scholarly journals Measuring spectrally-resolved information transfer

2020 ◽  
Vol 16 (12) ◽  
pp. e1008526
Author(s):  
Edoardo Pinzuti ◽  
Patricia Wollstadt ◽  
Aaron Gutknecht ◽  
Oliver Tüscher ◽  
Michael Wibral
Keyword(s):  
Information Transfer ◽  
Partial Information ◽  
Temporal Cortex ◽  
Field Potential ◽  
Simulated Data ◽  
Distributed Computation ◽  
Transfer Entropy ◽  
Discrete Wavelet ◽  
Low Frequencies ◽  
High Frequencies

Information transfer, measured by transfer entropy, is a key component of distributed computation. It is therefore important to understand the pattern of information transfer in order to unravel the distributed computational algorithms of a system. Since in many natural systems distributed computation is thought to rely on rhythmic processes a frequency resolved measure of information transfer is highly desirable. Here, we present a novel algorithm, and its efficient implementation, to identify separately frequencies sending and receiving information in a network. Our approach relies on the invertible maximum overlap discrete wavelet transform (MODWT) for the creation of surrogate data in the computation of transfer entropy and entirely avoids filtering of the original signals. The approach thereby avoids well-known problems due to phase shifts or the ineffectiveness of filtering in the information theoretic setting. We also show that measuring frequency-resolved information transfer is a partial information decomposition problem that cannot be fully resolved to date and discuss the implications of this issue. Last, we evaluate the performance of our algorithm on simulated data and apply it to human magnetoencephalography (MEG) recordings and to local field potential recordings in the ferret. In human MEG we demonstrate top-down information flow in temporal cortex from very high frequencies (above 100Hz) to both similarly high frequencies and to frequencies around 20Hz, i.e. a complex spectral configuration of cortical information transmission that has not been described before. In the ferret we show that the prefrontal cortex sends information at low frequencies (4-8 Hz) to early visual cortex (V1), while V1 receives the information at high frequencies (> 125 Hz).

scholarly journals Measuring spectrally-resolved information transfer for sender- and receiver-specific frequencies

2020 ◽  
Author(s):  
Edoardo Pinzuti ◽  
Patricia Wollsdtadt ◽  
Aaron Gutknecht ◽  
Oliver Tüscher ◽  
Michael Wibral
Keyword(s):  
Information Transfer ◽  
Partial Information ◽  
Temporal Cortex ◽  
Object Perception ◽  
Distributed Computation ◽  
Transfer Entropy ◽  
Low Frequencies ◽  
High Frequencies ◽  
Very High Frequencies ◽  
Very High

AbstractInformation transfer, measured by transfer entropy, is a key component of distributed computation. It is therefore important to understand the pattern of information transfer in order to unravel the distributed computational algorithms of a system. Since in many natural systems distributed computation is thought to rely on rhythmic processes a frequency resolved measure of information transfer is highly desirable. Here, we present a novel algorithm, and its efficient implementation, to identify separately frequencies sending and receiving information in a network. Our approach relies on the invertible maximum overlap discrete wavelet transform (MODWT) for the creation of surrogate data in the computation of transfer entropy and entirely avoids filtering of the original signals. The approach thereby avoids well-known problems due to phase shifts or the ineffectiveness of filtering in the information theoretic setting. We also show that measuring frequency-resolved information transfer is a partial information decomposition problem that cannot be fully resolved to date and discuss the implications of this issue. Last, we evaluate the performance of our algorithm on simulated data and apply it to human magnetoencephalography (MEG) recordings and to local field potential recordings in the ferret. In human MEG we demonstrate top-down information flow in temporal cortex from very high frequencies (above 100Hz) to both similarly high frequencies and to frequencies around 20Hz, i.e. a complex spectral configuration of cortical information transmission that has not been described before. In the ferret we show that the prefrontal cortex sends information at low frequencies (4-8 Hz) to early visual cortex (V1), while V1 receives the information at high frequencies (> 125 Hz).Author SummarySystems in nature that perform computations typically consist of a large number of relatively simple but interacting parts. In human brains, for example, billions of neurons work together to enable our cognitive abilities. This well-orchestrated teamwork requires information to be exchanged very frequently. In many cases this exchange happens rhythmically and, therefore, it seems beneficial for our understanding of physical systems if we could link the information exchange to specific rhythms. We here present a method to determine which rhythms send, and which rhythms receive information. Since many rhythms can interact at both sender and receiver side, we show that the interpretation of results always needs to consider that the above problem is tightly linked to partial information decomposition - an intriguing problem from information theory only solved recently, and only partly. We applied our novel method to information transfer in the human inferior temporal cortex, a brain region relevant for object perception, and unexpectedly found information transfer originating at very high frequencies at 100Hz and then forking to be received at both similarly high but also much lower frequencies around 20Hz. These results overturn the current standard assumption that low frequencies send information to high frequencies.

scholarly journals Synergistic Information Transfer in the Global System of Financial Markets

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 1000
Author(s):  
Tomas Scagliarini ◽  
Luca Faes ◽  
Daniele Marinazzo ◽  
Sebastiano Stramaglia ◽  
Rosario N. Mantegna
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
Information Flow ◽  
Information Transfer ◽  
Partial Information ◽  
Higher Order ◽  
Transfer Entropy ◽  
Order Effects ◽  
Target Market ◽  
Stock Market Index

Uncovering dynamic information flow between stock market indices has been the topic of several studies which exploited the notion of transfer entropy or Granger causality, its linear version. The output of the transfer entropy approach is a directed weighted graph measuring the information about the future state of each target provided by the knowledge of the state of each driving stock market index. In order to go beyond the pairwise description of the information flow, thus looking at higher order informational circuits, here we apply the partial information decomposition to triplets consisting of a pair of driving markets (belonging to America or Europe) and a target market in Asia. Our analysis, on daily data recorded during the years 2000 to 2019, allows the identification of the synergistic information that a pair of drivers carry about the target. By studying the influence of the closing returns of drivers on the subsequent overnight changes of target indexes, we find that (i) Korea, Tokyo, Hong Kong, and Singapore are, in order, the most influenced Asian markets; (ii) US indices SP500 and Russell are the strongest drivers with respect to the bivariate Granger causality; and (iii) concerning higher order effects, pairs of European and American stock market indices play a major role as the most synergetic three-variables circuits. Our results show that the Synergy, a proxy of higher order predictive information flow rooted in information theory, provides details that are complementary to those obtained from bivariate and global Granger causality, and can thus be used to get a better characterization of the global financial system.

An Adaptive Binarization Method for Cost-efficient Document Image System in Wavelet Domain

2020 ◽  
Vol 64 (3) ◽  
pp. 30401-1-30401-14 ◽  
Author(s):  
Chih-Hsien Hsia ◽  
Ting-Yu Lin ◽  
Jen-Shiun Chiang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Document Image ◽  
Background Information ◽  
Raspberry Pi ◽  
Discrete Wavelet ◽  
Image System ◽  
Low Frequencies ◽  
Cost Efficient ◽  
Binarization Method

Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized. However, the selection of different thicknesses of the paper for printing or writing is likely to make the content of the back page seep into the front page. In order to solve this, a cost-efficient document image system is proposed. In this system, the authors use Adaptive Directional Lifting-Based Discrete Wavelet Transform to transform image data from spatial domain to frequency domain and perform on high and low frequencies, respectively. For low frequencies, the authors use local threshold to remove most background information. For high frequencies, they use modified Least Mean Square training algorithm to produce a unique weighted mask and perform convolution on original frequency, respectively. Afterward, Inverse Adaptive Directional Lifting-Based Discrete Wavelet Transform is performed to reconstruct the four subband images to a resulting image with original size. Finally, a global binarization method, Otsu’s method, is applied to transform a gray scale image to a binary image as the output result. The results show that the difference in operation time of this work between a personal computer (PC) and Raspberry Pi is little. Therefore, the proposed cost-efficient document image system which performed on Raspberry Pi embedded platform has the same performance and obtains the same results as those performed on a PC.

scholarly journals Bayesian modeling and significant features exploration in wavelet power spectra

2007 ◽  
Vol 14 (1) ◽  
pp. 79-88 ◽  
Author(s):  
D. V. Divine ◽  
F. Godtliebsen
Keyword(s):  
Data Analysis ◽  
Traditional Approach ◽  
Statistical Significance ◽  
Power Spectra ◽  
Simulated Data ◽  
Scale Space ◽  
Independent Random Variables ◽  
Discrete Wavelet ◽  
Wavelet Coefficients ◽  
Testing Procedures

Abstract. This study proposes and justifies a Bayesian approach to modeling wavelet coefficients and finding statistically significant features in wavelet power spectra. The approach utilizes ideas elaborated in scale-space smoothing methods and wavelet data analysis. We treat each scale of the discrete wavelet decomposition as a sequence of independent random variables and then apply Bayes' rule for constructing the posterior distribution of the smoothed wavelet coefficients. Samples drawn from the posterior are subsequently used for finding the estimate of the true wavelet spectrum at each scale. The method offers two different significance testing procedures for wavelet spectra. A traditional approach assesses the statistical significance against a red noise background. The second procedure tests for homoscedasticity of the wavelet power assessing whether the spectrum derivative significantly differs from zero at each particular point of the spectrum. Case studies with simulated data and climatic time-series prove the method to be a potentially useful tool in data analysis.

Effect of Blowing Agent on Cell Morphology and Acoustic Absorption of Natural Rubber Foam

2015 ◽  
Vol 804 ◽  
pp. 25-29 ◽  
Author(s):  
Wanlop Harnnarongchai ◽  
Kantima Chaochanchaikul
Keyword(s):  
Natural Rubber ◽  
Cell Size ◽  
Cell Morphology ◽  
Foam Cell ◽  
Adsorption Coefficient ◽  
Low Frequencies ◽  
Potassium Oleate ◽  
High Frequencies ◽  
Blowing Agent ◽  
Open Cell Foam

The sound absorbing efficiency of natural rubber (NR) foam is affected by the cell morphology of foam. Potassium oleate (K-oleate) and sodium bicarbonate (NaHCO3) were used as blowing agents to create open-cell foam. Amounts of the blowing agent were varied from 0.5 to 8.0 part per hundred of rubber (phr) to evaluate cell size and number of foam cell as well as sound adsorption coefficient of NR foam. The NR foam specimens were prepared using mould and air-circulating oven for vulcanizing and foaming processes. The results indicated that K-oleate at 2.0 phr and NaHCO3 at 0.5 phr led to form NR foam with the smallest cell size and the largest number of foam cell. At low frequencies, the optimum sound adsorption coefficient of NR foam was caused by filling K-oleate 2 phr. However, that of NR foam at high frequencies was provided by 0.5 phr-NaHCO3 addition.

Hearing loss in diabetics

1993 ◽  
Vol 107 (3) ◽  
pp. 179-182 ◽  
Author(s):  
J. R. Cullen ◽  
M. J. Cinnamond
Keyword(s):  
Hearing Loss ◽  
Sensorineural Deafness ◽  
Insulin Dosage ◽  
Speech Discrimination ◽  
Low Frequencies ◽  
High Frequencies ◽  
History Of ◽  
Insulin Dependent ◽  
Stapedial Reflex ◽  
The Relationship

The relationship between diabetes and senbsorineural hearing loss has been disputed. This study compares 44 insulin-dependent diabetics with 38 age and sex matched controls. All had pure tone and speech audiometry performed, with any diabetics showing sensorineural deafness undergoing stapedial reflecx decat tests. In 14 diabetics stapedial reflex tests showed no tone decay in any patient, but seven showed evidence of recruitment. Analysis of vaiance showed the diabetics to be significantly deafer than the control population.The hearing loss affected high frequencies in both sexes, but also low frequencies in the male. Speech discrimination scores showed no differences. Further analysis by sex showed the males to account for most of the differences. Analysys of the audiograms showered mostly a high tone loss. Finally duration of disbetes, insulin dosage and family history of diabtes were not found to have a significant effect on threshold.

Use of Measured Mobility to Improve SEA Predictions in the Mid-Frequency Range

1999 ◽  
Author(s):  
Jerome E. Manning
Keyword(s):  
Dynamic Systems ◽  
Broad Band ◽  
Measured Data ◽  
Hybrid Technique ◽  
Complex Dynamic ◽  
Low Frequencies ◽  
Large Variability ◽  
High Frequencies ◽  
Complex Dynamic Systems ◽  
Light Coupling

Abstract Statistical energy analysis provides a technique to predict acoustic and vibration levels in complex dynamic systems. The technique is most useful for broad-band excitation at high frequencies where many modes contribute to the response in any given frequency band. At mid and low frequencies, the number of modes contributing to the response may be quite small. In this case SEA predictions show large variability from measured data and may not be useful for vibroacoustic design. This paper focuses on the use of measured data to improve the accuracy of the predictions. Past work to measure the SEA coupling and damping loss factors has not been successful for a broad range of systems that do not have light coupling. This paper introduces a new hybrid SEA technique that combines measured mobility functions with analytical SEA predictions. The accuracy of the hybrid technique is shown to be greatly improved at mid and low frequencies.

Frequency-Weighted Variable-Length Controllers Using Anytime Control Strategies

2011 ◽  
Author(s):  
Gundula B. Runge ◽  
Al Ferri ◽  
Bonnie Ferri
Keyword(s):  
Time Scale ◽  
Weighting Function ◽  
Control Strategies ◽  
Low Frequency ◽  
Low Frequencies ◽  
High Frequencies ◽  
Frequency Components ◽  
Computational Resources ◽  
Weighted Variable ◽  
Selection Of

This paper considers an anytime strategy to implement controllers that react to changing computational resources. The anytime controllers developed in this paper are suitable for cases when the time scale of switching is in the order of the task execution time, that is, on the time scale found commonly with sporadically missed deadlines. This paper extends the prior work by developing frequency-weighted anytime controllers. The selection of the weighting function is driven by the expectation of the situations that would require anytime operation. For example, if the anytime operation is due to occasional and isolated missed deadlines, then the weighting on high frequencies should be larger than that for low frequencies. Low frequency components will have a smaller change over one sample time, so failing to update these components for one sample period will have less effect than with the high frequency components. An example will be included that applies the anytime control strategy to a model of a DC motor with deadzone and saturation nonlinearities.

scholarly journals The Estimation of Hydrometeor Profiles from Wideband Microwave Observations

2000 ◽  
Vol 39 (10) ◽  
pp. 1645-1656 ◽  
Author(s):  
Gail M. Skofronick-Jackson ◽  
James R. Wang
Keyword(s):  
High Frequency ◽  
Cloud Water ◽  
Tropical Ocean ◽  
Low Frequencies ◽  
High Frequencies ◽  
Atmospheric Research ◽  
Brightness Temperatures ◽  
Microphysical Properties ◽  
Ice Microphysics ◽  
Updraft Region

Abstract Profiles of the microphysical properties of clouds and rain cells are essential in many areas of atmospheric research and operational meteorology. To enhance the understanding of the nonlinear and underconstrained relationships between cloud and hydrometeor microphysical profiles and passive microwave brightness temperatures, estimations of cloud profiles for an anvil region, a convective region, and an updraft region of an oceanic squall were performed. The estimations relied on comparisons between radiative transfer calculations of incrementally estimated microphysical profiles and concurrent dual-altitude wideband brightness temperatures from the 22 February 1993 flight during the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment. The wideband observations (10–220 GHz) are necessary for estimating cloud profiles reaching up to 20 km. The low frequencies enhance the rain and cloud water profiles, and the high frequencies are required to detail the higher-altitude ice microphysics. A microphysical profile was estimated for each of the three regions of the storm. Each of the three estimated profiles produced calculated brightness temperatures within ∼10 K of the observations. A majority of the total iterative adjustments were to the estimated profile’s frozen hydrometeor characteristics and were necessary to match the high-frequency calculations with the observations. This requirement indicates a need to validate cloud-resolving models using high frequencies. Some difficulties matching the 37-GHz observation channels on the DC-8 and ER-2 aircraft with the calculations simulated at the two aircraft heights (∼11 km and 20 km, respectively) were noted, and potential causes were presented.

scholarly journals Near-optimal decoding of transient stimuli from coupled neuronal subpopulations

2014 ◽  
Author(s):  
James Trousdale ◽  
Samuel R. Carroll ◽  
Fabrizio Gabbiani ◽  
Krešimir Josić
Keyword(s):  
Visual Processing ◽  
Information Transfer ◽  
Partial Information ◽  
Rotation Axis ◽  
Biophysical Model ◽  
General Mechanism ◽  
Small Subset ◽  
Vertical System ◽  
Optimal Decoding

Coupling between sensory neurons impacts their tuning properties and correlations in their responses. How such coupling affects sensory representations and ultimately behavior remains unclear. We investigated the role of neuronal coupling during visual processing using a realistic biophysical model of the vertical system (VS) cell network in the blow fly. These neurons are thought to encode the horizontal rotation axis during rapid free flight manoeuvres. Experimental findings suggest neurons of the vertical system are strongly electrically coupled, and that several downstream neurons driving motor responses to ego-rotation receive inputs primarily from a small subset of VS cells. These downstream neurons must decode information about the axis of rotation from a partial readout of the VS population response. To investigate the role of coupling, we simulated the VS response to a variety of rotating visual scenes and computed optimal Bayesian estimates from the relevant subset of VS cells. Our analysis shows that coupling leads to near-optimal estimates from a subpopulation readout. In contrast, coupling between VS cells has no impact on the quality of encoding in the response of the full population. We conclude that coupling at one level of the fly visual system allows for near-optimal decoding from partial information at the subsequent, pre-motor level. Thus, electrical coupling may provide a general mechanism to achieve near-optimal information transfer from neuronal subpopulations across organisms and modalities.

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