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P04-Spatial geometric analysis in sleep polysomnographic data
Abstracts / Clinical Neurophysiology 129 (2018) e14–e16
the space to maintain the required percentage of information from the original data. We analyzed 24 features from program WaveFinder, which is used in clinical practice and we used data with 49,554 segments. We kept 98% of information in the reduction to 15 dimension of feature space. For 11 dimension we kept 95%, for 8 dimension we kept 90% and for 6 dimension we kept 85% of information. We also try to reduce space to 3D, which we can visualize. In this case we kept 70% of original information. So the dimension reduction offers the possibility of facilitating classification with corrected loss of information.
e15
Results: We observed a trend towards increased speed of some ST subtests after the iTBS of the SPL. This stimulation induced a significant increase in connectivity between the SPL and the nodule of the cerebellum as well as increased connectivity within the dorsal attentional network. Conclusion: Our results reveal that using TBS we may modify cognitive speed and intranetwork connectivity within the dorsal attentional network. doi:10.1016/j.clinph.2018.01.050
doi:10.1016/j.clinph.2018.01.048
P04-Spatial geometric analysis in sleep polysomnographic data— E. Saifutdinova 1,2, V. Gerla 1, M. Macas 1, L. Lhotska 1,3 (1 CIIRC, CTU in Prague, Czech Republic, 2 NIMH, Czech Republic, 3 FBMI, CTU in Prague, Czech Republic) The study is devoted to data processing methods in automatic sleep polysomnography (PSG) analysis. The idea is in using covariance matrices a carrier of a discriminative information. In the study, we are challenging with a problem of sleep stage classification. We are trying to solve that problem using spatial geometric analysis. For experiments, we took data from seven patients; data were recorded in National Institute of Mental Health. Artifact-free segments were extracted from the data. The covariance matrix was obtained for each segment. The classification was performed using a minimum distance to a class or in k-nearest-neighbor (KNN) method. A distance between objects was calculated using Riemannian Geometry. Classification methods were tested by cross-validation scheme. Using only covariance matrix of multimodal data and without additional information divided by frequency ranges, it is possible to classify sleep stages with high accuracy: the average accuracy for KNN is 0.929, for minimum distance to a class center it is only 0.816. Advantages of the method are working with data from different domains, adjustability to a different number of channels. Support: project No. 17-20480S of GACR, project ‘‘National Institute of Mental Health (NIMH-CZ),” Grant No. ED2.1.00/03.0078 and project No. LO1611. doi:10.1016/j.clinph.2018.01.049
P05-Theta burst stimulation induces changes in dorsal attentional network—L. Anderkova 1,2, D. Pizem 1, P. Klobusiakova 1, M. Gajdos 1, I. Rektorova 1,2 (1 CEITEC, Masaryk University, Brno, Czech Republic, 2 First Department of Neurology, St. Anne’s University Hospital, Brno, Czech Republic) Background and objective: Repetitive transcranial magnetic stimulation is a promising tool to study and modulate brain plasticity and connectivity. The aim of this study was to investigate the effects of theta burst stimulation (TBS) on the Stroop task (ST) performance and related changes in resting state functional brain connectivity. dorsal attentional resting state network. Patients and methods: Twenty healthy young subjects received a session of stimulation of the right inferior frontal gyrus (IFG) and the left superior parietal lobule (SPL) using continuous TBS (cTBS) or intermittent TBS (iTBS) protocol in a randomized order. Prior to and right after each stimulation session each participant performed an fMRI version of the ST and resting state fMRI measurement in 3T Siemens Prisma. Behavioural results from the ST and functional connectivity analyses of the resting state data were performed.
P06-Cortical somatosensory processing after botulinum toxin therapy in post-stroke spasticity—P. Hluštík 1, T. Veverka 1, ˇ ovsky´ 1 P. Hok 1, P. Otruba 1, A. Krobot 1,2, J. Zapletalová 3, P. Kan (1 Department of Neurology, Palacky´ University, Olomouc, Czech Republic, 2 Department of Rehabilitation, University Hospital, Olomouc, Czech Republic, 3 Medical Biophysics, Palacky´ University, Olomouc, Czech Republic) In movement disorders, neurophysiology and functional MRI demonstrated abnormalities of sensorimotor processing, responding to peripheral botulinum toxin A (BoNT) treatment. We used Modified Ashworth scale (MAS) to assess spasticity and median nerve somatosensory evoked potentials (SEP) to study changes in sensorimotor cortical areas after BoNT therapy of post-stroke arm spasticity. Seventeen patients (10 men, 7 women, average age 60.2 years) with post-stroke arm spasticity were treated with BoNT into the affected muscles. Clinical and electrophysiological examinations were performed before BoNT (W0), 4 (W4) and 11 (W11) weeks after BoNT. BoNT treatment was associated with statistically significant MAS decrease MAS at W4 (W0: 2.63 ± 0.40, W4: 1.65 ± 0.37, P = 0.001) and increase at W11 (2.25 ± 0.41), the reduction against W0 remained significant (P = 0.022). In the impaired limb median nerve SEP, both components of interest manifested non-significant trends of transient decrease at W4. Peak-to-peak P22/N30: W0, 1.83 ± 1.3 2 lV, W4, 1.33 ± 0.65 lV, W11, 1.57 ± 1.41 lV. N20/P23 at W0: 2.3 9 ± 2.41 lV, W4: 2.12 ± 1.74 lV, W11: 2.24 ± 2.13 lV. In conclusion, median nerve SEP responses manifested transient non-significant decreases at the time of effective BoNT treatment of post-stroke spasticity, possibly reflecting decreased cortical excitability. Larger patient group may be necessary to reach significance. doi:10.1016/j.clinph.2018.01.051
P07-Automatic pallidal neurons recognition based on the detection of the number of clusters from microrecordings in dystonia—O. Klempírˇ 1, R. Krupicˇka 1, T. Sieger 1,2, R. Jech 2 (1 Czech Technical University, Prague, Czech Republic, 2 Center of Clinical Neuroscience, Prague, Czech Republic) Intraoperative microelectrode records (MER) are considered as the standard electrophysiological method for the precise positioning of the deep brain stimulation (DBS) electrode into the Globus pallidus interna (GPi). The final GPi position is chosen based on the firing patterns of individual neurons. Finding the number of neurons is usually done manually during the spike sorting. We propose methodology for neurons recognition based on the unsupervised learning. Thirty MERs (24 kHz 10s) of the basal ganglia from 10 patients (43.3(±14), 5F) with dystonia were recorded during DBS
the space to maintain the required percentage of information from the original data. We analyzed 24 features from program WaveFinder, which is used in clinical practice and we used data with 49,554 segments. We kept 98% of information in the reduction to 15 dimension of feature space. For 11 dimension we kept 95%, for 8 dimension we kept 90% and for 6 dimension we kept 85% of information. We also try to reduce space to 3D, which we can visualize. In this case we kept 70% of original information. So the dimension reduction offers the possibility of facilitating classification with corrected loss of information.
e15
Results: We observed a trend towards increased speed of some ST subtests after the iTBS of the SPL. This stimulation induced a significant increase in connectivity between the SPL and the nodule of the cerebellum as well as increased connectivity within the dorsal attentional network. Conclusion: Our results reveal that using TBS we may modify cognitive speed and intranetwork connectivity within the dorsal attentional network. doi:10.1016/j.clinph.2018.01.050
doi:10.1016/j.clinph.2018.01.048
P04-Spatial geometric analysis in sleep polysomnographic data— E. Saifutdinova 1,2, V. Gerla 1, M. Macas 1, L. Lhotska 1,3 (1 CIIRC, CTU in Prague, Czech Republic, 2 NIMH, Czech Republic, 3 FBMI, CTU in Prague, Czech Republic) The study is devoted to data processing methods in automatic sleep polysomnography (PSG) analysis. The idea is in using covariance matrices a carrier of a discriminative information. In the study, we are challenging with a problem of sleep stage classification. We are trying to solve that problem using spatial geometric analysis. For experiments, we took data from seven patients; data were recorded in National Institute of Mental Health. Artifact-free segments were extracted from the data. The covariance matrix was obtained for each segment. The classification was performed using a minimum distance to a class or in k-nearest-neighbor (KNN) method. A distance between objects was calculated using Riemannian Geometry. Classification methods were tested by cross-validation scheme. Using only covariance matrix of multimodal data and without additional information divided by frequency ranges, it is possible to classify sleep stages with high accuracy: the average accuracy for KNN is 0.929, for minimum distance to a class center it is only 0.816. Advantages of the method are working with data from different domains, adjustability to a different number of channels. Support: project No. 17-20480S of GACR, project ‘‘National Institute of Mental Health (NIMH-CZ),” Grant No. ED2.1.00/03.0078 and project No. LO1611. doi:10.1016/j.clinph.2018.01.049
P05-Theta burst stimulation induces changes in dorsal attentional network—L. Anderkova 1,2, D. Pizem 1, P. Klobusiakova 1, M. Gajdos 1, I. Rektorova 1,2 (1 CEITEC, Masaryk University, Brno, Czech Republic, 2 First Department of Neurology, St. Anne’s University Hospital, Brno, Czech Republic) Background and objective: Repetitive transcranial magnetic stimulation is a promising tool to study and modulate brain plasticity and connectivity. The aim of this study was to investigate the effects of theta burst stimulation (TBS) on the Stroop task (ST) performance and related changes in resting state functional brain connectivity. dorsal attentional resting state network. Patients and methods: Twenty healthy young subjects received a session of stimulation of the right inferior frontal gyrus (IFG) and the left superior parietal lobule (SPL) using continuous TBS (cTBS) or intermittent TBS (iTBS) protocol in a randomized order. Prior to and right after each stimulation session each participant performed an fMRI version of the ST and resting state fMRI measurement in 3T Siemens Prisma. Behavioural results from the ST and functional connectivity analyses of the resting state data were performed.
P06-Cortical somatosensory processing after botulinum toxin therapy in post-stroke spasticity—P. Hluštík 1, T. Veverka 1, ˇ ovsky´ 1 P. Hok 1, P. Otruba 1, A. Krobot 1,2, J. Zapletalová 3, P. Kan (1 Department of Neurology, Palacky´ University, Olomouc, Czech Republic, 2 Department of Rehabilitation, University Hospital, Olomouc, Czech Republic, 3 Medical Biophysics, Palacky´ University, Olomouc, Czech Republic) In movement disorders, neurophysiology and functional MRI demonstrated abnormalities of sensorimotor processing, responding to peripheral botulinum toxin A (BoNT) treatment. We used Modified Ashworth scale (MAS) to assess spasticity and median nerve somatosensory evoked potentials (SEP) to study changes in sensorimotor cortical areas after BoNT therapy of post-stroke arm spasticity. Seventeen patients (10 men, 7 women, average age 60.2 years) with post-stroke arm spasticity were treated with BoNT into the affected muscles. Clinical and electrophysiological examinations were performed before BoNT (W0), 4 (W4) and 11 (W11) weeks after BoNT. BoNT treatment was associated with statistically significant MAS decrease MAS at W4 (W0: 2.63 ± 0.40, W4: 1.65 ± 0.37, P = 0.001) and increase at W11 (2.25 ± 0.41), the reduction against W0 remained significant (P = 0.022). In the impaired limb median nerve SEP, both components of interest manifested non-significant trends of transient decrease at W4. Peak-to-peak P22/N30: W0, 1.83 ± 1.3 2 lV, W4, 1.33 ± 0.65 lV, W11, 1.57 ± 1.41 lV. N20/P23 at W0: 2.3 9 ± 2.41 lV, W4: 2.12 ± 1.74 lV, W11: 2.24 ± 2.13 lV. In conclusion, median nerve SEP responses manifested transient non-significant decreases at the time of effective BoNT treatment of post-stroke spasticity, possibly reflecting decreased cortical excitability. Larger patient group may be necessary to reach significance. doi:10.1016/j.clinph.2018.01.051
P07-Automatic pallidal neurons recognition based on the detection of the number of clusters from microrecordings in dystonia—O. Klempírˇ 1, R. Krupicˇka 1, T. Sieger 1,2, R. Jech 2 (1 Czech Technical University, Prague, Czech Republic, 2 Center of Clinical Neuroscience, Prague, Czech Republic) Intraoperative microelectrode records (MER) are considered as the standard electrophysiological method for the precise positioning of the deep brain stimulation (DBS) electrode into the Globus pallidus interna (GPi). The final GPi position is chosen based on the firing patterns of individual neurons. Finding the number of neurons is usually done manually during the spike sorting. We propose methodology for neurons recognition based on the unsupervised learning. Thirty MERs (24 kHz 10s) of the basal ganglia from 10 patients (43.3(±14), 5F) with dystonia were recorded during DBS