The complex fluctuations of probabilistic Boolean networks

Probabilistic Boolean networks (PBNs) are extensions of Boolean networks (BNs), and both have been widely used to model biological systems. In this paper, we study the long-range correlations of PBNs based on their corresponding Markov chains. PBN states are quantified by the deviation of their steady-state distributions. The results demonstrate that, compared with BNs, PBNs can exhibit these dynamics over a wider and higher noise range. In addition, the constituent BNs significantly impact the generation of 1/f dynamics of PBNs, and PBNs with homogeneous steady-state distributions tend to sustain the 1/f dynamics over a wider noise range.     

Alpha blocking and 1/fβ spectral scaling in resting EEG can be accounted for by a sum of damped alpha band oscillatory processes

The dynamical and physiological basis of alpha band activity and 1/f^β noise in the EEG are the subject of continued speculation. Here we conjecture, on the basis of empirical data analysis, that both of these features may be economically accounted for through a single process if the resting EEG is conceived of being the sum of multiple stochastically perturbed alpha band damped linear oscillators with a distribution of dampings (relaxation rates). The modulation of alpha-band and 1/f^β noise activity by changes in damping is explored in eyes closed (EC) and eyes open (EO) resting state EEG. We aim to estimate the distribution of dampings by solving an inverse problem applied to EEG power spectra. The characteristics of the damping distribution are examined across subjects, sensors and recording condition (EC/EO). We find that there are robust changes in the damping distribution between EC and EO recording conditions across participants. The estimated damping distributions are found to be predominantly bimodal, with the number and position of the modes related to the sharpness of the alpha resonance and the scaling (β) of the power spectrum (1/f^β). The results suggest that there exists an intimate relationship between resting state alpha activity and 1/f^β noise with changes in both governed by changes to the damping of the underlying alpha oscillatory processes. In particular, alpha-blocking is observed to be the result of the most weakly damped distribution mode becoming more heavily damped. The results suggest a novel way of characterizing resting EEG power spectra and provides new insight into the central role that damped alpha-band activity may play in characterising the spatio-temporal features of resting state EEG.     

Deep learning-based reconstruction in ultra-high-resolution computed tomography: Can image noise caused by high definition detector and the miniaturization of matrix element size be improved?

PurposeThis study aimed to assess the noise characteristics of ultra-high-resolution computed tomography (UHRCT) with deep learning-based reconstruction (DLR).MethodsTwo different diameters of water phantom were scanned with three different resolution acquisition modes. Images were reconstructed by filtered back projection (FBP), hybrid iterative reconstruction (hybrid-IR), and DLR. Image noise analysis was performed with noise magnitude, peak frequency (f_p) of the noise power spectrum (NPS), and the square root of the area under the curve (√AUC_NPS) for the NPS curve.ResultsThe noise magnitude was up to 3.30 times higher for the FBP acquired in SHR mode than that for the NR mode.The f_p values of the FBP were 0.20–0.21, 0.34–0.36, and 0.34–0.37 cycles/mm for normal resolution (NR), high resolution (HR), and super high resolution (SHR) mode, respectively. The f_p of hybrid-IR was 0.16–0.19, 0.21–0.26, and 0.23–0.26 cycles/mm for NR, HR, and SHR mode, respectively. The f_p of DLR was 0.21–0.32 and 0.22–0.33 cycles/mm for HR and SHR mode, respectively.√AUC_NPS showed that the highest value in FBP images of the SHR mode was up to 1.89 times that of the NR mode. DLR in the HR and SHR modes showed high noise reduction while suppressing f_p shift with respect to FBP.ConclusionsThe new DLR algorithm could be a solution to the noise increase due to the high-definition detector elements and the small reconstruction matrix element size.     

Visuospatial Tasks Affect Locomotor Control More than Nonspatial Tasks in Older People

Background

Previous research has shown that visuospatial processing requiring working memory is particularly important for balance control during standing and stepping, and that limited spatial encoding contributes to increased interference in postural control dual tasks. However, visuospatial involvement during locomotion has not been directly determined. This study examined the effects of a visuospatial cognitive task versus a nonspatial cognitive task on gait speed, smoothness and variability in older people, while controlling for task difficulty.

Methods

Thirty-six people aged ≥75 years performed three walking trials along a 20 m walkway under the following conditions: (i) an easy nonspatial task; (ii) a difficult nonspatial task; (iii) an easy visuospatial task; and (iv) a difficult visuospatial task. Gait parameters were computed from a tri-axial accelerometer attached to the sacrum. The cognitive task response times and percentage of correct answers during walking and seated trials were also computed.

Results

No significant differences in either cognitive task type error rates or response times were evident in the seated conditions, indicating equivalent task difficulty. In the walking trials, participants responded faster to the visuospatial tasks than the nonspatial tasks but at the cost of making significantly more cognitive task errors. Participants also walked slower, took shorter steps, had greater step time variability and less smooth pelvis accelerations when concurrently performing the visuospatial tasks compared with the nonspatial tasks and when performing the difficult compared with the easy cognitive tasks.

Conclusions

Compared with nonspatial cognitive tasks, visuospatial cognitive tasks led to a slower, more variable and less smooth gait pattern. These findings suggest that visuospatial processing might share common networks with locomotor control, further supporting the hypothesis that gait changes during dual task paradigms are not simply due to limited attentional resources but to competition for common networks for spatial information encoding.     

Energy Detection Based on Undecimated Discrete Wavelet Transform and Its Application in Magnetic Anomaly Detection

Magnetic anomaly detection (MAD) is a passive approach for detection of a ferromagnetic target, and its performance is often limited by external noises. In consideration of one major noise source is the fractal noise (or called 1/f noise) with a power spectral density of 1/f^a (0<a<2), which is non-stationary, self-similarity and long-range correlation. Meanwhile the orthonormal wavelet decomposition can play the role of a Karhunen-Loève-type expansion to the 1/f-type signal by its decorrelation abilities, an effective energy detection method based on undecimated discrete wavelet transform (UDWT) is proposed in this paper. Firstly, the foundations of magnetic anomaly detection and UDWT are introduced in brief, while a possible detection system based on giant magneto-impedance (GMI) magnetic sensor is also given out. Then our proposed energy detection based on UDWT is described in detail, and the probabilities of false alarm and detection for given the detection threshold in theory are presented. It is noticeable that no a priori assumptions regarding the ferromagnetic target or the magnetic noise probability are necessary for our method, and different from the discrete wavelet transform (DWT), the UDWT is shift invariant. Finally, some simulations are performed and the results show that the detection performance of our proposed detector is better than that of the conventional energy detector even utilized in the Gaussian white noise, especially when the spectral parameter α is less than 1.0. In addition, a real-world experiment was done to demonstrate the advantages of the proposed method.     

<Emphasis Type="Italic">PLP1</Emphasis> Gene Variation Modulates Leftward and Rightward Functional Hemispheric Asymmetries

Molecular neurobiological factors determining corpus callosum physiology and anatomy have been suggested to be one of the major factors determining functional hemispheric asymmetries. Recently, it was shown that allelic variations in two myelin-related genes, the proteolipid protein 1 gene PLP1 and the contactin 1 gene CNTN1, are associated with differences in interhemispheric integration. Here, we investigated whether three single nucleotide polymorphisms that were associated with interhemispheric integration via the corpus callosum in a previous study also are relevant for functional hemispheric asymmetries. To this end, we tested more than 900 healthy adults with the forced attention dichotic listening task, a paradigm to assess language lateralization and its modulation by cognitive control processes. Moreover, we used the line bisection task, a paradigm to assess functional hemispheric asymmetries in spatial attention. We found that a polymorphism in PLP1, but not CNTN1, was associated with performance differences in both tasks. Both functional hemispheric asymmetries and their modulation by cognitive control processes were affected. These findings suggest that both left and right hemisphere dominant cognitive functions can be modulated by allelic variation in genes affecting corpus callosum structure. Moreover, higher order cognitive processes may be relevant parameters when investigating the molecular basis of hemispheric asymmetries.     

Retinal Vascular Fractal Dimension,Childhood IQ,and Cognitive Ability in Old Age: The Lothian Birth Cohort Study 1936

Purpose

Cerebral microvascular disease is associated with dementia. Differences in the topography of the retinal vascular network may be a marker for cerebrovascular disease. The association between cerebral microvascular state and non-pathological cognitive ageing is less clear, particularly because studies are rarely able to adjust for pre-morbid cognitive ability level. We measured retinal vascular fractal dimension (D _f) as a potential marker of cerebral microvascular disease. We examined the extent to which it contributes to differences in non-pathological cognitive ability in old age, after adjusting for childhood mental ability.

Methods

Participants from the Lothian Birth Cohort 1936 Study (LBC1936) had cognitive ability assessments and retinal photographs taken of both eyes aged around 73 years (n = 648). IQ scores were available from childhood. Retinal vascular D _f was calculated with monofractal and multifractal analysis, performed on custom-written software. Multiple regression models were applied to determine associations between retinal vascular D _f and general cognitive ability (g), processing speed, and memory.

Results

Only three out of 24 comparisons (two eyes × four D _f parameters × three cognitive measures) were found to be significant. This is little more than would be expected by chance. No single association was verified by an equivalent association in the contralateral eye.

Conclusions

The results show little evidence that fractal measures of retinal vascular differences are associated with non-pathological cognitive ageing.     

Traffic noise inhibits cognitive performance in a songbird

Noise pollution is commonly associated with human environments and mounting evidence indicates that noise has a variety of negative effects on wildlife. Noise has also been linked to cognitive impairment in humans and because many animals use cognitively intensive processes to overcome environmental challenges, noise pollution has the potential to interfere with cognitive function in animals living in urban areas or near roads. We experimentally examined how road traffic noise impacts avian cognitive performance by testing adult zebra finches (Taeniopygia guttata) on a battery of foraging tasks in the presence or absence of traffic noise playback. Here, we show that traffic noise reduces cognitive performance, including inhibitory control, motor learning, spatial memory and social learning, but not associative colour learning. This study demonstrates a novel mechanism through which anthropogenic noise can impact animals, namely through cognitive interference, and suggests that noise pollution may have previously unconsidered consequences for animals.     

Microscopic Modelling Circadian and Bursty Pattern of Human Activities

Recent studies for a wide range of human activities such as email communication, Web browsing, and library visiting, have revealed the bursty nature of human activities. The distribution of inter-event times (IETs) between two consecutive human activities exhibits a heavy-tailed decay behavior and the oscillating pattern with a one-day period, reflective of the circadian pattern of human life. Even though a priority-based queueing model was successful as a basic model for understanding the heavy-tailed behavior, it ignored important ingredients, such as the diversity of individual activities and the circadian pattern of human life. Here, we collect a large scale of dataset which contains individuals’ time stamps when articles are posted on blog posts, and based on which we construct a theoretical model which can take into account of both ignored ingredients. Once we identify active and inactive time intervals of individuals and remove the inactive time interval, thereby constructing an ad hoc continuous time domain. Therein, the priority-based queueing model is applied by adjusting the arrival and the execution rates of tasks by comparing them with the activity data of individuals. Then, the obtained results are transferred back to the real-time domain, which produces the oscillating and heavy-tailed IET distribution. This microscopic model enables us to develop theoretical understanding towards more empirical results.     

Use of linear mixed models for genetic evaluation of gestation length and birth weight allowing for heavy-tailed residual effects

Background

The distribution of residual effects in linear mixed models in animal breeding applications is typically assumed normal, which makes inferences vulnerable to outlier observations. In order to mute the impact of outliers, one option is to fit models with residuals having a heavy-tailed distribution. Here, a Student''s-t model was considered for the distribution of the residuals with the degrees of freedom treated as unknown. Bayesian inference was used to investigate a bivariate Student''s-t (BSt) model using Markov chain Monte Carlo methods in a simulation study and analysing field data for gestation length and birth weight permitted to study the practical implications of fitting heavy-tailed distributions for residuals in linear mixed models.

Methods

In the simulation study, bivariate residuals were generated using Student''s-t distribution with 4 or 12 degrees of freedom, or a normal distribution. Sire models with bivariate Student''s-t or normal residuals were fitted to each simulated dataset using a hierarchical Bayesian approach. For the field data, consisting of gestation length and birth weight records on 7,883 Italian Piemontese cattle, a sire-maternal grandsire model including fixed effects of sex-age of dam and uncorrelated random herd-year-season effects were fitted using a hierarchical Bayesian approach. Residuals were defined to follow bivariate normal or Student''s-t distributions with unknown degrees of freedom.

Results

Posterior mean estimates of degrees of freedom parameters seemed to be accurate and unbiased in the simulation study. Estimates of sire and herd variances were similar, if not identical, across fitted models. In the field data, there was strong support based on predictive log-likelihood values for the Student''s-t error model. Most of the posterior density for degrees of freedom was below 4. Posterior means of direct and maternal heritabilities for birth weight were smaller in the Student''s-t model than those in the normal model. Re-rankings of sires were observed between heavy-tailed and normal models.

Conclusions

Reliable estimates of degrees of freedom were obtained in all simulated heavy-tailed and normal datasets. The predictive log-likelihood was able to distinguish the correct model among the models fitted to heavy-tailed datasets. There was no disadvantage of fitting a heavy-tailed model when the true model was normal. Predictive log-likelihood values indicated that heavy-tailed models with low degrees of freedom values fitted gestation length and birth weight data better than a model with normally distributed residuals.Heavy-tailed and normal models resulted in different estimates of direct and maternal heritabilities, and different sire rankings. Heavy-tailed models may be more appropriate for reliable estimation of genetic parameters from field data.     

Noise analysis and relaxation experiments of transport of hydrophobic anions across lipid membranes at equilibrium and nonequilibrium

Under equilibrium and nonequilibnum steady-stale conditions the spectral intensity of current noise S_J(f) generated by the transport of hydrophobic unions across lipid bilayer membranes was investigated. The experimental results were compared with different reaction models S_J(f) showed a characteristic increase proportional to f² between frequency-independent tails at low and high frequencies. This gradient was found to be independent of applied voltage which indicates the contribution of a single voltage-dependent reaction step of ion translocation across the membrane From the shape of S_J(f) at low frequencies the rate constant of ion desorption from the membrane into the aqueous phase could be estimated. Unambiguous evidence for the application of a general model, which includes the coupling of slow ion diffusion in the aqueous phase to ion adsorption/desorption at the membrane interface, could not be obtained from the low-frequency shape of S_J(f). The shot noise of this ion transport determines the amplitude of S_J(f) at high frequencies which decreases with increasing voltage applied. Analysis of voltage-jump current-relaxation experiments and of current noise carried cut on one membrane yielded significant differences of the derived ion partition coefficient. This deviation is qualitatively described on the basis of incomplete reaction steps.     

Power spectra of extinction in the fossil record

Recent Fourier analyses of fossil extinction data have indicated that the power spectrum of extinction during the Phanerozoic may take the form of 1/f noise, a result which, it has been suggested, could be indicative of the presence of `critical dynamics'' in the processes giving rise to extinction. In this paper we examine extinction power spectra in some detail, using family-level data from two widely available compilations. We find that although the average form of the power spectrum roughly obeys the 1/f law, the spectrum can be represented more accurately by dividing it into two regimes: a low-frequency one which is well fit by an exponential, and a high-frequency one in which it follows a power law with a 1/f² form. We give explanations for the occurrence of each of these behaviours and for the position of the crossover between them.     

Unexpected Dual Task Benefits on Cycling in Parkinson Disease and Healthy Adults: A Neuro-Behavioral Model

BackgroundWhen performing two tasks at once, a dual task, performance on one or both tasks typically suffers. People with Parkinson’s disease (PD) usually experience larger dual task decrements on motor tasks than healthy older adults (HOA). Our objective was to investigate the decrements in cycling caused by performing cognitive tasks with a range of difficulty in people with PD and HOAs.MethodsTwenty-eight participants with Parkinson’s disease and 20 healthy older adults completed a baseline cycling task with no secondary tasks and then completed dual task cycling while performing 12 tasks from six cognitive domains representing a wide range of difficulty.ResultsCycling was faster during dual task conditions than at baseline, and was significantly faster for six tasks (all p<.02) across both groups. Cycling speed improved the most during the easiest cognitive tasks, and cognitive performance was largely unaffected. Cycling improvement was predicted by task difficulty (p<.001). People with Parkinson’s disease cycled slower (p<.03) and showed reduced dual task benefits (p<.01) than healthy older adults.ConclusionsUnexpectedly, participants’ motor performance improved during cognitive dual tasks, which cannot be explained in current models of dual task performance. To account for these findings, we propose a model integrating dual task and acute exercise approaches which posits that cognitive arousal during dual tasks increases resources to facilitate motor and cognitive performance, which is subsequently modulated by motor and cognitive task difficulty. This model can explain both the improvement observed on dual tasks in the current study and more typical dual task findings in other studies.     

Unified theory of 1f and conductance noise in nerve membrane

A theory of $\text{1}\text{f}$ and conductance noise is given for ionic channels in nerve membrane. The theory is based on the assumption that the channels are in constant, stochastically independent, rotational motion within a fluid bilayer membrane. The resulting expression for the current noise power density S contains a conduction noise term consistent withStevens (1972) and Hill & Chen (1972) and a $\text{1}\text{f}$ noise term consistent with Lundstrom & McQueen (1974) and Clay & Shlesinger (1976). The expression for S also contains a third term which is the spectrum of the product of the single channel conduction noise and $\text{1}\text{f}$ noise correlation functions. This term is independent of the number of channels in the membrane, R. Consequently, the expression for S effectively reduces to a sum of $\text{1}\text{f}$ and conduction noise for R 10–100 which is in agreement with noise measurements on squid axon. The theory is applied in detail to potassium squid noise measurements of Conti, DeFelice & Wanke (1975) using the stochastic analysis of single file ion motion developed in our previous paper (Clay & Shlesinger (1976)).     

Random currents through nerve membranes

The linear cable equation with uniform Poisson or white noise input current is employed as a model for the voltage across the membrane of a onedimensional nerve cylinder, which may sometimes represent the dendritic tree of a nerve cell. From the Green's function representation of the solutions, the mean, variance and covariance of the voltage are found. At large times, the voltage becomes asymptotically wide-sense stationary and we find the spectral density functions for various cable lengths and boundary conditions. For large frequencies the voltage exhibits “1/f ^3/2 noise”. Using the Fourier series representation of the voltage we study the moments of the firing times for the diffusion model with numerical techniques, employing a simplified threshold criterion. We also simulate the solution of the stochastic cable equation by two different methods in order to estimate the moments and density of the firing time.     

Competitive blocking of apical sodium channels in epithelia

Apical sodium-selective channels in frog skin, when blocked by amiloride or triamterene, exhibit fluctuations in current, the spectra of which are Lorentzian. These effects have been modeled previously with two-state and three-state models by Lindemann and Van Driessche. A recent observation by Hoshiko and Van Driessche that corner frequencies are lowered by increasing the apical sodium concentration cannot be accounted for by these models. We explore the possibility that sodium (S) and amiloride (A) compete for a site at the mouth of the channel. A new three-state channel model (sodium-occupied, open/unoccupied, open/amiloride-blocked) is analyzed. Its corner frequency is of the form f_c = f_co[1 + (A/K_A)/(1 + S/K_S)], consistent with the observed sodium dependence of the corner frequency. The minimum frequency, f_co, and the inhibition constants, K_A and K_S, are expressed in terms of the rate constants of the model. To account for sodium self-inhibition, we postulate that two sodium ions in the channel may result in clogging — a fourth state. The two corner frequencies are calculated; so are the plateau values of the noise power. The noise power shows a maximum as a function of blocker concentration, as observed previously using triamterene. The four-state model predicts the observed suppression by small amounts of blocker of the low-frequency sodium (clogging) noise.     

Effects of Partial and Acute Total Sleep Deprivation on Performance across Cognitive Domains,Individuals and Circadian Phase

Background

Cognitive performance deteriorates during extended wakefulness and circadian phase misalignment, and some individuals are more affected than others. Whether performance is affected similarly across cognitive domains, or whether cognitive processes involving Executive Functions are more sensitive to sleep and circadian misalignment than Alertness and Sustained Attention, is a matter of debate.

Methodology/Principal Findings

We conducted a 2 × 12-day laboratory protocol to characterize the interaction of repeated partial and acute total sleep deprivation and circadian phase on performance across seven cognitive domains in 36 individuals (18 males; mean ± SD of age = 27.6±4.0 years). The sample was stratified for the rs57875989 polymorphism in PER3, which confers cognitive susceptibility to total sleep deprivation. We observed a deterioration of performance during both repeated partial and acute total sleep deprivation. Furthermore, prior partial sleep deprivation led to poorer cognitive performance in a subsequent total sleep deprivation period, but its effect was modulated by circadian phase such that it was virtually absent in the evening wake maintenance zone, and most prominent during early morning hours. A significant effect of PER3 genotype was observed for Subjective Alertness during partial sleep deprivation and on n-back tasks with a high executive load when assessed in the morning hours during total sleep deprivation after partial sleep loss. Overall, however, Subjective Alertness and Sustained Attention were more affected by both partial and total sleep deprivation than other cognitive domains and tasks including n-back tasks of Working Memory, even when implemented with a high executive load.

Conclusions/Significance

Sleep loss has a primary effect on Sleepiness and Sustained Attention with much smaller effects on challenging Working Memory tasks. These findings have implications for understanding how sleep debt and circadian rhythmicity interact to determine waking performance across cognitive domains and individuals.     

Identification and Characterization of a Novel Galactofuranose-Specific β-D-Galactofuranosidase from Streptomyces Species

β-D-galactofuranose (Galf) is a component of polysaccharides and glycoconjugates and its transferase has been well analyzed. However, no β-D-galactofuranosidase (Galf-ase) gene has been identified in any organism. To search for a Galf-ase gene we screened soil samples and discovered a strain, identified as a Streptomyces species by the 16S ribosomal RNA gene analysis, that exhibits Galf-ase activity for 4-nitrophenyl β-D-galactofuranoside (pNP-β-D-Galf) in culture supernatants. By draft genome sequencing of the strain, named JHA19, we found four candidate genes encoding Galf-ases. Using recombinant proteins expressed in Escherichia coli, we found that three out of four candidates displayed the activity of not only Galf-ase but also α-L-arabinofuranosidase (Araf-ase), whereas the other one showed only the Galf-ase activity. This novel Galf-specific hydrolase is encoded by ORF1110 and has an optimum pH of 5.5 and a Km of 4.4 mM for the substrate pNP-β-D-Galf. In addition, this enzyme was able to release galactose residue from galactomannan prepared from the filamentous fungus Aspergillus fumigatus, suggesting that natural polysaccharides could be also substrates. By the BLAST search using the amino acid sequence of ORF1110 Galf-ase, we found that there are homolog genes in both prokaryotes and eukaryotes, indicating that Galf-specific Galf-ases widely exist in microorganisms.