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PubMed2006

Dynamics of memory representations in networks with novelty-facilitated synaptic plasticity.

The ability to associate some stimuli while differentiating between others is an essential characteristic of biological memory. Theoretical models identify memories as attractors of neural network activity, with learning based on Hebb-like synaptic modifications. Our analysis shows that when network inputs are correlated, this mechanism results in overassociations, even up to several memories "merging" into one. To counteract this tendency, we introduce a learning mechanism that involves novelty-facilitated modifications, accentuating synaptic changes proportionally to the difference between network input and stored memories. This mechanism introduces a dependency of synaptic modifications on previously acquired memories, enabling a wide spectrum of memory associations, ranging from absolute discrimination to complete merging. The model predicts that memory representations should be sensitive to learning order, consistent with recent psychophysical studies of face recognition and electrophysiological experiments on hippocampal place cells. The proposed mechanism is compatible with a recent biological model of novelty-facilitated learning in hippocampal circuitry.

Animals↗
PubMed2006

Experience-dependent plasticity in adult visual cortex.

Experience-dependent plasticity is a prominent feature of the mammalian visual cortex. Although such neural changes are most evident during development, adult cortical circuits can be modified by a variety of manipulations, such as perceptual learning and visual deprivation. Elucidating the underlying mechanisms at the cellular and synaptic levels is an essential step in understanding neural plasticity in the mature animal. Although developmental and adult plasticity share many common features, notable differences may be attributed to developmental cortical changes at multiple levels. These range from shifts in the molecular profiles of cortical neurons to changes in the spatiotemporal dynamics of network activity. In this review, we will discuss recent progress and remaining challenges in understanding adult visual plasticity, focusing on the primary visual cortex.

Animals↗
PubMed2005

Temporal dynamics of cerebro-cerebellar network recruitment during a cognitive task.

Previous investigations have demonstrated that two regions in the right cerebellum, one located superiorly in hemispheral lobule VI/Crus I and another located inferiorly in hemispheral lobule VIIB/VIIIA, are activated during verbal working memory performance. On the basis of functional neuroimaging patterns of activation, as well as known cortico-pontine and ponto-cerebellar projections, the superior region has been hypothesized to contribute to the articulatory control system of working memory whereas the inferior region has been linked to the phonological store. The present study used event-related fMRI and individual estimates of hemodynamic response for both the cerebellum and neocortex to test this model and characterize the task phase specific cerebro-cerebellar activations for a Sternberg verbal working memory task. Results demonstrated that the right superior cerebellum showed the strongest activation during the initial encoding phase of the task, and, consistent with predictions, a similar pattern was observed in left opercular inferior frontal and premotor regions. In contrast, the right inferior cerebellum exhibited the greatest activation during the maintenance phase of the task, and as predicted, corresponded with activation in the left inferior parietal lobule. The significance of the results with respect to cerebro-cerebellar models of verbal working memory and to theoretical accounts of cerebellar involvement in cognition is discussed.

Adolescent↗
PubMed2004

Dynamics of sensory thalamocortical synaptic networks during information processing states.

The thalamocortical network consists of the pathways that interconnect the thalamus and neocortex, including thalamic sensory afferents, corticothalamic and thalamocortical pathways. These pathways are essential to acquire, analyze, store and retrieve sensory information. However, sensory information processing mostly occurs during behavioral arousal, when activity in thalamus and neocortex consists of an electrographic sign of low amplitude fast activity, known as activation, which is caused by several neuromodulator systems that project to the thalamocortical network. Logically, in order to understand how the thalamocortical network processes sensory information it is essential to study its response properties during states of activation. This paper reviews the temporal and spatial response properties of synaptic pathways in the whisker thalamocortical network of rodents during activated states as compared to quiescent (non-activated) states. The evidence shows that these pathways are differentially regulated via the effects of neuromodulators as behavioral contingencies demand. Thus, during activated states, the temporal and spatial response properties of pathways in the thalamocortical network are transformed to allow the processing of sensory information.

Animals↗
PubMed2003

Tropomodulins: life at the slow end.

Dynamic exchange of actin monomers at filament ends is crucial for the functional architecture of many cytoskeletal-dependent processes. Recent evidence indicates that tropomodulins (Tmods), a conserved family of actin-capping proteins that bind to the pointed (slow-growing) end of actin filaments, regulate a variety of actin structures, including dynamic actin networks found in some motile cells. Actin structures that are more stable, such as sarcomeric thin filaments, require capping by Tmods to specify filament lengths and to provide filament stability. Here, we discuss the functional differences between the capping of pointed and barbed ends within the context of these actin-filament systems, and how Tmods uniquely contribute to their regulation and organization.

Actin Cytoskeleton↗
PubMed2005

From A to Z and back? Multicompartment proteins in the sarcomere.

Sarcomeres, the smallest contractile units of striated muscle, are conventionally perceived as the most regular macromolecular assemblies in biology, with precisely assigned localizations for their constituent proteins. However, recent studies have revealed complex multiple locations for several sarcomere proteins within the sarcomere and other cellular compartments such as the nucleus. Several of these proteins appear to relocalize in response to mechanical stimuli. Here, we review the emerging role of these protein networks as dynamic information switchboards that communicate between the contractile machinery and the nucleus to central pathways controlling cell survival, protein breakdown, gene expression and extracellular signaling.

Animals↗
PubMed2004

The dynamic clamp comes of age.

The dynamic clamp uses computer simulation to introduce artificial membrane or synaptic conductances into biological neurons and to create hybrid circuits of real and model neurons. In the ten years since it was first developed, the dynamic clamp has become a widely used tool for the study of neural systems at the cellular and circuit levels. This review describes recent state-of-the-art implementations of the dynamic clamp and summarizes insights gained through its use, ranging from the role of voltage-dependent conductances in shaping neuronal activity to the effects of synaptic dynamics on network behavior and the impact of in vivo-like input on neuronal information processing.

Animals↗
PubMed2000

Dynamic oscillation measurements of starch networks at temperatures above 100 degrees C.

Small deformation oscillatory studies were performed on wheat flour paste with a starch content of 75.4%. Work focused on temperatures above 100 degrees C in an effort to seek molecular understanding of such high-temperature processes as bakery operations which are characterised by evaporation of water. The moisture content of the sample decreased from about 32% at 100 degrees C to 6.5% at 130 degrees C. Viscoelastic spectra produced a sigmoidal profile with a disproportionate viscous element also seen in the glass transition of semiamorphous synthetic polymers and high sugar/polysaccharide mixtures during cooling. It is argued that the loss of water upon heating reduces the available free volume between neighbouring chain segments, thus generating a high-density thermoplastic melt suspending granule fragments. The configurational rearrangements of the disordered chains contribute mainly to an energy-dissipating process, as observed in the vitrification of cooled high-solids systems. The equation of Williams, Landel, and Ferry was modified with a 'moisture term' in order to describe the temperature function of viscoelasticity.

Carbohydrate Conformation↗
PubMed2003

Evolution of indirect reciprocity by social information: the role of trust and reputation in evolution of altruism.

The complexity of human's cooperative behavior cannot be fully explained by theories of kin selection and group selection. If reciprocal altruism is to provide an explanation for altruistic behavior, it would have to depart from direct reciprocity, which requires dyads of individuals to interact repeatedly. For indirect reciprocity to rationalize cooperation among genetically unrelated or even culturally dissimilar individuals, information about the reputation of individuals must be assessed and propagated in a population. Here, we propose a new framework for the evolution of indirect reciprocity by social information: information selectively retrieved from and propagated through dynamically evolving networks of friends and acquaintances. We show that for indirect reciprocity to be evolutionarily stable, the differential probability of trusting and helping a reputable individual over a disreputable individual, at a point in time, must exceed the cost-to-benefit ratio of the altruistic act. In other words, the benefit received by the trustworthy must out-weigh the cost of helping the untrustworthy.

Altruism↗
PubMed1985

Mathematical modelling of dynamics and control in metabolic networks. V. Static bifurcations in single biochemical control loops.

Here we expand an earlier study of feedback activation in simple linear reaction sequences by searching the parameter space of biologically realistic rate laws for multiple stable steady states. The impetus for this work is to seek the origin of decision making strategies at the metabolic level, with particular emphasis on the switching between the operating conditions needed to meet changing substrate availability and organism requirements. The control loop considered herein is a linear reaction chain in which the end product of the reaction sequence feedback activates the first reaction in the sequence to produce feedback control. It has been found that the criteria for the existence of multiple steady state solutions in such loops involve only the kinetics of the regulatory enzyme controlling the first reaction and that of end product removal. The effects of these kinetics are examined here using two representative models for the regulatory enzyme: the lumped controller, based on Hill-type kinetics, and the symmetry model. The behavior of these two models is qualitatively similar, and both show the characteristics needed for switching between low and high substrate utilization. The removal rate is assumed to be of the Michaelis-Menten type. Judicious scaling of the governing equations permits separation of genetically determined kinetic parameters from concentration dependent ones. This allows us to conclude that, for a fixed set of kinetic parameters, the steady state flux through the loop can be switched between stable steady states by merely varying metabolite or enzyme concentrations. In particular, when the initial substrate exceeds a certain critical level, the loop can be "switched on" (by a discontinuous increase in the flux through the chain), and similarly, when it falls below a critical level, the pathway is shut down. Similar effects can be realized by varying the ratios of enzyme concentrations. It is proposed that by identifying these critical points one can gain significant insight into the objectives of decision making at the metabolic level.

Enzymes↗
PubMed2005

Dynamics of thalamo-cortical network oscillations and human perception.

There is increasing evidence that human cognitive functions can be addressed from a robust neuroscience perspective. In particular, the distributed coherent electrical properties of central neuronal ensembles are considered to be a promising avenue of inquiry concerning global brain functions. The intrinsic oscillatory properties of neurons (Llinás, R. (1988) The intrinsic electrophysiological properties of mammalian neurons: Insights into central nervous system function. Science, 242: 1654-1664), supported by a large variety of voltage-gated ionic conductances are recognized to be the central elements in the generation of the temporal binding required for cognition. Research in neuroscience further indicates that oscillatory activity in the gamma band (25-50 Hz) can be correlated with both sensory acquisition and pre-motor planning, which are non-continuous functions in the time domain. From this perspective, gamma-band activity is viewed as serving a broad temporal binding function, where single-cell oscillators and the conduction time of the intervening pathways support large multicellular thalamo-cortical resonance that is closely linked with cognition and subjective experience. Our working hypothesis is that although dedicated units achieve sensory processing, the cognitive binding process is a common mechanism across modalities. Moreover, it is proposed that such time-dependent binding when altered, will result in modifications of the sensory motor integration that will affect and impair cognition and conscious perception.

Cerebral Cortex↗
PubMed2003

Cortical operational synchrony during audio-visual speech integration.

Information from different sensory modalities is processed in different cortical regions. However, our daily perception is based on the overall impression resulting from the integration of information from multiple sensory modalities. At present it is not known how the human brain integrates information from different modalities into a unified percept. Using a robust phenomenon known as the McGurk effect it was shown in the present study that audio-visual synthesis takes place within a distributed and dynamic cortical networks with emergent properties. Various cortical sites within these networks interact with each other by means of so-called operational synchrony (Kaplan, Fingelkurts, Fingelkurts, & Darkhovsky, 1997). The temporal synchronization of cortical operations processing unimodal stimuli at different cortical sites reveals the importance of the temporal features of auditory and visual stimuli for audio-visual speech integration.

Cerebral Cortex↗
PubMed1999

Promoter analysis of co-regulated genes in the yeast genome.

The use of high density DNA arrays to monitor gene expression at a genome-wide scale constitutes a fundamental advance in biology. In particular, the expression pattern of all genes in Saccharomyces cerevisiae can be interrogated using microarray analysis where cDNAs are hybridized to an array of more than 6000 genes in the yeast genome. In an effort to build a comprehensive Yeast Promoter Database and to develop new computational methods for mapping upstream regulatory elements, we started recently in an on going collaboration with experimental biologists on analysis of large-scale expression data. It is well known that complex gene expression patterns result from dynamic interacting networks of genes in the genetic regulatory circuitry. Hierarchical and modular organization of regulatory DNA sequence elements are important information for our understanding of combinatorial control of gene expression. As a bioinformatics attempt in this new direction, we have done some computational exploration of various initial experimental data. We will use cell-cycle regulated gene expression as a specific example to demonstrate how one may extract promoter information computationally from such genome-wide screening. Full report of the experiments and of the complete analysis will be published elsewhere when all the experiments are to be finished later in this year (Spellman, P.T., et al. 1998. Mol. Biol. Cell 9, 3273-3297).

Base Sequence↗
PubMed2003

Conformon-driven biopolymer shape changes in cell modeling.

Conceptual models of the atom preceded the mathematical model of the hydrogen atom in physics in the second decade of the 20th century. The computer modeling of the living cell in the 21st century may follow a similar course of development. A conceptual model of the cell called the Bhopalator was formulated in the mid-1980s, along with its twin theories known as the conformon theory of molecular machines and the cell language theory of biopolymer interactions [Ann. N.Y. Acad. Sci. 227 (1974) 211; BioSystems 44 (1997) 17; Ann. N.Y. Acad. Sci. 870 (1999a) 411; BioSystems 54 (2000) 107; Semiotica 138 (1-4) (2002a) 15; Fundamenta Informaticae 49 (2002b) 147]. The conformon theory accounts for the reversible actions of individual biopolymers coupled to irreversible chemical reactions, while the cell language theory provides a theoretical framework for understanding the complex networks of dynamic interactions among biopolymers in the cell. These two theories are reviewed and further elaborated for the benefit of both computational biologists and computer scientists who are interested in modeling the living cell and its functions. One of the critical components of the mechanisms of cell communication and cell computing has been postulated to be space- and time-organized teleonomic (i.e. goal-directed) shape changes of biopolymers that are driven by exergonic (free energy-releasing) chemical reactions. The generalized Franck-Condon principle is suggested to be essential in resolving the apparent paradox arising when one attempts to couple endergonic (free energy-requiring) biopolymer shape changes to the exergonic chemical reactions that are catalyzed by biopolymer shape changes themselves. Conformons, defined as sequence-specific mechanical strains of biopolymers first invoked three decades ago to account for energy coupling in mitochondria, have been identified as shape changers, the agents that cause shape changes in biopolymers. Given a set of space- and time-organized teleonomic shape changes of biopolymers driven by conformons, all of the functions of the cell can be accounted for in molecular terms-at least in principle. To convert a conceptual model of the cell into a computer model, it is necessary to represent the conceptual model in an algebraic language. To this end, we have begun to apply the process algebra of Milner [Communicating and Mobile Systems: The pi-calculus, Cambridge University Press, Cambridge, 1999] to develop what is here called the "shape algebra," capable of describing complex and mobile patterns of interactions among biomolecules leading to cell functions.

Algorithms↗
PubMed1997

Dynamical behavior of a neural network with periodical external inputs.

Localized neural populations in different brain areas can undergo periodical external influence. To study this situation we consider the well known model by Wilson and Cowan (1972). It describes the evolution of two interconnected neuronal subpopulations of excitatory and inhibitory neurons correspondingly. Besides, it could be considered as a model of an abstract self-regulatory system. We describe and reveal underlying mechanisms of two regimes of forced oscillations in the model. In the first one the system acts as a phase comparator, demonstrating high sensitivity to a value of a phase shift between inputs to excitatory and inhibitory neurons. In the second regime it acts similar to a low pass filter: amplitudes of forced oscillations of the both components are not small and almost constant for low frequencies of the external input to the excitatory subpopulation. But they decrease significantly when the frequency becomes rather high. For simplified versions of the model analytical estimates for corresponding ranges of parameters are derived. It is shown that they are in good agreement with the results of computer simulations.

Animals↗
PubMed1998

Incorporation of Long-Range Feedback in Neural Networks Under Stability Conditions.

Feedback endows neural networks with several interesting properties. It is thus not surprising that several well-known models (e.g. ART, Hopfield, neocognitron) include feedback connections. However, neural networks with feedback may possess unstable dynamics and should be carefully designed. In this paper we show how to incorporate long-range feedback in a broad class of dynamically stable neural networks using the basic idea of symmetric connections. The case of networks with binary inputs and binary outputs is treated first. Then, as the main contribution of this paper, the analysis is extended to networks with analog (continuous-time continuous-output) neurons.

Journal Article↗