The pathophysiological model of dystonia proposed that in addition to reduced firing rate in the internal pallidum, changes in the pattern may also play a role in disease manifestation. While common methods for patterns separation depends on arbitrary spiketrain parameters, we considered the new method for neural patterns based on spike density histograms and hierarchical clustering of real datasets. We used the single unit activity recordings from the globus pallidus external (GPe) and the globus pallidus internal (GPi) from 10 cervical dystonia (CD), 7 segmental dystonia (SD) and 8 generalized dystonia (GD) patients undergoing deep brain stimulation surgery. Using novel method, we separated three patterns of activity: burst, burst-like and tonic. Using this separation, we revealed the differences both in firing rate and pattern distribution between dystonia patients. We have shown the suitability of the proposed method for pattern clusterization on real data and assume that further application of this method would facilitate more detailed study of the neural activity in the basal ganglia and the search for neurophysiological biomarkers of movement disorders.
Keywords: Basal ganglia; Cluster analysis; Dystonia; Neuronal activity; Neuronal patterns; Spike density histogram.
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