Starlings solve the ephemeral reward task.

In this paper, by replacing the exponential memory kernel function of a tabu learning single-neuron model with the power-law memory kernel function, a novel Caputo’s fractional-order tabu learning single-neuron model and a network of two interacting fractional-order tabu learning neurons are constructed firstly. Different from the integer-order tabu learning model, the order of the fractional-order derivative is used to measure the neuron’s memory decay rate and then the stabilities of the models are evaluated by the eigenvalues of the Jacobian matrix at the equilibrium point of the fractional-order models. By choosing the memory decay rate (or the order of the fractional-order derivative) as the bifurcation parameter, it is proved that Hopf bifurcation occurs in the fractional-order tabu learning single-neuron model where the value of bifurcation point in the fractional-order model is smaller than the integer-order model’s. By numerical simulations, it is shown that the fractional-order network with a lower memory decay rate is capable of producing tangent bifurcation as the learning rate increases from 0 to 0.4. When the learning rate is fixed and the memory decay increases, the fractional-order network enters into frequency synchronization firstly and then enters into amplitude synchronization. During the synchronization process, the oscillation frequency of the fractional-order tabu learning two-neuron network increases with an increase in the memory decay rate. This implies that the higher the memory decay rate of neurons, the higher the learning frequency will be.

The influence of single option or forced-exposure (FE) trials was studied in the suboptimal choice task. Pigeons chose between an optimal alternative that led to food half of the time and a suboptimal alternative that led to food 20% of the time. Choice of the suboptimal alternative was compared across groups of subjects that received different numbers of FE trials during training. In Experiment 1, subjects received 100% FE trials, 67% FE trials, or only choice trials. Pigeons in the two groups that had FE trials developed extreme preference for the signaled suboptimal alternative over the unsignaled optimal alternative, while pigeons that had no FE trials showed pronounced individual differences. Experiment 2 compared 10% and 90% FE trials. When neither alternative signaled trial outcomes, both groups of subjects strongly preferred the optimal alternative. When the suboptimal alternative provided differential signals, the subjects in the 90% FE group developed strong preference for the suboptimal alternative and subjects in the 10% FE group maintained preference for the optimal alternative. The results of both experiments demonstrate that FE trials can have substantial effects on the development of preference in the suboptimal choice task.

Suboptimal choice in pigeons: Does the predictive value of the conditioned reinforcer alone determine choice?

Action video game playing has been experimentally linked to a number of perceptual and cognitive improvements. These benefits are captured through a wide range of psychometric tasks and have led to the proposition that action video game experience may promote the ability to extract statistical evidence from sensory stimuli. Such an advantage could arise from a number of possible mechanisms: improvements in visual sensitivity, enhancements in the capacity or duration for which information is retained in visual memory, or higher-level strategic use of information for decision making. The present study measured the capacity and time course of visual sensory memory using a partial report performance task as a means to distinguish between these three possible mechanisms. Sensitivity measures and parameter estimates that describe sensory memory capacity and the rate of memory decay were compared between individuals who reported high evels and low levels of action video game experience. Our results revealed a uniform increase in partial report accuracy at all stimulus-to-cue delays for action video game players but no difference in the rate or time course of the memory decay. The present findings suggest that action video game playing may be related to enhancements in the initial sensitivity to visual stimuli, but not to a greater retention of information in iconic memory buffers.

Alzheimer's dementia produces a loss of discrimination but no increase in rate of memory decay in delayed matching to sample

Emerging work suggests that acute, moderate-intensity aerobic exercise may help to subserve episodic memory of neutral stimuli. Less investigated, however, is whether acute exercise is associated with enhanced memory recognition of emotional stimuli, which was the purpose of this experiment. A parallel-group randomized controlled experiment was employed. Participants (mean age = 20 yr) were randomized into an exercise (n = 17) or control group (n = 17). The exercise group engaged in a 15-min bout of moderate-intensity treadmill walking. Emotional memory recognition was assessed via images from the International Affective Picture System, including assessments of varying degrees of valence and arousal. Memory recognition was assessed at 1 day, 7 days, and 14 days post-memory encoding. We observed a significant main effect for time (F(2) = 104.2, p < 0.001, η2p = 0.77) and a significant main effect for valence–arousal classification (F(4) = 21.39, p < 0.001, η2p = 0.40), but there was no significant time by group interaction (F(2) = 1.09, p = 0.34, η2p = 0.03), classification by group interaction (F(4) = 0.12, p = 0.97, η2p = 0.01), time by classification interaction (F(8) = 1.78, p = 0.08, η2p = 0.05), or time by classification by group interaction (F(8) = 0.78, p = 0.62, η2p = 0.02). In conclusion, emotional memory recognition decreased over the 14-day follow-up period and this rate of memory decay was not altered by acute moderate-intensity exercise engagement. We discuss these findings in the context of exercise intensity and the temporal effects of exercise.

Heatwaves, exacerbated by global warming, are progressively affecting various ecosystems, with coral reefs among the most susceptible. Within these ecosystems, cleaner wrasses (Labroides dimidiatus) engage in cooperative interactions with client fish by removing ectoparasites and play an essential role in sustaining client abundance and diversity. In 2016, the northern section of the Great Barrier Reef experienced widespread and intense bleaching due to unparalleled ocean temperatures associated with a marine heatwave. While prior studies have connected changes in fish densities following this heatwave to modifications in cleaner fish cognitive performance, the immediate impact of heatwave exposure on cleaner fish cognition and brain structure has yet to be investigated. Here, we exposed cleaner wrasses to a laboratory‐simulated Category 1 marine heatwave for 55 days, mirroring the 2016 Great Barrier Reef event. Cleaners' cognitive performance was evaluated through a visual discrimination task during the heatwave and after a 14‐day recovery phase. This was followed by an analysis of brain development 30 days after the cessation of the marine heatwave. Our results demonstrate that although heatwave exposure temporarily hindered cognitive performance, these deficits were recoverable. Interestingly, cleaner fish brain morphology, measured after recovery, underwent significant changes. Specifically, despite cleaners exposed to heatwaves having notably larger brains, their telencephalon was substantially smaller, while their brainstem was enlarged. These findings indicate that while some cognitive effects may be reversible, marine heatwave exposure leads to lasting alterations in brain morphology, particularly in regions associated with higher cognitive functions and social behaviour. This raises questions about the potential impact on more complex tasks that rely on these brain regions. We argue that the significant disruptions in cleaners' cognitive performance observed months after the 2016 due to neurological impairments linked to brain morphological changes. If so, a mere recovery of fish densities may not necessarily lead to a restoration of cognitive performance, as experiencing marine heatwaves might induce life‐long morphological alterations in fish. Our results underscore marine heatwaves' intricate and enduring impact on cleaner fish, emphasizing the need for comprehensive strategies to safeguard these vital components of coral reef ecosystems. Read the free Plain Language Summary for this article on the Journal blog.

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design abstraction, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and humansystem interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

Effects of intertrial reinforcers on rats' timing behavior

In this paper, a tabu learning single neuron model is investigated. By applying the frequency domain approach and analyzing the associated characteristic equation, the existence of bifurcation parameter for this model is determined. Furthermore, we found that if the memory decay rate is used as a bifurcation parameter, Hopf bifurcation occurs in the neuron. This means that a family of periodic solutions bifurcates out from the equilibrium when the bifurcation parameter exceeds a critical value. The direction and stability of the bifurcating periodic solutions are determine by the Nyquist criterion and the graphical Hopf bifurcation theorem. Some numerical simulations for justifying the theoretical analysis are also given.

We study a hidden Markov process which is the result of a transmission of the binary symmetric Markov source over the memoryless binary symmetric channel. This process has been studied extensively in Information Theory and is often used as a benchmark case for the so-called denoising algorithms. Exploiting the link between this process and the 1D Random Field Ising Model (RFIM), we are able to identify the Gibbs potential of the resulting Hidden Markov process. Moreover, we obtain a stronger bound on the memory decay rate. We conclude with a discussion on implications of our results for the development of denoising algorithms.

Time-dependent active force drives periodic reversal in collective cell migration.

Despite evidence on the interaction between cognitive individual differences (IDs) and task complexity, our knowledge of how affective IDs, such as foreign language enjoyment (FLE), interact with task complexity and other factors is limited. Since tasks and activities were found by Dewaele and MacIntyre (2014) to be most relevant to FLE, and since task complexity might interact with learners’ perceptions of task difficulty, it is important to investigate how task complexity impacts FLE changes. Informed by the complex dynamic systems theory, this study employed a mixed-methods multiple case study design to study patterns and causes of high and low FLE arousals. The participants were four pairs of Taiwanese high-intermediate EFL university students who were engaged in simple or complex storytelling tasks with speech acts of refusals. The speakers’ interactions were triangulated with an individual learner’s rating of FLE on a per-second scale and stimulated recalls. Results revealed idiosyncratic patterns of FLE fluctuations of peer interlocutors and a high degree of overlap in sources of low and high FLE in both groups. Speakers reported high FLE as a result of interesting storylines inherent in task design and created by peers, the use of picture prompts, peer collaboration, and task performance. Performance problems, failure to retrieve appropriate vocabulary, task design, and lack of ideas led to low FLE arousals. The findings suggest that task complexity combined with other task-induced, social, and individual factors to affect the fluctuations of FLE. Implications for task design and oral communication instruction to promote FLE are discussed.

Effect of intertrial intervals on recovery and amplitude of electrodermal reactions

Systems engineering processes coordinate the efforts of many individuals to design a complex system. However, the goals of the involved individuals do not necessarily align with the system-level goals. Everyone, including managers, systems engineers, subsystem engineers, component designers, and contractors, is self-interested. It is not currently understood how this discrepancy between organizational and personal goals affects the outcome of complex systems engineering processes. To answer this question, we need a systems engineering theory that accounts for human behavior. Such a theory can be ideally expressed as a dynamic hierarchical network game of incomplete information. The nodes of this network represent individual agents and the edges the transfer of information and incentives. All agents decide independently on how much effort they should devote to a delegated task by maximizing their expected utility; the expectation is over their beliefs about the actions of all other individuals and the moves of nature. An essential component of such a model is the quality function, defined as the map between an agent’s effort and the quality of their job outcome. In the economics literature, the quality function is assumed to be a linear function of effort with additive Gaussian noise. This simplistic assumption ignores two critical factors relevant to systems engineering: (1) the complexity of the design task, and (2) the problem-solving skills of the agent. Systems engineers establish their beliefs about these two factors through years of job experience. In this paper, we encode these beliefs in clear mathematical statements about the form of the quality function. Our approach proceeds in two steps: (1) we construct a generative stochastic model of the delegated task, and (2) we develop a reduced order representation suitable for use in a more extensive game-theoretic model of a systems engineering process. Focusing on the early design stages of a systems engineering process, we model the design task as a function maximization problem and, thus, we associate the systems engineer’s beliefs about the complexity of the task with their beliefs about the complexity of the function being maximized. Furthermore, we associate an agent’s problem solving-skills with the strategy they use to solve the underlying function maximization problem. We identify two agent types: “naïve” (follows a random search strategy) and “skillful” (follows a Bayesian global optimization strategy). Through an extensive simulation study, we show that the assumption of the linear quality function is only valid for small effort levels. In general, the quality function is an increasing, concave function with derivative and curvature that depend on the problem complexity and agent’s skills.