2010
DOI: 10.1016/j.neuroimage.2010.04.250
|View full text |Cite
|
Sign up to set email alerts
|

Tonic and phasic EEG and behavioral changes induced by arousing feedback

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

7
93
1

Year Published

2010
2010
2019
2019

Publication Types

Select...
6
2
1

Relationship

1
8

Authors

Journals

citations
Cited by 76 publications
(101 citation statements)
references
References 57 publications
7
93
1
Order By: Relevance
“…Since central electrodes were assessed and since SON is known to be more attention-grabbing than any other name -in respect to the seminal work of Moray (1959), the differential effects in the alpha range are very reasonable. Lower amplitudes in the alpha range can also be detected for targets in oddball tasks in which subjects are requested to respond to a target (Ishii et al, 2009;Mazaheri and Picton, 2005), and in general for arousing stimuli and alertness (Li et al, 2010;Makeig and Inlow, 2005). However, the reported effect was assessed on group level, only.…”
Section: Introductionmentioning
confidence: 99%
“…Since central electrodes were assessed and since SON is known to be more attention-grabbing than any other name -in respect to the seminal work of Moray (1959), the differential effects in the alpha range are very reasonable. Lower amplitudes in the alpha range can also be detected for targets in oddball tasks in which subjects are requested to respond to a target (Ishii et al, 2009;Mazaheri and Picton, 2005), and in general for arousing stimuli and alertness (Li et al, 2010;Makeig and Inlow, 2005). However, the reported effect was assessed on group level, only.…”
Section: Introductionmentioning
confidence: 99%
“…During the first 5 minutes, subjects were asked to stay alert and the average RT of these short-RT (presumably alert) trials was computed. During the rest of the experiments, if subjects' reaction times were over three times the mean RT (1.51~2.54 s, depending on subjects), the system triggered a 1,750 Hz tone-burst to the subject in half of these drowsy trials [26]. The lane-departure event after the "current trial" was labeled as the "next trial".…”
Section: Methodsmentioning
confidence: 99%
“…Three time points immediately following the feedback onset and eleven extra time points between 5 and 15 times the mean RTs, all normalized to the averaged power spectrum of the first 3 time points, were used as inputs to machine learning algorithms to estimate the efficacy of the arousing feedback, judged by the RTs of the next trials. Note that all time points preceded the onsets of next lane-deviation events and were thus not affected by the phasic spectral changes induced by the events [26]. The resultant EEG feature for each time point consisted of 37 estimates of log EEG power (frequencies between 2 and 20 Hz, spacing at 0.5Hz) and the dimension of the time-frequency matrix was 14 by 37.…”
Section: F Eeg Pattern Recognitionmentioning
confidence: 99%
“…3) include a wireless transmission module and a chargeable battery, which allow recordings to be made without being tethered to a computer; thus, subjects are able to move freely around the room/office. For instance, we can use these wireless and wearable EEG devices to conduct complex experiments, such as drowsy driving [33][34][35][36][37][38][39][40], distracted driving [41], [42], motion sickness [43], [44], or navigation [45] in a motion simulator (Fig. 4(a-b)) or real-world driving environment (Fig.…”
Section: Eeg-based Neuroimaging Technology For Bcismentioning
confidence: 99%