Advances in Electrical Neuroimaging, Brain Networks and Neurofeedback Protocols

Human EEG biofeedback (neurofeedback) started in the 1940s using 1 EEG recording channel, then to 4 channels in the 1990s. New advancements in electrical neuroimaging expanded EEG biofeedback to 19 channels using Low Resolution Electromagnetic Tomography (LORETA) three-dimensional current sources of the EEG. In 2004–2006 the concept of a “real-time” comparison of the EEG to a healthy reference database was developed and tested using surface EEG z-score neurofeedback based on a statistical bell curve called “real-time” z-scores. The “real-time” or “live” normative reference database comparison was developed to help reduce the uncertainty of what threshold to select to activate a feedback signal and to unify all EEG measures to a single value, i.e., the distance from the mean of an age matched reference sample. In 2009 LORETA z-score neurofeedback further increased the specificity by targeting brain network hubs referred to as Brodmann areas. A symptom check list program to help link symptoms to dysregulation of brain networks based on fMRI and PET and neurology was created in 2009. The symptom checklist and NIH based networks linking symptoms to brain networks grew out of the human brain mapping program starting in 1990 which is continuing today. A goal is to increase specificity of EEG biofeedback by targeting brain network hubs and connections between hubs likely linked to the patient’s symptoms. New advancements in electrical neuroimaging introduced in 2017 provide increased resolution of three-dimensional source localization with 12,700 voxels using swLORETA with the capacity to conduct cerebellar neurofeedback and neurofeedback of subcortical brain hubs such as the thalamus, amygdala and habenula. Future applications of swLORETA z-score neurofeedback represents another example of the transfer of knowledge gained by the human brain mapping initiatives to further aid in helping people with cognition problems as well as balance problems and parkinsonism. A brief review of the past, present and future predictions of z-score neurofeedback are discussed with special emphasis on new developments that point toward a bright and enlightened future in the field of EEG biofeedback.

Uncovering the mechanisms of real-world attentional control over the course of primary education

Schooling may shape children’s abilities to control their attention, but it is unclear if this impact extends from control over visual objects to encompass multisensory objects, which are more typical of everyday environments. We compared children across three primary school grades (Swiss 1st, 3rd, and 5th grade) on their performance on a computer game-like audio-visual attentional control task, while recording their EEG. Behavioural markers of visual attentional control were present from 3rd grade (after 2 years of schooling), whereas multisensory attentional control was not detected in any group. However, multivariate whole-brain EEG analyses (‘electrical neuroimaging’) revealed stable patterns of brain activity that indexed both types of attentional control – visual control in all groups, and multisensory attentional control – from 3rd grade onwards. Our findings suggest that using multivariate EEG approaches can uncover otherwise undetectable mechanisms of attentional control over visual and multisensory objects and characterise how they differ at different educational stages.Lay AbstractWe measured how visual and audiovisual distractors differ in capturing attention of 1st- to 5th-graders while recording the children’s brain activity. Brain activity results showed that all children were sensitive to visual distraction, and from 3rd grade onwards, children were also sensitive to audiovisual distraction. These results deepen our understanding of how school children control their attention in everyday environments, which are made up of information that stimulates multiple senses at a time.

How we pay attention in naturalistic settings

Research on attentional control has largely focused on single senses and the importance of one s behavioural goals in controlling attention. However, everyday situations are multisensory and contain regularities, both likely influencing attention. We investigated how visual attentional capture is simultaneously impacted by top-down goals, multisensory nature of stimuli, and contextual factors of stimulus semantic relationship and predictability. Participants performed a multisensory version of the Folk et al., (1992) spatial cueing paradigm, searching for a target of a predefined colour (e.g. a red bar) within an array preceded by a distractor. We manipulated: 1) stimulus goal-relevance via distractor s colour (matching vs. mismatching the target), 2) stimulus multisensory nature (colour distractors appearing alone vs. with tones), 3) relationship between the distractor sound and colour (arbitrary vs. semantically congruent) and 4) predictability of the distractor onset. Reaction-time spatial cueing served as a behavioural measure of attentional selection. We also recorded 129-channel event-related potentials (ERPs), analysing the distractor elicited N2pc component both canonically and using a multivariate electrical neuroimaging (EN) framework. Behaviourally, arbitrary target-matching distractors captured attention more strongly than semantically congruent ones, with no evidence for context modulating multisensory enhancements of capture. Notably, EN analyses revealed context-based influences on attention to both visual and multisensory distractors, in how strongly they activated the brain and type of activated brain networks. In both cases, these context-driven brain response modulations occurred long before the N2pc timewindow, with network-based modulations at app. 30ms, followed by strength-based modulations at app. 100ms post-distractor. This points to meaning being a second source, next to predictions, of contextual information facilitating goal-directed behaviour. More broadly, in everyday situations, attentional is controlled by an interplay between one s goals, stimulus perceptual salience and stimulus meaning and predictability. Our study calls for a revision of attentional control theories to account for the role of contextual and multisensory control.

The development of attentional control mechanisms in multisensory environments

Outside the laboratory, people need to pay attention to relevant objects that are typically multisensory, but it remains poorly understood how the underlying neurocognitive mechanisms develop. We investigated when adult-like mechanisms controlling one’s attentional selection of visual and multisensory objects emerge across childhood. Five-, 7-, and 9-year-olds were compared with adults in their performance on a computer game-like multisensory spatial cueing task, while 129-channel EEG was simultaneously recorded. Markers of attentional control were behavioural spatial cueing effects and the N2pc ERP component (analysed traditionally and using a multivariate electrical neuroimaging framework). In behaviour, adult-like visual attentional control was present from age 7 onwards, whereas multisensory control was absent in all children groups. In EEG, multivariate analyses of the activity over the N2pc time-window revealed stable brain activity patterns in children. Adult-like visual-attentional control EEG patterns were present age 7 onwards, while multisensory control activity patterns were found in 9-year-olds (albeit behavioural measures showed no effects). By combining rigorous yet naturalistic paradigms with multivariate signal analyses, we demonstrated that visual attentional control seems to reach an adult-like state at ~7 years, before adult-like multisensory control, emerging at ~9 years. These results enrich our understanding of how attention in naturalistic settings develops.HighlightsBy age 7, children showed adult-like task-set contingent attentional capture in behaviourChildren’s behavioural data did not show evidence for attentional enhancement for multisensory objects, but 9-year-olds’ EEG topographic patterns elicited by multisensory vs. purely visual distractors differed reliablyTraditional visual attentional event-related potential (ERP) analyses, such as the N2pc, did not detect attentional enhancement for multisensory objects in adults, and visual or multisensory attention in childrenMultivariate analyses of ERPs, such as electrical neuroimaging, are more sensitive to the change of attentional control processes over development

QEEG as a Useful Tool for the Evaluation of Early Cognitive Changes in Dementia and Traumatic Brain Injury

Quantitative electroencephalography (QEEG)-electrical neuroimaging has been underutilized in general neurology practice. Recent advances in computer technology have made this electrophysiological testing relatively inexpensive as well as precise in identifying brain areas with electrical dysfunction related to either traumatic injury or neurodegenerative process. In this article, the author presents 2 cases that can be frequently encountered in every general neurological practice: case of early dementia and traumatic brain injury. The clinical usefulness of QEEG is demonstrated by showing evidence of electrical abnormalities and networks dysfunctions (including an elevation of frontal/temporal delta and theta powers as well as abnormalities in functional connectivity). In addition, the correlation of QEEG and findings from structural imaging technique—magnetic resonance imaging diffusion tensor imaging and another functional imaging—positron emission tomography is presented.