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Institute
Objective
Brain-computer interfaces (BCIs) provide a non-muscular communication channel for patients with late-stage motoneuron disease (e.g., amyotrophic lateral sclerosis (ALS)) or otherwise motor impaired people and are also used for motor rehabilitation in chronic stroke. Differences in the ability to use a BCI vary from person to person and from session to session. A reliable predictor of aptitude would allow for the selection of suitable BCI paradigms. For this reason, we investigated whether P300 BCI aptitude could be predicted from a short experiment with a standard auditory oddball.
Methods
Forty healthy participants performed an electroencephalography (EEG) based visual and auditory P300-BCI spelling task in a single session. In addition, prior to each session an auditory oddball was presented. Features extracted from the auditory oddball were analyzed with respect to predictive power for BCI aptitude.
Results
Correlation between auditory oddball response and P300 BCI accuracy revealed a strong relationship between accuracy and N2 amplitude and the amplitude of a late ERP component between 400 and 600 ms. Interestingly, the P3 amplitude of the auditory oddball response was not correlated with accuracy.
Conclusions
Event-related potentials recorded during a standard auditory oddball session moderately predict aptitude in an audiory and highly in a visual P300 BCI. The predictor will allow for faster paradigm selection.
Significance
Our method will reduce strain on patients because unsuccessful training may be avoided, provided the results can be generalized to the patient population.
Objective: Brain-computer interfaces (BCIs) provide a non-muscular communication channel for patients with late-stage motoneuron disease (e.g., amyotrophic lateral sclerosis (ALS)) or otherwise motor impaired people and are also used for motor rehabilitation in chronic stroke. Differences in the ability to use a BCI vary from person to person and from session to session. A reliable predictor of aptitude would allow for the selection of suitable BCI paradigms. For this reason, we investigated whether P300 BCI aptitude could be predicted from a short experiment with a standard auditory oddball. Methods: Forty healthy participants performed an electroencephalography (EEG) based visual and auditory P300-BCI spelling task in a single session. In addition, prior to each session an auditory oddball was presented. Features extracted from the auditory oddball were analyzed with respect to predictive power for BCI aptitude. Results: Correlation between auditory oddball response and P300 BCI accuracy revealed a strong relationship between accuracy and N2 amplitude and the amplitude of a late ERP component between 400 and 600 ms. Interestingly, the P3 amplitude of the auditory oddball response was not correlated with accuracy. Conclusions: Event-related potentials recorded during a standard auditory oddball session moderately predict aptitude in an audiory and highly in a visual P300 BCI. The predictor will allow for faster paradigm selection. Significance: Our method will reduce strain on patients because unsuccessful training may be avoided, provided the results can be generalized to the patient population.
The charge transport properties of disordered organic and nanocrystalline inorganic semiconductors as well as their combinations have been investigated in regard to the charge carrier density employing field-effect-transistor structures. The results were discussed in the framework of different theoretical models. In organic semiconductors the presence of positional and energetic disorder determines the transport of charges through the respective thin films and interfaces. The electronic disorder is characterized by statistically distributed and localized transport sites which were shown to form a Gaussian density of states. In this electronic environment the charge transport occurs via thermally activated hopping between the localized states and therefore depends on the temperature and the local electric field. Particularly, a dependence of the carrier mobility on the charge carrier concentration is observed due to filling of tail states. Inorganic nanocrystalline semiconductors, however, are expected to present a different electronic structure: Within the volume of a nanocrystallite the semiconductor is assumed to reflect the electronic properties of the crystalline bulk material. However, the outer shell is characterized by a relatively large density of surface states and correspondingly bending of the energy bands, which creates an energetic barrier between the adjacent particles. In a nanocrystalline thin film this characteristic can be rate-limiting for the inter-particle carrier transport as reflected by reduced charge carrier mobility. The effective barrier height can be reduced by controlled doping of the nanocrystals which results in improved majority carrier transfer rates across the barrier. However, doping results in the simultaneous increase of the defect density and consequently to enhanced limitation of the mobility due to charge carrier scattering. In the experiments, thin films of commercially available p- and n-type organic semiconductors (P3HT, and two derivatives of PCBM) were investigated in field-effect transistor structures. Further, sol-gel synthesized n-type nanocrystalline-ZnO (nc-ZnO) with varied doping concentration (agent: aluminum Al$^{3+}$) was introduced in order to establish an alternative way of customizing the charge transport properties of the neat material and in combination with the organic polymer semiconductor P3HT.