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Brain-computer interfaces (BCIs) are promising tools for motor neurorehabilitation. Achieving a balance between classification accuracy and system responsiveness is crucial for real-time applications. This study aimed to assess how the duration of time windows affects performance, specifically classification accuracy and the false positive rate, to optimize the temporal parameters of MI-BCI systems. We investigated the impact of time window duration on classification accuracy and false positive rate, employing Linear Discriminant Analysis (LDA), Multilayer Perceptron (MLP), and Support Vector Machine (SVM) on data acquired from six post-stroke patients and on the external BCI IVa dataset. EEG signals were recorded and processed using the Common Spatial Patterns (CSP) algorithm for feature extraction. Our results indicate that longer time windows generally enhance classification accuracy and reduce false positives across all classifiers, with LDA performing the best. However, to maintain the real-time responsiveness, crucial for practical applications, a balance must be struck. The results suggest an optimal time window of 1-2 s, offering a trade-off between classification performance and excessive delay to guarantee the system responsiveness. These findings underscore the importance of temporal optimization in MI-BCI systems to improve usability in real rehabilitation scenarios.

Electroencephalographic neurofeedback (EEG-NFB) represents a broadly used method that involves a real-time EEG signal measurement, immediate data processing with the extraction of the parameter(s) of interest, and feedback to the individual in a real-time. Using such a feedback loop, the individual may gain better control over the neurophysiological parameters, by inducing changes in brain functioning and, consequently, behavior. It is used as a complementary treatment for a variety of neuropsychological disorders and improvement of cognitive capabilities, creativity or relaxation in healthy subjects. In this review, various types of EEG-NFB training are described, including training of slow cortical potentials (SCPs) and frequency and coherence training, with their main results and potential limitations. Furthermore, some general concerns about EEG-NFB methodology are presented, which still need to be addressed by the NFB community. Due to the heterogeneity of research designs in EEG-NFB protocols, clear conclusions on the effectiveness of this method are difficult to draw. Despite that, there seems to be a well-defined path for the EEG-NFB research in the future, opening up possibilities for improvement.

Objective: A direct link between the mouth cavity and the brain for glucose (GLUC) and caffeine (CAF) has been established. The aim of this study is to determine whether a direct link for both substrates also exist between the nasal cavity and the brain. Methods: Ten healthy male subjects (age 22 ± 1 years) performed three experimental trials, separated by at least 2 days. Each trial included a 20-s nasal spray (NAS) period in which solutions placebo (PLAC), GLUC, or CAF were provided in a double-blind, randomized order. During each trial, four cognitive Stroop tasks were performed: two familiarization trials and one pre- and one post-NAS trial. Reaction times and accuracy for different stimuli (neutral, NEUTR; congruent, CON; incongruent INCON) were determined. Electroencephalography was continuously measured throughout the trials. During the Stroop tasks pre- and post-NAS, the P300 was assessed and during NAS, source localization was performed using standardized low-resolution brain electromagnetic tomography (sLORETA). Results and discussion: NAS activated the anterior cingulate cortex (ACC). CAF-NAS also increased θ and β activity in frontal cortices. Furthermore, GLUC-NAS increased the β activity within the insula. GLUC-NAS also increased the P300 amplitude with INCON ( P = 0.046) and reduced P300 amplitude at F3-F4 and P300 latency at CP1-CP2-Cz with NEUTR ( P = 0.001 and P = 0.016, respectively). The existence of nasal bitter and sweet taste receptors possibly induce these brain responses. Conclusion: Greater cognitive efficiency was observed with GLUC-NAS. CAF-NAS activated cingulate, insular, and sensorymotor cortices, whereas GLUC-NAS activated sensory, cingulate, and insular cortices. However, no effect on the Stroop task was found. [ABSTRACT FROM AUTHOR]