Fuzzy Integral with Particle Swarm Optimization for a Motor-Imagery-Based Brain-Computer Interface

© 2016 IEEE. A brain-computer interface (BCI) system using electroencephalography signals provides a convenient means of communication between the human brain and a computer. Motor imagery (MI), in which motor actions are mentally rehearsed without engaging in actual physical execution, has been widely used as a major BCI approach. One robust algorithm that can successfully cope with the individual differences in MI-related rhythmic patterns is to create diverse ensemble classifiers using the subband common spatial pattern (SBCSP) method. To aggregate outputs of ensemble members, this study uses fuzzy integral with particle swarm optimization (PSO), which can regulate subject-specific parameters for the assignment of optimal confidence levels for classifiers. The proposed system combining SBCSP, fuzzy integral, and PSO exhibits robust performance for offline single-trial classification of MI and real-time control of a robotic arm using MI. This paper represents the first attempt to utilize fuzzy fusion technique to attack the individual differences problem of MI applications in real-world noisy environments. The results of this study demonstrate the practical feasibility of implementing the proposed method for real-world applications

A motor imagery based brain-computer interface system via swarm-optimized fuzzy integral and its application

© 2016 IEEE. A brain-computer interface (BCI) system provides a convenient means of communication between the human brain and a computer, which is applied not only to healthy people but also for people that suffer from motor neuron diseases (MNDs). Motor imagery (MI) is one well-known basis for designing Electroencephalography (EEG)-based real-life BCI systems. However, EEG signals are often contaminated with severe noise and various uncertainties, imprecise and incomplete information streams. Therefore, this study proposes spectrum ensemble based on swam-optimized fuzzy integral for integrating decisions from sub-band classifiers that are established by a sub-band common spatial pattern (SBCSP) method. Firstly, the SBCSP effectively extracts features from EEG signals, and thereby the multiple linear discriminant analysis (MLDA) is employed during a MI classification task. Subsequently, particle swarm optimization (PSO) is used to regulate the subject-specific parameters for assigning optimal confidence levels for classifiers used in the fuzzy integral during the fuzzy fusion stage of the proposed system. Moreover, BCI systems usually tend to have complex architectures, be bulky in size, and require time-consuming processing. To overcome this drawback, a wireless and wearable EEG measurement system is investigated in this study. Finally, in our experimental result, the proposed system is found to produce significant improvement in terms of the receiver operating characteristic (ROC) curve. Furthermore, we demonstrate that a robotic arm can be reliably controlled using the proposed BCI system. This paper presents novel insights regarding the possibility of using the proposed MI-based BCI system in real-life applications

The Discriminative Lexicon: A Unified Computational Model for the Lexicon and Lexical Processing in Comprehension and Production Grounded Not in (De)Composition but in Linear Discriminative Learning

© 2019 R. Harald Baayen et al. The discriminative lexicon is introduced as a mathematical and computational model of the mental lexicon. This novel theory is inspired by word and paradigm morphology but operationalizes the concept of proportional analogy using the mathematics of linear algebra. It embraces the discriminative perspective on language, rejecting the idea that words' meanings are compositional in the sense of Frege and Russell and arguing instead that the relation between form and meaning is fundamentally discriminative. The discriminative lexicon also incorporates the insight from machine learning that end-to-end modeling is much more effective than working with a cascade of models targeting individual subtasks. The computational engine at the heart of the discriminative lexicon is linear discriminative learning: simple linear networks are used for mapping form onto meaning and meaning onto form, without requiring the hierarchies of post-Bloomfieldian 'hidden' constructs such as phonemes, morphemes, and stems. We show that this novel model meets the criteria of accuracy (it properly recognizes words and produces words correctly), productivity (the model is remarkably successful in understanding and producing novel complex words), and predictivity (it correctly predicts a wide array of experimental phenomena in lexical processing). The discriminative lexicon does not make use of static representations that are stored in memory and that have to be accessed in comprehension and production. It replaces static representations by states of the cognitive system that arise dynamically as a consequence of external or internal stimuli. The discriminative lexicon brings together visual and auditory comprehension as well as speech production into an integrated dynamic system of coupled linear networks

Peak exercise capacity estimated from incremental shuttle walking test in patients with COPD: a methodological study

BACKGROUND: In patients with COPD, both laboratory exercise tests and field walking tests are used to assess physical performance. In laboratory tests, peak exercise capacity in watts (W peak) and/or peak oxygen uptake (VO(2 )peak) are assessed, whereas the performance on walking tests usually is expressed as distance walked. The aim of the study was to investigate the relationship between an incremental shuttle walking test (ISWT) and two laboratory cycle tests in order to assess whether W peak could be estimated from an ISWT. METHODS: Ninety-three patients with moderate or severe COPD performed an ISWT, an incremental cycle test (ICT) to measure W peak and a semi-steady-state cycle test with breath-by-breath gas exchange analysis (CPET) to measure VO(2 )peak. Routine equations for conversion between cycle tests were used to estimate W peak from measured VO(2 )peak (CPET). Conversion equation for estimation of W peak from ISWT was found by univariate regression. RESULTS: There was a significant correlation between W peak and distance walked on ISWT × body weight (r = 0.88, p < 0.0001). The agreement between W peak measured by ICT and estimated from ISWT was similar to the agreement between measured W peak (ICT) and W peak estimated from measured VO(2 )peak by CPET. CONCLUSION: Peak exercise capacity measured by an incremental cycle test could be estimated from an ISWT with similar accuracy as when estimated from peak oxygen uptake in patients with COPD

Matched sizes of activating and inhibitory receptor/ligand pairs are required for optimal signal integration by human Natural Killer cells

It has been suggested that receptor-ligand complexes segregate or co-localise within immune synapses according to their size, and this is important for receptor signaling. Here, we set out to test the importance of receptor-ligand complex dimensions for immune surveillance of target cells by human Natural Killer (NK) cells. NK cell activation is regulated by integrating signals from activating receptors, such as NKG2D, and inhibitory receptors, such as KIR2DL1. Elongating the NKG2D ligand MICA reduced its ability to trigger NK cell activation. Conversely, elongation of KIR2DL1 ligand HLA-C reduced its ability to inhibit NK cells. Whereas normal-sized HLA-C was most effective at inhibiting activation by normal-length MICA, only elongated HLA-C could inhibit activation by elongated MICA. Moreover, HLA-C and MICA that were matched in size co-localised, whereas HLA-C and MICA that were different in size were segregated. These results demonstrate that receptor-ligand dimensions are important in NK cell recognition, and suggest that optimal integration of activating and inhibitory receptor signals requires the receptor-ligand complexes to have similar dimensions

SNAI2/Slug promotes growth and invasion in human gliomas

<p>Abstract</p> <p>Background</p> <p>Numerous factors that contribute to malignant glioma invasion have been identified, but the upstream genes coordinating this process are poorly known.</p> <p>Methods</p> <p>To identify genes controlling glioma invasion, we used genome-wide mRNA expression profiles of primary human glioblastomas to develop an expression-based rank ordering of 30 transcription factors that have previously been implicated in the regulation of invasion and metastasis in cancer.</p> <p>Results</p> <p>Using this approach, we identified the oncogenic transcriptional repressor, <it>SNAI2</it>/Slug, among the upper tenth percentile of invasion-related transcription factors overexpressed in glioblastomas. <it>SNAI2 </it>mRNA expression correlated with histologic grade and invasive phenotype in primary human glioma specimens, and was induced by EGF receptor activation in human glioblastoma cells. Overexpression of <it>SNAI2/</it>Slug increased glioblastoma cell proliferation and invasion <it>in vitro </it>and promoted angiogenesis and glioblastoma growth <it>in vivo</it>. Importantly, knockdown of endogenous <it>SNAI2</it>/Slug in glioblastoma cells decreased invasion and increased survival in a mouse intracranial human glioblastoma transplantation model.</p> <p>Conclusion</p> <p>This genome-scale approach has thus identified <it>SNAI2</it>/Slug as a regulator of growth and invasion in human gliomas.</p

Risks of second primary cancer among patients with major histological types of lung cancers in both men and women

10.1038/sj.bjc.6605616British Journal of Cancer10271190-1195BJCA

Brain-Derived Neurotrophic Factor Ameliorates Brain Stem Cardiovascular Dysregulation during Experimental Temporal Lobe Status Epilepticus

Background: Status epilepticus (SE) is an acute, prolonged epileptic crisis with a mortality rate of 20–30%; the underlying mechanism is not completely understood. We assessed the hypothesis that brain stem cardiovascular dysregulation occurs during SE because of oxidative stress in rostral ventrolateral medulla (RVLM), a key nucleus of the baroreflex loop; to be ameliorated by brain-derived neurotrophic factor (BDNF) via an antioxidant action. Methodology/Principal Findings: In a clinically relevant experimental model of temporal lobe SE (TLSE) using Sprague-Dawley rats, sustained hippocampal seizure activity was accompanied by progressive hypotension that was preceded by a reduction in baroreflex-mediated sympathetic vasomotor tone; heart rate and baroreflex-mediated cardiac responses remained unaltered. Biochemical experiments further showed concurrent augmentation of superoxide anion, phosphorylated p47 phox subunit of NADPH oxidase and mRNA or protein levels of BDNF, tropomyosin receptor kinase B (TrkB), angiotensin AT1 receptor subtype (AT1R), nitric oxide synthase II (NOS II) or peroxynitrite in RVLM. Whereas pretreatment by microinjection bilaterally into RVLM of a superoxide dismutase mimetic (tempol), a specific antagonist of NADPH oxidase (apocynin) or an AT1R antagonist (losartan) blunted significantly the augmented superoxide anion or phosphorylated p47 phox subunit in RVLM, hypotension and the reduced baroreflex-mediated sympathetic vasomotor tone during experimental TLSE, pretreatment with a recombinant human TrkB-Fc fusion protein or an antisense bdn

Auditory stimulation of opera music induced prolongation of murine cardiac allograft survival and maintained generation of regulatory CD4+CD25+ cells

<p>Abstract</p> <p>Background</p> <p>Interactions between the immune response and brain functions such as olfactory, auditory, and visual sensations are likely. This study investigated the effect of sounds on alloimmune responses in a murine model of cardiac allograft transplantation.</p> <p>Methods</p> <p>Naïve CBA mice (H2^k) underwent transplantation of a C57BL/6 (B6, H2^b) heart and were exposed to one of three types of music--opera (<it>La Traviata</it>), classical (Mozart), and New Age (Enya)--or one of six different single sound frequencies, for 7 days. Additionally, we prepared two groups of CBA recipients with tympanic membrane perforation exposed to opera for 7 days and CBA recipients exposed to opera for 7 days before transplantation (pre-treatment). An adoptive transfer study was performed to determine whether regulatory cells were generated in allograft recipients. Immunohistochemical, cell-proliferation, cytokine, and flow cytometry assessments were also performed.</p> <p>Results</p> <p>CBA recipients of a B6 cardiac graft that were exposed to opera music and Mozart had significantly prolonged allograft survival (median survival times [MSTs], 26.5 and 20 days, respectively), whereas those exposed to a single sound frequency (100, 500, 1000, 5000, 10,000, or 20,000 Hz) or Enya did not (MSTs, 7.5, 8, 9, 8, 7.5, 8.5 and 11 days, respectively). Untreated, CBA mice with tympanic membrane perforations and CBA recipients exposed to opera for 7 days before transplantation (pre-treatment) rejected B6 cardiac grafts acutely (MSTs, 7, 8 and 8 days, respectively). Adoptive transfer of whole splenocytes, CD4⁺cells, or CD4⁺CD25⁺cells from opera-exposed primary allograft recipients resulted in significantly prolonged allograft survival in naive secondary recipients (MSTs, 36, 68, and > 100 days, respectively). Proliferation of splenocytes, interleukin (IL)-2 and interferon (IFN)-γ production was suppressed in opera-exposed mice, and production of IL-4 and IL-10 from opera-exposed transplant recipients increased compared to that from splenocytes of untreated recipients. Flow cytometry studies showed an increased CD4⁺CD25⁺Forkhead box P3 (Foxp3)⁺cell population in splenocytes from those mice.</p> <p>Conclusion</p> <p>Our findings indicate that exposure to opera music, such as La traviata, could affect such aspects of the peripheral immune response as generation of regulatory CD4⁺CD25⁺cells and up-regulation of anti-inflammatory cytokines, resulting in prolonged allograft survival.</p