scholarly journals A Non-negative Measure Of Feature-Related Information Transfer Between Neural Signals

2019 ◽  
Author(s):  
Jan Bím ◽  
Vito De Feo ◽  
Daniel Chicharro ◽  
Malte Bieler ◽  
Ileana L. Hanganu-Opatz ◽  
...  
Keyword(s):  
Granger Causality ◽  
Information Flow ◽  
Information Transfer ◽  
Specific Information ◽  
Specific Stimulus ◽  
Brain Functions ◽  
Related Information ◽  
Sensory Features ◽  
Flow Of Information ◽  
The Brain

AbstractQuantifying both the amount and content of the information transferred between neuronal populations is crucial to understand brain functions. Traditional data-driven methods based on Wiener-Granger causality quantify information transferred between neuronal signals, but do not reveal whether transmission of information refers to one specific feature of external stimuli or another. Here, we developed a new measure called Feature-specific Information Transfer (FIT), that quantifies the amount of information transferred between neuronal signals about specific stimulus features. The FIT quantifies the feature-related information carried by a receiver that was previously carried by a sender, but that was never carried by the receiver earlier. We tested the FIT on simulated data in various scenarios. We found that, unlike previous measures, FIT successfully disambiguated genuine feature-specific communication from non-feature specific communication, from external confounding inputs and synergistic interactions. Moreover, the FIT had enhanced temporal sensitivity that facilitates the estimation of the directionality of transfer and the communication delay between neuronal signals. We validated the FIT’s ability to track feature-specific information flow using neurophysiological data. In human electroencephalographic data acquired during a face detection task, the FIT demonstrated that information about the eye in face pictures flowed from the hemisphere contralateral to the eye to the ipsilateral one. In multi-unit activity recorded from thalamic nuclei and primary sensory cortices of rats during multimodal stimulation, FIT, unlike Wiener-Granger methods, credibly detected both the direction of information flow and the sensory features about which information was transmitted. In human cortical high-gamma activity recorded with magnetoencephalography during visuomotor mapping, FIT showed that visuomotor-related information flowed from superior parietal to premotor areas. Our work suggests that the FIT measure has the potential to uncover previously hidden feature-specific information transfer in neuronal recordings and to provide a better understanding of brain communication.Author summaryThe emergence of coherent percepts and behavior relies on the processing and flow of information about sensory features, such as the color or shape of an object, across different areas of the brain. To understand how computations within the brain lead to the emergence of these functions, we need to map the flow of information about each specific feature. Traditional methods, such as those based on Wiener-Granger causality, quantify whether information is transmitted from one brain area to another, but do not reveal if the information being transmitted is about a certain feature or another feature. Here, we develop a new mathematical technique for the analysis of brain activity recordings, called Feature-specific Information Transfer (FIT), that can reveal not only if any information is being transmitted across areas, but whether or not such transmitted information is about a certain sensory feature. We validate the method with both simulated and real neuronal data, showing its power in detecting the presence of feature-specific information transmission, as well as the timing and directionality of this transfer. This work provides a tool of high potential significance to map sensory information processing in the brain.

scholarly journals Stimulus-Specific Information Flow Across the Canonical Cortical Microcircuit

2019 ◽  
Author(s):  
David A. Tovar ◽  
Jacob A. Westerberg ◽  
Michele A. Cox ◽  
Kacie Dougherty ◽  
Thomas Carlson ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Information Flow ◽  
Information Transfer ◽  
Stimulus Presentation ◽  
Stimulus Orientation ◽  
Specific Information ◽  
Brain Areas ◽  
Specific Stimulus ◽  
Cortical Microcircuit ◽  
Activation Sequence

AbstractThe vast majority of mammalian neocortex consists of a stereotypical microcircuit, the canonical cortical microcircuit (CCM), consisting of a granular input layer, positioned between superficial and deep layers. Due to this uniform layout, neuronal activation tends to follow a similar laminar sequence, with unique information extracted at each step. For example, the primate primary visual cortex (V1) combines the two eyes’ signals, extracts stimulus orientation and modulates its activity depending on stimulus history. Several theories have been proposed on when and where these processes happen within the CCM’s laminar activation sequence, but it has been methodologically challenging to test these hypotheses. Here, we use time-resolved multivariate pattern analysis (MVPA) to decode information regarding the eye-of-origin, stimulus orientation and stimulus repetition from simultaneously measured spiking responses across V1’s laminar microcircuit. We find that eye-of-origin information was decodable for the entire duration of stimulus presentation, but diminished in the deepest layers of V1, consistent with the notion that two eyes’ signals are combined within the upper layers. Conversely, orientation information was transient and equally pronounced across the microcircuit, in line with the idea that this information is relayed to other areas for further processing. Moreover, when stimuli were repeated, information regarding orientation was enhanced at the expense of eye-of origin information, suggesting that V1 modulates information flow to optimize specific stimulus dimensions. Taken together, these findings provide empirical evidence that adjudicates between long-standing hypotheses and reveals how information transfer within the CCM supports unique cortical functions.Significance StatementDespite the brain’s daunting complexity, there are common organizing principles across brain areas. For example, neocortical activation follows a stereotypical pattern that spreads from input layers towards layers above and below. While this activation pattern is well known, it has been challenging to ascertain how unique types of information are extracted within this common sequence in different brain areas. Here we use machine learning to track the flow of stimulus-specific information across the layers of visual cortex. We found that information regarding several separate stimulus dimensions was routed uniquely within the common activation sequence in a manner that confirmed prior model predictions. This finding demonstrates how differences in information flow within the stereotypical neocortical activation sequence shape area-specific functions.

scholarly journals Photoreceptive retinal ganglion cells control the information rate of the optic nerve

2018 ◽  
Vol 115 (50) ◽  
pp. E11817-E11826 ◽  
Author(s):  
Nina Milosavljevic ◽  
Riccardo Storchi ◽  
Cyril G. Eleftheriou ◽  
Andrea Colins ◽  
Rasmus S. Petersen ◽  
...  
Keyword(s):  
Optic Nerve ◽  
Retinal Ganglion Cells ◽  
Information Flow ◽  
Information Transfer ◽  
Ganglion Cells ◽  
Retinal Ganglion ◽  
Ambient Light ◽  
Visual Responses ◽  
Light Irradiance ◽  
The Brain

Information transfer in the brain relies upon energetically expensive spiking activity of neurons. Rates of information flow should therefore be carefully optimized, but mechanisms to control this parameter are poorly understood. We address this deficit in the visual system, where ambient light (irradiance) is predictive of the amount of information reaching the eye and ask whether a neural measure of irradiance can therefore be used to proactively control information flow along the optic nerve. We first show that firing rates for the retina’s output neurons [retinal ganglion cells (RGCs)] scale with irradiance and are positively correlated with rates of information and the gain of visual responses. Irradiance modulates firing in the absence of any other visual signal confirming that this is a genuine response to changing ambient light. Irradiance-driven changes in firing are observed across the population of RGCs (including in both ON and OFF units) but are disrupted in mice lacking melanopsin [the photopigment of irradiance-coding intrinsically photosensitive RGCs (ipRGCs)] and can be induced under steady light exposure by chemogenetic activation of ipRGCs. Artificially elevating firing by chemogenetic excitation of ipRGCs is sufficient to increase information flow by increasing the gain of visual responses, indicating that enhanced firing is a cause of increased information transfer at higher irradiance. Our results establish a retinal circuitry driving changes in RGC firing as an active response to alterations in ambient light to adjust the amount of visual information transmitted to the brain.

Information Processing in the Mental Workspace Is Fundamentally Distributed

2016 ◽  
Vol 28 (2) ◽  
pp. 295-307 ◽  
Author(s):  
Alexander Schlegel ◽  
Prescott Alexander ◽  
Peter U. Tse
Keyword(s):  
Information Processing ◽  
Information Flow ◽  
The Novel ◽  
Neural Basis ◽  
Distributed Information ◽  
Network Support ◽  
Component Processes ◽  
High Level ◽  
Flow Of Information ◽  
The Brain

The brain is a complex, interconnected information processing network. In humans, this network supports a mental workspace that enables high-level abilities such as scientific and artistic creativity. Do the component processes underlying these abilities occur in discrete anatomical modules, or are they distributed widely throughout the brain? How does the flow of information within this network support specific cognitive functions? Current approaches have limited ability to answer such questions. Here, we report novel multivariate methods to analyze information flow within the mental workspace during visual imagery manipulation. We find that mental imagery entails distributed information flow and shared representations throughout the cortex. These findings challenge existing, anatomically modular models of the neural basis of higher-order mental functions, suggesting that such processes may occur at least in part at a fundamentally distributed level of organization. The novel methods we report may be useful in studying other similarly complex, high-level informational processes.

IDENTIFICATION OF GRANGER CAUSALITY BETWEEN GENE SETS

2010 ◽  
Vol 08 (04) ◽  
pp. 679-701 ◽  
Author(s):  
ANDRÉ FUJITA ◽  
JOÃO RICARDO SATO ◽  
KANAME KOJIMA ◽  
LUCIANA RODRIGUES GOMES ◽  
MASAO NAGASAKI ◽  
...  
Keyword(s):  
Granger Causality ◽  
Information Flow ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Complete Information ◽  
Gene Expressions ◽  
Vector Autoregressive ◽  
Gene Sets ◽  
Intuitive Concept ◽  
Flow Of Information

Wiener and Granger have introduced an intuitive concept of causality (Granger causality) between two variables which is based on the idea that an effect never occurs before its cause. Later, Geweke generalized this concept to a multivariate Granger causality, i.e. n variables Granger-cause another variable. Although Granger causality is not "effective causality" in the Aristothelic sense, this concept is useful to infer directionality and information flow in observational data. Granger causality is usually identified by using VAR (Vector Autoregressive) models due to their simplicity. In the last few years, several VAR-based models were presented in order to model gene regulatory networks. Here, we generalize the multivariate Granger causality concept in order to identify Granger causalities between sets of gene expressions, i.e. whether a set of n genes Granger-causes another set of m genes, aiming at identifying the flow of information between gene networks (or pathways). The concept of Granger causality for sets of variables is presented. Moreover, a method for its identification with a bootstrap test is proposed. This method is applied in simulated and also in actual biological gene expression data in order to model regulatory networks. This concept may be useful for the understanding of the complete information flow from one network or pathway to the other, mainly in regulatory networks. Linking this concept to graph theory, sink and source can be generalized to node sets. Moreover, hub and centrality for sets of genes can be defined based on total information flow. Another application is in annotation, when the functionality of a set of genes is unknown, but this set is Granger-caused by another set of genes which is well studied. Therefore, this information may be useful to infer or construct some hypothesis about the unknown set of genes.

THE DYNAMICS OF PRICE–VOLUME INFORMATION TRANSFER IN THE CRYPTOCURRENCY MARKETS

2020 ◽  
Vol 23 (05) ◽  
pp. 2050014
Author(s):  
JINGLAN ZHENG ◽  
CHUN-XIAO NIE
Keyword(s):  
Information Flow ◽  
Information Transfer ◽  
Transfer Entropy ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Dynamic Information ◽  
Market Values ◽  
Daily Data ◽  
Flow Of Information

This study examines the information flow between prices and transaction volumes in the cryptocurrency market, where transfer entropy is used for measurement. We selected four cryptocurrencies (Bitcoin, Ethereum, Litecoin and XRP) with large market values, and Bitcoin and BCH (Bitcoin Cash) for hard fork analysis; a hard fork is when a single cryptocurrency splits in two. By examining the real price data, we show that the long-term time series includes too much noise obscuring the local information flow; thus, a dynamic calculation is needed. The long-term and short-term sliding transfer entropy (TE) values and the corresponding [Formula: see text]-values, based on daily data, indicate that there is a dynamic information flow. The dominant direction of which is [Formula: see text]. In addition, the example based on minute Bitcoin data also shows a dynamic flow of information between price and transaction volume. The price–volume dynamics of multiple time scales helps to analyze the price mechanism in the cryptocurrency market.

scholarly journals Emergence of the Affect from the Variation in the Whole-Brain Flow of Information

2019 ◽  
Vol 10 (1) ◽  
pp. 8
Author(s):  
Soheil Keshmiri ◽  
Masahiro Shiomi ◽  
Hiroshi Ishiguro
Keyword(s):  
Information Flow ◽  
Cortical Neurons ◽  
Large Scale ◽  
Brain Activation ◽  
Brain Regions ◽  
Neural Basis ◽  
Whole Brain ◽  
Affect States ◽  
Flow Of Information ◽  
The Brain

Over the past few decades, the quest for discovering the brain substrates of the affect to understand the underlying neural basis of the human’s emotions has resulted in substantial and yet contrasting results. Whereas some point at distinct and independent brain systems for the Positive and Negative affects, others propose the presence of flexible brain regions. In this respect, there are two factors that are common among these previous studies. First, they all focused on the change in brain activation, thereby neglecting the findings that indicate that the stimuli with equivalent sensory and behavioral processing demands may not necessarily result in differential brain activation. Second, they did not take into consideration the brain regional interactivity and the findings that identify that the signals from individual cortical neurons are shared across multiple areas and thus concurrently contribute to multiple functional pathways. To address these limitations, we performed Granger causal analysis on the electroencephalography (EEG) recordings of the human subjects who watched movie clips that elicited Negative, Neutral, and Positive affects. This allowed us to look beyond the brain regional activation in isolation to investigate whether the brain regional interactivity can provide further insights for understanding the neural substrates of the affect. Our results indicated that the differential affect states emerged from subtle variation in information flow of the brain cortical regions that were in both hemispheres. They also showed that these regions that were rather common between affect states than distinct to a specific affect were characterized with both short- as well as long-range information flow. This provided evidence for the presence of simultaneous integration and differentiation in the brain functioning that leads to the emergence of different affects. These results are in line with the findings on the presence of intrinsic large-scale interacting brain networks that underlie the production of psychological events. These findings can help advance our understanding of the neural basis of the human’s emotions by identifying the signatures of differential affect in subtle variation that occurs in the whole-brain cortical flow of information.

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.

scholarly journals Functional determinants of enhanced and depressed inter-areal information flow in NREM sleep between neuronal ensembles in rat cortex and hippocampus

2018 ◽  
Author(s):  
Umberto Olcese ◽  
Jeroen J. Bos ◽  
Martin Vinck ◽  
Cyriel M.A. Pennartz
Keyword(s):  
Information Processing ◽  
Time Scales ◽  
Information Flow ◽  
Rem Sleep ◽  
Transfer Entropy ◽  
Behavioral Task ◽  
Related Information ◽  
Long Time ◽  
The Brain ◽  
Spiking Activity

AbstractCompared to wakefulness, neuronal activity during non-REM sleep is characterized by a decreased ability to integrate information, but also by the re-emergence of task-related information patterns. To investigate the mechanisms underlying these seemingly opposing phenomena, we measured directed information flow by computing transfer entropy between neuronal spiking activity in three cortical regions and the hippocampus of rats across brain states. State-dependent information flow resulted to be jointly determined by the anatomical distance between neurons and by their functional specialization. We distinguished two regimes, operating at short and long time scales, respectively. From wakefulness to non-REM sleep, transfer entropy at short time scales increased for inter-areal connections between neurons showing behavioral task correlates. Conversely, transfer entropy at long time scales became stronger between non-task modulated neurons and weaker between task- modulated neurons. These results may explain how, during non-REM sleep, a global inter-areal disconnection is compatible with highly specific task-related information transfer.Author SummaryThe brain remains active during deep sleep, yet we still do not know which rules govern information processing between neurons across wakefulness and sleep. Here we provide a first study of how information flow at the level of spiking activity varies as a function of brain state, temporal scale, brain area and behavioral task correlates of single neurons. We found that inter-areal communication at millisecond time scales is enhanced during sleep compared to wakefulness between neurons that code for task information. Conversely, non-modulated neurons showed more prominent communication at longer time scales. These results indicate that multiple, functionally determined communicative architectures coexist in the brain, and provide a novel framework to understand information processing and its consequences during sleep.

TEORI KECERDASAN, PENDIDIKAN ANAK, DAN KOMUNIKASI DALAM KELUARGA

1970 ◽  
Vol 6 (1) ◽  
Author(s):  
Muskinul Fuad
Keyword(s):  
Multiple Intelligences ◽  
Educational Activity ◽  
Howard Gardner ◽  
Human Beings ◽  
Brain Functions ◽  
Starting Point ◽  
The Family ◽  
Education Today ◽  
The Brain ◽  
Spatial Logics

The education system in Indonesia emphasize on academic intelligence, whichincludes only two or three aspects, more than on the other aspects of intelligence. For thatreason, many children who are not good at academic intelligence, but have good potentials inother aspects of intelligence, do not develop optimally. They are often considered and labeledas "stupid children" by the existing system. This phenomenon is on the contrary to the theoryof multiple intelligences proposed by Howard Gardner, who argues that intelligence is theability to solve various problems in life and produce products or services that are useful invarious aspects of life.Human intelligence is a combination of various general and specific abilities. Thistheory is different from the concept of IQ (intelligence quotient) that involves only languageskills, mathematical, and spatial logics. According to Gardner, there are nine aspects ofintelligence and its potential indicators to be developed by each child born without a braindefect. What Gardner suggested can be considered as a starting point to a perspective thatevery child has a unique individual intelligence. Parents have to treat and educate theirchildren proportionally and equitably. This treatment will lead to a pattern of education that isfriendly to the brain and to the plurality of children’s potential.More than the above points, the notion that multiple intelligences do not just comefrom the brain needs to be followed. Humans actually have different immaterial (spiritual)aspects that do not refer to brain functions. The belief in spiritual aspects and its potentialsmeans that human beings have various capacities and they differ from physical capacities.This is what needs to be addressed from the perspective of education today. The philosophyand perspective on education of the educators, education stakeholders, and especially parents,are the first major issue to be addressed. With this step, every educational activity andcommunication within the family is expected to develop every aspect of children'sintelligence, especially the spiritual intelligence.

scholarly journals (Ascorb)ing Pb Neurotoxicity in the Developing Brain

Antioxidants ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 1311
Author(s):  
Faraz Ahmad ◽  
Ping Liu
Keyword(s):  
Ascorbic Acid ◽  
Animal Studies ◽  
Redox Homeostasis ◽  
Special Role ◽  
Developmental Exposure ◽  
Brain Functions ◽  
Brain States ◽  
Pb Exposure ◽  
The Brain ◽  
Potent Therapeutic Agent

Lead (Pb) neurotoxicity is a major concern, particularly in children. Developmental exposure to Pb can alter neurodevelopmental trajectory and has permanent neuropathological consequences, including an increased vulnerability to further stressors. Ascorbic acid is among most researched antioxidant nutrients and has a special role in maintaining redox homeostasis in physiological and physio-pathological brain states. Furthermore, because of its capacity to chelate metal ions, ascorbic acid may particularly serve as a potent therapeutic agent in Pb poisoning. The present review first discusses the major consequences of Pb exposure in children and then proceeds to present evidence from human and animal studies for ascorbic acid as an efficient ameliorative supplemental nutrient in Pb poisoning, with a particular focus on developmental Pb neurotoxicity. In doing so, it is hoped that there is a revitalization for further research on understanding the brain functions of this essential, safe, and readily available vitamin in physiological states, as well to justify and establish it as an effective neuroprotective and modulatory factor in the pathologies of the nervous system, including developmental neuropathologies.

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