EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features

Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first time, it is applied to BCI regression problems, an important category of BCI applications. More specifically, we propose a new feature extraction approach for Electroencephalogram (EEG) based BCI regression problems: a spatial filter is first used to increase the signal quality of the EEG trials and also to reduce the dimensionality of the covariance matrices, and then Riemannian tangent space features are extracted. We validate the performance of the proposed approach in reaction time estimation from EEG signals measured in a large-scale sustained-attention psychomotor vigilance task, and show that compared with the traditional powerband features, the tangent space features can reduce the root mean square estimation error by 4.30-8.30%, and increase the estimation correlation coefficient by 6.59-11.13%.Comment: arXiv admin note: text overlap with arXiv:1702.0291

Spike Rate and Spike Timing Contributions to Coding Taste Quality Information in Rat Periphery

There is emerging evidence that individual sensory neurons in the rodent brain rely on temporal features of the discharge pattern to code differences in taste quality information. In contrast, investigations of individual sensory neurons in the periphery have focused on analysis of spike rate and mostly disregarded spike timing as a taste quality coding mechanism. The purpose of this work was to determine the contribution of spike timing to taste quality coding by rat geniculate ganglion neurons using computational methods that have been applied successfully in other systems. We recorded the discharge patterns of narrowly tuned and broadly tuned neurons in the rat geniculate ganglion to representatives of the five basic taste qualities. We used mutual information to determine significant responses and the van Rossum metric to characterize their temporal features. While our findings show that spike timing contributes a significant part of the message, spike rate contributes the largest portion of the message relayed by afferent neurons from rat fungiform taste buds to the brain. Thus, spike rate and spike timing together are more effective than spike rate alone in coding stimulus quality information to a single basic taste in the periphery for both narrowly tuned specialist and broadly tuned generalist neurons

Rating-based Reinforcement Learning

This paper develops a novel rating-based reinforcement learning approach that uses human ratings to obtain human guidance in reinforcement learning. Different from the existing preference-based and ranking-based reinforcement learning paradigms, based on human relative preferences over sample pairs, the proposed rating-based reinforcement learning approach is based on human evaluation of individual trajectories without relative comparisons between sample pairs. The rating-based reinforcement learning approach builds on a new prediction model for human ratings and a novel multi-class loss function. We conduct several experimental studies based on synthetic ratings and real human ratings to evaluate the effectiveness and benefits of the new rating-based reinforcement learning approach.Comment: This is an extended version of the paper "Rating-based Reinforcement Learning" accepted to the 38th Annual AAAI Conference on Artificial Intelligenc

CD4 receptor is a key determinant of divergent HIV-1 sensing by plasmacytoid dendritic cells

Plasmacytoid dendritic cells (pDC) are innate immune cells that sense viral nucleic acids through endosomal Toll-like receptor (TLR) 7/9 to produce type I interferon (IFN) and to differentiate into potent antigen presenting cells (APC). Engagement of TLR7/9 in early endosomes appears to trigger the IRF7 pathway for IFN production whereas engagement in lysosomes seems to trigger the NF-κB pathway for maturation into APC. We showed previously that HIV-1 (HIV) localizes predominantly to early endosomes, not lysosomes, and mainly stimulate IRF7 rather than NF-κB signaling pathways in pDC. This divergent signaling may contribute to disease progression through production of pro-apoptotic and pro-inflammatory IFN and inadequate maturation of pDCs. We now demonstrate that HIV virions may be re-directed to lysosomes for NF-κB signaling by either pseudotyping HIV with influenza hemagglutinin envelope or modification of CD4 mediated-intracellular trafficking. These data suggest that HIV envelope-CD4 receptor interactions drive pDC activation toward an immature IFN producing phenotype rather than differentiation into a mature dendritic cell phenotype

Risk stratification of smoldering multiple myeloma: predictive value of free light chains and group-based trajectory modeling.

We investigated the predictive role for serum free light chain ratio (FLCr) ≥100, bone marrow plasma cell (BMPC) ≥60%, and evolving biomarkers through group-based trajectory modeling (GBTM) as high-risk defining events in 273 smoldering multiple myeloma (SMM) patients with a median follow-up of 74 months. FLCr ≥100 was confirmed as a marker for high-risk progression with a median time to progression (TTP) of 40 months with a 44% risk of progression of disease (PD) at 2 years; however, 44% of FLCr ≥100 also did not progress during follow-up. For patients with BMPC ≥60% by core biopsy, the median TTP was 31 months with a 2-year PD of 41%. GBTM established high-risk trajectories for evolving hemoglobin (eHb; characterized as a 1.57 g/dL decrease in hemoglobin), evolving m-protein (eMP; 64% increase in m-protein), and evolving differences in FLC (edFLC; 169% increase in dFLC) within 1 year of diagnosis associated with a decreased median TTP and an increased 2 year rate of PD. Of all the variables examined, we identify a model where immunoparesis, eHb, eMP, and edFLC were significant predictors for ultra-high-risk progression with a median TTP of only 13 months with 3 or more variables present. Our results not only confirm a more modest 2 year PD associated with FLCr ≥100 and BMPC ≥60 but also suggest that eHb, eMP, and edFLC may help identify an ultra-high-risk SMM group

Eccentric muscle challenge shows osteopontin polymorphism modulation of muscle damage.

A promoter polymorphism of the osteopontin (OPN) gene (rs28357094) has been associated with multiple inflammatory states, severity of Duchenne muscular dystrophy (DMD) and muscle size in healthy young adults. We sought to define the mechanism of action of the polymorphism, using allele-specific in vitroreporter assays in muscle cells, and a genotype-stratified intervention in healthy controls. In vitro reporter constructs showed the G allele to respond to estrogen treatment, whereas the T allele showed no transcriptional response. Young adult volunteers (n = 187) were enrolled into a baseline study, and subjects with specific rs28357094 genotypes enrolled into an eccentric muscle challenge intervention [n = 3 TT; n = 3 GG/GT (dominant inheritance model)]. Female volunteers carrying the G allele showed significantly greater inflammation and increased muscle volume change as determined by magnetic resonance imaging T1- and T2-weighted images after eccentric challenge, as well as greater decrement in biceps muscle force. Our data suggest a model where the G allele enables enhanced activities of upstream enhancer elements due to loss of Sp1 binding at the polymorphic site. This results in significantly greater expression of the pro-inflammatory OPN cytokine during tissue remodeling in response to challenge in G allele carriers, promoting muscle hypertrophy in normal females, but increased damage in DMD patients

Depth versus surface: A critical review of subdural and depth electrodes in intracranial electroencephalographic studies

Intracranial electroencephalographic (IEEG) recording, using subdural electrodes (SDEs) and stereoelectroencephalography (SEEG), plays a pivotal role in localizing the epileptogenic zone (EZ). SDEs, employed for superficial cortical seizure foci localization, provide information on two-dimensional seizure onset and propagation. In contrast, SEEG, with its three-dimensional sampling, allows exploration of deep brain structures, sulcal folds, and bihemispheric networks. SEEG offers the advantages of fewer complications, better tolerability, and coverage of sulci. Although both modalities allow electrical stimulation, SDE mapping can tessellate cortical gyri, providing the opportunity for a tailored resection. With SEEG, both superficial gyri and deep sulci can be stimulated, and there is a lower risk of afterdischarges and stimulation-induced seizures. Most systematic reviews and meta-analyses have addressed the comparative effectiveness of SDEs and SEEG in localizing the EZ and achieving seizure freedom, although discrepancies persist in the literature. The combination of SDEs and SEEG could potentially overcome the limitations inherent to each technique individually, better delineating seizure foci. This review describes the strengths and limitations of SDE and SEEG recordings, highlighting their unique indications in seizure localization, as evidenced by recent publications. Addressing controversies in the perceived usefulness of the two techniques offers insights that can aid in selecting the most suitable IEEG in clinical practice

Energy partition of seismic coda waves in layered media: theory and application to Pinyon Flats Observatory

We have studied the partition of shear, compressional and kinetic energies in the coda of ten earthquakes recorded on a dense array, located at Pinyon Flats Observatory (PFO), California. We observe a clear stabilization of the shear to compressional ($W^s/W^p$) energy ratio in the coda, with an average value of about 2.8. The ratio between the vertical and horizontal kinetic energies ($V^2/H^2$) can be measured from 5 to 25Hz and shows an abrupt transitionfrom 0.1 in the 5-10Hz band, to about 0.8 in the 15-25Hz band. These measured values are in sharp contrast with the theoretical prediction for equipartitioned elastic waves in a homogeneous half-space. To explain these observations, we have developed a theory of equipartition in a layered elastic half-space. Using a rigorous spectral decomposition of the elastic wave equation, we define equipartition as a white noise distributed over the complete set of eigenfunctions. The theory predicts that close to the resonance frequency of a low-velocity layer, the ratio between shear and compressional energies strongly decreases. Using a detailed model of the subsurface at PFO, this conterintuitive result is found to be in good qualitative and quantitative agreement with the observations