Attention and associative learning in humans: An integrative review

This article presents a comprehensive survey of research concerning interactions between associative learning and attention in humans. Four main findings are described. First, attention is biased toward stimuli that predict their consequences reliably (learned predictiveness). This finding is consistent with the approach taken by Mackintosh (1975) in his attentional model of associative learning in nonhuman animals. Second, the strength of this attentional bias is modulated by the value of the outcome (learned value). That is, predictors of high-value outcomes receive especially high levels of attention. Third, the related but opposing idea that uncertainty may result in increased attention to stimuli (Pearce & Hall, 1980), receives less support. This suggests that hybrid models of associative learning, incorporating the mechanisms of both the Mackintosh and Pearce-Hall theories, may not be required to explain data from human participants. Rather, a simpler model, in which attention to stimuli is determined by how strongly they are associated with significant outcomes, goes a long way to account for the data on human attentional learning. The last main finding, and an exciting area for future research and theorizing, is that learned predictiveness and learned value modulate both deliberate attentional focus, and more automatic attentional capture. The automatic influence of learning on attention does not appear to fit the traditional view of attention as being either goal-directed or stimulus-driven. Rather, it suggests a new kind of “derived” attention

Dissociable learning processes, associative theory, and testimonial reviews: A comment on Smith and Church (2018

Smith and Church (Psychonomic Bulletin & Review, 25, 1565–1584 2018) present a “testimonial” review of dissociable learning processes in comparative and cognitive psychology, by which we mean they include only the portion of the available evidence that is consistent with their conclusions. For example, they conclude that learning the information-integration category-learning task with immediate feedback is implicit, but do not consider the evidence that people readily report explicit strategies in this task, nor that this task can be accommodated by accounts that make no distinction between implicit and explicit processes. They also consider some of the neuroscience relating to information-integration category learning, but do not report those aspects that are more consistent with an explicit than an implicit account. They further conclude that delay conditioning in humans is implicit, but do not report evidence that delay conditioning requires awareness; nor do they present the evidence that conditioned taste aversion, which should be explicit under their account, can be implicit. We agree with Smith and Church that it is helpful to have a clear definition of associative theory, but suggest that their definition may be unnecessarily restrictive. We propose an alternative definition of associative theory and briefly describe an experimental procedure that we think may better distinguish between associative and non-associative processes

Transport and retention of microparticles in packed sand columns at low and intermediate ionic strengths: experiments and mathematical modeling

Functional relationships correlating particle filtration coefficients and porewater ionic strength are herein proposed and validated, based on deposition experiments of micrometer-sized particles onto siliceous sand. Experiments were conducted using one-dimensional laboratory columns and stable monodisperse aqueous suspensions of negatively charged latex particles with a mean size of 1.90 lm. The role of ionic strength was systematically investigated and six different monovalent salt concentrations (1, 3, 10, 30, 100, 300 mM) were employed by addition of sodium chloride to the aqueous solution. A mathematical advection-dispersiondeposition transport model was adopted assuming that attachment and detachment of particles in the porous medium are concurrent mechanisms of particle filtration, and including a Langmuir-type blocking function to account for availability in deposition sites. The system of equations modeling colloid transport was solved numerically. Attachment rate and detachment rate coefficients were thereby determined for each employed ionic strength, as well as a blocking coefficient in the form of a maximum particle concentration in the solid phase. Therefore, functional relationships expressing the dependence of these coefficients on ionic strength were proposed, based on literature findings and present experimental observations. The existence of a critical salt deposition concentration (and release concentration) separating a favorable attachment (and detachment) regime from an unfavorable condition is assumed. In respect to the blocking coefficient, a power-law dependence on ionic strength is hypothesized. The proposed functional relationships proved adequate to reproduce the coefficient trends extrapolated from data fitting by the transport model. They may represent a powerful tool to describe and predict microparticle mobility in saturated porous media if embedded a priori in the related mathematical transport model