Electrical Neuroimaging Reveals Timing of Attentional Control in Human Brain

2007 ◽  
Author(s):  
John J. McDonald ◽  
Jessica J. Green
Author(s):  
Robert W. Thatcher ◽  
Carl J. Biver ◽  
Ernesto Palermero Soler ◽  
Joel Lubar ◽  
J. Lucas Koberda

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.


Author(s):  
Nora Turoman ◽  
Ruxandra I. Tivadar ◽  
Chrysa Retsa ◽  
Anne M. Maillard ◽  
Gaia Scerif ◽  
...  

AbstractSchooling 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.


2019 ◽  
Vol 31 (3) ◽  
pp. 412-430 ◽  
Author(s):  
Pawel J. Matusz ◽  
Nora Turoman ◽  
Ruxandra I. Tivadar ◽  
Chrysa Retsa ◽  
Micah M. Murray

In real-world environments, information is typically multisensory, and objects are a primary unit of information processing. Object recognition and action necessitate attentional selection of task-relevant from among task-irrelevant objects. However, the brain and cognitive mechanisms governing these processes remain not well understood. Here, we demonstrate that attentional selection of visual objects is controlled by integrated top–down audiovisual object representations (“attentional templates”) while revealing a new brain mechanism through which they can operate. In multistimulus (visual) arrays, attentional selection of objects in humans and animal models is traditionally quantified via “the N2pc component”: spatially selective enhancements of neural processing of objects within ventral visual cortices at approximately 150–300 msec poststimulus. In our adaptation of Folk et al.'s [Folk, C. L., Remington, R. W., & Johnston, J. C. Involuntary covert orienting is contingent on attentional control settings. Journal of Experimental Psychology: Human Perception and Performance, 18, 1030–1044, 1992] spatial cueing paradigm, visual cues elicited weaker behavioral attention capture and an attenuated N2pc during audiovisual versus visual search. To provide direct evidence for the brain, and so, cognitive, mechanisms underlying top–down control in multisensory search, we analyzed global features of the electrical field at the scalp across our N2pcs. In the N2pc time window (170–270 msec), color cues elicited brain responses differing in strength and their topography. This latter finding is indicative of changes in active brain sources. Thus, in multisensory environments, attentional selection is controlled via integrated top–down object representations, and so not only by separate sensory-specific top–down feature templates (as suggested by traditional N2pc analyses). We discuss how the electrical neuroimaging approach can aid research on top–down attentional control in naturalistic, multisensory settings and on other neurocognitive functions in the growing area of real-world neuroscience.


2014 ◽  
Vol 10 (3) ◽  
pp. 253-267 ◽  
Author(s):  
Yiwen Wang ◽  
Liang Huang ◽  
Wei Zhang ◽  
Zhen Zhang ◽  
Stephanie Cacioppo

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