Dynamics of Neural Networks with Continuous Attractors

We investigate the dynamics of continuous attractor neural networks (CANNs). Due to the translational invariance of their neuronal interactions, CANNs can hold a continuous family of stationary states. We systematically explore how their neutral stability facilitates the tracking performance of a CANN, which is believed to have wide applications in brain functions. We develop a perturbative approach that utilizes the dominant movement of the network stationary states in the state space. We quantify the distortions of the bump shape during tracking, and study their effects on the tracking performance. Results are obtained on the maximum speed for a moving stimulus to be trackable, and the reaction time to catch up an abrupt change in stimulus.Comment: 6 pages, 7 figures with 4 caption

Variation in the Response of Three Different Pinus Radiata Kraft Pulps to Xylanase Treatments

Two xylanase preparations (Pulpzyme HC and Xylanasc E) were assessed for their ability to enhance the refining properties of three different Pinus radiata kraft pulps. Both preparations selectively solubilized a significant proportion of the available xylan; however, xylanase E proved to be more aggressive, regardless of the pulp type. The selective removal of pulp xylan improved pulp beatability by increasing the apparent densities of the resultant handsheets over their corresponding controls. There were, however, variations in the response of the different pulp types, with an unbleached kappa 70 pulp showing the greatest improvement in sheet densification, as compared to an isothermal-cooked (kappa 33) and a fully bleached pulp. In general, xylanase treatments improved tear strength at a given density without significant loss in tensile strength and intrinsic fiber strength. These results suggest that xylanase treatments may be a means of enhancing the collapsibility/flexibility of certain kraft fibers while maintaining intrinsic strength

A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks

Understanding how the dynamics of a neural network is shaped by the network structure, and consequently how the network structure facilitates the functions implemented by the neural system, is at the core of using mathematical models to elucidate brain functions. This study investigates the tracking dynamics of continuous attractor neural networks (CANNs). Due to the translational invariance of neuronal recurrent interactions, CANNs can hold a continuous family of stationary states. They form a continuous manifold in which the neural system is neutrally stable. We systematically explore how this property facilitates the tracking performance of a CANN, which is believed to have clear correspondence with brain functions. By using the wave functions of the quantum harmonic oscillator as the basis, we demonstrate how the dynamics of a CANN is decomposed into different motion modes, corresponding to distortions in the amplitude, position, width or skewness of the network state. We then develop a perturbative approach that utilizes the dominating movement of the network's stationary states in the state space. This method allows us to approximate the network dynamics up to an arbitrary accuracy depending on the order of perturbation used. We quantify the distortions of a Gaussian bump during tracking, and study their effects on the tracking performance. Results are obtained on the maximum speed for a moving stimulus to be trackable and the reaction time for the network to catch up with an abrupt change in the stimulus.Comment: 43 pages, 10 figure

Dynamical Synapses Enhance Neural Information Processing: Gracefulness, Accuracy and Mobility

Experimental data have revealed that neuronal connection efficacy exhibits two forms of short-term plasticity, namely, short-term depression (STD) and short-term facilitation (STF). They have time constants residing between fast neural signaling and rapid learning, and may serve as substrates for neural systems manipulating temporal information on relevant time scales. The present study investigates the impact of STD and STF on the dynamics of continuous attractor neural networks (CANNs) and their potential roles in neural information processing. We find that STD endows the network with slow-decaying plateau behaviors-the network that is initially being stimulated to an active state decays to a silent state very slowly on the time scale of STD rather than on the time scale of neural signaling. This provides a mechanism for neural systems to hold sensory memory easily and shut off persistent activities gracefully. With STF, we find that the network can hold a memory trace of external inputs in the facilitated neuronal interactions, which provides a way to stabilize the network response to noisy inputs, leading to improved accuracy in population decoding. Furthermore, we find that STD increases the mobility of the network states. The increased mobility enhances the tracking performance of the network in response to time-varying stimuli, leading to anticipative neural responses. In general, we find that STD and STP tend to have opposite effects on network dynamics and complementary computational advantages, suggesting that the brain may employ a strategy of weighting them differentially depending on the computational purpose.Comment: 40 pages, 17 figure

Constraints from Solar and Reactor Neutrinos on Unparticle Long-Range Forces

We have investigated the impact of long-range forces induced by unparticle operators of scalar, vector and tensor nature coupled to fermions in the interpretation of solar neutrinos and KamLAND data. If the unparticle couplings to the neutrinos are mildly non-universal, such long-range forces will not factorize out in the neutrino flavour evolution. As a consequence large deviations from the observed standard matter-induced oscillation pattern for solar neutrinos would be generated. In this case, severe limits can be set on the infrared fix point scale, Lambda_u, and the new physics scale, M, as a function of the ultraviolet (d_UV) and anomalous (d) dimension of the unparticle operator. For a scalar unparticle, for instance, assuming the non-universality of the lepton couplings to unparticles to be of the order of a few per mil we find that, for d_UV=3 and d=1.1, M is constrained to be M > O(10^9) TeV (M > O(10^10) TeV) if Lambda_u= 1 TeV (10 TeV). For given values of Lambda_u and d, the corresponding bounds on M for vector [tensor] unparticles are approximately 100 [3/Sqrt(Lambda_u/TeV)] times those for the scalar case. Conversely, these results can be translated into severe constraints on universality violation of the fermion couplings to unparticle operators with scales which can be accessible at future colliders.Comment: 13 pages, 3 figures. Minor changes due to precision in numerical factors and correction in figure labels. References added. Conclusions remain unchange

Constraints on Astro-unparticle Physics from SN 1987A

SN 1987A observations have been used to place constraints on the interactions between standard model particles and unparticles. In this study we calculate the energy loss from the supernovae core through scalar, pseudo scalar, vector, pseudo vector unparticle emission from nuclear bremsstrahlung for degenerate nuclear matter interacting through one pion exchange. In order to examine the constraints on $d_{\cal U}=1$ we considered the emission of scalar, pseudo scalar, vector, pseudo vector and tensor through the pair annihilation process $e^+e^-\to {\cal U} \gamma$. In addition we have re-examined other pair annihilation processes. The most stringent bounds on the dimensionless coupling constants for $d_{\cal U} =1$ and $\Lambda_{\cal U}= m_Z$ are obtained from nuclear bremsstrahlung process for the pseudo scalar and pseudo-vector couplings $\bigl|\lambda^{\cal P}_{0,1}\bigr|\leq 4\times 10^{-11}$ and for tensor interaction, the best limit on dimensionless coupling is obtained from $e^+ e^-\to {\cal U} \gamma$ and we get $\bigl|\lambda^{\cal T}\bigr| \leq 6\times 10^{-6}$.Comment: 12 pages, 2 postscript figure

Vedolizumab for the Treatment of Adults with Moderate-to-Severe Active Ulcerative Colitis: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.

As part of its single technology appraisal (STA) process, the National Institute for Health and Care Excellence (NICE) invited the manufacturer of vedolizumab (Takeda UK) to submit evidence of the clinical effectiveness and cost effectiveness of vedolizumab for the treatment of patients with moderate-to-severe active ulcerative colitis (UC). The Evidence Review Group (ERG) produced a critical review of the evidence for the clinical effectiveness and cost effectiveness of the technology, based upon the company's submission to NICE. The evidence was derived mainly from GEMINI 1, a Phase 3, multicentre, randomised, double-blinded, placebo-controlled study of the induction and maintenance of clinical response and remission by vedolizumab (MLN0002) in patients with moderate-to-severe active UC with an inadequate response to, loss of response to or intolerance of conventional therapy or anti-tumour necrosis factor (TNF)-α. The clinical evidence showed that vedolizumab performed significantly better than placebo in both the induction and maintenance phases. In the post hoc subgroup analyses in patients with or without prior anti-TNF-α therapy, vedolizumab performed better then placebo (p value not reported). In addition, a greater improvement in health-related quality of life was observed in patients treated with vedolizumab, and the frequency and types of adverse events were similar in the vedolizumab and placebo groups, but the evidence was limited to short-term follow-up. There were a number of limitations and uncertainties in the clinical evidence base, which warrants caution in its interpretation-in particular, the post hoc subgroup analyses and high dropout rates in the maintenance phase of GEMINI 1. The company also presented a network meta-analysis of vedolizumab versus other biologic therapies indicated for moderate-to-severe UC. However, the ERG considered that the results presented may have underestimated the uncertainty in treatment effects, since fixed-effects models were used, despite clear evidence of heterogeneity among the trials included in the network. Results from the company's economic evaluation (which included price reductions to reflect the proposed patient access scheme for vedolizumab) suggested that vedolizumab is the most effective option compared with surgery and conventional therapy in the following three populations: (1) a mixed intention-to-treat population, including patients who have previously received anti-TNF-α therapy and those who are anti-TNF-α naïve; (2) patients who are anti-TNF-α naïve only; and (3) patients who have previously failed anti-TNF-α therapy only. The ERG concluded that the results of the company's economic evaluation could not be considered robust, because of errors in model implementation, omission of relevant comparators, deviations from the NICE reference case and questionable model assumptions. The ERG amended the company's model and demonstrated that vedolizumab is expected to be dominated by surgery in all three populations