Auditory Evoked Potential Waveforms Research Articles

Exploring Electrode Placements to Optimize the Identification and Measurement of Early Auditory Evoked Potentials.

Cochlear synaptic loss (termed cochlear synaptopathy) has been suggested to contribute to suprathreshold hearing difficulties. However, its existence and putative effects in humans remain inconclusive, largely due to the heterogeneous methods used across studies to indirectly evaluate the health of cochlear synapses. There is a need to standardize proxies of cochlear synaptopathy to appropriately compare and interpret findings across studies. Early auditory evoked potentials (AEPs), including the compound action potential (AP)/Wave I of the auditory brainstem response are a popular proxy, yet remain variable based on technical considerations. This study evaluated one such consideration-electrode array (i.e., montage)-to optimize the use of early AEP waveforms. In 35 young adults, electrocochleography (ECochG) responses were collected using vertical and horizontal montages. Standard ECochG measures and AP/Wave I and Wave II peak-to-trough amplitudes and latencies were compared between montages. Vertical montage recordings consistently produced significantly larger AP/Wave I peak-to-trough amplitudes compared to horizontal recordings. These findings support the use of a vertical electrode montage for optimal recordings of peripheral cochlear nerve activity. As cochlear synaptopathy continues to be explored in humans, the methods highlighted here should be considered in the development of a standardized assessment.

Auditory evoked potentials in adolescents with autism: An investigation of brain development, intellectual impairment, and neural encoding.

Limited research has evaluated neural encoding of sounds from a developmental perspective in individuals with autism (ASD), especially among those with intellectual disability. We compared auditory evoked potentials (AEPs) in autistic adolescents with a wide range of intellectual abilities (n = 40, NVIQ 30-160) to both age-matched cognitively able neurotypical adolescent controls (NT-A, n = 37) and younger neurotypical children (NT-C, n = 27) to assess potential developmental delays. In addition to a classic measure of peak amplitude, we calculated a continuous measure of intra-class correlation (ICC) between each adolescent participant's AEP and the age-normative, average AEP waveforms calculated from NT-C and NT-A to study differences in signal morphology. We found that peak amplitudes of neural responses were significantly smaller in autistic adolescents compared to NT-A. We also found that the AEP morphology of autistic adolescents looked more like NT-A peers than NT-C but was still significantly different from NT-A AEP waveforms. Results suggest that AEPs of autistic adolescents present differently from NTs, regardless of age, and differences cannot be accounted for by developmental delay. Nonverbal intelligence significantly predicted how closely each adolescent's AEP resembled the age-normed waveform. These results support an evolving theory that the degree of disruption in early neural responses to low-level inputs is reflected in the severity of intellectual impairments in autism.

Modulation of mGlu2 Receptors, but Not PDE10A Inhibition Normalizes Pharmacologically-Induced Deviance in Auditory Evoked Potentials and Oscillations in Conscious Rats.

Improvement of cognitive impairments represents a high medical need in the development of new antipsychotics. Aberrant EEG gamma oscillations and reductions in the P1/N1 complex peak amplitude of the auditory evoked potential (AEP) are neurophysiological biomarkers for schizophrenia that indicate disruption in sensory information processing. Inhibition of phosphodiesterase (i.e. PDE10A) and activation of metabotropic glutamate receptor (mGluR2) signaling are believed to provide antipsychotic efficacy in schizophrenia, but it is unclear whether this occurs with cognition-enhancing potential. The present study used the auditory paired click paradigm in passive awake Sprague Dawley rats to 1) model disruption of AEP waveforms and oscillations as observed in schizophrenia by peripheral administration of amphetamine and the N-methyl-D-aspartate (NMDA) antagonist phencyclidine (PCP); 2) confirm the potential of the antipsychotics risperidone and olanzapine to attenuate these disruptions; 3) evaluate the potential of mGluR2 agonist LY404039 and PDE10 inhibitor PQ-10 to improve AEP deficits in both the amphetamine and PCP models. PCP and amphetamine disrupted auditory information processing to the first click, associated with suppression of the P1/N1 complex peak amplitude, and increased cortical gamma oscillations. Risperidone and olanzapine normalized PCP and amphetamine-induced abnormalities in AEP waveforms and aberrant gamma/alpha oscillations, respectively. LY404039 increased P1/N1 complex peak amplitudes and potently attenuated the disruptive effects of both PCP and amphetamine on AEPs amplitudes and oscillations. However, PQ-10 failed to show such effect in either models. These outcomes indicate that modulation of the mGluR2 results in effective restoration of abnormalities in AEP components in two widely used animal models of psychosis, whereas PDE10A inhibition does not.

How do albino fish hear?

Pigmentation disorders such as albinism are occasionally associated with hearing impairments in mammals. Therefore, we wanted to investigate whether such a phenomenon also exists in non-mammalian vertebrates. We measured the hearing abilities of normally pigmented and albinotic specimens of two catfish species, the European wels Silurus glanis (Siluridae) and the South American bronze catfish Corydoras aeneus (Callichthyidae). The non-invasive auditory evoked potential (AEP) recording technique was utilized to determine hearing thresholds at 10 frequencies from 0.05 to 5 kHz. Neither auditory sensitivity nor shape of AEP waveforms differed between normally pigmented and albinotic specimens at any frequency tested in both species. Silurus glanis and C. aeneus showed the best hearing between 0.3 and 1 kHz; the lowest thresholds were 78.4 dB at 0.5 kHz in S. glanis (pigmented), 75 dB at 1 kHz in S. glanis (albinotic), 77.6 dB at 0.5 kHz in C. aeneus (pigmented) and 76.9 dB at 1 kHz in C. aeneus (albinotic). This study indicates no association between albinism and hearing ability. Perhaps because of the lack of melanin in the fish inner ear, hearing in fishes is less likely to be affected by albinism than in mammals.

Auditory Evoked Potentials in the Detection of Interaural Intensity Differences in Children and Adults

The goal of the current study was to identify neurophysiological indices of binaural processing in children with no history of hearing loss or listening problems. The results will guide our efforts to diagnose children for whom impaired binaural processing may contribute to difficulty understanding speech in adverse listening environments. Our main aim was to document the cortical auditory evoked potentials (AEPs) in response to interaural intensity differences (IIDs) in children. It is well known, however, that the morphology of AEPs is substantially different in children and adults. Comparison of AEPs in response to IIDs between children and adults allowed us to evaluate age-related differences in the AEP waveform of binaural processing. Nine children (ages 7 yr 0 mo to 9 yr 4 mo) and 11 adults (23 to 34 yr) with normal hearing and no known or suspected neurological or academic problems listened to click stimuli under earphones. Click trains consisted of broadband noise of 1-msec duration with a click rate of 100 Hz. In the experimental condition (IID-present) 50-msec intervals containing an interaural intensity difference of 20 dB were introduced periodically in the continuous stream of otherwise diotic click trains. The diotic trains alternated in intensity between 50 and 70 dB peSPL. In the baseline condition (IID-absent), the same continuous diotic click stream utilized in the IID-present condition was presented with no IID. Finally, for comparison with existing literature on AEPs in children and adults, we presented monaural click trains of 50-msec duration, like those used in the IID stimulus (but with no continuous stream) to the left ear at 70 dB peSPL, with an interstimulus interval of 750 msec. Stimuli were presented in separate blocks for each stimulus type and AEPs were recorded in a passive listening condition. A prominent AEP activation was present in both age groups for the IID-present condition; the IID-absent condition did not evoke substantial AEPs. Adult waveform characteristics of the AEPs to monaural clicks and IID-present around 100 and 200 msec were comparable to previous reports. The children demonstrated the expected AEP activation patterns in response to monaural clicks (i.e., positivity around 100 msec, followed by prominent negativity around 250 msec); however their AEP waveforms to IIDs were mainly comprised of a prolonged positivity around 200 to 250 msec after stimulus onset. A two-step temporal-spatial Principal Component Analysis (PCA) was used to evaluate the temporal (time) and spatial (electrode location) composition of the AEP waveforms in children and adults in response to IID-present and IID-absent conditions. Separate repeated-measures ANOVAs with factor scores as the dependent variable were conducted for each temporal factor (TF) representing the waveform deflections around 100, 200 and 250 msec (i.e., TF110, TF200, and TF255) at the frontocentral spatial factor (SF1). Significantly greater negative activation was observed in adults than in children in response to IID-present for TF110. The IID-present condition evoked a significantly greater waveform inflection for TF200 in both age groups than IID-absent. A positive going activation for TF255 was observed in the IID-present condition in children but not in adults. This study compared obligatory AEPs in response to binaural processing of IIDs in children and adults with normal hearing. The morphology of the AEP waveform in children was different for monaural clicks and IID-present stimuli. The difference between AEPs for monaural clicks and IID-present did not occur in adults. It is likely that polarity reversal of the AEPs in response to the IID accounts for the observed AEP morphology in children.

Rapid brain discrimination of sounds of objects.

Electrical neuroimaging in humans identified the speed and spatiotemporal brain mechanism whereby sounds of living and man-made objects are discriminated. Subjects performed an "oddball" target detection task, selectively responding to sounds of either living or man-made objects on alternating blocks, which were controlled for in their spectrogram and harmonics-to-noise ratios between categories. Analyses were conducted on 64-channel auditory evoked potentials (AEPs) from nontarget trials. Comparing responses to sounds of living versus man-made objects, these analyses tested for modulations in local AEP waveforms, global response strength, and the topography of the electric field at the scalp. In addition, the local autoregressive average distributed linear inverse solution was applied to periods of observed modulations. Just 70 ms after stimulus onset, a common network of brain regions within the auditory "what" processing stream responded more strongly to sounds of man-made versus living objects, with differential activity within the right temporal and left inferior frontal cortices. Over the 155-257 ms period, the duration of activity of a brain network, including bilateral temporal and premotor cortices, differed between categories of sounds. Responses to sounds of living objects peaked approximately 12 ms later and the activity of the brain network active over this period was prolonged relative to that in response to sounds of man-made objects. The earliest task-related effects were observed at approximately 100 ms poststimulus onset, placing an upper limit on the speed of cortical auditory object discrimination. These results provide critical temporal constraints on human auditory object recognition and semantic discrimination processes.

Cerebral Monitoring in the Operating Room and the Intensive Care Unit – An Introductory for the Clinician and a Guide for the Novice Wanting to Open a Window to the Brain

An evoked potential differs from the EEG mainly in two ways: 1. The EEG is a random, continuous signal, which arises from the ongoing activity of the outer layers of the cortex. An evoked potential is the brain's response to a repetitive stimulus along a specific nerve pathway. 2.EEG signals range from 10-200 milliVolt (mV). Evoked potentials are smaller in amplitude (1-5-20 microVolt requiring precise electrode positioning and special techniques (signal averaging) to extract the specific response from the underlying EEG "noise". The technique of signal averaging, as originally described by Dawson in 1954 [69J, has been further developed in computer processing. The technique is now used by applying a stimulus repeatedly--preferably at randomized intervals--and to record the evoked response over the corresponding area of the brain, averaging out mathematically the change over the number of stimuli. Rationale for the use of EPs in the OR and the ICU. Evoked potentials (EPs) serve the following major purposes: 1. Monitoring of the functional integrity of neural structures that may be at risk during, for instance, ECC (extracorporeal circulation) or endarterectomy indicating cerebral hypoxia. 2. Monitoring of the effects of anesthetic agents and other centrally active drugs, which, besides the cortex, affect deeper neuronal structures. 3. Orthopedic cases where the spinal cord is at risk such as Harrington rod insertion and removal. 4. Clamping of the abdominal aortic artery during aneurysmectomy resulting in a potential damage of the lower parts of the spinal cord. 5. Clipping of an intracerebral aneurysm, which may be impeding blood flow to vital cerebral textures. 6. An indicator of cerebral hypoxia when the blood pressure is deliberately lowered. 7. Operation on peripheral nerves and nerve roots to identify early trauma. 8. Monitoring the cerebral function during controlled hypothermia when the EEG becomes flat. 9. Monitoring of the pathophysiological conditions after severe head trauma and the effects of therapy. 10. An intraoperative warning device of unsuspected awareness during light anesthesia when movement is abolished by muscle relaxants and cardiovascular responses are modified by vasoactive drugs. In case of the latter the stimulus is a small electrical potential applied to the skin of the hand. Thereafter, the stimulus travels along the specific nervous pathways inducing (= generating) potential activation at various sites. The generation of potential changes at various sites along the pathway is an index for the integrity of the nerve. Thus, the evoked potential can be considered a neurophysiological response (usually of the cortex) to impulses originating from some externally stimulated sensory nerve. They provide a physiological measure of the functional integrity of the sensory nerve pathway, which can be used as a clinical diagnostic tool as well as for intraoperative monitoring. The evoked potential usually is recorded from the specific cortical area corresponding to the stimulus input. The classification of evoked potentials. Stimulating a sensory nervous pathway induces evoked potentials. If the auditory nerve is stimulated by "clicks" from headphones, it is called the auditory evoked potential (AEP). The early part of the AEP waveform (less than 10 msec) is called the Brainstem Auditory Evoked Potential (BAEP) since it reflects the passing of the impulse through the brainstem. If a nerve on the arm or the leg is stimulated by a small electrical current applied to the overlying skin, it is called the Somatosensory Evoked Potential (SSEP). If, however, the retina is stimulated by means of flicker light or a sudden change in a checkerboard pattern, the evoked potential thus recorded over the corresponding cortical area is called the Visual Evoked Potential (VEP). Evoked potentials are used both as a diagnostic tool and as a monitoring technique. As diagnostic tests, evoked potentials are useful to evaluate neurologic disorders such as: a) multiple sclerosis, b) acoustic nerve tumors, and c) optic neuritis. As a monitoring modality, evoked potentials are used during all surgical procedures, which might compromise part of the brain or the spinal cord.

Cerebral Monitoring in the Operating Room and the Intensive Care Unit: An introductory for the clinician and a guide for the novice wanting to open a window to the brain

An evoked potential differs from the EEG mainly in two ways: 1. The EEG is a random, continuous signal, which arises from the ongoing activity of the outer layers of the cortex. An evoked potential is the brain's response to a repetitive stimulus along a specific nerve pathway. 2.EEG signals range from 10-200 milliVolt (mV). Evoked potentials are smaller in amplitude (1-5-20 microVolt requiring precise electrode positioning and special techniques (signal averaging) to extract the specific response from the underlying EEG "noise". The technique of signal averaging, as originally described by Dawson in 1954 [69J, has been further developed in computer processing. The technique is now used by applying a stimulus repeatedly--preferably at randomized intervals--and to record the evoked response over the corresponding area of the brain, averaging out mathematically the change over the number of stimuli. Rationale for the use of EPs in the OR and the ICU. Evoked potentials (EPs) serve the following major purposes: 1. Monitoring of the functional integrity of neural structures that may be at risk during, for instance, ECC (extracorporeal circulation) or endarterectomy indicating cerebral hypoxia. 2. Monitoring of the effects of anesthetic agents and other centrally active drugs, which, besides the cortex, affect deeper neuronal structures. 3. Orthopedic cases where the spinal cord is at risk such as Harrington rod insertion and removal. 4. Clamping of the abdominal aortic artery during aneurysmectomy resulting in a potential damage of the lower parts of the spinal cord. 5. Clipping of an intracerebral aneurysm, which may be impeding blood flow to vital cerebral textures. 6. An indicator of cerebral hypoxia when the blood pressure is deliberately lowered. 7. Operation on peripheral nerves and nerve roots to identify early trauma. 8. Monitoring the cerebral function during controlled hypothermia when the EEG becomes flat. 9. Monitoring of the pathophysiological conditions after severe head trauma and the effects of therapy. 10. An intraoperative warning device of unsuspected awareness during light anesthesia when movement is abolished by muscle relaxants and cardiovascular responses are modified by vasoactive drugs. In case of the latter the stimulus is a small electrical potential applied to the skin of the hand. Thereafter, the stimulus travels along the specific nervous pathways inducing (= generating) potential activation at various sites. The generation of potential changes at various sites along the pathway is an index for the integrity of the nerve. Thus, the evoked potential can be considered a neurophysiological response (usually of the cortex) to impulses originating from some externally stimulated sensory nerve. They provide a physiological measure of the functional integrity of the sensory nerve pathway, which can be used as a clinical diagnostic tool as well as for intraoperative monitoring. The evoked potential usually is recorded from the specific cortical area corresponding to the stimulus input. The classification of evoked potentials. Stimulating a sensory nervous pathway induces evoked potentials. If the auditory nerve is stimulated by "clicks" from headphones, it is called the auditory evoked potential (AEP). The early part of the AEP waveform (less than 10 msec) is called the Brainstem Auditory Evoked Potential (BAEP) since it reflects the passing of the impulse through the brainstem. If a nerve on the arm or the leg is stimulated by a small electrical current applied to the overlying skin, it is called the Somatosensory Evoked Potential (SSEP). If, however, the retina is stimulated by means of flicker light or a sudden change in a checkerboard pattern, the evoked potential thus recorded over the corresponding cortical area is called the Visual Evoked Potential (VEP). Evoked potentials are used both as a diagnostic tool and as a monitoring technique. As diagnostic tests, evoked potentials are useful to evaluate neurologic disorders such as: a) multiple sclerosis, b) acoustic nerve tumors, and c) optic neuritis. As a monitoring modality, evoked potentials are used during all surgical procedures, which might compromise part of the brain or the spinal cord.

Spatiotemporal maturation of the central and lateral N1 components to tones

This paper examines maturational changes in the spatiotemporal features of central and lateral N1 components of the auditory evoked potentials (AEPs) to tone stimuli presented with a long stimulus onset asyncrony (SOA; 4200 ms) using the scalp current density (SCD) technique. A group of typically developing children ranging from 6 to 12 years of age and a group of adults were studied. Recently studies have begun to explore the topography of these components in children. These studies, however, often used rapidly presented stimuli and did not elicit observable central N1s in the younger children. Our stimuli elicited both central and lateral N1s. Peak latencies of both components decreased with age. Peak amplitude also decreased with age for the lateral N1 but not for the central N1. Consequently, the difference between the lateral N1 and the central N1 amplitudes (or the ratio of lateral N1 amplitude to central N1 amplitude) also decreased with age, dramatically altering the morphology of the elicited AEP waveforms. Topography of the lateral N1 did not change with age. The location of maximal activation for the central N1 appeared to move more medially with age but this ‘apparent’ movement is probably due to the decreasing impact of the partially overlapping lateral N1 component whose amplitude is significantly smaller in adults than in children.

Of Kittens and Kids: Altered Cortical Maturation following Profound Deafness and Cochlear Implant Use

Profoundly deaf children who use a cochlear implant (CI) provide a unique opportunity to investigate the effects of auditory sensory deprivation on the maturing human central nervous system. Previous results suggest that children fitted with a CI show evidence of altered auditory cortical maturation, based on evoked potentials. This altered maturation was characterized by both latency delays and morphological changes in the cortical auditory evoked potentials (AEPs). Based on prolonged P₁ latencies compared to age-matched normal-hearing (NH) peers, these data suggested a delayed maturation nearly equivalent to the period of deafness. However, rates of maturation for this AEP peak were essentially the same in NH and CI children. This suggests that, given enough time, the AEPs of CI children would assume the characteristic morphology found in older NH teens and NH adults. However, the data also indicated a substantial alteration of the typical set of obligatory P₁-N_1b-P₂ peaks, specifically related to the absence of the N₁ potential. Recent analyses of more extensive sets of longitudinal and cross-sectional data indicate that even after many years of implant use, the AEPs of CI users in their late teens remain very different from those of their NH peers. The P₁ peak latency remains prolonged and P₁ amplitude remains much larger in CI users than in age-matched NH teens. These findings suggested that age-related changes in the P₁ peak are completed by 12 years of age. In addition, the normal N_1b peak fails to emerge in virtually all of the CI children tested in our laboratory. A major new interpretation of the abnormal maturation of AEP waveforms in CI children is presented. It is based on direct evidence showing that a persistent immaturity of the superficial layer axons has persistent negative effects on the generation of the N_1b and, consequently, on the morphology of the AEPs. A comparison of scalp-recorded AEPs from implanted children with local field potentials measured from the cortical surface in deaf white kittens suggests the effects of deafness and CI use are similar across these mammalian species. For both species, a period of profound deafness followed by CI stimulation reveals a substantial immaturity in cortical activation even after a period of electrical stimulation by the CI.

Developmental changes in P1 and N1 central auditory responses elicited by consonant-vowel syllables

Normal maturation and functioning of the central auditory system affects the development of speech perception and oral language capabilities. This study examined maturation of central auditory pathways as reflected by age-related changes in the P1/N1 components of the auditory evoked potential (AEP). A synthesized consonant-vowel syllable (ba) was used to elicit cortical AEPs in 86 normal children ranging in age from 6 to 15 years and ten normal adults. Distinct age-related changes were observed in the morphology of the AEP waveform. The adult response consists of a prominent negativity (N1) at about 100 ms, preceded by a smaller P1 component at about 50 ms. In contrast, the child response is characterized by a large P1 response at about 100 ms. This wave decreases significantly in latency and amplitude up to about 20 years of age. In children, P1 is followed by a broad negativity at about 200 ms which we term N1b. Many subjects (especially older children) also show an earlier negativity (N1a). Both N1a and N1b latencies decrease significantly with age. Amplitudes of N1a and N1b do not show significant age-related changes. All children have the N1b; however, the frequency of occurrence of N1a increases with age. Data indicate that the child P1 develops systematically into the adult response; however, the relationship of N1a and N1b to the adult N1 is unclear. These results indicate that maturational changes in the central auditory system are complex and extend well into the second decade of life.

Fast habituation of the long-latency auditory evoked potential in the awake albino rat

Fast habituation of the long-latency, vertex-recorded auditory evoked potential (AEP) peaks in humans was first described by Callaway (1973) as a reduction in AEP amplitude that occurs to the second of a pair of acoustic stimuli when both stimuli are presented with an interstimulus interval (ISI) of no more than 10 sec. When acoustic stimuli are presented in pairs with an ISI of 2 sec and an interpair interval (IPI) of approximately 10 sec, reduction in amplitude to the second tone occurs by as much as 30–50%. Fast habituation may depend somewhat on a subject's anticipation of the stimulus and on other factors related to attention and orienting. Studies in our laboratory have demonstrated this amplitude decrement to the second tone of a pair in human infants, children and adults and have explored the implications of this finding with respect to attentional processes and the allocation of cerebral resources. In the present investigation we describe an animal model of fast habituation. Here, vertex-recorded AEPs were obtained to paired tone stimuli delivered to awake adult male Sprague-Dawley rats chronically implanted with skull electrodes. Findings showed: (a) an AEP wave form with 8 distinct peaks, (b) for one component there was a marked decrement in amplitude from tone 1 to tone 2 in recordings obtained from an electrode placed slightly to the right of midline, and (c) that there were no significant differences in peak latencies across tones. This methodology may further our understanding of fast habituation in humans and may prove useful for studies of attention, orienting, and resource allocation using techniques that are not possible for use with human subjects.

Clinical evaluation of a method for automatic detection and removal of artifacts in auditory evoked potential monitoring

The objective of our study was to evaluate the method for detection and removal of artifacts in evoked potential monitoring described earlier by Cluitmans and colleagues in a clinical setting. The method for detection and removal of artifacts by Cluitmans and colleagues is based on the assumption that a sweep of the recorded electroencephalogram (EEG) signal contains artifacts if one or more variables derived from the signal deviates strongly from the normal range of values. Once these normal ranges are defined, all future EEG recordings that are recorded under comparable circumstances can be automatically evaluated for artifacts by tracking when one or more signal variables falls outside the normal range. To assess the performance of this method in a clinical setting, recordings from a learning set were visually evaluated for artifacts. From the empirical distribution functions of the signal variables, the thresholds for automatic detection of artifacts were determined. The auditory evoked potential (AEP) waveforms resulting after automatic screening were compared with the waveforms obtained after visual evaluation of the raw signal combined with manual exclusion of signal periods containing artifacts. The quality of the resulting waveform was improved by our method of automatic detection and removal of artifacts in 97% of partly contaminated recordings. In only 2% of the recordings, automatic screening slightly degraded the resulting waveform. We conclude that the described method of automatic detection and removal of artifacts in AEP recordings effectively improves the quality of the resulting AEP waveform, without excessive rejection of artifact-free signal periods. The signal variables used in this method seem appropriate for distinguishing artifact-free signal periods from periods containing artifacts for the types of artifact that were studied.

Cortical responses to speech sounds and their formants in normal infants: maturational sequence and spatiotemporal analysis

Cortical auditory evoked potentials (AEPs) to the synthesized syllables [da[ and [ta[ and to the isolated 3 formants of [da[ were obtained from 32 normal infants studied at monthly intervals from birth through 3 months and at 6 months of age. A bilateral array of 16 electrodes referenced to the mid-occiput permitted a topographic analysis of the cortical AEPs at selected latencies. A differential maturational sequence was seen: a predominantly negative cortical AEP wave form became positive, first over the frontocentral region (around term), and then over the temporal region (at 1-2 months). The timing of these electrophysiological changes coincides with a differential anatomical maturational sequence in the auditory cortex, as myelination and synaptogenesis are more advanced in primary than secondary auditory areas at term. All infants in this study followed this developmental sequence. However, there was no systematic effect of the center frequency of the formant stimuli on the maturational level of their respective cortical AEPs, suggesting a relative maturational equivalence in those regions of auditory cortex responding to stimuli across the frequency range present in human speech. In term infants, an initial midline positivity and bitemporal negativities were asynchronous in their peak and offset latencies. suggesting independent generators for each of these components. In infants from 3 to 6 months of age, cortical AEP wave forms consisted of 2 initial positive peaks followed by a negative peak. While the wave forms were similar over midline and lateral scalp, spatiotemporal analysis revealed differences in the latency of onset, duration and in the spatial extent of these components, again suggesting that 2 bilateral, temporally overlapping generators contribute to the cortical AEP. No systematic topographic difference was observed in the cortical AEPs elicited by each of the 3 formants, which differed in center frequencies.

パソコンによる聴覚誘発電位の計測と処理

A microcomputer-based system for the recording and analysis of the auditory evoked potentials (AEPs) was developed. A software system consists of three parts. (1) Measurement of the AEPs : By the use of the A/D converter with DMA interface and the D/A converter with internal clock, the AEPs are recorded while acoustic stimuli are being presented. The AEPs are averaged in realtime and the waveform is displayed on the CRT with every presentation of acoustic stimuli. (2) Off-line data analysis : One can measure the values of response amplitude and latency at two vertical cursors on the averaged AEP waveform which is displayed on the CRT. A waveform difference between two averaged AEP waveforms is calculated and listed to a file. (3) Topographic disply : Interpolation is carried out by means of the two-variable sampling function. The interpolated values are quantized to 11 levels. The potential distributions are graphically displayed on the CRT. We have confirmed that the system is useful in the analysis of the AEPs of the Mynah bird.

Scalp distribution of human auditory evoked potentials. II. Evidence for overlapping sources and involvement of auditory cortex

The scalp distributions of human auditory evoked potentials (AEPs) between 20 and 250 msec were investigated using non-cephalic reference recordings. AEPs to binaural click stimuli were recorded simulataneously from 20 scalp locations over the right hemisphere in 11 subjects. Computer-generated isovoltage topographic maps at high temporal resolution were used to assess the stability of AEP scalp distributions over time and relate them to major peaks in the AEP wave forms. For potentials between 20 and 60 msec, the results demonstrate a stable scalp distribution of dipolar form that is consistent with sources in primary auditory cortex on the superior temporal plane near the temporoparietal junction. For potentials between 60 and 250 msec, the results demonstrate changes in AEP morphology across electrode locations and changes in scalp distribution over time that lead to two major conclusions. First, AEPs in this latency period are generated by multiple sources which partially overlap in time. Second, one or more regions of auditory cortex contribute significantly to AEPs in this period. Additional data are needed to determine the relative contribution of auditory cortex sources on the superior temporal plane and the lateral temporal surface and to identify AEP sources outside the temporal lobe.