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J. Dichgans

Publications and source records attributed to J. Dichgans.

2 recordsLinked to original sources

Motor reorganization after spinal cord injury: evidence of adaptive changes in remote muscles.

Purpose: Given that SCI leads to substantial changes in biomechanical properties of the body and to widespread postlesional reorganization of the motor system as determined by functional imaging studies, we sought to identify neurophysiological correlations and time course of reorganization affecting muscles more distant to a SCI. Methods: Two arm muscles distant to a SCI (T2-L3), M.biceps brachii (BIC), M.abductor pollicis brevis (APB), were studied in 13 SCI-patients and 15 controls. Motor thresholds at rest (MT), facilitatory effects on MEP-amplitudes (FE) with voluntary activation, MEP-amplitudes with maximal stimulation (MA) and recruitment curves (RC) were measured and correlated with level, age and severity of the lesion. Follow-up studies (t2) were performed in five patients with clinical recovery. Results: Patients exhibited smaller MA from activated BIC, a tendency towards smaller FE and smaller RC-slopes at t1. With clinical recovery, activated BIC-FE, MA and RC-slopes tended to normalize. Conclusions: Our data support the hypothesis that postlesional reorganization of the motor system also involves remote muscles. Considering pattern and time course of reorganization, we speculate that they appear as sequelae of the trauma, possibly representing an adaptation of the motor system to an altered biomechanical status after SCI.

Journal Article↗

Variations on tremor parameters.

This paper describes our analysis procedure for long-term tremor EMG recordings, as well as three examples of applications. The description of the method focuses on how characteristics of the tremor (e.g. frequency, intensity, agonist-antagonist interaction) can be defined and calculated based on surface EMG data. The resulting quantitative characteristics are called "tremor parameters." We discuss sinusoidally modulated, band-limited white noise as a model for pathological tremor-EMG, and show how the basic parameters can be extracted from this class of signals. The method is then applied to (1) estimate tremor severity in clinical studies, (2) quantify agonist-antagonist interaction, and (3) investigate the variations of the tremor parameters using simple methods from time-series analysis. (c) 1995 American Institute of Physics.

Journal Article↗