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This review summarizes linear spatiotemporal signal analysis methods that derive their power from careful consideration of spatial and temporal features of skull surface potentials. BCIs offer tremendous potential for improving the quality of life for those with severe neurological disabilities. At the same time, it is now possible to use noninvasive systems to improve performance for time-demanding tasks. Signal processing and machine learning are playing a fundamental role in enabling applications of BCI and in many respects, advances in signal processing and computation have helped to lead the way to real utility of noninvasive BCI. [ABSTRACT FROM PUBLISHER]

Conventional wisdom on psychological experiments has held that when one or more independent variables are manipulated it is essential that all other conditions are kept constant such that confounding factors can be assumed negligible (Woodworth, 1938). In practice, the latter assumption is often questionable because it is generally difficult to guarantee that all other conditions are constant between any two trials. Therefore, the most common way to check for confounding violations of this assumption is to split the experimental conditions in terms of "trial types" to simulate a reduction of unintended trial-by-trial variation. Here, we pose a method which is more general than the use of trial types: use of mathematical models treating measures of potentially confounding factors and manipulated variables as equals on the single-trial level. We show how the method can be applied with models that subsume under the generalized linear item response theory (GLIRT), which is the case for most of the well-known psychometric models (Mellenbergh, 1994). As an example, we provide a new analysis of a single-letter recognition experiment using a nested likelihood ratio test that treats manipulated and measured variables equally (i.e., in exactly the same way) on the single-trial level. The test detects a confounding interaction with time-on-task as a single-trial measure and yields a substantially better estimate of the effect size of the main manipulation compared with an analysis made in terms of trial types.

Background: Several studies have demonstrated a bilateral field advantage (BFA) in early visual attentional processing, that is, enhanced visual processing when stimuli are spread across both visual hemifields. The results are reminiscent of a hemispheric resource model of parallel visual attentional processing, suggesting more attentional resources on an early level of visual processing for bilateral displays [e.g. Sereno AB, Kosslyn SM. Discrimination within and between hemifields: a new constraint on theories of attention. Neuropsychologia 1991;29(7):659-75.]. Several studies have shown that the BFA extends beyond early stages of visual attentional processing, demonstrating that visual short term memory (VSTM) capacity is higher when stimuli are distributed bilaterally rather than unilaterally., Objective/hypothesis: Here we examine whether hemisphere-specific resources are also evident on later stages of visual attentional processing., Methods: Based on the Theory of Visual Attention (TVA) [Bundesen C. A theory of visual attention. Psychol Rev 1990;97(4):523-47.] we used a whole report paradigm that allows investigating visual attention capacity variability in unilateral and bilateral displays during navigated repetitive transcranial magnetic stimulation (rTMS) of the precuneus region., Results: A robust BFA in VSTM storage capacity was apparent after rTMS over the left precuneus and in the control condition without rTMS. In contrast, the BFA diminished with rTMS over the right precuneus., Conclusion: This finding indicates that the right precuneus plays a causal role in VSTM capacity, particularly in bilateral visual displays., (Copyright © 2015 Elsevier Inc. All rights reserved.)

In this study the primary aims were to characterize the effects of age on basic components of visual attention derived from assessments based on a theory of visual attention (TVA) in 325 healthy volunteers covering the adult lifespan (19-81 years). Furthermore, we aimed to investigate how age-related differences on TVA parameters are associated with white matter (WM) microstructure as indexed by diffusion tensor imaging (DTI). Finally, we explored how TVA parameter estimates were associated with complex, or multicomponent indices of processing speed (Digit-symbol substitution, DSS) and fluid intelligence (gF). The results indicated that the TVA parameters for visual short-term memory capacity, K, and for attentional selectivity, α, were most strongly associated with age before the age of 50. However, in this age range, it was the parameter for processing speed, C, that was most clearly associated with DTI indices, in this case fractional anisotropy (FA), particularly in the genu and body of the corpus callosum. Furthermore, differences in the C parameter partially mediated differences in DSS within this age range. After the age of 50, the TVA parameter for the perceptual threshold, t 0, as well as K, were most strongly related to participant age. Both parameters, but t 0 more strongly so than K, were associated WM diffusivity, particularly in projection fibers such as the internal capsule, the sagittal stratum, and the corona radiata. Within this age range, t 0 partially mediated age-related differences in gF. The results are consistent with, and provide novel empirical support for the neuroanatomical localization of TVA computations as outlined in the neuronal interpretation of TVA (NTVA). Furthermore, the results indicate that to understand the biological sources of age-related changes in processing speed and fluid cognition, it may be useful to employ methods that allow for computational fractionation of these multicomponent measures.

We identified neural correlates of declined and preserved basic visual attention functions in aging individuals based on Bundesen "Theory of Visual Attention". In an interindividual difference approach, we contrasted electrophysiology of higher- and lower-performing younger and older participants. In both age groups, the same distinct components indexed performance levels of parameters visual processing speed C and visual short-term memory storage capacity K. The posterior N1 marked interindividual differences in C and the contralateral delay activity marked interindividual differences in K. Moreover, both parameters were selectively related to 2 further event-related potential waves in older age. The anterior N1 was reduced for older participants with lower processing speed, indicating that age-related loss of attentional resources slows encoding. An enhanced right-central positivity was found only for older participants with high storage capacity, suggesting compensatory recruitment for retaining visual short-term memory performance. Together, our results demonstrate that attentional capacity in older age depends on both preservation and successful reorganization of the underlying brain circuits., (Copyright © 2014 Elsevier Inc. All rights reserved.)

An individual's visual attentional capacity is characterized by 2 central processing resources, visual perceptual processing speed and visual short-term memory (vSTM) storage capacity. Based on Bundesen's theory of visual attention (TVA), independent estimates of these parameters can be obtained from mathematical modeling of performance in a whole report task. The framework's neural interpretation (NTVA) further suggests distinct brain mechanisms underlying these 2 functions. Using an interindividual difference approach, the present study was designed to establish the respective ERP correlates of both parameters. Participants with higher compared to participants with lower processing speed were found to show significantly reduced visual N1 responses, indicative of higher efficiency in early visual processing. By contrast, for participants with higher relative to lower vSTM storage capacity, contralateral delay activity over visual areas was enhanced while overall nonlateralized delay activity was reduced, indicating that holding (the maximum number of) items in vSTM relies on topographically specific sustained activation within the visual system. Taken together, our findings show that the 2 main aspects of visual attentional capacity are reflected in separable neurophysiological markers, validating a central assumption of NTVA., (© The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

The attentional weight of a visual object depends on the contrast of the features of the object to its local surroundings (feature contrast) and the relevance of the features to one's goals (feature relevance). We investigated the dependency in partial report experiments with briefly presented stimuli but unspeeded responses. The task was to report the letters from a mixture of letters (targets) and digits (distractors). Color was irrelevant to the task, but many stimulus displays contained an item (target or distractor) in a deviant color (a color singleton). The results showed concurrent effects of feature contrast (color singleton vs. nonsingleton) and relevance (target vs. distractor). A singleton target had a higher probability of being reported than did a nonsingleton target, and a singleton distractor interfered more strongly with report of targets than did a nonsingleton distractor. Measured by use of Bundesen's (1990) computational theory of visual attention, the attentional weight of a singleton object was nearly proportional to the weight of an otherwise similar nonsingleton object, with a factor of proportionality that increased with the strength of the feature contrast of the singleton. This result is explained by generalizing the weight equation of Bundesen's (1990) theory of visual attention such that the attentional weight of an object becomes a product of a bottom-up (feature contrast) and a top-down (feature relevance) component., (PsycINFO Database Record (c) 2013 APA, all rights reserved.)

The theory of visual attention (TVA; Bundesen, 1990. Psychological Review, 97(4), 523-547), allows one to measure distinct visual attention parameters, such as the temporal threshold for visual perception, visual processing capacity, and visual short-term memory (VSTM) capacity. It has long been assumed that visual processing capacity and VSTM capacity parameters are nearly constant from trial to trial. However, Dyrholm, Kyllingsbæk, Espeseth, and Bundesen (2011). Journal of Mathematical Psychology, 55(6), 416-429, found evidence of considerable trial-by-trial variability of VSTM capacity. Here we show that one cause of trial-by-trial variation is that some parameters depend on whether processing of relevant information occurs in only one hemifield or in both hemifields. Our results show that VSTM and visual processing capacities are higher when stimuli are distributed across the hemifields rather than located in the same hemifield. This corresponds to previous suggestions that parallel processing is more efficient across hemifields than within a single hemifield because both hemispheres are involved (e.g., Alvarez & Cavanagh, 2005. Psychological Science, 16(8), 637-643; Kraft et al., 2005. Cognitive Brain Research, 24(1), 453-463). We argue that the established view of a fixed visual attentional capacity must be relativized by taking hemifield distribution into account., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

The intraparietal sulcus (IPS) has been implicated in selective attention as well as visual short-term memory (VSTM). To contrast mechanisms of target selection, distracter filtering, and access to VSTM, we combined behavioral testing, computational modeling and functional magnetic resonance imaging. Sixteen healthy subjects participated in a change detection task in which we manipulated both target and distracter set sizes. We directly compared the IPS response as a function of the number of targets and distracters in the display and in VSTM. When distracters were not present, the posterior and middle segments of IPS showed the predicted asymptotic activity increase with an increasing target set size. When distracters were added to a single target, activity also increased as predicted. However, the addition of distracters to multiple targets suppressed both middle and posterior IPS activities, thereby displaying a significant interaction between the two factors. The interaction between target and distracter set size in IPS could not be accounted for by a simple explanation in terms of number of items accessing VSTM. Instead, it led us to a model where items accessing VSTM receive differential weights depending on their behavioral relevance, and secondly, a suppressive effect originates during the selection phase when multiple targets and multiple distracters are simultaneously present. The reverse interaction between target and distracter set size was significant in the right temporoparietal junction (TPJ), where activity was highest for a single target compared to any other condition. Our study reconciles the role of middle IPS in attentional selection and biased competition with its role in VSTM access., (Copyright © 2012 Elsevier Inc. All rights reserved.)

We present a new algorithm for maximum likelihood convolutive independent component analysis (ICA) in which components are unmixed using stable autoregressive filters determined implicitly by estimating a convolutive model of the mixing process. By introducing a convolutive mixing model for the components, we show how the order of the filters in the model can be correctly detected using Bayesian model selection. We demonstrate a framework for deconvolving a subspace of independent components in electroencephalography (EEG). Initial results suggest that in some cases, convolutive mixing may be a more realistic model for EEG signals than the instantaneous ICA model.

The goal of this paper is to improve on single-trial classification of electro-encephalography (EEG) using linear methods. The paper proposes to combine the classification of the spatial distribution of activity with the classification of its temporal profile. The work is based on the idea that a current source in the brain has a reproducible temporal profile with a static spatial projection to the electrodes. This assumption reduces the parameter space of a linear classifier to a rank-one factorial space. The new model limits over-fitting due to the fewer number of parameters, and furthermore, it allows us to declare a prior belief of smoothness on the spatial and temporal profiles of the source. Our experiments show that the method is useful as a classifier with an area under the ROC curve of 0.93 having only 40 target trials available for training. Investigation of the trained classifier encourages us to belief that the method can also be useful as a tool to interpret the activity in the data at hand with respect to experimental events.