16 research outputs found
Abnormal neural connectivity in schizophrenia and fMRI-brain computer interface as a potential therapeutic approach
No full textConsidering that single locations of structural and functional abnormalities are insufficient to explain the diverse psychopathology of schizophrenia, new models have postulated that the impairments associated with the disease arise from a failure to integrate the activity of local and distributed neural circuits: the abnormal neural connectivity hypothesis. In the last years, new evidence coming from neuroimaging have supported and expanded this theory. However, despite the increasing evidence that schizophrenia is a disorder of neural connectivity, so far there are no treatments that have shown to produce a significant change in brain connectivity, or that have been specifically designed to alleviate this problem. Brain-Computer Interfaces based on real-time functional Magnetic Resonance Imaging (fMRI-BCI) are novel techniques that have allowed subjects to achieve self-regulation of circumscribed brain regions. In recent studies, experiments with this technology have resulted in new findings suggesting that this methodology could be used to train subjects to enhance brain connectivity, and therefore could potentially be used as a therapeutic tool in mental disorders including schizophrenia.The present article summarizes the findings coming from hemodynamics-based neuroimaging that support the abnormal connectivity hypothesis in schizophrenia, and discusses a new approach that could address this problem
Movement related slow cortical potentials in severely paralyzed chronic stroke patients
No full textMovement-related slow cortical potentials (SCPs) are proposed as reliable and immediate indicators of cortical reorganisation in motor learning. SCP amplitude and latency have been reported as markers for the brain’s computational effort, attention and movement planning. SCPs have been used as an EEG signature of motor control and as a main feature in Brain-Machine-Interfaces (BMIs). Some reports suggest SCPs are modified following stroke. In this study, we investigated movement-related SCPs in severe chronic stroke patients with no residual paretic hand movements preceding and during paretic (when they try to move) and healthy hand movements. The aim was to identify SCP signatures related to cortex integrity and complete paralysis due to stroke in the chronic stage. 20 severely impaired (no residual finger extension) chronic stoke patients, of whom 10 presented subcortical and 10 cortical and subcortical lesions, underwent EEG and EMG recordings during a cue triggered hand movement (open/close) paradigm. SCP onset appeared and peaked significantly earlier during paretic hand movements than during healthy hand movements. Amplitudes were significantly larger over the midline (Cz, Fz) for paretic hand movements while contralateral (C4, F4) and midline (Cz, Fz) amplitudes were significantly larger than ipsilateral activity for healthy hand movements. Dividing the participants into subcortical only and mixed lesioned patient groups, no significant differences observed in SCP amplitude and latency between groups. This suggests lesions in the thalamocortical loop as the main factor in SCP changes after stroke. Furthermore, we demonstrated how, after long-term complete paralysis, post-stroke intention to move a paralyzed hand resulted in longer and larger SCPs originating in the frontal areas. These results suggest SCP are a valuable feature that should be incorporated in the design of new neurofeedback strategies for motor neurorehabilitation
Fast mental states decoding in mixed reality.
No full textThe combination of Brain-Computer Interface technology, allowing online monitoring and decoding of brain activity, with virtual and mixed reality systems may help to shape and guide implicit and explicit learning using ecological scenarios. Real-time information of ongoing brain states acquired through BCI might be exploited for controlling data presentation in virtual environments. In this context, assessing to what extent brain states can be discriminated during mixed reality experience is critical for adapting specific data features to contingent brain activity. In this study we recorded EEG data while participants experienced a mixed reality scenario implemented through the eXperience Induction Machine (XIM). The XIM is a novel framework modeling the integration of a sensing system that evaluates and measures physiological and psychological states with a number of actuators and effectors that coherently reacts to the user's actions. We then assessed continuous EEG-based discrimination of spatial navigation, reading and calculation performed in mixed reality, using LDA and SVM classifiers. Dynamic single trial classification showed high accuracy of LDA and SVM classifiers in detecting multiple brain states as well as in differentiating between high and low mental workload, using a 5 s time-window shifting every 200 ms. Our results indicate overall better performance of LDA with respect to SVM and suggest applicability of our approach in a BCI-controlled mixed reality scenario. Ultimately, successful prediction of brain states might be used to drive adaptation of data representation in order to boost information processing in mixed reality
Coupling BCI and cortical stimulation for brain-state-dependent stimulation: Methods for spectral estimation in the presence of stimulation after-effects
No full textBrain-state-dependent stimulation combines brain-computer interfaces (BCI) and cortical stimulation into one paradigm that allows the online decoding for example of movement intention from brain signals while simultaneously applying stimulation. If the BCI decoding is performed by spectral features, stimulation after-effects such as artefacts and evoked activity present a challenge for a successful implementation of brain-state-dependent stimulation because they can impair the detection of targeted brain states. Therefore, efficient and robust methods are needed to minimize the influence of the stimulation-induced effects on spectral estimation without violating the real-time constraints of the BCI.In this work, we compared 4 methods for spectral estimation with autoregressive (AR) models in the presence of pulsed cortical stimulation. Using combined EEG-TMS as well as combined ECoG and epidural electrical stimulation, 3 patients performed a motor task using a sensorimotor-rhythm BCI. Three stimulation paradigms were varied between sessions: (1) no stimulation, (2) single stimulation pulses applied independently (open-loop) or (3) coupled to the BCI output (closed-loop) such that stimulation was given only while an intention to move was detected using neural data.We found that removing the stimulation after-effects by linear interpolation can introduce a bias in the estimation of the spectral power of the sensorimotor rhythm, leading to an overestimation of decoding performance in the closed-loop setting. We propose the use of the Burg algorithm for segmented data to deal with stimulation after-effects. This work shows that the combination of BCIs controlled with spectral features and cortical stimulation in a closed-loop fashion is possible when the influence of stimulation after-effects on spectral estimation is minimized
Editorial on Learned brain self-regulation for emotional processing and attentional modulation: from theory to clinical applications
No full textNeurophysiology of robot-mediated training and therapy: A perspective for future use in clinical populations.
No full textThe recovery of functional movements following injury to the central nervous system (CNS) is multifaceted and is accompanied by processes occurring in the injured and non-injured hemispheres of the brain or above/below a spinal cord lesion. The changes in the CNS are the consequence of functional and structural processes collectively termed neuroplasticity and these may occur spontaneously and/or be induced by movement practice. The neurophysiological mechanisms underlying such brain plasticity may take different forms in different types of injury, for example stroke vs. spinal cord injury (SCI). Recovery of movement can be enhanced by intensive, repetitive, variable and rewarding motor practice. To this end, robots that enable or facilitate repetitive movements have been developed to assist recovery and rehabilitation. Here, we suggest some elements of robot-mediated training such as assistance, perturbation and unloading may have the potential to enhance neuroplasticity. Together the elemental components for developing integrated robot-mediated training protocols may form part of a neurorehabilitation framework alongside those methods already employed by therapists. Robots could thus open up a wider choice of options for delivering movement rehabilitation grounded on the principles underpinning neuroplasticity in the human CNS
Psychosocial adjustment to ALS: a longitudinal study
No full textFor the current study the Lazarian stress-coping theory and the appendant model of psychosocial adjustment to chronic illness and disabilities (Pakenham 1999) has shaped the foundation for identifying determinants of adjustment to ALS. We aimed to investigate the evolution of psychosocial adjustment to ALS and to determine its long-term predictors. A longitudinal study design with four measurement time points was therefore, used to assess patients’ quality of life, depression, and stress-coping model related aspects, such as illness characteristics, social support, cognitive appraisals and coping strategies during a period of two years. Regression analyses revealed that 55% of the variance of severity of depressive symptoms and 47% of the variance in quality of life at T2 was accounted for by all the T1 predictor variables taken together. On the level of individual contributions, protective buffering and appraisal of own coping potential accounted for a significant percentage in the variance in severity of depressive symptoms, whereas problem management coping strategies explained variance in quality of life scores. Illness characteristics at T2 did not explain any variance of both adjustment outcomes. Overall, the pattern of the longitudinal results indicated stable depressive symptoms and quality of life indices reflecting a successful adjustment to the disease across four measurement time points during a period of about two years.Empirical evidence is provided for the predictive value of social support, cognitive appraisals, and coping strategies, but not illness parameters such as severity and duration for adaptation to ALS. The current study contributes to a better conceptualization of adjustment, allowing us to provide evidence-based support beyond medical and physical intervention for people with ALS
Semantic classical conditioning and brain-computer interface (BCI) control: Encoding of affirmative and negative thinking
No full textThe aim of the study was to investigate conditioned electroencephalographic (EEG) responses to factually correct and incorrect statements in order to enable binary communication by means of a brain-computer interface (BCI). In two experiments with healthy participants true and false statements (serving as conditioned stimuli, CSs) were paired with two different tones which served as unconditioned stimuli (USs). The features of the USs were varied and tested for their effectiveness to elicit differentiable conditioned reactions (CRs). After acquisition of the CRs, these CRs to true and false statements were classified offline using a radial basis function kernel support vector machine. A mean single-trial classification accuracy of 50.5% was achieved for differentiating conditioned yes versus no thinking and mean accuracies of 65.4% for classification of yes and 68.8% for no thinking (both relative to baseline) were found using the best US. Analysis of the area under the curve of the conditioned EEG responses revealed significant differences between conditioned yes and no answers. Even though improvements are necessary, these first results indicate that the semantic conditioning paradigm could be a useful basis for further research regarding BCI communication in patients with complete locked-in syndrome (CLIS)
Winning the game: Brain processes in expert, young elite and amateur table tennis players
No full textThis study tested two hypotheses: (1) compared with amateurs and young elite, expert table tennis players are characterized by enhanced cortical activation in the motor and fronto-parietal cortex during motor imagery in response to table tennis videos; (2) in elite athletes, world rank points are associated with stronger cortical activation. To this aim, electroencephalographic data were recorded in 14 expert, 15 amateur and 15 young elite right-handed table tennis players. All subjects watched videos of a serve and imagined themselves responding with a specific table tennis stroke. With reference to a baseline period, power decrease/increase of the sensorimotor rhythm (SMR) during the pretask- and task period indexed the cortical activation/deactivation (event-related desynchronization/synchronization, ERD/ERS). Regarding hypothesis (1), 8–10 Hz SMR ERD was stronger in elite athletes than in amateurs with an intermediate ERD in young elite athletes over the whole scalp. Regarding hypothesis (2), there was no correlation between ERD/ERS in the motor cortex and world rank points in elite experts, but a weaker ERD in the fronto-parietal cortex was associated with higher world rank points. These results suggest that motor skill in table tennis is associated with focused excitability of the motor cortex during reaction, movement planning and execution with high attentional demands. Among elite experts, less activation of the fronto-parietal attention network may be necessary to become a world champion
tACS phase locking of frontal midline theta oscillations disrupts working memory performance
No full textFrontal midline theta (FMT) oscillations (4-8Hz) are strongly related to cognitive and executive control during mental tasks such as memory processing, arithmetic problem solving or sustained attention. While maintenance of temporal order information during a working memory (WM) task was recently linked to FMT phase, a positive correlation between FMT power, WM demand and WM performance was shown. However, the relationship between these measures is not well understood, and it is unknown whether purposeful FMT phase manipulation during a WM task impacts FMT power and WM performance. Here we present evidence that FMT phase manipulation mediated by transcranial alternating current stimulation (tACS) can block WM demand-related FMT power increase and disrupt normal WM performance. Methods: 20 healthy volunteers were assigned to one of two groups (group A, group B) and performed a 2-back task across a baseline block (block 1) and an intervention block (block 2) while 275-sensor magnetoencephalography (MEG) was recorded. After no stimulation was applied during block 1, participants in group A received tACS oscillating at their individual FMT frequency over the prefrontal cortex (PFC) while group B received sham stimulation during block 2. After assessing and mapping phase locking values (PLV) between the tACS signal and brain oscillatory activity across the whole brain, FMT power and WM performance were assessed and compared between blocks and groups. Results: During block 2 of group A but not B, FMT oscillations showed increased PLV across task-related cortical areas underneath the frontal tACS electrode. While WM task-related FMT power increase (FMTpower) and WM performance were comparable across groups in block 1, tACS resulted in lower FMTpower and WM performance compared to sham stimulation in block 2. Conclusion: tACS-related manipulation of FMT phase can disrupt WM performance and influence WM task-related FMT power increase. This finding may have important implications for the treatment of brain disorders such as depression and attention deficit disorder associated with abnormal regulation of FMT activity or disorders characterized by dysfunctional coupling of brain activity, e.g. epilepsy, Alzheimer’s or Parkinson’s disease
