Nesting in an uncertain world: information and sampling the future

Seasonal fecundity is strongly influenced by the number of nests attempted (including renests following nest failure) in a season. This number is often assumed to be set by the length of the breeding season or through some predetermined maximum. Instead, the decision to renest likely results from a cost–benefit analysis honed by natural selection where the ultimate components of fitness, i.e. reproduction and survival, tradeoff with one another. Moreover, reproductive decision making should not occur in an information‐vacuum. In a world where habitat quality (i.e. likelihood of nest success) is uncertain females should use nest failures to update the probability their renest nest will succeed, and this estimate in turn can affect the decision to renest. We develop a model of renesting behavior based on these conceptual ideas using the framework of statistical decision theory (SDT) and the process of Bayesian updating. We assume that renesting incurs 1) a cost to future reproductive success and 2) a reduction in expected reproductive success for each successive replacement nest. We show, all else equal, birds should curtail renesting with (1) increased residual reproductive success, (2) increased cost to future reproduction, (3) declines in current reproduction with successive attempts, and (4) increasing nest predation rates. We also explore several ecological implications of the model. First, uncertainty in habitat quality and the process of information updating, based on nest outcomes, link changes in the quality or proportion of one habitat type to the behavior in the other habitat. Second, females may use their estimate of habitat quality, based on a sample of nesting attempts, to decide whether to return or disperse to a new site between years. We compare this to the win‐stay: lose‐switch rule for dispersal and discuss the implications for population dynamics.     

持变概率法与核酸序列中的信息提取

利用一种新的序列分析方法——持变概率法,对GenBank数据库中果蝇、小家鼠、人类的7310条核酸序列片断进行分析,得出：（1）核酸序列中的持变概率与持变数呈指数关系变化;（2）同一种生物同一染色体的持变指数很相近;（3）同一种生物不同染色体的持变指数有一定的差异;（4）不同种生物染色体的持变指数之间有显著差异。说明持变概率法能够提取核酸序列的特征,持变指数有助于基因的分类与识别,此方法可用于基因序列分析。     

Dynamic decision-making in uncertain environments II. Allais paradox in human behavior

In both animal and human behavioral repertoires, classical expected utility theory is considered a fundamental element of decision making under conditions of uncertainty. This theory has been widely applied to problems of animal behavior and evolutionary game theory, as well as to human economic behavior. The Allais paradox hinges on the expression of avoidance of bankruptcy by humans, or death by starvation in animals. This paradox reveals that human behavioral patterns are often inconsistent with predictions under the classical expected utility theory as formulated by von Neumann and Morgenstern. None of the many attempts to reformulate utility theory has been entirely successful in resolving this paradox with rigorous logic. We present a simple, but novel approach to the theory of decision making, in which utility is dependent on current wealth, and in which losses are more heavily weighted than gains. Our approach resolves the Allais paradox in a manner that is consistent with how humans formulate decisions under uncertainty. Our results indicate that animals, including humans, are in principle risk-averse. Our restructuring of dynamic utility theory presents a basic optimization scheme for sequential or dynamic decisions in both animals and humans.     

Electromyogram refinement using muscle synergy based regulation of uncertain information

Electromyogram signal (EMG) measurement frequently experiences uncertainty attributed to issues caused by technical constraints such as cross talk and maximum voluntary contraction. Due to these problems, individual EMGs exhibit uncertainty in representing their corresponding muscle activations. To regulate this uncertainty, we proposed an EMG refinement, which refines EMGs with regulating the contribution redundancy of the signals from EMGs to approximating torques through EMG-driven torque estimation (EDTE) using the muscular skeletal forward dynamic model. To regulate this redundancy, we must consider the synergistic contribution redundancy of muscles, including “unmeasured” muscles, to approximating torques, which primarily causes redundancy of EDTE. To suppress this redundancy, we used the concept of muscle synergy, which is a key concept of analyzing the neurophysiological regulation of contribution redundancy of muscles to exerting torques. Based on this concept, we designed a muscle-synergy-based EDTE as a framework for EMG refinement, which regulates the abovementioned uncertainty of individual EMGs in consideration of unmeasured muscles. In achieving the proposed EMG refinement, the most considerable point is to suppress a large change such as overestimation attributed to enhancement of the contribution of particular muscles to estimating torques. Therefore it is reasonable to refine EMGs by minimizing the change in EMGs. To evaluate this model, we used a Bland-Altman plot, which quantitatively evaluates the proportional bias of refined signals to EMGs. Through this evaluation, we showed that the proposed EDTE minimizes the bias while approximating torques. Therefore this minimization optimally regulates the uncertainty of EMGs and thereby leads to optimal EMG refinement.     

Dynamic decision-making in uncertain environments I. The principle of dynamic utility

Understanding the dynamics or sequences of animal behavior usually involves the application of either dynamic programming or stochastic control methodologies. A difficulty of dynamic programming lies in interpreting numerical output, whereas even relatively simple models of stochastic control are notoriously difficult to solve. Here we develop the theory of dynamic decision-making under probabilistic conditions and risks, assuming individual growth rates of body size are expressed as a simple stochastic process. From our analyses we then derive the optimization of dynamic utility, in which the utility of weight gain, given the current body size, is a logarithmic function: hence the fitness function of an individual varies depending on its current body size. The dynamic utility function also shows that animals are universally sensitive to risk and display risk-averse behaviors. Our result proves the traditional use of expected utility theory and game theory in behavioral studies is valid only as a static model.     

The RNA worlds in context

There are two RNA worlds. The first is the primordial RNA world, a hypothetical era when RNA served as both information and function, both genotype and phenotype. The second RNA world is that of today's biological systems, where RNA plays active roles in catalyzing biochemical reactions, in translating mRNA into proteins, in regulating gene expression, and in the constant battle between infectious agents trying to subvert host defense systems and host cells protecting themselves from infection. This second RNA world is not at all hypothetical, and although we do not have all the answers about how it works, we have the tools to continue our interrogation of this world and refine our understanding. The fun comes when we try to use our secure knowledge of the modern RNA world to infer what the primordial RNA world might have looked like.     

Small worlds in RNA structures

I consider conformational spaces of tRNA^phe defined by sets of suboptimal structures from the perspective of small-world networks. Herein, the influence of modifications on typical small-world network properties and the shape of energy landscapes is discussed. Results indicate that natural modifications influence the degree of local clustering and mean path lengths far more than random or no modifications. High frequencies in the thermodynamic ensemble coincide with high numbers of neighboring structures that one conformation can adopt by one elementary move. Conformation spaces indicate the existence of modular substructures. It can be shown that modifications leave the nature of small-world topology untouched albeit natural modifications have a reasonable enhancing and streamlining effect on the degree of clustering and therefore on the substructures of the conformational space.     

Real neuroscience in virtual worlds

Virtual reality (VR) holds great promise as a tool to study the neural circuitry underlying animal behaviors. Here, we discuss the advantages of VR and the experimental paradigms and technologies that enable closed loop behavioral experiments. We review recent results from VR research in genetic model organisms where the potential combination of rich behaviors, genetic tools and cutting edge neural recording techniques are leading to breakthroughs in our understanding of the neural basis of behavior. We also discuss several key issues to consider when performing VR experiments and provide an outlook for the future of this exciting experimental toolkit.     

Dynamic integration of reward and stimulus information in perceptual decision-making

In perceptual decision-making, ideal decision-makers should bias their choices toward alternatives associated with larger rewards, and the extent of the bias should decrease as stimulus sensitivity increases. When responses must be made at different times after stimulus onset, stimulus sensitivity grows with time from zero to a final asymptotic level. Are decision makers able to produce responses that are more biased if they are made soon after stimulus onset, but less biased if they are made after more evidence has been accumulated? If so, how close to optimal can they come in doing this, and how might their performance be achieved mechanistically? We report an experiment in which the payoff for each alternative is indicated before stimulus onset. Processing time is controlled by a “go” cue occurring at different times post stimulus onset, requiring a response within msec. Reward bias does start high when processing time is short and decreases as sensitivity increases, leveling off at a non-zero value. However, the degree of bias is sub-optimal for shorter processing times. We present a mechanistic account of participants'' performance within the framework of the leaky competing accumulator model [1], in which accumulators for each alternative accumulate noisy information subject to leakage and mutual inhibition. The leveling off of accuracy is attributed to mutual inhibition between the accumulators, allowing the accumulator that gathers the most evidence early in a trial to suppress the alternative. Three ways reward might affect decision making in this framework are considered. One of the three, in which reward affects the starting point of the evidence accumulation process, is consistent with the qualitative pattern of the observed reward bias effect, while the other two are not. Incorporating this assumption into the leaky competing accumulator model, we are able to provide close quantitative fits to individual participant data.     

Dynamic process of information transmission complexity in human brains

Based on a complexity analysis of mutual information transmission of EEG developed by us [Xu J, Liu Z, Liu R, Yang Q (1997) Physica D 106: 363–374], dynamic processes of the complexity of mutual information transmission in human brains were studied. To diminish possible problems due to coarse graining preprocessing, some new measures of complexity were used. The results show that, just before and after generalized seizures, the complexities of almost all information transmission between different brain areas drop significantly; there is also a temporary decrease of complexity when subjects shift their attention. The above facts suggest that there is a transient decrease of information transmission complexity when brain state changes occur suddenly. Mental arithmetic tasks activate the left temporal lobe to exchange more information with other brain areas. The results hint that the methods used here might be an approach to observe quick processes in the living brain. Received: 14 October 1999 / Accepted in revised form: 24 March 2000     

Predation risk assessment based on uncertain information: interacting effects of known and unknown cues

Prey use reliable public information in order to assess local habitat condirions such as predation risks, competitive interactions, and foraging opportunities (Dall et al. 2005), allowing for context appropriate behavioral decisions. However, public information can often differ widely in reliability (Feyten and Brown 2018), increasing the potential costs associated with behavioral decision making (Dall et al. 2005). The reliability of public information is expected to decrease with in creased un certainty of environmental conditio ns (Koops 2004;Dall et al. 2005), where ecological uncertainty is the ambiguity about the current state of the environment due to imperfect or incomplete information (Dall et al. 2005;Munoz and Blumstein 2012;Feyten and Brown 2018).     

Attention improves information flow between neuronal populations without changing the communication subspace

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Animal survival strategies in Neoproterozoic ice worlds

The timing of the first appearance of animals is of crucial importance for understanding the evolution of life on Earth. Although the fossil record places the earliest metazoans at 572–602 Ma, molecular clock studies suggest a far earlier origination, as far back as ~850 Ma. The difference in these dates would place the rise of animal life into a time period punctuated by multiple colossal, potentially global, glacial events. Although the two schools of thought debate the limitations of each other's methods, little time has been dedicated to how animal life might have survived if it did arise before or during these global glacial periods. The history of recent polar biota shows that organisms have found ways of persisting on and around the ice of the Antarctic continent throughout the Last Glacial Maximum (33–14 Ka), with some endemic species present before the breakup of Gondwana (180–23 Ma). Here we discuss the survival strategies and habitats of modern polar marine organisms in environments analogous to those that could have existed during Neoproterozoic glaciations. We discuss how, despite the apparent harshness of many ice covered, sub-zero, Antarctic marine habitats, animal life thrives on, in and under the ice. Ice dominated systems and processes make some local environments more habitable through water circulation, oxygenation, terrigenous nutrient input and novel habitats. We consider how the physical conditions of Neoproterozoic glaciations would likely have dramatically impacted conditions for potential life in the shallows and erased any possible fossil evidence from the continental shelves. The recent glacial cycle has driven the evolution of Antarctica's unique fauna by acting as a “diversity pump,” and the same could be true for the late Proterozoic and the evolution of animal life on Earth, and the existence of life elsewhere in the universe on icy worlds or moons.