79 resultados para auditory EEG

em University of Queensland eSpace - Australia


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The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).

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This paper presents a new relative measure of signal complexity, referred to here as relative structural complexity, which is based on the matching pursuit (MP) decomposition. By relative, we refer to the fact that this new measure is highly dependent on the decomposition dictionary used by MP. The structural part of the definition points to the fact that this new measure is related to the structure, or composition, of the signal under analysis. After a formal definition, the proposed relative structural complexity measure is used in the analysis of newborn EEG. To do this, firstly, a time-frequency (TF) decomposition dictionary is specifically designed to compactly represent the newborn EEG seizure state using MP. We then show, through the analysis of synthetic and real newborn EEG data, that the relative structural complexity measure can indicate changes in EEG structure as it transitions between the two EEG states; namely seizure and background (non-seizure).

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This study examined spoken-word recognition in children with specific language impairment (SLI) and normally developing children matched separately for age and receptive language ability. Accuracy and reaction times on an auditory lexical decision task were compared. Children with SLI were less accurate than both control groups. Two subgroups of children with SLI, distinguished by performance accuracy only, were identified. One group performed within normal limits, while a second group was significantly less accurate. Children with SLI were not slower than the age-matched controls or language-matched controls. Further, the time taken to detect an auditory signal, make a decision, or initiate a verbal response did not account for the differences between the groups. The findings are interpreted as evidence for language-appropriate processing skills acting upon imprecise or underspecified stored representations.

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Thirty-two pouch-young tammar wallabies were used to discover the generators of the auditory brainstem response (ABR) during development by the use of simultaneous ABR and focal brainstem recordings. A click response from the auditory nerve root (ANR) in the wallaby was recorded from postnatal day (PND) 101, when no central auditory station was functional, and coincided with the ABR, a simple positive wave. The response of the cochlear nucleus (CN) was detected from PND 110, when the ABR had developed 1 positive and 1 negative peak. The dominant component of the focal ANR response, the N-1 wave, coincided with the first half of the ABR P wave, and that of the focal CN response, the N-1 wave, coincided with the later two thirds. In older animals, the ANR response coincided with the ABR's N-1, wave, while the CN response coincided with the ABR's P-2, N-2 and P-3 waves, with its contribution to the ABR P-2 dominant. The protracted development of the marsupial auditory system which facilitated these correlations makes the tammar wallaby a particularly suitable model. Copyright (C) 2001 S. Karger AG, Basel.

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To discover the developmental relationship between the auditory brainstem response (ABR) and the focal inferior colliculus (IC) response, 32 young tammar wallabies were used, by the application of simultaneous ABR and focal brainstem recordings, in response to acoustic clicks and tone bursts of seven frequencies. The ic or the tammar wallaby undergoes a rapid functional development from postnatal day (PND) 114 to 160. The earliest (PND 114) auditory evoked response was recorded from the rostral IC. With development, more caudal parts of the IC became functional until age about PND 127, when all parts of the IC were responsive to sound. Along a dorsoventral direction, the duration of the IC response decreased, the peak latency shortened, while the amplitude increased, reaching a maximum value at the central IC, then decreased. After PND 160, the best frequency (BF) of the ventral IC was the highest, with values between 12.5 and 16 kHz, the BF of the dorsal IC was the lowest, varying between 3.2 and 6.4 kHz, while the BF of the central IC was between 6.4 and 12.5 kHz. Between PND 114 and 125, the IC response did not have temporal correlation with the ABR. Between PND 140 and 160, only the early components of the responses from the ventral and central IC correlated with the P4 waves of the ABR. After PND 160, responses recorded from different depths of the IC had a temporal correlation with the ABR. (C) 2001 Published by Elsevier Science B.V.

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Spontaneous and tone-evoked changes in light reflectance were recorded from primary auditory cortex (A1) of anesthetized cats (barbiturate induction, ketamine maintenance). Spontaneous 0.1-Hz oscillations of reflectance of 540- and 690-nm light were recorded in quiet. Stimulation with tone pips evoked localized reflectance decreases at 540 nm in 3/10 cats. The distribution of patches activated by tones of different frequencies reflected the known tonotopic organization of auditory cortex. Stimulus-evoked reflectance changes at 690 nm were observed in 9/10 cats but lacked stimulus-dependent topography. In two experiments, stimulus-evoked optical signals at 540 nm were compared with multiunit responses to the same stimuli recorded at multiple sites. A significant correlation (P < 0.05) between magnitude of reflectance decrease and multiunit response strength was evident in only one of five stimulus conditions in each experiment. There was no significant correlation when data were pooled across all stimulus conditions in either experiment. In one experiment, the spatial distribution of activated patches, evident in records of spontaneous activity at 540 nm, was similar to that of patches activated by tonal stimuli. These results suggest that local cerebral blood volume changes reflect the gross tonotopic organization of A1 but are not restricted to the sites of spiking neurons.

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Neurological disease or dysfunction in newborn infants is often first manifested by seizures. Prolonged seizures can result in impaired neurodevelopment or even death. In adults, the clinical signs of seizures are well defined and easily recognized. In newborns, however, the clinical signs are subtle and may be absent or easily missed without constant close observation. This article describes the use of adaptive signal processing techniques for removing artifacts from newborn electroencephalogram (EEG) signals. Three adaptive algorithms have been designed in the context of EEG signals. This preprocessing is necessary before attempting a fine time-frequency analysis of EEG rhythmical activities, such as electrical seizures, corrupted by high amplitude signals. After an overview of newborn EEG signals, the authors describe the data acquisition set-up. They then introduce the basic physiological concepts related to normal and abnormal newborn EEGs and discuss the three adaptive algorithms for artifact removal. They also present time-frequency representations (TFRs) of seizure signals and discuss the estimation and modeling of the instantaneous frequency related to the main ridge of the TFR.

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Objectives: This study examines human scalp electroencephalographic (EEG) data for evidence of non-linear interdependence between posterior channels. The spectral and phase properties of those epochs of EEG exhibiting non-linear interdependence are studied. Methods: Scalp EEG data was collected from 40 healthy subjects. A technique for the detection of non-linear interdependence was applied to 2.048 s segments of posterior bipolar electrode data. Amplitude-adjusted phase-randomized surrogate data was used to statistically determine which EEG epochs exhibited non-linear interdependence. Results: Statistically significant evidence of non-linear interactions were evident in 2.9% (eyes open) to 4.8% (eyes closed) of the epochs. In the eyes-open recordings, these epochs exhibited a peak in the spectral and cross-spectral density functions at about 10 Hz. Two types of EEG epochs are evident in the eyes-closed recordings; one type exhibits a peak in the spectral density and cross-spectrum at 8 Hz. The other type has increased spectral and cross-spectral power across faster frequencies. Epochs identified as exhibiting non-linear interdependence display a tendency towards phase interdependencies across and between a broad range of frequencies. Conclusions: Non-linear interdependence is detectable in a small number of multichannel EEG epochs, and makes a contribution to the alpha rhythm. Non-linear interdependence produces spatially distributed activity that exhibits phase synchronization between oscillations present at different frequencies. The possible physiological significance of these findings are discussed with reference to the dynamical properties of neural systems and the role of synchronous activity in the neocortex. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

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This study reexamined the association between speech rate and memory span in children from kindergarten to sixth grade (N = 152) in order to potentially account for the inconsistencies within the published literature on this topic. Some of the inconsistencies in past research may reflect the different methods adopted in assessing speech rate. In particular, repeating word triples may itself involve memory demands, contaminating the correlation between speech rate and memory span in younger children. Analyses using composite speech rate and memory span measures showed that speech rate for word triples shared variance with memory span that was independent of speech rate for single words. Moreover, speech rate for word triples was largely redundant with age in explaining additional variation in memory span once the effects of speech rate for single words were controlled. (C) 2002 Elsevier Science.

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In this paper, we describe an algorithm that automatically detects and labels peaks I - VII of the normal, suprathreshold auditory brainstem response (ABR). The algorithm proceeds in three stages, with the option of a fourth: ( 1) all candidate peaks and troughs in the ABR waveform are identified using zero crossings of the first derivative, ( 2) peaks I - VII are identified from these candidate peaks based on their latency and morphology, ( 3) if required, peaks II and IV are identified as points of inflection using zero crossings of the second derivative and ( 4) interpeak troughs are identified before peak latencies and amplitudes are measured. The performance of the algorithm was estimated on a set of 240 normal ABR waveforms recorded using a stimulus intensity of 90 dBnHL. When compared to an expert audiologist, the algorithm correctly identified the major ABR peaks ( I, III and V) in 96 - 98% of the waveforms and the minor ABR peaks ( II, IV, VI and VII) in 45 - 83% of waveforms. Whilst peak II was correctly identified in only 83% and peak IV in 77% of waveforms, it was shown that 5% of the peak II identifications and 31% of the peak IV identifications came as a direct result of allowing these peaks to be found as points of inflection. Copyright (C) 2005 S. Karger AG, Basel.

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Despite several decades of research, neither clinicians nor academics can agree on a single definition of central auditory processing (CAP) or central auditory processing disorder (CAPD). This article considers why this is the case, and comments on the resulting implications for CAP assessment and CAPD rehabilitation in the clinic.