Search

We consider the problem of recovering random graph signals from nonlinear measurements. For this setting, closed-form Bayesian estimators are usually intractable and even numerical evaluation may be difficult to compute for large networks. In this paper, we propose a graph signal processing (GSP) framework for random graph signal recovery that utilizes information on the structure behind the data. First, we develop the GSP-linear minimum mean-squared-error (GSP-LMMSE) estimator, which minimizes the mean-squared-error (MSE) among estimators that are represented as an output of a graph filter. The GSP-LMMSE estimator is based on diagonal covariance matrices in the graph frequency domain, and thus, has reduced complexity compared with the LMMSE estimator. This property is especially important when using the sample-mean estimators that are based on a training dataset. We then state conditions under which the low-complexity GSP-LMMSE estimator coincides with the optimal LMMSE estimator. Next, we develop an approximate parametrization of the GSP-LMMSE estimator by graph filters. We present three implementations of the parametric GSP-LMMSE estimator for typical graph filters. These parametric graph filters are more robust to outliers and to network topology changes. In our simulations, we evaluate the performance of the proposed GSP-LMMSE estimators for the problem of state estimation in power systems, which can be interpreted as a graph signal recovery task. We show that the proposed sample-GSP estimators outperform the sample-LMMSE estimator for a limited training dataset and that the parametric GSP-LMMSE estimators are more robust to topology changes in the form of adding/removing vertices/edges. [ABSTRACT FROM AUTHOR]

The problem of bus imbalance identification in a three-phase power network using a phasor measurement unit (PMU) is considered. We propose new algorithms to identify and localize imbalances occurring at any location in the power grid, based only on single-phase PMU data. First, we develop a technique using the minimum description length (MDL) criterion that is carried out at the control center. The centralized MDL methodology is time consuming and has computational complexity that grows exponentially with the network size. Therefore, we next develop a projected orthogonal matching pursuit (POMP) algorithm, which is a low-complexity method for bus imbalance identification in large-scale power networks implemented at the control center. POMP is a computationally efficient compressive sensing technique that exploits the sparse structure of the voltage measurements. The proposed methods are validated through three case studies: a two-port $\pi$-model, an IEEE-14 bus system, and an IEEE 118-bus system. Simulations show that our networked algorithms, MDL and POMP, obtain improved performance over local bus-level identification techniques. The performance of POMP is close to that of centralized MDL, with the advantage of being applicable to large-scale networks. [ABSTRACT FROM AUTHOR]

The problem of voltage imbalance detection in a three-phase power system using phasor measurement unit (PMU) data is considered within a hypothesis testing framework. A general model for the PMU output with a downsampled negative sequence is presented. The new formulation takes into account computation complexity and tolerance of imbalance. A new monitoring tool, referred to as a generalized locally most powerful (GLMP) test, is proposed for detection in the presence of nuisance parameters. A closed-form expression of the GLMP test is developed for the detection of an imbalance problem, based on a single PMU's measurements. Numerical simulations show improved performance over benchmark techniques. [ABSTRACT FROM AUTHOR]

The problem of imbalance detection in a three-phase power system using a phasor measurement unit (PMU) is considered. A general model for the zero, positive, and negative sequences from a PMU measurement at off-nominal frequencies is presented and a hypothesis testing framework is formulated. The new formulation takes into account the fact that minor degree of imbalance in the system is acceptable and does not indicate subsequent interruptions, failures, or degradation of physical components. A generalized likelihood ratio test (GLRT) is developed and shown to be a function of the negative-sequence phasor estimator and the acceptable level of imbalances for nominal system operations. As a by-product to the proposed detection method, a constrained estimation of the positive and negative phasors and the frequency deviation is obtained for both balanced and unbalanced situations. The theoretical and numerical performance analyses show improved performance over benchmark techniques and robustness to the presence of additional harmonics. [ABSTRACT FROM PUBLISHER]

It is here proposed that the evanescent network derived from malleable or supple synapses is the substrate for long-lasting memory. The subjective sense of memory permanence is not derived, as suggested by Bain and others, from the stabilization of synaptic structure which gives rise to consolidated distributed networks. This generally held wisdom that synapses are activated and ultimately stabilized to reflect the long-lasting substrate of memory is reinforced by increased interest in the importance of sparse coding in memory consolidation. One line of evidence for sparse coding derives from studies on the lateral nucleus neurons of the amygdala (for review, see Josselyn, 2010). These findings lead to the conclusion that a small number of neurons are both necessary and sufficient to retrieve the fear engram. Recently, it has been shown that sparse coding in the dentate gyrus of the hippocampus is sufficient for retrieving the fear conditioning engram (Liu et al., 2012). One implication of these findings is that memory is stored in selected cells and that this restricted storage is more or less permanent, as the authors note: '... Defined cell populations can form the cellular basis for fear memory engrams (Liu et al., 2012, p. 89).' But the problem with this model is that because new learning is incorporated into existing networks, stabilization would work against this integration. For this reason and because of obligatory processes of metabolic protein turnover and ongoing synaptic malleability, the 'supple synapse' model is proposed (Routtenberg, A., Rekart, 2005; Routtenberg, 2008a,b). Specifically, long-lasting memory is derived from the instructive, use-dependent sampling of neural networks selected from a very large universe of networks that are evanescent because they are linked together by supple synapses. Importantly, if such suppleness did not exist, the stabilization of synapses would then prevent the physiological malleability of brain circuitry that is essential both for proper integrated information storage and for flexible information retrieval. A corollary of this proposal is that it suggests an alternative view of consolidation: the same agent which is disruptive immediately after learning is no longer effective later because the network, over time, becomes widely distributed and evanescent. Thus, time-dependence is replaced with space-dependence. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

In this paper, a new class of lower bounds on the outage error probability in Bayesian parameter estimation is proposed. The outage error probability is an important criterion in parameter estimation that provides meaningful information even in the presence of large errors and is useful for prediction of the system operation region. Computation of the minimum outage error probability is usually not tractable and thus, lower bounds on this probability can be very useful for performance analysis. The proposed class of lower bounds on the outage error probability is derived using Hölder's inequality. Several bounds in the proposed class are presented. It is shown that the Ziv–Zakai lower bound on the outage error probability can be obtained from a subclass in the proposed class of bounds. The proposed class of bounds is utilized to derive a new class of Bayesian bounds on the mean-square error. It is shown that, for unimodal posterior probability density functions, the tightest lower bound on the probability of outage error in the proposed class attains the minimum probability of outage error. The proposed bounds are exemplified in linear Gaussian model parameter estimation and time-delay estimation. [ABSTRACT FROM AUTHOR]

In this paper, a new method for Bayesian periodic parameter estimation is derived using periodic cost functions. The method, named parameter estimation via root finding (PERF), is based on Fourier series representation of the Bayes periodic-risk functions. The PERF method is implemented for minimum cyclic error, minimum absolute periodic error, and minimum mean-square-periodic-error (MSPE) estimators and the corresponding estimators are derived. The periodic estimators are applied to direction-of-arrival and phase estimation problems and compared with the minimum mean-square-error and maximum a posteriori probability estimators, and the periodic Ziv-Zakai lower bound in terms of MSPE. [ABSTRACT FROM PUBLISHER]

In this paper, a new method for system identification and blind source separation in a multiple-input multiple-output (MIMO) system is proposed. The MIMO channel is modeled by a multi-dimensional autoregressive (AR) system. The transmitted signals are assumed to take values from a finite alphabet, modeled by the Gaussian mixture model (GMM) with infinitesimal variances. The expectation-maximization (EM) algorithm for estimation of the MIMO-AR model parameters is derived. The performance of the proposed algorithm in terms of probability of error in signal detection and root mean squared error (RMSE) of the system parameters and system transfer function estimates is evaluated via simulations. It is shown that the obtained probability of error is very close to the probability of error of the optimal algorithm which assumes known channel state information. [ABSTRACT FROM AUTHOR]

The mossy fiber (MF) system targets the apical dendrites of CA3 pyramidal cells in the stratum lucidum (SL). In mice overexpressing the growth-associated protein GAP-43 there is an apparent ectopic growth of these MFs into the stratum oriens (SO) targeting the basal dendrites of these same pyramidal cells (Aigner et al. (1995) Cell 83:269-278). This is the first evidence to our knowledge that links increased GAP-43 expression with growth of central axons. Here we studied the Aigner et al. transgenic mice but were unable to confirm such growth into SO. However, using quantitative methods we did observe enhanced growth within the regions normally targeted by MFs, for example, the SL in the CA3a region. These contrasting results led us to study MFs with double-immunostaining using an immunohistochemical marker for MFs, the zinc transporter, ZnT3, to visualize the colocalization of transgenic GAP-43 within MFs. Unexpectedly, using both fluorescence and confocal microscopy, we were unable to detect colocalization of GAP-43-positive axons with ZnT3-positive MF axons within the MF pathways, either in the region of the MF axons or in the SL, where MF terminals are abundant. In contrast, the plasma membrane-associated presynaptic marker SNAP-25 did colocalize with transgenic GAP-43-positive terminals in the SL. Synaptophysin, the vesicle-associated presynaptic terminal marker, colocalized with ZnT3 but did not appear to colocalize with GAP-43. The present findings raise important questions about the properties of granule cells and the MF mechanisms that differentially regulate axonal remodeling in the adult hippocampus: (1) Because there appears to be at least two populations of granule cells defined by their differential protein expression, this points to the existence of an intrinsic heterogeneity of granule cell expression beyond that contributed by adult neurogenesis; (2) Giventhe present evidence that growth is induced in mice overexpressing GAP-43 in adjacent non-GAP-43 containing MFs, the potential exists for a heretofore unexplored interaxonal communication mechanism. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

The problem of blind source separation (BSS) and system identification for multiple-input multiple-output (MIMO) auto-regressive (AR) mixtures is addressed in this paper. Two new time-domain algorithms for system identification and BSS are proposed based on the Gaussian mixture model (GMM) for sources distribution. Both algorithms are based on the generalized expectation-maximization (GEM) method for joint estimation of the MIMO-AR model parameters and the GMM parameters of the sources. The first algorithm is derived under the assumption of unstructured input signal statistics, while the second algorithm incorporates the prior knowledge about the structure of the input signal statistics due to the statistically independent source assumption. These methods are tested via simulations using synthetic and audio signals. The system identification performances are tested by comparison between the state transition matrix estimation using the proposed algorithms and the well-known multidimensional Yule-Walker solution followed by an instantaneous BSS method. The results show that the proposed algorithms outperform the Yule-Walker based approach. The BSS performances were corn- pared to other convolutive BSS methods. The results show that the proposed algorithms achieve higher signal-to-interference ratio (SIR) compared to the other tested methods. [ABSTRACT FROM AUTHOR]

Protein kinase C (PKC) is known to regulate phosphorylation of substrates such as MARCKS, GAP-43, and the NMDA receptor, all of which have been linked to synaptic plasticity underlying information storage processes. Here we report on three transgenic mice isoforms differentiated both by mutation of the PKC site on GAP-43 as well as by their performance in three learning situations: (1) a radial arm maze task, which evaluates spatial memory and its retention, (2) fear conditioning which assesses contextual memory, and (3) the water maze which also evaluates spatial memory and its retention. The present results show, for the first time to our knowledge, that the phosphorylation state of a single site on an identified brain growth- and plasticity-associated protein differentially regulates performance of three different memory-associated tasks. © 2008 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Abstract: Current models of memory typically require a protein synthetic step leading to a more or less permanent structural change in synapses of the network that represent the stored information. This instructive role of protein synthesis has recently been called into question [Routtenberg, A., Rekart, J.L. 2005. Post-translational modification of synaptic proteins as the substrate for long-lasting memory. Trends Neurosci. 28, 12–19]. In its place a new theory is proposed in which post-translational modifications (PTMs) of proteins already synthesized and present within the synapse calibrate synaptic strength. PTM is thus the only mechanism required to sustain long-lasting memories. Activity-induced, PTM-dependent structural modifications within brain synapses then define network formation which is thus a product of the concatenation of cascaded PTMs. This leads to a formulation different from current protein synthesis models in which neural networks initially formed from these individual synaptic PTM-dependent changes is maintained by regulated positive feedback maintains. One such positive feedback mechanism is ‘cryptic rehearsal’ typically referred to as ‘noise’ or ‘spontaneous’ activity. This activity is in fact not random or spontaneous but determined in a stochastic sense by the past history of activation of the nerve cell. To prevent promiscuous network formation, the regulated positive feedback maintains the altered state given specific decay kinetics for the PTM. The up or down state of individual synapses actually exists in an infinite number of intermediate states, never fully ‘up'', nor fully ‘down.'' The networks formed from these uncertain synapses are therefore metastable. A particular memory is also multiply represented by a ‘degenerate code’ so that should loss of a subset of representations occur, erasure can be protected against. This mechanism also solves the flexibility–stability problem by positing that the brain eschews synaptic stability having its own uncertainty principle that allows retrieval from a probabilistic network, so that a retrieved memory can be represented by a selection of components from an essentially infinite number of networks. The network so formed, that is the retrieval, thus emerges from a hierarchy of connectionistic probabilities. The relation of this new theory of memory network formation to current and potential computational implementations will benefit by its unusual point of initiation: deep concerns about the molecular substrates of information storage. [Copyright &y& Elsevier]

Abstract: The prevailing textbook view that de novo protein synthesis is required for memory (e.g., []) is seriously flawed and an alternative hypothesis has been proposed in which post-translational modification (PTM) of proteins already synthesized and already present within the synapse is ‘the’ substrate for long-lasting memory. Protein synthesis serves a replenishment role. The first part of this review discusses how long-lasting memory can be achieved with ‘only’ PTM of existing synaptic proteins. The second part critically reviews a recent report published in Neuron 2007 that exemplifies the current view of protein synthesis and memory while also illustrating how these results can be understood within this new PTM framework. A necessary yet unexpected conclusion to emerge from consideration of the consequences of a PTM mechanism as the necessary, sufficient and exclusive substrate for long-lasting memory, is that the central Hebbian dogma that cells that ‘fire together, wire together’ is an unlikely mechanism for long-lasting memory. Thus, a unique feature of the PTM model is that longevity of information storage is achieved not by stability of the synaptic mechanism, but by impermanent pseudoredundant circuits. This is so because PTM is a reversible process and thus any permanent connection, any ‘lasting effect’ cannot be in the form of stable synapse formation. We have therefore proposed a solution in which network level processes regulate cellular mechanisms, even as such mechanisms regulate the network. Thus, synapses are ‘meta-stabilized’ by regulated feedback mediated by the circuit in which the synapse is embedded. For example, spontaneous activity is proposed to be a substrate feedback mechanism we term ‘cryptic rehearsal’ to sustain for some period of time after learning an approximation to the state initially created by input. Additionally, because the duplication of these traces is ongoing, this provides a degenerate code for the engram. Stability is thus achieved, not by stabilizing the synapse, but by implementing a pseudo-redundant yet malleable circuitry so that memory can be protected in the face of small catastrophes in network representation. [Copyright &y& Elsevier]

The current view of the molecular basis for information storage is that post-translational modification (PTM) of brain proteins is important for the early stages of memory storage and that protein synthesis is necessary for long-lasting memory. This view has been challenged by the proposal that PTM of synaptic proteins is the critical instructive mechanism underlying both recent as well as long-lasting memories (Routtenberg and Rekart,). As an initial test, a broad spectrum serine/threonine kinase inhibitor (H-7) was delivered bilaterally to rat anterior cingulate cortex 1 h before a 3 week retention test of contextual fear conditioning. This significantly blocked 21-Day retention. In the second experiment evaluating extinction of a 21-Day remote memory, H-7 injected into mouse medial prefrontal cortex blocked fear extinction. As the H-7-induced impairment in 21-Day retention was indexed by a decrease in freezing, while the extinction blockade by no decrease in freezing, the results could not be ascribed to a direct effect of the drug on behavioral performance. This represents the first demonstration, to our knowledge, that PTM inhibition, here serine/threonine kinase activity, interferes with long-lasting memory, providing initial support for the PTM model. © 2006 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Prevailing models of memory identify mRNA translation as necessary for long-lasting information storage. However, there are enough instances of memory storage in the virtual absence of protein synthesis to prompt consideration of alternative models. A comprehensive review of the protein synthesis literature leads us to conclude that the translational mechanism is exclusively a permissive, replenishment step. Therefore, we propose that post-translational modification (PTM) of proteins already at the synapse is the crucial instructive mechanism underlying long-lasting memory. A novel feature of this model is that non-random spontaneous (or endogenous) brain activity operates as a regulated positive-feedback rehearsal mechanism, updating network configurations by fine-tuning the PTM state of previously modified proteins. Synapses participating in memory storage are therefore supple, a feature required for networks to alter complexity and update continuously. In analogy with codons for amino acids, a long-lasting memory is represented by a ‘degenerate code’ – a set of pseudo-redundant networks that can ensure its longevity. [Copyright &y& Elsevier]

AbstractDuring axonal regeneration synthesis of different growth-associated proteins is increased. As yet there is no clear picture of the specific contribution made by the transcriptional and post-transcriptional machinery that provides the gene products necessary for process outgrowth. Here we focus our study on the transcriptional processes in neurons by using intron-directed in situ hybridization to the primary transcript of a brain growth protein GAP-43. In most brain regions, levels of primary transcript expression of GAP-43 were highly correlated with levels of its mRNA. However, there were notable dissociations: in hippocampal granule cells, high levels of primary transcript were evident yet no GAP-43 mRNA was detected. In locus coeruleus the reverse was true; there were high levels of GAP-43 mRNA but no detectable primary transcript. A primary transcript antitermination mechanism is proposed to explain the first dissociation, and a post-transcriptional mRNA stabilization mechanism to explain the second. Transcriptional activation during nerve regeneration was monitored by assessing primary transcript induction of GAP-43 in mouse facial motor neurons. This induction, as well as its mRNA, was restricted to the side of the facial nerve crush. Increases were first observed at 24 h with a rapid increase in both measures up to 3 days. To our knowledge, this is the first in vivo evidence demonstrating transcriptional activation of a brain growth protein in regenerating neurons. The present study points to the GAP-43 transcriptional mechanism as a key determinant of GAP-43 synthesis. Along with the recruitment of post-transcriptional mechanisms, such synthesis occurs in response to both intrinsic developmental programs and extrinsic environmental signals. [ABSTRACT FROM AUTHOR]

Presents a study which showed that genetic overexpression of the growth-associated protein, axonal kinase C substrate, dramatically enhanced learning and long-term potentiation in transgenic mice. Materials and methods; Results.

ABSTRACT This short note, which honors Nobelists O'Keefe and the Mosers, asks how the patterning of inputs to a single place cell regulates its firing. Because the combination of inputs to a single CA1 place cell is very large, the generally accepted view is rejected that inputs to a place cell are relatively restricted, near identical repetition upon re-presentation of the environment. The alternative proposed here is that when any 100 excitatory inputs are fired activating a subset combination, which is a large number, selected from the 30,000 synapses, this leads to CA1 cell firing. The selection of the combination of inputs is a very large number it nonetheless leads to the conclusion that even though the same cell dutifully fires when the animal is in an identical location, the inputs that fire the place cell are nonetheless obligatorily non-identical. This CA1 input combinatorial proposal may help us understand the physiological underpinnings of the memory mechanism arising from supple synapses (Routtenberg (2013), Hippocampus 23:202-206). © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Provides information on the role of a protein, GAP-43, in regulating the growth state of axon terminals of neuron. Role in neural development and structural plasticity; Interactions with the guanosine triphosphate-binding proteins; Relationship to the membrane skeleton.

Relates the authors experience on the teaching profession of Mordecai Kaplan at the Rabbi Isaac Elchanan Yeshiva Jewish seminary in the United States. Experience on the apotheositization in the Midrash Shir Hashirim Rabbah subject; Affection of Kaplan on the Jewish tradition; Interest of Kaplan on the philosophy of Judaism.

This paper considers the problem of estimating the states in an unobservable power system, where the number of measurements is not sufficiently large for conventional state estimation. Existing methods are either based on pseudo-data that is inaccurate or depends on a large amount of data that is unavailable in current systems. This study proposes novel graph signal processing (GSP) methods to overcome the lack of information. To this end, first, the graph smoothness property of the states (i.e., voltages) is validated through empirical and theoretical analysis. Then, the regularized GSP weighted least squares (GSP-WLS) state estimator is developed by utilizing the state smoothness. In addition, a sensor placement strategy that aims to optimize the estimation performance of the GSP-WLS estimator is proposed. Simulation results on the IEEE 118-bus system show that the GSP methods reduce the estimation error magnitude by up to two orders of magnitude compared to existing methods, using only 70 sampled buses, and increase of up to 30 % in the probability of bad data detection for the same probability of false alarms in unobservable systems The results conclude that the proposed methods enable an accurate state estimation, even when the system is unobservable, and significantly reduce the required measurement sensors. [ABSTRACT FROM AUTHOR]

Statistical inference problems where both the hypothesis testing and the parameter estimation are of primary interest arise in various signal processing applications. A special case is a cascaded scheme where first, a signal is detected, and then, its parameters of interest are estimated. In this work, we present a new performance evaluation measure for estimation-after-detection that incorporates the estimation and detection-related errors by considering the mean-squared-selected-error, false-alarm-error, and miss-detection-error. The proposed risk is suitable for parameters representing intensity, since its penalty of estimating a high-intensity value of a non-existing phenomenon (wrongly detected) is higher than the penalty of estimating it by a low value. Similarly, according to this risk, miss-detecting a signal of high intensity is worse than miss-detecting a signal of low intensity. We derive a new Cramér-Rao type bound on the risk that can be used for performance analysis and system design. We present the use of the risk for the Pareto-efficient design of the detection threshold. We demonstrate the results on a simple detection-estimation problem, inspired by the application of rain and humidity estimation, and on a problem of noise source detection and estimation of its intensity (standard deviation). Simulations show that the proposed bound is tight. [ABSTRACT FROM AUTHOR]

In this paper, we consider the detection of a small deviation of the frequency of sinusoidal signals, which arises in various signal processing applications. The generalized likelihood ratio test (GLRT) for this problem uses the maximum likelihood (ML) estimator of the frequency, and therefore suffers from high computational complexity. In addition, the GLRT is not necessarily optimal and its performance may degrade for non-asymptotic scenarios that are characterized by close hypotheses and small sample sizes. In this paper we propose a new detection method, named the generalized locally most powerful unbiased (GLMPU) test, which is a general method for local detection in the presence of nuisance parameters. A closed-form expression of the GLMPU test is developed for the detection of frequency deviation in the case where the complex amplitudes of the measured signals and the noise variance are unknown. Numerical simulations show improved performance over the GLRT in terms of probability of detection performance and computational complexity. [ABSTRACT FROM AUTHOR]

Two articles in this issue concern the presynaptic structural remodeling and the molecular events that are important novel mechanisms underlying long-term memory storage processes. © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Two articles in this issue concerning the overexpression of GAP-43 on mossy fiber growth are related to the plasticity of these axons in relation to learning and memory. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Presents an erratum for the article 'Long-term potentiation recruits a trisynaptic excitory associative network within the mouse dentate gyrus,' published in the 2003 issue of the 'European Journal of Neuroscience.'

Abstract Granule cells of the hippocampal dentate gyrus receive two powerful excitatory inputs: the perforant path, originating from the entorhinal cortex, and the associational pathway, originating from mossy cells, the principal neurons of the dentate gyrus hilus. We examined the electrophysiological properties of the less well-studied associational pathway and its interaction with the perforant path in the intact mouse hippocampus and then tested homosynaptic, trans-synaptic and associative long-term potentiation of these pathways. The associational pathway was either monosynaptically activated by stimulation within the inner molecular layer or trisynaptically activated after stimulation of the perforant path. Laminar profiles of extracellularly recorded associational pathway field potentials demonstrated a bell-shaped curve with a peak in the inner molecular layer. Tetanization of the perforant path induced not only homosynaptic potentiation of the perforant path (162.4 ± 6.7% at 0.5–1.5 h after tetanus) but also heterosynaptic potentiation of the associational pathway (115.7 ± 4.9%). Direct tetanization of the associational pathway within the inner molecular layer was ineffective in either the septo-temporal (97.2 ± 4.5%) or temporal-septal (104.4 ± 4.6%) direction. In contrast, conjoint tetanization of the associational pathway with the perforant path potentiated the associational pathway responses in both the septo-temporal (123.4 ± 5.8%) and the temporal-septal (124.8 ± 7.3%) directions. Paired-pulse facilitation was attenuated by long-term potentiation in the perforant path and the associational pathway, suggesting pre-synaptic involvement. These results demonstrate that long-term potentiation of the associational pathway and the perforant path is a product of the network properties of the dentate gyrus rather than of each monosynaptic input alone. The architecture of this neural network may be designed for flexible... [ABSTRACT FROM AUTHOR]

The hippocampal mossy fibers (MFs) are capable of behaviorally selective, use-dependent structural remodeling. Indeed, we previously observed a new layer of Timm's staining induced in the stratum oriens (SO) in CA3 after spatial but not cued water maze learning (Rekart et al., (2007) Learn Mem 14:416-421). This led to the prediction that there is a learning-specific induction of presynaptic terminal plasticity of MF axons. This study confirms this prediction demonstrating, at the confocal level of analysis, terminal-specific, and behavior-selective presynaptic structural plasticity linked to long-term memory. Male adult Wistar rats were trained for 5 days to locate a hidden or visible platform in a water maze and a retention test was performed 7 days later. MF terminal subtypes, specifically identified by an antibody to zinc transporter 3 (ZnT3), were counted from confocal z-stacks in the stratum lucidum (SL) and the SO. In hidden platform trained rats, there was a significant increase in the number of large MF terminals (LMTs, 2.5-10 μm diameter, >2 μm2 area) compared to controls both in the proximal SL ( P < 0.05) and in the SO ( P < 0.01). Surprisingly, there was no detectable increase in small MF terminals (SMTs, 0.5-2 μm diameter, <2 μm2 area) in either SL or SO as a consequence of training. This distinction of the two MF terminal types is functionally important as LMTs synapse on CA3 pyramidal neurons, while SMTs are known to target inhibitory interneurons. The present findings highlight the pivotal role in memory of presynaptic structural plasticity. Because the 'sprouting' observed is specific to the LMT, with no detectable change in the number of the SMT, learning may enhance net excitatory input to CA3 pyramidal neurons. Given the sparse coding of the MF-CA3 connection, and the role that granule cells play in pattern separation, the remodeling observed here may be expected to have a major impact on the long-term integration of spatial context into memory. © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

In a previous study, it was shown that transgenic mice, designated G-NonP, forget the location of a water maze hidden platform when tested 7 days after the last training day (Holahan and Routtenberg (2008) Hippocampus 18:1099-1102). The memory loss in G-NonP mice might be related to altered hippocampal architecture suggested by the fact that in the rat, 7 days after water maze training, there is discernible mossy fiber (MF) growth (Holahan et al. (2006) Hippocampus 16:560-570; Rekart et al. (2007) Learn Mem 14:416-421). In the present report, we studied the distribution of the MF system within the hippocampus of naïve, untrained, G-NonP mouse. In WT mice, the MF projection was restricted to the stratum lucidum of CA3 with no detectable MF innervation in distal stratum oriens (dSO). In G-NonP mice, in contrast, there was an ectopic projection terminating in the CA3 dSO. Unexpectedly, there was nearly a complete loss of immunostaining for the axonal marker Tau1 in the G-NonP transgenic mice in the MF terminal fields indicating that transgenesis itself leads to off-target consequences (Routtenberg (1996) Trends Neurosci 19:471-472). Because transgenic mice overexpressing nonmutated, wild type GAP-43 do not show this ectopic growth (Rekart et al., in press) and the G-NonP mice overexpress a mutated form of GAP-43 precluding its phosphorylation by protein kinase C (PKC), the possibility exists that permanently dephosphorylated GAP-43 disrupts normal axonal fasciculation which gives rise to the ectopic growth into dSO. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Abstract: Damage to the hippocampal formation results in profound impairments in spatial navigation in rats and mice leading to the widely accepted assumption that the hippocampal cellular and molecular memory mechanisms of both genera are conserved. Recently our group has shown in two rat strains that hippocampal-dependent training in the water maze specifically induces robust ‘sprouting’ of granule cell suprapyramidal mossy fiber axon terminal fields. Here we sought to investigate whether the pronounced remodeling of adult hippocampal circuitry observed in the rat is also present in the mouse motivated by the thought that subsequent studies using genetically-engineered mice could then be implemented to explore the molecular mechanisms underlying training-dependent axonal growth in adult rodents. However, in contrast to Wistar rats, no changes in the Timm’s-stained area of mossy fiber terminal fields (MFTFs) were observed in C57BL/6J or 129Sv/EmsJ inbred wild-type mice after water maze training. Neither extending the duration of training nor scaling down the size of the apparatus was able to induce sprouting in mouse mossy fiber pathways. Though there may be similarities in the ultimate output of the hippocampus of rats and mice as inferred from lesion studies, the current results, as well as differences in learning and memory characteristics between the two genera, suggest that the way in which the component circuitry functions is likely to be different; a not too surprising conclusion given the substantial evolutionary distance between them (>20 million years). The present findings afford an opportunity for uncovering linkages between evolutionarily significant alterations in hippocampal circuitry in relation to genera-specific information storage requirements. [Copyright &y& Elsevier]

We have recently discovered differences in the distribution of the mossy fiber terminal field (MFTF) between adult Long-Evans rats (LER) and Wistar rats(WR): the suprapyramidal MFTF extends into distal stratum oriens (dSO) in LER, but is nearly absent in WR (Holahan et al., Hippocampus 16:560-570). To our knowledge, there is no developmental evidence that sheds light on how this strain-dependent MFTF innervation in the adult is achieved. Accordingly, the present study examined the time course of MFTF development from postnatal days 0 to 40 and the effect of NMDA-receptor antagonist 3-(2-carboxypiperazin-4-yl) propyl-1-phosphonic acid (CPP) on this developmental organization. In both LER and WR, a MFTF projection to dSO was observed between P18 and P21. By P24, the dSO projection in WR was no longer detectable whereas in LER, the dSO projection seen on P21 remained. We suggest that in WR a retraction of the MFTF projection from dSO to stratum lucidum between P21 and P24 leads to its adult pattern. In WR, CPP administration enhanced the dSO projection, possibly by blocking the retraction process. In LER, CPP administration reduced the dSO projection. Thus, in each strain, NMDA receptor blockade effectively reversed the developmental course of MFTF pattern of innervation. The present results lend strong support to the view that NMDA receptor regulation of input-dependent processes during development is of critical importance in promoting the motility and target selection of presynaptic MF axons. This regulation extends later into development than had previously been thought. © 2006 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Cajal proposed that the rearrangement and growth of neurites and synaptic terminals is a substrate for the formation and storage of long-term memories. Proteins that regulate this learning-dependent growth are therefore likely to be 'core determinants' (Sanes and Lichtman, Nat Neurosci 1999; 2:597-604) of such information storage processes. Although the growth-associated, protein kinase C (PKC) substrate GAP-43 has been oft-implicated in synaptic plasticity and memory, it has never been demonstrated that a reduction in the level of this protein has a deleterious effect on memory, because most homozygotes die perinatally. In this report, we observe significant memory impairments in heterozygous GAP-43 knockout mice with GAP-43 levels reduced by one-half. Impaired memory for a context was demonstrated in contextual fear conditioning. Importantly, no significant impairments in cued conditioning or on tests of nociceptive or auditory perception were observed in the heterozygous knockout, indicating that the observed impairments were unlikely related to performance or acquisition factors and are the result of reduced GAP-43 levels in the hippocampus. The present results, taken together with the prior demonstration of enhanced memory in transgenic mice overexpressing GAP-43, provide strong evidence for a pivotal role of hippocampal GAP-43 in the bidirectional regulation of mnemonic processing. © 2004 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

There is increasing evidence that transcription factors (TFs) play a critical role in maintaining later phases of hippocampal long-term potentiation (LTP). We have been led to study the role in synaptic plasticity of the powerful, yet generally unheralded, NF-κB TF because it may serve as both a signaling molecule after its activation at the synapse and then a transcription initiator upon reaching the nucleus. In the present study, we show that LTP activates NF-κB in the intact mouse hippocampus. Mice were sacrificed 15 min after one of three treatments: tetanization (high-frequency stimulation [HFS]), low-frequency stimulation (LFS), or no stimulated control animals (CT). In a first study, nuclear NF-κB activity from hippocampus was estimated by electrophoretic mobility shift assays (EMSAs). A higher level of hippocampal TF binding to the NF-κB recognition element was found in the HFS group compared with LFS or CT. In a second study, NF-κB activity was evaluated by immunohistochemistry with a specific antibody that recognizes the activated form of NF-κB. This antibody binds to the exposed nuclear location sequence on the p65 subunit of NF-κB consequent to its dissociation from the inhibitory IκB molecule. In the four subfields of hippocampus examined-granule cell layer, hilus of the dentate gyrus, CA3 and CA1 pyramidal fields of the hippocampal gyrus-the highest levels of activated NF-κB, statistically significant in all cases were found after HFS. In certain comparisons, LFS animals also showed significant elevation with respect to CT. These results support the role of NF-κB as part of the synaptic signaling and transcriptional regulation mechanism required in long-term plasticity, emphasizing the combinatorial nature of TF function. © 2004 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Provides abstracts of plenary lectures articles presented in the second scientific conference "Restauración Neurológica 2004". Examination of the compensatory mechanisms and motor functions of the basal ganglia; Role of progesterone and related neurosteroids in the treatment of traumatic brain injury and stroke; Investigation into the extent of growth of the Hebb Synapse; Evaluation of the functional magnetic resonance imaging in Parkinson's disease before and after levodopa.

In this paper, we consider the problem of blind estimation of states and topology (BEST) in power systems. We use the linearized dc model of real power measurements with unknown voltage phases (i.e., states) and an unknown admittance matrix (i.e., topology) and show that the BEST problem can be formulated as a blind source separation (BSS) problem with a weighted Laplacian mixing matrix. We develop the constrained maximum likelihood (ML) estimator of the Laplacian matrix for this graph BSS problem with Gaussian-distributed states. The ML-BEST is shown to be only a function of the states’ second-order statistics. Since the topology recovery stage of the ML-BEST approach results in a high-complexity optimization problem, we propose two low-complexity methods to implement it: First, two-phase topology recovery, which is based on solving the relaxed convex optimization and then finding the closest Laplacian matrix, and second, augmented Lagrangian topology recovery. We derive a closed-form expression for the associated Cram $\acute{\text{e}}$ r–Rao bound (CRB) on the topology matrix estimation. The performance of the proposed methods is evaluated for three case studies: the IEEE-14 bus system, the IEEE 118-bus system, and a random network, and compared with the oracle minimum mean-squared-error state estimator and with the proposed CRB. [ABSTRACT FROM AUTHOR]

Hippocampal mossy fibers (MFs) can show plasticity of their axon terminal arbor consequent to learning a spatial memory task. Such plasticity is seen as translaminar sprouting from the stratum lucidum (SL) of CA3 into the stratum pyramidale (SP) and the stratum oriens (SO). However, the functional role of this presynaptic remodeling is still obscure. In vivo imaging that allows longitudinal observation of such remodeling could provide a deeper understanding of this presynaptic growth phenomenon as it occurs over time. Here we used manganese-enhanced magnetic resonance imaging (MEMRI), which shows a high-contrast area that co-localizes with the MFs. This technique was applied in the detection of learning-induced MF plasticity in two strains of rats. Quantitative analysis of a series of sections in the rostral dorsal hippocampus showed increases in the CA3a′ area in MEMRI of trained Wistar rats consistent with the increased SO + SP area seen in the Timm's staining. MF plasticity was not seen in the trained Lister-Hooded rats in either MEMRI or in Timm's staining. This indicates the potential of MEMRI for revealing neuro-architectures and plasticity of the hippocampal MF system in vivo in longitudinal studies. [ABSTRACT FROM AUTHOR]

Learning and memory employs a series of cognitive processes which require the coordination of multiple areas across the brain. However in vivo imaging of cognitive function has been challenging in rodents. Since these processes involve synchronous firing among different brain loci we explored functional connectivity imaging with resting-state fMRI. After 5-day training on a hidden platform watermaze task, notable signal correlations were seen between the hippocampal CA3 and other structures, including thalamus, septum and cingulate cortex, compared to swim control or naïve animals. The connectivity sustained 7 days after training and was reorganized toward the cortex, consistent with views of memory trace distribution leading to memory consolidation. These data demonstrates that, after a cognitive task, altered functional connectivity can be detected in the subsequently sedated rodent using in vivo imaging. This approach paves the way to understand dynamics of area-dependent distribution processes in animal models of cognition. [ABSTRACT FROM AUTHOR]

ABSTRACT Wnt proteins have emerged as transmembrane signaling molecules that regulate learning and memory as well as synaptic plasticity at central synapses (Inestrosa and Arenas (2010) Nat Rev Neurosci 11:77-86; Maguschak and Ressler (2011) J Neurosci 31:13057-13067; Tabatadze et al. (2012) Hippocampus 22: 1228-1241; Fortress et al. (2013) J Neurosci 33:12619-12626). For example, there is both a training-selective and Wnt isoform-specific increase in Wnt 7 levels in hippocampus seven days after spatial learning in rats (Tabatadze et al. (2012) Hippocampus 22: 1228-1241). Despite growing interest in Wnt signaling pathways in the adult brain, intracellular distribution and release of Wnt molecules from synaptic compartments as well as their influence on synaptic strength and connectivity remain less well understood. As a first step in such an analysis, we show here that Wnt 7 levels in primary hippocampal cells are elevated by potassium or glutamate activation in a time-dependent manner. Subsequent Wnt 7 elevation in dendrites suggests selective somato-dendritic trafficking followed by transport from dendrites to their spines. Wnt 7 elevation is also TTX-reversible, establishing that its elevation is indeed an activity-dependent process. A second stimulation given 6 h after the first significantly reduces Wnt 7 levels in dendrites 3 h later as compared to non-stimulated controls suggesting activity-dependent Wnt 7 release from dendrites and spines. In a related experiment designed to mimic the release of Wnt 7, exogenous recombinant Wnt 7 increased the number of active zones in presynaptic terminals as indexed by bassoon. This suggests the formation of new presynaptic release sites and/or presynaptic terminals. Wnt signaling inhibitor sFRP-1 completely blocked this Wnt 7-induced elevation of bassoon cluster number and cluster area. We suggest that Wnt 7 is a plasticity-related protein involved in the regulation of presynaptic plasticity via a retrograde signaling mechanism as previously proposed (Routtenberg (1999) Trends in Neuroscience 22:255-256). These findings provide support for this proposal, which offers a new perspective on the synaptic tagging mechanism (Redondo and Morris (2011) Nat Rev Neurosci 12:17-30). © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Abstract: Zinc (Zn) is involved in regulating mental and motor functions of the brain. Previous approaches have determined Zn content in the brain using semi-quantitative histological methods. We present here an alternative approach to map and quantify Zn levels in the synapses from mossy fibers to CA3 region of the hippocampus. Based on the use of nuclear microscopy, which is a combination of imaging and analysis techniques encompassing scanning transmission ion microscopy (STIM), Rutherford backscattering spectrometry (RBS), and particle induced X-ray emission (PIXE), it enables quantitative elemental mapping down to the parts per million (μg/g dry weight) levels of zinc in rat hippocampal mossy fibers. Our results indicate a laminar-specific Zn concentration of 240±9μM in wet weight level (135±5μg/g dry weight) in the stratum lucidum (SL) compared to 144±6μM in wet weight level (81±3μg/g dry weight) in the stratum pyramidale (SP) and 78±10μM in wet weight level (44±5μg/g dry weight) in the stratum oriens (SO) of the hippocampus. The mossy fibers terminals in CA3 are mainly located in the SL. Hence the Zn concentration is suggested to be within this axonal presynaptic terminal system. [Copyright &y& Elsevier]

Transmembrane signaling mechanisms are critical for regulating the plasticity of neuronal connections underlying the establishment of long-lasting memory (e.g., Linden and Routtenberg (1989) Brain Res Rev 14:279-296; Sossin (1996) Trends Neurosci 19:215-218; Mayr and Montminy (2001) Nat Rev Mol Cell Biol 2:599-609; Chen et al. (2011) Nature 469:491-497). One signaling mechanism that has received surprisingly little attention in this regard is the well-known Wnt transmembrane signaling pathway even though this pathway in the adult plays a significant role, for example, in postsynaptic dendritic spine morphogenesis and presynaptic terminal neurotransmitter release (Inestrosa and Arenas (2010) Nat Rev Neurosci 11:77-86). The present report now provides the first evidence of Wnt signaling in spatial information storage processes. Importantly, this Wnt participation is specific and selective. Thus, spatial, but not cued, learning in a water maze selectively elevates the levels in hippocampus of Wnt 7 and Wnt 5a, but not the Wnt 3 isoform, indicating behavioral selectivity and isoform specificity. Wnt 7 elevation is subfield-specific: granule cells show an increase with no detectable change in CA3 neurons. Wnt 7 elevation is temporally specific: increased Wnt signaling is not observed during training, but is seen 7 days and, unexpectedly, 30 days later. If the Wnt elevation after learning is activity-dependent, then it may be possible to model this effect in primary hippocampal neurons in culture. Here, we evaluate the consequence of potassium or glutamate depolarization on Wnt signaling. This represents, to our knowledge, the first demonstration of an activation-dependent elevation of Wnt levels and surprisingly an increased number of Wnt-stained puncta in neurites suggestive of trafficking from the cell body to neuronal processes, probably dendrites. It is proposed that Wnt signaling pathways regulate long-term information storage in a behavioral-, cellular-, and isoform-specific manner. © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

NF-κB is an evolutionarily conserved family of transcription factors (TFs) critically involved in basic cellular mechanisms of the immune response, inflammation, development and apoptosis. In spite of the fact that it is expressed in the central nervous system, particularly in areas involved in memory processing, and is activated by signals such as glutamate and Ca2+, its role in neural plasticity and memory has only recently become apparent. A surprising feature of this molecule is its presence within the synapse. An increasing number of reports have called attention to the role of this TF in processes that require long-term regulation of the synaptic function underlying memory and neural plasticity. Here we review the evidence regarding a dual role for NF-κB, as both a signalling molecule after its activation at the synapse and a transcriptional regulator upon reaching the nucleus. The specific role of this signal, as well as the general transcriptional mechanism, in the process of memory formation is discussed. Converging lines of evidence summarized here point to a pivotal role for the NF-κB transcription factor as a direct signalling mechanism in the regulation of gene expression involved in long-term memory. [ABSTRACT FROM AUTHOR]

Hebb () proposed that after learning both presynaptic and postsynaptic structural changes form the neural substrate oflong-lasting memory. Despite this, there are few instances linking presynaptic remodeling with learning. Here the authors demonstrate in two different rat strains that learning the location of a hidden platform induces expansion of the presynaptic hippocampal mossy fiber terminal field (MFTF) from the stratum lucidum to the distal stratum oriens (dSO). Prior to any training, Long Evans rats (LER) showed an extensive endogenous MFTF innervation of DSO, in contrast to Wistar rats (WR) that showed minimal innervation. LER showed better recall than WR on the hidden platform water maze task and a visible reversal water maze task. In both strains, significant MFTF expansion to dSO, spanning approximately 200 μm, was detected 7 days after training on the hidden platform task, but only LER showed significant MFTF expansion 24 h after training. It is attractive to think that the MFTF expansion to dSO contributes both to long-lasting memory formation and to facilitating spatial navigation strategies. The present results establish learning-induced axonal remodeling of the hippocampal MF system in adult rats as an especially useful system for exploring presynaptic morphological adjustments consequent to learning. © 2006 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

The neuropathology of Alzheimer''s disease (AD) reflects a precarious balance between neurodegenerative phenomena and reactive events of neuroplasticity. This latter aspect of AD neuropathology has received less attention than it deserves and its contribution to memory loss is therefore not well understood. To monitor neuroplastic-related events we studied the distribution of the plasticity-associated, brain growth protein GAP-43 in AD subjects and age-matched controls. In tissue from AD patients, we observed a consistent elevation of GAP-43 in a subfield of the hippocampus, stratum lacunosum moleculare. This subfield contains inputs from multiple brain regions and is known to regulate declarative memory function. Levels of potentially aberrant sprouting, as marked by elevated growth protein, were positively correlated with the severity of AD suggesting that increased expression of GAP-43 leads to a miswiring of circuits critical for memory function. Our findings suggest a mechanism, aberrant neuroplasticity, that in concert with neurodegeneration may importantly contribute to the memory loss in AD. [Copyright &y& Elsevier]