Refine
Has Fulltext
- yes (17)
Is part of the Bibliography
- yes (17)
Year of publication
Document Type
- Journal article (17) (remove)
Language
- English (17) (remove)
Keywords
- EEG (17) (remove)
Institute
3D visualization of movements can amplify motor cortex activation during subsequent motor imagery
(2015)
A repetitive movement practice by motor imagery (MI) can influence motor cortical excitability in the electroencephalogram (EEG). This study investigated if a realistic visualization in 3D of upper and lower limb movements can amplify motor related potentials during subsequent MI. We hypothesized that a richer sensory visualization might be more effective during instrumental conditioning, resulting in a more pronounced event related desynchronization (ERD) of the upper alpha band (10–12 Hz) over the sensorimotor cortices thereby potentially improving MI based brain-computer interface (BCI) protocols for motor rehabilitation. The results show a strong increase of the characteristic patterns of ERD of the upper alpha band components for left and right limb MI present over the sensorimotor areas in both visualization conditions. Overall, significant differences were observed as a function of visualization modality (VM; 2D vs. 3D). The largest upper alpha band power decrease was obtained during MI after a 3-dimensional visualization. In total in 12 out of 20 tasks the end-user of the 3D visualization group showed an enhanced upper alpha ERD relative to 2D VM group, with statistical significance in nine tasks.With a realistic visualization of the limb movements, we tried to increase motor cortex activation during subsequent MI. The feedback and the feedback environment should be inherently motivating and relevant for the learner and should have an appeal of novelty, real-world relevance or aesthetic value (Ryan and Deci, 2000; Merrill, 2007). Realistic visual feedback, consistent with the participant’s MI, might be helpful for accomplishing successful MI and the use of such feedback may assist in making BCI a more natural interface for MI based BCI rehabilitation.
Current brain-computer interface (BCIs) software is often tailored to the needs of scientists and technicians and therefore complex to allow for versatile use. To facilitate home use of BCIs a multifunctional P300 BCI with a graphical user interface intended for non-expert set-up and control was designed and implemented. The system includes applications for spelling, web access, entertainment, artistic expression and environmental control. In addition to new software, it also includes new hardware for the recording of electroencephalogram (EEG) signals. The EEG system consists of a small and wireless amplifier attached to a cap that can be equipped with gel-based or dry contact electrodes. The system was systematically evaluated with a healthy sample, and targeted end users of BCI technology, i.e., people with a varying degree of motor impairment tested the BCI in a series of individual case studies. Usability was assessed in terms of effectiveness, efficiency and satisfaction. Feedback of users was gathered with structured questionnaires. Two groups of healthy participants completed an experimental protocol with the gel-based and the dry contact electrodes (N = 10 each). The results demonstrated that all healthy participants gained control over the system and achieved satisfactory to high accuracies with both gel-based and dry electrodes (average error rates of 6 and 13%). Average satisfaction ratings were high, but certain aspects of the system such as the wearing comfort of the dry electrodes and design of the cap, and speed (in both groups) were criticized by some participants. Six potential end users tested the system during supervised sessions. The achieved accuracies varied greatly from no control to high control with accuracies comparable to that of healthy volunteers. Satisfaction ratings of the two end-users that gained control of the system were lower as compared to healthy participants. The advantages and disadvantages of the BCI and its applications are discussed and suggestions are presented for improvements to pave the way for user friendly BCIs intended to be used as assistive technology by persons with severe paralysis.
Brain-computer interfaces (BCIs) can serve as muscle independent communication aids. Persons, who are unable to control their eye muscles (e.g., in the completely locked-in state) or have severe visual impairments for other reasons, need BCI systems that do not rely on the visual modality. For this reason, BCIs that employ auditory stimuli were suggested. In this study, a multiclass BCI spelling system was implemented that uses animal voices with directional cues to code rows and columns of a letter matrix. To reveal possible training effects with the system, 11 healthy participants performed spelling tasks on 2 consecutive days. In a second step, the system was tested by a participant with amyotrophic lateral sclerosis (ALS) in two sessions. In the first session, healthy participants spelled with an average accuracy of 76% (3.29 bits/min) that increased to 90% (4.23 bits/min) on the second day. Spelling accuracy by the participant with ALS was 20% in the first and 47% in the second session. The results indicate a strong training effect for both the healthy participants and the participant with ALS. While healthy participants reached high accuracies in the first session and second session, accuracies for the participant with ALS were not sufficient for satisfactory communication in both sessions. More training sessions might be needed to improve spelling accuracies. The study demonstrated the feasibility of the auditory BCI with healthy users and stresses the importance of training with auditory multiclass BCIs, especially for potential end-users of BCI with disease.
The main prediction of the Uncanny Valley Hypothesis (UVH) is that observation of humanlike characters that are difficult to distinguish from the human counterpart will evoke a state of negative affect. Well-established electrophysiological [late positive potential (LPP) and facial electromyography (EMG)] and self-report [Self-Assessment Manikin (SAM)] indices of valence and arousal, i.e., the primary orthogonal dimensions of affective experience, were used to test this prediction by examining affective experience in response to categorically ambiguous compared with unambiguous avatar and human faces (N = 30). LPP and EMG provided direct psychophysiological indices of affective state during passive observation and the SAM provided self-reported indices of affective state during explicit cognitive evaluation of static facial stimuli. The faces were drawn from well-controlled morph continua representing the UVH' dimension of human likeness (DHL). The results provide no support for the notion that category ambiguity along the DHL is specifically associated with enhanced experience of negative affect. On the contrary, the LPP and SAM-based measures of arousal and valence indicated a general increase in negative affective state (i.e., enhanced arousal and negative valence) with greater morph distance from the human end of the DHL. A second sample (N = 30) produced the same finding, using an ad hoc self-rating scale of feelings of familiarity, i.e., an oft-used measure of affective experience along the UVH' familiarity dimension. In conclusion, this multi-method approach using well-validated psychophysiological and self-rating indices of arousal and valence rejects for passive observation and for explicit affective evaluation of static faces the main prediction of the UVH.
Recent research suggests that the P3b may be closely related to the activation of the locus coeruleus-norepinephrine (LC-NE) system. To further study the potential association, we applied a novel technique, the non-invasive transcutaneous vagus nerve stimulation (tVNS), which is speculated to increase noradrenaline levels. Using a within-subject cross-over design, 20 healthy participants received continuous tVNS and sham stimulation on two consecutive days (stimulation counterbalanced across participants) while performing a visual oddball task. During stimulation, oval non-targets (standard), normal-head (easy) and rotated-head (difficult) targets, as well as novel stimuli (scenes) were presented. As an indirect marker of noradrenergic activation we also collected salivary alpha-amylase (sAA) before and after stimulation. Results showed larger P3b amplitudes for target, relative to standard stimuli, irrespective of stimulation condition. Exploratory post hoc analyses, however, revealed that, in comparison to standard stimuli, easy (but not difficult) targets produced larger P3b (but not P3a) amplitudes during active tVNS, compared to sham stimulation. For sAA levels, although main analyses did not show differential effects of stimulation, direct testing revealed that tVNS (but not sham stimulation) increased sAA levels after stimulation. Additionally, larger differences between tVNS and sham stimulation in P3b magnitudes for easy targets were associated with larger increase in sAA levels after tVNS, but not after sham stimulation. Despite preliminary evidence for a modulatory influence of tVNS on the P3b, which may be partly mediated by activation of the noradrenergic system, additional research in this field is clearly warranted. Future studies need to clarify whether tVNS also facilitates other processes, such as learning and memory, and whether tVNS can be used as therapeutic tool.
Electroencephalography (EEG) often fails to assess both the level (i.e., arousal) and the content (i.e., awareness) of pathologically altered consciousness in patients without motor responsiveness. This might be related to a decline of awareness, to episodes of low arousal and disturbed sleep patterns, and/or to distorting and attenuating effects of the skull and intermediate tissue on the recorded brain signals. Novel approaches are required to overcome these limitations. We introduced epidural electrocorticography (ECoG) for monitoring of cortical physiology in a late-stage amytrophic lateral sclerosis patient in completely locked-in state (CLIS) Despite long-term application for a period of six months, no implant related complications occurred. Recordings from the left frontal cortex were sufficient to identify three arousal states. Spectral analysis of the intrinsic oscillatory activity enabled us to extract state-dependent dominant frequencies at <4, similar to 7 and similar to 20 Hz, representing sleep-like periods, and phases of low and elevated arousal, respectively. In the absence of other biomarkers, ECoG proved to be a reliable tool for monitoring circadian rhythmicity, i.e., avoiding interference with the patient when he was sleeping and exploiting time windows of responsiveness. Moreover, the effects of interventions addressing the patient's arousal, e.g., amantadine medication, could be evaluated objectively on the basis of physiological markers, even in the absence of behavioral parameters. Epidural ECoG constitutes a feasible trade-off between surgical risk and quality of recorded brain signals to gain information on the patient's present level of arousal. This approach enables us to optimize the timing of interactions and medical interventions, all of which should take place when the patient is in a phase of high arousal. Furthermore, avoiding low responsiveness periods will facilitate measures to implement alternative communication pathways involving brain-computer interfaces (BCI).
Background: Since the replication crisis, standardization has become even more important in psychological science and neuroscience. As a result, many methods are being reconsidered, and researchers’ degrees of freedom in these methods are being discussed as a potential source of inconsistencies across studies.
New Method: With the aim of addressing these subjectivity issues, we have been working on a tutorial-like EEG (pre-)processing pipeline to achieve an automated method based on the semi-automated analysis proposed by Delorme and Makeig.
Results: Two scripts are presented and explained step-by-step to perform basic, informed ERP and frequency-domain analyses, including data export to statistical programs and visual representations of the data. The open-source software EEGlab in MATLAB is used as the data handling platform, but scripts based on code provided by Mike Cohen (2014) are also included.
Comparison with existing methods: This accompanying tutorial-like article explains and shows how the processing of our automated pipeline affects the data and addresses, especially beginners in EEG-analysis, as other (pre)-processing chains are mostly targeting rather informed users in specialized areas or only parts of a complete procedure. In this context, we compared our pipeline with a selection of existing approaches.
Conclusion: The need for standardization and replication is evident, yet it is equally important to control the plausibility of the suggested solution by data exploration. Here, we provide the community with a tool to enhance the understanding and capability of EEG-analysis. We aim to contribute to comprehensive and reliable analyses for neuro-scientific research.
Anxiety is characterized by anxious anticipation and heightened vigilance to uncertain threat. However, if threat is not reliably indicated by a specific cue, the context in which threat was previously experienced becomes its best predictor, leading to anxiety. A suitable means to induce anxiety experimentally is context conditioning: In one context (CTX+), an unpredictable aversive stimulus (US) is repeatedly presented, in contrast to a second context (CTX−), in which no US is ever presented. In this EEG study, we investigated attentional mechanisms during acquisition and extinction learning in 38 participants, who underwent a context conditioning protocol. Flickering video stimuli (32 s clips depicting virtual offices representing CTX+/−) were used to evoke steady‐state visual evoked potentials (ssVEPs) as an index of visuocortical engagement with the contexts. Analyses of the electrocortical responses suggest a successful induction of the ssVEP signal by video presentation in flicker mode. Furthermore, we found clear indices of context conditioning and extinction learning on a subjective level, while cortical processing of the CTX+ was unexpectedly reduced during video presentation. The differences between CTX+ and CTX− diminished during extinction learning. Together, these results indicate that the dynamic sensory input of the video presentation leads to disruptions in the ssVEP signal, which is greater for motivationally significant, threatening contexts.
Background:
In major depressive disorder (MDD), electrophysiological and imaging studies suggest reduced neural activity in the parietal and dorsolateral prefrontal cortex regions. In the present study, neural correlates of emotional processing in MDD were analyzed for the first time in a pre-/post-treatment design by means of magnetoencephalography (MEG), allowing for detecting temporal dynamics of brain activation.
Methods:
Twenty-five medication-free Caucasian in-patients with MDD and 25 matched controls underwent a baseline MEG session with passive viewing of pleasant, unpleasant, and neutral pictures. Fifteen patients were followed-up with a second MEG session after 4 weeks of antidepressant monopharmacotherapy with mirtazapine. The corresponding controls received no intervention between the measurements. The clinical course of depression was assessed using the Hamilton Depression scale.
Results:
Prior to treatment, an overall neocortical hypoactivation during emotional processing, particularly at the parietal regions and areas at the right temporoparietal junction, as well as abnormal valence-specific reactions at the right parietal and bilateral dorsolateral prefrontal cortex (dlPFC) regions were observed in patients compared to controls. These effects occurred <150ms, suggesting dysfunctional processing of emotional stimuli at a preconscious level. Successful antidepressant treatment resulted in a normalization of the hypoactivation at the right parietal and right temporoparietal regions. Accordingly, both dlPFC regions revealed an increase of activity after therapy.
Conclusions:
The present study provides neurophysiological evidence for dysfunctional emotional processing in a fronto-parieto-temporal network, possibly contributing to the pathogenesis of MDD. These activation patterns might have the potential to serve as biomarkers of treatment success.
Background:
In major depressive disorder (MDD), electrophysiological and imaging studies suggest reduced neural activity in the parietal and dorsolateral prefrontal cortex regions. In the present study, neural correlates of emotional processing in MDD were analyzed for the first time in a pre-/post-treatment design by means of magnetoencephalography (MEG), allowing for detecting temporal dynamics of brain activation.
Methods:
Twenty-five medication-free Caucasian in-patients with MDD and 25 matched controls underwent a baseline MEG session with passive viewing of pleasant, unpleasant, and neutral pictures. Fifteen patients were followed-up with a second MEG session after 4 weeks of antidepressant monopharmacotherapy with mirtazapine. The corresponding controls received no intervention between the measurements. The clinical course of depression was assessed using the Hamilton Depression scale.
Results:
Prior to treatment, an overall neocortical hypoactivation during emotional processing, particularly at the parietal regions and areas at the right temporoparietal junction, as well as abnormal valence-specific reactions at the right parietal and bilateral dorsolateral prefrontal cortex (dlPFC) regions were observed in patients compared to controls. These effects occurred <150ms, suggesting dysfunctional processing of emotional stimuli at a preconscious level. Successful antidepressant treatment resulted in a normalization of the hypoactivation at the right parietal and right temporoparietal regions. Accordingly, both dlPFC regions revealed an increase of activity after therapy.
Conclusions:
The present study provides neurophysiological evidence for dysfunctional emotional processing in a fronto-parieto-temporal network, possibly contributing to the pathogenesis of MDD. These activation patterns might have the potential to serve as biomarkers of treatment success.