Electroencephalography (EEG) is one fundamental tool for functional brain imaging. EEG signals tend to be represented by a vector or a matrix to facilitate data processing and analysis with generally understood methodologies like time-series analysis, spectral analysis and matrix decomposition. Indeed, EEG signals are often naturally born with more than two modes of time and space, and they can be denoted by a multi-way array called as tensor. This review summarizes the current progress of tensor decomposition of EEG signals with three aspects. The first is about the existing modes and tensors of EEG signals. Second, two fundamental tensor decomposition models, canonical polyadic decomposition (CPD, it is also called parallel factor analysis-PARAFAC) and Tucker decomposition, are introduced and compared. Moreover, the applications of the two models for EEG signals are addressed. Particularly, the determination of the number of components for each mode is discussed. Finally, the N-way partial least square and higher-order partial least square are described for a potential trend to process and analyze brain signals of two modalities simultaneously.

Unicellular eukaryotic phytoplankton, such as diatoms, rely on microbial communities for survival despite lacking specialized compartments to house microbiomes (e.g., animal gut). Microbial communities have been widely shown to benefit from diatom excretions that accumulate within the microenvironment surrounding phytoplankton cells, known as the phycosphere. However, mechanisms that enable diatoms and other unicellular eukaryotes to nurture specific microbiomes by fostering beneficial bacteria and repelling harmful ones are mostly unknown. We hypothesized that diatom exudates may tune microbial communities and employed an integrated multiomics approach using the ubiquitous diatom Asterionellopsis glacialis to reveal how it modulates its naturally associated bacteria. We show that A. glacialis reprograms its transcriptional and metabolic profiles in response to bacteria to secrete a suite of central metabolites and two unusual secondary metabolites, rosmarinic acid and azelaic acid. While central metabolites are utilized by potential bacterial symbionts and opportunists alike, rosmarinic acid promotes attachment of beneficial bacteria to the diatom and simultaneously suppresses the attachment of opportunists. Similarly, azelaic acid enhances growth of beneficial bacteria while simultaneously inhibiting growth of opportunistic ones. We further show that the bacterial response to azelaic acid is numerically rare but globally distributed in the world’s oceans and taxonomically restricted to a handful of bacterial genera. Our results demonstrate the innate ability of an important unicellular eukaryotic group to modulate select bacteria in their microbial consortia, similar to higher eukaryotes, using unique secondary metabolites that regulate bacterial growth and behavior inversely across different bacterial populations.

The Wnt/β-catenin signaling pathway has a crucial role in embryonic development, stem cell maintenance and human disease. By screening a synthetic chemical library of lycorine derivatives, we identified 4-ethyl-5-methyl-5,6-dihydro-[1,3]dioxolo[4,5-j]phenanthridine (HLY78) as an activator of the Wnt/β-catenin signaling pathway, which acts in a Wnt ligand-dependent manner. HLY78 targets the DIX domain of Axin and potentiates the Axin-LRP6 association, thus promoting LRP6 phosphorylation and Wnt signaling transduction. Moreover, we identified the critical residues on Axin for HLY78 binding and showed that HLY78 may weaken the autoinhibition of Axin. In addition, HLY78 acts synergistically with Wnt in the embryonic development of zebrafish and increases the expression of the conserved hematopoietic stem cell (HSC) markers, runx1 and cmyb, in zebrafish embryos. Collectively, our study not only provides new insights into the regulation of the Wnt/β-catenin signaling pathway by a Wnt-specific small molecule but also will facilitate therapeutic applications, such as HSC expansion.

Any occasional changes in the acoustic environment are of potential importance for survival. In humans, the preattentive detection of such changes generates the mismatch negativity (MMN) component of event-related brain potentials. MMN is elicited to rare changes (‘deviants’) in a series of otherwise regularly repeating stimuli (‘standards’). Deviant stimuli are detected on the basis of a neural comparison process between the input from the current stimulus and the sensory memory trace of the standard stimuli. It is, however, unclear to what extent animals show a similar comparison process in response to auditory changes. To resolve this issue, epidural potentials were recorded above the primary auditory cortex of urethane-anesthetized rats. In an oddball condition, tone frequency was used to differentiate deviants interspersed randomly among a standard tone. Mismatch responses were observed at 60–100 ms after stimulus onset for frequency increases of 5% and 12.5% but not for similarly descending deviants. The response diminished when the silent inter-stimulus interval was increased from 375 ms to 600 ms for +5% deviants and from 600 ms to 1000 ms for +12.5% deviants. In comparison to the oddball condition the response also diminished in a control condition in which no repetitive standards were presented (equiprobable condition). These findings suggest that the rat mismatch response is similar to the human MMN and indicate that anesthetized rats provide a valuable model for studies of central auditory processing.

Abstract. The objective of this research is to improve traffic safety through collecting and distributing up-to-date road surface condition information using mobile phones. Road surface condition information is seen useful for both travellers and for the road network maintenance. The problem we consider is to detect road surface anomalies that, when left unreported, can cause wear of vehicles, lesser driving comfort and vehicle controllability, or an accident. In this work we developed a pattern recognition system for detecting road condition from accelerometer and GPS readings. We present experimental results from real urban driving data that demonstrate the usefulness of the system. Our contributions are: 1) Performing a throughout spectral analysis of tri-axis acceleration signals in order to get reliable road surface anomaly labels. 2) Comprehensive preprocessing of GPS and acceleration signals. 3) Proposing a speed dependence removal approach for feature extraction and demonstrating its positive effect in multiple feature sets for the road surface anomaly detection task. 4) A framework for visually analyzing the classifier predictions over the validation data and labels.

SUMMARYThis cross-sectional study aimed to investigate whether body fat distribution, physical activity levels and dietary intakes are associated with insomnia and/or obstructive sleep apnea among overweight middleaged men. Participants were 211 Finnish men aged 30-65 years. Among the 163 overweight or obese participants, 40 had insomnia only, 23 had obstructive sleep apnea only, 24 had comorbid insomnia and obstructive sleep apnea and 76 were without sleep disorder. The remaining 48 participants had normal weight without sleep disorder. Fat mass, levels of physical activity and diet were assessed by dual-energy X-ray densitometry, physical activity questionnaire and 3-day food diary, respectively. Among the overweight participants, we found that: (i) groups with sleep disorders had higher fat mass in trunk and android regions than the group without sleep disorder (P = 0.048-0.004); (ii) the insomnia-only group showed a lower level of leisure-time physical activity (436.9 versus 986.5 MET min week À1 , P = 0.009) and higher intake of saturated fatty acids (14.8 versus 12.7 E%, P = 0.011) than the group without sleep disorder; and (iii) the comorbid group had a lower level of leisure-time physical activity (344.4 versus 986.5 MET min week À1 , P = 0.007) and lower folate intake (118.9 versus 152.1 lg, P = 0.002) than the group without sleep disorder, which were independent of body mass index. The results suggest that central obesity is associated with insomnia and/or obstructive sleep apnea. In addition, low levels of leisure-time physical activity and poor dietary intakes are related to insomnia or comorbid insomnia and obstructive sleep apnea among overweight men. IN TROD UCTI ONSleep disorders such as insomnia and obstructive sleep apnea (OSA) have become a significant health issue worldwide. The prevalence of insomnia has been estimated as 6-7% among the US and European populations (Ohayon, 2002;Wittchen et al., 2011), while more than 30% of the population may suffer at least one symptom related to insomnia (Ohayon, 2002). In Finland, the prevalence of diagnosed insomnia is 11.7%, which is 1.5-2 times higher than other European countries (Ohayon and Partinen, 2002). OSA is another sleep disorder with increasing prevalence, which affects 3-17% American adults in different age and gender groups, and is most observed commonly among men from middle to old age (Peppard et al., 2013). The prevalence of OSA is approximately 8% among Finnish population (Kronholm et al., 2009). Insomnia and OSA also often exist as comorbidity (Luyster et al., 2010).An increasing number of studies have shown the association between obesity and sleep disorders. One study Sleep and body fat suggests that obese individuals are 50% more likely to suffer insomnia than participants of normal weight, thus obesity is regarded as a risk factor for insomnia (Singareddy et al., 2012). The association between obesity and OSA is more widely recognized (Punjabi, 2008). More than two-thirds of individuals with OSA are obese (Punjabi, 2008;Vgontzas et...

Visual mismatch negativity (vMMN), a component in event-related potentials (ERPs), can be elicited when rarely presented “deviant” facial expressions violate regularity formed by repeated “standard” faces. vMMN is observed as differential ERPs elicited between the deviant and standard faces. It is not clear, however, whether differential ERPs to rare emotional faces interspersed with repeated neutral ones reflect true vMMN (i.e., detection of regularity violation) or merely encoding of the emotional content in the faces. Furthermore, a face-sensitive N170 response, which reflects structural encoding of facial features, can be modulated by emotional expressions. Owing to its similar latency and scalp topography with vMMN, these two components are difficult to separate. We recorded ERPs to neutral, fearful, and happy faces in two different stimulus presentation conditions in adult humans. For the oddball condition group, frequently presented neutral expressions (p = 0.8) were rarely replaced by happy or fearful expressions (p = 0.1), whereas for the equiprobable condition group, fearful, happy, and neutral expressions were presented with equal probability (p = 0.33). Independent component analysis (ICA) revealed two prominent components in both stimulus conditions in the relevant latency range and scalp location. A component peaking at 130 ms post stimulus showed a difference in scalp topography between the oddball (bilateral) and the equiprobable (right-dominant) conditions. The other component, peaking at 170 ms post stimulus, showed no difference between the conditions. The bilateral component at the 130-ms latency in the oddball condition conforms to vMMN. Moreover, it was distinct from N170 which was modulated by the emotional expression only. The present results suggest that future studies on vMMN to facial expressions should take into account possible confounding effects caused by the differential processing of the emotional expressions as such.

The TC-based phase de-ambiguity is essential to prepare the SM phases. The SM phases provide a new post-ICA index for reliably identifying and suppressing the unwanted voxels.