Face or building superiority in peripheral vision reversed by task requirements

Peripheral vision has been the topic of few studies compared with central vision. Nevertheless, given that visual information covers all the visual field and that relevant information can originate from highly eccentric positions, the understanding of peripheral vision abilities for object perception seems essential. The poorer resolution of peripheral vision would first suggest that objects requiring large-scale feature integration such as buildings would be better processed than objects requiring finer analysis such as faces. Nevertheless, task requirements also determine the information (coarse or fine) necessary for a given object to be processed. We therefore investigated how task and eccentricity modulate object processing in peripheral vision. Three experiments were carried out requiring finer or coarser information processing of faces and buildings presented in central and peripheral vision. Our results showed that buildings were better judged as identical or familiar in periphery whilst faces were better categorised. We conclude that this superiority for a given stimulus in peripheral vision results (a) from the available information, which depends on the decrease of resolution with eccentricity, and (b) from the useful information, which depends on both the task and the semantic category

Preferred Spatial Frequencies for Human Face Processing Are Associated with Optimal Class Discrimination in the Machine

Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance

Optics of Nonuniformly Moving Media

A moving dielectric appears to light as an effective gravitational field. At low flow velocities the dielectric acts on light in the same way as a magnetic field acts on a charged matter wave. We develop in detail the geometrical optics of moving dispersionless media. We derive a Hamiltonian and a Lagrangian to describe ray propagation. We elucidate how the gravitational and the magnetic model of light propagation are related to each other. Finally, we study light propagation around a vortex flow. The vortex shows an optical Aharonov--Bohm effect at large distances from the core, and, at shorter ranges, the vortex may resemble an optical black hole.Comment: Physical Review A (submitted

“I Look in Your Eyes, Honey”: Internal Face Features Induce Spatial Frequency Preference for Human Face Processing

Numerous psychophysical experiments found that humans preferably rely on a narrow band of spatial frequencies for recognition of face identity. A recently conducted theoretical study by the author suggests that this frequency preference reflects an adaptation of the brain's face processing machinery to this specific stimulus class (i.e., faces). The purpose of the present study is to examine this property in greater detail and to specifically elucidate the implication of internal face features (i.e., eyes, mouth, and nose). To this end, I parameterized Gabor filters to match the spatial receptive field of contrast sensitive neurons in the primary visual cortex (simple and complex cells). Filter responses to a large number of face images were computed, aligned for internal face features, and response-equalized (“whitened”). The results demonstrate that the frequency preference is caused by internal face features. Thus, the psychophysically observed human frequency bias for face processing seems to be specifically caused by the intrinsic spatial frequency content of internal face features

Fabrication of Feedhorn-Coupled Transition Edge Sensor Arrays for Measurement of the Cosmic Microwave Background Polarization

Characterization of the minute cosmic microwave background (CMB) polarization signature requires multi-frequency high-throughput precision instrument systems. We have previously described the detector fabrication of a 40 gigahertz focal plane and now describe the fabrication of a 37-element dual-polarization detector module for measurement of the CMB at 90 gigahertz. The 72-TES (Transition Edge Sensor)-based bolometers in each module are coupled to a niobium-based planar orthomode transducer with integrated band defining filters implemented in microstrip transmission line. A single crystal silicon dielectric substrate serves as microstrip dielectric and as a thermal link between the membrane isolated MoAu TES operating at 150 millikelvins and the heat bath. A short silicon leg between the heat bath and the TES bolometer is designed for ballistic phonon transport and provides improved process control and uniformity of thermal conductance in the presence of phonon scattering on roughened surfaces. Micro-machined structures are used to realize the orthomode transducer backshort, provide out of band signal rejection, and a silicon photonic choke for feedhorn coupling are described. The backshort, choke wafer, and detector wafer are indium bump-bonded to create a single 37-element dual-polarization detector module. Fourteen such hexagonally shaped modules each 80 millimeters in size comprise two focal planes. These, along with the recently delivered 40 gigahertz focal plane, will survey a large fraction of the sky as part of the Johns Hopkins University-led ground-based CLASS (Cosmology Large Angular Scale Surveyor) telescope

Processing of spatial-frequency altered faces in schizophrenia: Effects of illness phase and duration

Low spatial frequency (SF) processing has been shown to be impaired in people with schizophrenia, but it is not clear how this varies with clinical state or illness chronicity. We compared schizophrenia patients (SCZ, n534), first episode psychosis patients (FEP, n522), and healthy controls (CON, n535) on a gender/facial discrimination task. Images were either unaltered (broadband spatial frequency, BSF), or had high or low SF information removed (LSF and HSF conditions, respectively). The task was performed at hospital admission and discharge for patients, and at corresponding time points for controls. Groups were matched on visual acuity. At admission, compared to their BSF performance, each group was significantly worse with low SF stimuli, and most impaired with high SF stimuli. The level of impairment at each SF did not depend on group. At discharge, the SCZ group performed more poorly in the LSF condition than the other groups, and showed the greatest degree of performance decline collapsed over HSF and LSF conditions, although the latter finding was not significant when controlling for visual acuity. Performance did not change significantly over time for any group. HSF processing was strongly related to visual acuity at both time points for all groups. We conclude the following: 1) SF processing abilities in schizophrenia are relatively stable across clinical state; 2) face processing abnormalities in SCZ are not secondary to problems processing specific SFs, but are due to other known difficulties constructing visual representations from degraded information; and 3) the relationship between HSF processing and visual acuity, along with known SCZ- and medication-related acuity reductions, and the elimination of a SCZ-related impairment after controlling for visual acuity in this study, all raise the possibility that some prior findings of impaired perception in SCZ may be secondary to acuity reductions

Face-specific capacity limits under perceptual load do not depend on holistic processing

Previous observations that face recognition may proceed automatically, without drawing on attentional resources, have been challenged by recent demonstrations that only a few faces can be processed at one time. However, a question remains about the nature of the stimulus properties that underlie face-specific capacity limits. Two experiments showed that speeded categorization of a famous face (such as a politician or pop star) is facilitated when it is congruent with a peripheral distractor face. This congruency effect is eliminated if the visual search is loaded with more than one face, unlike previous demonstrations of speeded classification using semantic information. Importantly, congruency effects are also eliminated when the search task is loaded with nontarget faces that are shown in an inverted orientation. These results indicate that face-specific capacity limits are not determined by the configural (“holistic”) properties of face recognition

A Finite Element Model Approach to Determine the Influence of Electrode Design and Muscle Architecture on Myoelectric Signal Properties.

INTRODUCTION: Surface electromyography (sEMG) is the measurement of the electrical activity of the skeletal muscle tissue detected at the skin's surface. Typically, a bipolar electrode configuration is used. Most muscles have pennate and/or curved fibres, meaning it is not always feasible to align the bipolar electrodes along the fibres direction. Hence, there is a need to explore how different electrode designs can affect sEMG measurements. METHOD: A three layer finite element (skin, fat, muscle) muscle model was used to explore different electrode designs. The implemented model used as source signal an experimentally recorded intramuscular EMG taken from the biceps brachii muscle of one healthy male. A wavelet based intensity analysis of the simulated sEMG signal was performed to analyze the power of the signal in the time and frequency domain. RESULTS: The model showed muscle tissue causing a bandwidth reduction (to 20-92- Hz). The inter-electrode distance (IED) and the electrode orientation relative to the fibres affected the total power but not the frequency filtering response. The effect of significant misalignment between the electrodes and the fibres (60°- 90°) could be reduced by increasing the IED (25-30 mm), which attenuates signal cancellation. When modelling pennated fibres, the muscle tissue started to act as a low pass filter. The effect of different IED seems to be enhanced in the pennated model, while the filtering response is changed considerably only when the electrodes are close to the signal termination within the model. For pennation angle greater than 20°, more than 50% of the source signal was attenuated, which can be compensated by increasing the IED to 25 mm. CONCLUSION: Differences in tissue filtering properties, shown in our model, indicates that different electrode designs should be considered for muscle with different geometric properties (i.e. pennated muscles)

Stochastic many-particle model for LFP electrodes

In the framework of non-equilibrium thermodynamics, we derive a new model for many-particle electrodes. The model is applied to LiFePO4 (LFP) electrodes consisting of many LFP particles of nanometer size. The phase transition from a lithium-poor to a lithium-rich phase within LFP electrodes is controlled by both different particle sizes and surface fluctuations leading to a system of stochastic differential equations. An explicit relation between battery voltage and current controlled by the thermodynamic state variables is derived. This voltage–current relation reveals that in thin LFP electrodes lithium intercalation from the particle surfaces into the LFP particles is the principal rate-limiting process. There are only two constant kinetic parameters in the model describing the intercalation rate and the fluctuation strength, respectively. The model correctly predicts several features of LFP electrodes, viz. the phase transition, the observed voltage plateaus, hysteresis and the rate-limiting capacity. Moreover we study the impact of both the particle size distribution and the active surface area on the voltage–charge characteristics of the electrode. Finally we carefully discuss the phase transition for varying charging/discharging rates