Publications by authors named "Clemens Brunner"

44 Publications

Fact retrieval or compacted counting in arithmetic-A neurophysiological investigation of two hypotheses.

J Exp Psychol Learn Mem Cogn 2021 Feb 4. Epub 2021 Feb 4.

Parenting and Special Education Research Unit.

There is broad consensus on the assumption that adults solve single-digit multiplication problems almost exclusively by fact retrieval from memory. In contrast, there has been a long-standing debate on the cognitive processes involved in solving single-digit addition problems. This debate has evolved around two theoretical accounts. Proponents of a fact-retrieval account postulate that these are also solved through fact retrieval, whereas proponents of a compacted-counting account propose that solving very small additions (with operands between 1 and 4) involves highly automatized and unconscious compacted counting. In the present electroencephalography (EEG) study, we put these two accounts to the test by comparing neurophysiological correlates of solving very small additions and multiplications. Forty adults worked on an arithmetic production task involving all (nontie) single-digit additions and multiplications. Afterward, participants completed trial-by-trial strategy self-reports. In our EEG analyses, we focused on induced activity (event-related synchronization/desynchronization, ERS/ERD) in three frequency bands (theta, lower alpha, upper alpha). Across all frequency bands, we found higher evidential strength for similar rather than different neurophysiological processes accompanying the solution of very small addition and multiplication problems. In the alpha bands, evidence for similarity was even stronger when operand-1-problems were excluded. In two additional analyses, we showed that ERS/ERD can differentiate between self-reported problem-solving strategies (retrieval vs. procedure) and between very small × 1 and + 1 problems, demonstrating its high sensitivity to cognitive processes in arithmetic. The present findings support a fact-retrieval account, suggesting that both very small additions and multiplications are solved through fact retrieval. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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http://dx.doi.org/10.1037/xlm0000982DOI Listing
February 2021

Inter- and Intra-individual Variability in Brain Oscillations During Sports Motor Imagery.

Front Hum Neurosci 2020 30;14:576241. Epub 2020 Oct 30.

Institute of Neural Engineering, Graz University of Technology, Graz, Austria.

The aim of this work was to re-evaluate electrophysiological data from a previous study on motor imagery (MI) with a special focus on observed inter- and intra-individual differences. More concretely, we investigated event-related desynchronization/synchronization patterns during sports MI (playing tennis) compared with simple MI (squeezing a ball) and discovered high variability across participants. Thirty healthy volunteers were divided in two groups; the experimental group (EG) performed a physical exercise between two imagery sessions, and the control group (CG) watched a landscape movie without physical activity. We computed inter-individual differences by assessing the dissimilarities among subjects for each group, condition, time period, and frequency band. In the alpha band, we observe some clustering in the ranking of the subjects, therefore showing smaller distances than others. Moreover, in our statistical evaluation, we observed a consistency in ranking across time periods both for the EG and for the CG. For the latter, we also observed similar rankings across conditions. On the contrary, in the beta band, the ranking of the subjects was more similar for the EG across conditions and time periods than for the subjects of the CG. With this study, we would like to draw attention to variability measures instead of primarily focusing on the identification of common patterns across participants, which often do not reflect the whole neurophysiological reality.
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http://dx.doi.org/10.3389/fnhum.2020.576241DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662155PMC
October 2020

Effects of Anodal tDCS on Arithmetic Performance and Electrophysiological Activity.

Front Hum Neurosci 2020 11;14:17. Epub 2020 Feb 11.

Educational Neuroscience, Institute of Psychology, University of Graz, Graz, Austria.

Arithmetic abilities are among the most important school-taught skills and form the basis for higher mathematical competencies. At the same time, their acquisition and application can be challenging. Hence, there is broad interest in methods to improve arithmetic abilities. One promising method is transcranial direct current stimulation (tDCS). In the present study, we compared two anodal tDCS protocols in their efficacy to improve arithmetic performance and working memory. In addition, we investigated stimulation-related electrophysiological changes. Three groups of participants solved arithmetic problems (additions and subtractions) and an n-back task before, during, and after receiving either frontal or parietal anodal tDCS (25 min; 1 mA) or sham stimulation. EEG was simultaneously recorded to assess stimulation effects on event-related (de-) synchronisation (ERS/ERD) in theta and alpha bands. Persons receiving frontal stimulation showed an acceleration of calculation speed in large subtractions from before to during and after stimulation. However, a comparable, but delayed (apparent only after stimulation) increase was also found in the sham stimulation group, while it was absent in the group receiving parietal stimulation. In additions and small subtractions as well as the working memory task, analyses showed no effects of stimulation. Results of ERS/ERD during large subtractions indicate changes in ERS/ERD patterns over time. In the left hemisphere there was a change from theta band ERD to ERS in all three groups, whereas a similar change in the right hemisphere was restricted to the sham group. Taken together, tDCS did not lead to a general improvement of arithmetic performance. However, results indicate that frontal stimulation accelerated training gains, while parietal stimulation halted them. The absence of general performance improvements, but acceleration of training effects might be a further indicator of the advantages of using tDCS as training or learning support over tDCS as a sole performance enhancer.
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http://dx.doi.org/10.3389/fnhum.2020.00017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026470PMC
February 2020

MRI-related anxiety in healthy individuals, intrinsic BOLD oscillations at 0.1 Hz in precentral gyrus and insula, and heart rate variability in low frequency bands.

PLoS One 2018 26;13(11):e0206675. Epub 2018 Nov 26.

Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal.

Participation in magnetic resonance imaging (MRI) scanning is associated with increased anxiety, thus possibly impacting baseline recording for functional MRI studies. The goal of the paper is to elucidate the significant hemispheric asymmetry between blood-oxygenation-level-dependent (BOLD) signals from precentral gyrus (PCG) and insula in 23 healthy individuals without any former MRI experience recently published in a PLOSONE paper. In addition to BOLD signals state anxiety and heart rate variability (HRV) were analyzed in two resting state sessions (R1, R2). Phase-locking and time delays from BOLD signals were computed in the frequency band 0.07-0.13 Hz. Positive (pTD) and negative time delays (nTD) were found. The pTD characterize descending neural BOLD oscillations spreading from PCG to insula and nTD characterize ascending vascular BOLD oscillations related to blood flow in the middle cerebral artery. HRV power in two low frequency bands 0.06-0.1 Hz and 0.1-0.14 Hz was computed. Based on the anxiety change from R1 to R2, two groups were separated: one with a strong anxiety decline (large change group) and one with a moderate decline or even anxiety increase (small change group). A significant correlation was found only between the left-hemispheric time delay (pTD, nTD) and anxiety change, with a dominance of nTD in the large change group. The analysis of within-scanner HRV revealed a pronounced increase of low frequency power between both resting states, dominant in the band 0.06-0.1 Hz in the large change group and in the band 0.1-0.14 Hz in the small change group. These results suggest different mechanisms related to anxiety processing in healthy individuals. One mechanism (large anxiety change) could embrace an increase of blood circulation in the territory of the left middle cerebral artery (vascular BOLD) and another (small anxiety change) translates to rhythmic central commands (neural BOLD) in the frequency band 0.1-0.14 Hz.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0206675PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6261029PMC
April 2019

Frequency Specific Cortical Dynamics During Motor Imagery Are Influenced by Prior Physical Activity.

Front Psychol 2018 25;9:1976. Epub 2018 Oct 25.

Institute of Neural Engineering, Graz University of Technology, Graz, Austria.

Motor imagery is often used inducing changes in electroencephalographic (EEG) signals for imagery-based brain-computer interfacing (BCI). A BCI is a device translating brain signals into control signals providing severely motor-impaired persons with an additional, non-muscular channel for communication and control. In the last years, there is increasing interest using BCIs also for healthy people in terms of enhancement or gaming. Most studies focusing on improving signal processing feature extraction and classification methods, but the performance of a BCI can also be improved by optimizing the user's control strategies, e.g., using more vivid and engaging mental tasks for control. We used multichannel EEG to investigate neural correlates of a sports imagery task (playing tennis) compared to a simple motor imagery task (squeezing a ball). To enhance the vividness of both tasks participants performed a short physical exercise between two imagery sessions. EEG was recorded from 60 closely spaced electrodes placed over frontal, central, and parietal areas of 30 healthy volunteers divided in two groups. Whereas Group 1 (EG) performed a physical exercise between the two imagery sessions, Group 2 (CG) watched a landscape movie without physical activity. Spatiotemporal event-related desynchronization (ERD) and event-related synchronization (ERS) patterns during motor imagery (MI) tasks were evaluated. The results of the EG showed significant stronger ERD patterns in the alpha frequency band (8-13 Hz) during MI of tennis after training. Our results are in evidence with previous findings that MI in combination with motor execution has beneficial effects. We conclude that sports MI combined with an interactive game environment could be a future promising task in motor learning and rehabilitation improving motor functions in late therapy processes or support neuroplasticity.
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http://dx.doi.org/10.3389/fpsyg.2018.01976DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6209646PMC
October 2018

Target probability modulates fixation-related potentials in visual search.

Biol Psychol 2018 10 22;138:199-210. Epub 2018 Sep 22.

Institute of Psychology, University of Graz, Graz, Austria; BioTechMed Graz, Graz, Austria.

This study investigated the influence of target probability on the neural response to target detection in free viewing visual search. Participants were asked to indicate the number of targets (one or two) among distractors in a visual search task while EEG and eye movements were co-registered. Target probability was manipulated by varying the set size of the displays between 10, 22, and 30 items. Fixation-related potentials time-locked to first target fixations revealed a pronounced P300 at the centro-parietal cortex with larger amplitudes for set sizes 22 and 30 than for set size 10. With increasing set size, more distractor fixations preceded the detection of the target, resulting in a decreased target probability and, consequently, a larger P300. For distractors, no increase of P300 amplitude with set size was observed. The findings suggest that set size specifically affects target but not distractor processing in overt serial visual search.
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http://dx.doi.org/10.1016/j.biopsycho.2018.09.007DOI Listing
October 2018

Synchronization of intrinsic 0.1-Hz blood-oxygen-level-dependent oscillations in amygdala and prefrontal cortex in subjects with increased state anxiety.

Eur J Neurosci 2018 03 8;47(5):417-426. Epub 2018 Feb 8.

Institute of Biophysics and Biomedical Engineering, Faculty of Sciences, University of Lisbon, Lisbon, Portugal.

Low-frequency oscillations with a dominant frequency at 0.1 Hz are one of the most influential intrinsic blood-oxygen-level-dependent (BOLD) signals. This raises the question if vascular BOLD oscillations (originating from blood flow in the brain) and intrinsic slow neural activity fluctuations (neural BOLD oscillations) can be differentiated. In this study, we report on two different approaches: first, on computing the phase-locking value in the frequency band 0.07-0.13 Hz between heart beat-to-beat interval (RRI) and BOLD oscillations and second, between multiple BOLD oscillations (functional connectivity) in four resting states in 23 scanner-naïve, anxious healthy subjects. The first method revealed that vascular 0.1-Hz BOLD oscillations preceded those in RRI signals by 1.7 ± 0.6 s and neural BOLD oscillations lagged RRI oscillations by 0.8 ± 0.5 s. Together, vascular BOLD oscillations preceded neural BOLD oscillations by ~90° or ~2.5 s. To verify this discrimination, connectivity patterns of neural and vascular 0.1-Hz BOLD oscillations were compared in 26 regions involved in processing of emotions. Neural BOLD oscillations revealed significant phase-coupling between amygdala and medial frontal cortex, while vascular BOLD oscillations showed highly significant phase-coupling between amygdala and multiple regions in the supply areas of the anterior and medial cerebral arteries. This suggests that not only slow neural and vascular BOLD oscillations can be dissociated but also that two strategies may exist to optimize regulation of anxiety, that is increased functional connectivity between amygdala and medial frontal cortex, and increased cerebral blood flow in amygdala and related structures.
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http://dx.doi.org/10.1111/ejn.13845DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5887876PMC
March 2018

Impact of Disseminated Neuroblastoma Cells on the Identification of the Relapse-Seeding Clone.

Clin Cancer Res 2017 Aug 22;23(15):4224-4232. Epub 2017 Feb 22.

CCRI, Children's Cancer Research Institute, Vienna, Austria.

Tumor relapse is the most frequent cause of death in stage 4 neuroblastomas. Since genomic information on the relapse precursor cells could guide targeted therapy, our aim was to find the most appropriate tissue for identifying relapse-seeding clones. We analyzed 10 geographically and temporally separated samples of a single patient by SNP array and validated the data in 154 stage 4 patients. In the case study, aberrations unique to certain tissues and time points were evident besides concordant aberrations shared by all samples. Diagnostic bone marrow-derived disseminated tumor cells (DTCs) as well as the metastatic tumor and DTCs at relapse displayed a 1q deletion, not detected in any of the seven primary tumor samples. In the validation cohort, the frequency of 1q deletion was 17.8%, 10%, and 27.5% in the diagnostic DTCs, diagnostic tumors, and DTCs at relapse, respectively. This aberration was significantly associated with 19q and deletions. We observed a significant increased likelihood of an adverse event in the presence of 19q deletion in the diagnostic DTCs. Different frequencies of 1q and 19q deletions in the primary tumors as compared with DTCs, their relatively high frequency at relapse, and their effect on event-free survival (19q deletion) indicate the relevance of analyzing diagnostic DTCs. Our data support the hypothesis of a branched clonal evolution and a parallel progression of primary and metastatic tumor cells. Therefore, searching for biomarkers to identify the relapse-seeding clone should involve diagnostic DTCs alongside the tumor tissue. .
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http://dx.doi.org/10.1158/1078-0432.CCR-16-2082DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5528137PMC
August 2017

Distinction between Neural and Vascular BOLD Oscillations and Intertwined Heart Rate Oscillations at 0.1 Hz in the Resting State and during Movement.

PLoS One 2017 4;12(1):e0168097. Epub 2017 Jan 4.

Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal.

In the resting state, blood oxygen level-dependent (BOLD) oscillations with a frequency of about 0.1 Hz are conspicuous. Whether their origin is neural or vascular is not yet fully understood. Furthermore, it is not clear whether these BOLD oscillations interact with slow oscillations in heart rate (HR). To address these two questions, we estimated phase-locking (PL) values between precentral gyrus (PCG) and insula in 25 scanner-naïve individuals during rest and stimulus-paced finger movements in both hemispheres. PL was quantified in terms of time delay and duration in the frequency band 0.07 to 0.13 Hz. Results revealed both positive and negative time delays. Positive time delays characterize neural BOLD oscillations leading in the PCG, whereas negative time delays represent vascular BOLD oscillations leading in the insula. About 50% of the participants revealed positive time delays distinctive for neural BOLD oscillations, either with short or long unilateral or bilateral phase-locking episodes. An expected preponderance of neural BOLD oscillations was found in the left hemisphere during right-handed movement and unexpectedly in the right hemisphere during rest. Only neural BOLD oscillations were significantly associated with heart rate variability (HRV) in the 0.1-Hz range in the first resting state. It is well known that participating in magnetic resonance imaging (MRI) studies may be frightening and cause anxiety. In this respect it is important to note that the most significant hemispheric asymmetry (p<0.002) with a right-sided dominance of neural BOLD and a left-sided dominance of vascular BOLD oscillations was found in the first resting session in the scanner-naïve individuals. Whether the enhanced left-sided perfusion (dominance of vascular BOLD) or the right-sided dominance of neural BOLD is related to the increased level of anxiety, attention or stress needs further research.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0168097PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5215612PMC
August 2017

Variability of ICA decomposition may impact EEG signals when used to remove eyeblink artifacts.

Psychophysiology 2017 03 27;54(3):386-398. Epub 2016 Dec 27.

Institute of Psychology, University of Graz, Graz, Austria.

Despite the growing use of independent component analysis (ICA) algorithms for isolating and removing eyeblink-related activity from EEG data, we have limited understanding of how variability associated with ICA uncertainty may be influencing the reconstructed EEG signal after removing the eyeblink artifact components. To characterize the magnitude of this ICA uncertainty and to understand the extent to which it may influence findings within ERP and EEG investigations, ICA decompositions of EEG data from 32 college-aged young adults were repeated 30 times for three popular ICA algorithms. Following each decomposition, eyeblink components were identified and removed. The remaining components were back-projected, and the resulting clean EEG data were further used to analyze ERPs. Findings revealed that ICA uncertainty results in variation in P3 amplitude as well as variation across all EEG sampling points, but differs across ICA algorithms as a function of the spatial location of the EEG channel. This investigation highlights the potential of ICA uncertainty to introduce additional sources of variance when the data are back-projected without artifact components. Careful selection of ICA algorithms and parameters can reduce the extent to which ICA uncertainty may introduce an additional source of variance within ERP/EEG studies.
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http://dx.doi.org/10.1111/psyp.12804DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5584537PMC
March 2017

Volume Conduction Influences Scalp-Based Connectivity Estimates.

Front Comput Neurosci 2016 22;10:121. Epub 2016 Nov 22.

Swartz Center for Computational Neuroscience, University of California, San Diego San Diego, CA, USA.

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http://dx.doi.org/10.3389/fncom.2016.00121DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5119053PMC
November 2016

Brain-heart communication: Evidence for "central pacemaker" oscillations with a dominant frequency at 0.1Hz in the cingulum.

Clin Neurophysiol 2017 Jan 10;128(1):183-193. Epub 2016 Nov 10.

Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Portugal.

Objectives: In the brain and heart, oscillations at about 0.1Hz are conspicuous. It is therefore worthwhile to study the interaction between intrinsic BOLD oscillations (0.1Hz) and slow oscillations in heart rate interval (RRI) signals and differentiate between their neural and vascular origin.

Methods: We studied the phase-coupling with a 3T scanner with high scanning rate between BOLD signals in 22 regions and simultaneously recorded RRI oscillations in 23 individuals in two resting states.

Results: By applying a hierarchical cluster analysis, it was possible to separate two clusters of phase-coupling between slow BOLD and RRI oscillations in the midcingulum, one representative for neural and the other for vascular BOLD oscillations. About half of the participants revealed positive time delays characteristic for neural BOLD oscillations and neurally-driven RRI oscillations.

Conclusions: The results suggest that slow vascular and neural BOLD oscillations can be differentiated and that intrinsic oscillations (0.1Hz) originate in the cingulum or its close vicinity and contribute to heart rate variability (HRV).

Significance: The study provides new insights into the dynamics of resting state activities, helps to explain HRV, and offers the possibility to investigate slow rhythmic neural activity changes in different brain regions without EEG recording.
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http://dx.doi.org/10.1016/j.clinph.2016.10.097DOI Listing
January 2017

Tumor Touch Imprints as Source for Whole Genome Analysis of Neuroblastoma Tumors.

PLoS One 2016 25;11(8):e0161369. Epub 2016 Aug 25.

Department of Tumor Biology, CCRI, Children's Cancer Research Institute, St. Anna Kinderkrebsforschung, Vienna, Austria.

Introduction: Tumor touch imprints (TTIs) are routinely used for the molecular diagnosis of neuroblastomas by interphase fluorescence in-situ hybridization (I-FISH). However, in order to facilitate a comprehensive, up-to-date molecular diagnosis of neuroblastomas and to identify new markers to refine risk and therapy stratification methods, whole genome approaches are needed. We examined the applicability of an ultra-high density SNP array platform that identifies copy number changes of varying sizes down to a few exons for the detection of genomic changes in tumor DNA extracted from TTIs.

Material And Methods: DNAs were extracted from TTIs of 46 neuroblastoma and 4 other pediatric tumors. The DNAs were analyzed on the Cytoscan HD SNP array platform to evaluate numerical and structural genomic aberrations. The quality of the data obtained from TTIs was compared to that from randomly chosen fresh or fresh frozen solid tumors (n = 212) and I-FISH validation was performed.

Results: SNP array profiles were obtained from 48 (out of 50) TTI DNAs of which 47 showed genomic aberrations. The high marker density allowed for single gene analysis, e.g. loss of nine exons in the ATRX gene and the visualization of chromothripsis. Data quality was comparable to fresh or fresh frozen tumor SNP profiles. SNP array results were confirmed by I-FISH.

Conclusion: TTIs are an excellent source for SNP array processing with the advantage of simple handling, distribution and storage of tumor tissue on glass slides. The minimal amount of tumor tissue needed to analyze whole genomes makes TTIs an economic surrogate source in the molecular diagnostic work up of tumor samples.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0161369PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4999140PMC
July 2017

The genetic tumor background is an important determinant for heterogeneous MYCN-amplified neuroblastoma.

Int J Cancer 2016 Jul 22;139(1):153-63. Epub 2016 Mar 22.

Department of Tumor Biology, CCRI, Children's Cancer Research Institute, St. Anna Kinderkrebsforschung, Vienna, Austria.

Amplification of MYCN is the signature genetic aberration of 20-25% of neuroblastoma and a stratifying marker associated with aggressive tumor behavior. The detection of heterogeneous MYCN amplification (hetMNA) poses a diagnostic dilemma due to the uncertainty of its relevance to tumor behavior. Here, we aimed to shed light on the genomic background which permits hetMNA in neuroblastoma and tied the occurrence to other stratifying markers and disease outcome. We performed SNP analysis using Affymetrix Cytoscan HD arrays on 63 samples including constitutional DNA, tumor, bone marrow and relapse samples of 26 patients with confirmed hetMNA by MYCN-FISH. Tumors of patients ≤18m were mostly aneuploid with numeric chromosomal aberrations (NCAs), presented a prominent MNA subclone and carried none or a few segmental chromosomal aberrations (SCAs). In older patients, tumors were mostly di- or tetraploid, contained a lower number of MNA cells and displayed a multitude of SCAs including concomitant 11q deletions. These patients often suffered disease progression, tumor dissemination and relapse. Restricted to aneuploid tumors, we detected chromosomes with uniparental di- or trisomy (UPD/UPT) in almost every sample. UPD11 was exclusive to tumors of younger patients whereas older patients featured UPD14. In this study, the MNA subclone appears to be constraint by the tumor environment and thus less relevant for tumor behavior in aggressive tumors with a high genomic instability and many segmental aberrations. A more benign tumor background and lower tumor stage may favor an outgrowth of the MNA clone but tumors generally responded better to treatment.
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http://dx.doi.org/10.1002/ijc.30050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4949549PMC
July 2016

Online visualization of brain connectivity.

J Neurosci Methods 2015 Dec 6;256:106-16. Epub 2015 Sep 6.

Institute for Knowledge Discovery, Graz University of Technology, Inffeldgasse 13/IV, 8010 Graz, Austria.

Background: While visualization of brain activity has well established practical applications such as real-time functional mapping or neurofeedback, visual representation of brain connectivity is not widely used. In addition, technically challenging single-trial connectivity estimation may have hindered practical usage of connectivity in online applications.

New Method: In this work, we developed algorithms that are capable of estimating and visualizing (effective) connectivity between independent cortical sources during online EEG recordings.

Results: The core routines of our procedure, such as CSPVARICA source extraction and regularized connectivity estimation, are available in our open source Python-based toolbox SCoT. We demonstrate for the first time that online connectivity visualization is feasible. We show this in a feasibility study with twelve participants performing two different tasks, namely motor execution and resting with eyes open or closed. Connectivity patterns were significantly different between two motor tasks in four participants, whereas significant differences between resting task patterns were found in seven participants.

Comparison With Existing Methods: Existing connectivity studies have focused on offline methods. In contrast, there are only a small number of examples in the literature that explored online connectivity estimation. For example, a system based on wearable EEG has been demonstrated to work for one subject, and the Glass Brain project has received considerable attention in popular sciences last year. However, none of these attempts validate their methods on multiple subjects.

Conclusions: Our results show that causal connectivity patterns can be observed online during EEG measurements, which is a first step towards real-time connectivity analysis.
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http://dx.doi.org/10.1016/j.jneumeth.2015.08.031DOI Listing
December 2015

Single trial classification of fNIRS-based brain-computer interface mental arithmetic data: a comparison between different classifiers.

Annu Int Conf IEEE Eng Med Biol Soc 2014 ;2014:2004-7

Functional near infrared spectroscopy (fNIRS) is an emerging technique for the in-vivo assessment of functional activity of the cerebral cortex as well as in the field of brain-computer-interface (BCI) research. A common challenge for the utilization of fNIRS for BCIs is a stable and reliable single trial classification of the recorded spatio-temporal hemodynamic patterns. Many different classification methods are available, but up to now, not more than two different classifiers were evaluated and compared on one data set. In this work, we overcome this issue by comparing five different classification methods on mental arithmetic fNIRS data: linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), support vector machines (SVM), analytic shrinkage regularized LDA (sLDA), and analytic shrinkage regularized QDA (sQDA). Depending on the used method and feature type (oxy-Hb or deoxy-Hb), achieved classification results vary between 56.1 % (deoxy-Hb/QDA) and 86.6% (oxy-Hb/SVM). We demonstrated that regularized classifiers perform significantly better than non-regularized ones. Considering simplicity and computational effort, we recommend the use of sLDA for fNIRS-based BCIs.
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http://dx.doi.org/10.1109/EMBC.2014.6944008DOI Listing
July 2016

Initiation of voluntary movements at free will and ongoing 0.1-Hz BOLD oscillations in the insula-a pilot study.

Front Integr Neurosci 2014 8;8:93. Epub 2014 Dec 8.

Center for NeuroScience, Swammerdam Institute for Life Sciences, University of Amsterdam Amsterdam, Netherlands.

Recently we hypothesized that the intention to initiate a voluntary movement at free will may be related to the dynamics of hemodynamic variables, which may be supported by the intertwining of networks for the timing of voluntary movements and the control of cardiovascular variables in the insula. In the present study voluntary movements of 3 healthy subjects were analyzed using fMRI scans at 1.83-s intervals along with the time course of slow hemodynamic changes in sensorimotor networks. For the analyses of BOLD time courses the Wavelet transform coherence (WTC) and calculation of phase-locking values were used. Analyzed was the frequency band between 0.07 and 0.13 Hz in the supplementary motor area (SMA) and insula, two widely separated regions co-active in motor behavior. BOLD signals displayed slow fluctuations, concentrated around 0.1 Hz whereby the intrinsic oscillations in the insula preceded those in the SMA by 0.5-1 s. These preliminary results suggest that slow hemodynamic changes in SMA and insula may condition the initiation of a voluntary movement at free will.
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http://dx.doi.org/10.3389/fnint.2014.00093DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4259110PMC
December 2014

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.

Brain Comput Interfaces (Abingdon) 2014 Jan;1(1):27-49

Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States, 2800 Plymouth Road, Bdlg 26 Rm G06W-B; Ann Arbor, MI 48109; 734-763-7104.

The Fifth International Brain-Computer Interface (BCI) Meeting met June 3-7, 2013 at the Asilomar Conference Grounds, Pacific Grove, California. The conference included 19 workshops covering topics in brain-computer interface and brain-machine interface research. Topics included translation of BCIs into clinical use, standardization and certification, types of brain activity to use for BCI, recording methods, the effects of plasticity, special interest topics in BCIs applications, and future BCI directions. BCI research is well established and transitioning to practical use to benefit people with physical impairments. At the same time, new applications are being explored, both for people with physical impairments and beyond. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and high-lighting important issues for future research and development.
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http://dx.doi.org/10.1080/2326263X.2013.876724DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4255956PMC
January 2014

Bone marrows from neuroblastoma patients: an excellent source for tumor genome analyses.

Mol Oncol 2015 Mar 28;9(3):545-54. Epub 2014 Oct 28.

Tumor Biology, Children's Cancer Research Institute, St. Anna Kinderkrebsforschung, Vienna, Austria; Department of Pediatrics, Medical University of Vienna, Vienna, Austria. Electronic address:

Neuroblastoma is the most common extra-cranial solid tumor in childhood. Presence of disseminated tumor cells (DTCs) in the bone marrow (BM) at diagnosis and at relapse is a common event in stage M neuroblastomas. Although the clinical heterogeneity of disseminated neuroblastomas is frequently associated with genomic diversity, so far, only little information exists about the genomic status of DTCs. This lack of knowledge is mainly due to the varying amount of BM infiltrating tumor cells, which is usually below 30% even at diagnosis thereby hampering systematic analyses. Thus, a valuable chance to analyze metastatic and relapse clones is, so far, completely unexploited. In this study, we show that the enrichment of tumor cells in fresh or DMSO frozen BM samples with a minimum of 0.05% or 0.1% infiltration rate, respectively, by applying magnetic bead-based technique increased the DTC content to a sufficient level to allow SNP array analyses in 49 out of 69 samples. In addition, we successfully used non-enriched BM samples with ≥30% DTCs including non-stained and immunostained cytospin and BM smear slides for SNP array analyses in 44 cases. We analyzed the genomic profile of DTCs by an ultra-high density SNP array technique with highest performance detecting all segmental chromosomal aberrations, amplified regions, acquired loss of heterozygosity events and minor aberrations affecting single genes or parts thereof.
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http://dx.doi.org/10.1016/j.molonc.2014.10.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5528711PMC
March 2015

Ultra-High Density SNParray in Neuroblastoma Molecular Diagnostics.

Front Oncol 2014 12;4:202. Epub 2014 Aug 12.

Children's Cancer Research Institute, St. Anna Kinderkrebsforschung , Vienna , Austria ; Department of Pediatrics, Medical University of Vienna , Vienna , Austria.

Neuroblastoma serves as a paradigm for applying tumor genomic data for determining patient prognosis and thus for treatment allocation. MYCN status, i.e., amplified vs. non-amplified, was one of the very first biomarkers in oncology to discriminate aggressive from less aggressive or even favorable clinical courses of neuroblastoma. However, MYCN amplification is by far not the only genetic change associated with unfavorable clinical courses. So called "segmental chromosomal aberrations," (SCAs) i.e., gains or losses of chromosomal fragments, can also indicate tumor aggressiveness. The clinical use of these genomic aberrations has, however, been hampered for many years by methodical and interpretational problems. Only after reaching worldwide consensus on markers, methodology, and data interpretation, information on SCAs has recently been implemented in clinical studies. Now, a number of collaborative studies within COG, GPOH, and SIOPEN use genomic information to stratify therapy for patients with localized and metastatic disease. Recently, new types of DNA based aberrations influencing the clinical behavior of neuroblastomas have been described. Deletions or mutations of genes like ATRX and a phenomenon referred to as "chromothripsis" are all assumed to correlate with an unfavorable clinical behavior. However, these genomic aberrations need to be scrutinized in larger studies applying the most appropriate techniques. Single nucleotide polymorphism arrays have proven successful in deciphering genomic aberrations of cancer cells; these techniques, however, are usually not applied in the daily routine. Here, we present an ultra-high density (UHD) SNParray technique which is, because of its high specificity and sensitivity and the combined copy number and allele information, highly appropriate for the genomic diagnosis of neuroblastoma and other malignancies.
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http://dx.doi.org/10.3389/fonc.2014.00202DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4129917PMC
August 2014

SCoT: a Python toolbox for EEG source connectivity.

Front Neuroinform 2014 11;8:22. Epub 2014 Mar 11.

Institute for Knowledge Discovery, Graz University of Technology Graz, Austria.

Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT-a source connectivity toolbox for Python. This toolbox implements routines for blind source decomposition and connectivity estimation with the MVARICA approach. Additionally, a novel extension called CSPVARICA is available for labeled data. SCoT estimates connectivity from various spectral measures relying on vector autoregressive (VAR) models. Optionally, these VAR models can be regularized to facilitate ill posed applications such as single-trial fitting. We demonstrate basic usage of SCoT on motor imagery (MI) data. Furthermore, we show simulation results of utilizing SCoT for feature extraction in a BCI application. These results indicate that CSPVARICA and correct regularization can significantly improve MI classification. While SCoT was mainly designed for application in BCIs, it contains useful tools for other areas of neuroscience. SCoT is a software package that (1) brings combined source decomposition and connectivtiy estimation to the open Python platform, and (2) offers tools for single-trial connectivity estimation. The source code is released under the MIT license and is available online at github.com/SCoT-dev/SCoT.
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http://dx.doi.org/10.3389/fninf.2014.00022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3949292PMC
March 2014

Eeglab - an Open Source Matlab Toolbox for Electrophysiological Research.

Biomed Tech (Berl) 2013 08 7;58 Suppl 1. Epub 2013 Sep 7.

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http://dx.doi.org/10.1515/bmt-2013-4182DOI Listing
August 2013

Single-trial connectivity estimation for classification of motor imagery data.

J Neural Eng 2013 Aug 11;10(4):046006. Epub 2013 Jun 11.

Institute for Knowledge Discovery, Graz University of Technology, Graz, Austria.

Objective: Many brain-computer interfaces (BCIs) use band power (BP) changes in the electroencephalogram to distinguish between different motor imagery (MI) patterns. Most current approaches do not take connectivity of separated brain areas into account. Our objective is to introduce single-trial connectivity features and apply these features to BCI data.

Approach: We introduce a procedure for extracting single-trial connectivity estimates from vector autoregressive (VAR) models of independent components in a BCI setting.

Main Results: In a simulated BCI, we demonstrate that the directed transfer function (DTF) with full-frequency normalization and the direct DTF give classification results similar to BP, while other measures such as the partial directed coherence perform significantly worse.

Significance: We show that single-trial MI classification is possible with connectivity measures extracted from VAR models, and that a BCI could potentially utilize such measures.
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http://dx.doi.org/10.1088/1741-2560/10/4/046006DOI Listing
August 2013

Investigating the influence of proficiency on semantic processing in bilinguals: an ERP and ERD/S analysis.

Acta Neurobiol Exp (Wars) 2012 ;72(4):421-38

Department of Psychology, University of Graz, Austria.

In this study, we presented sentences either ending with high or low probability cloze words or semantically incongruent words to investigate the influence of L2 proficiency on electrophysiological correlates of semantic processing in bilinguals. Event-related potentials (ERPs) as well as the oscillatory dynamics of the EEG signal, specifically, frequency power changes expressed as event-related (de)synchronization (ERD/S), were analyzed. Replicating earlier results, we found an N400 on semantically incongruent words, as well as on low cloze probability words. For the bilinguals investigated in the present study, N400 latency in the low cloze probability condition was found to be modulated by L2 proficiency, indicating that L2 proficiency in our sample might have influenced the speed of semantic integration. Relative Theta power increased for all three word conditions, but no influence of proficiency was observed. Different from the ERP results, we found a stronger increase in theta power for low cloze probability words than for incongruent and high cloze probability words, especially over temporo-parietal brain areas. The spatial distribution of the theta ERD/S results also differed from the N400 topography. Whereas the N400 showed a typical topography with a maximum over temporo-posterior electrode positions, the theta ERD/S topography was maximal for high and low cloze probability words over left central-posterior electrode positions. These findings show that the ERP and ERD/S results are sensitive to semantic processing. The different pattern of the ERD/S results compared to the ERP results, functionally and with regard to topography, suggests that the ERD/S reflects a different aspect or stage of semantic processing, possibly the successful conceptualization of a sentence.
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November 2013

Review of the BCI Competition IV.

Front Neurosci 2012 13;6:55. Epub 2012 Jul 13.

Machine Learning Laboratory, Berlin Institute of Technology Berlin, Germany.

The BCI competition IV stands in the tradition of prior BCI competitions that aim to provide high quality neuroscientific data for open access to the scientific community. As experienced already in prior competitions not only scientists from the narrow field of BCI compete, but scholars with a broad variety of backgrounds and nationalities. They include high specialists as well as students. The goals of all BCI competitions have always been to challenge with respect to novel paradigms and complex data. We report on the following challenges: (1) asynchronous data, (2) synthetic, (3) multi-class continuous data, (4) session-to-session transfer, (5) directionally modulated MEG, (6) finger movements recorded by ECoG. As after past competitions, our hope is that winning entries may enhance the analysis methods of future BCIs.
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http://dx.doi.org/10.3389/fnins.2012.00055DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3396284PMC
October 2012

A hybrid ERD/SSVEP BCI for continuous simultaneous two dimensional cursor control.

J Neurosci Methods 2012 Aug 4;209(2):299-307. Epub 2012 Jul 4.

Institute for Knowledge Discovery, Graz University of Technology, Krenngasse 37, Graz, Austria.

We introduce a new type of BCI for continuous simultaneous two dimensional cursor control. Users tried to control the vertical position of a virtual ball via ERD activity associated with imagined movement while simultaneously controlling horizontal position with SSVEP activity resulting from visual attention. Ten subjects participated in one offline and six online control sessions. The online sessions assessed subjective measures via questionnaires as well as objective measures. Subjects generally reported that the hybrid task combination was not especially difficult or annoying. Two subjects attained very good performance, while the remaining subjects did not. Training did not affect subjective or objective measures. Overall, results show that this new hybrid approach is viable for some users, and that substantial further research is needed to identify and optimize the best BCIs for each user.
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http://dx.doi.org/10.1016/j.jneumeth.2012.06.022DOI Listing
August 2012

Rehabilitation of gait after stroke: a review towards a top-down approach.

J Neuroeng Rehabil 2011 Dec 13;8:66. Epub 2011 Dec 13.

Instituto de Biomecánica de Valencia, Universitat Politécnica de Valencia, Valencia, Spain.

This document provides a review of the techniques and therapies used in gait rehabilitation after stroke. It also examines the possible benefits of including assistive robotic devices and brain-computer interfaces in this field, according to a top-down approach, in which rehabilitation is driven by neural plasticity.The methods reviewed comprise classical gait rehabilitation techniques (neurophysiological and motor learning approaches), functional electrical stimulation (FES), robotic devices, and brain-computer interfaces (BCI).From the analysis of these approaches, we can draw the following conclusions. Regarding classical rehabilitation techniques, there is insufficient evidence to state that a particular approach is more effective in promoting gait recovery than other. Combination of different rehabilitation strategies seems to be more effective than over-ground gait training alone. Robotic devices need further research to show their suitability for walking training and their effects on over-ground gait. The use of FES combined with different walking retraining strategies has shown to result in improvements in hemiplegic gait. Reports on non-invasive BCIs for stroke recovery are limited to the rehabilitation of upper limbs; however, some works suggest that there might be a common mechanism which influences upper and lower limb recovery simultaneously, independently of the limb chosen for the rehabilitation therapy. Functional near infrared spectroscopy (fNIRS) enables researchers to detect signals from specific regions of the cortex during performance of motor activities for the development of future BCIs. Future research would make possible to analyze the impact of rehabilitation on brain plasticity, in order to adapt treatment resources to meet the needs of each patient and to optimize the recovery process.
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http://dx.doi.org/10.1186/1743-0003-8-66DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3261106PMC
December 2011