Computational Neuroscience Group

Department of Cybernetics, Karlovo nám. 13, 121 35 Praha 2
doc. Daniel Novak
Tel.: +420 224 357 314
http://neuro.felk.cvut.cz/

Who we are?

We focus on studying the physiology and pathophysiology of the human brain, mostly those of patients suffering from Parkinson disease or dystonia, and treated with the deep brain stimulation. By analyzing and modeling single neuron recordings and fMRI data, our aim is to better understand how the brain and deep brain stimulation work.

Daniel Novák, PhD – group leader
Tomáš Sieger, PhD – researcher
Jiří Wild, PhD – researcher
Eduard Bakštein, PhD – researcher
Jakub Schneider – PhD student
Jiří Vošmik – master student

Our research

Emotion-related neurons of the human subthalamus

Deep brain stimulation of the subthalamic nucleus (STN) is an effective treatment of advanced Parkinson's disease. However, it can be linked with adverse side-effects of altered perception and processing of emotions. To investigate the involvement of the STN in motivational and emotional processes, we searched for single STN neurons whose activity was related to emotional stimuli.

Nuclei identification from the microelectrode EEG

In order to achieve good clinical outcome with low side effects, accurate positioning of the stimulating contacts in the subthalamic nucleus (STN) is necessary. The most commonly used method of accurate electrode placement consists of 1) preoperative MRI and CT imaging, 2) intra-operative micro-EEG recording around the presumed target position using a set of micro-electrodes 3) post-operative verification of electrode position using MRI and/or CT.

Artifact detection in the microEEG

Micro-EEG recordings are very susceptible to motion-induced and other types of technical artifacts. As the mEEG signals are often used not only in DBS targetting and nuclei identification process but also in all sorts of neuroscience experiments and unit activity evaluation, it is crucial to identify artifact-free segments.

Spike sorting mehods

The detection of neural spike activity is a technical challenge that is a prerequisite for studying many types of brain function. Measuring the activity of individual neurons accurately can be dicult due to large amounts of background noise and the diculty in distinguishing the action potentials of one neuron from those of others in the local area.

DBS objective parameter setting

It has been already more than 20 years that deep brain stimulation (DBS) was used instead of pallidotomy on patient with Parkinson disease (PD). This procedure is used to reduce some symptoms of PD and therefore reduce amount of medication needed. In DBS electrodes are implanted in specific part of brain (mostly in globus pallidus (GP) or subthalamic nucleus (STN)).

Cooperation

We tightly cooperate work with colleagues from various institutions and disciplines, such as:

  • Department of Neurology, 1st Faculty of Medicine, Charles University in Prague and General Teaching Hospital, Czech Republic
  • Max Planck Institute, Leipzig, Germany
  • Technological Institute of Informatics, Polytechnic University of Valencia, Spain
  • 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Czech Republic
  • Group ESIEE, Paris, France
  • Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University in Prague and General University Hospital, Prague, Czech Republic
  • Third Department of Medicine, Department of Endocrinology and Metabolism, 1st Faculty of Medicine, Charles University in Prague and General University Hospital, Czech Republic
  • Faculty of Physical Education and Sports, Charles University, Prague. Czech Republic
  • National Institute of Mental Health, Klecany,Czech Republic
  • Medizinische Klinik IV, Staedtisches Klinikum Karlsruhe, Germany
  • Centro de Bioingenierıa, Universidad Pontificia Bolivariana, Medellın, Colombia
  • Institute of Microbiology, Academy of Sciences of the Czech Republic
  • University of Bologna, Italy
  • Newcastle University, United Kingdom
  • University of Vienna, Austria

Selected publications

  • Bakštein, E., Sieger, T., Wild, J., Novák, D., Schneider, J., Vostatek, P., Urgošík, D., Jech, R. Methods for automatic detection of artifacts in microelectrode recordings. In: Journal of Neuroscience Methods, 290, 39–51, 2017
  • Sieger T, Hurley CB, Fišer K, Beleites C. Interactive Dendrograms: The R Packages idendro and idendr0. Journal of Statistical Software 76(10), doi: 10.18637/jss.v076.i10, 2017
  • Bakštein, E.; Sieger, T.; Novák, D.; Jech, R. Probabilistic model of neuronal background activity in deep brain stimulation trajectories, In: Information Technology in Bio- and Medical Informatics. Basel: Springer, pp. 97-111. LNCS 9832,2 016
  • Sieger T., Serranová T., Růžička F., Vostatek P., Wild J., Štastná D., Bonnet C., Novák D., Růžička E., Urgošík D., Jech R. Distinct populations of neurons respond to emotional valence and arousal in the human subthalamic nucleus, Proceedings of the National Academy of Sciences of the United States of America, 2015 112 (10) 3116-3121; published ahead of print February 23, doi:10.1073/pnas.1410709112, 2015
  • Sieger T., Bonnet C., Serranová T., Wild J., Novák D., Růžička F., Urgošík D., Růžička E., Gaymard B., Jech R. Basal ganglia neuronal activity during scanning eye movements in Parkinson’s disease. PLoS ONE, 8(11):e78581, 2013
  • P. Vostatek, D. Novak, T. Rychnovský, S. Rychnovská, Diaphragm Postural Function Analysis Using Magnetic Resonance Imaging, Plos One, 2013
  • J.Wild, Z.Prekopcsak, T.Sieger, D.Novak, ,R.Jech, Performance comparison of spike sorting algorithms for single-channel recordings, Journal of Neuroscience Methods, 203(2), 2012
  • D. Novak, F.Albert, D.Cuesta, 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Discrimination of Deep Brain Nuclei using Regularity Measure, 2012
  • Bakštein, E. - Burgess, J. - Warwick, K. - Ruiz, V. - Aziz, T. - et al.: Parkinsonian Tremor Identification with Multiple Local Field Potential Feature Classification. Journal of Neuroscience Methods. vol. 2, no. 209, p. 320-330. ISSN 0165-0270, 2012