Neural and Computational Principles of Real-World Sequence Processing

We are constantly processing sequential information in our day-to-day life, from listening to a piece of music (processing a stream of notes), watching a movie (processing a series of scenes), to having conversations with people around us (processing a stream of syllables, words, and sentences). What are the neural and computational principles underlying this ubiquitous cognitive process? In this thesis, I first review the background and prior studies regarding the neural and computational mechanisms of real-life sequence processing and present our research questions. I then present four research projects to answer those questions: By combining neuroimaging data analysis and computational modeling, I discovered the neural phenomena of integrating and forgetting temporal information during naturalistic sequence processing in the human cerebral cortex. Furthermore, I identified computational principles (e.g., hierarchical architecture) and processes (e.g., dynamical context gating) which can help to explain the neural state changes observed during naturalistic processing. These neural and computational findings not only validate the existing components of hierarchical temporal integration theory, but also rule out alternative models, and propose important new elements of the theory, including context gating at event boundaries. I next explored the computations for natural language processing in brains and machines, by (1) applying our neuroscience-inspired methods to examine the timescale and functional organization of neural network language models, thereby revealing their own architecture for processing information over multiple timescales; and by (2) investigating the context and entity representations in two neural networks with brain-inspired architectures, thereby revealing a gap between brain-inspired and performance-optimized architectures. Finally, I discuss the positions and contributions of our findings in the field and some future directions

Assessment of Chitosan-Affected Metabolic Response by Peroxisome Proliferator-Activated Receptor Bioluminescent Imaging-Guided Transcriptomic Analysis

Chitosan has been widely used in food industry as a weight-loss aid and a cholesterol-lowering agent. Previous studies have shown that chitosan affects metabolic responses and contributes to anti-diabetic, hypocholesteremic, and blood glucose-lowering effects; however, the in vivo targeting sites and mechanisms of chitosan remain to be clarified. In this study, we constructed transgenic mice, which carried the luciferase genes driven by peroxisome proliferator-activated receptor (PPAR), a key regulator of fatty acid and glucose metabolism. Bioluminescent imaging of PPAR transgenic mice was applied to report the organs that chitosan acted on, and gene expression profiles of chitosan-targeted organs were further analyzed to elucidate the mechanisms of chitosan. Bioluminescent imaging showed that constitutive PPAR activities were detected in brain and gastrointestinal tract. Administration of chitosan significantly activated the PPAR activities in brain and stomach. Microarray analysis of brain and stomach showed that several pathways involved in lipid and glucose metabolism were regulated by chitosan. Moreover, the expression levels of metabolism-associated genes like apolipoprotein B (apoB) and ghrelin genes were down-regulated by chitosan. In conclusion, these findings suggested the feasibility of PPAR bioluminescent imaging-guided transcriptomic analysis on the evaluation of chitosan-affected metabolic responses in vivo. Moreover, we newly identified that downregulated expression of apoB and ghrelin genes were novel mechanisms for chitosan-affected metabolic responses in vivo

Observational connection of non-thermal X-ray emission from pulsars with their timing properties and thermal emission

The origin and radiation mechanisms of high energy emissions from pulsars have remained mysterious since their discovery. Here we report, based on a sample of 68 pulsars, observational connection of non-thermal X-ray emissions from pulsars with their timing properties and thermal emissions, which may provide some constraints on theoretical modeling. Besides strong correlations with the spin-down power $\dot{E}$ and the magnetic field strength at the light cylinder $B_{\rm lc}$, the non-thermal X-ray luminosity in 0.5 - 8 keV, $L_{\rm p}$, represented by the power-law component in the spectral model, is found to be strongly correlated with the highest possible electric field strength in the polar gap, $E_{\rm pc}$, of the pulsar. The spectral power index $\Gamma_{\rm p}$ of that power-law component is also found, for the first time in the literature, to strongly correlate with $\dot{E}$, $B_{\rm lc}$ and $E_{\rm pc}$, thanks to the large sample. In addition, we found that $L_{\rm p}$ can be well described by $L_{\rm p}\propto T^{5.96\pm 0.64}R^{2.24\pm 0.18}$, where $T$ and $R$ are the surface temperature and the emitting-region radius of the surface thermal emission, represented by the black-body component in the spectral model. $\Gamma_{\rm p}$, on the other hand, can be well described only when timing variables are included, and the relation is $\Gamma_{\rm p} = \log(T^{-5.8\pm 1.93}R^{-2.29\pm 0.85}P^{-1.19\pm 0.88}\dot{P}^{0.94\pm 0.44})$ plus a constant. These relations strongly suggest the existence of connections between surface thermal emission and electron-positron pair production in pulsar magnetospheres.Comment: 13 pages, 11 figures, accepted by MNRA

MAEEG: Masked Auto-encoder for EEG Representation Learning

Decoding information from bio-signals such as EEG, using machine learning has been a challenge due to the small data-sets and difficulty to obtain labels. We propose a reconstruction-based self-supervised learning model, the masked auto-encoder for EEG (MAEEG), for learning EEG representations by learning to reconstruct the masked EEG features using a transformer architecture. We found that MAEEG can learn representations that significantly improve sleep stage classification (~5% accuracy increase) when only a small number of labels are given. We also found that input sample lengths and different ways of masking during reconstruction-based SSL pretraining have a huge effect on downstream model performance. Specifically, learning to reconstruct a larger proportion and more concentrated masked signal results in better performance on sleep classification. Our findings provide insight into how reconstruction-based SSL could help representation learning for EEG.Comment: 10 pages, 5 figures, accepted by Workshop on Learning from Time Series for Health, NeurIPS2022 as poster presentatio

Regulation of clpQ+Y+ (hslV+U+) Gene Expression in Escherichia coli

The Escherichia coli ClpYQ (HslUV) complex is an ATP-dependent protease, and the clpQ+Y+ (hslV+U+) operon encodes two heat shock proteins, ClpQ and ClpY, respectively. The transcriptional (op) or translational (pr) clpQ+::lacZ fusion gene was constructed, with the clpQ+Y+ promoter fused to a lacZ reporter gene. The clpQ+::lacZ (op or pr) fusion gene was each crossed into lambda phage. The λclpQ+::lacZ+ (op), a transcriptional fusion gene, was used to form lysogens in the wild-type, rpoH or/and rpoS mutants. Upon shifting the temperature up from 30 °C to 42 °C, the wild-type λclpQ+::lacZ+ (op) demonstrates an increased β-galactosidase (βGal) activity. However, the βGal activity of clpQ+::lacZ+ (op) was decreased in the rpoH and rpoH rpoS mutants but not in the rpoS mutant. The levels of clpQ+::lacZ+ mRNA transcripts correlated well to their βGal activity. Similarly, the expression of the clpQ+::lacZ+ gene fusion was nearly identical to the clpQ+Y+ transcript under the in vivo condition. The clpQm1::lacZ+, containing a point mutation in the -10 promoter region for RpoH binding, showed decreased βGal activity, independent of activation by RpoH. We conclude that RpoH itself regulates clpQ+Y+ gene expression. In addition, the clpQ+Y+ message carries a conserved 71 bp at the 5’ untranslated region (5’UTR) that is predicted to form the stem-loop structure by analysis of its RNA secondary structure. The clpQm2Δ40::lacZ+, with a 40 bp deletion in the 5’UTR, showed a decreased βGal activity. In addition, from our results, it is suggested that this stem-loop structure is necessary for the stability of the clpQ+Y+ message

Conserved charged amino acid residues in the extracellular region of sodium/iodide symporter are critical for iodide transport activity

<p>Abstract</p> <p>Background</p> <p>Sodium/iodide symporter (NIS) mediates the active transport and accumulation of iodide from the blood into the thyroid gland. His-226 located in the extracellular region of NIS has been demonstrated to be critical for iodide transport in our previous study. The conserved charged amino acid residues in the extracellular region of NIS were therefore characterized in this study.</p> <p>Methods</p> <p>Fourteen charged residues (Arg-9, Glu-79, Arg-82, Lys-86, Asp-163, His-226, Arg-228, Asp-233, Asp-237, Arg-239, Arg-241, Asp-311, Asp-322, and Asp-331) were replaced by alanine. Iodide uptake abilities of mutants were evaluated by steady-state and kinetic analysis. The three-dimensional comparative protein structure of NIS was further modeled using sodium/glucose transporter as the reference protein.</p> <p>Results</p> <p>All the NIS mutants were expressed normally in the cells and targeted correctly to the plasma membrane. However, these mutants, except R9A, displayed severe defects on the iodide uptake. Further kinetic analysis revealed that mutations at conserved positively charged amino acid residues in the extracellular region of NIS led to decrease NIS-mediated iodide uptake activity by reducing the maximal rate of iodide transport, while mutations at conserved negatively charged residues led to decrease iodide transport by increasing dissociation between NIS mutants and iodide.</p> <p>Conclusions</p> <p>This is the first report characterizing thoroughly the functional significance of conserved charged amino acid residues in the extracellular region of NIS. Our data suggested that conserved charged amino acid residues, except Arg-9, in the extracellular region of NIS were critical for iodide transport.</p

Deer Antler Extract Improves Fatigue Effect through Altering the Expression of Genes Related to Muscle Strength in Skeletal Muscle of Mice

Deer antler is a well-known traditional Chinese medicine used in Asian countries for the tonic and the improvement of aging symptoms. The present study was designed to investigate the antifatigue effect and mechanism of Formosan sambar deer tip antler extract (FSDTAE). The swimming times to exhaustion of mice administered FSDTAE (8.2 mg/day) for 28 days were apparently longer than those of the vehicle-treated mice in forced swim test. However, the indicators of fatigue, such as the reduction in glucose level and the increases in blood urea nitrogen and lactic acid levels, were not significantly inhibited by FSDTAE. Therefore, microarray analysis was further used to examine the anti-fatigue mechanism of FSDTAE. We selected genes with fold changes >2 or <−2 in skeletal muscle for pathway analysis. FSDTAE-affected genes were involved in 9 different signaling pathways, such as GnRH signaling pathway and insulin signaling pathway. All of the significantly expressed genes were classified into 8 different categories by their functions. The most enriched category was muscular system, and 6 upregulated genes, such as troponin I, troponin T1, cysteine and glycine-rich protein 2, myosin heavy polypeptide 7, tropomyosin 2, and myomesin family member 3, were responsible for the development and contraction of muscle. Real-time PCR analysis indicated that FSDTAE increased troponins mRNA expression in skeletal muscle. In conclusion, our findings suggested that FSDTAE might increase the muscle strength through the upregulation of genes responsible for muscle contraction and consequently exhibited the anti-fatigue effect in mice