Behavioral and EEG Measures Show no Amplifying Effects of Shared Attention on Attention or Memory

Abstract:

Shared attention experiments examine the potential differences in function or behavior when stimuli are experienced alone or in the presence of others, and when simultaneous attention of the participants to the same stimulus or set is involved. Previous work has found enhanced reactions to emotional stimuli in social situations, yet these changes might represent enhanced communicative or motivational purposes. This study examines whether viewing emotional stimuli in the presence of another person influences attention to or memory for the stimulus. Participants passively viewed emotionally-valenced stimuli while completing another task (counting flowers). Each participant performed this task both alone and in a shared attention condition (simultaneously with another person in the same room) while EEG signals were measured. Recognition of the emotional pictures was later measured. A significant shared attention behavioral effect was found in the attention task but not in the recognition task. Compared to event-related potential responses for neutral pictures, we found higher P3b response for task relevant stimuli (flowers), and higher Late Positive Potential (LPP) responses for emotional stimuli. However, no main effect was found for shared attention between presence conditions. To conclude, shared attention may therefore have a more limited effect on cognitive processes than previously suggested.

Authors:

• Noam Mairon

• Mor Nahum

• Arjen Stolk

• Robert T Knight

• Anat Perry

Date: 2020

DOI: 10.1038/s41598-020-65311-7

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The brain tracks auditory rhythm predictability independent of selective attention

Abstract:

The brain responds to violations of expected rhythms, due to extraction- and prediction of the temporal structure in auditory input. Yet, it is unknown how probability of rhythm violations affects the overall rhythm predictability. Another unresolved question is whether predictive processes are independent of attention processes. In this study, EEG was recorded while subjects listened to rhythmic sequences. Predictability was manipulated by changing the stimulus-onset-asynchrony (SOA deviants) for given tones in the rhythm. When SOA deviants were inserted rarely, predictability remained high, whereas predictability was lower with more frequent SOA deviants. Dichotic tone-presentation allowed for independent manipulation of attention, as specific tones of the rhythm were presented to separate ears. Attention was manipulated by instructing subjects to attend to tones in one ear only, while keeping the rhythmic structure of tones constant. The analyses of event-related potentials revealed an attenuated N1 for tones when rhythm predictability was high, while the N1 was enhanced by attention to tones. Bayesian statistics revealed no interaction between predictability and attention. A right-lateralization of attention effects, but not predictability effects, suggested potentially different cortical processes. This is the first study to show that probability of rhythm violation influences rhythm predictability, independent of attention.

Authors:

• Maja D Foldal

• Alejandro O Blenkmann

• Anaïs Llorens

• Robert T Knight

• Anne-Kristin Solbakk

• Tor Endestad

Date: 2020

DOI: https://doi.org/10.1038/s41598-020-64758-y

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Using Coherence-based spectro-spatial filters for stimulus features prediction from electro-corticographic recordings

Abstract:

The traditional approach in neuroscience relies on encoding models where brain responses are related to different stimuli in order to establish dependencies. In decoding tasks, on the contrary, brain responses are used to predict the stimuli, and traditionally, the signals are assumed stationary within trials, which is rarely the case for natural stimuli. We hypothesize that a decoding model assuming each experimental trial as a realization of a random process more likely reflects the statistical properties of the undergoing process compared to the assumption of stationarity. Here, we propose a Coherence-based spectro-spatial filter that allows for reconstructing stimulus features from brain signal’s features. The proposed method extracts common patterns between features of the brain signals and the stimuli that produced them. These patterns, originating from different recording electrodes are combined, forming a spatial filter that produces a unified prediction of the presented stimulus. This approach takes into account frequency, phase, and spatial distribution of brain features, hence avoiding the need to predefine specific frequency bands of interest or phase relationships between stimulus and brain responses manually. Furthermore, the model does not require the tuning of hyper-parameters, reducing significantly the computational load attached to it. Using three different cognitive tasks (motor movements, speech perception, and speech production), we show that the proposed method consistently improves stimulus feature predictions in terms of correlation (group averages of 0.74 for motor movements, 0.84 for speech perception, and 0.74 for speech production) in comparison with other methods based on regularized multivariate regression, probabilistic graphical models and artificial neural networks. Furthermore, the model parameters revealed those anatomical regions and spectral components that were discriminant in the different cognitive tasks. This novel method does not only provide a useful tool to address fundamental neuroscience questions, but could also be applied to neuroprosthetics.

Authors:

• Jaime Delgado Saa

• Andy Christen

• Stephanie Martin

• Brian N Pasley

• Robert T Knight

• Anne-Lise Giraud

Date: 2020

DOI: https://doi.org/10.1038/s41598-020-63303-1

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Comparison between a wireless dry electrode EEG system with a conventional wired wet electrode EEG system for clinical applications

Abstract:

Dry electrode electroencephalogram (EEG) recording combined with wireless data transmission offers an alternative tool to conventional wet electrode EEG systems. However, the question remains whether the signal quality of dry electrode recordings is comparable to wet electrode recordings in the clinical context. We recorded the resting state EEG (rsEEG), the visual evoked potentials (VEP) and the visual P300 (P3) from 16 healthy subjects (age range: 26–79 years) and 16 neurological patients who reported subjective memory impairment (age range: 50–83 years). Each subject took part in two recordings on different days, one with 19 dry electrodes and another with 19 wet electrodes. They reported their preferred EEG system. Comparisons of the rsEEG recordings were conducted qualitatively by independent visual evaluation by two neurologists blinded to the EEG system used and quantitatively by spectral analysis of the rsEEG. The P100 visual evoked potential (VEP) and P3 event-related potential (ERP) were compared in terms of latency, amplitude and pre-stimulus noise. The majority of subjects preferred the dry electrode headset. Both neurologists reported that all rsEEG traces were comparable between the wet and dry electrode headsets. Absolute Alpha and Beta power during rest did not statistically differ between the two EEG systems (p > 0.05 in all cases). However, Theta and Delta power was slightly higher with the dry electrodes (p = 0.0004 for Theta and p < 0.0001 for Delta). For ERPs, the mean latencies and amplitudes of the P100 VEP and P3 ERP showed comparable values (p > 0.10 in all cases) with a similar spatial distribution for both wet and dry electrode systems. These results suggest that the signal quality, ease of set-up and portability of the dry electrode EEG headset used in our study comply with the needs of clinical applications.

Authors:

• Hermann Hinrichs

• Michael Scholz

• Anne Katrin Baum

• Julia WY Kam

• Robert T Knight

• Hans-Jochen Heinze

Date: 2020

DOI: https://doi.org/10.1038/s41598-020-62154-0

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