EEG and behavioral correlates of attentional processing while walking and navigating naturalistic environments

Liebherr, Magnus; Corcoran, Andrew W.; Alday, Phillip M.; Coussens, Scott; Bellan, Valeria; Howlett, Caitlin A.; Immink, Maarten A.; Köhler, Manfred; Schlesewsky, Matthias

doi:10.1038/s41598-021-01772-8

Cited by 25 publications

(15 citation statements)

References 64 publications

(65 reference statements)

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“…Mobile whole-head EEG applications have made great strides in the past decade, recently being applied to study memory [5][6][7] , emotion 8,9 , attention 10,11 and movement [12][13][14] in complex real-world settings. Advances in hardware and software have made fully mobile high-density EEG a useful tool for cognitive neuroscience 15,16 , however, what remains problematic is the ability to flexibly manipulate key variables, as now our cognitive variables of interest are part of the real world.…”

Section: Towards Real-world Neuroscience Using Mobile Eeg and Augment...mentioning

confidence: 99%

Towards real-world neuroscience using mobile EEG and augmented reality

Krugliak

Clarke

2022

Sci Rep

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Our visual environment impacts multiple aspects of cognition including perception, attention and memory, yet most studies traditionally remove or control the external environment. As a result, we have a limited understanding of neurocognitive processes beyond the controlled lab environment. Here, we aim to study neural processes in real-world environments, while also maintaining a degree of control over perception. To achieve this, we combined mobile EEG (mEEG) and augmented reality (AR), which allows us to place virtual objects into the real world. We validated this AR and mEEG approach using a well-characterised cognitive response—the face inversion effect. Participants viewed upright and inverted faces in three EEG tasks (1) a lab-based computer task, (2) walking through an indoor environment while seeing face photographs, and (3) walking through an indoor environment while seeing virtual faces. We find greater low frequency EEG activity for inverted compared to upright faces in all experimental tasks, demonstrating that cognitively relevant signals can be extracted from mEEG and AR paradigms. This was established in both an epoch-based analysis aligned to face events, and a GLM-based approach that incorporates continuous EEG signals and face perception states. Together, this research helps pave the way to exploring neurocognitive processes in real-world environments while maintaining experimental control using AR.

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Section: Towards Real-world Neuroscience Using Mobile Eeg and Augment...mentioning

confidence: 99%

Towards real-world neuroscience using mobile EEG and augmented reality

Krugliak

Clarke

2022

Sci Rep

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“…2017 ). Random intercepts were also specified for sentence items in all models; EEG electrode channel locations were included as random intercepts in the spectral power models only (see Liebherr et al. 2021 , for a similar approach).…”

Section: Discussionmentioning

confidence: 99%

Expectations boost the reconstruction of auditory features from electrophysiological responses to noisy speech

et al. 2022

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Online speech processing imposes significant computational demands on the listening brain, the underlying mechanisms of which remain poorly understood. Here, we exploit the perceptual “pop-out” phenomenon (i.e. the dramatic improvement of speech intelligibility after receiving information about speech content) to investigate the neurophysiological effects of prior expectations on degraded speech comprehension. We recorded electroencephalography (EEG) and pupillometry from 21 adults while they rated the clarity of noise-vocoded and sine-wave synthesized sentences. Pop-out was reliably elicited following visual presentation of the corresponding written sentence, but not following incongruent or neutral text. Pop-out was associated with improved reconstruction of the acoustic stimulus envelope from low-frequency EEG activity, implying that improvements in perceptual clarity were mediated via top-down signals that enhanced the quality of cortical speech representations. Spectral analysis further revealed that pop-out was accompanied by a reduction in theta-band power, consistent with predictive coding accounts of acoustic filling-in and incremental sentence processing. Moreover, delta-band power, alpha-band power, and pupil diameter were all increased following the provision of any written sentence information, irrespective of content. Together, these findings reveal distinctive profiles of neurophysiological activity that differentiate the content-specific processes associated with degraded speech comprehension from the context-specific processes invoked under adverse listening conditions.

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“…This is an open data set available at https://openneuro.org/datasets/ ds003620/versions/1.0.2 (Liebherr et al, 2021)…”

Section: Eeg Study Imentioning

confidence: 99%

Zapline‐plus: A Zapline extension for automatic and adaptive removal of frequency‐specific noise artifacts in M/EEG

Klug

Kloosterman

2022

Human Brain Mapping

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Removing power line noise and other frequency‐specific artifacts from electrophysiological data without affecting neural signals remains a challenging task. Recently, an approach was introduced that combines spectral and spatial filtering to effectively remove line noise: Zapline. This algorithm, however, requires manual selection of the noise frequency and the number of spatial components to remove during spatial filtering. Moreover, it assumes that noise frequency and spatial topography are stable over time, which is often not warranted. To overcome these issues, we introduce Zapline‐plus, which allows adaptive and automatic removal of frequency‐specific noise artifacts from M/electroencephalography (EEG) and LFP data. To achieve this, our extension first segments the data into periods (chunks) in which the noise is spatially stable. Then, for each chunk, it searches for peaks in the power spectrum, and finally applies Zapline. The exact noise frequency around the found target frequency is also determined separately for every chunk to allow fluctuations of the peak noise frequency over time. The number of to‐be‐removed components by Zapline is automatically determined using an outlier detection algorithm. Finally, the frequency spectrum after cleaning is analyzed for suboptimal cleaning, and parameters are adapted accordingly if necessary before re‐running the process. The software creates a detailed plot for monitoring the cleaning. We highlight the efficacy of the different features of our algorithm by applying it to four openly available data sets, two EEG sets containing both stationary and mobile task conditions, and two magnetoencephalography sets containing strong line noise.

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EEG and behavioral correlates of attentional processing while walking and navigating naturalistic environments

Cited by 25 publications

References 64 publications

Towards real-world neuroscience using mobile EEG and augmented reality

Towards real-world neuroscience using mobile EEG and augmented reality

Expectations boost the reconstruction of auditory features from electrophysiological responses to noisy speech

Zapline‐plus: A Zapline extension for automatic and adaptive removal of frequency‐specific noise artifacts in M/EEG

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