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D Poeppel

Publications and source records attributed to D Poeppel.

At least 19 recordsLinked to original sources
PubMed2000

Temporal encoding in auditory evoked neuromagnetic fields: stochastic resonance.

Recent investigations have demonstrated that temporal patterns of sensory neural activity detected by magnetoencephalography (MEG) reflect features of the stimulus. In this study, neuromagnetic activity was investigated using an event detection algorithm based on the correlation coefficient. The results of the technique are compared with widely used methods of analysis in two experimental conditions and are shown to identify features in the single-trial MEG response that are not apparent in the response obtained by averaging across repeated trials. As an example of the technique, the physiologic jitter in latency associated with the M100 of auditory evoked fields was reproducibly measured. Specifically, higher intensity sounds were associated with an increased reliability. The technique was also applied to the noise-enhanced evoked auditory response, producing an objective demonstration of a cortical manifestation of the phenomenon of stochastic resonance-the paradoxical enhancement in the measurement of the signal-to-noise ratio (SNR) induced by optimal addition of noise to system input.

Acoustic Stimulation↗
PubMed2000

Towards a functional neuroanatomy of speech perception.

The functional neuroanatomy of speech perception has been difficult to characterize. Part of the difficulty, we suggest, stems from the fact that the neural systems supporting 'speech perception' vary as a function of the task. Specifically, the set of cognitive and neural systems involved in performing traditional laboratory speech perception tasks, such as syllable discrimination or identification, only partially overlap those involved in speech perception as it occurs during natural language comprehension. In this review, we argue that cortical fields in the posterior-superior temporal lobe, bilaterally, constitute the primary substrate for constructing sound-based representations of speech, and that these sound-based representations interface with different supramodal systems in a task-dependent manner. Tasks that require access to the mental lexicon (i.e. accessing meaning-based representations) rely on auditory-to-meaning interface systems in the cortex in the vicinity of the left temporal-parietal-occipital junction. Tasks that require explicit access to speech segments rely on auditory-motor interface systems in the left frontal and parietal lobes. This auditory-motor interface system also appears to be recruited in phonological working memory.

Journal Article↗
PubMed2000

Latency of the auditory evoked neuromagnetic field components: stimulus dependence and insights toward perception.

This review will focus on investigations of the auditory evoked neuromagnetic field component, the M100, detectable in the magnetoencephalogram recorded during presentation of auditory stimuli, approximately 100 milliseconds after stimulus onset. In particular, the dependence of M100 latency on attributes of the stimulus, such as intensity, pitch and timbre will be discussed, along with evidence relating M100 latency observations to perceptual features of the stimuli. Comparison with investigation of the analogous electrical potential component, the N1, will be made. Parametric development of stimuli from pure tones through complex tones to speech elements will be made, allowing the influence of spectral pitch, virtual pitch and perceptual categorization to be delineated and suggesting implications for the role of such latency observations in the study of speech processing. The final section will deal with potential clinical applications offered by M100 latency measurements, as objective indices of normal and abnormal cortical processing.

Acoustic Stimulation↗
PubMed2000

Estimating neural sources from each time-frequency component of magnetoencephalographic data.

We have developed a method that incorporates the time-frequency characteristics of neural sources into magnetoencephalographic (MEG) source estimation. This method, referred to as the time-frequency multiple-signal-classification algorithm, allows the locations of neural sources to be estimated from any time-frequency region of interest. In this paper, we formulate the method based on the most general form of the quadratic time-frequency representations. We then apply it to two kinds of nonstationary MEG data: gamma-band (frequency range between 30-100 Hz) auditory activity data and spontaneous MEG data. Our method successfully detected the gamma-band source slightly medial to the N1m source location. The method was able to selectively localize sources for alpha-rhythm bursts at different locations. It also detected the mu-rhythm source from the alpha-rhythm-dominant MEG data that was measured with the subject's eyes closed. The results of these applications validate the effectiveness of the time-frequency MUSIC algorithm for selectively localizing sources having different time-frequency signatures.

Acoustic Stimulation↗
PubMed2000

Auditory cortex accesses phonological categories: an MEG mismatch study.

The studies presented here use an adapted oddball paradigm to show evidence that representations of discrete phonological categories are available to the human auditory cortex. Brain activity was recorded using a 37-channel biomagnetometer while eight subjects listened passively to synthetic speech sounds. In the phonological condition, which contrasted stimuli from an acoustic /dae/-/tae/ continuum, a magnetic mismatch field (MMF) was elicited in a sequence of stimuli in which phonological categories occurred in a many-to-one ratio, but no acoustic many-to-one ratio was present. In order to isolate the contribution of phonological categories to the MMF responses, the acoustic parameter of voice onset time, which distinguished standard and deviant stimuli, was also varied within the standard and deviant categories. No MMF was elicited in the acoustic condition, in which the acoustic distribution of stimuli was identical to the first experiment, but the many-to-one distribution of phonological categories was removed. The design of these studies makes it possible to demonstrate the all-or-nothing property of phonological category membership. This approach contrasts with a number of previous studies of phonetic perception using the mismatch paradigm, which have demonstrated the graded property of enhanced acoustic discrimination at or near phonetic category boundaries.

Acoustic Stimulation↗
PubMed1999

MEG spatio-temporal analysis using a covariance matrix calculated from nonaveraged multiple-epoch data.

We propose a magnetoencephalographic (MEG) spatio-temporal analysis in which the measurement-covariance matrix is calculated using nonaveraged multiple epoch data. The proposed analysis has two advantages. First, a very narrow time window can be used for the source estimation. Second, accurate localization is possible even when the source activation has a time jitter. Experiments using auditory evoked MEG data clearly demonstrate these advantages.

Algorithms↗
PubMed1999

Time-frequency MEG-MUSIC algorithm.

We propose a method that incorporates the time-frequency characteristics of neural sources into magnetoencephalographic (MEG) source estimation. The method is based on the multiple-signal-classification (MUSIC) algorithm and it calculates a time--frequency matrix in which diagonal and off-diagonal terms are the auto and crosstime--frequency distributions of multichannel MEG recordings, respectively. The method averages this time-frequency matrix over the time--frequency region of interest. The locations of neural sources are then estimated by checking the orthogonality between the noise subspace of this averaged matrix and the sensor lead field. Accordingly, the method allows us to estimate the locations of neural sources from each time--frequency component. A computer simulation was performed to test the validity of the proposed method, and the results demonstrate its effectiveness.

Algorithms↗
PubMed1998

Auditory evoked M100 reflects onset acoustics of speech sounds.

Magnetoencephalography (MEG) was used to investigate the response to speech sounds that differ in onset dynamics, parameterized as words that have initial stop consonants (e.g., /b/, /t/) or do not (e.g., /m/, /f/). Latency and amplitude of the M100 auditory evoked neuromagnetic field, recorded over right and left auditory cortices, varied as a function of onset: stops had shorter latencies and higher amplitudes than no-stops in both hemispheres, consistent with the hypothesis that M100 is a sensitive indicator of spectral properties of acoustic stimuli. Further, activation patterns in response to stops/no-stops differed in the two hemispheres, possibly reflecting differential perceptual processing for the acoustic-phonetic cues at the onset of spoken words.

Adult↗
PubMed1998

Latency of evoked neuromagnetic M100 reflects perceptual and acoustic stimulus attributes.

The latency of components of the auditory evoked neuromagnetic field has been shown to reflect, or encode, stimulus attributes. In particular, the M100 component, occurring approximately 100 ms post stimulus onset has a latency that depends on stimulus pitch, spectral complexity and presentation level. This study used magnetoencephalography to record neuromagnetic fields evoked by presentation of two-tone complexes consisting of various proportions of 100 Hz and 1 kHz energy. These are perceived categorically, as evidenced by classification and reaction time measurements. It is found that the M100 latency also varies categorically, that is, characterized by two plateau regions with a sharp interface. Thus, we find that not only does the M100 latency reflect acoustic attributes of a stimulus, but also such perceptual characteristics.

Acoustic Stimulation↗
PubMed1998

Peri-threshold encoding of stimulus frequency and intensity in the M100 latency.

Recent work has suggested that, in addition to spatial tonotopy, pitch and timbre information may be encoded in the temporal activity of the auditory cortex. Specifically, the post-stimulus latency of the maximal cortical evoked neuromagnetic field (M100 or N1m) is a function of stimulus frequency. We investigated the additional effect of varying the stimulus intensity on the M100 response. A 37-channel biomagnetometer recorded neuromagnetic fields over the temporal lobe of healthy volunteers in response to monaurally presented tones. The frequency dependence of the M100 latency remained remarkably invariant even at low stimulus intensity. Thus, for peri-threshold stimuli, frequency information appears encoded in the temporal form of the evoked response.

Acoustic Stimulation↗
PubMed1998

Comparison of covariance-based and waveform-based subtraction methods in removing the interference from button-pressing finger movements.

A covariance matrix-based subtraction method has recently been proposed to remove interference using two MEG measurements: The first has both target and interfering activities and the second only has the interference. This paper compared covariance matrix-based subtraction with conventional waveform-based subtraction, which requires that the waveforms of interference be equal at every time point between the two measurements. Our analysis showed that covariance-subtraction only requires that the time-average of the squared intensity of interference be equal between the two measurements. As a result, the method is still effective when the onset of interference differs or even their measured waveforms differ between the two measurements. The covariance- and waveform-subtraction methods were both applied to remove the interference caused by response-button-pressing finger movements in auditory-evoked MEG measurements. The results of this application demonstrated the superiority of the covariance-subtraction method over the conventional waveform-subtraction method.

Algorithms↗
PubMed1998

MEG covariance difference analysis: a method to extract target source activities by using task and control measurements.

A method is proposed for extracting target dipolesource activities from two sets of evoked magnetoencephalographic (MEG) data, one measured using task stimuli and the other using control stimuli. The difference matrix between the two covariance matrices obtained from these two measurements is calculated, and a procedure similar to the MEG-multiple signal classification (MUSIC) algorithm is applied to this difference matrix to extract the target dipole-source configuration. This configuration corresponds to the source-configuration difference between the two measurements. Computer simulation verified the validity of the proposed method. The method was applied to actual evoked-field data obtained from simulated task-and-control experiments. In these measurements, a combination of auditory and somatosensory stimuli was used as the task stimulus and the somatosensory stimulus alone was used as the control stimulus. The proposed covariance difference analysis successfully extracted the target auditory source and eliminated the disturbance from the somatosensory sources.

Algorithms↗
PubMed1998

Magnetoencephalography and magnetic source imaging.

Current brain imaging techniques, such as computed tomography (CT) and magnetic resonance imaging (MRI), provide noninvasive, high-resolution images that depict fine anatomic structure and delineate pathology by control of image contrast and sensitivity to the physicochemical microenvironment. These methods, although invaluable for the identification, characterization, and localization of lesions, do not provide any assessment of the functional viability of brain tissues, nor of the spatial organization of sensory, motor, and cognitive systems. However, such additional functional information is of great significance to the clinician in the determination of treatment strategies and patient management.

Brain Mapping↗
PubMed1997

Learning transfer and neuronal plasticity in humans trained in tactile discrimination.

Adult humans were unilaterally trained in a tactile discrimination task of sequentially applied multi-finger stimuli. Magnetic source imaging (MSI) was performed before and after the training to evaluate use-dependent neuronal plasticity. All subjects showed fast improvements in performance and complete transfer of the learned task. MSI recordings revealed an unilateral decrease in current dipole strength in the somatosensory system contralateral to the trained hand. Attenuation of sensory evoked fields and a complete learning transfer indicate learning in associative and secondary cortices rather than perceptual plasticity operating on neuronal populations involved in early sensory processing. This findings are discussed with respect to an equivalent animal model and to learning specificity and generalization.

Adult↗
PubMed1997

Processing of vowels in supratemporal auditory cortex.

The auditory evoked neuromagnetic fields elicited by synthesized vowels of two different fundamental frequencies F0 were recorded in six subjects over the left and right temporal cortices using a 37-channel biomagnetometer. Single equivalent current dipole modeling of the fields elicited by all vowel types localized activity to a well-circumscribed area in supratemporal auditory cortex in both hemispheres. There were hemisphere asymmetries in the amplitude and latency of the M100 response. We also observed changes in M100 latency related to vowel type, but not to F0. There was no clear effect of vowel type or F0 on dipole localization for the M100, but a possible vowel type by latency interaction. These M100 data provide further evidence that vowels are processed independently of their pitch.

Adult↗
PubMed1997

Noise covariance incorporated MEG-MUSIC algorithm: a method for multiple-dipole estimation tolerant of the influence of background brain activity.

This paper proposes a method of localizing multiple current dipoles from spatio-temporal biomagnetic data. The method is based on the multiple signal classification (MUSIC) algorithm and is tolerant of the influence of background brain activity. In this method, the noise covariance matrix is estimated using a portion of the data that contains noise, but does not contain any signal information. Then, a modified noise subspace projector is formed using the generalized eigenvectors of the noise and measured-data covariance matrices. The MUSIC localizer is calculated using this noise subspace projector and the noise covariance matrix. The results from a computer simulation have verified the effectiveness of the method. The method was then applied to source estimation for auditory-evoked fields elicited by syllable speech sounds. The results strongly suggest the method's effectiveness in removing the influence of background activity.

Algorithms↗
PubMed1996

Latency of auditory evoked M100 as a function of tone frequency.

This study investigated post-stimulus latency of the M100 component of auditory evoked fields as a function of tone frequency. A 37-channel biomagnetometer was used to record neuromagnetic fields over the temporal lobe in response to monaurally presented tones. M100 peaks in evoked field amplitude were found for each subject. The post-stimulus latency was observed to vary parabolically with tone frequency. Latencies as short as 99 ms were found in response to mid-audio range frequencies (1000-2000 Hz), whereas lower (100-500 Hz) and higher (3000-5000 Hz) frequencies were associated with longer latencies (up to 153 ms). All fields gave M100 dipole localizations in auditory cortex. Although it was not possible to resolve spatial tonotopy, it appears that frequency information is encoded in the temporal evoked response.

Acoustic Stimulation↗