Working Memory Networks for Learning Temporal Order, with Application to 3-D Visual Object Recognition

Working memory neural networks are characterized which encode the invariant temporal order of sequential events. Inputs to the networks, called Sustained Temporal Order REcurrent (STORE) models, may be presented at widely differing speeds, durations, and interstimulus intervals. The STORE temporal order code is designed to enable all emergent groupings of sequential events to be stably learned and remembered in real time, even as new events perturb the system. Such a competence is needed in neural architectures which self-organize learned codes for variable-rate speech perception, sensory-motor planning, or 3-D visual object recognition. Using such a working memory, a self-organizing architecture for invariant 3-D visual object recognition is described. The new model is based on the model of Seibert and Waxman (1990a), which builds a 3-D representation of an object from a temporally ordered sequence of its 2-D aspect graphs. The new model, called an ARTSTORE model, consists of the following cascade of processing modules: Invariant Preprocessor --> ART 2 --> STORE Model --> ART 2 --> Outstar Network.

Interaction Energy Based Protein Structure Networks

The three dimensional structure of a protein is formed and maintained by the noncovalent interactions among the amino acid residues of the polypeptide chain These interactions can be represented collectively in the form of a network So far such networks have been investigated by considering the connections based on distances between the amino acid residues Here we present a method of constructing the structure network based on interaction energies among the amino acid residues in the protein We have investigated the properties of such protein energy based networks (PENs) and have shown correlations to protein structural features such as the clusters of residues involved in stability formation of secondary and super secondary structural units Further we demonstrate that the analysis of PENs in terms of parameters such as hubs and shortest paths can provide a variety of biologically important information such as the residues crucial for stabilizing the folded units and the paths of communication between distal residues in the protein Finally the energy regimes for different levels of stabilization in the protein structure have clearly emerged from the PEN analysis

Efficient two-step digit-set-restricted modified signed-digit algorithm based on optoelectronic shared content-addressable memory

A two-step digit-set-restricted modified signed-digit (MSD) adder based on symbolic substitution is presented. In the proposed addition algorithm, carry propagation is avoided by using reference digits to restrict the intermediate MSD carry and sum digits into {(1) over bar ,0} and {0, 1}, respectively. The algorithm requires only 12 minterms to generate the final results, and no complementarity operations for nonzero outputs are involved, which simplifies the system complexity significantly. An optoelectronic shared content-addressable memory based on an incoherent correlator is used for experimental demonstration. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Efficient two-step digit-set-restricted modified signed-digit algorithm based on optoelectronic shared content-addressable memory

A two-step digit-set-restricted modified signed-digit (MSD) adder based on symbolic substitution is presented. In the proposed addition algorithm, carry propagation is avoided by using reference digits to restrict the intermediate MSD carry and sum digits into {(1) over bar ,0} and {0, 1}, respectively. The algorithm requires only 12 minterms to generate the final results, and no complementarity operations for nonzero outputs are involved, which simplifies the system complexity significantly. An optoelectronic shared content-addressable memory based on an incoherent correlator is used for experimental demonstration. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Novel nonvolatile memory with multibit storage based on a ZnO nanowire transistor.

We demonstrate a room temperature processed ferroelectric (FE) nonvolatile memory based on a ZnO nanowire (NW) FET where the NW channel is coated with FE nanoparticles. A single device exhibits excellent memory characteristics with the large modulation in channel conductance between ON and OFF states exceeding 10(4), a long retention time of over 4 × 10(4) s, and multibit memory storage ability. Our findings provide a viable way to create new functional high-density nonvolatile memory devices compatible with simple processing techniques at low temperature for flexible devices made on plastic substrates.

Modeling energy consumption in error-prone IEEE 802.11-based wireless ad-hoc networks

In the IEEE 802.11 MAC layer protocol, there are different trade-off points between the number of nodes competing for the medium and the network capacity provided to them. There is also a trade-off between the wireless channel condition during the transmission period and the energy consumption of the nodes. Current approaches at modeling energy consumption in 802.11 based networks do not consider the influence of the channel condition on all types of frames (control and data) in the WLAN. Nor do they consider the effect on the different MAC and PHY schemes that can occur in 802.11 networks. In this paper, we investigate energy consumption corresponding to the number of competing nodes in IEEE 802.11's MAC and PHY layers in error-prone wireless channel conditions, and present a new energy consumption model. Analysis of the power consumed by each type of MAC and PHY over different bit error rates shows that the parameters in these layers play a critical role in determining the overall energy consumption of the ad-hoc network. The goal of this research is not only to compare the energy consumption using exact formulae in saturated IEEE 802.11-based DCF networks under varying numbers of competing nodes, but also, as the results show, to demonstrate that channel errors have a significant impact on the energy consumption.

Constructing networks of continuous-time velocity-based models

A conventional local model (LM) network consists of a set of affine local models blended together using appropriate weighting functions. Such networks have poor interpretability since the dynamics of the blended network are only weakly related to the underlying local models. In contrast, velocity-based LM networks employ strictly linear local models to provide a transparent framework for nonlinear modelling in which the global dynamics are a simple linear combination of the local model dynamics. A novel approach for constructing continuous-time velocity-based networks from plant data is presented. Key issues including continuous-time parameter estimation, correct realisation of the velocity-based local models and avoidance of the input derivative are all addressed. Application results are reported for the highly nonlinear simulated continuous stirred tank reactor process.

Global exponential periodicity of a class of bidirectional associative memory networks with finite distributed delays

In this paper, we study the periodic oscillatory behavior of a class of bidirectional associative memory (BAM) networks with finite distributed delays. A set of criteria are proposed for determining global exponential periodicity of the proposed BAM networks, which assume neither differentiability nor monotonicity of the activation function of each neuron. In addition, our criteria are easily checkable. (c) 2005 Elsevier Inc. All rights reserved.

When the systems fail to communicate. Cerebral resting state networks in schizophrenia spectrum disorders.

There have been numerous attempts to reveal the neurobiological basis of schizophrenia spectrum disorders. Results however, remain as heterogeneous as the schizophrenia spectrum disorders itself. Therefore, one aim of this thesis was to divide patients affected by this disorder into subgroups in order to homogenize the results of future studies. In a first study it is suggested that psychopathological rating scales should focus on symptoms-clusters that may have a common neurophysiological background. The here presented Bern Psychopathology Scale (BPS) proposes that alterations in three wellknown brain systems (motor, language, and affective) are largely leading to the communication failures observable on a behavioral level, but also - as repeatedly hypothesized - to dysconnectivity within and between brain systems in schizophrenia spectrum disorders. The external validity of the motor domain in the BPS was tested against the objective measure of 24 hours wrist actigraphy, in a second study. The subjective, the quantitative, as well as the global rating of the degree of motor disorders in this patient group showed significant correlations to the acquired motor activity. This result confirmed in a first step the practicability of the motor domain of the BPS, but needs further validation regarding pathological brain alterations. Finally, in a third study (independent from the two other studies), two cerebral Resting State Networks frequently altered in schizophrenia were investigated for the first time using simultaneous EEG/fMRI: The well-known default mode network and the left working memory network. Besides the changes in these fMRI-based networks, there are well-documented findings that patients exhibit alterations in EEG spectra compared to healthy controls. However, only through the multimodal approach it was possible to discover that patients with schizophrenia spectrum disorders have a slower driving frequency of the Resting State Networks compared to the matched healthy controls. Such a dysfunctional coupling between neuronal frequency and functional brain organization could explain in a uni- or multifactorial way (dysfunctional cross-frequency coupling, maturational effects, vigilance fluctuations, task-related suppression), how the typical psychotic symptoms might occur. To conclude, the major contributions presented in this thesis were on one hand the development of a psychopathology rating scale that is based on the assumption of dysfunctional brain networks, as well as the new evidence of a dysfunctional triggering frequency of Resting State Networks from the simultaneous EEG/fMRI study in patients affected by a schizophrenia spectrum disorder.

Efficient clustering approach for intrusion detection in adhoc networks

Mobile ad-hoc networks (MANETs) are temporary wireless networks useful in emergency rescue services, battlefields operations, mobile conferencing and a variety of other useful applications. Due to dynamic nature and lack of centralized monitoring points, these networks are highly vulnerable to attacks. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. We take benefit of the clustering concept in MANETs for the effective communication between nodes, where each cluster involves a number of member nodes and is managed by a cluster-head. It can be taken as an advantage in these battery and memory constrained networks for the purpose of intrusion detection, by separating tasks for the head and member nodes, at the same time providing opportunity for launching collaborative detection approach. The clustering schemes are generally used for the routing purposes to enhance the route efficiency. However, the effect of change of a cluster tends to change the route; thus degrades the performance. This paper presents a low overhead clustering algorithm for the benefit of detecting intrusion rather than efficient routing. It also discusses the intrusion detection techniques with the help of this simplified clustering scheme.

Structural basis for the function of anti-idiotypic antibody in immune memory

We had earlier proposed a hypothesis to explain the mechanism of perpetuation of immunological memory based on the operation of idiotypic network in the complete absence of antigen. Experimental evidences were provided for memory maintenance through anti-idiotypic antibody (Ab2) carrying the internal image of the antigen. In the present work, we describe a structural basis for such memory perpetuation by molecular modeling and structural analysis studies. A three-dimensional model of Ab2 was generated and the structure of the antigenic site on the hemagglutinin protein H of Rinderpest virus was modeled using the structural template of hemagglutinin protein of Measles virus. Our results show that a large portion of heavy chain containing the CDR regions of Ab2 resembles the domain of the hemagglutinin housing the epitope regions. The similarity demonstrates that an internal image of the H antigen is formed in Ab2, which provides a structural basis for functional mimicry demonstrated earlier. This work brings out the importance of the structural similarity between a domain of hemagglutinin protein to that of its corresponding Ab2. It provides evidence that Ab2 is indeed capable of functioning as surrogate antigen and provides support to earlier proposed relay hypothesis which has provided a mechanism for the maintenance of immunological memory.

Structural basis for the function of anti-idiotypic antibody in immune memory

We had earlier proposed a hypothesis to explain the mechanism of perpetuation of immunological memory based on the operation of idiotypic network in the complete absence of antigen. Experimental evidences were provided for memory maintenance through anti-idiotypic antibody (Ab(2)) carrying the internal image of the antigen. In the present work, we describe a structural basis for such memory perpetuation by molecular modeling and structural analysis studies. A three-dimensional model of Ab(2) was generated and the structure of the antigenic site on the hemagglutinin protein H of Rinderpest virus was modeled using the structural template of hemagglutinin protein of Measles virus. Our results show that a large portion of heavy chain containing the CDR regions of Ab(2) resembles the domain of the hemagglutinin housing the epitope regions. The similarity demonstrates that an internal image of the H antigen is formed in Ab(2), which provides a structural basis for functional mimicry demonstrated earlier. This work brings out the importance of the structural similarity between a domain of hemagglutinin protein to that of its corresponding Ab(2). It provides evidence that Ab(2) is indeed capable of functioning as surrogate antigen and provides support to earlier proposed relay hypothesis which has provided a mechanism for the maintenance of immunological memory.

Structure determination and biochemical studies on Bacillus stearothermophilus E53Q serine hydroxymethyltransferase and its complexes provide insights on function and enzyme memory

Serine hydroxymethyltransferase (SHMT) belongs to the alpha-family of pyridoxal 5'-phosphate-dependent enzymes and catalyzes the reversible conversion of L-Ser and etrahydrofolate to Gly and 5,10-methylene tetrahydrofolate. 5,10-Methylene tetrahydrofolate serves as a source of one-carbon fragment in many biological processes. SHMT also catalyzes the tetrahydrofolate-independent conversion of L-allo-Thr to Gly and acetaldehyde. The crystal structure of Bacillus stearothermophilus SHMT (bsSHMT) suggested that E53 interacts with the substrate, L-Ser and etrahydrofolate. To elucidate the role of E53, it was mutated to Q and structural and biochemical studies were carried out with the mutant enzyme. The internal aldimine structure of E53QbsSHMT was similar to that of the except for significant changes at Q53, Y60 and Y61. The wild-type enzyme, carboxyl of Gly and side chain of L-Ser were in two conformations in the respective external aldimine structures. The mutant enzyme was completely inactive for tetrahydrofolate-depen dent cleavage of L-Ser, whereas there was a 1.5-fold increase in the rate of tetrahydrofolate-independent reaction with L-allo-Thr. The results obtained from these studies suggest that E53 plays an essential role in tetrahydrofolate/5-formyl tetrahydrofolate binding and in the proper positioning of C beta of L-Ser for direct attack by N5 of tetrahydrofolate. Most interestingly, the structure of the complex obtained by cocrystallization of E53QbsSHMT with Gly and 5-formyl tetrahydrofolate revealed the gem-diamine form of pyridoxal 5'-phosphate bound to Gly and active site Lys. However, density for 5-formyl tetrahydrofolate was not observed. Gly carboxylate was in a single conformation, whereas pyridoxal 5'-phosphate had two distinct conformations. The differences between the structures of this complex and Gly external aldimine suggest that the changes induced by initial binding of 5-formyl tetrahydrofolate are retained even though 5-formyl tetrahydrofolate is absent in the final structure. Spectral studies carried out with this mutant enzyme also suggest that 5-formyl tetrahydrofolate binds to the E53QbsSHMT-Gly complex forming a quinonoid intermediate and falls off within 4 h of dialysis, leaving behind the mutant enzyme in the gemdiamine form. This is the first report to provide direct evidence for enzyme memory based on the crystal structure of enzyme complexes.

Metabolome based reaction graphs of M.tuberculosis and M.leprae: A comparative network analysis

Background. Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. Methodology/Principal Findings. Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. Conclusions. We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a broad overview of the similarities and differences between organisms, taking comparative genomics studies to a higher dimension.

Single-Generation Network Coding for Networks with Delay

A single-source network is said to be memory-free if all of the internal nodes (those except the source and the sinks) do not employ memory but merely send linear combinations of the incoming symbols (received at their incoming edges) on their outgoing edges. Memory-free networks with delay using network coding are forced to do inter-generation network coding, as a result of which the problem of some or all sinks requiring a large amount of memory for decoding is faced. In this work, we address this problem by utilizing memory elements at the internal nodes of the network also, which results in the reduction of the number of memory elements used at the sinks. We give an algorithm which employs memory at all the nodes of the network to achieve single- generation network coding. For fixed latency, our algorithm reduces the total number of memory elements used in the network to achieve single- generation network coding. We also discuss the advantages of employing single-generation network coding together with convolutional network-error correction codes (CNECCs) for networks with unit- delay and illustrate the performance gain of CNECCs by using memory at the intermediate nodes using simulations on an example network under a probabilistic network error model.