Negative motor networks: Electric cortical stimulation and diffusion tensor imaging.

INTRODUCTION: This study investigated the networks of Negative motor areas (NMAs) using electric cortical stimulation and diffusion tensor imaging (DTI). METHODS: Twelve patients with intractable focal epilepsy, in which NMAs were identified by electrical cortical stimulation, were enrolled in this study. Electric stimulation at 50Hz was applied to the electrodes during motor tasks to identify the NMAs. DTI was used to identify the subcortical fibers originating from the NMAs found by electrical stimulation. RESULTS: NMAs were found in lateral frontal areas (premotor area (PM) and precentral gyrus) in all 12 patients, in pre-supplementary motor areas (pre-SMAs) in four patients, and in posterior parietal cortices (PPCs) in four. DTI detected fibers connecting to the ipsilateral PMs, PPCs and temporal regions via U-fibers, superior longitudinal fasciculus (SLF), and arcuate fasciculus (AF) from the lateral frontal NMAs. Pre-SMA-NMAs had connections with ipsilateral PMs and contralateral pre-SMAs via the frontal aslant tract and transcallosal commissural fibers, and PPC-NMAs with ipsilateral PMs via SLF and AF. CONCLUSION: This study found the characteristic cortical network of each NMA, and especially revealed new insight of pre-SMA-NMA and PPC NMA. These NMAs might be associated with different mechanism of negative motor response.

Contribution of motor unit activity enhanced by acute fatigue to physiological tremor of finger.

The contribution of motor unit activity to a physiological tremor (hereafter called as tremor) in a middle finger is studied by both a power spectrum and a correlation analysis in which the correlation coefficient and the coherence spectrum are obtained when five kinds of loads, 0, 50, 100, 150, and 200 g, are added to the middle finger for two minutes in a loading experiment on twelve male subjects. A weight of 200 g is applied to the subjects for ten minutes in a fatigue experiment. Throughout both experiments, the middle finger remains stretched from the load of the weight. The tremor is measured by an accelerometer (MT-3T, Nihon Kohden, Japan) attached to the middle finger, and the surface electromyogram (EMG) is measured by bipolar electrodes placed on m. extensor digitorum communis. A power spectrum analysis is carried out on the tremor and EMG, and a correlation analysis is performed on the relationship between the tremor and the demodulated EMG. It is found in the loading experiment that when the weight on the finger increases, the amplitude of the tremor oscillation increases since the activity of the motor units of the muscle is enhanced by the phenomenon of recruitment. Two frequency components of the tremor spectra at 10 Hz and 25 Hz under a no load condition reflect the components of the activity of the motor units of the muscle because the tremor shows a significant correlation in the frequency zone of 10 Hz and 25 Hz with the demodulated EMG. The lower frequency component of the tremor spectrum at 10 Hz results in synchronized activity of the motor units, while the higher frequency at 25 Hz occurs from the stretch reflex loop via the motoneurons of the spinal cord. The shift of the higher frequency component to the lower frequency domain due to the load of the weight originates from the prolongation of the response time of the finger mechanical system because the lag time at the peak of the correlation coefficient increases with the load of the weight. It is found in the fatigue experiment that the amplitude of the tremor oscillation increases with the progress of fatigue. The increase is caused by the recruitment of the motor unit activity of the muscle holding the finger as well as by the synchronization of the firings of the motoneurons. The progress of the synchronization is verified by the fact that the mean power frequency (MPF) of the EMG spectrum decreases and the correlation between the tremor and the demodulated EMG increases with the progress of fatigue. The mechanisms of the increase of the amplitude of the tremor oscillation under the load of the weight to the finger and under the state of fatigue of the finger are elucidated by the analysis of the tremor and EMG.

Evaluation of spectral characteristics of physiological tremor of finger based on mechanical model.

A mathematical model for a physiological tremor of a finger, hereafter referred to as tremor, has been developed in order to evaluate the variation of amplitudes and frequencies at two peaks obtained in the power spectrum of the tremor under two conditions: (a) four loads of weight, 50, 100, 150, and 200 g, are added to the finger (state of load of weight), and (b) the finger is held in a horizontal position with a weight of 200 g for ten minutes (state of fatigue). The mathematical model for the tremor consists of a mechanical system of the finger and a reflex feedback system via the spinal and the supraspinal pathways. In the condition of the load of the weight, the two peaks shown in the tremor spectrum at about 10 Hz and 25 Hz under the condition of no load are generated by the existence of the spinal and the supraspinal pathways. The variation of the frequencies at the two peaks due to the load of the weight, which is not obtained by the previous model (Sakamoto et al., 1998), is possible to evaluate by use of the reflex feedback system which includes the terms up to the second order derivative. The amplitudes at the two peaks of the tremor spectrum increase with the additional weight on the finger because of the increase of the activity level of the active element of muscles controlling the finger. This element is one of the sub-systems constituting the tremor model. Because the activity level of the active element corresponds to the contraction force produced by the muscles, the increase of the amplitudes at the two peaks results from the progress of the recruitment of the motor unit activity by the addition of the weight. The term presenting the activity level is here introduced in the tremor model, so that the phenomenon is found. In the condition of the state of fatigue, the amplitudes at the two peaks increase with the progress of the fatigue because the active element is presented as a function of the time course, so that the activity level of the active element increases with the time course. The increase of the activity level implies the progresses of the recruitment and synchronization of the motor unit activity due to the fatigue. These results obtained from the analysis of the tremor model verify the hypothesis that the amplitude of the tremor oscillation is attributable to the changes of the activity of the spinal and the supraspinal systems.

Analysis of interaction of spinal and supraspinal reflex pathways involved in physiological tremor.

A model of feedback type in which physiological tremor are produced by both muscular skeletal system and reflex action is described. Analysis of this model shows that the interaction between the spinal and the supraspinal reflex pathways is important in responsible for low and high frequency oscillations of physiological tremor. Particularly the effect of gain ratio of the two pathways is studied in order to examine the role for the two reflex pathways in controlling neuromuscular oscillations. The existence of a critical point of the gain ratio at which one oscillating frequency transitions to two ones is predicted theoretically. A shift of the critical point with variations of weight load is found and suggests a changeable correlation relation between the spinal and the supraspinal pathways due to loading conditions. Our computations for physiological tremor demonstrate the results that the high frequency component of about 25 Hz is produced by the muscle-spinal reflex loop, and the low frequency component of about 10 Hz originates from the central nervous system or from supraspinal reflex loop. Several relations derived in this study are described, and they can be compared with experimental observations. Our model sheds considerable light on the details of the possible mechanism for physiological tremor. In addition, a possibility arising from our study is that the tremulous oscillation associated with some pathological states, say Parkinson's disease, may arise from modified gains in one or more of the reflex pathways.