Angiotensinergic neurons in sympathetic coeliac ganglia innervating rat and human mesenteric resistance blood vessels

In contrast to the current belief that angiotensin II (Ang II) interacts with the sympathetic nervous system only as a circulating hormone, we document here the existence of endogenous Ang II in the neurons of rat and human sympathetic coeliac ganglia and their angiotensinergic innervation with mesenteric resistance blood vessels. Angiotensinogen - and angiotensin converting enzyme-mRNA were detected by using quantitative real time polymerase chain reaction in total RNA extracts of rat coeliac ganglia, while renin mRNA was untraceable. Cathepsin D, a protease responsible for cleavage beneath other substrates also angiotensinogen to angiotensin I, was successfully detected in rat coeliac ganglia indicating the possibility of existence of alternative pathways. Angiotensinogen mRNA was also detected by in situ hybridization in the cytoplasm of neurons of rat coeliac ganglia. Immunoreactivity for Ang II was demonstrated in rat and human coeliac ganglia as well as with mesenteric resistance blood vessels. By using confocal laser scanning microscopy we were able to demonstrate the presence of angiotensinergic synapses en passant along side of vascular smooth muscle cells. Our findings indicate that Ang II is synthesized inside the neurons of sympathetic coeliac ganglia and may act as an endogenous neurotransmitter locally with the mesenteric resistance blood vessels.

A 45nm CMOS DESIGN OF NEUROMORPHIC SYSTEM

Neuromorphic computing has become an emerging field in wide range of applications. Its challenge lies in developing a brain-inspired architecture that can emulate human brain and can work for real time applications. In this report a flexible neural architecture is presented which consists of 128 X 128 SRAM crossbar memory and 128 spiking neurons. For Neuron, digital integrate and fire model is used. All components are designed in 45nm technology node. The core can be configured for certain Neuron parameters, Axon types and synapses states and are fully digitally implemented. Learning for this architecture is done offline. To train this circuit a well-known algorithm Restricted Boltzmann Machine (RBM) is used and linear classifiers are trained at the output of RBM. Finally, circuit was tested for handwritten digit recognition application. Future prospects for this architecture are also discussed.

Simulating in vivo-like Synaptic Input Patterns in Multicompartmental Models

In the laboratory of Dr. Dieter Jaeger at Emory University, we use computer simulations to study how the biophysical properties of neurons—including their three-dimensional structure, passive membrane resistance and capacitance, and active membrane conductances generated by ion channels—affect the way that the neurons transfer synaptic inputs into the action potential streams that represent their output. Because our ultimate goal is to understand how neurons process and relay information in a living animal, we try to make our computer simulations as realistic as possible. As such, the computer models reflect the detailed morphology and all of the ion channels known to exist in the particular neuron types being simulated, and the model neurons are tested with synaptic input patterns that are intended to approximate the inputs that real neurons receive in vivo. The purpose of this workshop tutorial was to explain what we mean by ‘in vivo-like’ synaptic input patterns, and how we introduce these input patterns into our computer simulations using the freely available GENESIS software package (http://www.genesis-sim.org/GENESIS). The presentation was divided into four sections: first, an explanation of what we are talking about when we refer to in vivo-like synaptic input patterns

Learning by the Dendritic Prediction of Somatic Spiking

Recent modeling of spike-timing-dependent plasticity indicates that plasticity involves as a third factor a local dendritic potential, besides pre- and postsynaptic firing times. We present a simple compartmental neuron model together with a non-Hebbian, biologically plausible learning rule for dendritic synapses where plasticity is modulated by these three factors. In functional terms, the rule seeks to minimize discrepancies between somatic firings and a local dendritic potential. Such prediction errors can arise in our model from stochastic fluctuations as well as from synaptic input, which directly targets the soma. Depending on the nature of this direct input, our plasticity rule subserves supervised or unsupervised learning. When a reward signal modulates the learning rate, reinforcement learning results. Hence a single plasticity rule supports diverse learning paradigms.

Matching Recall and Storage in Sequence Learning with Spiking Neural Networks

Storing and recalling spiking sequences is a general problem the brain needs to solve. It is, however, unclear what type of biologically plausible learning rule is suited to learn a wide class of spatiotemporal activity patterns in a robust way. Here we consider a recurrent network of stochastic spiking neurons composed of both visible and hidden neurons. We derive a generic learning rule that is matched to the neural dynamics by minimizing an upper bound on the Kullback–Leibler divergence from the target distribution to the model distribution. The derived learning rule is consistent with spike-timing dependent plasticity in that a presynaptic spike preceding a postsynaptic spike elicits potentiation while otherwise depression emerges. Furthermore, the learning rule for synapses that target visible neurons can be matched to the recently proposed voltage-triplet rule. The learning rule for synapses that target hidden neurons is modulated by a global factor, which shares properties with astrocytes and gives rise to testable predictions.

Post-translational regulation of an Aplysia glutamate transporter during long-term facilitation.

Regulation of glutamate transporters accompanies plasticity of some glutamatergic synapses. The regulation of glutamate uptake at the Aplysia sensorimotor synapse during long-term facilitation (LTF) was investigated. Previously, increases in levels of ApGT1 (Aplysia glutamate transporter 1) in synaptic membranes were found to be related to long-term increases in glutamate uptake. In this study, we found that regulation of ApGT1 during LTF appears to occur post-translationally. Serotonin (5-HT) a transmitter that induces LTF did not increase synthesis of ApGT1. A pool of ApGT1 appears to exist in sensory neuron somata, which is transported to the terminals by axonal transport. Blocking the rough endoplasmic reticulum-Golgi-trans-Golgi network (TGN) pathway with Brefeldin A prevented the 5-HT-induced increase of ApGT1 in terminals. Also, 5-HT produced changes in post-translational modifications of ApGT1 as well as changes in the levels of an ApGT1-co-precipitating protein. These results suggest that regulation of trafficking of ApGT1 from the vesicular trafficking system (rough endoplasmic reticulum-Golgi-TGN) in the sensory neuron somata to the terminals by post-translational modifications and protein interactions appears to be the mechanism underlying the increase in ApGT1, and thus, glutamate uptake during memory formation.

Quantitation of contacts among sensory, motor, and serotonergic neurons in the pedal ganglion of aplysia.

Present models of long-term sensitization in Aplysia californica indicate that the enhanced behavioral response is due, at least in part, to outgrowth of sensory neurons mediating defensive withdrawal reflexes. Presumably, this outgrowth strengthens pre-existing connections by formation of new synapses with follower neurons. However, the relationship between the number of sensorimotor contacts and the physiological strength of the connection has never been examined in intact ganglia. As a first step in addressing this issue, we used confocal microscopy to examine sites of contact between sensory and motor neurons in naive animals. Our results revealed relatively few contacts between physiologically connected cells. In addition, the number of contact sites was proportional to the amplitude of the EPSP elicited in the follower motor neuron by direct stimulation of the sensory neuron. This is the first time such a correlation has been observed in the central nervous system. Serotonin is the neurotransmitter most closely examined for its role in modulating synaptic strength at the sensorimotor synapse. However, the structural relationship of serotonergic processes and sensorimotor synapses has never been examined. Surprisingly, serotonergic processes usually made contact with sensory and motor neurons at sites located relatively distant from the sensorimotor synapse. This result implies that heterosynaptic regulation is due to nondirected release of serotonin into the neuropil.

The ubiquitin-proteasome system is necessary for long-term synaptic depression in Aplysia.

The neuropeptide Phe-Met-Arg-Phe-NH(2) (FMRFa) can induce transcription-dependent long-term synaptic depression (LTD) in Aplysia sensorimotor synapses. We investigated the role of the ubiquitin-proteasome system and the regulation of one of its components, ubiquitin C-terminal hydrolase (ap-uch), in LTD. LTD was sensitive to presynaptic inhibition of the proteasome and was associated with upregulation of ap-uch mRNA and protein. This upregulation appeared to be mediated by CREB2, which is generally regarded as a transcription repressor. Binding of CREB2 to the promoter region of ap-uch was accompanied by histone hyperacetylation, suggesting that CREB2 cannot only inhibit but also promote gene expression. CREB2 was phosphorylated after FMRFa, and blocking phospho-CREB2 blocked LTD. In addition to changes in the expression of ap-uch, the synaptic vesicle-associated protein synapsin was downregulated in LTD in a proteasome-dependent manner. These results suggest that proteasome-mediated protein degradation is engaged in LTD and that CREB2 may act as a transcription activator under certain conditions.

TGF-beta1 in Aplysia: role in long-term changes in the excitability of sensory neurons and distribution of TbetaR-II-like immunoreactivity.

Exogenous recombinant human transforming growth factor beta-1 (TGF-beta1) induced long-term facilitation of Aplysia sensory-motor synapses. In addition, 5-HT-induced facilitation was blocked by application of a soluble fragment of the extracellular portion of the TGF-beta1 type II receptor (TbetaR-II), which presumably acted by scavenging an endogenous TGF-beta1-like molecule. Because TbetaR-II is essential for transmembrane signaling by TGF-beta, we sought to determine whether Aplysia tissues contained TbetaR-II and specifically, whether neurons expressed the receptor. Western blot analysis of Aplysia tissue extracts demonstrated the presence of a TbetaR-II-immunoreactive protein in several tissue types. The expression and distribution of TbetaR-II-immunoreactive proteins in the central nervous system was examined by immunohistochemistry to elucidate sites that may be responsive to TGF-beta1 and thus may play a role in synaptic plasticity. Sensory neurons in the ventral-caudal cluster of the pleural ganglion were immunoreactive for TbetaR-II, as well as many neurons in the pedal, abdominal, buccal, and cerebral ganglia. Sensory neurons cultured in isolation and cocultured sensory and motor neurons were also immunoreactive. TGF-beta1 affected the biophysical properties of cultured sensory neurons, inducing an increase of excitability that persisted for at least 48 hr. Furthermore, exposure to TGF-beta1 resulted in a reduction in the firing threshold of sensory neurons. These results provide further support for the hypothesis that TGF-beta1 plays a role in long-term synaptic plasticity in Aplysia.

SIGNALING MECHANISMS THAT CONTROL GAP JUNCTIONAL COUPLING BETWEEN RETINAL NEURONS

Gap junctions between neurons form the structural substrate for electrical synapses. Connexin 36 (Cx36, and its non-mammalian ortholog connexin 35) is the major neuronal gap junction protein in the central nervous system (CNS), and contributes to several important neuronal functions including neuronal synchronization, signal averaging, network oscillations, and motor learning. Connexin 36 is strongly expressed in the retina, where it is an obligatory component of the high-sensitivity rod photoreceptor pathway. A fundamental requirement of the retina is to adapt to broadly varying inputs in order to maintain a dynamic range of signaling output. Modulation of the strength of electrical coupling between networks of retinal neurons, including the Cx36-coupled AII amacrine cell in the primary rod circuit, is a hallmark of retinal luminance adaptation. However, very little is known about the mechanisms regulating dynamic modulation of Cx36-mediated coupling. The primary goal of this work was to understand how cellular signaling mechanisms regulate coupling through Cx36 gap junctions. We began by developing and characterizing phospho-specific antibodies against key regulatory phosphorylation sites on Cx36. Using these tools we showed that phosphorylation of Cx35 in fish models varies with light adaptation state, and is modulated by acute changes in background illumination. We next turned our focus to the well-studied and readily identifiable AII amacrine cell in mammalian retina. Using this model we showed that increased phosphorylation of Cx36 is directly related to increased coupling through these gap junctions, and that the dopamine-stimulated uncoupling of the AII network is mediated by dephosphorylation of Cx36 via protein kinase A-stimulated protein phosphatase 2A activity. We then showed that increased phosphorylation of Cx36 on the AII amacrine network is driven by depolarization of presynaptic ON-type bipolar cells as well as background light increments. This increase in phosphorylation is mediated by activation of extrasynaptic NMDA receptors associated with Cx36 gap junctions on AII amacrine cells and by Ca2+-calmodulin-dependent protein kinase II activation. Finally, these studies indicated that coupling is regulated locally at individual gap junction plaques. This work provides a framework for future study of regulation of Cx36-mediated coupling, in which increased phosphorylation of Cx36 indicates increased neuronal coupling.

Beta 1-integrins are required for hippocampal AMPA receptor-dependent synaptic transmission, synaptic plasticity, and working memory.

Integrins comprise a large family of cell adhesion receptors that mediate diverse biological events through cell-cell and cell-extracellular matrix interactions. Recent studies have shown that several integrins are localized to synapses with suggested roles in synaptic plasticity and memory formation. We generated a postnatal forebrain and excitatory neuron-specific knock-out of beta1-integrin in the mouse. Electrophysiological studies demonstrated that these mutants have impaired synaptic transmission through AMPA receptors and diminished NMDA receptor-dependent long-term potentiation. Despite the impairment in hippocampal synaptic transmission, the mutants displayed normal hippocampal-dependent spatial and contextual memory but were impaired in a hippocampal-dependent, nonmatching-to-place working memory task. These phenotypes parallel those observed in animals carrying knock-outs of the GluR1 (glutamate receptor subunit 1) subunit of the AMPA receptor. These observations suggest a new function of beta1-integrins as regulators of synaptic glutamate receptor function and working memory.

Bifurcation and singularity analysis of a molecular network for the induction of long-term memory.

Withdrawal reflexes of the mollusk Aplysia exhibit sensitization, a simple form of long-term memory (LTM). Sensitization is due, in part, to long-term facilitation (LTF) of sensorimotor neuron synapses. LTF is induced by the modulatory actions of serotonin (5-HT). Pettigrew et al. developed a computational model of the nonlinear intracellular signaling and gene network that underlies the induction of 5-HT-induced LTF. The model simulated empirical observations that repeated applications of 5-HT induce persistent activation of protein kinase A (PKA) and that this persistent activation requires a suprathreshold exposure of 5-HT. This study extends the analysis of the Pettigrew model by applying bifurcation analysis, singularity theory, and numerical simulation. Using singularity theory, classification diagrams of parameter space were constructed, identifying regions with qualitatively different steady-state behaviors. The graphical representation of these regions illustrates the robustness of these regions to changes in model parameters. Because persistent protein kinase A (PKA) activity correlates with Aplysia LTM, the analysis focuses on a positive feedback loop in the model that tends to maintain PKA activity. In this loop, PKA phosphorylates a transcription factor (TF-1), thereby increasing the expression of an ubiquitin hydrolase (Ap-Uch). Ap-Uch then acts to increase PKA activity, closing the loop. This positive feedback loop manifests multiple, coexisting steady states, or multiplicity, which provides a mechanism for a bistable switch in PKA activity. After the removal of 5-HT, the PKA activity either returns to its basal level (reversible switch) or remains at a high level (irreversible switch). Such an irreversible switch might be a mechanism that contributes to the persistence of LTM. The classification diagrams also identify parameters and processes that might be manipulated, perhaps pharmacologically, to enhance the induction of memory. Rational drug design, to affect complex processes such as memory formation, can benefit from this type of analysis.

A model of the roles of essential kinases in the induction and expression of late long-term potentiation.

The induction of late long-term potentiation (L-LTP) involves complex interactions among second-messenger cascades. To gain insights into these interactions, a mathematical model was developed for L-LTP induction in the CA1 region of the hippocampus. The differential equation-based model represents actions of protein kinase A (PKA), MAP kinase (MAPK), and CaM kinase II (CAMKII) in the vicinity of the synapse, and activation of transcription by CaM kinase IV (CAMKIV) and MAPK. L-LTP is represented by increases in a synaptic weight. Simulations suggest that steep, supralinear stimulus-response relationships between stimuli (e.g., elevations in [Ca(2+)]) and kinase activation are essential for translating brief stimuli into long-lasting gene activation and synaptic weight increases. Convergence of multiple kinase activities to induce L-LTP helps to generate a threshold whereby the amount of L-LTP varies steeply with the number of brief (tetanic) electrical stimuli. The model simulates tetanic, -burst, pairing-induced, and chemical L-LTP, as well as L-LTP due to synaptic tagging. The model also simulates inhibition of L-LTP by inhibition of MAPK, CAMKII, PKA, or CAMKIV. The model predicts results of experiments to delineate mechanisms underlying L-LTP induction and expression. For example, the cAMP antagonist RpcAMPs, which inhibits L-LTP induction, is predicted to inhibit ERK activation. The model also appears useful to clarify similarities and differences between hippocampal L-LTP and long-term synaptic strengthening in other systems.

Long-lasting synaptic potentiation induced by depolarization under conditions that eliminate detectable Ca2+ signals.

Activity-dependent alterations of synaptic transmission important for learning and memory are often induced by Ca(2+) signals generated by depolarization. While it is widely assumed that Ca(2+) is the essential transducer of depolarization into cellular plasticity, little effort has been made to test whether Ca(2+)-independent responses to depolarization might also induce memory-like alterations. It was recently discovered that peripheral axons of nociceptive sensory neurons in Aplysia display long-lasting hyperexcitability triggered by conditioning depolarization in the absence of Ca(2+) entry (using nominally Ca(2+)-free solutions containing EGTA, "0Ca/EGTA") or the absence of detectable Ca(2+) transients (adding BAPTA-AM, "0Ca/EGTA/BAPTA-AM"). The current study reports that depolarization of central ganglia to approximately 0 mV for 2 min in these same solutions induced hyperexcitability lasting >1 h in sensory neuron processes near their synapses onto motor neurons. Furthermore, conditioning depolarization in these solutions produced a 2.5-fold increase in excitatory postsynaptic potential (EPSP) amplitude 1-3 h afterward despite a drop in motor neuron input resistance. Depolarization in 0 Ca/EGTA produced long-term potentiation (LTP) of the EPSP lasting > or = 1 days without changing postsynaptic input resistance. When re-exposed to extracellular Ca(2+) during synaptic tests, prior exposure to 0Ca/EGTA or to 0Ca/EGTA/BAPTA-AM decreased sensory neuron survival. However, differential effects on neuronal health are unlikely to explain the observed potentiation because conditioning depolarization in these solutions did not alter survival rates. These findings suggest that unrecognized Ca(2+)-independent signals can transduce depolarization into long-lasting synaptic potentiation, perhaps contributing to persistent synaptic alterations following large, sustained depolarizations that occur during learning, neural injury, or seizures.

Hebbian analysis of the transformation of medial entorhinal grid-cell inputs to hippocampal place fields.

The discovery of grid cells in the medial entorhinal cortex (MEC) permits the characterization of hippocampal computation in much greater detail than previously possible. The present study addresses how an integrate-and-fire unit driven by grid-cell spike trains may transform the multipeaked, spatial firing pattern of grid cells into the single-peaked activity that is typical of hippocampal place cells. Previous studies have shown that in the absence of network interactions, this transformation can succeed only if the place cell receives inputs from grids with overlapping vertices at the location of the place cell's firing field. In our simulations, the selection of these inputs was accomplished by fast Hebbian plasticity alone. The resulting nonlinear process was acutely sensitive to small input variations. Simulations differing only in the exact spike timing of grid cells produced different field locations for the same place cells. Place fields became concentrated in areas that correlated with the initial trajectory of the animal; the introduction of feedback inhibitory cells reduced this bias. These results suggest distinct roles for plasticity of the perforant path synapses and for competition via feedback inhibition in the formation of place fields in a novel environment. Furthermore, they imply that variability in MEC spiking patterns or in the rat's trajectory is sufficient for generating a distinct population code in a novel environment and suggest that recalling this code in a familiar environment involves additional inputs and/or a different mode of operation of the network.