ライフサイエンスコーパス: EEG

1 EEG alpha connectivity was measured across different epo

2 EEG and force data were collected synchronously during e

3 EEG measurements revealed enhanced alpha power, suggesti

4 EEG microstates therefore have potential to be a non-inv

5 EEG recordings of a similar frequency range have been ap

6 EEG was recorded twice with a 1-week interval between se

7 EEG was recorded while 29 adult native speakers (22 wome

8 mal EEG compared to TDC or ASD with abnormal EEG.

9 relations between the resting-state absolute EEG powers and wisdom scores were significantly stronger

10 evertheless, stronger resting-state absolute EEG powers in the frontal lobe were associated with wise

11 ethod to record brain electrical activities, EEG has been widely used for capturing the underlying dy

12 Following ketamine administration, EEG changes were immediate and widespread, affecting the

13 were extracted for later comparison against EEG to determine degrees of accuracy.

14 This alternating EEG rhythm phase is likely to underlie the dissociative

15 Duration (ALD) and RALD to stimuli during an EEG experiment, with the most pronounced differences in

16 In an EEG experiment, participants viewed 100 face photographs

17 nding of antidepressant treatment through an EEG-tailored computational model and provide a clinical

18 f anaesthesia for the purpose of treating an EEG pattern concerning for incipient status epilepticus.

19 as confirmed in a second experiment using an EEG-based closed-loop system.

20 Analyzing EEG signals at the time they influence movement planning

21 outlasted SCS duration on the behavioral and EEG levels.

22 ld potential, electrocorticogram (ECoG), and EEG, and compared their information and decoding accurac

23 support insight solutions, although fMRI and EEG evidence for its involvement is, by nature, correlat

24 Combined fMRI and EEG measurements demonstrate that the perceived orientat

25 Behavioral ratings, fNIRS and EEG data showed positive correlations on a between-subje

26 art reviews of common clinical, imaging, and EEG prognostic variables and clinical outcomes for all p

27 Here we recorded simultaneous MEG and EEG (total of 328 sensors) in 9 human subjects (7 female

28 In two studies, MEG and EEG activity was measured as human participants (both se

29 zing the sharing and exploitation of MEG and EEG data, and we also discuss how this 'living' set of g

30 The MEG and EEG datasets revealed converging evidence that the simil

31 d changes in gCBF, cognitive performance and EEG were similar across observed partial pressures of ar

32 eness as indicated by interrelated pupil and EEG markers.

33 tes that tVNS reliably induces pupillary and EEG markers of arousal beyond the effects of somatosenso

34 rgic system while recording pupillometry and EEG to infer its functional capacity.

35 partially correct hemodynamic responses and EEG abnormalities, improve cognitive deficits, revert au

36 neralizable across different study sites and EEG equipment.

37 urrent transcranial magnetic stimulation and EEG.

38 rformed spectral power analyses of available EEGs during prominent burst suppression patterns (BSP) p

39 ghly associated with BECTS on a brief, awake EEG has the potential to improve diagnostic screening fo

40 re computed from 30-second segments of awake EEG signals.

41 henotypes of Fmr1-KO rats by measuring basal EEG power and auditory steady state response (ASSR) to c

42 uts aligned to the optimal phase of the beta EEG in the motor cortex enjoy transmission amplitude gai

43 Here we used a custom-built EEG system having an exceptionally high sample rate to a

44 neurophysiological activity, as measured by EEG, are different for children with ASD versus TD.

45 nd data fidelity (single-lead ECG/22-channel EEG).

46 brain activity measured through 256-channel EEG.

47 The 64-channel EEG signal was recorded while 27 human subjects (female:

48 ent resting-state high-density (128-channel) EEG data into microstates.

49 ed resting state high-density (256 channels) EEG from 31 patients with Parkinson's disease who underw

50 nverging evidence from studies using chronic EEG (cEEG) revealed that epileptic brain activity shows

51 We collected EEG data in 31 men and women who performed a hierarchica

52 roposes mechanisms that may underline common EEG seizure onset patterns and status epilepticus, and p

53 Continuous EEG monitoring data from >=2 hours before to >=48 hours

54 ppression or burst suppression on continuous EEG.

55 report amplified envelope-entrained cortical EEG responses to attended speech and to simple tones mod

56 e, namely the complete cessation of cortical EEG activity.

57 alpha-Delta EEG activity during stage 3 sleep was observed in 87% of

58 gh a combination of functional (high density EEG and 18F-fluorodeoxyglucose PET imaging) and structur

59 male volunteers (n = 24), using high-density EEG and pupillometry during visual fixation at rest.

60 Using novel high-density EEG electrode arrays in the mouse model of CSR where mic

61 High-density EEG facilitated characterization of cortical activity du

62 In this study, we applied high-density EEG recordings (HD-EEG) to quantitatively characterize t

63 Here we used high-density EEG recordings to ask whether the underlying neural sour

64 urce imaging approach that uses high-density EEG recordings to map brain networks.

65 ned magnetic resonance imaging, high-density EEG, and robotics in 17 individuals with severe chronic

66 ogether with the shoulder using high-density EEG.

67 linically defined dysmature and disorganised EEG patterns, cementing the link between early maturatio

68 nt error are reflected by spatially distinct EEG oscillatory components.

69 eding narrative context ("anomalous") during EEG recording.

70 ic tasks involving different modalities (ECG/EEG/EHR), required level of characterization (abnormalit

71 set-up and portability of the dry electrode EEG headset used in our study comply with the needs of c

72 oes not alter baseline electroencephalogram (EEG) total power, but significantly shortens delay to is

73 ial interaction-evoked electroencephalogram (EEG) signals, and an altered composition of cortical int

74 tory, and reflected in electroencephalogram (EEG) slow wave activity (SWA, 0.5-4 Hz) during sleep.

75 ignificantly weaker in electroencephalogram (EEG), suggesting that ECoG is more like LFP than EEG.

76 ncy band (15-29 Hz) of electroencephalogram (EEG).

77 nt scales, we recorded electroencephalogram (EEG) over medial frontal cortex of macaques performing a

78 eys, and also recorded electroencephalogram (EEG), while they viewed a variety of naturalistic images

79 recorded in the scalp electroencephalogram (EEG) during rapid eye movement (REM) sleep.

80 attern analysis of the electroencephalogram (EEG).

81 ed oscillations in the electroencephalogram (EEG).

82 ttacus undulatus) with electroencephalogram (EEG) and electrooculogram (EOG) electrodes to evaluate s

83 pileptic seizures with electroencephalogram (EEG).

84 es of the brain (e.g., electroencephalogram [EEG], functional MRI [fMRI]) and manifest variables of b

85 Electroencephalographic (EEG) "microstates" are canonical voltage topographies th

86 yographic (EMG) and electroencephalographic (EEG) recordings were used to quantify physiological chan

87 lographic (MEG) and electroencephalographic (EEG) research, recently developed by the OHBM neuroimagi

88 CA coma to identify electroencephalographic (EEG) markers of their recovery potential.

89 ions of interest in electroencephalographic (EEG) data.

90 esolved decoding of electroencephalographic (EEG) data, we demonstrate that the visual system represe

91 se (ASSR), a robust electroencephalographic (EEG) biomarker that is increasingly used to advance the

92 W) present as scalp electroencephalographic (EEG) bursts of slow waves contrasting with the low-volta

93 (n = 80) underwent electroencephalographic (EEG) measurements while watching a subset of the video-c

94 Electroencephalographical (EEG) coherence, which measures the degree of synchrony b

95 cular interest is electroencephalographical (EEG) data, collected noninvasively from humans in variou

96 Electroencephalography (EEG) abnormalities are also observed in subjects with FX

97 Electroencephalography (EEG) is a method for recording electrical activity, indi

98 psychoacoustics and electroencephalography (EEG) in male and female human listeners to examine poten

99 halography (MEG) and electroencephalography (EEG), in combination with representational similarity an

100 Chronic electroencephalography (EEG) is a widely used tool for monitoring cortical elect

101 xamined the cortical electroencephalography (EEG) response to ketamine of 12 sheep.

102 ormance and cortical electroencephalography (EEG).

103 asuring high-density electroencephalography (EEG) in healthy participants performing the sound-induce

104 the latter employing electroencephalography (EEG) acquired from parents while they shop in a simulate

105 We looked for Electroencephalography (EEG) markers of CVSA usable for virtual reality-based NF

106 roscience comes from electroencephalography (EEG), which records the tiny voltages generated when neu

107 rn analysis on human electroencephalography (EEG) data, we compared the oscillatory time courses of m

108 d human intracranial electroencephalography (EEG) coherence.

109 spectral density of electroencephalography (EEG) between patients with SS and those with obstructive

110 (BCI) based on scalp electroencephalography (EEG) have demonstrated the feasibility of decoding kinem

111 scillations in scalp electroencephalography (EEG) recordings over the primary motor cortex have been

112 MS) and simultaneous electroencephalography (EEG) to characterize individual brain dynamics within di

113 ed for resting-state electroencephalography (EEG) and applied it to data from the largest imaging-cou

114 ectories between the Electroencephalography (EEG)-derived 'brain-age' and postmenstrual age (the age

115 this study, we used electroencephalography (EEG) to assess the effects of a mindfulness-based, cogni

116 Here, using electroencephalography (EEG) recordings, we identified and validated a spatio-te

117 s of syllables using electroencephalography (EEG).

118 eural response using electroencephalography (EEG).

119 previously validated electroencephalography (EEG)-based device.

120 dball paradigm while electroencephalography (EEG) was recorded.

121 in conjunction with electroencephalography (EEG) and multivariate pattern classification analyses.

122 imulation (TMS) with electroencephalography (EEG) offers unique insights into the cortical circuits a

123 eficit at 30 Hz with electroencephalography (EEG), we applied 20 minutes of transcranial alternating

124 Subjects with electroencephalography (EEG)-confirmed seizures after >=20 and <40mg/kg phenobar

125 Low-frequency (<10 Hz) envelope-entrained EEG responses were enhanced in the HI listeners, both fo

126 ces EEG data from both healthy and epileptic EEG signals, but it also predicts EEG features, the Hurs

127 In 54 subjects, epileptiform EEG abnormalities were identified before seizures.

128 owever, the mechanisms underlying TMS-evoked EEG potentials (TEPs) remain largely unknown.

129 relates of spider phobia in a combined fNIRS-EEG study.

130 Interestingly, visual grading for EEG abnormalities that are thought to reflect E/I imbala

131 The proposed model is able to forecast EEG signals 5.76 s in the future.

132 ielded values resembling those obtained from EEG SWA and global vigilance states.

133 te that signals obtained via recordings from EEG electrodes at the nasal bridge represent responses f

134 spikes and describe resulting medial-frontal EEG on a male macaque monkey.

135 HD-EEG data were analysed using independent component analy

136 ding high-density electroencephalography (HD-EEG) data during a full-body reaching task to understand

137 , we applied high-density EEG recordings (HD-EEG) to quantitatively characterize the fine-grained spa

138 REM IEDs over NREM IEDs and suggests that HD-EEG may be of clinical utility in epilepsy surgery work-

139 Ds at the scalp and cortical levels using HD-EEG source-localization, during non-rapid eye movement (

140 similarity analysis of male and female human EEG signals, we show enhanced encoding of audiovisual ob

141 AG) on parietal resting-state theta (3-7 Hz) EEG coherence, which previously have been associated wit

142 to detect epileptic seizures using an imaged-EEG representation of brain signals.

143 AC demonstrated significant changes in EEG firing patterns characterize within explanatory (p <

144 is non-invasive and relatively inexpensive, EEG microstates have the potential to be useful clinical

145 uped in "epilepsy" or "no epilepsy." Initial EEGs were visually analyzed for spikes, spike ripples, a

146 the variability in the amplitude-integrated EEG (aEEG) outputs impact the determination of neurovasc

147 In these patients, the interictal EEG commonly shows interictal epileptiform discharges (I

148 ed effectively by Stereotactic intracerebral EEG (SEEG).

149 Using human intracranial EEG with concurrent pupillometry in 3 subjects (2 males,

150 source imaging results with the intracranial EEG (iEEG) findings and surgical resection outcomes in a

151 females and 9 males) undergoing intracranial EEG monitoring.

152 rs, range = 5-58) who underwent intracranial EEG evaluation for epilepsy surgery.

153 ess this knowledge gap, we used intracranial EEG to record LFPs at 858 widely distributed recording s

154 Here, using intracranial EEG recordings, we show that episodic memories formed af

155 Non-invasive EEG measures of this encoding could help clinicians iden

156 Future studies involving EEG recordings and chronic cranial windows must consider

157 significantly shortens delay to isoelectric EEG, which precedes respiratory and cardiac arrest.

158 Our results revealed that the best-known EEG marker of CVSA-increased alpha-power ipsilateral to

159 Source-level EEG propagation patterns were network-specific and highl

160 aracterized by a desynchronized, 'wake-like' EEG.

161 d with magneto- or electroencephalography (M/EEG) based on representational similarity.

162 Electrophysiological methods, that is M/EEG, provide unique views into brain health.

163 in which this problem can manifest in the M/EEG context is through post hoc tailoring of analysis wi

164 n-to-bound signal in simultaneously measured EEG signals.

165 Magneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with mil

166 rigins of electrical currents generating MEG/EEG.

167 variate analysis methods to a multimodal MEG/EEG dataset.

168 inicians interpret the neural origins of MEG/EEG.

169 rs is a limitation that constrains using MEG/EEG to reveal novel principles of information processing

170 In Syngap1(+/-) mice, EEG spectral power analyses identified a significant los

171 on significance thresholding and midfrontal EEG topography.

172 Moreover, this study utilised mobile EEG equipment and short presentation times that would be

173 RI-magnetoencephalography and functional MRI-EEG studies provide conclusive evidence that changes in

174 -varying network constituted by multivariate EEG signals, which represents the overall dynamics of th

175 Method (M2) uses a Neonatal EEG Analysis Toolbox (WU-NEAT).

176 ase who had no form of epilepsy and a normal EEG based on a clinical chart review.

177 ed fE/I and LRTC in ASD children with normal EEG compared to TDC or ASD with abnormal EEG.

178 We performed identical analyses of EEG recorded over the frontal lobe of macaque monkeys (o

179 in populations with limited availability of EEG data.

180 clear evidence that chronic implantation of EEG electrodes is associated with significant changes in

181 e of neural coupling - the imaginary part of EEG coherence - the study revealed that all meditation c

182 can optimise the test-retest reliability of EEG connectivity measures in infants.

183 cal injury but demonstrated prominent BSP on EEG.

184 examine potential effects of hearing loss on EEG correlates of speech envelope synchronization in cor

185 ive effects of sinusoidal rate modulation on EEG outlasted SCS duration on the behavioral and EEG lev

186 tency) in the cue-to-target foreperiod, only EEG alpha differed with the to-be-attended object catego

187 Oscillatory EEG activity in the alpha range (8-12 Hz) of neural popu

188 Overall EEG variation, spectral power and event-related potentia

189 in Syngap1(+/-) mice and during an overnight EEG from a child with SYNGAP1 haploinsufficiency.

190 This sertraline-predictive EEG signature generalized to two depression samples, whe

191 epileptic EEG signals, but it also predicts EEG features, the Hurst exponent, and the power spectrum

192 They reported their preferred EEG system.

193 In previous EEG research enhanced event-related potentials (ERPs) in

194 nts strengthens the validity of the proposed EEG signatures of consciousness, and is suggestive of a

195 MRI (rsfMRI), and resting-state quantitative EEG (qEEG) to investigate the effects of a behaviorally

196 The raw EEG was converted to aEEG using three different methods:

197 transplantation did not normalize recipient EEG signals measured during baseline states.

198 ld typically developing infants, we recorded EEG during presentation of dynamic movies of people and

199 emale and male human volunteers, we recorded EEG in a motor adaptation task in which a visual rotatio

200 Therefore, we recorded EEG signals during a perceptual color discrimination tas

201 ham-controlled crossover design, we recorded EEG while participants with schizophrenia completed a pr

202 In addition, tDCS reduced EEG interhemispheric coherence in parietal areas and aff

203 ysis and identifying salient texture related EEG features during active touch that are minimally infl

204 for the long-standing evidence of a relative EEG slowing over the injured hemisphere.

205 Our model not only successfully reproduces EEG data from both healthy and epileptic EEG signals, bu

206 eady-state response (40 Hz ASSR) and resting EEG.

207 In fourteen male volunteers, resting EEG and TEPs from prefrontal (PFC) and parietal (PAR) co

208 classical visual SL task, divergent rhythmic EEG activity in the interstimulus delay periods within p

209 algorithms could predict, using a patient's EEG record(s) as input, which medications were noted on

210 ctance, respiration, eye tracking, and scalp EEG).

211 at alpha-band activity, as measured by scalp EEG from human participants, varies with the specific ca

212 shows increases in 2-4 Hz power during scalp EEG STW, that STW are associated with a strong and wides

213 of interictal functional networks from scalp EEG can be estimated using a computer model and used to

214 Confirming results from scalp EEG, responses to audiovisual speech were weaker than re

215 Beta (15-25 Hz) scalp EEG signals recorded over the motor cortex during a pre-

216 We visually marked STW segments in scalp EEG and selected stereo-EEG channels exhibiting normal a

217 computational results for a realistic scalp EEG database show a detection rate of 93.6% and a false

218 networks were estimated in segments of scalp-EEG without interictal discharges (68 people with epilep

219 e outstanding result for forecasting seizure EEG with an error of 11.21%.

220 on evidence, as captured by the post-sensory EEG component, consistent with the emergence of multisen

221 post-sensory, rather than the early sensory, EEG component amplitudes that are being amplified during

222 orrelated signals that manifest with similar EEG scalp projections.

223 We further conducted simultaneous EEG recordings using specific saliency emphasis and foun

224 Since EEG is non-invasive and relatively inexpensive, EEG micr

225 n little progress in understanding how sleep EEG in different brain regions responds to CSR.

226 Compensatory elevation in NREM sleep EEG delta power has been typically observed following pr

227 tensive analysis of topographical NREM sleep EEG responses to the CSR condition, including period-amp

228 When combined with a spectral EEG measure, microstate complexity could classify AD wit

229 as performed to select temporal and spectral EEG features that contribute to texture classification b

230 te power spectral density values of standard EEG frequency bands between the SS (n = 42) and OSA (n =

231 We recorded the resting state EEG (rsEEG), the visual evoked potentials (VEP) and the

232 ed by language aptitude (17%), resting-state EEG power in beta and low-gamma bands (10%), and numerac

233 , we found that the sertraline resting-state EEG signature indexed prefrontal neural responsivity, as

234 Behavioral and neural (resting-state EEG) indices of language aptitude were used along with n

235 gold standard to determine conscious state, EEG has proven to be a promising complementary tool to m

236 Stereo-EEG performed for presurgical epilepsy evaluation offers

237 Using combined stereo-EEG/polysomnography possible only in the human brain dur

238 tients (14 women) undergoing combined stereo-EEG/polysomnography.

239 TW segments in scalp EEG and selected stereo-EEG channels exhibiting normal activity for intracranial

240 lation to CS(+) was correlated with stronger EEG alpha-beta desynchronization, suggesting a common de

241 In this study, EEG was collected from two independent cohorts of probab

242 In this study, EEG was recorded while subjects listened to rhythmic seq

243 Using intracranial and surface EEG recordings in four independent data sets, we demonst

244 The current study used a frequency-tagging EEG approach to separately measure responses to numerosi

245 Based on the spatio-temporal EEG features, we developed a system for detecting pain p

246 , suggesting that ECoG is more like LFP than EEG.

247 We suggest that EEG theta change in infancy is an excellent candidate pr

248 The EEG changes correlated with electric fields strengths in

249 The EEG responses were greater for binaural than monaural pr

250 We characterized the EEG phenotypes of Fmr1-KO rats by measuring basal EEG po

251 Here we address this issue by comparing the EEG activity preceding awakenings with recalled vs. no r

252 which low frequency activity dominated, the EEG was characterised by short periods (2-3 s) of altern

253 From the EEG and fMRI experiments, we first show that healthy/unh

254 volve changes in oscillatory activity in the EEG alpha band (8-12 Hz), with decreased alpha indicatin

255 neurons drove rhythmic theta activity in the EEG.

256 n between AHI and the absolute values of the EEG frequency bands.

257 widespread, affecting the full extent of the EEG frequency spectrum measured (0-125 Hz).

258 Spectral components of the EEG revealed no significant differences between successf

259 ccessful weaning: spectral components of the EEG signal, and spatial-correlation-based measures of fu

260 representational similarity analysis on the EEG data, we reveal representations of facial attractive

261 E) release, while concurrently recording the EEG of male younger (N = 39; 25.2 +/- 3.2 years) and old

262 h recalled vs. no recall of dreams using the EEG microstate approach.

263 Application of this algorithm to the EEGs of healthy adults showed that fE/I is balanced at t

264 ompanied with more prominent delta and theta EEG oscillations in the mutant mice, and reached burst-s

265 ts later diagnosed with autism, infant theta EEG explained over 80% of the variance in nonverbal skil

266 ed with posterior interhemispheric low theta EEG coherence (3-5 Hz).

267 We observed similar patterns of theta EEG change at 12 months, and found a predictive relation

268 ese results demonstrate the homology of this EEG signature between humans and macaques but raise ques

269 Here, we aim at testing whether this EEG slowing is linked to the pathological intrusion of s

270 Findings illustrate the potential of TMS-EEG perturbation-based biomarkers to characterize networ

271 come, while both global connectivity and TMS/EEG changes tracked clinical outcome.

272 nd causal excitability, resting fMRI and TMS/EEG were performed before and after the treatment.

273 stimulation and electroencephalography (TMS/EEG) to study cortical reactivity in a cohort of 30 cons

274 and (3) local and distributed changes in TMS/EEG potentials.

275 ource locations was developed and applied to EEG recordings obtained from 293 healthy subjects and 42

276 e trained on within-participant single-trial EEG data from a Sternberg working memory task.

277 hierarchical Bayesian model to single-trial EEG data from healthy human volunteers of either sex who

278 ed talker to be classified from single-trial EEG responses with high accuracy in both older hearing-i

279 did not statistically differ between the two EEG systems (p > 0.05 in all cases).

280 terns and sleep-related variables, we set up EEG/EMG and video recordings and found that A. cahirinus

281 Here, we used EEG and a visual search task in which the predictability

282 Here, we used EEG and machine learning to study how the brain processe

283 Here, we used EEG and MEG techniques to show that the brain is able to

284 Using EEG recordings in human participants (male and female),

285 Using EEG, we demonstrate that memory for past cognitive contr

286 al and social relationship information using EEG and representational similarity analysis.

287 ncope documented by continuous ECG and video EEG monitoring.

288 Video-EEG monitoring of heterozygous Kcnt1(+/R455H) animals re

289 Continuous video-EEG telemetry showed that AAV9-mediated delivery of CRIS

290 groups at all sensor locations, while visual EEG inspection by a board-certified child neurologist di

291 th between one, four and seven digits, where EEG recordings for working memory load estimation were t

292 = 62) practiced mindfulness meditation while EEG was recorded.

293 shown faces of that network's members while EEG was recorded.

294 with another person in the same room) while EEG signals were measured.

295 ding seizure territory expansion, widespread EEG synchronization, and slowing of the ictal rhythm as

296 g depression events that are associated with EEG low voltage activity events, which correlate with tr

297 ual stimulation (FPVS) paradigm coupled with EEG was used to assess the ability of younger and older

298 a conflict task in the auditory domain with EEG neurodynamics to test how neural and behavioral mark

299 r twenty hours in the first day of life with EEG and near infrared spectroscopy (NIRS)-based cerebral

300 001344; p = 1.3 x 10(-11)), and SLC6A1 with "EEG with generalized slow activity" (HP: 0010845; p = 0.