Filtering of Multichannel Recordings of Neuronal Activity during Deep Brain Stimulation
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1
RTRA/Foundation "Nanoscience at the limits of Nanoelectronics", France
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2
Institute of Applied System Analysis, Ukraine
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3
Institute of Mathematical Machines and Systems, Ukraine
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4
CEA, LETI, DTBS/STD/LE2S, France
High-frequency (100-300 Hz) Deep Brain Stimulation is a family of surgical procedure for treating a variety of disabling neurological symptoms. Analyses of neuronal activity during the DBS allow improving the protocol and developing novel DBS applications. One of the major difficulties of study is that the appropriate signal of neuronal activity, namely the extracellular microelectrode recording of action potentials (spikes), cannot be observed directly during the stimulation due to stimulation artifacts present in the recordings. The periodically repeated electrical impulses delivered to the target zone in the brain produce the artifacts of a common waveform but not identical due irregularities of stimulus production. The Artifact-to-Signal Ratio (ASR), which is the ratio of the mean of amplitudes of artifacts to the averaged amplitude of spikes of neuronal activity, varies from 5 to 50. That means that the amplitude of artifacts is 5-50 times lager than the amplitudes of spikes of neuronal activity.
There are several recent studies focused on filtering of stimulation artifacts from the signal. The best results were demonstrated by the use of template subtraction techniques based on averaging of a set of peri-stimulus segments. To take into account the variability of artifacts several templates are generated. Residual windows about 0.8-0.9 ms (about 11% of record time for DBS 130Hz) remove from the signal. Such a cut-off can significantly corrupt the results. Generally the stimulation artifacts are treated as a periodic function with additive noise. The analyses of time dependent STDs of artefacts showed that the reason for the loss of quality of filtering is the loss of synchronization. To face the problem an approach for DBS signal filtration based on the synchronization in phase space were proposed by authors. Nonlinear oscillation model of the artifacts of stimulation instead of the model with additive noise was applied. The multi channel recoding allows introducing the model in deviations which provides the following improvement. This paper presents the algorithm of filtering on bases of the model in deviations and the results of testing.
In order to explore the algorithm and to compare to the standard approaches two-channel artificial signal(s) with predefined ASR for each channel were constructed by mixing the record containing artifacts with no neuronal activity and record of single-neuron spikes and no stimulation. Appropriate constant gives desired value of ASR. The computational experiments shows that while the method of reference leads to the lost of 11% of information Phase Space Filtering provides only 0.6% of errors in spike detection (ASR≈5). Moreover the errors in spike detection don’t exceed 5% even in the case of artifacts of high amplitude (ASR≈5).
The study was partially supported by the Grant of Medtronic and by the Grant ICOBI of Foundation “Nanoscience at the limits of Nanoelectronics”.
Conference:
Neuroinformatics 2009, Pilsen, Czechia, 6 Sep - 8 Sep, 2009.
Presentation Type:
Poster Presentation
Topic:
Computational neuroscience
Citation:
Aksenova
TI,
Nowicki
DV and
Benabid
AL
(2019). Filtering of Multichannel Recordings of Neuronal Activity during Deep Brain Stimulation.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2009.
doi: 10.3389/conf.neuro.11.2009.08.110
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Received:
25 May 2009;
Published Online:
09 May 2019.
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Correspondence:
T. I Aksenova, RTRA/Foundation "Nanoscience at the limits of Nanoelectronics", Grenoble, France, tetiana.aksenova@cea.fr