Simulation of the effect of local adaption with nonlinear spatial filters

The visual system of vertebrates is capable of processing pattern signals over a wide range of intensity reaching from nearly absolute darkness to very bright sunlight. Typically the visual system of humans extracts fine contours of patterns of sufficiently high intensity or at high background intensity level, showing signal processing properties which can be explained by a bandpass system. Conversely, at very low intensity levels that system shows low-pass response: only coarse contours of patterns are recognized, however, the amplification of the signals has increased. The effect is called local adaption. A model is shown on the basis of a one-stage nonlinear spatial filter which, controlled by the local distribution of pattern intensity, can alter its frequency characteristic between low-pass response and bandpass response. Results are stated for computer-modelled filters. The investigation is restricted to one-dimensional filters, however, the results can be used to explain the function of two-dimensional filters qualitatively.     

Local estimate of surface Laplacian derivation on a realistically shaped scalp surface and its performance on noisy data

A new implementation of the surface Laplacian derivation (SLD) method is desribed which reconstructs a realistically shaped, local scalp surface geometry using measured electrode positions, generates a local spectral-interpolated potential distribution function, and estimates the surface Laplacian values through a local planar parametric space using a stable numerical method combining Taylor expansions with the least-squares technique. The implementation is modified for efficient repeated SLD operations on a time series. Examples are shown of applications to evoked potential data. The resolving power of the SLD is examined as a function of the spatial signal-to-noise (SNR) ratio. The analysis suggests that the Laplacian is effective when the spatial SNR is greater than 3. It is shown that spatial low-pass filtering with a Gaussian filter can be used to reduce the effect of noise and recover useful signal if the noise is spatially incoherent.     

A model of the human visual system in its response to certain classes of moving stimuli

The purpose of this study is to construct a functional model of the human visual system in its response to certain classes of moving stimuli.Experimental data are presented describing the interdependence of the input variables, temporal frequency, spatial period, etc., for two constant response states, viz. threshold motion response and threshold flicker response. On the basis of these data, two basic units are isolated, a vertical (V) unit and a horizontal (H) unit. The H-unit is identified with the Reichardt multiplier (Reichardt and Varju, 1959), and the V-unit with the de Lange filter (de Lange, 1954).A definition of the general motion response of the H-units is obtained, and this is then reduced to an expression which may be applied directly to the observed motion response data. By this method, Thorson's simplification of the Reichardt scheme (Thorson, 1966) is adopted for the H-unit and total and relative (population) weighting factors, associated with the H-unit output, are defined.In order to reconcile the theoretical square-wave threshold motion response with the experimental data, Thorson's simplification is modified with the introduction of a low-pass filter on the output. The amended scheme is shown to predict a (temporal) frequency-dependent phase-sensitivity. This prediction is tested experimentally, and its validity indicated.     

Impacts of the murine skull on high‐frequency transcranial photoacoustic brain imaging

Non‐invasive photoacoustic tomography (PAT) of mouse brains with intact skulls has been a challenge due to the skull's strong acoustic attenuation, aberration, and reverberation, especially in the high‐frequency range (>15 MHz). In this paper, we systematically investigated the impacts of the murine skull on the photoacoustic wave propagation and on the PAT image reconstruction. We studied the photoacoustic acoustic wave aberration due to the acoustic impedance mismatch at the skull boundaries and the mode conversion between the longitudinal wave and shear wave. The wave's reverberation within the skull was investigated for both longitudinal and shear modes. In the inverse process, we reconstructed the transcranial photoacoustic computed tomography (PACT) and photoacoustic microscopy (PAM) images of a point target enclosed by the mouse skull, showing the skull's different impacts on both modalities. Finally, we experimentally validated the simulations by imaging an in vitro mouse skull phantom using representative transcranial PAM and PACT systems. The experimental results agreed well with the simulations and confirmed the accuracy of our forward and inverse models. We expect that our results will provide better understanding of the impacts of the murine skull on transcranial photoacoustic brain imaging and pave the ways for future technical improvements.      

Low-pass filtering, a new method of fractal analysis: application to PET images of pulmonary blood flow.

The pattern of a spatial structure that repeats itself independently of the scale of magnification or resolution is often characterized by a fractal dimension (D). Two-dimensional low-pass filtering, which may serve as a method to assess D, was applied to functional images of pulmonary perfusion measured by positron emission tomography. The corner frequency of a low-pass filter is inversely proportional to the resolution scale. The method was applied to three types of images: random noise images, synthetic fractal images, and positron emission tomographic images of pulmonary perfusion. Images were processed with two-dimensional low-pass filters of decreasing corner frequencies, and a spatial heterogeneity index, the coefficient of variation, was calculated for each low-pass-filtered image. The natural logarithm of the coefficient of variation scaled linearly with the natural logarithm of the resolution scale for the PET images studied (average R(2) = 0.99). D ranged from 1.25 to 1.36 for the residual distribution of pulmonary perfusion after vertical gradients were removed by linear regression. D of the same data without removal of vertical gradients ranged from 1.11 to 1.14, but the fractal plots had systematic deviations from linearity and a lower linear correlation coefficient (R(2) = 0. 96). The method includes all data in the lung field and is insensitive to the effects of misregistration. We conclude that low-pass filtering offers new insights into the interpretation of D of two-dimensional functional images as a measure of the frequency content of spatial heterogeneity.     

The neural basis of catalepsy in the stick insect cuniculina impigra

The femur-tibia control system which is responsible for catalepsy is studied in the open-loop configuration (input: stimulation of the femoral chordotonal organ; output: spike-frequency of FETi and SETi as well as the force produced by the extensor tibiae muscle). Comparison of motor neuron activities and muscle force reveals the input-output relationships of the extensor tibiae muscle. This muscle behaves like a low-pass filter with a small time constant for rising inputs and a large time constant for falling inputs. It forms the decisive low-pass filter for force production of the complete system. For freely moving tibia, the elastic properties of the muscles combined with the inert mass of the tibia contribute to the low-pass filter properties. The muscle does not contribute to the high-pass filter properties of the complete system. During repetitive stimulation FETi habituates quickly.Supported by DFG Ba 578     

The neural basis of catalepsy in the stick insect cuniculina impigra

Catalepsy in the femur-tibia joint can be characterized as follows: When the joint is passively bent and then released, the joint first extends rapidly by 10°–30° and then returns to its starting position with extremely low speed.Catalepsy is a characteristic of the femur-tibia control system. This system is quantitatively described in the open-loop configuration (input: stimulation of the femoral chordotonal organ; output: movement of the tibia). The output shows a predominant dynamic portion which only responds to movement and a weak static portion which responds to position. The dynamic portion can be described by a high-pass and a low-pass filter in series. The time constant of the high-pass filter in series. The time constant of the high-pass filter depends on input slope. The system possesses a large phase reserve and is therefore very stable in the closed loop configuration.The results confirm the hypothesis that the high gain of the phasmid control system evolved only under a selection pressure towards catalepsy.Supported by DFG Ba 578     

Internal models and intermittency: A theoretical account of human tracking behavior

This paper concerns the use of tracking studies to test a theoretical account of the information processing performed by the human CNS during control of movement. The theory provides a bridge between studies of reaction time and continuous tracking. It is proposed that the human CNS includes neuronal circuitry to compute inverse internal models of the multiple input, multiple output, dynamic, nonlinear relationships between outgoing motor commands and their resulting perceptual consequences. The inverse internal models are employed during movement execution to transform preplanned trajectories of desired perceptual consequences into appropriate outgoing motor commands to achieve them. A finite interval of time is required by the CNS to preplan the desired perceptual consequences of a movement and it does not commence planning a new movement until planning of the old one has been completed. This behavior introduces intermittency into the planning of movements. In this paper we show that the gain and phase frequency response characteristics of the human operator in a visual pursuit tracking task can be derived theoretically from these assumptions. By incorporating the effects of internal model inaccuracy and of speed-accuracy trade-off in performance, it is shown that various aspects of experimentally measured tracking behavior can be accounted for.     

Analysis and simulation of networks of mutually inhibiting neurons

Networks of mutually inhibiting neurons are analyzed and simulated on a digital computer. In the analysis and simulation a continuous-variable model of the neuron is used as the basic element. It consists of a many-input adder, a first-order low-pass filter and a diode-type nonlinearity. A mutually inhibiting network is formed by connecting the output of every element to inputs of the other elements through weight-coefficient setting units. Each element of the network is assumed to receive a certain number of constant inputs from elements of other networks.An autonomous system of nonlinear differential equations is introduced to describe the network dynamics, and the steady-state solutions of the system are investigated in detail. The network has a unique equilibrium solution, multiple equilibrium solutions or a periodic solution depending on the weight-coefficients and the inputs. It is shown that these three cases correspond to three types of information processing functions: the sharpening of input patterns, the temporary storage of information and the generation of periodic signals.     

Cerebral responses to change in spatial location of unattended sounds

The neural basis of spatial processing in the auditory cortex has been controversial. Human fMRI studies suggest that a part of the planum temporale (PT) is involved in auditory spatial processing, but it was recently argued that this region is active only when the task requires voluntary spatial localization. If this is the case, then this region cannot harbor an ongoing spatial representation of the acoustic environment. In contrast, we show in three fMRI experiments that a region in the human medial PT is sensitive to background auditory spatial changes, even when subjects are not engaged in a spatial localization task, and in fact attend the visual modality. During such times, this area responded to rare location shifts, and even more so when spatial variation increased, consistent with spatially selective adaptation. Thus, acoustic space is represented in the human PT even when sound processing is not required by the ongoing task.     

Human vision combines oriented filters to compute edges.

The experiments examined the perceived spatial structure of plaid patterns, composed of two or three sinusoidal gratings of the same spatial frequency, superimposed at different orientations. Perceived structure corresponded well with the pattern of zero crossings in the output of a circular spatial filter applied to the image. This lends some support to Marr & Hildreth's (Proc. R. Soc. Lond. B 207, 187 (1980)) theory of edge detection as a model for human vision, but with a very different implementation. The perceived structure of two-component plaids was distorted by prior exposure to a masking or adapting grating, in a way that was perceptually equivalent to reducing the contrast of one of the plaid components. This was confirmed by finding that the plaid distortion could be nulled by increasing the contrast of the masked or adapted component. A corresponding reduction of perceived contrast for single gratings was observed after adaptation and in some masking conditions. I propose the outlines of a model for edge finding in human vision. The plaid components are processed through cortical, orientation-selective filters that are subject to attenuation by forward masking and adaptation. The outputs of these oriented filters are then linearly summed to emulate circular filtering, and zero crossings (zcs) in the combined output are used to determine edge locations. Masking or adapting to a grating attenuates some oriented filters more than others, and although this changes only the effective contrast of the components, it results in a geometric distortion at the zc level after different filters have been combined. The orientation of zcs may not correspond at all with the orientation of Fourier components, but they are correctly predicted by this two-stage model. The oriented filters are not 'orientation detectors', but are precursors to a more subtle stage that locates and represents spatial features.     

Learning Oncogenic Pathways from Binary Genomic Instability Data

Summary Genomic instability, the propensity of aberrations in chromosomes, plays a critical role in the development of many diseases. High throughput genotyping experiments have been performed to study genomic instability in diseases. The output of such experiments can be summarized as high‐dimensional binary vectors, where each binary variable records aberration status at one marker locus. It is of keen interest to understand how aberrations may interact with each other, as it provides insight into the process of the disease development. In this article, we propose a novel method, LogitNet, to infer such interactions among these aberration events. The method is based on penalized logistic regression with an extension to account for spatial correlation in the genomic instability data. We conduct extensive simulation studies and show that the proposed method performs well in the situations considered. Finally, we illustrate the method using genomic instability data from breast cancer samples.     

Compensation of the low-pass filter properties of the current measuring internode in potential-clamped myelinated nerve fibres

The bandwidth of membrane current measurements in potential-clamped Ranvier nodes is limited by the low-pass filter properties of the internodes. If about 35% of the current measuring internode is grounded via an additional electrode, the bandwidth of this internode increases by a factor of about 40. Consequently, in potential clamp experiments the measured time course of the early ionic currents changes markedly, while the duration of the capacity current is shortened.     

Extraction of the energetics of selected types of motion from molecular dynamics trajectories by filtering

A novel method for analyzing molecular dynamics trajectories has been developed which enables the study of selected motions and the corresponding energetics. In particular, it is possible to filter out the high-frequency motions and focus on the structural and energetic features of low-frequency collective motions. The trajectories of the properties of interest are Fourier transformed to the frequency domain, a filtering function is applied, and then an inverse transformation back to the time domain yields the filtered trajectory. The method is demonstrated for harmonic fluctuations and conformational transitions of acetamide and N-acetylalanine N-methylamide, as models for peptides and proteins.     

Handling of impact forces in inverse dynamics

In the standard inverse dynamic method, joint moments are assessed from ground reaction force data and position data, where segmental accelerations are calculated by numerical differentiation of position data after low-pass filtering. This method falls short in analyzing the impact phase, e.g. landing after a jump, by underestimating the contribution of the segmental accelerations to the joint moment assessment. This study tried to improve the inverse dynamics method for the assessment of knee moment by evaluating different cutoff frequencies in low-pass filtering of position data on the calculation of knee moment. Next to this, the effect of an inclusion of direct measurement of segmental acceleration using accelerometers to the inverse dynamics was evaluated. Evidence was obtained that during impact, the contribution of the ground reaction force to the sagittal knee moment was neutralized by the moments generated by very high segmental accelerations. Because the accelerometer-based method did not result in the expected improvement of the knee moment assessment during activities with high impacts, it is proposed to filter the ground reaction force with the same cutoff frequency as the calculated accelerations. When this precaution is not taken, the impact peaks in the moments can be considered as artifacts. On the basis of these findings, we recommend in the search to biomechanical explanations of chronic overuse injuries, like jumper's knee, not to consider the relation with impact peak force and impact peak moment.     

A general solution for the time delay introduced by a low-pass Butterworth digital filter: An application to musculoskeletal modeling

Low-pass Butterworth digital filters are commonly used in biomechanics-related research. In general, the input signal is filtered in the forward and reverse directions so that a temporal shift in the output signal does not occur. There are times, however, when introducing a specific time delay is an important consideration when modeling a physiological event. Filtering the data in the forward direction only can be used as an efficient method to account for a specific time delay. Specific delays are possible by carefully selecting the filter order and cut-off frequency. The purpose of this paper is to present the analytical formulation of a general solution for the time delay introduced by a low-pass Butterworth digital filter.     

A protocol for Papanicolaou staining of cytologic specimens following flow analysis

A protocol has been developed for restaining cytologic specimens that have been analyzed on a multidimensional slit-scan flow system. The technique involves Papanicolaou staining of cells on a membrane filter that has been previously stained with acridine orange and fixed with glutaraldehyde buffer. The specimen and staining solutions were sequentially added to a 5-micrometers pore size, 47-mm diameter Gelman "Metricel" filter while it remained in a glass filtration apparatus. The practice of retaining the filter in the filtration apparatus throughout the staining procedure minimizes cell loss and eliminates specimen cross contamination when compared with conventional filter dip staining. The availability of this postflow specimen Papanicolaou staining protocol permits accurate determination of the performance characteristics of a multidimensional slit-scan flow system and should be useful whenever staining of a limited number of cells with minimal cell loss is desired.     

Elasmobranch eye motor dynamics characterised using pseudorandom stimulus

A pseudorandom binary sequence electrical pulse rate stimulus was delivered to the abducens nerve of an elasmobranch preparation. Ipsilateral eye movements were recorded using a position-sensitive photodiode to measure the position of a reflective patch attached to the fish's eye. Eye position data was cross-correlated with the stimulus pattern, and exponential decay curves were fitted to the cross-correlograms to estimate the time constant of a linear first order low-pass filter model. The cross-correlograms were transformed into the frequency domain using a Digital Fourier Transform, and Bode plots of eye dynamics were plotted. Eye motor plant dynamics in the elasmobranch Cephaloscyllium isabella can be accurately characterised by a linear first order low-pass filter model with a corner frequency of 0.73 +/- 0.10 Hz. Non-minimum phase lag reaches 90 degrees at about 4 Hz, indicating a time delay of some 50-60 ms. Integration of the canal signal is not required for producing compensatory eye movements above the characteristic frequency of the eye motor plant. However, the canal signal may be integrated to ensure that the vestibulo-ocular reflex is compensatory at lower frequencies. Substantial phase compensation or prediction is required for effective control of the vestibulo-ocular reflex.     

Spatial patterns in temperature sensitivity of soil respiration in China: Estimation with inverse modeling

Temperature sensitivity of soil respiration (Q₁₀) is an important parameter in modeling the effects of global warming on ecosystem carbon release. Experimental studies of soil respiration have ubiquitously indicated that Q₁₀ has high spatial heterogeneity. However, most biogeochemical models still use a constant Q₁₀ in projecting future climate change and no spatial pattern of Q₁₀ values at large scales has been derived. In this study, we conducted an inverse modeling analysis to retrieve the spatial pattern of Q₁₀ in China at 8 km spatial resolution by assimilating data of soil organic carbon into a process-based terrestrial carbon model (CASA model). The results indicate that the optimized Q₁₀ values are spatially heterogeneous and consistent to the values derived from soil respiration observations. The mean Q10 values of different soil types range from 1.09 to 2.38, with the highest value in volcanic soil, and the lowest value in cold brown calcic soil. The spatial pattern of Q₁₀ is related to environmental factors, especially precipitation and top soil organic carbon content. This study demonstrates that inverse modeling is a useful tool in deriving the spatial pattern of Q₁₀ at large scales, with which being incorporated into biogeochemical models, uncertainty in the projection of future carbon dynamics could be potentially reduced.     

Sounds audible to migrating birds

We have measured sound levels from frog choruses in eastern New York State at altitudes of up to several hundred metres. Rana pipiens choruses from small ponds often could be recorded by a radio microphone up to 500 m, and on an especially favourable night with light winds they were clearly audible even at 965 m at about 20 dB SPL in the 1·5 to 2·5 2·5 kHz frequency band. Sound travels upward much farther and more predictably than along the surface. Many natural sounds, including those from frogs, insects, whitecaps, and perhaps wind-blown vegetation, arise from large areas and therefore act as extended sources. The intensities of such sounds decrease with altitude more slowly than expected from the inverse square law. Natural sound fields provide migrating birds with a potential source of information about the kind of land or water below them, and their progress over acoustic landmarks could inform them about wind velocity. Because atmospheric absorption increases with frequency, several hundred metres of air act as a low-pass filter, so that altitude could be estimated from the relative reduction of higher frequencies in a familiar sound.