Robustness and Enhancement of Neural Synchronization by Activity-Dependent Coupling

We study the synchronization of two model neurons coupled through a synapse having an activity-dependent strength. Our synapse follows the rules of Spike-Timing Dependent Plasticity (STDP). We show that this plasticity of the coupling between neurons produces enlarged frequency locking zones and results in synchronization that is more rapid and much more robust against noise than classical synchronization arising from connections with constant strength. We also present a simple discrete map model that demonstrates the generality of the phenomenon.Comment: 4 pages, accepted for publication in PR

Bumps and rings in a two-dimensional neural field: splitting and rotational instabilities

In this paper we consider instabilities of localised solutions in planar neural field firing rate models of Wilson-Cowan or Amari type. Importantly we show that angular perturbations can destabilise spatially localised solutions. For a scalar model with Heaviside firing rate function we calculate symmetric one-bump and ring solutions explicitly and use an Evans function approach to predict the point of instability and the shapes of the dominant growing modes. Our predictions are shown to be in excellent agreement with direct numerical simulations. Moreover, beyond the instability our simulations demonstrate the emergence of multi-bump and labyrinthine patterns. With the addition of spike-frequency adaptation, numerical simulations of the resulting vector model show that it is possible for structures without rotational symmetry, and in particular multi-bumps, to undergo an instability to a rotating wave. We use a general argument, valid for smooth firing rate functions, to establish the conditions necessary to generate such a rotational instability. Numerical continuation of the rotating wave is used to quantify the emergent angular velocity as a bifurcation parameter is varied. Wave stability is found via the numerical evaluation of an associated eigenvalue problem

Leiomyosarcoma of the inferior vena cava: Clinical experience with four cases

BACKGROUND: Leiomyosarcoma of the inferior vena cava is a rare tumor that presents in an insidious manner with non-specific symptoms. Given its rarity, there are no consensus guidelines to its management. The aim of this study was to report the clinical experience in the management of patients presenting to our institution during a 12 year period. PATIENTS AND METHODS: Four patients with leiomyosarcomas of the inferior vena cava were managed at our institution during the period reviewed. Patient details were identified through a search of the pathology department computerized database, and case notes were retrospectively reviewed to obtain details of presentation and management. RESULTS: There were 3 females and 1 male with a mean age of 59 years. All tumors were identified within 2 months of first symptoms. Three of the 4 had localized tumors whilst 1 patient had lung metastases at presentation. The three patients with resectable tumors underwent radical surgical excision of the tumor, and two patients had postoperative radiotherapy. One patient died of recurrence at 7 months, and another at 30 months. The third patient is currently well and disease free at 16 months. The fourth patient with metastatic disease was treated with chemotherapy alone and survived 36 months. CONCLUSION: Leiomyosarcoma of the inferior vena cava is an uncommon tumor that presents with non-specific symptoms. At the time of presentation, tumors are usually large and resection is challenging but probably offers the best opportunity for long-term survival

Synchrony-induced modes of oscillation of a neural field model

We investigate the modes of oscillation of heterogeneous ring-networks of quadratic integrate-and-fire (QIF) neurons with non-local, space-dependent coupling. Perturbations of the equilibrium state with a particular wave number produce transient standing waves with a specific temporal frequency, analogous to those in a tense string. In the neuronal network, the equilibrium corresponds to a spatially homogeneous, asynchronous state. Perturbations of this state excite the network’s oscillatory modes, which reflect the interplay of episodes of synchronous spiking with the excitatory-inhibitory spatial interactions. In the thermodynamic limit, an exact low-dimensional neural field model (QIF-NFM) describing the macroscopic dynamics of the network is derived. This allows us to obtain formulas for the Turing eigenvalues of the spatially-homogeneous state, and hence to obtain its stability boundary. We find that the frequency of each Turing mode depends on the corresponding Fourier coefficient of the synaptic pattern of connectivity. The decay rate instead, is identical for all oscillation modes as a consequence of the heterogeneity-induced desynchronization of the neurons. Finally, we numerically compute the spectrum of spatially-inhomogeneous solutions branching from the Turing bifurcation, showing that similar oscillatory modes operate in neural bump states, and are maintained away from onset

Magnon dispersion and thermodynamics in CsNiF_3

We present an accurate transfer matrix renormalization group calculation of the thermodynamics in a quantum spin-1 planar ferromagnetic chain. We also calculate the field dependence of the magnon gap and confirm the accuracy of the magnon dispersion derived earlier through an 1/n expansion. We are thus able to examine the validity of a number of previous calculations and further analyze a wide range of experiments on CsNiF_3 concerning the magnon dispersion, magnetization, susceptibility, and specific heat. Although it is not possible to account for all data with a single set of parameters, the overall qualitative agreement is good and the remaining discrepancies may reflect departure from ideal quasi-one-dimensional model behavior. Finally, we present some indirect evidence to the effect that the popular interpretation of the excess specific heat in terms of sine-Gordon solitons may not be appropriate.Comment: 9 pages 10 figure

Evaluation of applying IHC4 as a prognostic model in the translational study of Intergroup Exemestane Study (IES): PathIES

Background: Intergroup Exemestane Study (IES) was a randomised study that showed a survival benefit of switching adjuvant endocrine therapy after 2–3 years from tamoxifen to exemestane. This PathIES aimed to assess the role of immunohistochemical (IHC)4 score in determining the relative sensitivity to either tamoxifen or sequential treatment with tamoxifen and exemestane. Patients and methods: Primary tumour samples were available for 1274 patients (27% of IES population). Only patients for whom the IHC4 score could be calculated (based on oestrogen receptor, progesterone receptor, HER2 and Ki67) were included in this analysis (N = 430 patients). The clinical score (C) was based on age, grade, tumour size and nodal status. The association of clinicopathological parameters, IHC4(+C) scores and treatment effect with time to distant recurrence-free survival (TTDR) was assessed in univariable and multivariable Cox regression analyses. A modified clinical score (PathIEscore) (N = 350) was also estimated. Results: Our results confirm the prognostic importance of the original IHC4, alone and in conjunction with clinical scores, but no significant difference with treatment effects was observed. The combined IHC4 + Clinical PathIES score was prognostic for TTDR (P < 0.001) with a hazard ratio (HR) of 5.54 (95% CI 1.29–23.70) for a change from 1st quartile (Q1) to Q1–Q3 and HR of 15.54 (95% CI 3.70–65.24) for a change from Q1 to Q4. Conclusion: In the PathIES population, the IHC4 score is useful in predicting long-term relapse in patients who remain disease-free after 2–3 years. This is a first trial to suggest the extending use of IHC4+C score for prognostic indication for patients who have switched endocrine therapies at 2–3 years and who remain disease-free after 2–3 years