Delay discounting and under-valuing of recent information predict poorer adherence to social distancing measures during the COVID-19 pandemic.

The COVID-19 pandemic has brought about unprecedented global changes in individual and collective behaviour. To reduce the spread of the virus, public health bodies have promoted social distancing measures while attempting to mitigate their mental health consequences. The current study aimed to identify cognitive predictors of social distancing adherence and mental health symptoms, using computational models derived from delay discounting (the preference for smaller, immediate rewards over larger, delayed rewards) and patch foraging (the ability to trade-off between exploiting a known resource and exploring an unknown one).

Waiting in intertemporal choice tasks affects discounting and subjective time perception.

The literature on human delay discounting behavior is dominated by experimental paradigms, which do not impose actual delays. Given that waiting may be aversive even on short timescales, we present a novel delay discounting paradigm to study differences in delay discounting behavior either when real waiting is involved, or not. This paradigm retains the fundamental trade-off between rewards received versus their immediacy.

Temporal discounting does not influence body mass index.

The prevalence of obesity has driven searches for cognitive or behavioural economic factors related to Body Mass Index (BMI). One candidate is delay discounting: those who prefer smaller sooner rewards over larger but later rewards are hypothesised to have higher BMI. The findings in the literature are mixed however, with meta analyses suggesting only a very small correlation between discounting and BMI.

The case of muddled units in temporal discounting.

While parameters are crucial components of cognitive models, relatively little importance has been given to their units. We show that this has lead to some parameters to be contaminated, introducing an artifactual correlation between them. We also show that this has led to the illegal comparison of parameters with different units of measurement - this may invalidate parameter comparisons across participants, conditions, groups, or studies.

Hunger increases delay discounting of food and non-food rewards.

How do our valuation systems change to homeostatically correct undesirable psychological or physiological states, such as those caused by hunger? There is evidence that hunger increases discounting for food rewards, biasing choices towards smaller but sooner food reward over larger but later reward. However, it is not understood how hunger modulates delay discounting for non-food items. We outline and quantitatively evaluate six possible models of how our valuation systems modulate discounting of various commodities in the face of the undesirable state of being hungry.

Hierarchical Bayesian estimation and hypothesis testing for delay discounting tasks.

A state-of-the-art data analysis procedure is presented to conduct hierarchical Bayesian inference and hypothesis testing on delay discounting data. The delay discounting task is a key experimental paradigm used across a wide range of disciplines from economics, cognitive science, and neuroscience, all of which seek to understand how humans or animals trade off the immediacy verses the magnitude of a reward. Bayesian estimation allows rich inferences to be drawn, along with measures of confidence, based upon limited and noisy behavioural data.

Bayesian accounts of covert selective attention: A tutorial review.

Decision making and optimal observer models offer an important theoretical approach to the study of covert selective attention. While their probabilistic formulation allows quantitative comparison to human performance, the models can be complex and their insights are not always immediately apparent. Part 1 establishes the theoretical appeal of the Bayesian approach, and introduces the way in which probabilistic approaches can be applied to covert search paradigms.

How do we use the past to predict the future in oculomotor search?

A variety of findings suggest that when conducting visual search, we can exploit cues that are statistically related to a target's location. But is this the result of heuristic mechanisms or an internal model that tracks the statistics of the environment? Here, connections are made between the two explanations, and four models are assessed to probe the mechanisms underlying prediction in search. Participants conducted a simple gaze-contingent search task with five conditions, each of which consists of different combinations of 1st and 2nd order statistics.

Search asymmetries: parallel processing of uncertain sensory information.

What is the mechanism underlying search phenomena such as search asymmetry? Two-stage models such as Feature Integration Theory and Guided Search propose parallel pre-attentive processing followed by serial post-attentive processing. They claim search asymmetry effects are indicative of finding pairs of features, one processed in parallel, the other in serial. An alternative proposal is that a 1-stage parallel process is responsible, and search asymmetries occur when one stimulus has greater internal uncertainty associated with it than another.

Quantitative analysis of three-dimensional human mammary epithelial tissue architecture reveals a role for tenascin-C in regulating c-met function.

Remodeling of the stromal extracellular matrix and elevated expression of specific proto-oncogenes within the adjacent epithelium represent cardinal features of breast cancer, yet how these events become integrated is not fully understood. To address this question, we focused on tenascin-C (TN-C), a stromal extracellular matrix glycoprotein whose expression increases with disease severity. Initially, nonmalignant human mammary epithelial cells (MCF-10A) were cultured within a reconstituted basement membrane (BM) where they formed three-dimensional (3-D) polarized, growth-attenuated, multicellular acini, enveloped by a continuous endogenous BM.

Optimal feature integration in visual search.

Despite embodying fundamentally different assumptions about attentional allocation, a wide range of popular models of attention include a max-of-outputs mechanism for selection. Within these models, attention is directed to the items with the most extreme-value along a perceptual dimension via, for example, a winner-take-all mechanism. From the detection theoretic approach, this MAX-observer can be optimal under specific situations, however in distracter heterogeneity manipulations or in natural visual scenes this is not always the case.

Investigating a space-variant weighted salience account of visual selection.

Weighted salience models are a popular framework for image-driven visual attentional processes. These models operate by: sampling the visual environment; calculating feature maps; combining them in a weighted sum and using this to determine where the eye will fixate next. We examine these stages in turn.

The long and the short of it: spatial statistics at fixation vary with saccade amplitude and task.

We recorded over 90,000 saccades while observers viewed a diverse collection of natural images and measured low level visual features at fixation. The features that discriminated between where observers fixated and where they did not varied considerably with task, and the length of the preceding saccade. Short saccades (<8 degrees) are image feature dependent, long are less so.

Is the early visual system optimised to be energy efficient?

This paper demonstrates that a representation which balances natural image encoding with metabolic energy efficiency shows many similarities to the neural organisation observed in the early visual system. A simple linear model was constructed that learned receptive fields by optimally balancing information coding with metabolic expense for an entire visual field in a 2-stage visual system. The input to the model consists of a space variant retinal array of photoreceptors.

Synaptic energy efficiency in retinal processing.

Recent work suggests that the visual system may represent early visual information in an energy efficient manner [Nature 381 (1996); Nature, 381 (1996) 607; Neural Comput. 3 (2001) 799; Curr. Opin.