Faculty of Philosophy, Department of Clinical Psychology
Jagiellonian University, Krakow
The Czech Academy of Sciences, Institute of Scientific Instruments
Student / Ph.D. Student in EEG Research
We offer a position in the Computational Neuroscience research team
Multi-modal and Functional Neuroimaging Research Group is
Opening new PhD positions
in the field of Neurosciences
New MASARYK NEUROSCIENCE HUB website has been released.
We are happy to announce that our new website has been released.
A unique research cluster for the treatment of stroke has been established in Brno
STROKE BRNO is an interdisciplinary research cluster with the aim of connecting the knowledge and expertise of academic and industrial partners and ensuring the effective use of knowledge from basic research in clinical practice.
Our Latest Research
Next-generation sequencing in children with epilepsy: The importance of precise genotype-phenotype correlation
Aim: The primary goal was to determine the yield of next-generation sequencing (NGS) epilepsy gene panels used for epilepsy etiology diagnosing using a multidisciplinary approach and to demonstrate the importance of genotype-phenotype correlations. The secondary goal was to evaluate the application of precision medicine in selected patients.
Methods: This single-center retrospective study included a total of 175 patients (95 males and 80 females) aged 0-19 years. They were examined between 2015 and 2020 using an NGS epilepsy gene panel (270 genes). A bioinformatic analysis was performed including copy number variation identification. Thorough genotype-phenotype correlation was performed.
Evaluating Magnetic Resonance Diffusion Properties Together with Brain Volumetry May Predict Progression to Multiple Sclerosis
Rationale and objectives: Although the gold standard in predicting future progression from clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS) consists in the McDonald criteria, efforts are being made to employ various advanced MRI techniques for predicting clinical progression. This study's main aim was to evaluate the predictive power of diffusion tensor imaging (DTI) of the brain and brain volumetry to distinguish between patients having CIS with future progression to CDMS from those without progression during the following 2 years and to compare those parameters with conventional MRI evaluation.
Materials and methods: All participants underwent an MRI scan of the brain.
Electrical brain stimulation and continuous behavioral state tracking in ambulatory humans
Objective: Electrical deep brain stimulation (DBS) is an established treatment for patients with drug-resistant epilepsy. Sleep disorders are common in people with epilepsy, and DBS may actually further disturb normal sleep patterns and sleep quality. Novel devices capable of DBS and continuous intracranial EEG (iEEG) telemetry enable detailed assessments of therapy efficacy and tracking sleep related comorbidities. Here, we investigate the feasibility of automated sleep classification using continuous iEEG data recorded from Papez's circuit in four patients with drug resistant mesial temporal lobe epilepsy using an investigational implantable sensing and stimulation device with electrodes implanted in bilateral hippocampus (HPC) and anterior nucleus of thalamus (ANT).
Approach: The iEEG recorded from HPC is used to classify sleep during concurent DBS targeting ANT.
The role of central autonomic nervous system dysfunction in Takotsubo syndrome: a systematic review
Introduction: Takotsubo syndrome (TTS), also known as stress cardiomyopathy or "broken heart" syndrome, is a mysterious condition that often mimics an acute myocardial infarction. Both are characterized by left ventricular systolic dysfunction. However, this dysfunction is reversible in the majority of TTS patients.
Purpose: Recent studies surprisingly demonstrated that TTS, initially perceived as a benign condition, has a long-term prognosis akin to myocardial infarction. Therefore, the health consequences and societal impact of TTS are not trivial. The pathophysiological mechanisms of TTS are not yet completely understood. In the last decade, attention has been increasingly focused on the putative role of the central nervous system in the pathogenesis of TTS.
Cytokine-chemokine profiles in the hippocampus of patients with mesial temporal lobe epilepsy and hippocampal sclerosis
Purpose: Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) is the most common drug-resistant epilepsy. Despite major advances in epilepsy research, the epileptogenesis of the MTLE-HS is not well understood. The altered neuroimmune response is one of the pathomechanisms linked to progressive epileptogenesis in MTLE-HS, and understanding its role may help design future cures for pharmaco-resistant MTLE-HS. Here, the neuroimmune function was evaluated by the assessment of cytokine-chemokine profiles in brain samples from the hippocampus of patients with MTLE-HS.
Methods: Brain samples from patients with MTLE-HS collected during epileptosurgical resection (n = 21) were compared to those obtained from autopsy controls (n = 13).
Intracranial electrophysiological recordings from the human brain during memory tasks with pupillometry
Data comprise intracranial EEG (iEEG) brain activity represented by stereo EEG (sEEG) signals, recorded from over 100 electrode channels implanted in any one patient across various brain regions. The iEEG signals were recorded in epilepsy patients (N = 10) undergoing invasive monitoring and localization of seizures when they were performing a battery of four memory tasks lasting approx. 1 hour in total. Gaze tracking on the task computer screen with estimating the pupil size was also recorded together with behavioral performance. Each dataset comes from one patient with anatomical localization of each electrode contact. Metadata contains labels for the recording channels with behavioral events marked from all tasks, including timing of correct and incorrect vocalization of the remembered stimuli. The iEEG and the pupillometric signals are saved in BIDS data structure to facilitate efficient data sharing and analysis.
Identification of Laminar Composition in Cerebral Cortex Using Low-Resolution Magnetic Resonance Images and Trust Region Optimization Algorithm
Pathological changes in the cortical lamina can cause several mental disorders. Visualization of these changes in vivo would enhance their diagnostics. Recently a framework for visualizing cortical structures by magnetic resonance imaging (MRI) has emerged. This is based on mathematical modeling of multi-component T1 relaxation at the sub-voxel level. This work proposes a new approach for their estimation. The approach is validated using simulated data. Sixteen MRI experiments were carried out on healthy volunteers. A modified echo-planar imaging (EPI) sequence was used to acquire 105 individual volumes. Data simulating the images were created, serving as the ground truth. The model was fitted to the data using a modified Trust Region algorithm. In single voxel experiments, the estimation accuracy of the T1 relaxation times depended on the number of optimization starting points and the level of noise.
Insights into déjà vu: Associations between the frequency of experience and amplitudes of low-frequency oscillations in resting-state functional magnetic resonance imaging
The phenomenon of déjà vu (DV) has intrigued scientists for decades, yet its neurophysiological underpinnings remain elusive. Brain regions have been identified in which morphometry differs between healthy individuals according to the frequency of their DV experiences. This study built upon these findings by assessing if and how neural activity in these and other brain regions also differ with respect to DV experience. Resting-state fMRI was performed on 68 healthy volunteers, 44 of whom reported DV experiences (DV group) and 24 who did not (NDV group). Using multivariate analyses, we then assessed the (fractional) amplitude of low-frequency fluctuations (fALFF/ALFF), a metric that is believed to index brain tissue excitability, for five discrete frequency bands within sets of brain regions implicated in DV and those comprising the default mode network (DMN).