858 resultados para auditory evoked potentials
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Our previously observations showed that the amplitude of cortical evoked potentials to irrelevant auditory stimulus (probe) recorded from several different cerebral areas was differentially modulated by brain states. At present study, we simultaneously re
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The aim of this paper was to obtain normative data of auditory evoked potentials from 34 mixed breed dogs and evaluate the age influence. The animals were divided in two groups of different ages and auditory evoked potential was performed with a 85dB stimulus intensity. Group 1 included 16 dogs between 1 and 8 years of age, and group 2 included 18 dogs with over 8 years of age. The length and head diameter were measured and there was no statistical difference between the two groups. In group 1, mean latencies of waves I, III, and V were 1.13; 2.64, and 3.45ms, and the intervals I-III, III-V, and I-V were 1.51; 0.81, and 2.32 ms, respectively. In group 2, the mean latencies of waves I, III and V were 1.15, 2.62, and 3.55ms, and the intervals I-III, III-V, and I-V were 1.47, 0.93, and 2.40ms, respectively. The latencies observed in this study were similar to previous studies conducted by other authors. It was observed that significant differences were present for wave V and intervals III-V and I-V latencies when comparing groups with different ages, consequently this characteristic must be considered during BAEP result interpretation.
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Objective: To characterize the PI component of long latency auditory evoked potentials (LLAEPs) in cochlear implant users with auditory neuropathy spectrum disorder (ANSD) and determine firstly whether they correlate with speech perception performance and secondly whether they correlate with other variables related to cochlear implant use. Methods: This study was conducted at the Center for Audiological Research at the University of Sao Paulo. The sample included 14 pediatric (4-11 years of age) cochlear implant users with ANSD, of both sexes, with profound prelingual hearing loss. Patients with hypoplasia or agenesis of the auditory nerve were excluded from the study. LLAEPs produced in response to speech stimuli were recorded using a Smart EP USB Jr. system. The subjects' speech perception was evaluated using tests 5 and 6 of the Glendonald Auditory Screening Procedure (GASP). Results: The P-1 component was detected in 12/14 (85.7%) children with ANSD. Latency of the P-1 component correlated with duration of sensorial hearing deprivation (*p = 0.007, r = 0.7278), but not with duration of cochlear implant use. An analysis of groups assigned according to GASP performance (k-means clustering) revealed that aspects of prior central auditory system development reflected in the P-1 component are related to behavioral auditory skills. Conclusions: In children with ANSD using cochlear implants, the P-1 component can serve as a marker of central auditory cortical development and a predictor of the implanted child's speech perception performance. (c) 2012 Elsevier Ireland Ltd. All rights reserved.
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Studies about cortical auditory evoked potentials using the speech stimuli in normal hearing individuals are important for understanding how the complexity of the stimulus influences the characteristics of the cortical potential generated. OBJECTIVE: To characterize the cortical auditory evoked potential and the P3 auditory cognitive potential with the vocalic and consonantal contrast stimuli in normally hearing individuals. METHOD: 31 individuals with no risk for hearing, neurologic and language alterations, in the age range between 7 and 30 years, participated in this study. The cortical auditory evoked potentials and the P3 auditory cognitive one were recorded in the Fz and Cz active channels using consonantal (/ba/-/da/) and vocalic (/i/-/a/) speech contrasts. Design: A crosssectional prospective cohort study. RESULTS: We found a statistically significant difference between the speech contrast used and the latencies of the N2 (p = 0.00) and P3 (p = 0.00) components, as well as between the active channel considered (Fz/Cz) and the P3 latency and amplitude values. These correlations did not occur for the exogenous components N1 and P2. CONCLUSION: The speech stimulus contrast, vocalic or consonantal, must be taken into account in the analysis of the cortical auditory evoked potential, N2 component, and auditory cognitive P3 potential.
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Avoidance of excessively deep sedation levels is problematic in intensive care patients. Electrophysiologic monitoring may offer an approach to solving this problem. Since electroencephalogram (EEG) responses to different sedation regimens vary, we assessed electrophysiologic responses to two sedative drug regimens in 10 healthy volunteers. Dexmedetomidine/remifentanil (dex/remi group) and midazolam/remifentanil (mida/remi group) were infused 7 days apart. Each combination of medications was given at stepwise intervals to reach Ramsay scores (RS) 2, 3, and 4. Resting EEG, bispectral index (BIS), and the N100 amplitudes of long-latency auditory-evoked potentials (ERP) were recorded at each level of sedation. During dex/remi, resting EEG was characterized by a recurrent high-power low-frequency pattern which became more pronounced at deeper levels of sedation. BIS Index decreased uniformly in only the dex/remi group (from 94 +/- 3 at baseline to 58 +/- 14 at RS 4) compared to the mida/remi group (from 94 +/- 2 to 76 +/- 10; P = 0.029 between groups). The ERP amplitudes decreased from 5.3 +/- 1.3 at baseline to 0.4 +/- 1.1 at RS 4 (P = 0.003) in only the mida/remi group. We conclude that ERPs in volunteers sedated with dex/remi, in contrast to mida/remi, indicate a cortical response to acoustic stimuli, even when sedation reaches deeper levels. Consequently, ERP can monitor sedation with midazolam but not with dexmedetomidine. The reverse is true for BIS.
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The two elcctrophysiological tests currently favoured in the clinical measurement of hearing threshold arc the brainstorm evoked potential (BAEP) and the slow vertex response (SVR). However, both tests possess disadvantages. The BAEP is the test of choice in younger patients as it is stable at all levels of arousal, but little information has been obtained to date at a range of frequencies. The SVR is frequency specific but is unreliable in certain adult subjects and is unstable during sleep or in young children. These deficiencies have prompted research into a third group of potentials, the middle latency response (MLR) and the 40HZ responses. This research has compared the SVR and 40HZ response in waking adults and reports that the 40HZ test can provide a viable alternative to the SVR provided that a high degree of subject relaxation is ensured. A second study examined the morphology of the MLR and 40HZ during sleep. This work suggested that these potentials arc markedly different during sleep and that methodological factors have been responsible for masking these changes in previous studies. The clinical possibilities of tone pip BAEPs were then examined as these components were proved to be the only stable responses present in sleep. It was found that threshold estimates to 5OOHz, lOOOHz and 4000Hz stimuli could be made to within 15dBSL in most cases. A final study looked more closely at methods of obtaining frequency specific information in sleeping subjects. Threshold estimates were made using established BAEP parameters and this was compared to a 40HZ procedure which recorded a series of BAEPs over a 100msec. time sweep. Results indicated that the 40mHz procedure was superior to existing techniques in estimating threshold to low frequency stimuli. This research has confirmed a role for the MLR and 40Hz response as alternative measures of hearing capability in waking subjects and proposes that the 40Hz technique is useful in measuring frequency specific thresholds although the responses recorded derive primarily from the brainstem.
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We simultaneously recorded auditory evoked potentials (AEP) from the temporal cortex (TCx), the dorsolateral prefrontal cortex (dPFCx) and the parietal cortex (PCx) in the freely moving rhesus monkey to investigate state-dependent changes of the AEP. AEPs obtained during passive wakefulness, active wakefulness (AW), slow wave sleep and rapid-eye-movement sleep (REM) were compared. Results showed that AEP from all three cerebral areas were modulated by brain states. However, the amplitude of AEP from dPFCx and PCx significantly appeared greater attenuation than that from the TCx during AW and REM. These results indicate that the modulation of brain state on AEP from all three cerebral areas investigated is not uniform, which suggests that different cerebral areas have differential functional contributions during sleep-wake cycle. (C) 2002 Elsevier Science Ireland Ltd.. All rights reserved.
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There is controversy over how hormonal conditions influence cerebral physiology. We studied pattern-shift visual evoked potentials (PS-VEP), brain stem auditory evoked potentials (BAEP) and short-latency somatosensory evoked potentials (SSEV) in 20 female volunteers at different phases of the menstrual cycle (estrogen phase, ovulatory day and progesterone phase). Statistical analysis showed decreased latencies for P 100 (PS-VEP), N 19and P 22 (SSEV) waves in the progesterone phase compared with the estrogen phase. There was no significant difference between the estrogen and the ovulation day values. Comparing the three above stages, there were no significant differences in the brainstem auditory evoked potentials. The reduction of the latencies of the potentials generated in multisynaptic circuits provides the first consistent neurophysiological basis for a tentative comprehension of human pre-menstrual syndrome.
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Time-varying bispectra, computed using a classical sliding window short-time Fourier approach, are analyzed for scalp EEG potentials evoked by an auditory stimulus and new observations are presented. A single, short duration tone is presented from the left or the right, direction unknown to the test subject. The subject responds by moving the eyes to the direction of the sound. EEG epochs sampled at 200 Hz for repeated trials are processed between -70 ms and +1200 ms with reference to the stimulus. It is observed that for an ensemble of correctly recognized cases, the best matching timevarying bispectra at (8 Hz, 8Hz) are for PZ-FZ channels and this is also largely the case for grand averages but not for power spectra at 8 Hz. Out of 11 subjects, the only exception for time-varying bispectral match was a subject with family history of Alzheimer’s disease and the difference was in bicoherence, not biphase.
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Experience continuously imprints on the brain at all stages of life. The traces it leaves behind can produce perceptual learning [1], which drives adaptive behavior to previously encountered stimuli. Recently, it has been shown that even random noise, a type of sound devoid of acoustic structure, can trigger fast and robust perceptual learning after repeated exposure [2]. Here, by combining psychophysics, electroencephalography (EEG), and modeling, we show that the perceptual learning of noise is associated with evoked potentials, without any salient physical discontinuity or obvious acoustic landmark in the sound. Rather, the potentials appeared whenever a memory trace was observed behaviorally. Such memory-evoked potentials were characterized by early latencies and auditory topographies, consistent with a sensory origin. Furthermore, they were generated even on conditions of diverted attention. The EEG waveforms could be modeled as standard evoked responses to auditory events (N1-P2) [3], triggered by idiosyncratic perceptual features acquired through learning. Thus, we argue that the learning of noise is accompanied by the rapid formation of sharp neural selectivity to arbitrary and complex acoustic patterns, within sensory regions. Such a mechanism bridges the gap between the short-term and longer-term plasticity observed in the learning of noise [2, 4-6]. It could also be key to the processing of natural sounds within auditory cortices [7], suggesting that the neural code for sound source identification will be shaped by experience as well as by acoustics.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This study verifies the effects of contralateral noise on otoacoustic emissions and auditory evoked potentials. Short, middle and late auditory evoked potentials as well as otoacoustic emissions with and without white noise were assessed. Twenty-five subjects, normal-hearing, both genders, aged 18 to 30 years, were tested. In general, latencies of the various auditory potentials were increased at noise conditions, whereas amplitudes were diminished at noise conditions for short, middle and late latency responses combined in the same subject. The amplitude of otoacoustic emission decreased significantly in the condition with contralateral noise in comparison to the condition without noise. Our results indicate that most subjects presented different responses between conditions (with and without noise) in all tests, thereby suggesting that the efferent system was acting at both caudal and rostral portions of the auditory system.
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Introduction: The effects of lead on children’s health have been widely studied. Aim: To analyze the correlation between the long latency auditory evoked potential N2 and cognitive P3 with the level of lead poisoning in Brazilian children. Methods: This retrospective study evaluated 20 children ranging in age from 7 to 14 years at the time of audiological and electrophysiological evaluations. We performed periodic surveys of the lead concentration in the blood and basic audiological evaluations. Furthermore, we studied the auditory evoked potential long latency N2 and cognitive P3 by analyzing the absolute latency of the N2 and P3 potentials and the P3 amplitude recorded at Cz. At the time of audiological and electrophysiological evaluations, the average concentration of lead in the blood was less than 10 ug/dL. Results: In conventional audiologic evaluations, all children had hearing thresholds below 20 dBHL for the frequencies tested and normal tympanometry findings; the auditory evoked potential long latency N2 and cognitive P3 were present in 95% of children. No significant correlations were found between the blood lead concentration and latency (p = 0.821) or amplitude (p = 0.411) of the P3 potential. However, the latency of the N2 potential increased with the concentration of lead in the blood, with a significant correlation (p = 0.030). Conclusion: Among Brazilian children with low lead exposure, a significant correlation was found between blood lead levels and the average latency of the auditory evoked potential long latency N2; however, a significant correlation was not observed for the amplitude and latency of the cognitive potential P3
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RATIONALE: Olanzapine is an atypical antipsychotic drug with a more favourable safety profile than typical antipsychotics with a hitherto unknown topographic quantitative electroencephalogram (QEEG) profile. OBJECTIVES: We investigated electrical brain activity (QEEG and cognitive event related potentials, ERPs) in healthy subjects who received olanzapine. METHODS: Vigilance-controlled, 19-channel EEG and ERP in an auditory odd-ball paradigm were recorded before and 3 h, 6 h and 9 h after administration of either a single dose of placebo or olanzapine (2.5 mg and 5 mg) in ten healthy subjects. QEEG was analysed by spectral analysis and evaluated in nine frequency bands. For the P300 component in the odd-ball ERP, the amplitude and latency was analysed. Statistical effects were tested using a repeated-measurement analysis of variance. RESULTS: For the interaction between time and treatment, significant effects were observed for theta, alpha-2, beta-2 and beta-4 frequency bands. The amplitude of the activity in the theta band increased most significantly 6 h after the 5-mg administration of olanzapine. A pronounced decrease of the alpha-2 activity especially 9 h after 5 mg olanzapine administration could be observed. In most beta frequency bands, and most significantly in the beta-4 band, a dose-dependent decrease of the activity beginning 6 h after drug administration was demonstrated. Topographic effects could be observed for the beta-2 band (occipital decrease) and a tendency for the alpha-2 band (frontal increase and occipital decrease), both indicating a frontal shift of brain electrical activity. There were no significant changes in P300 amplitude or latency after drug administration. Conclusion: QEEG alterations after olanzapine administration were similar to EEG effects gained by other atypical antipsychotic drugs, such as clozapine. The increase of theta activity is comparable to the frequency distribution observed for thymoleptics or antipsychotics for which treatment-emergent somnolence is commonly observed, whereas the decrease of beta activity observed after olanzapine administration is not characteristic for these drugs. There were no clear signs for an increased cerebral excitability after a single-dose administration of 2.5 mg and 5 mg olanzapine in healthy controls.