Federal Information Processing Standards Publication: standard security label for information transfer

1994 ◽  
Author(s):  
Keyword(s):  
Information Processing ◽  
Information Transfer ◽  
Security Label

scholarly journals Information Rate in Humans during Visuomotor Tracking

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 228
Author(s):  
Sze-Ying Lam ◽  
Alexandre Zénon
Keyword(s):  
Information Processing ◽  
Information Transfer ◽  
Cost Benefit ◽  
Cognitive Effort ◽  
Task Demands ◽  
Information Rate ◽  
Present Contribution ◽  
Visuomotor Tracking ◽  
Processing Rate ◽  
Choice Tasks

Previous investigations concluded that the human brain’s information processing rate remains fundamentally constant, irrespective of task demands. However, their conclusion rested in analyses of simple discrete-choice tasks. The present contribution recasts the question of human information rate within the context of visuomotor tasks, which provides a more ecologically relevant arena, albeit a more complex one. We argue that, while predictable aspects of inputs can be encoded virtually free of charge, real-time information transfer should be identified with the processing of surprises. We formalise this intuition by deriving from first principles a decomposition of the total information shared by inputs and outputs into a feedforward, predictive component and a feedback, error-correcting component. We find that the information measured by the feedback component, a proxy for the brain’s information processing rate, scales with the difficulty of the task at hand, in agreement with cost-benefit models of cognitive effort.

Capacity of a Single Spiking Neuron Channel

2009 ◽  
Vol 21 (6) ◽  
pp. 1714-1748 ◽  
Author(s):  
Shiro Ikeda ◽  
Jonathan H. Manton
Keyword(s):  
Information Processing ◽  
Channel Capacity ◽  
Information Transfer ◽  
Communication Channel ◽  
Discrete Distribution ◽  
Random Variable ◽  
Temporal Coding ◽  
Reasonable Assumption ◽  
Rate Coding ◽  
The Brain

Information transfer through a single neuron is a fundamental component of information processing in the brain, and computing the information channel capacity is important to understand this information processing. The problem is difficult since the capacity depends on coding, characteristics of the communication channel, and optimization over input distributions, among other issues. In this letter, we consider two models. The temporal coding model of a neuron as a communication channel assumes the output is τ where τ is a gamma-distributed random variable corresponding to the interspike interval, that is, the time it takes for the neuron to fire once. The rate coding model is similar; the output is the actual rate of firing over a fixed period of time. Theoretical studies prove that the distribution of inputs, which achieves channel capacity, is a discrete distribution with finite mass points for temporal and rate coding under a reasonable assumption. This allows us to compute numerically the capacity of a neuron. Numerical results are in a plausible range based on biological evidence to date.

scholarly journals Adaptive Local Information Transfer in Random Boolean Networks

2017 ◽  
Vol 23 (1) ◽  
pp. 105-118 ◽  
Author(s):  
Taichi Haruna
Keyword(s):  
Information Processing ◽  
Information Transfer ◽  
Regulatory Networks ◽  
Mean Field Theory ◽  
Mean Field ◽  
Boolean Networks ◽  
Local Information ◽  
System Level ◽  
Adjustment Process ◽  
Random Boolean Networks

Living systems such as gene regulatory networks and neuronal networks have been supposed to work close to dynamical criticality, where their information-processing ability is optimal at the whole-system level. We investigate how this global information-processing optimality is related to the local information transfer at each individual-unit level. In particular, we introduce an internal adjustment process of the local information transfer and examine whether the former can emerge from the latter. We propose an adaptive random Boolean network model in which each unit rewires its incoming arcs from other units to balance stability of its information processing based on the measurement of the local information transfer pattern. First, we show numerically that random Boolean networks can self-organize toward near dynamical criticality in our model. Second, the proposed model is analyzed by a mean-field theory. We recognize that the rewiring rule has a bootstrapping feature. The stationary indegree distribution is calculated semi-analytically and is shown to be close to dynamical criticality in a broad range of model parameter values.

scholarly journals Information rate in humans during visuomotor tracking

2020 ◽  
Author(s):  
Sze-Ying Lam ◽  
Alexandre Zénon
Keyword(s):  
Information Processing ◽  
Real Time ◽  
Information Transfer ◽  
Cognitive Effort ◽  
Information Rate ◽  
Processing Rate ◽  
Total Information ◽  
Real Time Information ◽  
Choice Tasks ◽  
Time Information

AbstractWhile previous studies of human information rate focused primarily on discrete forced-choice tasks, we extend the scope of the investigation to the framework of sensorimotor tracking of continuous signals. We show how considering information transfer in this context sheds new light on the problem; crucially, such an analysis requires one to consider and carefully disentangle the effects due to real-time information processing of surprising inputs (feedback component) from the contribution to performance due to prediction (feedforward component). We argue that only the former constitutes a faithful representation of the true information processing rate. We provide information-theoretic measures which separately quantify these components and show that they correspond to a decomposition of the total information shared between target and tracking signals. We employ a linear quadratic regulator model to provide evidence for the validity of the measures, as well as of the estimator of visual-motor delay (VMD) from experimental data, instrumental to compute them in practice. On experimental tracking data, we show that the contribution of prediction as computed by the feedforward measure increases with the predictability of the signal, confirming previous findings. Importantly, we further find the feedback component to be modulated by task difficulty, with higher information transmission rates observed with noisier signals. Such opposite trends between feedback and feedforward point to a tradeoff of cognitive resources/effort and performance gain.Author summaryPrevious investigations concluded that the human brain’s information processing rate remains fundamentally constant, irrespective of task demands. However, their conclusion rested in analyses of simple discrete-choice tasks. The present contribution recasts the question of human information rate within the context of visuomotor tasks, which provides a more ecologically relevant arena, albeit a more complex one. We argue that, while predictable aspects of inputs can be encoded virtually free of charge, real-time information transfer should be identified with the processing of surprises. We formalise this intuition by deriving from first principles a decomposition of the total information shared by inputs and outputs into a feedforward, predictive component and a feedback, error-correcting component. We find that the information measured by the feedback component, a proxy for the brain’s information processing rate, scales with the difficulty of the task at hand, in agreement with cost-benefit models of cognitive effort.

scholarly journals Insuperable problems of the genetic code initially emerging in an RNA World

2017 ◽  
Author(s):  
Peter R Wills ◽  
Charles W Carter
Keyword(s):  
Protein Synthesis ◽  
Information Processing ◽  
Natural Selection ◽  
Information Transfer ◽  
Rna World ◽  
Biological Information ◽  
Universal System ◽  
Biological Information Processing ◽  
Relationship Of ◽  
The Relationship

AbstractDifferential equations for error-prone information transfer (template replication, transcription or translation) are developed in order to consider, within the theory of autocatalysis, the advent of coded protein synthesis. Variations of these equations furnish a basis for comparing the plausibility of contrasting scenarios for the emergence of tRNA aminoacylation, ultimately by enzymes, and the relationship of this process with the origin of the universal system of molecular biological information processing embodied in the Central Dogma. The hypothetical RNA World does not furnish an adequate basis for explaining how this system came into being, but principles of self-organisation that transcend Darwinian natural selection furnish an unexpectedly robust basis for a rapid, concerted transition to genetic coding from a peptide•RNA world.

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.

PSYCHOPHYSICS OF STOCHASTIC RESONANCE

2004 ◽  
Vol 04 (01) ◽  
pp. L11-L21 ◽  
Author(s):  
LAWRENCE M. WARD
Keyword(s):  
Information Processing ◽  
Signal Detection ◽  
Stochastic Resonance ◽  
Information Transfer ◽  
Signal Detection Theory ◽  
Biological Systems ◽  
Detection Theory ◽  
Human Beings ◽  
Soft Threshold

Although stochastic resonance has been demonstrated for many physical and biological systems, in both dynamic and threshold forms, its study in whole human beings presents special problems. Psychophysics provides theoretical and methodological tools for measuring information processing by humans, but modern psychophysics seems to be incompatible with some of the concepts of current theories of stochastic resonance. In this paper I review some of these problems, providing suggestions for solutions where none have as yet appeared. In particular, I discuss incompatibilities between signal detection theory and threshold stochastic resonance, and the problem of the effect of noise on information transfer across a "soft" threshold.

EEG Frequency and Phase Coupling during Human Information Processing

2001 ◽  
Vol 40 (02) ◽  
pp. 106-111 ◽  
Author(s):  
P. Rappelsberger ◽  
N. Vath ◽  
S. Weiss ◽  
E. Möller ◽  
G. Grießbach ◽  
...  
Keyword(s):  
Information Processing ◽  
Information Transfer ◽  
Network Activity ◽  
Single Frequency ◽  
Human Information Processing ◽  
Phase Coupling ◽  
Memory Processing ◽  
Neuronal Ensembles ◽  
Non Linear ◽  
Oscillatory Network

AbstractNeuronal activity during information processing is represented by oscillations within local or widespread neuronal networks. These oscillations may be recorded by the EEG (electroencephalogram). The oscillatory interaction between neuronal ensembles may be at one single frequency or at different frequencies due to non-linear coupling. The investigation of momentary coherence and phase enables the examination of synchronized oscillatory network activity during fast-changing cognitive processes. On this basis information transfer from occipital areas towards frontal areas could be described during processing of visual presented words. Non-linear phase coupling between oscillations with different frequencies during memory processing was detected by means of cross-bicoherence.

scholarly journals Cognitive capacity limits are remediated by practice-induced plasticity between the Putamen and Pre-Supplementary Motor Area

2019 ◽  
Author(s):  
K.G. Garner ◽  
M.I. Garrido ◽  
P.E. Dux
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Information Sharing ◽  
Information Transfer ◽  
Supplementary Motor Area ◽  
Cortical Network ◽  
Motor Area ◽  
Cognitive Capacity ◽  
Capacity Limits ◽  
Stimulus Response

AbstractHumans show striking limitations in information processing when multitasking, yet can modify these limits with practice. Such limitations have been linked to a frontal-parietal network, but recent models of decision-making implicate a striatal-cortical network. We adjudicated these accounts by investigating the circuitry underpinning multitasking in 100 individuals and the plasticity caused by practice. We observed that multitasking costs, and their practice induced remediation, are best explained by modulations in information transfer between the striatum and the cortical areas that represent stimulus-response mappings. Specifically, our results support the view that multitasking stems at least in part from taxation in information sharing between the putamen and pre-supplementary motor area (pre-SMA). Moreover, we propose that modulations to information transfer between these two regions leads to practice-induced improvements in multitasking.Significance statementHumans show striking limitations in information processing when multitasking, yet can modify these limits with practice. Such limitations have been linked to a frontal-parietal network, but recent models of decision-making implicate a striatal-cortical network. We adjudicated these accounts by investigating the circuitry underpinning multitasking in 100 individuals and the plasticity caused by practice. Our results support the view that multitasking stems at least in part from taxation in information sharing between the putamen and pre-supplementary motor area (pre-SMA). We therefore show that models of cognitive capacity limits must consider how subcortical and cortical structures interface to produce cognitive behaviours, and we propose a novel neurophysiological substrate of multitasking limitations.

American Jewish Ethnicity: Its Relationship to Some Selected Aspects of Consumer Behavior

1981 ◽  
Vol 45 (3) ◽  
pp. 102-110 ◽  
Author(s):  
Elizabeth C. Hirschman
Keyword(s):  
Information Processing ◽  
Consumer Behavior ◽  
Ethnic Groups ◽  
Information Seeking ◽  
Information Transfer ◽  
Product Information ◽  
Ethnic Identification ◽  
Childhood Exposure ◽  
Product Innovativeness ◽  
Cognitive Characteristics

The ethnicity literature within marketing has infrequently considered relevant subcultural norms in the derivation of hypotheses, the strength of ethnic identification in the grouping of subjects, and the investigation of ethnic groups other than blacks. The present research tests five hypotheses concerning Jewish ethnicity. It was found that Jewish subjects in two cohort samples differed significantly from non-Jewish subjects in childhood exposure to information, adulthood information seeking, product innovativeness, product information transfer, and cognitive characteristics relevant to consumption information processing.

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