Willy Wong

Suppression of γ -Oscillations in the Dorsolateral Prefrontal Cortex following Long Interval Cortical Inhibition: A TMS–EEG Study

Gamma (γ)-oscillations (30–50 Hz) represent important electrophysiological measures, which are generated through the execution of higher order cognitive tasks (eg, working memory) in the dorsolateral prefrontal cortex (DLPFC). By contrast, cortical inhibition (CI) refers to a neurophysiological process in which GABAergic inhibitory interneurons selectively suppress the activation of other neurons in the cortex. Recently, abnormalities in both CI and γ-oscillations have been associated with various neuropsychiatric disorders including schizophrenia. Animal research suggests that suppression of γ-oscillations is, in part, mediated through GABAergic inhibitory neurotransmission. However, no such evidence has been demonstrated in human, largely because of technological limitations. Recently, we reported on novel methods permitting the recording of CI from the DLPFC through transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG). The aim of this study was to examine the effects of GABAergic inhibitory neurotransmission on γ-oscillations by combining TMS with EEG. Long interval cortical inhibition (LICI), a paired TMS paradigm, was used to index GABAB receptor mediated inhibitory neurotransmission in the motor cortex and DLPFC of healthy individuals. γ-Oscillations were significantly inhibited by LICI (38.1±26.5%; p⩽0.013) in the DLPFC but not in the motor cortex. These results provide neurophysiological evidence to demonstrate γ-oscillations are inhibited by LICI in the DLPFC but not in the motor cortex. Such specificity suggests that the modulation of γ-oscillations may represent an important neurophysiological process that may, in part, be responsible for optimal DLPFC functioning in healthy human subjects.

Noise exposure of music teachers.

A noise exposure survey was performed to assess the risk of hearing loss to school music teachers during the course of their activities. Noise exposure of 18 teachers from 15 schools was measured using noise dosimeters. The equivalent continuous noise level (Leq) of each teacher was recorded during single activities (classes) as well as for the entire day, and a normalized 8-hour exposure, termed the noise exposure level (Lex) was also computed. The measured Leq exceeded the 85-dBA limit for 78% of the teachers. Lex exceeded 85 dBA for 39% of the teachers. Limited recommendations on how to reduce the noise exposures are provided. The need for a hearing conservation program has also been emphasized.

Recording human evoked potentials that follow the pitch contour of a natural vowel

We investigated whether pitch-synchronous neural activity could be recorded in humans, with a natural vowel and a vowel in which the fundamental frequency was suppressed. Small variations of speech periodicity were detected in the evoked responses using a fine structure spectrograph (FSS). A significant response (P/spl Lt/0.001) was measured in all seven normal subjects even when the fundamental frequency was suppressed, and it very accurately tracked the acoustic pitch contour (normalized mean absolute error <0.57%). Small variations in speech periodicity, which humans can detect, are therefore available to the perceptual system as pitch-synchronous neural firing. These findings suggest that the measurement of pitch-evoked responses may be a viable tool for objective speech audiometry.

Unification of psychophysical phenomena : The complete form of Fechner's law

Many of the laws and empirical observations of fundamental psychophysics can be unified with a single equation, which has been called the complete form of Fechner’s law. It can be shown that this law embraces both of the commonly used forms: Stevens’s and Fechner’s laws. It assumes one or the other form with appropriate values of the parameters. However, the complete equation confers an advantage beyond simply containing the classical laws. It offers greater flexibility in the representation of experimental data. It is shown that psychophysical phenomena may be represented by any number of triplets of quantities: subjective magnitude of stimulus, subjective just noticeable difference (jnd), and differential threshold. Each of the preceding quantities are functions of the physical magnitude of the stimulus. The investigator has the license to choose two of these quantities in the form he or she thinks is best; the third quantity is determined by the choice of the first two. Thus, for example, different forms of the law of sensation and different forms of the mathematical function for differential threshold may coexist with equal validity.

Indicators for Remission of Suicidal Ideation Following Magnetic Seizure Therapy in Patients With Treatment-Resistant Depression

IMPORTANCE Magnetic seizure therapy (MST) is a novel therapeutic option for treatment-resistant depression (TRD). Suicidal ideation is often associated with TRD and contributes to the increased mortality and morbidity of the disorder. OBJECTIVE To identify a biomarker that may serve as an indicator of remission of suicidal ideation following a course of MST by using cortical inhibition measures from interleaved transcranial magnetic stimulation and electroencephalography (TMS-EEG). DESIGN, SETTING, AND PARTICIPANTS Thirty-three patients with TRD were part of an open-label clinical trial of MST treatment. Data from 27 patients (82%) were available for analysis in this study. Baseline TMS-EEG measures were assessed within 1 week before the initiation of MST treatment using the TMS-EEG measures of cortical inhibition (ie, N100 and long-interval cortical inhibition [LICI]) from the left dorsolateral prefrontal cortex and the left motor cortex, with the latter acting as a control site. INTERVENTIONS The MST treatments were administered under general anesthesia, and a stimulator coil consisting of 2 individual cone-shaped coils was used. MAIN OUTCOMES AND MEASURES Suicidal ideation was evaluated before initiation and after completion of MST using the Scale for Suicide Ideation (SSI). Measures of cortical inhibition (ie, N100 and LICI) from the left dorsolateral prefrontal cortex were selected. N100 was quantified as the amplitude of the negative peak around 100 milliseconds in the TMS-evoked potential (TEP) after a single TMS pulse. LICI was quantified as the amount of suppression in the double-pulse TEP relative to the single-pulse TEP. RESULTS Of the 27 patients included in the analyses, 15 (56%) were women; mean (SD) age of the sample was 46.0 (15.3) years. At baseline, patients had a mean SSI score of 9.0 (6.8), with 8 of 27 patients (30%) having a score of 0. After completion of MST, patients had a mean SSI score of 4.2 (6.3) (pre-post treatment mean difference, 4.8 [6.7]; paired t26 = 3.72; P = .001), and 18 of 27 individuals (67%) had a score of 0 for a remission rate of 53%. The N100 and LICI in the frontal cortex-but not in the motor cortex-were indicators of remission of suicidal ideation with 89% accuracy, 90% sensitivity, and 89% specificity (area under the curve, 0.90; P = .003). CONCLUSIONS AND RELEVANCE These results suggest that cortical inhibition may be used to identify patients with TRD who are most likely to experience remission of suicidal ideation following a course of MST. Stronger inhibitory neurotransmission at baseline may reflect the integrity of transsynaptic networks that are targeted by MST for optimal therapeutic response.

Scaled factorial hidden Markov models: A new technique for compensating gain differences in model-based single channel speech separation

In model-based single channel speech separation, factorial hidden Markov models (FHMM) have been successfully applied to model the mixture signal Y(t) = X(t) + V(t) in terms of trained patterns of the speech signals X(t) and V(t). Nonetheless, when the test signals are scaled versions of the trained patterns (i.e. gxX(t) and gvV(t)), the performance of FHMM degrades significantly. In this paper, we introduce a modification to FHMM, called scaled FHMM, which compensates gain difference. In this technique, first, the scale factors are expressed in terms of the target-to-interference ratio (TIR). Then, an iteration quadratic optimization approach is coupled with FHMM to estimate TIR which with the decoded HMM sequences maximize the likelihood of the mixture signal. Experimental results, conducted on 180 mixtures with TIRs from 0 to 15 dB, show that the proposed technique significantly outperforms unscaled FHMM, and scaled/unscaled vector quantization speech separation techniques.

Deep Brain Stimulation Modulates Gamma Oscillations and Theta-Gamma Coupling in Treatment Resistant Depression.

BACKGROUND Deep brain stimulation (DBS) in the subcallosal cingulate gyrus (SCG) is becoming an effective therapeutic option for treatment resistant depression (TRD). OBJECTIVE/HYPOTHESIS Identifying the neurophysiological mechanisms altered by DBS may lead to more tailored treatment parameters and enhanced efficacy. METHODS Twenty TRD patients with implanted DBS in the SCG were recruited. Patients participated in three EEG recording sessions, one with DBS ON, one with DBS randomized to ON or OFF, and one with DBS OFF. During each session, subjects performed N-back working memory tasks, namely the 0-back and 3-back. Fourteen subjects with valid EEG were included in the analysis. Changes in frontal gamma oscillations (30-50 Hz) and coupling between theta (4-7 Hz) and gamma oscillations as a result of DBS stimulation were quantified and correlated with depressive symptoms. RESULTS DBS stimulation resulted in suppression of frontal oscillations in the ON state relative to the OFF state during the N-back tasks. Greatest suppression was demonstrated in beta and gamma oscillations and most pronounced during the 3-back. Suppression of gamma oscillations in the 3-back correlated with a reduction in depressive symptoms. DBS ON relative to OFF in the 3-back also resulted in an increase in theta-gamma coupling that correlated with a reduction in depressive symptoms. CONCLUSION Suppression of gamma oscillations and increased theta-gamma coupling through DBS is likely mediated by both SCG activation of inhibitory circuits and an enhancement of plasticity in the frontal cortex. Activation of both pathways may explain the therapeutic properties of DBS in TRD.

A linear model of acoustic-to-facial mapping: model parameters, data set size, and generalization across speakers.

The relationship between acoustic and visual speech is important for understanding speech perception, but it also forms the basis behind a type of facial animator, which can predict facial motion during speech given an acoustic input. This relationship was examined by revisiting a linear transformation model of audio-visual speech production. A mathematical model is constructed whereby the visual aspect of speech is reproduced from the acoustic signal via a linear transformation. Unlike previous studies in this area, this paper will address specific aspects of the model as related to the effects of window size for acoustic framing and the critical size of the training set. On average, facial motion is predicted with a correlation of 0.70 to the recorded motion, when the model is trained and then tested on the same subject. This is comparable to previous studies using either similar or different model approaches. Using a model trained on other subjects and then applying it to a new subject resulted in a prediction correlation of 0.65. Furthermore, acoustic windows of 100 ms and a data set of approximately 40 sentences are required for maximum predictability. The results are interpreted in terms of the underlying assumptions of the model.

Simulation of human sensory performance

The capacity of human sensory systems for transmitting information has been approximated in the past by using statistical estimators. However, a substantial margin of error remained. The problem is that the error can be reduced to a negligible level only by increasing the number of human trials or tests to the order of about 10(4). Since a human subject can perform at peak only in the order of 10(2) trials per day, the requisite total number of trials could be obtained realistically only by pooling of data from several subjects. Following Houtsma, we have overcome this problem to a large extent by the use of computer simulation. By introducing parameters characteristic of a given subject into the simulation program, we are able to reproduce the subjects performance (say for 500 trials), and to extrapolate his or her performance using the simulation program to 30000 trials. In this way we can establish limits to the capacity of a single human being to transmit information.

A novel method for removal of deep brain stimulation artifact from electroencephalography

BACKGROUND Deep brain stimulation (DBS) has treatment efficacy in neurological and psychiatric disorders such as Parkinsons disease and major depression. Electroencephalography (EEG) is a versatile neurophysiological tool that can be used to better understand DBS treatment mechanisms. DBS causes artifacts in EEG recordings that preclude meaningful neurophysiological activity from being quantified during stimulation. NEW METHOD In this study, we modeled the DBS stimulation artifact and illustrated a technique for removing the artifact using matched filters. The approach was validated using a synthetically generated DBS artifact superimposed on EEG data. Mean squared error (MSE) between the recovered signal and the artifact-free signal was used to quantify the effectiveness of the approach. RESULTS The DBS artifact was characterized by a series of narrow band components at the harmonic frequencies of DBS stimulation. The filtering approach successfully removed the DBS artifact with MSE value being less than 2% of base signal power for the typical stimulation and recording setups. General guidelines on how to setup DBS EEG studies and configure the subsequent artifact removal process are described. COMPARISON WITH PREVIOUS METHOD To avoid stimulus artifacts, a number of EEG studies with DBS subjects have resorted to turning the stimulator off during recording, while other studies have used low pass filters to remove artifacts and look at frequencies well below 50 Hz. CONCLUSIONS This study establishes a method through which DBS artifact in EEG recordings can be reliably eliminated, thereby preserving a meaningful neurophysiological signal through which to better understand DBS treatment mechanisms.