On the influence of spatial and value attentional cues across individuals

The visual world provides a myriad of cues every instance that can be used to direct information processing. How does the brain integrate predictive information from disparate sources to modify visual priorities, and are combination strategies consistent across individuals? Previous evidence shows that sensory cues that are predictive of the value of a visually guided task (incentive value) and cues that signal where task-relevant stimuli may occur (spatial certainty) act independently to bias attention. Anticipatory accounts propose that both cues are comparably encoded into an attentional priority map, whereas the counterfactual account argues that incentive value cues instead induce a reactive encoding of losses based on the direction of attention. Here we adjudicate between these alternatives and further determine whether there are individual differences in how attentional cues are encoded. 149 participants viewed two coloured placeholders that specified the potential value of correctly identifying an imminent target if it appeared in that specific placeholder. Prior to the target’s presentation, an endogenous spatial cue indicated the target’s more likely location. The anticipatory and counterfactual accounts were used to motivate parametric regressors that were compared in their explanatory power of the observed data, at the group level and on data stratified by a clustering algorithm applied to identify individual differences. The algorithm revealed 2 subtypes in the population; whereas all individuals use spatial certainty cues a subset does not use incentive value cues. However, when used, the influence of incentive value cues reflects a counterfactual loss function. The data show that spatial certainty and incentive value act independently to influence visual priorities because they act at distinct points in information processing, and that theories of motivated attention must account for the non-uniform influence of incentive value on visual priorities.

Processing of novel food reveals payoff and rank-biased social learning in a wild primate

Social learning—learning from others—is the basis for behavioural traditions. Different social learning strategies (SLS), where individuals biasedly learn behaviours based on their content or who demonstrates them, may increase an individual’s fitness and generate behavioural traditions. While SLS have been mostly studied in isolation, their interaction and the interplay between individual and social learning is less understood. We performed a field-based open diffusion experiment in a wild primate. We provided two groups of vervet monkeys with a novel food, unshelled peanuts, and documented how three different peanut opening techniques spread within the groups. We analysed data using hierarchical Bayesian dynamic learning models that explore the integration of multiple SLS with individual learning. We (1) report evidence of social learning compared to strictly individual learning, (2) show that vervets preferentially socially learn the technique that yields the highest observed payoff and (3) also bias attention toward individuals of higher rank. This shows that behavioural preferences can arise when individuals integrate social information about the efficiency of a behaviour alongside cues related to the rank of a demonstrator. When these preferences converge to the same behaviour in a group, they may result in stable behavioural traditions.

Noise of Investors’ Attention Mania in the Twenty-first-Century Indian Stock Markets: ARDL and Augmented GARCH-X Models

What brings the equilibrium consensus in the stock markets? We hypothesize that the markets’ equilibrium consensus depends on the noise of investors’ attention mania (NIAM). We refer to the NIAM as investors’ attention heterogeneity and explore its impacts on the National Stock Exchange (NSE) Nifty and Bombay Stock Exchange (BSE) Sensex stocks market returns. We use the methodology of the autoregressive distributed lag (ARDL) and augmented generalized autoregressiuve conditional heteroskedacity (GARCH)-X model, and we examine if there is the presence of NIAM at online attention searches within and across the attention layers, and within and across the stated two stock markets from 2004 to 2019 for investors’ economic–political attention searches. We have revealed that the impacts of the NIAM on the market returns are diverse in nature at the different attention layers and stock markets as well. Besides the ARCH and GARCH effects, we also document the presence of familiarity bias, attention confidence or confusion, and attention integration in the short run and long run.

Implications of a Soy-Based Diet for Animal Models

The use of animal models in fundamental or pre-clinical research remains an absolute requirement for understanding human pathologies and developing new drugs. In order to transpose these results into clinical practice, many parameters must be taken into account to limit bias. Attention has recently been focused on the sex, age or even strain of each animal, but the impact of diet has been largely neglected. Soy, which is commonly used in the diet in varying quantities can affect their physiology. In order to assess whether the presence of soy can impact the obtained results, we studied the impact of a soy-based diet versus a soy-free diet, on diastolic function in a rat model based on transgenic overexpression of the β3-adrenergic receptors in the endothelium and characterized by the appearance of diastolic dysfunction with age. Our results show that the onset of diastolic dysfunction is only observed in transgenic male rats fed with a soy-free diet in the long term. Our study highlights the importance of the diet’s choice in the study design process, especially regarding the proportion of soy, to correctly interpret the outcome as low-cost diets are more likely to be highly concentrated in soy.

Processing of novel food reveal payoff and rank-biased social learning in a wild primate

Cultural complexity is strongly shaped by the efficiency by which new knowledge is propagated. Different social learning strategies (SLS), where individuals biasedly learn particular behaviors or from specific demonstrators, can contribute to an individual’s success. While SLS have been mostly studied in isolation, their interaction and the interplay between individual and social learning is less understood. We performed a field-based open diffusion experiment in a wild primate. We provided two groups of vervet monkeys with a novel food, unshelled peanuts, and documented how three different peanut opening techniques spread within the groups. We analyzed data using hierarchical Bayesian dynamic learning models that explore the integration of multiple SLS with individual learning. We show that vervets preferentially use the technique yielding the highest observed payoff, and also bias attention toward individuals of higher rank. This shows that traditions may arise when individuals integrate information about the efficiency of a behavior alongside cues related to the rank of a demonstrator.

The Asymmetric Mixed-Category Advantage in Visual Working Memory: An Attentional, Not Perceptual (Face-Specific) Account

The mixed-category advantage in visual working memory refers to improved memory for an image in a display containing two different categories relative to a display containing only one category (Cohen et al., 2014). Jiang et al. (2016) found that this advantage characterizes mainly faces and suggested that face-only displays suffer from enhanced interference due to the unique configural nature of faces. Faces, however, possess social and emotional significance that may bias attention toward them in mixed-category displays at the expense of their counterpart category. Consequently, the counterpart category may suffer from little/no advantage, or even an inversed effect. Using a change-detection task, we showed that a category that demonstrated a mixed-category disadvantage when paired with faces, demonstrated a mixed-category advantage when paired with other non-facial categories. Furthermore, manipulating the likelihood of testing a specific category (i.e., changing its task-relevance) in mixed-category trials, altered its advantaged/disadvantaged status, suggesting that the effect may be mediated by attention. Finally, to control for perceptual exposure factors, a sequential presentation experimental version was conducted. Whereas faces showed a typical mixed-category advantage, this pattern was again modulated (yielding an advantage for a non-facial category) when inserting a task-relevance manipulation. Taken together, our findings support a central resource allocation account, according to which the asymmetric mixed-category effect likely stems from an attentional bias to one of the two categories. This attentional bias is not necessarily spatial in its nature, and it presumably affects processing stages subsequent to the initial perceptual encoding phase in working memory.

Neuropsychological rehabilitation of higher cortical functions after brain damage

Neuropsychological interventions for impairments of higher cognitive functions can be divided into four different approaches: restoration of function, compensation, physiological stimulations, and metacognitive strategies. Training that aims to restore an impaired function or to increase processing speed or capacity is repetitive and often stereotyped. Such training may lead to task-specific learning with little generalization, as may be observed in particular in the domain of attention rehabilitation. However, it remains a matter of debate whether such practice effects really reflect the restoration of function or improved processing due to preserved procedural learning skills. For some cognitive domains (such as memory), restoration of function is mostly impossible; consequently, training mainly relies on compensatory strategies. For example, enhancement of learning may be achieved by improving memory encoding with mental imagery, while everyday memory is supported with systematic training of external aids, such as, memory notebooks. A third approach is applied in neglect rehabilitation and uses physiological stimulations to bias attention and sensory representations (e.g. optokinetic stimulation) or decrease interhemispheric inhibition (transcranial magnetic stimulation). Finally, the fourth approach is to structure behaviour and to enhance metacognitive abilities; this strategy is applied in the rehabilitation of complex problem-solving skills and impaired emotional regulation. Although it is difficult to control experimental biases in intervention studies targeting cognitive and behavioural disturbances, an increasing number of controlled clinical trials provide evidence for the efficacy of each of the four therapeutic approaches.

The persistence of value-driven attention capture is task dependent

Visual features previously associated with reward can automatically capture attention even when task-irrelevant, a phenomenon known as value-driven attention capture (VDAC, Anderson et al., 2011b). VDAC persists without reinforcement, unlike other forms of learning where removing reinforcement typically leads to extinction (Pavlov, 1927). This study examined the conditions under which VDAC could be extinguished. In four experiments, factors known to affect attention were manipulated to examine their impact on VDAC and its extinction. All experiments included learning and test phases. During learning, participants completed a visual search task during which one of two target colors was associated with a reward, and the other with no reward. During test, one week later, participants completed another visual search task during which the reward association was not reinforced. The task during test had twice as many exposures to the rewarded feature than during learning to ensure a sufficient number of exposures to observe extinction. When a rewarded feature remained task-relevant (Exp. 1), the capture effect was reduced, but extinction was not complete. When a rewarded feature was made task-irrelevant (Exp. 2) there was no evidence of extinction. When the frequency of exposure to the task-irrelevant rewarded feature was reduced (Exp. 4), VDAC also persisted. A physically salient target (Exp. 3) resulted in the fastest rate of VDAC extinction. These findings demonstrate that the extinction of VDAC depends on various factors that affect priority for attention, especially those that bias attention away from reward-associated features.