A Primer on Electroencephalography and Event-Related Potentials for Organizational Neuroscience

Retsa

et al. 2020

Preprint

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AbstractAttentional control outside of the laboratory operates in multisensory settings, but the development of mechanisms subserving such control remains poorly understood. We investigated when, over the course of childhood, adult-like attentional control mechanisms begin to emerge. Children aged five, seven, and nine were compared with adults on behavioural performance in a computer game-like multisensory spatial cueing task, while simultaneous 129-channel EEG was recorded. Markers of attentional control were behavioural spatial cueing effects and the N2pc ERP component (analysed both traditionally and using a novel, multivariate electrical neuroimaging framework). In behaviour, adult-like visual attentional control was present from age 7 onwards, whereas multisensory control was not seen in children. In EEG, multivariate analyses of the activity over the N2pc time-window, revealed stable patterns of brain activity in children. Adult activity patterns linked to visual attentional control were present age 7 onwards, mirroring behaviour. Activity patterns linked to multisensory control were found in 9-year-olds, even though such patterns were not noted in behaviour. By combining rigorous yet naturalistic paradigms with multivariate signal analyses, we provided new insights into the development of visual attentional control skills vis-à-vis multisensory attentional control, thus generating a more complete account of attentional development.HighlightsBehaviourally, visual attentional control, as measured by task-set contingent attentional capture, was found to reach an adult-like state as early as age 7Behaviourally, attentional enhancement from multisensory stimuli was not found in 9-year-olds, but their EEG topographic patterns were different for multisensory vs. purely visual distractorsTraditional visual attentional event-related analyses, such as the N2pc, are not sensitive to detect attentional enhancement for multisensory objects in adults, and visual or multisensory attention in childrenSensitive, multivariate analyses of the event-related potential signal, such as electrical neuroimaging, are adept at revealing the neural underpinnings of attentional control processes over development

Section: Data Analysis Designmentioning

confidence: 99%

The development of attentional control mechanisms in multisensory environments

Turoman

Retsa

et al. 2020

Preprint

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“…Fig. 3 in (Tivadar et al, 2019)). Second, multivariate analyses also profit from the added information of high-density recordings.…”

Section: Introductionmentioning

confidence: 97%

“…In biophysical terms, voltages refer to the exertion needed to move charge from one site to another. More practically, this means that voltage is the difference between a "chosen" electrode and a "reference" electrode (Tivadar et al, 2019;Biasiucci et al, 2019). EEG is the measurement of this voltage as it varies in time, and thus results in "time series" across different sites on the scalp.…”

Section: Introductionmentioning

confidence: 99%

“…), as well as other derived and associated measures, including results of statistical contrasts, will change when the reference changes. These facts have generally led to -and to some extent continue to result in-misinterpretation and misuse of EEG data, despite good quality in experimental design (Michel and Murray, 2012;Biasiucci et al, 2019;Tivadar et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Topological Features of Electroencephalography are Reference-Invariant

Billings

Murray

et al. 2020

Preprint

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Electroencephalography (EEG) is among the most widely diffused, inexpensive, and applied neuroimaging techniques. Nonetheless, EEG requires measurements against a reference site(s), which is typically chosen by the experimenter, and specific pre-processing steps precede analysis. It is therefore valuable to obtain quantities that are reference-independent and minimally affected by pre-processing choices. Here, we show that the topological structure of embedding spaces, constructed either from multi-channel EEG timeseries or from their temporal structure, are subject-specific and robust to re-referencing and pre-processing pipelines. By contrast, the shape of correlation spaces, that is, discrete spaces where each point represents an electrode and the distance between them that is in turn related to the correlation between the respective timeseries, were neither significantly subject-specific nor robust to changes of reference. Our results suggest that the shape of spaces describing the observed configurations of EEG signals holds information about the individual specificity of the underlying individual's brain dynamics, and that temporal correlations constrain to a large degree the set of possible dynamics. In turn, these encode the differences between subjects' space of resting state EEG signals. Finally, our results and proposed methodology provide tools to explore the individual topographical landscapes and how they are explored dynamically. We propose therefore to augment conventional topographic analyses with an additional - topological - level of analysis, and to consider them jointly. More generally, these results provide a roadmap for the incorporation of topological analyses within EEG pipelines.

“…Therein, measures relying on the exquisite temporal resolution of EEG have been shedding light on the mechanisms governing joint action and attention and learning in everyday situations (Bevilacqua et al, 2018;Cohen & Parra, 2016;Dikker et al, 2017;Ko et al , 2017;Müller et al, 2018;Tseng et al 2018). The way to fully capitalise on the hardware-and information-level benefits of EEG likely lies in employing signal processing techniques that extract both temporal and reasonably resolved spatial information from EEG data that are also neurobiologically interpretable (Tivadar & Murray, 2018).…”

mentioning

confidence: 99%

Brain and Cognitive Mechanisms of Top–Down Attentional Control in a Multisensory World: Benefits of Electrical Neuroimaging

Matusz

Turoman

Journal of Cognitive Neuroscience

et al. 2019

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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.