Low Spatial Frequency Components Research Articles

Learning of the same task subserved by substantially different mechanisms between patients with body dysmorphic disorder and healthy individuals.

It has remained unclear whether individuals with psychiatric disorders involving altered visual processing employ similar neuronal mechanisms during perceptual learning of a visual task. We investigated this question by training patients with body dysmorphic disorder, a psychiatric disorder characterized by distressing or impairing preoccupation with nonexistent or slight defects in one's physical appearance, and healthy controls on a visual detection task for human faces with low spatial frequency components. Brain activation during task performance was measured with functional magnetic resonance imaging before the beginning and after the end of behavioral training. Both groups of participants improved performance on the trained task to a similar extent. However, neuronal changes in the fusiform face area were substantially different between groups such that activation for low spatial frequency faces in the right fusiform face area increased after training in body dysmorphic disorder patients but decreased in controls. Moreover, functional connectivity between left and right fusiform face area decreased after training in patients but increased in controls. Our results indicate that neuronal mechanisms involved in perceptual learning of a face detection task differ fundamentally between body dysmorphic disorder patients and controls. Such different neuronal mechanisms in body dysmorphic disorder patients might reflect the brain's adaptations to altered functions imposed by the psychiatric disorder.

Rapid Processing of Invisible Fearful Faces in the Human Amygdala.

Rapid detection of a threat or its symbol (e.g., fearful face), whether visible or invisible, is critical for human survival. This function is suggested to be enabled by a subcortical pathway to the amygdala independent of the cortex. However, conclusive electrophysiological evidence in humans is scarce. Here, we explored whether the amygdala can rapidly encode invisible fearful faces. We recorded intracranial electroencephalogram (iEEG) responses in the human (both sexes) amygdala to faces with fearful, happy, and neutral emotions rendered invisible by backward masking. We found that a short-latency intracranial event-related potential (iERP) in the amygdala, beginning 88 ms poststimulus onset, was preferentially evoked by invisible fearful faces relative to invisible happy or neutral faces. The rapid iERP exhibited selectivity to the low spatial frequency (LSF) component of the fearful faces. Time-frequency iEEG analyses further identified a rapid amygdala response preferentially for LSF fearful faces at the low gamma frequency band, beginning 45 ms poststimulus onset. In contrast, these rapid responses to invisible fearful faces were absent in cortical regions, including early visual areas, the fusiform gyrus, and the parahippocampal gyrus. These findings provide direct evidence for the existence of a subcortical pathway specific for rapid fear detection in the amygdala and demonstrate that the subcortical pathway can function without conscious awareness and under minimal influence from cortical areas.SIGNIFICANCE STATEMENT Automatic detection of biologically relevant stimuli, such as threats or dangers, has remarkable survival value. Here, we provide direct intracranial electrophysiological evidence that the human amygdala preferentially responds to fearful faces at a rapid speed, despite the faces being invisible. This rapid, fear-selective response is restricted to faces containing low spatial frequency information transmitted by magnocellular neurons and does not appear in cortical regions. These results support the existence of a rapid subcortical pathway independent of cortical pathways to the human amygdala.

Three-Dimensional Nanoscale Morphological Surface Analysis of Polymeric Particles Containing Allium sativum Essential Oil.

Biodegradable particles were developed using poly-ε-caprolactone and gelatin carriers containing different concentrations of Allium sativum essential oil (EO) (360 µg/mL, 420 µg/mL, and 460 µg/mL). Atomic force microscopy was useful to evaluate the particles’ surface based on morphological parameters. The particles’ size varied from 150 nm to 300 nm. The diameter was related to the increase of the particles’ height as a function of the EO concentration, influencing the roughness of the surface core values (from 20 to 30 nm) and surface irregularity. The spatial parameters Str (texture aspect ratio) and Std (texture direction) revealed low spatial frequency components. The hybrid parameters Sdq (root mean square gradient) and Sdr (interfacial area ratio) also increased as a function of the EO concentration, revealing fewer flat particles. On the other hand, the functional parameters (inverse areal material ratio and peak extreme height) suggested differences in surface irregularities. Higher concentrations of EO resulted in greater microtexture asperity on the particles’ surface, as well as sharper peaks. The nanoscale morphological surface analysis allowed the determination of the most appropriate concentration of encapsulated EO, influencing statistical surface parameters.

Intermediate, Wholistic Shape Representation in Object Recognition: A Pre-Attentive Stage of Processing?

Evidence is presented for intermediate, wholistic visual representations of objects and non-objects that are computed online and independent of visual attention. Short-term visual priming was examined between visually similar shapes, with targets either falling at the (valid) location cued by primes or at another (invalid) location. Object decision latencies were facilitated when the overall shapes of the stimuli were similar irrespective of whether the location of the prime was valid or invalid, with the effects being equally large for object and non-object targets. In addition, the effects were based on the overall outlines of the stimuli and low spatial frequency components, not on local parts. In conclusion, wholistic shape representations based on outline form, are rapidly computed online during object recognition. Moreover, activation of common wholistic shape representations prime the processing of subsequent objects and non-objects irrespective of whether they appear at attended or unattended locations. Rapid derivation of wholistic form provides a key intermediate stage of object recognition.

Analyzing and identifying oscillatory activities of emotions based on Electroencephalography signals using power spectral density and spatial filtering techniques

The electromagnetic waves or field potentials are generated by the activation of a population of neurons. These potentials are projected towards all the sensors or electrodes which are attached to the scalp and measured through Electroencephalography (EEG) sensors. These projections are mixing the source activities through the scalp and this over scalp is known as Volume-Conduction (VC). The signals are dominated by the dynamics of low spatial frequency components which are spread over all electrodes. In the literature, different spatial filtering techniques are introduced to cognitive electrophysiology for the separation of local source signals and the reflections of volume conduction artifacts. In this study, we have used two spatial filtering techniques: Surface Laplacian (SL) and Principal Component Analysis (PCA) to identify the source of emotion activity underneath the scalp. The SL isolates the brain localization features or topographical features within several square centimeters (cm2). It minimizes the spatial overlap of different visualized emotions such as High-Valence-Low-Valence (HVLV), and High-Arousal-Low-Arousal (HALA). The results have shown that the different types of emotions are likely to have been generated by local sources, not by the reflections of volume conduction artifacts. It assists psychologists in the rapid processing of EEG-like signals and gives quick neurofeedback for Brain-computer Interface applications. It has been analyzed that how SL and PCA using Eigenvalue decomposition find the spatial sources of information in the brain and incorporates a finite set of electrodes.

Substantial changes in global brain processing related to face perception in body dysmorphic disorder patients by training on low spatial frequency components in faces

Substantial changes in global brain processing related to face perception in body dysmorphic disorder patients by training on low spatial frequency components in faces

Quantifying the data quality of focal series for inline electron holography

Inline electron holography, the recovery of amplitude and phase of an electron wave function having passed through a thin specimen from a focal series recorded in a transmission electron microscope is being applied in many labs worldwide. At medium range magnification (i.e. typically ≥0.8 nm where the lattice of small unit cell crystals such as silicon is not resolved), where the defocus needs to be varied over a rather large range of several hundred nm or even μm, the retrieval of low spatial frequency information is severely affected by the choice of experimental parameters as well as the way of data normalization. Methods to quantitatively analyze the reliability of phase maps obtained by inline electron holography are presented, and data recorded and processed in different ways are compared. While, even under optimized conditions, the phase reconstructed from an experimental focal series still lacks very low spatial frequency components, regularization schemes exist and are demonstrated to effectively hide artifacts associated with this lack of information.

Power spectral analysis of surface microtopography formed in CW Laser surface texturing

Laser surface texturing (LST) has shown immense promise in modifying the physical as well as interactive properties of the surfaces. Understanding the surface microtopography generated during LST provides key knowledge on developing desirable surfaces for different technologies. The work focuses on determining the range of frequency components present in the microtopography when processed at different parameters, such as beam diameter (BD), scanning speed (SS), and beam overlap (BO). Power spectral density (PSD) is utilized to evaluate the intensity of each spatial frequency and fitting models are applied to quantify their contribution to the overall microtopography. The experiments were performed on titanium alloy Ti6Al4V using a continuous watt fiber laser at constant power. The surface microtopography differs when processed under different conditions. The microtopography contains low and high spatial frequency components distributed along both the scan and overlap direction. The PSD analysis reveals the increase in high spatial frequency features when BD and SS are increased. Conversely, the growth of spatial features is observed with an increase in BO reducing the dominance of high spatial frequencies. With the increase in BD, the energy density decreases which reduces the growth of spatial features inducing increased contribution of high spatial frequency content noticeable by upward curvature in the PSD. An increase in SS causes rapid laser motion to affect the microtopography along the scan direction. The increase in BO leads to the enhanced overlapping between successive passes causing remelting and growth of previously formed microtopography and increasing the contribution of low spatial frequency content in the microtopography. The fitting model parameters from ABC at low spatial frequency and Fractal at high frequency provide the quantitative reasoning for the observed trend. Power spectral analysis reveals significant information about the surface microtopography formed during LST and accurate quantification of the PSD may help numerical models to fine-tune the surface features according to the desired functionality.

Superresolution Imaging via Subwavelength Hole Resonances

This work presents a new super-resolution imaging approach by using subwavelength hole resonances. We employ a subwavelength structure in which an array of tiny holes are etched in a metallic slab with the neighboring distance $\ell$ that is smaller than half of the wavelength. By tuning the incident wave at resonant frequencies, the subwavelength structure generates strong illumination patterns that are able to probe both low and high spatial frequency components of the imaging sample sitting above the structure. The image of the sample is obtained by performing stable numerical reconstruction from the far-field measurement of the diffracted wave. It is demonstrated that a resolution of $\ell/2$ can be obtained for reconstructed images, thus one can achieve super-resolution by arranging multiple holes within one wavelength. The proposed approach may find applications in wave-based imaging such as electromagnetic and ultrasound imaging. It attains two advantages that are important for practical realization. It avoids the difficulty to control the distance the between the probe and the sample surface with high precision. In addition, the numerical reconstructed images are very stable against noise by only using the low frequency band of the far-field data in the numerical reconstruction.

Twin mechanisms: Rapid scene recognition involves both feedforward and feedback processing

The low spatial frequency (LSF) component of visual information rapidly conveyed coarse information for global perception, while the high spatial frequency (HSF) component delivered fine-grained information for detailed analyses. The feedforward theorists deemed that a coarse-to-fine process was sufficient for a rapid scene recognition. Based on the response priming paradigm, the present study aimed to deeply explore how different spatial frequency interacted with each other during rapid scene recognition. The response priming paradigm posited that as long as the prime slide could be rapidly recognized, the prime-target system was behaviorally equivalent to a feedforward system. Adopting broad spatial frequency images, experiment 1 revealed a typical response priming effect. But in experiment 2, when the HSF and the LSF components of the same pictures were separately presented, neither the LSF-to-HSF sequence nor the HSF-to-LSF sequence reproduced the response priming effect. These results demonstrated that LSF or HSF component alone was not sufficient for rapid scene recognition and, further, that the integration of different spatial frequency needed some early feedback loops. These findings supported that the local recurrent processing loops among early visual cortex was involved during rapid scene recognition.

Interaction between motion scales: When performance in motion discrimination is worse for a compound stimulus than for its integrating components

Motion direction discrimination becomes impaired when combinations of drifting high spatial frequency (HSF) and static low spatial frequency (LSF) patterns are merged into a compound stimulus. Such impairment has been suggested to occur due to an interaction between motion sensors tuned to coarse and fine scale spatial patterns. This interaction is modulated by different stimulus parameters like temporal frequency, size, the spectral components mixed, and their relative contrast. The present research precisely aims to explore in a deeper way the interaction’s dependency upon the spatial frequency and the relative contrast of the components when both move coherently. Two experiments were therefore performed measuring duration thresholds (Experiment 1) and proportion of correct responses (Experiment 2) in a motion direction discrimination task. Stimuli were vertical Gabor patches of 4 deg diameter horizontally drifting with a speed of 2 deg/sec. Simple LSF and HSF stimuli as well as complex stimuli where both components moved coherently (LSFm + HSFm) were used. These were grouped in the following LSF and HSF pairs: 0.25–0.75, 0.5–1.5, 1–3 and 2–6 c/deg. Each component had a Michelson contrast of 28% or 7%, giving rise to different relative contrast combinations. Most interestingly, the results show a decrease in performance for complex stimuli with respect to each of their simple components when the LSF component has a lower contrast than the HSF one. The decrease depends on the particular spatial frequencies mixed in a stimulus. Further knowledge about the inhibitory mechanism is thus provided, revealing its joint dependency upon contrast and spatial frequency.

Affective blindsight relies on low spatial frequencies

The human brain can process facial expressions of emotions rapidly and without awareness. Several studies in patients with damage to their primary visual cortices have shown that they may be able to guess the emotional expression on a face despite their cortical blindness. This non-conscious processing, called affective blindsight, may arise through an intact subcortical visual route that leads from the superior colliculus to the pulvinar, and thence to the amygdala. This pathway is thought to process the crude visual information conveyed by the low spatial frequencies of the stimuli.In order to investigate whether this is the case, we studied a patient (TN) with bilateral cortical blindness and affective blindsight. An fMRI paradigm was performed in which fearful and neutral expressions were presented using faces that were either unfiltered, or filtered to remove high or low spatial frequencies. Unfiltered fearful faces produced right amygdala activation although the patient was unaware of the presence of the stimuli. More importantly, the low spatial frequency components of fearful faces continued to produce right amygdala activity while the high spatial frequency components did not. Our findings thus confirm that the visual information present in the low spatial frequencies is sufficient to produce affective blindsight, further suggesting that its existence could rely on the subcortical colliculo-pulvino-amygdalar pathway.

Admissible Shape Parameters for a Planar Quasi-Static Constraint Mode Tire Model

Abstract : The interaction between the tire and terrain has long been of interest for vehicle dynamic simulation. Detailed tire models produce accurate results, but are too computationally intensive for the iterative vehicle design process. The objective of this work is to develop a computationally efficient way to estimate the tire's deformed shape, from which the tire forces can be evaluated. A novel, planar, quasi-static, constraint mode tire model is developed to address this objective. The required model parameters are reduced to two non-dimensional shape parameters and an overall stiffness factor. An admissible domain of the shape parameters is developed based on the deformation limitations of a physical tire. Specifically, no single harmonic may dominates the tire shape and the low spatial frequency components must contribute more than higher frequency components to the overall tire shape. The ability of the model to accurately predict the spindle force is evaluated by comparing simulation and experimental responses for quasi-static flat plate and cleat tests. This work provides a simple, accurate tire model for circumferential displacement and vertical spindle force prediction to improve the vehicle design process.

Development and testing of low spatial frequency holographic concentrator elements for collection of solar energy

Abstract The aim of this research is to use holographically recorded diffractive optical elements (DOEs) recorded in photopolymer in order to effectively collect and concentrate solar radiation. The potential for recording high diffraction efficiency DOEs with a large angular and wavelength range of operation in acrylamide based photopolymer and the optimum recording conditions have been presented in our previous work (Akbari et al., 2014b, 2014a). Theoretical modelling and experimental test are presented which demonstrate that low spatial frequency components, around 300 line pairs/mm, have an appropriate spectral bandwidth, high efficiency and very limited polarization dependence. Pairs of concentrating off-axis lenses are fabricated in photopolymer and arranged to concentrate light on a c-Si cell. The optical recording process is described and discussed. The results from electrical characterization confirm that with the (two) spherical DOEs (each of area 113 mm 2 ) in place, the output current of c-Si solar cells is approximately doubled for the solar cells with area of 12 mm 2 .

Early Recognition of Alzheimer’s Disease using Brain MRI

Abstract—Alzheimer’s disease (AD) is a brain disease that causes a slow decline in memory, thinking and reasoning skills. It represents a major public health problem. Magnetic Resonance Imaging (MRI) have shown that the brains of people with (AD) shrink significantly as the disease progresses. This shrinkage appears in specific brain regions such as the hippocampus which is a small, curved formation in the brain that plays an important role in the limbic system also involved in the formation of new memories and is also associated with learning and emotions. Medical information on brain MRI is used in detecting the abnormalities in physiological structures. Structural MRI measurements can detect and follow the evolution of brain atrophy which is a marker of the disease progression; therefore, it allows diagnosis and prediction of AD. The research’s main target is the early recognition of Alzheimer’s disease automatically, which will thereby avoid deterioration of the case resulting in complete brain damage stage. Alzheimer’s disease yields visible changes in the brain structures. The aim is to recognize if the patient belongs to Alzheimer’s disease category or a normal healthy person at an early stage.
 Initially, image pre-processing and features extraction techniques are applied including data reduction using Discrete Cosine Transform (DCT) and Cropping, then traditional classification techniques like Euclidean Distance, Chebyshev Distance, Cosine Distance, City Block Distance, and Black pixel counter, were applied on the resulting vectors for classification. Image pre-processing includes noise reduction, Gray-scale conversion and binary scale conversion were applied for the MRI images. Feature extraction techniques follow including cropping and low spatial frequency components (DCT). This paper aims to automatically recognize and detect Alzheimer’s infected brain using MRI, without the need of clinical expert. This early recognition would be helpful to postpone the disease progression and maintain it at an almost steady stage. It was concluded after collecting a dataset of 50 MRI , 25 for normal MRI and 25 for AD MRI that Chebyshev Distance classifier yielded the highest success rate in the recognition of Alzheimer’s disease with accuracy 94% compared to other classification techniques used where, Euclidean Distance is 91.6%, Cosine Distance is 86.8%, City block Distance is 89.6%, Correlation Distance is 86.4% and Black pixels counter is 90%.

Analysis of Fingerprint Image Enhancement using Gabor Filtering with Different Orientation Field Values

<p>Fingerprint image enhancement is the key process in IAFIS systems. In order to reduce false identification ratio and to supply good fingerprint images to IAFIS systems for exact identification, fingerprint images are generally enhanced. A filtering process tries to filter out the noise from the input image, and emphasize on low, high and directional spatial frequency components of an image. This paper presents an experimental summary of enhancing fingerprint images using Gabor filters. Frequency, width and window domain filter ranges are fixed. The orientation angle alone is modified by 0 radians, , and radians. The experimental results show that Gabor filter enhances the fingerprint image in a better way than other filtering methods and extracts features. </p>

A fast pathway for fear in human amygdala

A fast, subcortical pathway to the amygdala is thought to have evolved to enable rapid detection of threat. This pathway's existence is fundamental for understanding nonconscious emotional responses, but has been challenged as a result of a lack of evidence for short-latency fear-related responses in primate amygdala, including humans. We recorded human intracranial electrophysiological data and found fast amygdala responses, beginning 74-ms post-stimulus onset, to fearful, but not neutral or happy, facial expressions. These responses had considerably shorter latency than fear responses that we observed in visual cortex. Notably, fast amygdala responses were limited to low spatial frequency components of fearful faces, as predicted by magnocellular inputs to amygdala. Furthermore, fast amygdala responses were not evoked by photographs of arousing scenes, which is indicative of selective early reactivity to socially relevant visual information conveyed by fearful faces. These data therefore support the existence of a phylogenetically old subcortical pathway providing fast, but coarse, threat-related signals to human amygdala.

Synthesis of wave surface by frame loudspeaker array with limited spatial frequency band

We have studied a frame loudspeaker array for sound reproduction of three-dimensional television aiming at realizing clear localization and better sound depth control. Because such array has no secondary sources in its center region, the reproduced wave surface is sometimes deteriorated even if the least squares optimization will be used to reshape the surface. Over the past few decades, a considerable number of studies have been made on the sound field reproduction by loudspeaker array. Recently, higher order ambisonics (HOA) and near-field compensated HOA (NFC-HOA) attract attention of the researchers. It is well known that these methods can limit a spatial frequency band by controlling the degree of spherical function. If such limitation is introduced to the frame loudspeaker array, the deterioration of wave surface will be alleviated because the optimization will be easy to progress by matching only the low spatial frequency components of the reproduced wave surface with those of the reference. The co...

Examining the role of red background in magnocellular contribution to face perception.

This study examines the role of the magnocellular system in the early stages of face perception, in particular sex categorization. Utilizing the specific property of magnocellular suppression in red light, we investigated visually guided reaching to low and high spatial frequency hybrid faces against red and grey backgrounds. The arm movement curvature measure shows that reduced response of the magnocellular pathway interferes with the low spatial frequency component of face perception. This finding provides behavioral evidence for magnocellular contribution to non-emotional aspect of face perception.

Spatial Frequency Components of Images Modulate Neuronal Activity in Monkey Amygdala.

Processing the spatial frequency components of an image is a crucial feature for visual perception, especially in recognition of faces. Here, we study the correlation between spatial frequency components of images of faces and neuronal activity in monkey amygdala while performing a visual recognition task. The frequency components of the images were analyzed using a fast Fourier transform for 40 spatial frequency ranges. We recorded 65 neurons showing statistically significant responses to at least one of the images used as a stimulus. A total of 37 of these neurons (n = 37) showed significant responses to at least three images, and in eight of them (8/37, 22%), we found a statistically significant correlation between neuron response and the modulus amplitude of at least one frequency range present in the images. Our results indicate that high spatial frequency and low spatial frequency components of images influence the activity of amygdala neurons.