https://www.cell.com/trends/cognitive-sciences/pdf/S1364-6613(12)00243-4.pdf

Alpha-band oscillations, attention, and controlled access to stored information

Inter-individual variability in perception, thought and action is frequently treated as a source of 'noise' in scientific investigations of the neural mechanisms that underlie these processes, and discarded by averaging data from a group of participants. However, recent MRI studies in the human brain show that inter- individual variability in a wide range of basic and higher cognitive functions — including perception, motor control, memory, aspects of consciousness and the ability to introspect — can be predicted from the local structure of grey and white matter as assessed by voxel-based morphometry or diffusion tensor imaging. We propose that inter-individual differences can be used as a source of information to link human behaviour and cognition to brain anatomy.

/pdf/the-structural-basis-of-inter-individual-differences-in-2fo6a5hcs9.pdf

The structural basis of inter-individual differences in human behaviour and cognition

How do we find what we are looking for? Even when the desired target is in the current field of view, we need to search because fundamental limits on visual processing make it impossible to recognize everything at once. Searching involves directing attention to objects that might be the target. This deployment of attention is not random. It is guided to the most promising items and locations by five factors discussed here: bottom-up salience, top-down feature guidance, scene structure and meaning, the previous history of search over timescales ranging from milliseconds to years, and the relative value of the targets and distractors. Modern theories of visual search need to incorporate all five factors and specify how these factors combine to shape search behaviour. An understanding of the rules of guidance can be used to improve the accuracy and efficiency of socially important search tasks, from security screening to medical image perception. How do we find what we are looking for? Wolfe and Horowitz discuss the five factors that guide attention in visual search.

Five factors that guide attention in visual search

http://wexler.free.fr/library/files/martens%20%282010%29%20the%20attentional%20blink.%20past%2C%20present%2C%20and%20future%20of%20a%20blind%20spot%20in%20perceptual%20awareness.pdf

The attentional blink: Past, present, and future of a blind spot in perceptual awareness

There is growing consensus that reward plays an important role in the control of attention. Until recently, reward was thought to influence attention indirectly by modulating task-specific motivation and its effects on voluntary control over selection. Such an account was consistent with the goal-directed (endogenous) versus stimulus-driven (exogenous) framework that had long dominated the field of attention research. Now, a different perspective is emerging. Demonstrations that previously reward-associated stimuli can automatically capture attention even when physically inconspicuous and task-irrelevant challenge previously held assumptions about attentional control. The idea that attentional selection can be value driven, reflecting a distinct and previously unrecognized control mechanism, has gained traction. Since these early demonstrations, the influence of reward learning on attention has rapidly become an area of intense investigation, sparking many new insights. The result is an emerging picture of how the reward system of the brain automatically biases information processing. Here, I review the progress that has been made in this area, synthesizing a wealth of recent evidence to provide an integrated, up-to-date account of value-driven attention and some of its broader implications.

The attention habit: how reward learning shapes attentional selection

Neural evidence reveals the rapid effects of reward history on selective attention

Accuracy for a second target is reduced when it is presented within 500 msec of a first target. This phenomenon is called the attentional blink (AB). A diffused attentional state (via positive affect or an additional task) has been shown to reduce the AB, whereas a focused attentional state (via negative affect) has been shown to increase the AB, purportedly by influencing the amount of attentional investment and flexibility. In the present study, individual differences in personality traits related to positive affect, negative affect, and cognitive flexibility were used to predict individual differences in AB magnitude. As hypothesized, greater extraversion and openness predicted smaller ABs. Greater openness also predicted higher overall target accuracy. Greater neuroticism predicted larger ABs and lower overall target accuracy. Conscientiousness, associated with less cognitive flexibility, predicted lower overall target accuracy. Personality may modulate the AB by influencing overinvestment via dispositional tendencies toward more or less stringent or capable cognitive control.

/pdf/personality-predicts-temporal-attention-costs-in-the-1plgv7o39g.pdf

Personality predicts temporal attention costs in the attentional blink paradigm

Resting EEG in alpha and beta bands predicts individual differences in attentional blink magnitude

The attentional blink (AB) is a transient attention cost that is shown when report accuracy for a second target (T2) is reduced when T2 is presented within approximately 500 ms of a first target (T1). Thus, by definition an AB is only observed when T2 accuracy is reduced at short relative to long T1–T2 separations, and the magnitude of the AB is reflected in the change in T2 performance across target separations. However, the designs, analyses, and interpretations of several studies of the AB have suggested a lack of clear definitions about what constitutes a demonstration of the AB, what constitutes a modulation of the AB across participant groups or manipulations, and how AB magnitude might best be represented accurately as a single value for a given individual. In this article, we discuss the important conceptual and methodological issues that should be considered when obtaining, analyzing, and interpreting AB data, and we discuss the pros and cons of various approaches while providing suggestions as to how best to validly represent the AB and its modulations.

https://link.springer.com/content/pdf/10.3758%2Fs13414-012-0338-4.pdf

A conceptual and methodological framework for measuring and modulating the attentional blink

Greater attentional blink magnitude is associated with higher levels of anticipatory attention as measured by alpha event-related desynchronization (ERD)

Mary H. MacLean

Papers

Neural evidence reveals the rapid effects of reward history on selective attention

Personality predicts temporal attention costs in the attentional blink paradigm

Resting EEG in alpha and beta bands predicts individual differences in attentional blink magnitude

A conceptual and methodological framework for measuring and modulating the attentional blink

Greater attentional blink magnitude is associated with higher levels of anticipatory attention as measured by alpha event-related desynchronization (ERD)