more in social interactions.     

Hormone‐mediated foraging strategies in an uncertain environment: Insights into the at‐sea behavior of a marine predator

1. Hormones are extensively known to be physiological mediators of energy mobilization and allow animals to adjust behavioral performance in response to their environment, especially within a foraging context.
2. Few studies, however, have narrowed focus toward the consistency of hormonal patterns and their impact on individual foraging behavior. Describing these relationships can further our understanding of how individuals cope with heterogeneous environments and exploit different ecological niches.
3. To address this, we measured between‐ and within‐individual variation of basal cortisol (CORT), thyroid hormone T3, and testosterone (TEST) levels in wild adult female Galápagos sea lions (Zalophus wollebaeki) and analyzed how these hormones may be associated with foraging strategies. In this marine predator, females exhibit one of three spatially and temporally distinct foraging patterns (i.e., “benthic,” “pelagic,” and “night” divers) within diverse habitat types.
4. Night divers differentiated from other strategies by having lower T3 levels. Considering metabolic costs, night divers may represent an energetically conservative strategy with shorter dive durations, depths, and descent rates to exploit prey which migrate up the water column based on vertical diel patterns.
5. Intriguingly, CORT and TEST levels were highest in benthic divers, a strategy characterized by congregating around limited, shallow seafloors to specialize on confined yet reliable prey. This pattern may reflect hormone‐mediated behavioral responses to specific risks in these habitats, such as high competition with conspecifics, prey predictability, or greater risks of predation.
6. Overall, our study highlights the collective effects of hormonal and ecological variation on marine foraging. In doing so, we provide insights into how mechanistic constraints and environmental pressures may facilitate individual specialization in adaptive behavior in wild populations.

     

Neural Computations Mediating One-Shot Learning in the Human Brain

Incremental learning, in which new knowledge is acquired gradually through trial and error, can be distinguished from one-shot learning, in which the brain learns rapidly from only a single pairing of a stimulus and a consequence. Very little is known about how the brain transitions between these two fundamentally different forms of learning. Here we test a computational hypothesis that uncertainty about the causal relationship between a stimulus and an outcome induces rapid changes in the rate of learning, which in turn mediates the transition between incremental and one-shot learning. By using a novel behavioral task in combination with functional magnetic resonance imaging (fMRI) data from human volunteers, we found evidence implicating the ventrolateral prefrontal cortex and hippocampus in this process. The hippocampus was selectively “switched” on when one-shot learning was predicted to occur, while the ventrolateral prefrontal cortex was found to encode uncertainty about the causal association, exhibiting increased coupling with the hippocampus for high-learning rates, suggesting this region may act as a “switch,” turning on and off one-shot learning as required.     

Thunderstruck: The ACDC model of flexible sequences and rhythms in recurrent neural circuits

Adaptive sequential behavior is a hallmark of human cognition. In particular, humans can learn to produce precise spatiotemporal sequences given a certain context. For instance, musicians can not only reproduce learned action sequences in a context-dependent manner, they can also quickly and flexibly reapply them in any desired tempo or rhythm without overwriting previous learning. Existing neural network models fail to account for these properties. We argue that this limitation emerges from the fact that sequence information (i.e., the position of the action) and timing (i.e., the moment of response execution) are typically stored in the same neural network weights. Here, we augment a biologically plausible recurrent neural network of cortical dynamics to include a basal ganglia-thalamic module which uses reinforcement learning to dynamically modulate action. This “associative cluster-dependent chain” (ACDC) model modularly stores sequence and timing information in distinct loci of the network. This feature increases computational power and allows ACDC to display a wide range of temporal properties (e.g., multiple sequences, temporal shifting, rescaling, and compositionality), while still accounting for several behavioral and neurophysiological empirical observations. Finally, we apply this ACDC network to show how it can learn the famous “Thunderstruck” song intro and then flexibly play it in a “bossa nova” rhythm without further training.     

Neural Tuning Size in a Model of Primate Visual Processing Accounts for Three Key Markers of Holistic Face Processing

Faces are an important and unique class of visual stimuli, and have been of interest to neuroscientists for many years. Faces are known to elicit certain characteristic behavioral markers, collectively labeled “holistic processing”, while non-face objects are not processed holistically. However, little is known about the underlying neural mechanisms. The main aim of this computational simulation work is to investigate the neural mechanisms that make face processing holistic. Using a model of primate visual processing, we show that a single key factor, “neural tuning size”, is able to account for three important markers of holistic face processing: the Composite Face Effect (CFE), Face Inversion Effect (FIE) and Whole-Part Effect (WPE). Our proof-of-principle specifies the precise neurophysiological property that corresponds to the poorly-understood notion of holism, and shows that this one neural property controls three classic behavioral markers of holism. Our work is consistent with neurophysiological evidence, and makes further testable predictions. Overall, we provide a parsimonious account of holistic face processing, connecting computation, behavior and neurophysiology.     

Niche theory‐based modeling of assembly processes of viral communities in bats

Understanding the assembly processes of symbiont communities, including viromes and microbiomes, is important for improving predictions on symbionts’ biogeography and disease ecology. Here, we use phylogenetic, functional, and geographic filters to predict the similarity between symbiont communities, using as a test case the assembly process in viral communities of Mexican bats. We construct generalized linear models to predict viral community similarity, as measured by the Jaccard index, as a function of differences in host phylogeny, host functionality, and spatial co‐occurrence, evaluating the models using the Akaike information criterion. Two model classes are constructed: a “known” model, where virus–host relationships are based only on data reported in Mexico, and a “potential” model, where viral reports of all the Americas are used, but then applied only to bat species that are distributed in Mexico. Although the “known” model shows only weak dependence on any of the filters, the “potential” model highlights the importance of all three filter types—phylogeny, functional traits, and co‐occurrence—in the assemblage of viral communities. The differences between the “known” and “potential” models highlight the utility of modeling at different “scales” so as to compare and contrast known information at one scale to another one, where, for example, virus information associated with bats is much scarcer.     

Evolutionary Establishment of Moral and Double Moral Standards through Spatial Interactions

Situations where individuals have to contribute to joint efforts or share scarce resources are ubiquitous. Yet, without proper mechanisms to ensure cooperation, the evolutionary pressure to maximize individual success tends to create a tragedy of the commons (such as over-fishing or the destruction of our environment). This contribution addresses a number of related puzzles of human behavior with an evolutionary game theoretical approach as it has been successfully used to explain the behavior of other biological species many times, from bacteria to vertebrates. Our agent-based model distinguishes individuals applying four different behavioral strategies: non-cooperative individuals (“defectors”), cooperative individuals abstaining from punishment efforts (called “cooperators” or “second-order free-riders”), cooperators who punish non-cooperative behavior (“moralists”), and defectors, who punish other defectors despite being non-cooperative themselves (“immoralists”). By considering spatial interactions with neighboring individuals, our model reveals several interesting effects: First, moralists can fully eliminate cooperators. This spreading of punishing behavior requires a segregation of behavioral strategies and solves the “second-order free-rider problem”. Second, the system behavior changes its character significantly even after very long times (“who laughs last laughs best effect”). Third, the presence of a number of defectors can largely accelerate the victory of moralists over non-punishing cooperators. Fourth, in order to succeed, moralists may profit from immoralists in a way that appears like an “unholy collaboration”. Our findings suggest that the consideration of punishment strategies allows one to understand the establishment and spreading of “moral behavior” by means of game-theoretical concepts. This demonstrates that quantitative biological modeling approaches are powerful even in domains that have been addressed with non-mathematical concepts so far. The complex dynamics of certain social behaviors become understandable as the result of an evolutionary competition between different behavioral strategies.     

Relative Influence of Genetics and Shared Environment on Child Mental Health Symptoms Depends on Comorbidity

Background

Comorbidity among childhood mental health symptoms is common in clinical and community samples and should be accounted for when investigating etiology. We therefore aimed to uncover latent classes of mental health symptoms in middle childhood in a community sample, and to determine the latent genetic and environmental influences on those classes.

Methods

The sample comprised representative cohorts of twins. A questionnaire-based assessment of mental health symptoms was used in latent class analyses. Data on 3223 twins (1578 boys and 1645 girls) with a mean age of 7.5 years were analyzed. The sample was predominantly non-Hispanic Caucasian (92.1%).

Results

Latent class models delineated groups of children according to symptom profiles–not necessarily clinical groups but groups representing the general population, most with scores in the normative range. The best-fitting models suggested 9 classes for both girls and boys. Eight of the classes were very similar across sexes; these classes ranged from a “Low Symptom” class to a “Moderately Internalizing & Severely Externalizing” class. In addition, a “Moderately Anxious” class was identified for girls but not boys, and a “Severely Impulsive & Inattentive” class was identified for boys but not girls. Sex-combined analyses implicated moderate genetic influences for all classes. Shared environmental influences were moderate for the “Low Symptom” and “Moderately Internalizing & Severely Externalizing” classes, and small to zero for other classes.

Conclusions

We conclude that symptom classes are largely similar across sexes in middle childhood. Heritability was moderate for all classes, but shared environment played a greater role for classes in which no one type of symptom predominated.     

Neural oscillations are a start toward understanding brain activity rather than the end

Does rhythmic neural activity merely echo the rhythmic features of the environment, or does it reflect a fundamental computational mechanism of the brain? This debate has generated a series of clever experimental studies attempting to find an answer. Here, we argue that the field has been obstructed by predictions of oscillators that are based more on intuition rather than biophysical models compatible with the observed phenomena. What follows is a series of cautionary examples that serve as reminders to ground our hypotheses in well-developed theories of oscillatory behavior put forth by theoretical study of dynamical systems. Ultimately, our hope is that this exercise will push the field to concern itself less with the vague question of “oscillation or not” and more with specific biophysical models that can be readily tested.     

Emerging Object Representations in the Visual System Predict Reaction Times for Categorization

Recognizing an object takes just a fraction of a second, less than the blink of an eye. Applying multivariate pattern analysis, or “brain decoding”, methods to magnetoencephalography (MEG) data has allowed researchers to characterize, in high temporal resolution, the emerging representation of object categories that underlie our capacity for rapid recognition. Shortly after stimulus onset, object exemplars cluster by category in a high-dimensional activation space in the brain. In this emerging activation space, the decodability of exemplar category varies over time, reflecting the brain’s transformation of visual inputs into coherent category representations. How do these emerging representations relate to categorization behavior? Recently it has been proposed that the distance of an exemplar representation from a categorical boundary in an activation space is critical for perceptual decision-making, and that reaction times should therefore correlate with distance from the boundary. The predictions of this distance hypothesis have been born out in human inferior temporal cortex (IT), an area of the brain crucial for the representation of object categories. When viewed in the context of a time varying neural signal, the optimal time to “read out” category information is when category representations in the brain are most decodable. Here, we show that the distance from a decision boundary through activation space, as measured using MEG decoding methods, correlates with reaction times for visual categorization during the period of peak decodability. Our results suggest that the brain begins to read out information about exemplar category at the optimal time for use in choice behaviour, and support the hypothesis that the structure of the representation for objects in the visual system is partially constitutive of the decision process in recognition.