Spatial exploration induces a persistent reversal of long-term potentiation in rat hippocampus

Experience-dependent long-lasting increases in excitatory synaptic transmission in the hippocampus are believed to underlie certain types of memory(1-3). Whereas stimulation of hippocampal pathways in freely moving rats can readily elicit a long-term potentiation (LTP) of transmission that may last for weeks, previous studies have failed to detect persistent increases in synaptic efficacy after hippocampus-mediated learning(4-6). As changes in synaptic efficacy are contingent on the history of plasticity at the synapses(7), we have examined the effect of experience-dependent hippocampal activation on transmission after the induction of LTP, We show that exploration of a new, non-stressful environment rapidly induces a complete and persistent reversal of the expression of high-frequency stimulation-induced early-phase LTP in the CA1 area of the hippocampus, without affecting baseline transmission in a control pathway. LTP expression is not affected by exploration of familiar environments. We found that spatial exploration affected LTP within a defined time window because neither the induction of LTP nor the maintenance of long-established LTP was blocked. The discovery of a novelty-induced reversal of LTP expression provides strong evidence that extensive long-lasting decreases in synaptic efficacy may act in tandem with enhancements at selected synapses to allow the detection and storage of new information by the hippocampus.

Propofol effects on excitatory synaptic efficacy in the CA1 region of the developing hippocarnpus

The anesthetic, propofol, effectively suppresses excitatory synaptic transmission and facilitates long-term depression (LTD) in the CA1 region of the hippocampus. Here, we have examined whether these effects are different in the developing hippocampus. We found that propofol in suppressing whole-cell excitatory postsynaptic currents (EPSC) was more effective in 21 day old rats than either in 7 day old rats or under the condition of high intracellular chloride concentration in 21 day old rats. Furthermore, the propofol concentration to facilitate the NMDA receptor-dependent LTD was lower at postnatal day 21 than at postnatal day 7. Interestingly, the decay time of EPSC was decreased during the development from postnatal day 7 to 21, but it was increased by the recording condition of high intracellular chloride concentration or by propofol administration. All these effects of propofol were dependent on the chloride channel opening. These observations suggest that propofol may induce differential anesthetic effects in the developing hippocampus, at least partially, depending on the intracellular chloride concentration. (c) 2005 Elsevier B.V. All rights reserved.

N-methyl-D-aspartate receptor-dependent long-term potentiation in CA1 region affects synaptic expression of glutamate receptor subunits and associated proteins in the whole hippocampus

Long term potentiation in hippocampus, evoked by high-frequency stimulation, is mediated by two major glutamate receptor subtypes, alpha-amino-3-hydroxyl-5-methyl-4-isoxazole propionate receptors and N-methyl-D-aspartate receptors. Receptor subunit compos

Discrete dislocation plasticity analysis of size effects in single crystals

The effect of size and slip system configuration on the tensile stress-strain response of micron-sized planar crystals as obtained from discrete dislocation plasticity simulations is presented. The crystals are oriented for either single or symmetric double slip. With the rotation of the tensile axis unconstrained, there is a strong size dependence, with the flow strength increasing with decreasing specimen size. Below a certain specimen size, the flow strength of the crystals is set by the nucleation strength of the initially present Frank-Read sources. The main features of the size dependence are the same for both the single and symmetric double slip configurations.

SynGAP isoforms exert opposing effects on synaptic strength.

Alternative promoter usage and alternative splicing enable diversification of the transcriptome. Here we demonstrate that the function of Synaptic GTPase-Activating Protein (SynGAP), a key synaptic protein, is determined by the combination of its amino-terminal sequence with its carboxy-terminal sequence. 5' rapid amplification of cDNA ends and primer extension show that different N-terminal protein sequences arise through alternative promoter usage that are regulated by synaptic activity and postnatal age. Heterogeneity in C-terminal protein sequence arises through alternative splicing. Overexpression of SynGAP α1 versus α2 C-termini-containing proteins in hippocampal neurons has opposing effects on synaptic strength, decreasing and increasing miniature excitatory synaptic currents amplitude/frequency, respectively. The magnitude of this C-terminal-dependent effect is modulated by the N-terminal peptide sequence. This is the first demonstration that activity-dependent alternative promoter usage can change the function of a synaptic protein at excitatory synapses. Furthermore, the direction and degree of synaptic modulation exerted by different protein isoforms from a single gene locus is dependent on the combination of differential promoter usage and alternative splicing.

Active dendrites: Adaptation to spike-based communication

Computational analyses of dendritic computations often assume stationary inputs to neurons, ignoring the pulsatile nature of spike-based communication between neurons and the moment-to-moment fluctuations caused by such spiking inputs. Conversely, circuit computations with spiking neurons are usually formalized without regard to the rich nonlinear nature of dendritic processing. Here we address the computational challenge faced by neurons that compute and represent analogue quantities but communicate with digital spikes, and show that reliable computation of even purely linear functions of inputs can require the interplay of strongly nonlinear subunits within the postsynaptic dendritic tree.Our theory predicts a matching of dendritic nonlinearities and synaptic weight distributions to the joint statistics of presynaptic inputs. This approach suggests normative roles for some puzzling forms of nonlinear dendritic dynamics and plasticity.

Modeling fatigue crack growth in crystalline solids with discrete dislocation plasticity

Analyses of crack growth under cyclic loading conditions are discussed where plastic flow arises from the motion of large numbers of discrete dislocations and the fracture properties are embedded in a cohesive surface constitutive relation. The formulation is the same as used to analyse crack growth under monotonic loading conditions, differing only in the remote loading being a cyclic function of time. Fatigue, i.e. crack growth in cyclic loading at a driving force for which the crack would have arrested under monotonic loading, emerges in the simulations as a consequence of the evolution of internal stresses associated with the irreversibility of the dislocation motion. A fatigue threshold, Paris law behaviour, striations, the accelerated growth of short cracks and the scaling with material properties are outcomes of the calculations. Results for single crystals and polycrystals will be discussed.

Slowness: an objective for spike-timing-dependent plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.

Plane-strain discrete dislocation plasticity with climb-assisted glide motion of dislocations

A small-strain two-dimensional discrete dislocation plasticity (DDP) framework is developed wherein dislocation motion is caused by climb-assisted glide. The climb motion of the dislocations is assumed to be governed by a drag-type relation similar to the glide-only motion of dislocations: such a relation is valid when vacancy kinetics is either diffusion limited or sink limited. The DDP framework is employed to predict the effect of dislocation climb on the uniaxial tensile and pure bending response of single crystals. Under uniaxial tensile loading conditions, the ability of dislocations to bypass obstacles by climb results in a reduced dislocation density over a wide range of specimen sizes in the climb-assisted glide case compared to when dislocation motion is only by glide. A consequence is that, at least in a single slip situation, size effects due to dislocation starvation are reduced. By contrast, under pure bending loading conditions, the dislocation density is unaffected by dislocation climb as geometrically necessary dislocations (GNDs) dominate. However, climb enables the dislocations to arrange themselves into lower energy configurations which significantly reduces the predicted bending size effect as well as the amount of reverse plasticity observed during unloading. The results indicate that the intrinsic plasticity material length scale associated with GNDs is strongly affected by thermally activated processes and will be a function of temperature. © 2013 IOP Publishing Ltd.