Top-Down Control of Motor Cortex Ensembles by Dorsomedial Prefrontal Cortex

SummaryDorsomedial prefrontal cortex is critical for the temporal control of behavior. Dorsomedial prefrontal cortex might alter neuronal activity in areas such as motor cortex to inhibit temporally inappropriate responses. We tested this hypothesis by recording from neuronal ensembles in rodent dorsomedial prefrontal cortex during a delayed-response task. One-third of dorsomedial prefrontal neurons were significantly modulated during the delay period. The activity of many of these neurons was predictive of premature responding. We then reversibly inactivated dorsomedial prefrontal cortex while recording ensemble activity in motor cortex. Inactivation of dorsomedial prefrontal cortex reduced delay-related firing, but not response-related firing, in motor cortex. Finally, we made simultaneous recordings in dorsomedial prefrontal cortex and motor cortex and found strong delay-related temporal correlations between neurons in the two cortical areas. These data suggest that functional interactions between dorsomedial prefrontal cortex and motor cortex might serve as a top-down control signal that inhibits inappropriate responding

GFRP - FAILURE CHARACTERISTICS ANALYSIS

The objective of this paper is to predict the ultimate failure load and also is to characterize the failure modes in GFRP composite coupons using Multi linear regression. IBM SSPS20 version is used to predict the ultimate failure load using Multi linear regression with failure loads as dependent variable and the load range of 10kg each and its corresponding hits as independent variable. The three point bending test was conducted on the GFRP composite coupons till failure of the GFRP composite coupons. Based on the effect of various failure modes the ultimate failures of the specimen were also predicted by means of multi linear regression method. Â

Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses

Spiking neural networks (SNN) are artificial computational models that have been inspired by the brain's ability to naturally encode and process information in the time domain. The added temporal dimension is believed to render them more computationally efficient than the conventional artificial neural networks, though their full computational capabilities are yet to be explored. Recently, computational memory architectures based on non-volatile memory crossbar arrays have shown great promise to implement parallel computations in artificial and spiking neural networks. In this work, we experimentally demonstrate for the first time, the feasibility to realize high-performance event-driven in-situ supervised learning systems using nanoscale and stochastic phase-change synapses. Our SNN is trained to recognize audio signals of alphabets encoded using spikes in the time domain and to generate spike trains at precise time instances to represent the pixel intensities of their corresponding images. Moreover, with a statistical model capturing the experimental behavior of the devices, we investigate architectural and systems-level solutions for improving the training and inference performance of our computational memory-based system. Combining the computational potential of supervised SNNs with the parallel compute power of computational memory, the work paves the way for next-generation of efficient brain-inspired systems

Generation of Test Vectors for Sequential Cell Verification

For Application Specific Integrated Circuits (ASIC) and System-on-Chip (SOC) designs, Cell - Based Design (CBD) is the most prevalent practice as it guarantees a shorter design cycle, minimizes errors and is easier to maintain. In modern ASIC design, standard cell methodology is practiced with sizable libraries of cells, each containing multiple implementations of the same logic functionality, in order to give the designer differing options based on area, speed or power consumption. For such library cells, thorough verification of functionality and timing is crucial for the overall success of the chip, as even a small error can prove fatal due to the repeated use of the cell in the design. Both formal and simulation based methods are being used in the industry for cell verification. We propose a method using the latter approach that generates an optimized set of test vectors for verification of sequential cells, which are guaranteed to give complete Single Input Change transition coverage with minimal redundancy. Knowledge of the cell functionality by means of the State Table is the only prerequisite of this procedure

Effects of enteropathogenic bacteria & lactobacilli on chemokine secretion & Toll like receptor gene expression in two human colonic epithelial cell lines

Background & objectives: The intestinal epithelium is part of the innate immune system responding to contact with pathogenic or commensal bacteria. The objective of this study was to compare innate responses of intestinal epithelial cell lines to pathogenic bacteria and to lactobacilli. Methods: Two human intestinal epithelial cell lines, HT29 (enterocyte-like) and T84 (crypt-like), were exposed to pathogenic bacteria representative of non invasive (Vibrio cholerae O1 and O139), adherent (enterohaemorrhagic Escherichia coli, EHEC) or invasive (Salmonella Typhimurium and Shigella flexneri) phenotypes and to non pathogenic Lactobacillus rhamnosus GG or Lactobacillus plantarum. Interleukin-8 (IL-8) was measured in culture supernatant by ELISA, while mRNA from cells was subjected to quantitative reverse transcriptase PCR for several other chemokines (CXCL1, CCL5 and CXCL5) and for Toll-like receptors (TLR) 2, 4, 5 and 9. Results: V. cholerae, S. Typhimurium, S. flexneri and EHEC induced IL-8 secretion from epithelial cells into the medium. Salmonella, Shigella and EHEC, but not V. cholerae, significantly increased mRNA expression of CXCL1. None of the pathogens induced CCL5 or CXCL5. Salmonella and Vibrio significantly increased TLR4 expression, while Vibrio and EHEC decreased TLR5 expression. EHEC also decreased TLR9 expression. Lactobacilli attenuated the IL-8 response of the cell lines to V. cholerae, Salmonella, and EHEC but did not significantly change the IL-8 response to Shigella. Interpretation amp; conclusions: Distinct patterns of epithelial cell chemokine responses were induced by the bacterial pathogens studied and these were modulated by commensal lactobacilli. Alterations in TLR expression by these pathogens are likely to be important in pathogenesis

Effective Continued Fraction Dimension versus Effective Hausdorff Dimension of Reals

We establish that constructive continued fraction dimension originally defined using $s$-gales is robust, but surprisingly, that the effective continued fraction dimension and effective (base-$b$) Hausdorff dimension of the same real can be unequal in general. We initially provide an equivalent characterization of continued fraction dimension using Kolmogorov complexity. In the process, we construct an optimal lower semi-computable $s$-gale for continued fractions. We also prove new bounds on the Lebesgue measure of continued fraction cylinders, which may be of independent interest. We apply these bounds to reveal an unexpected behavior of continued fraction dimension. It is known that feasible dimension is invariant with respect to base conversion. We also know that Martin-L\"of randomness and computable randomness are invariant not only with respect to base conversion, but also with respect to the continued fraction representation. In contrast, for any $0 < \varepsilon < 0.5$, we prove the existence of a real whose effective Hausdorff dimension is less than $\varepsilon$, but whose effective continued fraction dimension is greater than or equal to $0.5$. This phenomenon is related to the ``non-faithfulness'' of certain families of covers, investigated by Peres and Torbin and by Albeverio, Ivanenko, Lebid and Torbin. We also establish that for any real, the constructive Hausdorff dimension is at most its effective continued fraction dimension