scholarly journals Multiscale criticality measures as general-purpose gauges of proper brain function

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tomer Fekete ◽  
Hermann Hinrichs ◽  
Jacobo Diego Sitt ◽  
Hans-Jochen Heinze ◽  
Oren Shriki
Keyword(s):  
Information Processing ◽  
General Purpose ◽  
Processing Capacity ◽  
Hierarchical Networks ◽  
Information Processing Capacity ◽  
Eeg Data ◽  
Hierarchical Complexity ◽  
Processing Information ◽  
Ictal Activity ◽  
The Brain

AbstractThe brain is universally regarded as a system for processing information. If so, any behavioral or cognitive dysfunction should lend itself to depiction in terms of information processing deficiencies. Information is characterized by recursive, hierarchical complexity. The brain accommodates this complexity by a hierarchy of large/slow and small/fast spatiotemporal loops of activity. Thus, successful information processing hinges upon tightly regulating the spatiotemporal makeup of activity, to optimally match the underlying multiscale delay structure of such hierarchical networks. Reduced capacity for information processing will then be expressed as deviance from this requisite multiscale character of spatiotemporal activity. This deviance is captured by a general family of multiscale criticality measures (MsCr). MsCr measures reflect the behavior of conventional criticality measures (such as the branching parameter) across temporal scale. We applied MsCr to MEG and EEG data in several telling degraded information processing scenarios. Consistently with our previous modeling work, MsCr measures systematically varied with information processing capacity: MsCr fingerprints showed deviance in the four states of compromised information processing examined in this study, disorders of consciousness, mild cognitive impairment, schizophrenia and even during pre-ictal activity. MsCr measures might thus be able to serve as general gauges of information processing capacity and, therefore, as normative measures of brain health.

scholarly journals Multiscale criticality measures as general-purpose gauges of proper brain function

2019 ◽  
Author(s):  
Tomer Fekete ◽  
Hermann Hinrichs ◽  
Jacobo Diego Sitt ◽  
Hans-Jochen Heinze ◽  
Oren Shriki
Keyword(s):  
Information Processing ◽  
General Purpose ◽  
Processing Capacity ◽  
Brain Health ◽  
Hierarchical Networks ◽  
Information Processing Capacity ◽  
Eeg Data ◽  
Hierarchical Complexity ◽  
Processing Information ◽  
The Brain

ABSTRACTThe brain is universally regarded as a system for processing information. If so, any behavioral or cognitive dysfunction should lend itself to depiction in terms of information processing deficiencies. Information is characterized by recursive, hierarchical complexity. The brain accommodates this complexity by a hierarchy of large/slow and small/fast spatiotemporal loops of activity. Thus, successful information processing hinges upon tightly regulating the spatiotemporal makeup of activity, to optimally match the underlying multiscale delay structure of such hierarchical networks. Reduced capacity for information processing will then be expressed as deviance from this requisite multiscale character of spatiotemporal activity. This deviance is captured by a general family of multiscale criticality measures (MsCr). We applied MsCr to MEG and EEG data in four telling degraded information processing scenarios: disorders of consciousness, mild cognitive impairment, schizophrenia and preictal activity. Consistently with our previous modeling work, MsCr measures systematically varied with information processing capacity. MsCr measures might thus be able to serve as general gauges of information processing capacity and, therefore, as normative measures of brain health.

scholarly journals Entropy and the Brain: An Overview

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 917 ◽  
Author(s):  
Soheil Keshmiri
Keyword(s):  
Information Processing ◽  
Brain Function ◽  
Conscious Experience ◽  
Brain Networks ◽  
Fundamental Property ◽  
Future Research ◽  
Processing Capacity ◽  
Information Processing Capacity ◽  
Ageing Brain ◽  
The Brain

Entropy is a powerful tool for quantification of the brain function and its information processing capacity. This is evident in its broad domain of applications that range from functional interactivity between the brain regions to quantification of the state of consciousness. A number of previous reviews summarized the use of entropic measures in neuroscience. However, these studies either focused on the overall use of nonlinear analytical methodologies for quantification of the brain activity or their contents pertained to a particular area of neuroscientific research. The present study aims at complementing these previous reviews in two ways. First, by covering the literature that specifically makes use of entropy for studying the brain function. Second, by highlighting the three fields of research in which the use of entropy has yielded highly promising results: the (altered) state of consciousness, the ageing brain, and the quantification of the brain networks’ information processing. In so doing, the present overview identifies that the use of entropic measures for the study of consciousness and its (altered) states led the field to substantially advance the previous findings. Moreover, it realizes that the use of these measures for the study of the ageing brain resulted in significant insights on various ways that the process of ageing may affect the dynamics and information processing capacity of the brain. It further reveals that their utilization for analysis of the brain regional interactivity formed a bridge between the previous two research areas, thereby providing further evidence in support of their results. It concludes by highlighting some potential considerations that may help future research to refine the use of entropic measures for the study of brain complexity and its function. The present study helps realize that (despite their seemingly differing lines of inquiry) the study of consciousness, the ageing brain, and the brain networks’ information processing are highly interrelated. Specifically, it identifies that the complexity, as quantified by entropy, is a fundamental property of conscious experience, which also plays a vital role in the brain’s capacity for adaptation and therefore whose loss by ageing constitutes a basis for diseases and disorders. Interestingly, these two perspectives neatly come together through the association of entropy and the brain capacity for information processing.

scholarly journals Electrophysiological Measure of Impaired Information Processing in Drivers with Hematological Malignancy

2018 ◽  
Vol 2672 (37) ◽  
pp. 64-73 ◽  
Author(s):  
David E. Anderson ◽  
Vijaya R. Bhatt ◽  
Kendra Schmid ◽  
Matthew Lunning ◽  
Sarah A. Holstein ◽  
...  
Keyword(s):  
Information Processing ◽  
Visual Search ◽  
Automobile Driving ◽  
Small Sample ◽  
Processing Capacity ◽  
Brain Physiology ◽  
Brain Functions ◽  
Information Processing Capacity ◽  
Cohen’S D ◽  
Cohen's D

The broad goal of this study is to measure remote effects of cancer on brain physiology and behaviors that underpin instrumental activities of daily living such as automobile driving. Studies of hematological malignancies (HM) have demonstrated impairments in multiple brain functions shown to be critical for safe automobile driving. In the current pilot study, brain physiology during driving simulation was examined in 14 HM patients and 13 healthy comparison drivers. Electroencephalography was used to measure the eye fixation-related potential (EFRP)—a positive amplitude deflection evoked approximately 100 milliseconds after eye movement termination. Previous studies have demonstrated sensitivity of EFRP activity to information-processing capacity. All drivers completed visual search tasks to evaluate the relationship between driving-related changes in performance and EFRP activity. Results showed smaller EFRP amplitudes in drivers who had: (1) greater driving-related changes in visual search performance ( p = 0.03, Cohen’s d = 0.91); and (2) HM diagnosis ( p = 0.18, Cohen’s d = 0.54). Extending previous studies, these results provide neural evidence of reduced information-processing capacity associated with cancer diagnosis. Future large-scale studies are needed to confirm these results, given the high level of uncertainty and small sample size. This study provides a novel platform for linking changes in brain physiology and safety-critical driving behaviors.

Two cheers for bounded rationality

2000 ◽  
Vol 23 (5) ◽  
pp. 756-757 ◽  
Author(s):  
Raanan Lipshitz
Keyword(s):  
Regression Analysis ◽  
Information Processing ◽  
Rational Choice ◽  
Bounded Rationality ◽  
Processing Capacity ◽  
Limited Information ◽  
Information Processing Capacity ◽  
Simple Heuristics ◽  
Normative Status

Replacing logical coherence by effectiveness as criteria of rationality, Gigerenzer et al. show that simple heuristics can outperform comprehensive procedures (e.g., regression analysis) that overload human limited information processing capacity. Although their work casts long overdue doubt on the normative status of the Rational Choice Paradigm, their methodology leaves open its relevance as to how decisions are actually made.

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