Causal Event Networks: Cognition, Complexity and Physical Laws

Information flow framed in a computational and complexity context is relevant to the understanding of cognitive processes and awareness. In this paper, we begin with analyzing an information theory framework developed in recent years under Information and Integration Theory (IIT) based on interactions among partitions of cognitive information sets. We discuss the scope and limitations of these ideas, introducing a related measure for partitioning information sets. We introduce a set of postulates describing cognition as a partially ordered set of events in space and time. We consider the relevant sequential and concurrent computational concepts in an idealized minimal cognitive device. The concept of fundamental cognitive chain formalizes temporal limits of cognition.Comment: 31 page

Consciousness, Time and Complexity

We explore the connection between the mind and the brain. We propose that consciousness is the consequence of processing information and that the solution to the binding problem does not entail quantum mechanical coherence or entanglement. We argue for an alternative inspiration from quantum mechanics and quantum field theory based on time-energy uncertainly: not to reduce consciousness to a quantum wave function but to see what quantum mechanics teaches us about information, time, complexity and transformation. We introduce three postulates and a law governing cognitive systems

Intravascular Hemolysis following Acute Zinc Phosphide Poisoning; a Case Report

Zinc phosphide (ZnP) is low-cost, accessible, and very effective as a rodenticide. It has been used for many human suicide poisonings around the world, including Iran. Nonspecific gastrointestinal symptoms and cardiotoxicity are the most serious complications of ZnP poisoning, which are associated with a high mortality rate. The aim of this paper was to report a poisoned patient that ingested ZnP with suicidal attempt and faced complications due to hemolysis

Product Estimators for Hidden Markov Models

In this thesis, risk-sensitive estimation for Hidden Markov Models isstudied from a dynamical systems point of view. We show that risk-sensitive estimators belong to a broaderclass of product estimators in which risk-sensitivity willbe shown to be related to certain scaling functions.The product structureand the scaling functions perspective give us new insights into the underlying mechanism of risk-sensitive estimation.For the first time, in a series of theorems and examples, we relate risk-sensitivity to the dynamics of the underlying process and exposerelations among the transition probabilities, risk-sensitivity andthe decision regions. We introduce the risk-sensitive Maximum A Posterior Probability (MAP) criterion for HMM's with discrete rangeobservation. This criterion is the discrete time finite dimensionalversion of the classic risk-sensitive estimation problem for linear/quadratic partial observation case. The risk-sensitive filters take into account the"higher order" moments of the of the estimation error. In the context of risk-sensitive MAP for HMM's, we clarify and quantify the influence of risk-sensitivityon the behavior of the sample paths of the estimator; theproduct structure representationwill play an important role

Improvement of Drug Delivery Properties of Risperidone via Preparation of Oral Disintegration Tablet Containing Nanostructured Microparticles

Introduction: The aim of this study was to improve the dissolution profile of risperidone and increase the compliance of psychotic patients through the design of an oral disintegration tablet­ (ODT) of microparticles containing nanoparticles. Methods and Results: In order to prepare nanoparticles, the effect of six surfactants on the size and stability of nanoparticles was evaluated. The nanoaggregate fabricated via the spray freeze drying ­(SFD) process using mannitol, lactose and maltodextrin as a matrix agent. Nine formulations were prepared and evaluated on the particle size, dissolution rate , and other physicochemical properties.Finally, the formulations of ODT were designed and evaluated. The results show that using of cremophore EL and hydroxypropyl methyl cellulose E15 with the synergic effect can develop the risperidone nanosuspension with nano range particle size (~188 nm). Also, it is showed that fabrication of risperidone microparticles containig nanoparticles enhanced the drug dissolution up to 2 min for  lactose-based microparticles (as a superior formulation) that is very faster time than coarse risperidone powder with dissolution time of 60 min. the formulations of  ODT containing  10%  Sodium Starch Glycolate and 88% Microcrystalline Cellulose as Super disintegrants were selected with a disintegration time of fewer than 30 seconds and dissolution time of 10 min in superior formulation. Conclusions: It is indicated that the simultaneous use of non-ionic surfactants can prepare risperidone nanoparticles by creating a steric barrier around the drug particles. In addition, the dissolution rate of risperidone has increased significantly due to the small particle size of nanoparticles according to Noyes-Whitney equation. The use of sugars maintains the size of the nanoparticles and prevents the formation of irreversible coalescence of nanoparticles. Thus, this investigation shows that the preparation of microparticles containing nanoparticles using SFD is an easy and usable method for improving the dissolution profile of many low solubility drugs

The Study on Possible Gene Therapy on Diabetics Type I Using Insulin Gene under Control of Heat Shock Promoter in Laboratory Animals

Background: Gene therapy is one of the treatment method for diabetes mellitus. An insulin gene, under control of heat shock inducer promoter was used in the study.Materials and Methods: Six mice used in this study. Streptozotocin (STZ) induced diabetes mellitus in BALB/C mice and rats. Recombinant plasmid was injected to each animal. Animal’s blood sugar (BS) was measured. Warming was done at injection site with a hair dryer to induced gene expression.Results: Immediately after warming blood sugar was increased in mouse 1 and decreased after one hour. However, blood sugar increased again in mice 2 and 4. Blood sugar increased for two hours after warming in mouse 3. Blood sugar increased to 150 mg/dl after STZ injection and immediately after warming reached to 160 mg/dl, after one hour BS dropped to 116 mg/dl and on the second hour was 126 mg/dl, in mouse 5 BS had an increasing trend, BS in mouse 6 had a similar pattern to mouse 2.Conclusion: With fixing the defects of the project will be used in gene therapy in future

The role of serotonin in memory: interactions with neurotransmitters and downstream signaling

Abstract Serotonin, or 5-hydroxytryptamine (5-HT), is found to be involved in many physiological or pathophysiological processes including cognitive function. Seven distinct receptors (5-HT1–7), each with several subpopulations, have been identified for serotonin, which are different in terms of localization and downstream signaling. Because of the development of selective agonists and antagonists for these receptors as well as transgenic animal models of cognitive disorders, our understanding of the role of serotonergic transmission in learning and memory has improved in recent years. A large body of evidence indicates the interplay between serotonergic transmission and other neurotransmitters including acetylcholine, dopamine, γ-aminobutyric acid (GABA) and glutamate, in the neurobiological control of learning and memory. In addition,there has been an alteration in the density of serotonergic receptors in aging and Alzheimer’s disease, and serotonin modulators are found to alter the process of amyloidogenesis and exert cognitive-enhancing properties. Here, we discuss the serotonin-induced modulation of various systems involved in mnesic function including cholinergic, dopaminergic, GABAergic, glutamatergic transmissions as well as amyloidogenesis and intracellular pathways

Risk-Sensitive Probability for Markov Chains

The probability distribution of a Markov chain is viewed as the information state of an additive optimization problem. This optimization problem is then generalized to a product form whose information state gives rise to a generalized notion of probability distributionfor Markov chains. The evolution and the asymptoticbehavior of this generalized or "risk-sensitive"probability distribution is studied in this paper and a conjecture isproposed regarding the asymptotic periodicity of risk-sensitive probability. The relation between a set of simultaneous non-linear equations and the set of periodic attractors is analyzed. <p

Estimation of Hidden Markov Models

A risk-sensitive generalization of the Maximum A Posterior Probability (MAP) estimationfor partially observed Markov chains is presented.Using a change of measure technique,a cascade filtering scheme for the risk-sensitivestate estimation is introduced. Structural results,the influence of the availability of information, mixing and non-mixingdynamics, and the connection with other risk-sensitive estimation methodsare considered. A qualitative analysis of the samplepaths clarifies the underlying mechanism