Density dependent neurodynamics

The dynamics of a neural network depends on density parameters at (at least) two different levels: the subcellular density of ion channels in single neurons, and the density of cells and synapses at a network level. For the Frankenhaeuser-Huxley (FH) neural model, the density of sodium (Na) and potassium (K) channels determines the behaviour of a single neuron when exposed to an external stimulus. The features of the onset of single neuron oscillations vary qualitatively among different regions in the channel density plane. At a network level, the density of neurons is reflected in the global connectivity. We study the relation between the two density levels in a network of oscillatory FH neurons, by qualitatively distinguishing between three regions, where the mean network activity is (1) spiking, (2) oscillating with enveloped frequencies, and (3) bursting, respectively. We demonstrate that the global activity can be shifted between regions by changing either the density of ion channels at the subcellular level, or the connectivity at the network level, suggesting that different underlying mechanisms can explain similar global phenomena. Finally, we model a possible effect of anaesthesia by blocking specific inhibitory ion channels.     

A method of statistical neurodynamics

A method of statistical neurodynamics is presented for treating ensembles of nets of randomly connected neuron-like elements. The concept of a macrostate plays a fundamental role in statistical neurodynamics and a criterion is given for ascertaining that given macroscopic quantities together constitute a macrostate. The activity of a nerve net is shown to be a macrostate and the equation of the dynamics of the activity is elucidated for various ensembles of random nerve nets. It is shown that the distance between two microstates can also be treated as a macrostate in a generalized sense. The equation of its dynamics represents how the distance between two states changes in the course of state transitions. The dynamics of distance reveals interesting microscopic properties of random nerve nets, such as the stability of state-transition, the transient lengths, etc.     

A neural network model of attention-modulated neurodynamics

Visual attention appears to modulate cortical neurodynamics and synchronization through various cholinergic mechanisms. In order to study these mechanisms, we have developed a neural network model of visual cortex area V4, based on psychophysical, anatomical and physiological data. With this model, we want to link selective visual information processing to neural circuits within V4, bottom-up sensory input pathways, top-down attention input pathways, and to cholinergic modulation from the prefrontal lobe. We investigate cellular and network mechanisms underlying some recent analytical results from visual attention experimental data. Our model can reproduce the experimental findings that attention to a stimulus causes increased gamma-frequency synchronization in the superficial layers. Computer simulations and STA power analysis also demonstrate different effects of the different cholinergic attention modulation action mechanisms.     

Terminal chaos for information processing in neurodynamics

New nonlinear phenomenon — terminal chaos caused by failure of the Lipschitz condition at equilibrium points of dynamical systems is introduced. It is shown that terminal chaos has a well organized probabilistic structure which can be predicted and controlled. This gives an opportunity to exploit this phenomenon for information processing. It appears that chaotic states of neurons activity are associated with higher level of cognitive processes such as generalization and abstraction.     

On the neurodynamics of the creation of consciousness

Consciousness is expected to have a specific temporal dynamics. The COrollary Discharge of Attention Movement (CODAM) model of consciousness is deduced from an engineering approach to attention and motor attention. This model is briefly described, as is support arising from brain dynamics, especially that for the attentional blink. The understanding of known temporal dynamics in the brain associated with the emergence of consciousness is then developed from CODAM, and specifically related to the N2 ERP brain signal. How the pre-reflective self, as content-free, interacts with the content of experience is discussed in terms of the possibility that such experience arises from some proto-self generated by body signals; experiments are described which indicate that no pre-reflective self based on body signals is observable. Only a content-free pre-reflective self is consistent with this data, as CODAM suggests. How such a pre-reflective self can be further fused to give temporal continuity of a sense of self is considered in terms of various mechanisms which could be present for preserving the sense of self. The observation of the N2 signal in hippocampal encoding is proposed as providing a justification for the encoding of the N2–P3 sequence of brain signals. This would correspond to episodic encoding of the sequence of experiences of the pre-reflective self; this will thereby provide the necessary control signals in time so that ‘I’ is experienced as part of the retrieval of such memories.     

Heritability of neurodynamics and psychodynamics in human populations

A component analysis of human neurodynamic and psychodynamic characters in the norm was carried out in 8 human populations characterized by different degrees of isolation and ethnic origin. An increase in phenotypic variability and a decrease in heritability with increasing complexity of organization of the characters under study were demonstrated for all these populations. The additive effect plays the major role in genetic determination of neurodynamic and psychodynamic characters studied. For a number of neurodynamic parameters the effect of intralocus dominance indicative of the oligogenic determination system was observed. Data in favour of real contribution of the factors linked to X-chromosome were obtained for simple sensomotor reactions.     

The neurodynamics underlying attentional control in set shifting tasks

In this work we address key phenomena observed with classical set shifting tasks as the “Wisconsin Card Sorting Test” or the “Stroop” task: Different types of errors and increased response times reflecting decreased attention. A component of major importance in these tasks is referred to as the “attentional control” thought to be implemented by the prefrontal cortex which acts primarily by an amplification of task relevant information. This mode of operation is illustrated by a neurodynamical model developed for a new kind of set shifting experiment: The Wisconsin-Delayed-Match-to-Sample task combines uninstructed shifts as investigated in Wisconsin-like tasks with a Delayed-Match-to-Sample paradigm. These newly developed WDMS experiments in conjunction with the neurodynamical simulations are able to explain the reason for decreased attention in set shifting experiments as well the different consequences of decreased attention in tasks requiring bivalent yes/no responses compared to tasks requiring multivalent responses. Electronic supplementary material  The online version of this article (doi: ) contains supplementary material, which is available to authorized users.

On consciousness,resting state fMRI,and neurodynamics

Background

During the last years, functional magnetic resonance imaging (fMRI) of the brain has been introduced as a new tool to measure consciousness, both in a clinical setting and in a basic neurocognitive research. Moreover, advanced mathematical methods and theories have arrived the field of fMRI (e.g. computational neuroimaging), and functional and structural brain connectivity can now be assessed non-invasively.

Results

The present work deals with a pluralistic approach to "consciousness'', where we connect theory and tools from three quite different disciplines: (1) philosophy of mind (emergentism and global workspace theory), (2) functional neuroimaging acquisitions, and (3) theory of deterministic and statistical neurodynamics – in particular the Wilson-Cowan model and stochastic resonance.

Conclusions

Based on recent experimental and theoretical work, we believe that the study of large-scale neuronal processes (activity fluctuations, state transitions) that goes on in the living human brain while examined with functional MRI during "resting state", can deepen our understanding of graded consciousness in a clinical setting, and clarify the concept of "consiousness" in neurocognitive and neurophilosophy research.

     

Mesoscopic Model of Actin-Based Propulsion

Two theoretical models dominate current understanding of actin-based propulsion: microscopic polymerization ratchet model predicts that growing and writhing actin filaments generate forces and movements, while macroscopic elastic propulsion model suggests that deformation and stress of growing actin gel are responsible for the propulsion. We examine both experimentally and computationally the 2D movement of ellipsoidal beads propelled by actin tails and show that neither of the two models can explain the observed bistability of the orientation of the beads. To explain the data, we develop a 2D hybrid mesoscopic model by reconciling these two models such that individual actin filaments undergoing nucleation, elongation, attachment, detachment and capping are embedded into the boundary of a node-spring viscoelastic network representing the macroscopic actin gel. Stochastic simulations of this ‘in silico’ actin network show that the combined effects of the macroscopic elastic deformation and microscopic ratchets can explain the observed bistable orientation of the actin-propelled ellipsoidal beads. To test the theory further, we analyze observed distribution of the curvatures of the trajectories and show that the hybrid model''s predictions fit the data. Finally, we demonstrate that the model can explain both concave-up and concave-down force-velocity relations for growing actin networks depending on the characteristic time scale and network recoil. To summarize, we propose that both microscopic polymerization ratchets and macroscopic stresses of the deformable actin network are responsible for the force and movement generation.     

Comparative population analysis of the variability of human neurodynamics and psychodynamics

A number of characteristics of morphological, neurodynamical, and psychodynamical levels of organization of individual personality was studied in five isolated different ethnical populations and two panmixic ones. The degree of heritability was found to decrease and that of variability to increase with the rise of organization level. Significant interpopulational differences were shown in the mean values of characteristics under study and their dispersions. The results obtained were discussed in connection with peculiarities of genetical and social structures of investigated human populations.     

Mesoscopic modeling of bacterial flagellar microhydrodynamics

A particle-based hybrid method of elastic network model and smooth-particle hydrodynamics has been employed to describe the propulsion of bacterial flagella in a viscous hydrodynamic environment. The method explicitly models the two aspects of bacterial propulsion that involve flagellar flexibility and long-range hydrodynamic interaction of low-Reynolds-number flow. The model further incorporates the molecular organization of the flagellar filament at a coarse-grained level in terms of the 11 protofilaments. Each of these protofilaments is represented by a collection of material points that represent the flagellin proteins. A computational model of a single flexible helical segment representing the filament of a bacterial flagellum is presented. The propulsive dynamics and the flow fields generated by the motion of the model filament are examined. The nature of flagellar deformation and the influence of hydrodynamics in determining the shape of deformations are examined based on the helical filament.     

Mesoscopic lateral diffusion in lipid bilayers

The lateral diffusion in bilayers is modeled with a multiscale mesoscopic simulation. The methodology consists of two simulations, where the first employs atomistic models to obtain exact results for the mesoscopic model. The second simulation takes the results obtained from the first to parameterize an effective force field that is employed in a new coarse-grained model. The multiscale aspect of this scheme occurs at the point where the microscopic time-averaged results of the first simulation are employed to parameterize the second simulation that operates in a higher spatial and temporal domain. The results of both simulation schemes give quantitative information on the details associated with lipid lateral diffusion.     

Mesoscopic gels at low agarose concentration: perturbation effects of ethanol.

Aqueous agarose solutions at low concentrations (0.5 g/liter) were temperature quenched below the spinodal line to form mutually disconnected mesoscopic gels. In the presence of 6% ethanol, these solutions, obtained by quenching at the same temperature depth as in pure water, appear much more fluid, as determined by probe diffusion experiments. We show by static and dynamic light scattering that this can be explained by the solvent-mediated effects of ethanol, leading to a globular shape of mesoscopic agarose gels, rather than to an extended rodlike structure observed in pure water. Our findings show the significant effects of solvent perturbations on particle condensation and, therefore, may be useful in understanding the role of the solvent in the folding of biomolecules.     

The role of interhemispheric neurodynamics in the process of probability predicting]

The interhemispheric asymmetry of electrocortical components of the orienting reaction (the amplitude and latency of P300) were studied in the projection (occipital) and associative (central) areas in 8 subjects who were capable for adequate prediction under conditions of different information significance and 6 subjects with prediction problems. Under conditions of relevant stimulation, the amplitude asymmetry was more expressed and the latency of P300 in the central areas of both hemispheres was considerably shorter in good predictors than in bad ones. The rostrocaudal activation gradient was more expressed in good than in bad predictors, especially, under conditions of high information importance. It is suggested that the observed asymmetry in persons with prediction problems is related with nonspecific activation of subcortical structures and in good predictors it is caused by the local neocortical activation.