Date: Wednesday, June 22, 2016
Session Title: Parkinson's disease: Neuroimaging and neurophysiology
Session Time: 12:00pm-1:30pm
Location: Exhibit Hall located in Hall B, Level 2
Objective: To determine the most suitable spike sorting algorithm for intraoperatively recorded extracellular currents in the subthalamic nucleus (STN) of patients with Parkinson’s disease (PD).
Background: In PD the STN may play an important role in the generation of pathological oscillatory activity within the basal ganglia-cortex loop. Extracellular currents recorded from the STN of PD patients, obtained during Deep Brain Stimulation surgery can provide important information about pathological spiking activity of STN neurons. A challenge in analyzing neural spike data is to assign detected spikes to individual neurons that contribute to the extracellularly recorded activity. To this end, a group of algorithms commonly referred to as "spike sorting" is used. Today, numerous spike sorting algorithms are available, partly side-by-side in commercial spike sorting packages. However, it is unclear to which degree different algorithms yield similar sorting results.
Methods: Spiking activity was recorded intraoperatively at multiple sites within the STN-area of 3 awake PD patients. The recorded time series were sorted ("Plexon Offline-Sorter") by 2 semi-automatic (template-based (TB) and K-Means) and by 4 automatic algorithms (K-Means, Valley-Seeking (VS), standard- and t-distribution Expectation-Maximization). We took a multiple validation approach by comparing the spike times in the detected single units (SU) to determine how the sorting procedure influences the subsequent spike train analysis.
Results: Preliminary results demonstrated a wide variability in the number of detected SU between the 6 sorting algorithms (26-62 SU in 21 channels). Additionally, the analysis of the spike trains statistics revealed a large variability in the inter-spike interval (between 52 +/-38 and 321 +/- 778 (mean +/-SD in ms)) and the coefficient of variation (between 0.61 and 18.91). In summary, though not optimal, TB- and VS-algorithms proved to be the most conservative among the sorting methods investigated.
Conclusions: Our results strongly argue for the need of a standardized validation procedure for spike sorting algorithms based on ground-truth data. Moreover, to ensure reproducibility of results and enable scientists to understand differences between results obtained from different experiments, a detailed description of spike sorting procedure becomes a necessity.
To cite this abstract in AMA style:J. Sukiban, R. Pauli, T.A. Dembek, I. Weber, F. Jung, N. Voges, M. Denker, S. Gruen, L. Timmermann. Influence of different spike sorting algorithms on the detection of single unit spiking activity in the subthalamic nucleus of patients with Parkinson’s disease [abstract]. Mov Disord. 2016; 31 (suppl 2). https://www.mdsabstracts.org/abstract/influence-of-different-spike-sorting-algorithms-on-the-detection-of-single-unit-spiking-activity-in-the-subthalamic-nucleus-of-patients-with-parkinsons-disease/. Accessed September 23, 2023.
« Back to 2016 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/influence-of-different-spike-sorting-algorithms-on-the-detection-of-single-unit-spiking-activity-in-the-subthalamic-nucleus-of-patients-with-parkinsons-disease/