Geometry of Information Integration

Information geometry is used to quantify the amount of information integration within multiple terminals of a causal dynamical system. Integrated information quantifies how much information is lost when a system is split into parts and information transmission between the parts is removed. Multiple measures have been proposed as a measure of integrated information. Here, we analyze four of the previously proposed measures and elucidate their relations from a viewpoint of information geometry. Two of them use dually flat manifolds and the other two use curved manifolds to define a split model. We show that there are hierarchical structures among the measures. We provide explicit expressions of these measures

Magical Contagion and AIDS Scale: Development and Validation

A Magical Contagion and AIDS Scale was developed to address problems with existing Contagion and AIDS measures. Magical Contagion is an influence that exists after contact is terminated. It is comprised of Permanence, Holographic Effects, Moral Germ Conflation and Backward Action. Data from 280 undergraduates revealed low mean levels of Magical Contagion and AIDS. Contagion effects did not differ on demographic variables. Content validity, criterion-related validity, discriminate validity, and internal consistency were evaluated. Significant correlations were found between the Contagion Scale and Merging/Separation and Homophobia Scales. Negative correlations were found between the Contagion scale and the AIDS knowledge and social desirability scales. Alpha reliabilities were high (a > .93) for the Contagion scale and subscales. Factor analysis suggested the existence of a single factor and mixed support for three factors

A Tale of Two Animats: What does it take to have goals?

What does it take for a system, biological or not, to have goals? Here, this question is approached in the context of in silico artificial evolution. By examining the informational and causal properties of artificial organisms ('animats') controlled by small, adaptive neural networks (Markov Brains), this essay discusses necessary requirements for intrinsic information, autonomy, and meaning. The focus lies on comparing two types of Markov Brains that evolved in the same simple environment: one with purely feedforward connections between its elements, the other with an integrated set of elements that causally constrain each other. While both types of brains 'process' information about their environment and are equally fit, only the integrated one forms a causally autonomous entity above a background of external influences. This suggests that to assess whether goals are meaningful for a system itself, it is important to understand what the system is, rather than what it does.Comment: This article is a contribution to the FQXi 2016-2017 essay contest "Wandering Towards a Goal

Impurity Effect on Superconducting Properties in Molecular Substituted Organic Superconductor κ\kappa-(ET)2_2Cu(NCS)2_2

We report an impurity effect in the organic superconductor $\kappa$-(ET)$_2$Cu(NCS)$_2$ by substitution of the ET molecule with an analogue, bis(methyleneditio)tetrathiafulvalene (MT). The superconducting transition temperature decreases with increasing substitution. The in-plane magnetic penetration depth is enhanced with substitution, which is quantitatively attributed to the decrease in the in-plane mean free path. The enhancement of the penetration depth can also explain the reduction of the effective pinning in terms of the condensation energy.Comment: 4 pages, submitted to J. Phys. Soc. Jp

Inhomogeneous superconductivity in organic conductors: role of disorder and magnetic field

Several experimental studies have shown the presence of spatially inhomogeneous phase coexistence of superconducting and non superconducting domains in low dimensional organic superconductors. The superconducting properties of these systems are found to be strongly dependent on the amount of disorder introduced in the sample regardless of its origin. The suppression of the superconducting transition temperature $T_c$ shows clear discrepancy with the result expected from the Abrikosov-Gor'kov law giving the behavior of $T_c$ with impurities. Based on the time dependent Ginzburg-Landau theory, we derive a model to account for the striking feature of $T_c$ in organic superconductors for different types of disorder by considering the segregated texture of the system. We show that the calculated $T_c$ quantitatively agrees with experiments. We also focus on the role of superconducting fluctuations on the upper critical fields $H_{c2}$ of layered superconductors showing slab structure where superconducting domains are sandwiched by non-superconducting regions. We found that $H_{c2}$ may be strongly enhanced by such fluctuations.Comment: to appear in Journal of Physics: Condensed Matte

Complexity of multi-dimensional spontaneous EEG decreases during propofol induced general anaesthesia

Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions). In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation. Here we investigated complexity of spontaneous high-density EEG data during propofol-induced general anaesthesia. We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels. After some simulations on Kuramoto oscillator models which demonstrate that these measures capture distinct ‘flavours’ of complexity, we show that there is a robustly measurable decrease in the complexity of spontaneous EEG during general anaesthesia

Dynamical complexity in the C.elegans neural network

We model the neuronal circuit of the C.elegans soil worm in terms of a Hindmarsh-Rose system of ordinary differential equa- tions, dividing its circuit into six communities which are determined via the Walktrap and Louvain methods. Using the numerical solution of these equations, we analyze important measures of dynamical com- plexity, namely synchronicity, the largest Lyapunov exponent, and the ?AR auto-regressive integrated information theory measure. We show that ?AR provides a useful measure of the information contained in the C.elegans brain dynamic network. Our analysis reveals that the C.elegans brain dynamic network generates more information than the sum of its constituent parts, and that attains higher levels of integrated information for couplings for which either all its communities are highly synchronized, or there is a mixed state of highly synchronized and de- synchronized communities

Angiotensin-converting enzyme gene and retinal arteriolar narrowing: The Funagata Study

The purpose of this study is to determine whether the angiotensin-converting enzyme (ACE) gene polymorphism is associated with retinal arteriolar narrowing, a subclinical marker of chronic hypertension. The Funagata Study examined a population-based sample of Japanese aged 35+ years; 368 participants had both retinal vessel diameter measurements and ACE insertion/deletion (ACE I/D) polymorphism analyses performed. Assessment of retinal vessel diameter and retinal vessel wall signs followed the protocols used in the Blue Mountains Eye Study. ACE gene polymorphisms D/D, I/D and I/I were present in 34 (9.2%), 170 (46.2%) and 164 (44.5%) participants, respectively, distributed in Hardy–Weinberg equilibrium. After multivariable adjustment, retinal arteriolar diameter was significantly narrower in subjects with the D/D genotype compared to subjects with I/D and I/I genotypes (mean difference −6.49 μm, 95% confidence interval (CI): −12.86 μm, −0.11 μm). Our study suggests that the ACE I/D polymorphism may be associated with subclinical structural arteriolar changes related to chronic hypertension

γ-Secretase inhibitor enhances antitumour effect of radiation in Notch-expressing lung cancer

BACKGROUND: Notch receptor has an important role in both development and cancer. We previously reported that inhibition of the Notch3 by γ-secretase inhibitor (GSI) induces apoptosis and suppresses tumour proliferation in non-small-cell lung cancer. Although radiation is reported to induce Notch activation, little is known about the relationship between radiation and Notch pathway. METHODS: We examined the effect of combining GSI and radiation at different dosing in three Notch expressing lung cancer cell lines. The cytotoxic effect of GSI and radiation was evaluated using MTT assay and clonogenic assay in vitro and xenograft models. Expressions of Notch pathway, mitogen-activated protein kinase (MAPK) pathway and Bcl-2 family proteins were investigated using western blot analysis. RESULTS: We discovered that the antitumour effect of combining GSI and radiation was dependent on treatment schedule. γ-Secretase inhibitor administration after radiation had the greatest growth inhibition of lung cancer in vitro and in vivo. We showed that the combination induced apoptosis of lung cancer cell lines through the regulation of MAPK and Bcl-2 family proteins. Furthermore, activation of Notch after radiation was ameliorated by GSI administration, suggesting that treatment with GSI prevents Notch-induced radiation resistance. CONCLUSION: Notch has an important role in lung cancer. Treatment with GSI after radiation can significantly enhance radiation-mediated tumour cytotoxicity