scholarly journals Information decomposition of multichannel EMG to map functional interactions in the distributed motor system

2019 ◽  
Author(s):  
Tjeerd W Boonstra ◽  
Luca Faes ◽  
Jennifer N Kerkman ◽  
Daniele Marinazzo
Keyword(s):  
Information Transfer ◽  
Surface Emg ◽  
Neural Circuitry ◽  
Information Storage ◽  
Spinal Reflex ◽  
Experimental Conditions ◽  
Information Measures ◽  
Functional Interactions ◽  
Postural Tasks ◽  
Time Lagged

AbstractThe central nervous system needs to coordinate multiple muscles during postural control. Functional coordination is established through the neural circuitry that interconnects different muscles. Here we used multivariate information decomposition of multichannel EMG acquired from 14 healthy participants during postural tasks to investigate the neural interactions between muscles. A set of information measures were estimated from an instantaneous linear regression model and a time-lagged VAR model fitted to the EMG envelopes of 36 muscles. We used network analysis to quantify the structure of functional interactions between muscles and compared them across experimental conditions. Conditional mutual information and transfer entropy revealed sparse networks dominated by local connections between muscles. We observed significant changes in muscle networks across postural tasks localized to the muscles involved in performing those tasks. Information decomposition revealed distinct patterns in task-related changes: unimanual and bimanual pointing were associated with reduced transfer to the pectoralis major muscles, but an increase in total information compared to no pointing, while postural instability resulted in increased information, information transfer and information storage in the abductor longus muscles compared to normal stability. These findings show robust patterns of directed interactions between muscles that are task-dependent and can be assessed from surface EMG recorded during static postural tasks. We discuss directed muscle networks in terms of the neural circuitry involved in generating muscle activity and suggest that task-related effects may reflect gain modulations of spinal reflex pathways.

scholarly journals A Framework to Assess the Information Dynamics of Source EEG Activity and Its Application to Epileptic Brain Networks

2020 ◽  
Vol 10 (9) ◽  
pp. 657
Author(s):  
Ivan Kotiuchyi ◽  
Riccardo Pernice ◽  
Anton Popov ◽  
Luca Faes ◽  
Volodymyr Kharytonov
Keyword(s):  
Information Transfer ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Epileptic Seizures ◽  
Information Storage ◽  
Source Analysis ◽  
Source Information ◽  
Information Dynamics ◽  
Experimental Conditions ◽  
Eeg Activity

This study introduces a framework for the information-theoretic analysis of brain functional connectivity performed at the level of electroencephalogram (EEG) sources. The framework combines the use of common spatial patterns to select the EEG components which maximize the variance between two experimental conditions, simultaneous implementation of vector autoregressive modeling (VAR) with independent component analysis to describe the joint source dynamics and their projection to the scalp, and computation of information dynamics measures (information storage, information transfer, statistically significant network links) from the source VAR parameters. The proposed framework was tested on simulated EEGs obtained mixing source signals generated under different coupling conditions, showing its ability to retrieve source information dynamics from the scalp signals. Then, it was applied to investigate scalp and source brain connectivity in a group of children manifesting episodes of focal and generalized epilepsy; the analysis was performed on EEG signals lasting 5 s, collected in two consecutive windows preceding and one window following each ictal episode. Our results show that generalized seizures are associated with a significant decrease from pre-ictal to post-ictal periods of the information stored in the signals and of the information transferred among them, reflecting reduced self-predictability and causal connectivity at the level of both scalp and source brain dynamics. On the contrary, in the case of focal seizures the scalp EEG activity was not discriminated across conditions by any information measure, while source analysis revealed a tendency of the measures of information transfer to increase just before seizures and to decrease just after seizures. These results suggest that focal epileptic seizures are associated with a reorganization of the topology of EEG brain networks which is only visible analyzing connectivity among the brain sources. Our findings emphasize the importance of EEG modeling approaches able to deal with the adverse effects of volume conduction on brain connectivity analysis, and their potential relevance to the development of strategies for prediction and clinical treatment of epilepsy.

EEG TRANSFER ENTROPY TRACKS CHANGES IN INFORMATION TRANSFER ON THE ONSET OF VISION

2012 ◽  
Vol 17 ◽  
pp. 9-18 ◽  
Author(s):  
M. D. MADULARA ◽  
P. A. B. FRANCISCO ◽  
S. NAWANG ◽  
D. C. AROGANCIA ◽  
C. J. CELLUCCI ◽  
...  
Keyword(s):  
Mutual Information ◽  
Information Transfer ◽  
Occipital Lobe ◽  
Transfer Entropy ◽  
The Other ◽  
Information Measures ◽  
Eyes Closed ◽  
Eyes Open ◽  
Almost All ◽  
Nonlinear Correlations

We investigate the pairwise mutual information and transfer entropy of ten-channel, free-running electroencephalographs measured from thirteen subjects under two behavioral conditions: eyes open resting and eyes closed resting. Mutual information measures nonlinear correlations; transfer entropy determines the directionality of information transfer. For all channel pairs, mutual information is generally lower with eyes open compared to eyes closed indicating that EEG signals at different scalp sites become more dissimilar as the visual system is engaged. On the other hand, transfer entropy increases on average by almost two-fold when the eyes are opened. The largest one-way transfer entropies are to and from the Oz site consistent with the involvement of the occipital lobe in vision. The largest net transfer entropies are from F3 and F4 to almost all the other scalp sites.

scholarly journals Solvent viscosity facilitates replication and ribozyme catalysis from an RNA duplex in a model prebiotic process

2019 ◽  
Vol 47 (13) ◽  
pp. 6569-6577 ◽  
Author(s):  
Christine He ◽  
Adriana Lozoya-Colinas ◽  
Isaac Gállego ◽  
Martha A Grover ◽  
Nicholas V Hud
Keyword(s):  
Information Transfer ◽  
Rna World ◽  
Hammerhead Ribozyme ◽  
Information Storage ◽  
Additional Challenge ◽  
The Origin Of Life ◽  
World Hypothesis ◽  
Synthesis Reactions ◽  
Rna World Hypothesis ◽  
Single Sequence

Abstract The RNA World hypothesis posits that RNA was once responsible for genetic information storage and catalysis. However, a prebiotic mechanism has yet to be reported for the replication of duplex RNA that could have operated before the emergence of polymerase ribozymes. Previously, we showed that a viscous solvent enables information transfer from one strand of long RNA duplex templates, overcoming ‘the strand inhibition problem'. Here, we demonstrate that the same approach allows simultaneous information transfer from both strands of long duplex templates. An additional challenge for the RNA World is that structured RNAs (like those with catalytic activity) function poorly as templates in model prebiotic RNA synthesis reactions, raising the question of how a single sequence could serve as both a catalyst and as a replication template. Here, we show that a viscous solvent also facilitates the transition of a newly synthesized hammerhead ribozyme sequence from its inactive, duplex state to its active, folded state. These results demonstrate how fluctuating environmental conditions can allow a ribozyme sequence to alternate between acting as a template for replication and functioning as a catalyst, and illustrate the potential for temporally changing environments to enable molecular processes necessary for the origin of life.

Sex differences in surface EMG interference pattern power spectrum

1994 ◽  
Vol 77 (5) ◽  
pp. 2163-2168 ◽  
Author(s):  
R. Cioni ◽  
F. Giannini ◽  
C. Paradiso ◽  
N. Battistini ◽  
C. Navona ◽  
...  
Keyword(s):  
Sex Differences ◽  
Power Spectrum ◽  
Surface Emg ◽  
Progressive Increase ◽  
Experimental Conditions ◽  
Spectral Parameters ◽  
Mean Values ◽  
Healthy Female ◽  
Power Frequency ◽  
Median Power Frequency

Sex differences in the spectral parameters of the surface electromyogram (EMG) power spectrum were studied during voluntary muscle contractions of different strength with rest in between. The influence of two different types of leads (unipolar and bipolar) on the values of the spectral parameters was also investigated under the same experimental conditions. The subjects were 15 healthy female and 15 healthy male volunteers. The relationship between the amplitude (root mean square) of the EMG and the force developed was not linear. The mean values of the median power frequency were lower in women than in men. With both types of lead, the increase in force was accompanied by a progressive increase in median power frequency in male and female subjects. The significant differences in spectral parameters observed in the two sexes are probably correlated with anatomic differences.

scholarly journals Transitions in brain-network level information processing dynamics are driven by alterations in neural gain

2019 ◽  
Author(s):  
Mike Li ◽  
Yinuo Han ◽  
Matthew J. Aburn ◽  
Michael Breakspear ◽  
Russell A. Poldrack ◽  
...  
Keyword(s):  
Information Processing ◽  
Information Transfer ◽  
Large Scale ◽  
Functional Integration ◽  
Brain Network ◽  
Information Storage ◽  
Transfer Entropy ◽  
Arousal System ◽  
Neural Gain ◽  
The Brain

AbstractA key component of the flexibility and complexity of the brain is its ability to dynamically adapt its functional network structure between integrated and segregated brain states depending on the demands of different cognitive tasks. Integrated states are prevalent when performing tasks of high complexity, such as maintaining items in working memory, consistent with models of a global workspace architecture. Recent work has suggested that the balance between integration and segregation is under the control of ascending neuromodulatory systems, such as the noradrenergic system. In a previous large-scale nonlinear oscillator model of neuronal network dynamics, we showed that manipulating neural gain led to a ‘critical’ transition in phase synchrony that was associated with a shift from segregated to integrated topology, thus confirming our original prediction. In this study, we advance these results by demonstrating that the gain-mediated phase transition is characterized by a shift in the underlying dynamics of neural information processing. Specifically, the dynamics of the subcritical (segregated) regime are dominated by information storage, whereas the supercritical (integrated) regime is associated with increased information transfer (measured via transfer entropy). Operating near to the critical regime with respect to modulating neural gain would thus appear to provide computational advantages, offering flexibility in the information processing that can be performed with only subtle changes in gain control. Our results thus link studies of whole-brain network topology and the ascending arousal system with information processing dynamics, and suggest that the constraints imposed by the ascending arousal system constrain low-dimensional modes of information processing within the brain.Author summaryHigher brain function relies on a dynamic balance between functional integration and segregation. Previous work has shown that this balance is mediated in part by alterations in neural gain, which are thought to relate to projections from ascending neuromodulatory nuclei, such as the locus coeruleus. Here, we extend this work by demonstrating that the modulation of neural gain alters the information processing dynamics of the neural components of a biophysical neural model. Specifically, we find that low levels of neural gain are characterized by high Active Information Storage, whereas higher levels of neural gain are associated with an increase in inter-regional Transfer Entropy. Our results suggest that the modulation of neural gain via the ascending arousal system may fundamentally alter the information processing mode of the brain, which in turn has important implications for understanding the biophysical basis of cognition.

scholarly journals Encoding Temporal Regularities and Information Copying in Hippocampal Circuits

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Terri P. Roberts ◽  
Felix B. Kern ◽  
Chrisantha Fernando ◽  
Eörs Szathmáry ◽  
Phil Husbands ◽  
...  
Keyword(s):  
Information Transfer ◽  
Electrode Array ◽  
Information Storage ◽  
Cellular Mechanisms ◽  
Motor Processing ◽  
Fundamental Properties ◽  
Temporal Relationships ◽  
Array Technology ◽  
Critical Requirement

AbstractDiscriminating, extracting and encoding temporal regularities is a critical requirement in the brain, relevant to sensory-motor processing and learning. However, the cellular mechanisms responsible remain enigmatic; for example, whether such abilities require specific, elaborately organized neural networks or arise from more fundamental, inherent properties of neurons. Here, using multi-electrode array technology, and focusing on interval learning, we demonstrate that sparse reconstituted rat hippocampal neural circuits are intrinsically capable of encoding and storing sub-second-order time intervals for over an hour timescale, represented in changes in the spatial-temporal architecture of firing relationships among populations of neurons. This learning is accompanied by increases in mutual information and transfer entropy, formal measures related to information storage and flow. Moreover, temporal relationships derived from previously trained circuits can act as templates for copying intervals into untrained networks, suggesting the possibility of circuit-to-circuit information transfer. Our findings illustrate that dynamic encoding and stable copying of temporal relationships are fundamental properties of simple in vitro networks, with general significance for understanding elemental principles of information processing, storage and replication.

scholarly journals A Changing Climatology of Precipitation Persistence across the United States Using Information-Based Measures

2019 ◽  
Vol 20 (8) ◽  
pp. 1649-1666 ◽  
Author(s):  
Allison E. Goodwell ◽  
Praveen Kumar
Keyword(s):  
United States ◽  
Time Scales ◽  
Daily Precipitation ◽  
Temporal Trends ◽  
The United States ◽  
Binary Sequences ◽  
Precipitation Frequency ◽  
Climate Trend ◽  
Information Measures ◽  
Time Lagged

Abstract The sequencing, or persistence, of daily precipitation influences variability in streamflow, soil moisture, and vegetation states. As these factors influence water availability and ecosystem health, it is important to identify spatial and temporal trends in precipitation persistence and predictability. We take an information theoretic perspective to address regional and temporal trends in daily patterns, based on the Climate Prediction Center (CPC) gridded gauge-based dataset of daily precipitation over the continental United States from 1948 to 2018. We apply information measures to binary sequences of precipitation occurrence to quantify uncertainty, predictability in the form of lagged mutual information between the current state and two time-lagged histories, and associated dominant time scales. We find that this information-based predictability is highest in the western United States, but the relative influence of longer lagged histories in comparison to a 1-day history is highest in the east. Information characteristics and time scales vary seasonally and regionally and constitute an information climatology that can be compared with traditional indices of precipitation and climate. Trend analyses over the 70-yr time period also show varying regional characteristics that differ between seasons. In addition to increasing precipitation frequency over most of the country, we detect increasing and decreasing predictability in western and eastern regions, respectively, with average trend magnitudes corresponding to shifts in predictability ranging from −50% to 110%. This new perspective on precipitation persistence has broad potential to link shifts in climate and weather to patterns and predictability of related environmental factors.

Stochastic chromatin packing of 3D mitotic chromosomes revealed by coherent X-rays

2021 ◽  
Vol 118 (46) ◽  
pp. e2109921118
Author(s):  
Daeho Sung ◽  
Chan Lim ◽  
Masatoshi Takagi ◽  
Chulho Jung ◽  
Heemin Lee ◽  
...  
Keyword(s):  
Information Transfer ◽  
3D Structure ◽  
Three Dimensional ◽  
Information Storage ◽  
Atomic Scale ◽  
Scaling Analysis ◽  
X Rays ◽  
Mitotic Chromosomes ◽  
Metaphase Chromosomes ◽  
Chromatin Packing

DNA molecules are atomic-scale information storage molecules that promote reliable information transfer via fault-free repetitions of replications and transcriptions. Remarkable accuracy of compacting a few-meters-long DNA into a micrometer-scale object, and the reverse, makes the chromosome one of the most intriguing structures from both physical and biological viewpoints. However, its three-dimensional (3D) structure remains elusive with challenges in observing native structures of specimens at tens-of-nanometers resolution. Here, using cryogenic coherent X-ray diffraction imaging, we succeeded in obtaining nanoscale 3D structures of metaphase chromosomes that exhibited a random distribution of electron density without characteristics of high-order folding structures. Scaling analysis of the chromosomes, compared with a model structure having the same density profile as the experimental results, has discovered the fractal nature of density distributions. Quantitative 3D density maps, corroborated by molecular dynamics simulations, reveal that internal structures of chromosomes conform to diffusion-limited aggregation behavior, which indicates that 3D chromatin packing occurs via stochastic processes.

Preparation of In Situ Magnetically Loaded Cellulose Fibers

1990 ◽  
Vol 197 ◽  
Author(s):  
Serge Ricard ◽  
Robert H. Marchessault
Keyword(s):  
Magnetic Properties ◽  
Floppy Disk ◽  
Information Storage ◽  
Oxidation Reactions ◽  
X Ray Diffraction ◽  
Experimental Conditions ◽  
Storage Security ◽  
New Concepts ◽  
Before And After

ABSTRACTMagnetic paper handsheets with pigment loadings in the order of 10–30%, depending on the experimental conditions, have been made using the established “lumen-loading” technology. These sheets have bulk magnetic properties comparable with the computer floppy-disk products. In order to minimize the particle size of pigments and thereby explore a new level of optical and magnetic properties, in situ synthesis of pigment particles is a second approach. This chemistry starts with a carboxymethylcellulose substrate with ion-exchange properties for Fe(ll). The substrates, before and after oxidation reactions to produce ferrite particles, are characterized by: conductimetric titration, x-ray diffraction, thermogravimetric analysis, and magnetization determination. Electron microscopy and diffraction provide insight on the ferrite morphologicals. These specialty fibers allow exploration of new concepts in papermaking, information storage, security printing and paper handling.

Information Dynamics in Small-World Boolean Networks

2011 ◽  
Vol 17 (4) ◽  
pp. 293-314 ◽  
Author(s):  
Joseph T. Lizier ◽  
Siddharth Pritam ◽  
Mikhail Prokopenko
Keyword(s):  
Information Transfer ◽  
Small World ◽  
Boolean Networks ◽  
Information Storage ◽  
Systems Science ◽  
Small World Networks ◽  
Information Dynamics ◽  
Quantitative Evidence ◽  
Naturally Occurring ◽  
Complex Systems Science

Small-world networks have been one of the most influential concepts in complex systems science, partly due to their prevalence in naturally occurring networks. It is often suggested that this prevalence is due to an inherent capability to store and transfer information efficiently. We perform an ensemble investigation of the computational capabilities of small-world networks as compared to ordered and random topologies. To generate dynamic behavior for this experiment, we imbue the nodes in these networks with random Boolean functions. We find that the ordered phase of the dynamics (low activity in dynamics) and topologies with low randomness are dominated by information storage, while the chaotic phase (high activity in dynamics) and topologies with high randomness are dominated by information transfer. Information storage and information transfer are somewhat balanced (crossed over) near the small-world regime, providing quantitative evidence that small-world networks do indeed have a propensity to combine comparably large information storage and transfer capacity.

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