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
The reliability of a deep learning model in clinical out-of-distribution MRI data: A multicohort study
Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in medical imaging are often trained on public research cohorts with images acquired with a single scanner or with strict protocol harmonization, which is not representative of a clinical setting. The aim of this study was to investigate how well a DL model performs in unseen clinical datasets-collected with different scanners, protocols and disease populations-and whether more heterogeneous training data improves generalization. In total, 3117 MRI scans of brains from multiple dementia research cohorts and memory clinics, that had been visually rated by a neuroradiologist according to Scheltens' scale of medial temporal atrophy (MTA), were included in this study. By training multiple versions of a convolutional neural network on different subsets of this data to predict MTA ratings, we assessed the impact of including images from a wider distribution during training had on performance in external memory clinic data.
MR Diffusion Properties of Cervical Spinal Cord as a Predictor of Progression to Multiple Sclerosis in Patients with Clinically Isolated Syndrome
Background and purpose: This study's aim was to investigate diffusion properties of the cervical spinal cord in patients with clinically isolated syndrome (CIS) through analysis of diffusion tensor imaging (DTI) data and thereby to assess the capacity of this technique for predicting the progression of CIS to clinically definite multiple sclerosis (CDMS).
Methods: The study groups were comprised of 47 patients with CIS (15 of them with progression to CDMS within 2 years of follow-up) and 57 asymptomatic controls. All patients and controls had undergone magnetic resonance imaging (MRI) of the cervical spine including DTI and brain MRI. Methodological approaches included histogram analysis of the cervical cord's diffusion parameters and evaluation of T2 hyperintense lesions of the spinal cord and brain.
Imagery-induced negative affect, social touch and frontal EEG power band activity
Social touch seems to modulate emotions, but its brain correlates are poorly understood. Here, we investigated if frontal power band activity in the electroencephalogram (EEG) during aversive mental imagery is modulated by social touch from one's romantic partner and a stranger. We observed the highest theta and beta power when imaging alone, next so when being touched by a stranger, with lowest theta and beta activity during holding hands with the loved one. Delta power was higher when being alone than with a stranger or a partner, with no difference between the two. Gamma power was highest during the stranger condition and lower both when being alone and with the partner, while alpha power did not change as a function of social touch. Theta power displayed a positive correlation with electrodermal activity supporting its relation to emotional arousal. Attachment style modulated the effect of touch on the EEG as only secure but not insecure partner bonding was associated with theta power reductions.
Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations
Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice.
Novel polygenic risk score as a translational tool linking depression-related changes in the corticolimbic transcriptome with neural face processing and anhedonic symptoms.
Convergent data from imaging and postmortem brain transcriptome studies implicate corticolimbic circuit (CLC) dysregulation in the pathophysiology of depression. To more directly bridge these lines of work, we generated a novel transcriptome-based polygenic risk score (T-PRS), capturing subtle shifts toward depression-like gene expression patterns in key CLC regions, and mapped this T-PRS onto brain function and related depressive symptoms in a nonclinical sample of 478 young adults (225 men; age 19.79 +/- 1.24) from the Duke Neurogenetics Study. First, T-PRS was generated based on common functional SNPs shifting CLC gene expression toward a depression-like state. Next, we used multivariate partial least squares regression to map T-PRS onto whole-brain activity patterns during perceptual processing of social stimuli (i.e., human faces).
Cognitive Processing Impacts High Frequency Intracranial EEG Activity of Human Hippocampus in Patients With Pharmacoresistant Focal Epilepsy
The electrophysiological EEG features such as high frequency oscillations, spikes and functional connectivity are often used for delineation of epileptogenic tissue and study of the normal function of the brain. The epileptogenic activity is also known to be suppressed by cognitive processing. However, differences between epileptic and healthy brain behavior during rest and task were not studied in detail. In this study we investigate the impact of cognitive processing on epileptogenic and non-epileptogenic hippocampus and the intracranial EEG features representing the underlying electrophysiological processes. We investigated intracranial EEG in 24 epileptic and 24 non-epileptic hippocampi in patients with intractable focal epilepsy during a resting state period and during performance of various cognitive tasks.
The impact of lymphocytosis and CD4/CD8 ratio on the anti-JCV antibody index and clinical data in patients treated with natalizumab
Background: Natalizumab is an effective therapy in the treatment of relapsing-remitting multiple sclerosis; it induces lymphocytosis (NIL, natalizumab-induced lymphocytosis) and changes the peripheral lymphocyte pattern.
Methods: This study aims to evaluate NIL, peripheral blood lymphocyte subsets, CD4/CD8 ratio, and their impacts on JCV index and clinical data-No Evidence of Disease Activity (NEDA-3) and annualized relapse rate (ARR) in patients treated with natalizumab.
Mindfulness-Based Programs for Patients With Cancer via eHealth and Mobile Health: Systematic Review and Synthesis of Quantitative Research
Background: eHealth mindfulness-based programs (eMBPs) are on the rise in complex oncology and palliative care. However, we are still at the beginning of answering the questions of how effective eMBPs are and for whom, and what kinds of delivery modes are the most efficient.
Objective: This systematic review aims to examine the feasibility and efficacy of eMBPs in improving the mental health and well-being of patients with cancer, to describe intervention characteristics and delivery modes of these programs, and to summarize the results of the included studies in terms of moderators, mediators, and predictors of efficacy, adherence, and attrition.