Mapping of the central sulcus using non-invasive ultra-high-density brain recordings.

Brain mapping is vital in understanding the brain's functional organization. Electroencephalography (EEG) is one of the most widely used brain mapping approaches, primarily because it is non-invasive, inexpensive, straightforward, and effective. Increasing the electrode density in EEG systems provides more neural information and can thereby enable more detailed and nuanced mapping procedures. Here, we show that the central sulcus can be clearly delineated using a novel ultra-high-density EEG system (uHD EEG) and somatosensory evoked potentials (SSEPs). This uHD EEG records from 256 channels with an inter-electrode distance of 8.6 mm and an electrode diameter of 5.9 mm. Reconstructed head models were generated from T1-weighted MRI scans, and electrode positions were co-registered to these models to create topographical plots of brain activity. EEG data were first analyzed with peak detection methods and then classified using unsupervised spectral clustering. Our topography plots of the spatial distribution from the SSEPs clearly delineate a division between channels above the somatosensory and motor cortex, thereby localizing the central sulcus. Individual EEG channels could be correctly classified as anterior or posterior to the central sulcus with 95.2% accuracy, which is comparable to accuracies from invasive intracranial recordings. Our findings demonstrate that uHD EEG can resolve the electrophysiological signatures of functional representation in the brain at a level previously only seen from surgically implanted electrodes. This novel approach could benefit numerous applications, including research, neurosurgical mapping, clinical monitoring, detection of conscious function, brain-computer interfacing (BCI), rehabilitation, and mental health.

Real-time estimation of EEG-based engagement in different tasks.

Objective.Recent trends in brain-computer interface (BCI) research concern the passive monitoring of brain activity, which aim to monitor a wide variety of cognitive states. Engagement is such a cognitive state, which is of interest in contexts such as learning, entertainment or rehabilitation. This study proposes a novel approach for real-time estimation of engagement during different tasks using electroencephalography (EEG).Approach.Twenty-three healthy subjects participated in the BCI experiment. A modified version of the d2 test was used to elicit engagement. Within-subject classification models which discriminate between engaging and resting states were trained based on EEG recorded during a d2 test based paradigm. The EEG was recorded using eight electrodes and the classification model was based on filter-bank common spatial patterns and a linear discriminant analysis. The classification models were evaluated in cross-task applications, namely when playing Tetris at different speeds (i.e. slow, medium, fast) and when watching two videos (i.e. advertisement and landscape video). Additionally, subjects' perceived engagement was quantified using a questionnaire.Main results.The models achieved a classification accuracy of 90% on average when tested on an independent d2 test paradigm recording. Subjects' perceived and estimated engagement were found to be greater during the advertisement compared to the landscape video (p= 0.025 andp<0.001, respectively); greater during medium and fast compared to slow Tetris speed (p<0.001, respectively); not different between medium and fast Tetris speeds. Additionally, a common linear relationship was observed for perceived and estimated engagement (rrm= 0.44,p<0.001). Finally, theta and alpha band powers were investigated, which respectively increased and decreased during more engaging states.Significance.This study proposes a task-specific EEG engagement estimation model with cross-task capabilities, offering a framework for real-world applications.

Individual finger movement decoding using a novel ultra-high-density electroencephalography-based brain-computer interface system.

Brain-Computer Interface (BCI) technology enables users to operate external devices without physical movement. Electroencephalography (EEG) based BCI systems are being actively studied due to their high temporal resolution, convenient usage, and portability. However, fewer studies have been conducted to investigate the impact of high spatial resolution of EEG on decoding precise body motions, such as finger movements, which are essential in activities of daily living. Low spatial sensor resolution, as found in common EEG systems, can be improved by omitting the conventional standard of EEG electrode distribution (the international 10-20 system) and ordinary mounting structures (e.g., flexible caps). In this study, we used newly proposed flexible electrode grids attached directly to the scalp, which provided ultra-high-density EEG (uHD EEG). We explored the performance of the novel system by decoding individual finger movements using a total of 256 channels distributed over the contralateral sensorimotor cortex. Dense distribution and small-sized electrodes result in an inter-electrode distance of 8.6 mm (uHD EEG), while that of conventional EEG is 60 to 65 mm on average. Five healthy subjects participated in the experiment, performed single finger extensions according to a visual cue, and received avatar feedback. This study exploits mu (8-12 Hz) and beta (13-25 Hz) band power features for classification and topography plots. 3D ERD/S activation plots for each frequency band were generated using the MNI-152 template head. A linear support vector machine (SVM) was used for pairwise finger classification. The topography plots showed regular and focal post-cue activation, especially in subjects with optimal signal quality. The average classification accuracy over subjects was 64.8 (6.3)%, with the middle versus ring finger resulting in the highest average accuracy of 70.6 (9.4)%. Further studies are required using the uHD EEG system with real-time feedback and motor imagery tasks to enhance classification performance and establish the basis for BCI finger movement control of external devices.

Phagocytosis and digestion of pH-sensitive fluorescent dye (Eos-FP) transfected E. coli in whole blood assays from patients with severe sepsis and septic shock.

The function of phagocytic and antigen presenting cells is of crucial importance to sustain immune competence against infectious agents as well as malignancies. We here describe a reproducible procedure for the quantification of phagocytosis by leukocytes in whole blood. For this, a pH-sensitive green-fluorescent protein- (GFP) like dye (Eos-FP) is transfected into infectious microroganisms. After UV-irradiation, the transfected bacteria emit green (≈5160 nm) and red (≈581 nm) fluorescent light at 490 nm excitation. Since the red fluorescent light is sensitive to acidic pH, the phagocytosed bacteria stop emitting red fluorescent light as soon as the phagosomes fuse with lysosomes. The green fluorescence is maintained in the phagolysosome until pathogen degradation is completed. Fluorescence emission can be followed by flow cytometry with filter settings documenting fluorescence 1 (FL 1, FITC) and fluorescence 2 (FL 2, phycoerythrin, PE). Eos-FP transfected bacteria can also be traced within phagocytes using microscopical techniques. A standardized assay has been developed which is suitable for clinical studies by providing clinicians with syringes pre-filled with fixed and appropriately UV-irradiated Eos-FP E. coli (TruCulture™). After adding blood or body fluids to these containers and starting the incubation at 37°C, phagocytosis by granulocytes proceeds over time. Cultures can be terminated at a given time by lysing red blood cells followed by flow cytometry. A pilot study demonstrated that Eos-FP E. coli phagocytosis and digestion was up-regulated in the majority of patients with either severe sepsis or septic shock as compared to healthy donors (p < 0.0001 after o/n incubation). Following treatment with recombinant human granulocyte colony-stimulating factor (rhG-CSF) in selected patients with sepsis, phagolysosome fusion appeared to be accelerated.