Speed of processing in the primary motor cortex: A continuous theta burst stimulation study

‘Temporally urgent’ reactions are extremely rapid, spatially precise movements that are evoked following discrete stimuli. The involvement of primary motor cortex (M1) and its relationship to stimulus intensity in such reactions is not well understood. Continuous theta burst stimulation (cTBS) suppresses focal regions of the cortex and can assess the involvement of motor cortex in speed of processing. The primary objective of this study was to explore the involvement of M1 in speed of processing with respect to stimulus intensity. Thirteen healthy young adults participated in this experiment. Behavioral testing consisted of a simple button press using the index finger following median nerve stimulation of the opposite limb, at either high or low stimulus intensity. Reaction time was measured by the onset of electromyographic activity from the first dorsal interosseous (FDI) muscle of each limb. Participants completed a 30 min bout of behavioral testing prior to, and 15 min following, the delivery of cTBS to the motor cortical representation of the right FDI. The effect of cTBS on motor cortex was measured by recording the average of 30 motor evoked potentials (MEPs) just prior to, and 5 min following, cTBS. Paired t-tests revealed that, of thirteen participants, five demonstrated a significant attenuation, three demonstrated a significant facilitation and five demonstrated no significant change in MEP amplitude following cTBS. Of the group that demonstrated attenuated MEPs, there was a biologically significant interaction between stimulus intensity and effect of cTBS on reaction time and amplitude of muscle activation. This study demonstrates the variability of potential outcomes associated with the use of cTBS and further study on the mechanisms that underscore the methodology is required. Importantly, changes in motor cortical excitability may be an important determinant of speed of processing following high intensity stimulation.

A statistical framework for channel availability modelling in the polarisation domain

Cognitive radio has been proposed as a means of improving the spectrum utilisation and increasing spectrum efficiency of wireless systems. This can be achieved by allowing cognitive radio terminals to monitor their spectral environment and opportunistically access the unoccupied frequency channels. Due to the opportunistic nature of cognitive radio, the overall performance of such networks depends on the spectrum occupancy or availability patterns. Appropriate knowledge on channel availability can optimise the sensing performance in terms of spectrum and energy efficiency. This work proposes a statistical framework for the channel availability in the polarization domain. A Gaussian Normal approximation is used to model real-world occupancy data obtained through a measurement campaign in the cellular frequency bands within a realistic scenario.

Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels

With the rapid development of internet-of-things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently in these IoT applications, biometric verification needs to be carried out in the scrambled domain, presenting significant challenges in face recognition. Since face models become chaotic signals after scrambling/encryption, a typical solution is to utilize traditional data-driven face recognition algorithms. While chaotic pattern recognition is still a challenging task, in this paper we propose a new ensemble approach – Many-Kernel Random Discriminant Analysis (MK-RDA) to discover discriminative patterns from chaotic signals. We also incorporate a salience-aware strategy into the proposed ensemble method to handle chaotic facial patterns in the scrambled domain, where random selections of features are made on semantic components via salience modelling. In our experiments, the proposed MK-RDA was tested rigorously on three human face datasets: the ORL face dataset, the PIE face dataset and the PUBFIG wild face dataset. The experimental results successfully demonstrate that the proposed scheme can effectively handle chaotic signals and significantly improve the recognition accuracy, making our method a promising candidate for secure biometric verification in emerging IoT applications.

Early processing in the human lateral occipital complex is highly responsive to illusory contours but not to salient regions.

Human electrophysiological studies support a model whereby sensitivity to so-called illusory contour stimuli is first seen within the lateral occipital complex. A challenge to this model posits that the lateral occipital complex is a general site for crude region-based segmentation, based on findings of equivalent hemodynamic activations in the lateral occipital complex to illusory contour and so-called salient region stimuli, a stimulus class that lacks the classic bounding contours of illusory contours. Using high-density electrical mapping of visual evoked potentials, we show that early lateral occipital cortex activity is substantially stronger to illusory contour than to salient region stimuli, whereas later lateral occipital complex activity is stronger to salient region than to illusory contour stimuli. Our results suggest that equivalent hemodynamic activity to illusory contour and salient region stimuli probably reflects temporally integrated responses, a result of the poor temporal resolution of hemodynamic imaging. The temporal precision of visual evoked potentials is critical for establishing viable models of completion processes and visual scene analysis. We propose that crude spatial segmentation analyses, which are insensitive to illusory contours, occur first within dorsal visual regions, not the lateral occipital complex, and that initial illusory contour sensitivity is a function of the lateral occipital complex.

Phonological processing in the reading of deaf and normally hearing children

This paper reviews measurement of phonological processes in reading among deaf children and children who are of normal hearing.

The point source method for inverse scattering in the time domain

Many recent inverse scattering techniques have been designed for single frequency scattered fields in the frequency domain. In practice, however, the data is collected in the time domain. Frequency domain inverse scattering algorithms obviously apply to time-harmonic scattering, or nearly time-harmonic scattering, through application of the Fourier transform. Fourier transform techniques can also be applied to non-time-harmonic scattering from pulses. Our goal here is twofold: first, to establish conditions on the time-dependent waves that provide a correspondence between time domain and frequency domain inverse scattering via Fourier transforms without recourse to the conventional limiting amplitude principle; secondly, we apply the analysis in the first part of this work toward the extension of a particular scattering technique, namely the point source method, to scattering from the requisite pulses. Numerical examples illustrate the method and suggest that reconstructions from admissible pulses deliver superior reconstructions compared to straight averaging of multi-frequency data. Copyright (C) 2006 John Wiley & Sons, Ltd.

Prospects for bio-molecular control using femtosecond transients parametrised in the wavelet domain [poster]

We discuss the parametrisation of am-plitude and phase genes corre-sponding to space encoded femto-second transients in the wavelet domain. Differential evolution is used to improve the speed of con-vergence of the genetic algorithm. We discuss prospects of bio-molecular control using such methodology.

Optimal discrimination and classification of THz spectra in the wavelet domain

In rapid scan Fourier transform spectrometry, we show that the noise in the wavelet coefficients resulting from the filter bank decomposition of the complex insertion loss function is linearly related to the noise power in the sample interferogram by a noise amplification factor. By maximizing an objective function composed of the power of the wavelet coefficients divided by the noise amplification factor, optimal feature extraction in the wavelet domain is performed. The performance of a classifier based on the output of a filter bank is shown to be considerably better than that of an Euclidean distance classifier in the original spectral domain. An optimization procedure results in a further improvement of the wavelet classifier. The procedure is suitable for enhancing the contrast or classifying spectra acquired by either continuous wave or THz transient spectrometers as well as for increasing the dynamic range of THz imaging systems. (C) 2003 Optical Society of America.

Effect of seasonal variation on the composition and properties of raw milk destined for processing in the UK

The composition and physical properties of raw milk from a commercial herd were studied over a one year period in order to understand how best to utilise milk for processing throughout the year. Protein and fat levels demonstrated seasonal trends, while minerals and many physical properties displayed considerable variations, which were apparently unrelated to season. However, rennet clotting time, ethanol stability and foaming ability were subject to seasonal variation. Many significant interrelationships in physico-chemical properties were found. It is clear that the milk supply may be more suited to the manufacture of different products at different times of the year or even on a day to day basis. Subsequent studies will report on variation in production and quality of products manufactured from the same milk samples described in the current study and will thus highlight potential advantages of seasonal processing of raw milk.

A MATLAB GUI for learning controller design in the frequency domain

A MATLAB GUI is presented which is used to help students learn to design controllers in the frequency domain. It complements the author’s two previous GUIs for plotting and identification of systems in the frequency domain. It also incorporates the concept used in the “electronic calculator that makes students think” to assist learning. Positive student feedback affirms that the GUI has helped their understanding.

Parametric preference functionals under risk in the gain domain: a Bayesian analysis

The performance of rank dependent preference functionals under risk is comprehensively evaluated using Bayesian model averaging. Model comparisons are made at three levels of heterogeneity plus three ways of linking deterministic and stochastic models: the differences in utilities, the differences in certainty equivalents and contextualutility. Overall, the"bestmodel", which is conditional on the form of heterogeneity is a form of Rank Dependent Utility or Prospect Theory that cap tures the majority of behaviour at both the representative agent and individual level. However, the curvature of the probability weighting function for many individuals is S-shaped, or ostensibly concave or convex rather than the inverse S-shape commonly employed. Also contextual utility is broadly supported across all levels of heterogeneity. Finally, the Priority Heuristic model, previously examined within a deterministic setting, is estimated within a stochastic framework, and allowing for endogenous thresholds does improve model performance although it does not compete well with the other specications considered.

Monitoring and Explanation of Contract Execution: A Case Study in the Aerospace Domain

In the domain of aerospace aftermarkets, which often has long supply chains that feed into the maintenance of aircraft, contracts are used to establish agreements between aircraft operators and maintenance suppliers. However, violations at the bottom of the supply chain (part suppliers) can easily cascade to the top (aircraft operators), making it difficult to determine the source of the violation, and seek to address it. In this context, we have developed a global monitoring architecture that ensures the detection of norm violations and generates explanations for the origin of violations. In this paper, we describe the implementation and deployment of a global monitor in the aerospace domain of [8] and show how it generates explanations for violations within the maintenance supply chain. We show how these explanations can be used not only to detect violations at runtime, but also to uncover potential problems in contracts before their deployment, thus improving them.