scholarly journals Decoding the covert shift of spatial attention from electroencephalographic signals permits reliable control of a brain-computer interface

2020 ◽  
Author(s):  
Christoph Reichert ◽  
Stefan Dürschmid ◽  
Mandy V. Bartsch ◽  
Jens-Max Hopf ◽  
Hans-Jochen Heinze ◽  
...  
Keyword(s):  
Event Related Potentials ◽  
Right Visual Field ◽  
Spatial Filters ◽  
Computer Interfaces ◽  
Eeg Data ◽  
Related Potentials ◽  
Left And Right ◽  
Viable Approach ◽  
Number Of Classes ◽  
Electroencephalogram Eeg

AbstractObjectiveOne of the main goals of brain-computer interfaces (BCI) is to restore communication abilities in patients. BCIs often use event-related potentials (ERPs) like the P300 which signals the presence of a target in a stream of stimuli. The P300 and related approaches, however, are inherently limited, as they require many stimulus presentations to obtain a usable control signal. Many approaches depend on gaze-direction to focus the target, which is also not a viable approach in many cases, because eye movements might be impaired in potential users. Here we report on a BCI that avoids both shortcomings by decoding spatial target information, independent of gaze shifts.ApproachWe present a new method to decode from the electroencephalogram (EEG) covert shifts of attention to one out of four targets simultaneously presented in the left and right visual field. The task is designed to evoke the N2pc component – a hemisphere lateralized response, elicited over the occipital scalp contralateral to the attended target. The decoding approach involves decoding of the N2pc based on data-driven estimation of spatial filters and a correlation measure.Main resultsDespite variability of decoding performance across subjects, 22 out of 24 subjects performed well above chance level. Six subjects even exceeded 80% (cross-validated: 89%) correct predictions in a four-class discrimination task. Hence, the single-trial N2pc proves to be a component that allows for reliable BCI control. An offline analysis of the EEG data with respect to their dependence on stimulation time and number of classes demonstrates that the present method is also a workable approach for two-class tasks.SignificanceOur method extends the range of strategies for gaze-independent BCI control. The proposed decoding approach has the potential to be efficient in similar applications intended to decode ERPs.

Electroencephalogram Recording in Humans

2015 ◽  
Author(s):  
Julia W. Y. Kam ◽  
Todd C. Handy
Keyword(s):  
Data Acquisition ◽  
Event Related Potentials ◽  
Cellular Mechanisms ◽  
Presentation Software ◽  
Eeg Data ◽  
Scientific Papers ◽  
Related Potentials ◽  
Definition Of ◽  
Data Acquisition And Processing ◽  
Electroencephalogram Eeg

This chapter provides an elementary introduction to the theory and practical application of electroencephalogram (EEG) recording for the purpose of studying neurocognitive processes. It is aimed at readers who have had little or no experience in EEG data collection, and would like to gain a better understanding of scientific papers employing this methodology or start their own EEG experiment. We begin with a definition of EEG, and a summary of the strengths and limitations of EEG-based techniques. Following this is a description of the basic theory concerning the cellular mechanisms underlying EEG, as well as two types of data generated by EEG recording. We then present a brief summary of the equipment necessary for EEG data acquisition and important considerations for presentation software. Finally, we provide an overview of the protocol for data acquisition and processing, as well as methods for quantifying both EEG and event-related potentials data.

scholarly journals Eliciting and Recording Event Related Potentials (ERPs) in Behaviourally Unresponsive Populations: A Retrospective Commentary on Critical Factors

2021 ◽  
Vol 11 (7) ◽  
pp. 835
Author(s):  
Alexander Rokos ◽  
Richard Mah ◽  
Rober Boshra ◽  
Amabilis Harrison ◽  
Tsee Leng Choy ◽  
...  
Keyword(s):  
Event Related Potentials ◽  
Stimulus Presentation ◽  
Event Related Potential ◽  
Critical Factors ◽  
Healthy Elderly ◽  
States Of Consciousness ◽  
Long Latency ◽  
Eeg Data ◽  
Related Potentials ◽  
The Relationship

A consistent limitation when designing event-related potential paradigms and interpreting results is a lack of consideration of the multivariate factors that affect their elicitation and detection in behaviorally unresponsive individuals. This paper provides a retrospective commentary on three factors that influence the presence and morphology of long-latency event-related potentials—the P3b and N400. We analyze event-related potentials derived from electroencephalographic (EEG) data collected from small groups of healthy youth and healthy elderly to illustrate the effect of paradigm strength and subject age; we analyze ERPs collected from an individual with severe traumatic brain injury to illustrate the effect of stimulus presentation speed. Based on these critical factors, we support that: (1) the strongest paradigms should be used to elicit event-related potentials in unresponsive populations; (2) interpretation of event-related potential results should account for participant age; and (3) speed of stimulus presentation should be slower in unresponsive individuals. The application of these practices when eliciting and recording event-related potentials in unresponsive individuals will help to minimize result interpretation ambiguity, increase confidence in conclusions, and advance the understanding of the relationship between long-latency event-related potentials and states of consciousness.

scholarly journals Reduced Visual Magnocellular Event-Related Potentials in Developmental Dyslexia

2021 ◽  
Vol 11 (1) ◽  
pp. 48
Author(s):  
John Stein
Keyword(s):  
Steady State ◽  
Developmental Dyslexia ◽  
Reading Ability ◽  
Event Related Potentials ◽  
Black And White ◽  
Reverse Pattern ◽  
Related Potentials ◽  
The Right ◽  
Visual Hemifields ◽  
Electroencephalogram Eeg

(1) Background—the magnocellular hypothesis proposes that impaired development of the visual timing systems in the brain that are mediated by magnocellular (M-) neurons is a major cause of dyslexia. Their function can now be assessed quite easily by analysing averaged visually evoked event-related potentials (VERPs) in the electroencephalogram (EEG). Such analysis might provide a useful, objective biomarker for diagnosing developmental dyslexia. (2) Methods—in adult dyslexics and normally reading controls, we recorded steady state VERPs, and their frequency content was computed using the fast Fourier transform. The visual stimulus was a black and white checker board whose checks reversed contrast every 100 ms. M- cells respond to this stimulus mainly at 10 Hz, whereas parvocells (P-) do so at 5 Hz. Left and right visual hemifields were stimulated separately in some subjects to see if there were latency differences between the M- inputs to the right vs. left hemispheres, and these were compared with the subjects’ handedness. (3) Results—Controls demonstrated a larger 10 Hz than 5 Hz fundamental peak in the spectra, whereas the dyslexics showed the reverse pattern. The ratio of subjects’ 10/5 Hz amplitudes predicted their reading ability. The latency of the 10 Hz peak was shorter during left than during right hemifield stimulation, and shorter in controls than in dyslexics. The latter correlated weakly with their handedness. (4) Conclusion—Steady state visual ERPs may conveniently be used to identify developmental dyslexia. However, due to the limited numbers of subjects in each sub-study, these results need confirmation.

scholarly journals Anytime collaborative brain–computer interfaces for enhancing perceptual group decision-making

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Saugat Bhattacharyya ◽  
Davide Valeriani ◽  
Caterina Cinel ◽  
Luca Citi ◽  
Riccardo Poli
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Brain Activity ◽  
Event Related Potentials ◽  
Brain Computer Interfaces ◽  
Appearance Time ◽  
Perceptual Group ◽  
Computer Interfaces ◽  
Related Potentials

AbstractIn this paper we present, and test in two realistic environments, collaborative Brain-Computer Interfaces (cBCIs) that can significantly increase both the speed and the accuracy of perceptual group decision-making. The key distinguishing features of this work are: (1) our cBCIs combine behavioural, physiological and neural data in such a way as to be able to provide a group decision at any time after the quickest team member casts their vote, but the quality of a cBCI-assisted decision improves monotonically the longer the group decision can wait; (2) we apply our cBCIs to two realistic scenarios of military relevance (patrolling a dark corridor and manning an outpost at night where users need to identify any unidentified characters that appear) in which decisions are based on information conveyed through video feeds; and (3) our cBCIs exploit Event-Related Potentials (ERPs) elicited in brain activity by the appearance of potential threats but, uniquely, the appearance time is estimated automatically by the system (rather than being unrealistically provided to it). As a result of these elements, in the two test environments, groups assisted by our cBCIs make both more accurate and faster decisions than when individual decisions are integrated in more traditional manners.

scholarly journals Towards an Accessible Use of a Brain-Computer Interfaces-Based Home Care System through a Smartphone

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Koun-Tem Sun ◽  
Kai-Lung Hsieh ◽  
Syuan-Rong Syu
Keyword(s):  
Home Care ◽  
Event Related Potentials ◽  
End Users ◽  
Disabled People ◽  
Eeg Signals ◽  
Computer Interfaces ◽  
Related Potentials ◽  
The One ◽  
The Brain ◽  
Care System

This study proposes a home care system (HCS) based on a brain-computer interface (BCI) with a smartphone. The HCS provides daily help to motor-disabled people when a caregiver is not present. The aim of the study is two-fold: (1) to develop a BCI-based home care system to help end-users control their household appliances, and (2) to assess whether the architecture of the HCS is easy for motor-disabled people to use. A motion-strip is used to evoke event-related potentials (ERPs) in the brain of the user, and the system immediately processes these potentials to decode the user’s intentions. The system, then, translates these intentions into application commands and sends them via Bluetooth to the user’s smartphone to make an emergency call or to execute the corresponding app to emit an infrared (IR) signal to control a household appliance. Fifteen healthy and seven motor-disabled subjects (including the one with ALS) participated in the experiment. The average online accuracy was 81.8% and 78.1%, respectively. Using component N2P3 to discriminate targets from nontargets can increase the efficiency of the system. Results showed that the system allows end-users to use smartphone apps as long as they are using their brain waves. More important, only one electrode O1 is required to measure EEG signals, giving the system good practical usability. The HCS can, thus, improve the autonomy and self-reliance of its end-users.

SYNCHRONIZATION MEASURES OF THE SCALP ELECTROENCEPHALOGRAM CAN DISCRIMINATE HEALTHY FROM ALZHEIMER'S SUBJECTS

2007 ◽  
Vol 17 (02) ◽  
pp. 61-69 ◽  
Author(s):  
MARK A. KRAMER ◽  
FEN-LEI CHANG ◽  
MAURICE E. COHEN ◽  
DONNA HUDSON ◽  
ANDREW J. SZERI
Keyword(s):  
Cognitive Impairment ◽  
Healthy Subjects ◽  
Phase Synchronization ◽  
Eyes Closed ◽  
Eeg Data ◽  
Two Measures ◽  
Left And Right ◽  
Scalp Electroencephalogram ◽  
Occipital Lobes ◽  
Electroencephalogram Eeg

Three synchronization measures are applied to scalp electroencephalogram (EEG) data collected from 20 patients diagnosed to have either: (1) no dementia, (2) mild cognitive impairment (MCI), or (3) Alzheimer's disease (AD). We apply the three synchronization measures — the phase synchronization, and two measures of nonlinear interdependency — to the data collected from awake patients resting with eyes closed. We show that the synchronization in potential between electrodes near the left and right occipital lobes provides a statistically significant discriminant between the healthy and AD subjects, and the MCI and AD subjects. None of the three measures appears able to distinguish between the healthy and MCI subjects, although MCI subjects show synchronization values intermediate between healthy subjects (with high synchronization values) and AD subjects (with low synchronization values) on average.

scholarly journals How Social Power Affects the Processing of Angry Expressions: Evidence From Behavioral and Electrophysiological Data

2021 ◽  
Vol 11 ◽  
Author(s):  
Entao Zhang ◽  
Xueling Ma ◽  
Ruiwen Tao ◽  
Tao Suo ◽  
Huang Gu ◽  
...  
Keyword(s):  
Low Power ◽  
High Power ◽  
Late Stage ◽  
Social Power ◽  
Event Related Potentials ◽  
Oddball Paradigm ◽  
Neural Responses ◽  
Target Power ◽  
Related Potentials ◽  
Electroencephalogram Eeg

With the help of event-related potentials (ERPs), the present study used an oddball paradigm to investigate how both individual and target power modulate neural responses to angry expressions. Specifically, participants were assigned into a high-power or low-power condition. Then, they were asked to detect a deviant angry expression from a high-power or low-power target among a series of neutral expressions, while behavioral responses and electroencephalogram (EEG) were recorded. The behavioral results showed that high-power individuals responded faster to detect angry expressions than low-power individuals. The ERP analysis showed that high-power individuals showed larger P3 amplitudes in response to angry expressions than low-power individuals did. Target power increased the amplitudes of the P1, VPP, N3, and P3 in response to angry expressions did, but decreased the amplitudes of the N1 and N170 in response to angry expressions. The present study extended previous studies by showing that having more power could enhance individuals’ neural responses to angry expressions in the late-stage processes, and individuals could show stronger neural responses to angry expressions from high-power persons in both the early‐ and late-stage processes.

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