14,980 research outputs found
Propofol Induction Reduces the Capacity for Neural Information Integration: Implications for the Mechanism of Consciousness and General Anesthesia
The cognitive unbinding paradigm suggests that the synthesis of cognitive information is attenuated by general anesthesia. Here, we investigated the functional organization of brain activities in the conscious and anesthetized states, based on characteristic functional segregation and integration of electroencephalography (EEG). EEG recordings were obtained from 14 subjects undergoing induction of general anesthesia with propofol. We quantified changes in mean information integration capacity in each band of the EEG. After induction with propofol, mean information integration capacity was reduced most prominently in the gamma band of the EEG (p=0.0001). Furthermore, we demonstrate that loss of consciousness is reflected by the breakdown of the spatiotemporal organization of gamma waves. Induction of general anesthesia with propofol reduces the capacity for information integration in the brain. These data directly support the information integration theory of consciousness and the cognitive unbinding paradigm of general anesthesia
Solitonic Effects of the Local Electromagnetic Field on Neuronal Microtubules
Current wisdom in classical neuroscience suggests that the only direct action of the electric field in neurons is upon voltage-gated ion channels which open and close their gates during the passage of ions. The intraneuronal biochemical activities are thought to be modulated indirectly either by entering into the cytoplasm ions that act as\ud
second messengers, or via linkage to the ion channels enzymes. In this paper we present a novel possibility for subneuronal processing of information by cytoskeletal microtubule tubulin tails and we show that the local electromagnetic field supports information that could\ud
be converted into specific protein tubulin tail conformational states. Long-range collective coherent behavior of the tubulin tails could be modelled in the form of solitary waves such as sine-Gordon kinks, antikinks or breathers that propagate along the microtubule outer\ud
surface, and the tubulin tail soliton collisions could serve as elementary computational gates that control cytoskeletal processes. The biological importance of the presented model is due to the unique biological enzymatic energase action of the tubulin tails, which is experimentally verified for controlling the sites of microtubule-associated protein\ud
attachment and the kinesin transport of post-Golgi vesicles
Multi-Particle Collision Dynamics -- a Particle-Based Mesoscale Simulation Approach to the Hydrodynamics of Complex Fluids
In this review, we describe and analyze a mesoscale simulation method for
fluid flow, which was introduced by Malevanets and Kapral in 1999, and is now
called multi-particle collision dynamics (MPC) or stochastic rotation dynamics
(SRD). The method consists of alternating streaming and collision steps in an
ensemble of point particles. The multi-particle collisions are performed by
grouping particles in collision cells, and mass, momentum, and energy are
locally conserved. This simulation technique captures both full hydrodynamic
interactions and thermal fluctuations. The first part of the review begins with
a description of several widely used MPC algorithms and then discusses
important features of the original SRD algorithm and frequently used
variations. Two complementary approaches for deriving the hydrodynamic
equations and evaluating the transport coefficients are reviewed. It is then
shown how MPC algorithms can be generalized to model non-ideal fluids, and
binary mixtures with a consolute point. The importance of angular-momentum
conservation for systems like phase-separated liquids with different
viscosities is discussed. The second part of the review describes a number of
recent applications of MPC algorithms to study colloid and polymer dynamics,
the behavior of vesicles and cells in hydrodynamic flows, and the dynamics of
viscoelastic fluids
The Hydrodynamics of Active Systems
This is a series of four lectures presented at the 2015 Enrico Fermi summer
school in Varenna. The aim of the lectures is to give an introduction to the
hydrodynamics of active matter concentrating on low Reynolds number examples
such as cells and molecular motors. Lecture 1 introduces the hydrodynamics of
single active particles, covering the Stokes equation and the Scallop Theorem,
and stressing the link between autonomous activity and the dipolar symmetry of
the far flow field. In lecture 2 I discuss applications of this mathematics to
the behaviour of microswimmers at surfaces and in external flows, and describe
our current understanding of how swimmers stir the surrounding fluid. Lecture 3
concentrates on the collective behaviour of active particles, modelled as an
active nematic. I write down the equations of motion and motivate the form of
the active stress. The resulting hydrodynamic instability leads to a state
termed active turbulence characterised by strong jets and vortices in the flow
field and the continual creation and annihilation of pairs of topological
defects. Lecture 4 compares simulations of active turbulence to experiments on
suspensions of microtubules and molecular motors. I introduce lyotropic active
nematics and discuss active anchoring at interfaces.Comment: Lecture Notes, 2015 Enrico Fermi Summer School on Soft Matter
Self-Assembly, Vienn
Relaxation paths for single modes of vibrations in isolated molecules
A numerical simulation of vibrational excitation of molecules was devised,
and used to excite computational models of common molecules into a prescribed,
pure, normal vibration mode in the ground electronic state, with varying,
controlable energy content. The redistribution of this energy (either
non-chaotic or irreversible IVR) within the isolated, free molecule is then
followed in time with a view to determining the coupling strength between
modes. This work was triggered by the need to predict the general characters of
the infrared spectra to be expected from molecules in interstellar space, after
being excited by photon absorption or reaction with a radical. It is found that
IVR from a pure normal mode is very "restricted" indeed at energy contents of
one mode quantum or so. However, as this is increased, or when the excitation
is localized, our approach allows us to isolate, describe and quantify a number
of interesting phenomena, known to chemists and in non-linear mechanics, but
difficult to demonstrate experimentally: frequency dragging, mode locking or
quenching or, still, instability near a potential surface crossing, the first
step to generalized chaos as the energy content per mode is increased.Comment: 25 pages, 15 figures; accepted by J. Atom. Phys.
Implicit complexity for coinductive data: a characterization of corecurrence
We propose a framework for reasoning about programs that manipulate
coinductive data as well as inductive data. Our approach is based on using
equational programs, which support a seamless combination of computation and
reasoning, and using productivity (fairness) as the fundamental assertion,
rather than bi-simulation. The latter is expressible in terms of the former. As
an application to this framework, we give an implicit characterization of
corecurrence: a function is definable using corecurrence iff its productivity
is provable using coinduction for formulas in which data-predicates do not
occur negatively. This is an analog, albeit in weaker form, of a
characterization of recurrence (i.e. primitive recursion) in [Leivant, Unipolar
induction, TCS 318, 2004].Comment: In Proceedings DICE 2011, arXiv:1201.034
Footprints of information foragers: Behaviour semantics of visual exploration
Social navigation exploits the knowledge and experience of peer users of information resources. A wide variety of visual–spatial approaches become increasingly popular as a means to optimize information access as well as to foster and sustain a virtual community among geographically distributed users. An information landscape is among the most appealing design options of representing and communicating the essence of distributed information resources to users. A fundamental and challenging issue is how an information landscape can be designed such that it will not only preserve the essence of the underlying information structure, but also accommodate the diversity of individual users. The majority of research in social navigation has been focusing on how to extract useful information from what is in common between users' profiles, their interests and preferences. In this article, we explore the role of modelling sequential behaviour patterns of users in augmenting social navigation in thematic landscapes. In particular, we compare and analyse the trails of individual users in thematic spaces along with their cognitive ability measures. We are interested in whether such trails can provide useful guidance for social navigation if they are embedded in a visual–spatial environment. Furthermore, we are interested in whether such information can help users to learn from each other, for example, from the ones who have been successful in retrieving documents. In this article, we first describe how users' trails in sessions of an experimental study of visual information retrieval can be characterized by Hidden Markov Models. Trails of users with the most successful retrieval performance are used to estimate parameters of such models. Optimal virtual trails generated from the models are visualized and animated as if they were actual trails of individual users in order to highlight behavioural patterns that may foster social navigation. The findings of the research will provide direct input to the design of social navigation systems as well as to enrich theories of social navigation in a wider context. These findings will lead to the further development and consolidation of a tightly coupled paradigm of spatial, semantic and social navigation
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