A dementia classification framework using frequency and time-frequency features based on EEG signals.

Alzheimer's Disease (AD) accounts for 60-70% of all dementia cases, and clinical diagnosis at its early stage is extremely difficult. As several new drugs aiming to modify disease progression or alleviate symptoms are being developed, to assess their efficacy, novel robust biomarkers of brain function are urgently required. This study aims to explore a routine to gain such biomarkers using the quantitative analysis of Electroencephalography (QEEG). This paper proposes a supervised classification framework which uses EEG signals to classify healthy controls (HC) and AD participants. The framework consists of data augmentation, feature extraction, K-Nearest Neighbour (KNN) classification, quantitative evaluation and topographic visualisation. Considering the human brain either as a stationary or a dynamical system, both frequency-based and time-frequency-based features were tested in 40 participants. Results: a) The proposed method can achieve up to 99% classification accuracy on short (4s) eyes open EEG epochs, with the KNN algorithm that has best performance when compared to alternative machine learning approaches; b) The features extracted using the wavelet transform produced better classification performance in comparison to the features based on FFT; c) In the spatial domain, the temporal and parietal areas offer the best distinction between healthy controls and AD. The proposed framework can effectively classify HC and AD participants with high accuracy, meanwhile offering identification and localisation of significant QEEG features. These important findings and the proposed classification framework could be used for the development of a biomarker for the diagnosis and monitoring of disease progression in AD

Transport Measurements on Nano-engineered Two Dimensional Superconducting Wire Networks

Superconducting triangular Nb wire networks with high normal-state resistance are fabricated by using a negative tone hydrogen silsesquioxane (HSQ) resist. Robust magnetoresistance oscillations are observed up to high magnetic fields and maintained at low temperatures, due to the eective reduction of wire dimensions. Well-defined dips appear at integral and rational values (1/2, 1/3, 1/4) of the reduced flux f = Phi/Phi_0, which is the first observation in the triangular wire networks. These results are well consistent with theoretical calculations for the reduced critical temperature as a function of f.Comment: 4 pages, 3 figure

Morphology and Orientation Selection of Non-Metallic Inclusions in Electrified Molten Metal

The effect of electric current on morphology and orientation selection of non-metallic inclusions in molten metal has been investigated using theoretical modelling and numerical calculation. Two geometric factors, namely the circularity (fc) and alignment ratio (fe) were introduced to describe the inclusions shape and configuration. Electric current free energy was calculated and the values were used to determine the thermodynamic preference between different microstructures. Electric current promotes the development of inclusion along the current direction by either expatiating directional growth or enhancing directional agglomeration. Reconfiguration of the inclusions to reduce the system electric resistance drives the phenomena. The morphology and orientation selection follows the routine to reduce electric free energy. The numerical results are in agreement with our experimental observations

Zircon records of Miocene ultrapotassic rocks from southern Lhasa subterrane, Tiben Plateau

Zircons entrained in mantle-derived magmas offer a prime opportunity to reveal cryptic magmatic episodes in the deep crust. We have investigated zircons from mantle-derived ultrapotassic veins in the Xuena area, southern Lhasa subterrane. Zircons in the Xuena ultrapotassic rocks reveal four major magmatic pulses around <100Ma, 300 ~ 400Ma, 450 ~ 500Ma, and 700 ~ 850Ma. The high U / Yb ratios and low Y contents of these zircons demonstrate their continental origin. Cenozoic-Mesozoic and Late Paleozoic magmatism have been widely identified from the southern Lhasa subterrane, suggesting the contribution from overlying juvenile crust. But similar Proterozoic-Early Paleozoic age distributions (450 ~ 500Ma and 700 ~ 850Ma) between these zircon xenocrysts and those dating records in the Himalayan orogenic belt corroborate the input from underthrusted Indian continental crust. Furthermore, the Increasing (Dy / Yb) N ratio since ~ 60 Ma zircon and Rapid Decreasing epsilon Hf ( t ) values, from + 10 ~ + 5 to -10 ~ -25, are Interpreted to reflect Significant and progressive Crustal Thickening in Response to India-Asia convergence and the contribution from subducted Indian continental crust to postcollisional magmatism in the southern Lhasa sub-terrane

Imaging of nonlinear and dynamic functional brain connectivity based on EEG recordings with the application on the diagnosis of Alzheimer’s disease

Since age is the most significant risk factor for the development of Alzheimer’s disease (AD), it is important to understand the effect of normal ageing on brain network characteristics before we can accurately diagnose the condition based on information derived from resting state electroencephalogram (EEG) recordings, aiming to detect brain network disruption. This paper proposes a novel brain functional connectivity imaging method, particularly targeting the contribution of nonlinear dynamics of functional connectivity, on distinguishing participants with AD from healthy controls (HC). We describe a parametric method established upon a Nonlinear Finite Impulse Response model, and a revised orthogonal least squares algorithm used to estimate the linear, nonlinear and combined connectivity between any two EEG channels without fitting a full model. This approach, where linear and non-linear interactions and their spatial distribution and dynamics can be estimated independently, offered us the means to dissect the dynamic brain network disruption in AD from a new perspective and to gain some insight into the dynamic behaviour of brain networks in two age groups (above and below 70) with normal cognitive function. Although linear and stationary connectivity dominates the classification contributions, quantitative results have demonstrated that nonlinear and dynamic connectivity can significantly improve the classification

Tremor after long term lithium treatment; is it cortical myoclonus?

Introduction Tremor is a common side effect of treatment with lithium. Its characteristics can vary and when less rhythmical, distinction from myoclonus can be difficult. Methods We identified 8 patients on long-term treatment with lithium that developed upper limb tremor. All patients were assessed clinically and electrophysiologically, with jerk-locked averaging (JLA) and cross-correlation (CC) analysis, and five of them underwent brain MRI examination including spectroscopy (MRS) of the cerebellum. Results Seven patients (6 female) had action and postural myoclonus and one a regular postural and kinetic tremor that persisted at rest. Mean age at presentation was 58 years (range 42–77) after lengthy exposure to lithium (range 7–40 years). During routine monitoring all patients had lithium levels within the recommended therapeutic range (0.4-1 mmol/l). There was clinical and/or radiological evidence (on cerebellar MRS) of cerebellar dysfunction in 6 patients. JLA and/or CC suggested a cortical generator of the myoclonus in seven patients. All seven were on antidepressants and three additionally on neuroleptics, four of them had gluten sensitivity and two reported alcohol abuse. Conclusions A synergistic effect of different factors appears to be contributing to the development of cortical myoclonus after chronic exposure to lithium. We hypothesise that the cerebellum is involved in the generation of cortical myoclonus in these cases and factors aetiologically linked to cerebellar pathology like gluten sensitivity and alcohol abuse may play a role in the development of myoclonus. Despite the very limited evidence in the literature, lithium induced cortical myoclonus may not be so rare

Concept of temperature in multi-horizon spacetimes: Analysis of Schwarzschild-De Sitter metric

In case of spacetimes with single horizon, there exist several well-established procedures for relating the surface gravity of the horizon to a thermodynamic temperature. Such procedures, however, cannot be extended in a straightforward manner when a spacetime has multiple horizons. In particular, it is not clear whether there exists a notion of global temperature characterizing the multi-horizon spacetimes. We examine the conditions under which a global temperature can exist for a spacetime with two horizons using the example of Schwarzschild-De Sitter (SDS) spacetime. We systematically extend different procedures (like the expectation value of stress tensor, response of particle detectors, periodicity in the Euclidean time etc.) for identifying a temperature in the case of spacetimes with single horizon to the SDS spacetime. This analysis is facilitated by using a global coordinate chart which covers the entire SDS manifold. We find that all the procedures lead to a consistent picture characterized by the following features: (a) In general, SDS spacetime behaves like a non-equilibrium system characterized by two temperatures. (b) It is not possible to associate a global temperature with SDS spacetime except when the ratio of the two surface gravities is rational (c) Even when the ratio of the two surface gravities is rational, the thermal nature depends on the coordinate chart used. There exists a global coordinate chart in which there is global equilibrium temperature while there exist other charts in which SDS behaves as though it has two different temperatures. The coordinate dependence of the thermal nature is reminiscent of the flat spacetime in Minkowski and Rindler coordinate charts. The implications are discussed.Comment: 12 page

Partial Wave Analysis of J/ψ→γ(K+K−π+π−)J/\psi \to \gamma (K^+K^-\pi^+\pi^-)

BES data on $J/\psi \to \gamma (K^+K^-\pi^+\pi^-)$ are presented. The $K^*\bar K^*$ contribution peaks strongly near threshold. It is fitted with a broad $0^{-+}$ resonance with mass $M = 1800 \pm 100$ MeV, width $\Gamma = 500 \pm 200$ MeV. A broad $2^{++}$ resonance peaking at 2020 MeV is also required with width $\sim 500$ MeV. There is further evidence for a $2^{-+}$ component peaking at 2.55 GeV. The non-$K^*\bar K^*$ contribution is close to phase space; it peaks at 2.6 GeV and is very different from $K^{*}\bar{K^{*}}$.Comment: 15 pages, 6 figures, 1 table, Submitted to PL

A Pilot Study Investigating a Novel Non-Linear Measure of Eyes Open versus Eyes Closed EEG Synchronization in People with Alzheimer’s Disease and Healthy Controls

Background: The incidence of Alzheimer disease (AD) is increasing with the ageing population. The development of low cost non-invasive diagnostic aids for AD is a research priority. This pilot study investigated whether an approach based on a novel dynamic quantitative parametric EEG method could detect abnormalities in people with AD. Methods: 20 patients with probable AD, 20 matched healthy controls (HC) and 4 patients with probable fronto temporal dementia (FTD) were included. All had detailed neuropsychology along with structural, resting state fMRI and EEG. EEG data were analyzed using the Error Reduction Ratio-causality (ERR-causality) test that can capture both linear and nonlinear interactions between different EEG recording areas. The 95% confidence intervals of EEG levels of bi-centroparietal synchronization were estimated for eyes open (EO) and eyes closed (EC) states. Results: In the EC state, AD patients and HC had very similar levels of bi-centro parietal synchronization; but in the EO resting state, patients with AD had significantly higher levels of synchronization (AD = 0.44; interquartile range (IQR) 0.41 vs. HC = 0.15; IQR 0.17, p < 0.0001). The EO/EC synchronization ratio, a measure of the dynamic changes between the two states, also showed significant differences between these two groups (AD ratio 0.78 versus HC ratio 0.37 p < 0.0001). EO synchronization was also significantly different between AD and FTD (FTD = 0.075; IQR 0.03, p < 0.0001). However, the EO/EC ratio was not informative in the FTD group due to very low levels of synchronization in both states (EO and EC). Conclusion: In this pilot work, resting state quantitative EEG shows significant differences between healthy controls and patients with AD. This approach has the potential to develop into a useful non-invasive and economical diagnostic aid in AD