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Mutual Information (mutual + information)
Selected AbstractsDevelopmental experience alters information coding in auditory midbrain and forebrain neuronsDEVELOPMENTAL NEUROBIOLOGY, Issue 4 2010Sarah M.N. Woolley Abstract In songbirds, species identity and developmental experience shape vocal behavior and behavioral responses to vocalizations. The interaction of species identity and developmental experience may also shape the coding properties of sensory neurons. We tested whether responses of auditory midbrain and forebrain neurons to songs differed between species and between groups of conspecific birds with different developmental exposure to song. We also compared responses of individual neurons to conspecific and heterospecific songs. Zebra and Bengalese finches that were raised and tutored by conspecific birds, and zebra finches that were cross-tutored by Bengalese finches were studied. Single-unit responses to zebra and Bengalese finch songs were recorded and analyzed by calculating mutual information (MI), response reliability, mean spike rate, fluctuations in time-varying spike rate, distributions of time-varying spike rates, and neural discrimination of individual songs. MI quantifies a response's capacity to encode information about a stimulus. In midbrain and forebrain neurons, MI was significantly higher in normal zebra finch neurons than in Bengalese finch and cross-tutored zebra finch neurons, but not between Bengalese finch and cross-tutored zebra finch neurons. Information rate differences were largely due to spike rate differences. MI did not differ between responses to conspecific and heterospecific songs. Therefore, neurons from normal zebra finches encoded more information about songs than did neurons from other birds, but conspecific and heterospecific songs were encoded equally. Neural discrimination of songs and MI were highly correlated. Results demonstrate that developmental exposure to vocalizations shapes the information coding properties of songbird auditory neurons. © 2009 Wiley Periodicals, Inc. Develop Neurobiol 70: 235,252, 2010. [source] Gaussian inputs: performance limits over non-coherent SISO and MIMO channelsEUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, Issue 3 2007Rasika R. Perera Performance limits of information transfer over a discrete time memoryless Rayleigh fading channel with neither the receiver nor the transmitter knowing the fading coefficients except its statistics is an important problem in information theory. We derive closed form expressions for the mutual information of single input single output (SISO) and multiple input multiple output (MIMO) Rayleigh fading channels for any antenna number at any signal to noise ratio (SNR). Using these expressions, we show that the maximum mutual information of non-coherent Rayleigh fading MIMO channels is achieved with a single transmitter and multiple receivers when the input distribution is Gaussian. We show that the addition of transmit antennas for a fixed number of receivers result in a reduction of mutual information. Furthermore, we argue that the mutual information is bounded by the SNR in both SISO and MIMO systems showing the sub-optimality of Gaussian signalling in non-coherent Rayleigh fading channels. Copyright © 2006 AEIT [source] Mutual-information-based approach for neural connectivity during self-paced finger lifting taskHUMAN BRAIN MAPPING, Issue 3 2008Chun-Chuan Chen Abstract Frequency-dependent modulation between neuronal assemblies may provide insightful mechanisms of functional organization in the context of neural connectivity. We present a conjoined time-frequency cross mutual information (TFCMI) method to explore the subtle brain neural connectivity by magnetoencephalography (MEG) during a self-paced finger lifting task. Surface electromyogram (sEMG) was obtained from the extensor digitorum communis. Both within-modality (MEG-MEG) and between-modality studies (sEMG-MEG) were conducted. The TFCMI method measures both the linear and nonlinear dependencies of the temporal dynamics of signal power within a pre-specified frequency band. Each single trial of MEG across channels and sEMG signals was transformed into time-frequency domain with use of the Morlet wavelet to obtain better temporal spectral (power) information. As compared to coherence approach (linear dependency only) in broadband analysis, the TFCMI method demonstrated advantages in encompassing detection for the mesial frontocentral cortex and bilateral primary sensorimotor areas, clear demarcation of event- and non-event-related regions, and robustness for sEMG - MEG between-modality study, i.e., corticomuscular communication. We conclude that this novel TFCMI method promises a possibility to better unravel the intricate functional organizations of brain in the context of oscillation-coded communication. Hum Brain Mapp, 2008. © 2007 Wiley-Liss, Inc. [source] Improved inter-modality image registration using normalized mutual information with coarse-binned histogramsINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, Issue 6 2009Haewon Nam Abstract In this paper we extend the method of inter-modality image registration using the maximization of normalized mutual information (NMI) for the registration of [18F]-2-fluoro-deoxy-D-glucose (FDG)-positron emission tomography (PET) with T1-weighted magnetic resonance (MR) volumes. We investigate the impact on the NMI maximization with respect to using coarse-to-fine grained B-spline bases and to the number of bins required for the voxel intensity histograms of each volume. Our results demonstrate that the efficiency and accuracy of elastic, as well as rigid body, registration is improved both through the use of a reduced number of bins in the PET and MR histograms, and of a limited coarse-to-fine grain interpolation of the volume data. To determine the appropriate number of bins prior to registration, we consider the NMI between the two volumes, the mutual information content of the two volumes, as a function of the binning of each volume. Simulated data sets are used for validation and the registration improves that obtained with a standard approach based on the Statistical Parametric Mapping software. Copyright © 2008 John Wiley & Sons, Ltd. [source] The communication of meaning and the structuration of expectations: Giddens' "structuration theory" and Luhmann's "self-organization"JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 10 2010Loet Leydesdorff The communication of meaning as distinct from (Shannon-type) information is central to Luhmann's social systems theory and Giddens' structuration theory of action. These theories share an emphasis on reflexivity, but focus on meaning along a divide between interhuman communication and intentful action as two different systems of reference. Recombining these two theories into a theory about the structuration of expectations, interactions, organization, and self-organization of intentional communications can be simulated based on algorithms from the computation of anticipatory systems. The self-organizing and organizing layers remain rooted in the double contingency of the human encounter, which provides the variation. Organization and self-organization of communication are reflexive upon and therefore reconstructive of each other. Using mutual information in three dimensions, the imprint of meaning processing in the modeling system on the historical organization of uncertainty in the modeled system can be measured. This is shown empirically in the case of intellectual organization as "structurating" structure in the textual domain of scientific articles. [source] Prediction Variance and Information Worth of Observations in Time SeriesJOURNAL OF TIME SERIES ANALYSIS, Issue 4 2000Mohsen Pourahmadi The problem of developing measures of worth of observations in time series has not received much attention in the literature. Any meaningful measure of worth should naturally depend on the position of the observation as well as the objectives of the analysis, namely parameter estimation or prediction of future values. We introduce a measure that quantifies worth of a set of observations for the purpose of prediction of outcomes of stationary processes. The worth is measured as the change in the information content of the entire past due to exclusion or inclusion of a set of observations. The information content is quantified by the mutual information, which is the information theoretic measure of dependency. For Gaussian processes, the measure of worth turns out to be the relative change in the prediction error variance due to exclusion or inclusion of a set of observations. We provide formulae for computing predictive worth of a set of observations for Gaussian autoregressive moving-average processs. For non-Gaussian processes, however, a simple function of its entropy provides a lower bound for the variance of prediction error in the same manner that Fisher information provides a lower bound for the variance of an unbiased estimator via the Cramer-Rao inequality. Statistical estimation of this lower bound requires estimation of the entropy of a stationary time series. [source] Fetal heart rate monitoring from maternal body surface potentials using independent component analysisANIMAL SCIENCE JOURNAL, Issue 5 2004Wenxi CHEN ABSTRACT The fetal heart rate is indispensable for monitoring the health of unborn cattle fetuses. To monitor the fetal heart rate, a method employing independent component analysis (ICA) to extract the fetal electrocardiogram (fECG) from potentials measured on the maternal body surface and composed of a mixture of the maternal ECG (mECG), fECG, baseline drift and noise is described. A mixing of the raw data was simplified using a linear time-invariant model. To separate the fECG from the mECG, baseline drift, and noise, an ICA strategy was applied, using a hyperbolic tangent as the contrast function and treating mutual information with the minimization principle to find the optimum demixing matrix to derive the fECG from the measured signals. After the feasibility of this method was shown on simulated signals obtained by randomly mixing pure fECG, pure mECG, low frequency sinusoidal drift and noise, real signals from three cloned pregnant Holstein cows with 157, 177 and 224-day gestation periods were used to verify the separation method. The results show that the fECG, mECG, low-frequency sinusoidal drift and noise can be clearly segregated in simulations, and that the fECG, mECG, baseline drift and noise can be successfully derived from real signals. The ICA approach has great potential in effectively detecting the fECG from maternal body surface potentials. [source] Thermal roots of correlation-based complexity,COMPLEXITY, Issue 3 2008Philip Fraundorf Abstract Bayesian maxent lets one integrate thermal physics and information theory points of view in the quantitative study of complex systems. Since net surprisal (a free energy analog for measuring "departures from expected") allows one to place second law constraints on mutual information (a multimoment measure of correlations), it makes a quantitative case for the role of reversible thermalization in the natural history of invention, and suggests multiscale strategies to monitor standing crop as well. It prompts one to track evolved complexity starting from live astrophysically observed processes, rather than only from evidence of past events. Various gradients and boundaries that play a role in availability flow, ranging from the edge of a wave-packet to the boundary between idea-pools, allow one to frame wide-ranging correlations (including that between a phenomenon and its explanation) as delocalized physical structures. © 2007 Wiley Periodicals, Inc. Complexity, 2008 [source] Winner-relaxing and winner-enhancing Kohonen maps: Maximal mutual information from enhancing the winnerCOMPLEXITY, Issue 4 2003Jens Christian Claussen Abstract The magnification behavior of a generalized family of self-organizing feature maps, the winner relaxing and winner enhancing Kohonen algorithms is analyzed by the magnification law in the one-dimensional case, which can be obtained analytically. The winner-enhancing case allows to achieve a magnification exponent of one and therefore provides optimal mapping in the sense of information theory. A numerical verification of the magnification law is included, and the ordering behavior is analyzed. Compared to the original self-organizing map and some other approaches, the generalized winner enforcing algorithm requires minimal extra computations per learning step and is conveniently easy to implement. © 2003 Wiley Periodicals, Inc. [source] | ||||||||||||||||