182 research outputs found
Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges
No full textIn recent years, new research has brought the field of EEG-based Brain-Computer Interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely,“Communication and Control”, “Motor Substitution”, “Entertainment”, and “Motor Recovery”. We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user-machine adaptation algorithms, the exploitation of users’ mental states for BCI reliability and confidence measures, the incorporation of principles in human-computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices
Human movement-related potentials vs desynchronization of EEG alpha rhythm: A high-resolution EEG study
No full textMovement-related potentials (MRPs) and event-related desynchronization (ERD) of alpha rhythm were investigated with an advanced high-resolution electroencephalographic technology (128 channels, surface Laplacian estimate, realistic head modeling). The working hypothesis was that MRPs and alpha ERD reflect different aspects of sensorimotor cortical processes. Both MRPs and alpha ERD modeled the responses of primary sensorimotor (M1-S1), supplementary motor (SMA), and posterior parietal (PP, area 5) areas during the preparation and execution of unilateral finger movements. Maximum responses were modeled in the contralateral M1-S1 during both preparation and execution of the movement. The SMA and PP responses were modeled mainly from the MRPs and alpha ERD, respectively. The modeled ipsilateral M1-S1 responses were larger and stronger in the alpha ERD than MRPs. These results may suggest that alpha ERD reflects changes in the background oscillatory activity in wide cortical sensorimotor areas, whereas MRPs represent mainly increased, task-specific responses of SMA and contralateral M1-S1
Comparison of spatial-temporal features of human mu ERD and mean movement-related potentials. A high resolution electroencephalography study
No full textCortical mu (10-12 Hz) Event-Related Desynchronization (ERD) and mean Movement-Related Potentials (mMMRP8s) in response to preparation and cxecution of human internally- triggered unilateral one-digit extension were investigated with an advanced high resolution electroencephalography (EEG) technology, which included high surface sampling (128 chan- nels) and surface Laplacian estimate of the potential over a realistic magnetic resonance-constructed subject’s scalp sur- face model. The working hypothesis Was that these responses would reflect different aspects of sensorimotor cortical processes. Consistent mu ERD and mMRPs were modeled in primary sensorimotor (M1-S1), supplementary motor (SMA), and posterior parictal (arca 5) areas during the preparation and execution of the movement. M1-S1s and SMA would generate mu ERD and mMRPSs, whereas areas 5 would pro- duce only the mu ERD. Compared to the mMRPs, the mu ERD would be more represented in ipsilateral M1-S1 across the late preparation and the execution of the movement. These results indicate that the mu ERD would reflect basic changes in background activity of bilateral sensorimotor corti- cal areas, whereas the mMRPS would represent task-specific sensorimotor cortical responses prominently generated in the contralateral M1-S1 and the SMA
Is there "neural efficiency" during the processing of visuo-spatial information in male humans? An EEG study
No full textMore intelligent persons (high IQ) typically present a higher cortical activity during tasks requiring the encoding of visuo-spatial information, namely higher alpha (about 10 Hz) event-related desynchronization (ERD; Doppelmayr et al., 2005 [23]). The opposite is true ("neural efficiency") during the retrieval of the encoded information, as revealed by both lower alpha ERD and/or lower theta (about 5 Hz) event-related synchronization (ERS; Grabner et al., 2004 [19]). To reconcile these contrasting results, here we evaluated the working hypothesis that more intelligent male subjects are characterized by a high cortical activity during the encoding phase. This deep encoding would explain the relatively low cortical activity for the retrieval of the encoded information. To test this hypothesis, electroencephalographic (EEG) data were recorded in 22 healthy young male volunteers during visuo-spatial information processing (encoding) and short-term retrieval of the encoded information. Cortical activity was indexed by theta ERS and alpha ERD. It was found that the higher the subjects' total IQ, the stronger the frontal theta ERS during the encoding task. Furthermore, the higher the subjects' total IQ, the lower the frontal high-frequency alpha ERD (about 10-12 Hz) during the retrieval task. This was not true for parietal counterpart of these EEG rhythms. These results reconcile previous contrasting evidence confirming that more intelligent persons do not ever show event-related cortical responses compatible with "neural efficiency" hypothesis. Rather, their cortical activity would depend on flexible and task-adapting features of frontal activation. © 2009 Elsevier B.V. All rights reserved
Is there "neural efficiency" during the processing of visuo-spatial information in male humans? An EEG study.
No full textIs there "neural efficiency" during the processing of visuo-spatial information in male humans? An EEG study
No full textMore intelligent persons (high IQ) typically present a higher cortical activity during tasks requiring the encoding of visuo-spatial information, namely higher alpha (about 10 Hz) event-related desynchronization (ERD; Doppelmayr et al., 2005). The opposite is true ("neural efficiency") during the retrieval of the encoded information, as revealed by both lower alpha ERD and/or lower theta (about 5 Hz) event-related synchronization (ERS; Grabner et al., 2004). To reconcile these contrasting results, here we evaluated the working hypothesis that more intelligent male subjects are characterized by a high cortical activity during the encoding phase. This deep encoding would explain the relatively low cortical activity for the retrieval of the encoded information. To test this hypothesis, electroencephalographic (EEG) data were recorded in 22 healthy young male volunteers during visuo-spatial information processing (encoding) and short-term retrieval of the encoded information. Cortical activity was indexed by theta ERS and alpha ERD. It was found that the higher the subjects' total IQ, the stronger the frontal theta ERS during the encoding task. Furthermore, the higher the subjects' total IQ, the lower the frontal high-frequency alpha ERD (about 10-12 Hz) during the retrieval task. This was not true for parietal counterpart of these EEG rhythms. These results reconcile previous contrasting evidence confirming that more intelligent persons do not ever show event-related cortical responses compatible with "neural efficiency" hypothesis. Rather, their cortical activity would depend on flexible and task-adapting features of frontal activation
Abnormalities of Resting State Functional Connectivity Are Related to Sustained Attention Deficits in MS
No full textResting state (RS) functional MRI recently identified default network abnormalities related to cognitive impairment in MS. fMRI can also be used to map functional connectivity (FC) while the brain is at rest and not adhered to a specific task. Given the importance of the anterior cingulate cortex (ACC) for higher executive functioning in MS, we here used the ACC as seed-point to test for differences and similarities in RS-FC related to sustained attention between MS patients and controls.Block-design rest phases of 3 Tesla fMRI data were analyzed to assess RS-FC in 31 patients (10 clinically isolated syndromes, 16 relapsing-remitting, 5 secondary progressive MS) and 31 age- and gender matched healthy controls (HC). Participants underwent extensive cognitive testing.In both groups, signal changes in several brain areas demonstrated significant correlation with RS-activity in the ACC. These comprised the posterior cingulate cortex (PCC), insular cortices, the right caudate, right middle temporal gyrus, angular gyri, the right hippocampus, and the cerebellum. Compared to HC, patients showed increased FC between the ACC and the left angular gyrus, left PCC, and right postcentral gyrus. Better cognitive performance in the patients was associated with increased FC to the cerebellum, middle temporal gyrus, occipital pole, and the angular gyrus.We provide evidence for adaptive changes in RS-FC in MS patients compared to HC in a sustained attention network. These results extend and partly mirror findings of task-related fMRI, suggesting FC may increase our understanding of cognitive dysfunction in MS
Oscillatory neuronal dynamics during language comprehension
No full textLanguage comprehension involves two basic operations: the retrieval of lexical information (such as phonologic, syntactic, and semantic information) from long-term memory, and the unification of this information into a coherent representation of the overall utterance. Neuroimaging studies using hemo¬dynamic measures such as PET and fMRI have provided detailed information on which areas of the brain are involved in these language-related memory and unification operations. However, much less is known about the dynamics of the brain's language network. This chapter presents a literature review of the oscillatory neuronal dynamics of EEG and MEG data that can be observed during language comprehen¬sion tasks. From a detailed review of this (rapidly growing) literature the following picture emerges: memory retrieval operations are mostly accompanied by increased neuronal synchronization in the theta frequency range (4-7 Hz). Unification operations, in contrast, induce high-frequency neuronal synchro¬nization in the beta (12-30 Hz) and gamma (above 30 Hz) frequency bands. A desynchronization in the (upper) alpha frequency band is found for those studies that use secondary tasks, and seems to correspond with attentional processes, and with the behavioral consequences of the language comprehension process. We conclude that it is possible to capture the dynamics of the brain's language network by a careful analysis of the event-related changes in power and coherence of EEG and MEG data in a wide range of frequencies, in combination with subtle experimental manipulations in a range of language comprehension tasks. It appears then that neuronal synchrony is a mechanism by which the brain integrates the different types of information about language (such as phonological, orthographic, semantic, and syntactic infor¬mation) represented in different brain areas
Sensorimotor rhythm-based brain-computer interface training: The impact on motor cortical responsiveness
No full textThe main purpose of electroencephalography (EEG)-based brain-computer interface (BCI) technology is to provide an alternative channel to support communication and control when motor pathways are interrupted. Despite the considerable amount of research focused on the improvement of EEG signal detection and translation into output commands, little is known about how learning to operate a BCI device may affect brain plasticity. This study investigated if and how sensorimotor rhythm-based BCI training would induce persistent functional changes in motor cortex, as assessed with transcranial magnetic stimulation (TMS) and high-density EEG. Motor imagery (MI)-based BCI training in naive participants led to a significant increase in motor cortical excitability, as revealed by post-training TMS mapping of the hand muscle's cortical representation; peak amplitude and volume of the motor evoked potentials recorded from the opponens pollicis muscle were significantly higher only in those subjects who develop a MI strategy based on imagination of hand grasping to successfully control a computer cursor. Furthermore, analysis of the functional brain networks constructed using a connectivity matrix between scalp electrodes revealed a significant decrease in the global efficiency index for the higher-beta frequency range (22-29 Hz), indicating that the brain network changes its topology with practice of hand grasping MI. Our findings build the neurophysiological basis for the use of non-invasive BCI technology for monitoring and guidance of motor imagery-dependent brain plasticity and thus may render BCI a viable tool for post-stroke rehabilitation
The role and value of distributed precipitation data in hydrological models
No full textThis study investigates the role and value of distributed rainfall for the runoff generation of a mesoscale catchment (20 km2). We compare four hydrological model setups and show that a distributed model setup driven by distributed rainfall only improves the model performances during certain periods. These periods are dominated by convective summer storms that are typically characterized by higher spatiotemporal variabilities compared to stratiform precipitation events that dominate rainfall generation in winter. Motivated by these findings, we develop a spatially adaptive model that is capable of dynamically adjusting its spatial structure during model execution. This spatially adaptive model allows the varying relevance of distributed rainfall to be represented within a hydrological model without losing predictive performance compared to a fully distributed model. Our results highlight that spatially adaptive modeling has the potential to reduce computational times as well as improve our understanding of the varying role and value of distributed precipitation data for hydrological models.Water Resource
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