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@INPROCEEDINGS{Voges:819534,
author = {Voges, Nicole and Sukiban, Jeya and Pauli, Robin and
Denker, Michael and Timmermann, Lars and Grün, Sonja},
title = {{E}valuation of spike sorting results obtained from
neuronal activity in the {S}ubthalamic {N}ucleus of
{P}arkinson patients},
school = {Uniklinik Koeln},
reportid = {FZJ-2016-05177},
year = {2016},
abstract = {In Parkinson’s disease (PD) the STN plays an important
role in the formation of pathological oscillatoryactivity
within the basal ganglia-cortex loop. The primary measure to
reveal such oscillations is the localfield potential (LFP).
While it is assumed that the LFP reflects synaptic input to
groups of neurons, therelationship between this population
signal and the single neuron activity is still a matter of
debate [1, 2].Our long-term goals are to investigate the
spike-LFP relationship in STN recordings obtained during
deepbrain stimulation surgery, as well as to assess the
amount of synchrony between individual neurons in orderto
elucidate how oscillations on the population level translate
to neuronal synchrony.A critical step to achieve this goal
is to correctly isolate the spiking activity of single units
in extracellularSTN recordings from Parkinson patients
measured with a Ben Gun five channel
micro-marcro-electrodeholder. We employed a number of spike
sorting algorithms [e.g., 3] and found that different spike
sortingmethods yield inconsistent results. We quantify these
differences by the number of detected single unitsand the
individual assignment of spikes to the detected units. Our
long-term goal critically depends onthe spike sorting
quality [4], as, e.g., spike synchrony evaluation depends on
the percentage of correctlyidentified spikes [5]. Hence, we
introduced two additional approaches. Firstly, we developed
a set of toolsthat estimates the isolation quality of single
units [6]. These tools calculate the similarity of the spike
shapeswithin one unit compared to other units. Secondly, we
generated synthetic ground truth spike data of mixedunits
with the statistical features of the STN recordings: We
selected the two most different spike shapeswhich we
combined linearly to obtain pairs of spikes with a
controlled distinctness. Assuming Poisson spikerates we
generated spike trains by inserting such spike pairs into a
noisy background obtained by phaseshifting the original
noise. These data enable us to calibrate and verify our
spike sorting results, i.e., tocheck if the number of
extracted units and the spike-to-unit assignment is correct.
By use of these twoapproaches, we compare and evaluate
various spike sorting methods to finally select and apply
the mostappropriate one for the analysis of our STN
recordings.},
month = {Jul},
date = {2016-07-05},
organization = {INM6 retreat, FZJ (Germany), 5 Jul
2016 - 6 Jul 2016},
subtyp = {Other},
cin = {INM-6 / IAS-6},
cid = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828},
pnm = {574 - Theory, modelling and simulation (POF3-574) / DFG
project 147522227 - Charakterisierung der effektiven
Konnektivität motorischer Basalganglien-Kortex-Schleifen
durch loklale Feldpotentiale im Nucelus Subthalamicus und
EEG-Ableitungen bei Morbus Parkinson (147522227)},
pid = {G:(DE-HGF)POF3-574 / G:(GEPRIS)147522227},
typ = {PUB:(DE-HGF)6},
url = {https://juser.fz-juelich.de/record/819534},
}