Information in the cortex is encoded in spatiotemporal patterns of neuronal activity, but the exact nature of that code still remains elusive. While onset responses to simple stimuli are associated with specific loci in cortical sensory maps, it is completely unclear how the information about a sustained stimulus is encoded that is perceived for minutes or even longer, when discharge rates have decayed back to spontaneous levels. Using a newly developed statistical approach (multidimensional cluster statistics (MCS)) that allows for a comparison of clusters of data points in n-dimensional space, we here demonstrate that the information about long-lasting stimuli is encoded in the ongoing spatiotemporal activity patterns in sensory cortex. We successfully apply MCS to multichannel local field potential recordings in different rodent models and sensory modalities, as well as to human MEG and EEG data, demonstrating its universal applicability. MCS thus indicates novel ways for the development of powerful read-out algorithms of spatiotemporal brain activity that may be implemented in innovative brain-computer interfaces (BCI).
The lung constantly interacts with numerous pathogens. Thus, complex local immune defence mechanisms are essential to recognise and dispose of these intruders. This work describes the detection, characterisation and three-dimensional structure of a novel protein of the lung (surfactantassociated protein 3 (SFTA3/SP-H)) with putative immunological features.Bioinformatics, biochemical and immunological methods were combined to elucidate the structure and function of SFTA3. The tissue-specific detection and characterisation was performed by using electron microscopy as well as fluorescence imaging.Three-dimensional structure generation and analysis led to the development of specific antibodies and, as a consequence, to the localisation of a novel protein in human lung under consideration of cystic fibrosis, asthma and sepsis. In vitro experiments revealed that lipopolysaccharide induces expression of SFTA3 in the human lung alveolar type II cell line A549. By contrast, the inflammatory cytokines interleukin (IL)-1b and IL-23 inhibit expression of SFTA3 in A549. Sequence-and structure-based prediction analysis indicated that the novel protein is likely to belong to the family of lung surfactant proteins.The results suggest that SFTA3 is an immunoregulatory protein of the lung with relevant protective functions during inflammation at the mucosal sites. @ERSpublications SFTA3: a novel lung protein with putative protective and immunological functions during inflammation in lung diseases
Classic visual sleep stage scoring is based on electroencephalogram (EEG) frequency band analysis of 30 s epochs and is commonly performed by highly trained medical sleep specialists using additional information from submental EMG and eye movements electrooculogram (EOG). In this study, we provide the proof-of-principle in 40 subjects that sleep stages can be consistently differentiated solely on the basis of spatial 3-channel EEG patterns based on root-mean-square (RMS) amplitudes. The polysomnographic 3-channel EEG data are pre-processed by RMS averaging over intervals of 30 s leading to spatial cortical activity patterns represented by 3-dimensional vectors. These patterns are visualized using multidimensional scaling (MDS), allowing a comparison of the spatial cortical activity patterns with the conventional visual sleep scoring system according to the American Academy of Sleep Medicine (AASM). Spatial cortical activity patterns based on RMS amplitudes naturally divide into different clusters that correspond to visually scored sleep stages. Furthermore, these clusters are reproducible between different subjects. Especially the cluster associated with the REM sleep stage seems to be very different from the one associated with the wake state. This study provides a proof-of-principle that it is possible to separate sleep stages solely by analyzing spatially distributed EEG RMS amplitudes reflecting cortical activity and without classical EEG feature extractions like power spectrum analysis.
The sound spectra obtained in a synthetic larynx exhibited subharmonic tones that are characteristic for diplophonia. Although the generation of subharmonics is commonly associated with asymmetrically oscillating vocal folds, the synthetic elastic vocal folds showed symmetrical oscillations. The amplitudes of the subharmonics decreased with an increasing lateral diameter of the supraglottal channel, which indicates a strong dependence of the supraglottal boundary conditions. Investigations of the supraglottal flow field revealed small cycle-to-cycle variations of the static pressure in the region of the pulsatile glottal jet as the origin of the first subharmonic tone. It is located at half the fundamental frequency of the vocal fold oscillation. A principle component analysis of the supraglottal flow field with the fully developed glottal jet revealed a large recirculation area in the second spatial eigenvector which deflected the glottal jet slightly in a perpendicular direction of the jet axis. The rotation direction of the recirculation area changed with different oscillation cycles between clockwise and counterclockwise. As both directions were uniformly distributed across all acquired oscillation cycles, a cycle-wise change can be assumed. It is concluded that acoustic subharmonics are generated by small fluctuations of the glottal jet location favored by small lateral diameters of the supraglottal channel.
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