Ulrich Heute

Oscillating central motor networks in pathological tremors and voluntary movements. What makes the difference

Parkinsonian tremor (PD), essential tremor (ET) and voluntarily mimicked tremor represent fundamentally different motor phenomena, yet, magnetoencephalographic and imaging data suggest their origin in the same motor centers of the brain. Using EEG-EMG coherence and coherent source analysis we found a different pattern of corticomuscular delays, time courses and central representations for the basic and double tremor frequencies typical for PD suggesting a wider range defective oscillatory activity. For the basic tremor frequency similar central representations in primary sensorimotor, prefrontal/premotor and diencephalic (e.g. thalamic) areas were reproduced for all three tremors. But renormalized partial directed coherence of the spatially filtered (source) signals revealed a mainly unidirectional flow of information from the diencephalon to cortex in voluntary tremor, e.g. a thalamocortical relay, as opposed to a bidirectional subcortico-cortical flow in PD and ET promoting uncontrollable, e.g. thalamocortical, loop oscillations. Our results help to understand why pathological tremors although originating from the physiological motor network are not under voluntary control and they may contribute to the solution of the puzzle why high frequency thalamic stimulation has a selective effect on pathological tremor leaving voluntary movement performance almost unaltered.

A short-time spectrum analyzer with polyphase-network and DFT

Abstract Two algorithms for digital spectral analysis are compared: the conventional DFT, and a generalized polyphase principle, which is implemented by connecting a polyphase network to an FFT processor. Close relations as well as essential differences between these two analyzers are demonstrated, using the concept of multirate systems. A hardware realization of the system, capable of handling audio frequencies, is described briefly, and its practical performance is shown to agree with theory. Details on measurements as well as applications will be reported in a companion paper [20].

A new diagnostic test to distinguish tremulous Parkinson's disease from advanced essential tremor

Clinical distinction between advanced essential tremor and tremulous Parkinsons disease can be difficult.

Imaging coherent sources of tremor related EEG activity in patients with Parkinson's disease

The cortical sources of both the basic and first “harmonic” frequency of Parkinsonian tremor are addressed in this paper. The power and coherence was estimated using the multitaper method for EEG and EMG data from 6 Parkinsonian patients with a classical rest tremor. The Dynamic Imaging of Coherent Sources (DICS) was used to find the coherent sources in the brain. Before hand this method was validated for the application to the EEG by showing in 3 normal subjects that rhythmic stimuli (1–5Hz) to the median nerve leads to almost identical coherent sources for the basic and first harmonic frequency in the contralateral sensorimotor cortex which is the biologically plausible result. In all the Parkinson patients the corticomuscular coherence was also present in the basic and the first harmonic frequency of the tremor. However, the source for the basic frequency was close to the frontal midline and the first harmonic frequency was in the region of premotor and sensory motor cortex on the contralateral side for all the patients. Thus the generation of these two oscillations involves different cortical areas and possibly follows different pathways to the periphery.

Subband DFT—part II: accuracy, complexity and applications

Abstract A new DFT computation method based on a subband decomposition described in a companion paper (Shentov et al., 1995) is investigated. The two distinct parts of the algorithm, a preprocessing Hadamard transform stage and a ‘correction’ stage, were interpreted as a filter-bank-plus-recombination network. This interpretation provides a better understanding of the errors caused by dropping subbands in the approximate partial-band DFT computation. In this paper we analyze the approximation errors and computational complexity of the new algorithm in partial-band DFT computation, in addition to outlining a number of its possible applications. Specifically, formulae for the approximation errors due to linear distortions and to aliasing are derived. Two new general formulae are found for the aliasing terms under different conditions; one of them gives an interesting matrix formulation for the coefficients describing the aliasing effects of all frequency bands separately. The computational complexity of the algorithm is analyzed both theoretically and in terms of running-time measurements. This concerns both the full- and partial-band analysis cases in various realization structures as introduced in Shentov et al. (1995). With these insights, the novel algorithm is compared to existing methods, especially for the computation of a limited number of frequency points. A number of application examples are included to illustrate the efficiency of the proposed method in computing approximately the DFT of signals with energies concentrated in small parts of the spectrum.

The central oscillatory network of essential tremor

The responsible pathological mechanisms of essential tremor are not yet clear. In order to understand the mechanisms of the central network its sources need to be found. The cortical sources of both the basic and first “harmonic” frequency of essential tremor are addressed in this paper. The power and coherence were estimated using the multitaper method for EEG and EMG data from 6 essential tremor patients. The Dynamic Imaging of Coherent Sources (DICS) was used to find the coherent sources in the brain. Before hand this method was validated for the application of finding multiple sources for the same oscillation in the brain by using two model simulations which indicated the accuracy of the method. In all the essential tremor patients the corticomuscular coherence was also present in the basic and the first harmonic frequency of the tremor. The source for the basic frequency and the first harmonic frequency was in the region of primary sensory motor cortex, prefrontal and in the diencephalon on the contralateral side for all the patients. Thus the generation of these two oscillations involves the same cortical areas and indicates the oscillation at double the tremor frequency is a harmonic of the basic tremor frequency.

Spectral-subtraction speech enhancement in multirate systems with and without non-uniform and adaptive bandwidths

The method of spectral subtraction is widely used for single-channel speech enhancement, if the speech signal is corrupted by additive noise. It is based on the manipulation of the magnitude of the noisy-speech spectrum. Most realizations use fixed, uniformly-spaced frequency transformations or, equivalently, filter banks with identical sampling rates in each frequency band. In this paper, we generalize the basic structure: Different filter-bank systems with non-uniform and, especially, non-constant, signal-adaptive spectral resolutions and, therefore, different sampling rates are examined. An efficient realization of a time-varying band allocation is proposed. The arising problems are discussed and the enhancement results are compared to each other and to those obtained with uniform spectral transformations.

Discrimination of Parkinsonian tremor from essential tremor using statistical signal characterization of the spectrum of accelerometer signal.

A new technique for discrimination of Parkinson tremor from essential tremor is presented in this paper. This technique is based on Statistical Signal Characterization (SSC) of the spectrum of the accelerometer signal. The data has been recorded for diagnostic purposes in the Department of Neurology of the University of Kiel, Germany. Two sets of data are used. The training set, which consists of 21 essential-tremor (ET) subjects and 19 Parkinson-disease (PD) subjects, is used to obtain the threshold value of the classification factor differentiating between the two subjects. The test data set, which consists of 20 ET and 20 PD subjects, is used to test the technique and evaluate its performance. Three of twelve newly derived SSC parameters show good discrimination results. Specific results of those three parameters on training data and test data are shown in detail. A linear combination of the effects of those parameters on the discrimination results is also included. A total discrimination accuracy of 90% is obtained.

Subband DFT—part I: definition, interpretation and extensions

Abstract A new DFT computation method based on a subband decomposition is outlined for one- and two-dimensional (2-D) real-valued finite-length sequences. The two distinct parts of the algorithm, a preprocessing Hadamard-transform stage and a ‘correction’ stage are interpreted as a filter bank plus a recombination network, and are compared to the corresponding filter bank interpretation of the direct DFT and the classical FFT algorithms. The preprocessing stage decomposes the original sequence into a set of smaller length subsequences approximately separated in the spectral domain. The overall DFT is then given by a weighted sum of smaller length DFTs with the weights determined by the recombination network. The frequency-separation property of the subsequences permits elimination of the subsequences with negligible energy contribution from the DFT calculation thus resulting in a fast approximate DFT computation method. Various implementation schemes for the subband DFT computation method are outlined. As a first extension, adaptive versions are described, finding the band(s) of interest automatically. Furthermore, a generalized preprocessing stage as well as the extension to the 2-D case are addressed.

Time-varying MMSE modulated lapped transform and its applications to transform coding for speech and audio signals

The time-varying modulated lapped transform (MLT) is used in speech and audio coding schemes to adjust the time-frequency resolution, to eliminate pre-echoes in the reconstructed signal, and to improve the coding quality. In order to maintain the perfect-reconstruction property in transition periods, an asymmetrical window has to be used at cost of poorer frequency characteristics. We firstly generalize a window-design method for transition periods in the time-varying MLT with a rigorous proof of its PR property, then present a new window-design method, with which the prototype window is so designed that the total reconstruction distortion in presence of coefficient quantization is minimized. This leads to the time-varying minimum mean-square error (MMSE) MLT. Experiments have shown that the designed windows have better frequency characteristics than the sine window in both transition and regular periods. A general formulation of the quantization distortion for different quantization-error models and for all coding systems is given. A simplified optimal window-design algorithm without direct minimization of the distortion equation is suggested. As an example a transform-coding scheme with time-varying MMSE MLT for speech and audio signals is presented.