Modulation of somatosensory processing by action.

Psychophysical evidence suggests that sensations arising from our own movements are diminished when predicted by motor forward models and that these models may also encode the timing and intensity of movement. Here we report a functional magnetic resonance imaging study in which the effects on sensation of varying the occurrence, timing and force of movements were measured. We observed that tactile-related activity in a region of secondary somatosensory cortex is reduced when sensation is associated with movement and further that this reduction is maximal when movement and sensation occur synchronously. Motor force is not represented in the degree of attenuation but rather in the magnitude of this region's response. These findings provide neurophysiological correlates of previously-observed behavioural forward-model phenomena, and advocate the adopted approach for the study of clinical conditions in which forward-model deficits have been posited to play a crucial role.

Statistical inference for single- and multi-band probabilistic amplitude demodulation.

Amplitude demodulation is an ill-posed problem and so it is natural to treat it from a Bayesian viewpoint, inferring the most likely carrier and envelope under probabilistic constraints. One such treatment is Probabilistic Amplitude Demodulation (PAD), which, whilst computationally more intensive than traditional approaches, offers several advantages. Here we provide methods for estimating the uncertainty in the PAD-derived envelopes and carriers, and for learning free-parameters like the time-scale of the envelope. We show how the probabilistic approach can naturally handle noisy and missing data. Finally, we indicate how to extend the model to signals which contain multiple modulators and carriers.

Modeling natural sounds with modulation cascade processes

Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences ($\sim1$s); phonemes ($\sim10$−$1$ s); glottal pulses ($\sim 10$−$2$s); and formants ($\sim 10$−$3$s). The auditory system uses information from each of these time-scales to solve complicated tasks such as auditory scene analysis [1]. One route toward understanding how auditory processing accomplishes this analysis is to build neuroscience-inspired algorithms which solve similar tasks and to compare the properties of these algorithms with properties of auditory processing. There is however a discord: Current machine-audition algorithms largely concentrate on the shorter time-scale structures in sounds, and the longer structures are ignored. The reason for this is two-fold. Firstly, it is a difficult technical problem to construct an algorithm that utilises both sorts of information. Secondly, it is computationally demanding to simultaneously process data both at high resolution (to extract short temporal information) and for long duration (to extract long temporal information). The contribution of this work is to develop a new statistical model for natural sounds that captures structure across a wide range of time-scales, and to provide efficient learning and inference algorithms. We demonstrate the success of this approach on a missing data task.

Probabilistic Amplitude Demodulation

Auditory scene analysis is extremely challenging. One approach, perhaps that adopted by the brain, is to shape useful representations of sounds on prior knowledge about their statistical structure. For example, sounds with harmonic sections are common and so time-frequency representations are efficient. Most current representations concentrate on the shorter components. Here, we propose representations for structures on longer time-scales, like the phonemes and sentences of speech. We decompose a sound into a product of processes, each with its own characteristic time-scale. This demodulation cascade relates to classical amplitude demodulation, but traditional algorithms fail to realise the representation fully. A new approach, probabilistic amplitude demodulation, is shown to out-perform the established methods, and to easily extend to representation of a full demodulation cascade.

A performance evaluation of volumetric 3D interest point detectors

This paper presents the first performance evaluation of interest points on scalar volumetric data. Such data encodes 3D shape, a fundamental property of objects. The use of another such property, texture (i.e. 2D surface colouration), or appearance, for object detection, recognition and registration has been well studied; 3D shape less so. However, the increasing prevalence of 3D shape acquisition techniques and the diminishing returns to be had from appearance alone have seen a surge in 3D shape-based methods. In this work, we investigate the performance of several state of the art interest points detectors in volumetric data, in terms of repeatability, number and nature of interest points. Such methods form the first step in many shape-based applications. Our detailed comparison, with both quantitative and qualitative measures on synthetic and real 3D data, both point-based and volumetric, aids readers in selecting a method suitable for their application. © 2012 Springer Science+Business Media, LLC.

Studying adsorbent dynamics on a quartz crystal resonator using its nonlinear electrical response

The quartz crystal resonator has been traditionally employed in studying surface-confined physisorbed films and particles by measuring dissipation and frequency shifts. However, theoretical interpretation of the experimental observations is often challenged due to limited understanding of physical interaction mechanisms at the interfaces involved. Here we model a physisorbed interaction between particles and gold electrode surface of a quartz crystal and demonstrate how the nonlinear modulation of the electric response of the crystal due to the nonlinear interaction forces may be used to study the dynamics of the particles. In particular, we show that the graphs of the deviation in the third Fourier harmonic response versus oscillation amplitude provide important information about the onset, progress and nature of sliding of the particles. The graphs also present a signature of the surface-particle interaction and could be used to estimate the interaction energy profile. Interestingly, the insights gained from the model help to explain some of the experimental observations with physisorbed streptavidin-coated polystyrene microbeads on quartz resonators. © 2012 Elsevier B.V. All rights reserved.

Uncertainty increases pain: evidence for a novel mechanism of pain modulation involving the periaqueductal gray.

Predictions about sensory input exert a dominant effect on what we perceive, and this is particularly true for the experience of pain. However, it remains unclear what component of prediction, from an information-theoretic perspective, controls this effect. We used a vicarious pain observation paradigm to study how the underlying statistics of predictive information modulate experience. Subjects observed judgments that a group of people made to a painful thermal stimulus, before receiving the same stimulus themselves. We show that the mean observed rating exerted a strong assimilative effect on subjective pain. In addition, we show that observed uncertainty had a specific and potent hyperalgesic effect. Using computational functional magnetic resonance imaging, we found that this effect correlated with activity in the periaqueductal gray. Our results provide evidence for a novel form of cognitive hyperalgesia relating to perceptual uncertainty, induced here by vicarious observation, with control mediated by the brainstem pain modulatory system.

Modulation of pain processing in hyperalgesia by cognitive demand.

The relationship between pain and cognitive function is of theoretical and clinical interest, exemplified by observations that attention-demanding activities reduce pain in chronically afflicted patients. Previous studies have concentrated on phasic pain, which bears little correspondence to clinical pain conditions. Indeed, phasic pain is often associated with differential or opposing effects to tonic pain in behavioral, lesion, and pharmacological studies. To address how cognitive engagement interacts with tonic pain, we assessed the influence of an attention-demanding cognitive task on pain-evoked neural responses in an experimental model of chronic pain, the capsaicin-induced heat hyperalgesia model. Using functional magnetic resonance imaging (fMRI), we show that activity in the orbitofrontal and medial prefrontal cortices, insula, and cerebellum correlates with the intensity of tonic pain. This pain-related activity in medial prefrontal cortex and cerebellum was modulated by the demand level of the cognitive task. Our findings highlight a role for these structures in the integration of motivational and cognitive functions associated with a physiological state of injury. Within the limitations of an experimental model of pain, we suggest that the findings are relevant to understanding both the neurobiology and pathophysiology of chronic pain and its amelioration by cognitive strategies.

Experimental investigation of dynamic response of acoustically forced turbulent premixed CH4/CO2/air flames

Increasing demand for energy and continuing increase in environmental as well as financial cost of use of fossil fuels drive the need for utilization of fuels from sustainable sources for power generation. Development of fuel-flexible combustion systems is vital in enabling the use of sustainable fuels. It is also important that these sustainable combustion systems meet the strict governmental emission legislations. Biogas is considered as one of the viable sustainable fuels that can be used to power modern gas turbines: However, the change in chemical, thermal and transport properties as well as change in Wobbe index due to the variation of the fuel constituents can have a significant effect on the performance of the combustor. It is known that the fuel properties have strong influence on the dynamic flame response; however there is a lack of detailed information regarding the effect of fuel compositions on the sensitivity of the flames subjected to flow perturbations. In this study, we describe an experimental effort investigating the response of premixed biogas-air turbulent flames with varying proportions of CH4 and CO2 to velocity perturbations. The flame was stabilized using a centrally placed conical bluff body. Acoustic perturbations were imposed to the flow using loud speakers. The flame dynamics and the local heat release rate of these acoustically excited biogas flames were studied using simultaneous measurements of OH and H2CO planar laser induced fluorescence. OH* chemiluminescence along with acoustic pressure measurements were also recorded to estimate the total flame heat release modulation and the velocity fluctuations. The measurements were carried out by keeping the theoretical laminar flame speed constant while varying the bulk velocity and the fuel composition. The results indicate that the flame sensitivity to perturbations increased with increased dilution of CH4 by CO2 at low amplitude forcing, while at high amplitude forcing conditions the magnitude of the flame response was independent of dilution.

Orthogonal multipulse modulation for 64 Gigabit Fibre Channel

Real-time orthogonal multipulse modulation is demonstrated at 56 Gb/s with transmission over 500 m of single-mode fiber. Up to 2 dBo power budget advantage is predicted relative to alternatives such as PAM4. © 2013 OSA.

Orthogonal multipulse modulation in optical datacommunications

Optical datacommunication links are now required at rates beyond 40 Gb/s. Achieving robust low-cost transmission at these rates necessitates consideration of advanced modulation formats. This paper concentrates on schemes using multiple orthogonal pulses and outlines the advantages relative to alternatives such as multilevel modulation. Recent real-time experimental results at 56 Gb/s are described. © 2013 IEEE.

Parametrically excited MEMS vibration energy harvesters with design approaches to overcome the initiation threshold amplitude

Resonant-based vibration harvesters have conventionally relied upon accessing the fundamental mode of directly excited resonance to maximize the conversion efficiency of mechanical-to-electrical power transduction. This paper explores the use of parametric resonance, which unlike the former, the resonant-induced amplitude growth, is not limited by linear damping and wherein can potentially offer higher and broader nonlinear peaks. A numerical model has been constructed to demonstrate the potential improvements over the convention. Despite the promising potential, a damping-dependent initiation threshold amplitude has to be attained prior to accessing this alternative resonant phenomenon. Design approaches have been explored to passively reduce this initiation threshold. Furthermore, three representative MEMS designs were fabricated with both 25 and 10 μm thick device silicon. The devices include electrostatic cantilever-based harvesters, with and without the additional design modification to overcome initiation threshold amplitude. The optimum performance was recorded for the 25 μm thick threshold-aided MEMS prototype with device volume ∼0.147 mm3. When driven at 4.2 ms -2, this prototype demonstrated a peak power output of 10.7 nW at the fundamental mode of resonance and 156 nW at the principal parametric resonance, as well as a 23-fold decrease in initiation threshold over the purely parametric prototype. An approximate doubling of the half-power bandwidth was also observed for the parametrically excited scenario. © 2013 IOP Publishing Ltd.

Orthogonal multipulse modulation for 64 gigabit fibre channel

Real-time orthogonal multipulse modulation is demonstrated at 56 Gb/s with transmission over 500 m of single-mode fiber. Up to 2 dBo power budget advantage is predicted relative to alternatives such as PAM4. © 2013 OSA.

28 Gb/s unequalized PAM3 modulation of an 850 nm VCSEL for next-generation datacommunication links

An 850 nm vertical-cavity surface-emitting laser is modulated at 28 Gb/s using pulseamplitude modulation with three levels. Unequalized transmission over 100 m of OM3 MMF is demonstrated, with advantages over NRZ and PAM4 modulation. © OSA 2012.

Improved exponents and rates for bit-interleaved coded modulation

Mismatched decoding theory is applied to study the error exponents (both random-coding and expurgated) and achievable rates for bit-interleaved coded modulation (BICM). The gains achieved by constant-composition codes with respect to the the usual random codes are highlighted. © 2013 IEEE.