Long-term depression of excitatory synaptic transmission and its relationship to long-term potentiation

Critical involvement of postsynaptic protein kinase activation in long-term potentiation at hippocampal mossy fiber synapses on CA3 interneurons

Hippocampal mossy fiber (MF) synapses on area CA3 lacunosum-moleculare (L-M) interneurons are capable of undergoing a Hebbian form of NMDA receptor (NMDAR)-independent long-term potentiation (LTP) induced by the same type of high-frequency stimulation (HFS) that induces LTP at MF synapses on pyramidal cells. LTP of MF input to L-M interneurons occurs only at synapses containing mostly calcium-impermeable (CI)-AMPA receptors (AMPARs). Here, we demonstrate that HFS-induced LTP at these MF-interneuron synapses requires postsynaptic activation of protein kinase A (PKA) and protein kinase C (PKC). Brief extracellular stimulation of PKA with forskolin (FSK) alone or in combination with 1-Methyl-3-isobutylxanthine (IBMX) induced a long-lasting synaptic enhancement at MF synapses predominantly containing CI-AMPARs. However, the FSK/IBMX-induced potentiation in cells loaded with the specific PKA inhibitor peptide PKI(6-22) failed to be maintained. Consistent with these data, delivery of HFS to MFs synapsing onto L-M interneurons loaded with PKI(6-22) induced posttetanic potentiation (PTP) but not LTP. Hippocampal sections stained for the catalytic subunit of PKA revealed abundant immunoreactivity in interneurons located in strata radiatum and L-M of area CA3. We also found that extracellular activation of PKC with phorbol 12,13-diacetate induced a pharmacological potentiation of the isolated CI-AMPAR component of the MF EPSP. However, HFS delivered to MF synapses on cells loaded with the PKC inhibitor chelerythrine exhibited PTP followed by a significant depression. Together, our data indicate that MF LTP in L-M interneurons at synapses containing primarily CI-AMPARs requires some of the same signaling cascades as does LTP of glutamatergic input to CA3 or CA1 pyramidal cells.

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.

Differential induction of bidirectional long-term changes in neurotransmitter release by frequency-coded patterns at the cerebellar input

Sensory stimulation conveys spike discharges of variable frequency and duration along the mossy fibres of cerebellum raising the question of whether and how these patterns determine plastic changes at the mossy fibre-granule cell synapse. Although various combinations of high-frequency bursts and membrane depolarization can induce NMDA receptor-dependent long-term depression (LTD) and long-term potentiation (LTP), the effect of different discharge frequencies remained unknown. Here we show that low-frequency mossy fibre stimulation (100 impulses1 Hz) induces mGlu receptor-dependent LTD. For various burst frequencies, the plasticity-[Ca(2+)](i) relationship was U-shaped resembling the Bienenstok-Cooper-Munro (BCM) learning rule. Moreover, LTD expression was associated with increased paired-pulse ratio, coefficient of variation and failure rate, and with a decrease in release probability, therefore showing changes opposite to those characterizing LTP. The plasticity-[Ca(2+)](i) relationship and the changes in neurotransmitter release measured by varying induction frequencies were indistinguishable from those obtained by varying high-frequency burst duration. These results suggest that different glutamate receptors converge onto a final common mechanism translating the frequency and duration of mossy fibre discharges into a regulation of the LTP/LTD balance, which may play an important role in adapting spatio-temporal signal transformations at the cerebellar input stage.

Bidirectional synaptic plasticity in response to single or paired pulse activation of NMDA receptors

It is still incompletely known how NMDA receptors (NMDA-R) regulate bidirectional synaptic plasticity. We examined this issue by an experimental protocol in which paired pulse stimulation (PPS) with 50ms interstimulus interval and basal frequency of 0.1Hz was applied to CA1 area of rat hippocampal slices during low Mg(2+) perfusion. Under blockade of NMDA-Rs by AP5, PPS for 12-60min led to only a minor depression. In contrast, when PPS was applied in the absence of AP5, there was a prominent short-term potentiation (STP), mainly of AMPA-R mediated responses, with peak at 1min and lasting 10-15min. The STP was followed by a slowly developing long-term depression (LTD). Applying AP5 during the STP, converted it to a stable increase relative to the control pathway. Following peak STP, plasticity was controlled in a composite manner. Whereas the initial decay was counteracted by NMDA-R activation, the following LTD was dependent on such activation. Our data suggest that synaptic changes do not only depend on the instantaneous, NMDA-dependent Ca(2+) concentration in the dendritic spine, but are also influenced by prior induction events. In addition to NMDA-R driven processes, passive relaxation contributes to the synaptic plasticity and in some cases outbalances the active control.

Not the module does memory make – but the network

This commentary questions the target articles inferences from a limited set of empirical data to support this model and conceptual scheme. Especially questionable is the attribution of internal representation properties to an assembly of cells in a discrete cortical module firing at a discrete attractor frequency. Alternative inferences are drawn from cortical cooling and cell-firing data that point to the internal representation as a broad and specific cortical network defined by cortico-cortical connectivity. Active memory, it is proposed, consists in the sustained activation of the component neuron populations of the network.

Distributed cell assemblies and detailed cell models

Hebbian cell-assembly theory and attractor networks are good starting points for modeling cortical processing. Detailed cell models can be useful in understanding the dynamics of attractor networks. Cell assemblies are likely to be distributed, with the cortical column as the local processing unit. Synaptic memory may be dominant in all but the first couple of seconds.

Another ANN model for the Miyashita experiments

The Miyashita experiments are very interesting and the results should be examined from a viewpoint of attractor dynamics. Amit's target article shows a path toward realistic modeling by artificial neural networks (ANN), but it is not necessarily the only one. I introduce another model that can explain a substantial part of the empirical observations and makes an interesting prediction. This model consists of such units that have nonmonotonic input-output characteristics with local inhibition neurons.

The Hebbian paradigm reintegrated: Local reverberations as internal representations

Recurrent excitation is experimentally well documented in cortical populations. It provides for intracortical excitatory biases that linearize negative feedback interactions and induce macroscopic state transitions during perception. The concept of the local neighborhood should be expanded to spatial patterns as the basis for perception, in which large areas of cortex are bound into cooperative behavior with near-silent columns as important as active columns revealed by unit recording.

Where the adventure is

Interpreting the Miyashita et al. experiments in terms of a cellassembly representation does not adequately explain the performance of Miyashita's monkeys on novel stimuli. We will argue that the latter observations point to acompositionalrepresentation and suggest a dynamics involving rapid and reversible binding of distinct activity patterns.

Reverberation reconsidered: On the path to cognitive theory

Amit's work addresses a critical issue in cognitive science: the structure of neural representations. The use of Hebbian cell assemblies is a positive step, and we now need to consider its role in a larger cognitive theory. When considering the dynamics of a system built out of attractors, a more limited version of reverberation becomes necessary.

Reverberations of Hebbian thinking

Cortical reverberations may induce synaptic changes that underlie developmental plasticity as well as long-term memory. They may be especially important for the consolidation of synaptic changes. Reverberations in cortical networks should have particular significance during development, when large numbers of new representations are formed. This includes the formation of representations across different sensory modalities.

How do local reverberations achieve global integration?

Amit's Hebbian model risks being overexplanatory, since it does not depend on specific physiological modelling of cortical ANNs, but concentrates on those phenomena which are modelled by a large class of ANNs. While offering a strong demonstration of the presence of Hebb's “cell assemblies,” it does not offer an equal account of Hebb's “phase sequence” concept.

Mathematics of Hebbian attractors

The concept of an attractor in a mathematical dynamical system is reviewed. Emphasis is placed on the distinction between a cell assembly, the corresponding attractor, and the attractor dynamics. The biological significance of these entities is discussed, especially the question of whether the representation of the stimulus requires the full attractor dynamics, or merely the cell assembly as a set of reverberating neurons. Comparison is made to Freeman's study of dynamic patterns in olfaction.

What's in a cell assembly?

The cell assembly as a simple attractor cannot explain many cognitive phenomena. It must be a highly structured network that can sustain highly structured excitation patterns. Moreover, a cell assembly must be more widely distributed in space than on a square millimeter.

The Hebbian paradigm reintegrated: Local reverberations as internal representations

The neurophysiological evidence from the Miyashita group's experiments on monkeys as well as cognitive experience common to us all suggests that local neuronal spike rate distributions might persist in the absence of their eliciting stimulus. In Hebb's cell-assembly theory, learning dynamics stabilize such self-maintaining reverberations. Quasi-quantitive modeling of the experimental data on internal representations in association-cortex modules identifies the reverberations (delay spike activity) as the internal code (representation). This leads to cognitive and neurophysiological predictions, many following directly from the language used to describe the activity in the experimental delay period, others from the details of how the model captures the properties of the internal representations.

Additional tests of Amit's attractor neural networks

Further tests of Amit's model are indicated. One strategy is to use the apparent coding sparseness of the model to make predictions about coding sparseness in Miyashita's network. A second approach is to use memory overload to induce false positive responses in modules and biological systems. In closing, the importance of temporal coding and timing requirements in developing biologically plausible attractor networks is mentioned.

Experience-driven formation of parts-based representations in a model of layered visual memory

Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces.

Synaptic plasticity in the subiculum

The subiculum is the principal target of CA1 pyramidal cells. It functions as a mediator of hippocampal-cortical interaction and has been proposed to play an important role in the encoding and retrieval of long-term memory. The cellular mechanisms of memory formation are thought to include long-term potentiation (LTP) and depression (LTD) of synaptic strength. This review summarizes the contemporary knowledge of LTP and LTD at CA1-subiculum synapses. The observation that the underlying mechanisms of LTP and LTD at CA1-subiculum synapses correlate with the discharge properties of subicular pyramidal cell reveals a novel and intriguing mechanism of cell-specific consolidation of hippocampal output.

Gain in sensitivity and loss in temporal contrast of STDP by dopaminergic modulation at hippocampal synapses

Spike-timing-dependent plasticity (STDP) is considered a physiologically relevant form of Hebbian learning. However, behavioral learning often involves action of reinforcement or reward signals such as dopamine. Here, we examined how dopamine influences the quantitative rule of STDP at glutamatergic synapses of hippocampal neurons. The presence of 20 muM dopamine during paired pre- and postsynaptic spiking activity expanded the effective time window for timing-dependent long-term potentiation (t-LTP) to at least -45 ms, and allowed normally ineffective weak stimuli with fewer spike pairs to induce significant t-LTP. Meanwhile, dopamine did not affect the degree of t-LTP induced by normal strong stimuli with spike timing (ST) of +10 ms. Such dopamine-dependent enhancement in the sensitivity of t-LTP was completely blocked by the D1-like dopamine receptor antagonist SCH23390, but not by the D2-like dopamine receptor antagonist sulpiride. Surprisingly, timing-dependent long-term depression (t-LTD) at negative ST was converted into t-LTP by dopamine treatment; this conversion was also blocked by SCH23390. In addition, t-LTP in the presence of dopamine was completely blocked by the NMDA receptor antagonist 2-amino-5-phosphonovaleric acid, indicating that D1-like receptor-mediated modulation appears to act through the classical NMDA receptor-mediated signaling pathway that underlies STDP. These results provide a quantitative and mechanistic basis for a previously undescribed learning rule that depends on pre- and postsynaptic ST, as well as the global reward signal.

A novel mechanism of hippocampal LTD involving muscarinic receptor-triggered interactions between AMPARs, GRIP and liprin-alpha

BACKGROUND

Long-term depression (LTD) in the hippocampus can be induced by activation of different types of G-protein coupled receptors, in particular metabotropic glutamate receptors (mGluRs) and muscarinic acetylcholine receptors (mAChRs). Since mGluRs and mAChRs activate the same G-proteins and isoforms of phospholipase C (PLC), it would be expected that these two forms of LTD utilise the same molecular mechanisms. However, we find a distinct mechanism of LTD involving GRIP and liprin-alpha.

RESULTS

Whilst both forms of LTD require activation of tyrosine phosphatases and involve internalisation of AMPARs, they use different molecular interactions. Specifically, mAChR-LTD, but not mGluR-LTD, is blocked by peptides that inhibit the binding of GRIP to the AMPA receptor subunit GluA2 and the binding of GRIP to liprin-alpha. Thus, different receptors that utilise the same G-proteins can regulate AMPAR trafficking and synaptic efficacy via distinct molecular mechanisms.

CONCLUSION

Our results suggest that mAChR-LTD selectively involves interactions between GRIP and liprin-alpha. These data indicate a novel mechanism of synaptic plasticity in which activation of M1 receptors results in AMPAR endocytosis, via a mechanism involving interactions between GluA2, GRIP and liprin-alpha.

Recruitment and Consolidation of Cell Assemblies for Words by Way of Hebbian Learning and Competition in a Multi-Layer Neural Network

Current cognitive theories postulate either localist representations of knowledge or fully overlapping, distributed ones. We use a connectionist model that closely replicates known anatomical properties of the cerebral cortex and neurophysiological principles to show that Hebbian learning in a multi-layer neural network leads to memory traces (cell assemblies) that are both distributed and anatomically distinct. Taking the example of word learning based on action-perception correlation, we document mechanisms underlying the emergence of these assemblies, especially (i) the recruitment of neurons and consolidation of connections defining the kernel of the assembly along with (ii) the pruning of the cell assembly's halo (consisting of very weakly connected cells). We found that, whereas a learning rule mapping covariance led to significant overlap and merging of assemblies, a neurobiologically grounded synaptic plasticity rule with fixed LTP/LTD thresholds produced minimal overlap and prevented merging, exhibiting competitive learning behaviour. Our results are discussed in light of current theories of language and memory. As simulations with neurobiologically realistic neural networks demonstrate here spontaneous emergence of lexical representations that are both cortically dispersed and anatomically distinct, both localist and distributed cognitive accounts receive partial support.

Sleeping our way to weight normalization and stable learning

The functions of sleep have been an enduring mystery. Tononi and Cirelli (2003) hypothesized that one of the functions of slow-wave sleep is to scale down synapses in the cortex that have strengthened during awake learning. We create a computational model to test the functionality of this idea and examine some of its implications. We show that synaptic scaling during slow-wave sleep is capable of keeping Hebbian learning in check and that it enables stable development. We also show theoretically how it implements classical weight normalization, which has been in common use in neural models for decades. Finally, a significant computational limitation of this form of synaptic scaling is revealed through computer simulations.

Bidirectional Hebbian plasticity at hippocampal mossy fiber synapses on CA3 interneurons

Hippocampal area CA3 is critically involved in the formation of nonoverlapping neuronal subpopulations ("pattern separation") to store memory representations as distinct events. Efficient pattern separation relies on the strong and sparse excitatory input from the mossy fibers (MFs) to pyramidal cells and feedforward inhibitory interneurons. However, MF synapses on CA3 pyramidal cells undergo long-term potentiation (LTP), which, if unopposed, will degrade pattern separation because MF activation will now recruit additional CA3 pyramidal cells. Here, we demonstrate MF LTP in stratum lacunosum-moleculare (L-M) interneurons induced by the same stimulation protocol that induces MF LTP in pyramidal cells. This LTP was NMDA receptor (NMDAR) independent and occurred at MF Ca(2+)-impermeable AMPA receptor synapses. LTP was prevented by with voltage clamping the postsynaptic cell soma during high-frequency stimulation (HFS), intracellular injections of the Ca(2+) chelator BAPTA (20 mm), or bath applications of the L-type Ca(2+) channel blocker nimodipine (10 microm). We propose that MF LTP in L-M interneurons preserves the sparsity of pyramidal cell activation, thus allowing CA3 to maintain its role in pattern separation. In the presence of the mGluR1alpha antagonist LY367385 [(S)-(+)-a-amino-4-carboxy-2-methylbenzeneacetic acid] (100 microm), the same HFS that induces MF LTP in naive slices triggered NMDAR-independent MF LTD. This LTD, like LTP, required activation of the L-type Ca(2+) channel and also was induced after blockade of IP(3) receptors with heparin (4 mg/ml) or the selective depletion of receptor-gated Ca(2+) stores with ryanodine (10 or 100 microm). We conclude that L-M interneurons are endowed with Ca(2+) signaling cascades suitable for controlling the polarity of MF long-term plasticity induced by joint presynaptic and postsynaptic activities.

Amyloid beta-protein fragments 25-35 and 31-35 potentiate long-term depression in hippocampal CA1 region of rats in vivo

Amyloid beta-protein (Abeta) is thought to be responsible for the deficit of learning and memory in Alzheimer's disease (AD), possibly through interfering with synaptic plasticity in the brain. It has been reported that Abeta fragments suppress the long-term potentiation (LTP) of synaptic transmission. However, it is unclear whether Abeta fragments can regulate long-term depression (LTD), an equally important form of synaptic plasticity in the brain. The present study investigates the effects of Abeta fragments on LTD induced by low frequency stimulation (LFS) in the hippocampus in vivo. Our results showed that (1) prolonged 1-10 Hz of LFS all effectively elicited LTD, which could persist for at least 2 h and be reversed by high frequency stimulation (HFS); (2) the effectiveness of LTD induction depended mainly on the number of pulses but not the frequency of LFS; (3) pretreatment with Abeta fragment 25-35 (Abeta(25-35), 12.5 and 25 nmol) did not change baseline field excitatory postsynaptic potentials but dose-dependently potentiated LTD; (4) Abeta fragment 31-35 (Abeta(31-35)), a shorter Abeta fragment than Abeta(25-35), also dose-dependently strengthened LFS-induced hippocampal LTD. Thus, the present study demonstrates the enhancement of hippocampal LTD by Abeta in in vivo condition. We propose that Abeta-induced potentiation of LTD, together with the suppression of LTP, will result in the impairment of cognitive function of the brain.

Metabotropic glutamate receptor-mediated LTD involves two interacting Ca(2+) sensors, NCS-1 and PICK1

There are two major forms of long-term depression (LTD) of synaptic transmission in the central nervous system that require activation of either N-methyl-D-aspartate receptors (NMDARs) or metabotropic glutamate receptors (mGluRs). In synapses in the perirhinal cortex, we have directly compared the Ca(2+) signaling mechanisms involved in NMDAR-LTD and mGluR-LTD. While both forms of LTD involve Ca(2+) release from intracellular stores, the Ca(2+) sensors involved are different; NMDAR-LTD involves calmodulin, while mGluR-LTD involves the neuronal Ca(2+) sensor (NCS) protein NCS-1. In addition, there is a specific requirement for IP3 and PKC, as well as protein interacting with C kinase (PICK-1) in mGluR-LTD. NCS-1 binds directly to PICK1 via its BAR domain in a Ca(2+)-dependent manner. Furthermore, the NCS-1-PICK1 association is stimulated by activation of mGluRs, but not NMDARs, and introduction of a PICK1 BAR domain fusion protein specifically blocks mGluR-LTD. Thus, NCS-1 plays a distinct role in mGluR-LTD.

Mechanisms and applications of theta-burst rTMS on the human motor cortex

Theta-burst Stimulation (TBS) is a novel form of repetitive transcranial magnetic stimulation (rTMS). Applied over the primary motor cortex it has been successfully used to induce changes in cortical excitability. The advantage of this stimulation paradigm is that it is able to induce strong and long lasting effects using a lower stimulation intensity and a shorter time of stimulation compared to conventional rTMS protocols. Since its first description, TBS has been used in both basic and clinical research in the last years and more recently it has been expanded to other domains than the motor system. Its capacity to induce synaptic plasticity could lead to therapeutic implications for neuropsychiatric disorders. The neurobiological mechanisms of TBS are not fully understood at present; they may involve long-term potentiation (LTP)- and depression (LTD)-like processes, as well as inhibitory mechanisms modulated by GABAergic activity. This article highlights current hypotheses regarding the mechanisms of action of TBS and some central factors which may influence cortical responses to TBS. Furthermore, previous and ongoing research performed in the field of TBS on the motor cortex is summarized.

Neurophysiological mechanisms of electroconvulsive therapy for depression

The neurobiological foundation of electroconvulsive therapy (ECT) remains fragile. How ECT affects neural activities in the brain of depressives is largely unknown. There has been accumulating knowledge on genes and molecules induced by the animal model of ECT. Exact functions of those molecules in the context of mood disorder remain unknown. Among the dozens of molecules highly expressed by ECT, one that shows an especially prominent induction (>6-fold) is Homer 1a, a member of the intracellular scaffold protein family Homer. We have examined effects of Homer 1a in ECT-subjected cortical pyramidal cells, on the basis of which two neurobiological consequences of ECT are proposed. First, Homer 1a either injected intracellularly or induced by ECT was shown to reduce neuronal excitability. This agrees with diverse lines of mutually consistent clinical investigations, which unanimously point to an enhanced excitability in the cerebral cortex of depressive patients. The GABAergic dysfunction hypothesis of depression was thus revitalized. Second, again by relying on Homer 1a, we have proposed a molecular mechanism by which ECT affects a form of long-term depression (LTD). The possibility is discussed that clinical effects of ECT are exerted at least partly by reducing neural excitability and modifying synaptic plasticity.

Tag-trigger-consolidation: a model of early and late long-term-potentiation and depression

Changes in synaptic efficacies need to be long-lasting in order to serve as a substrate for memory. Experimentally, synaptic plasticity exhibits phases covering the induction of long-term potentiation and depression (LTP/LTD) during the early phase of synaptic plasticity, the setting of synaptic tags, a trigger process for protein synthesis, and a slow transition leading to synaptic consolidation during the late phase of synaptic plasticity. We present a mathematical model that describes these different phases of synaptic plasticity. The model explains a large body of experimental data on synaptic tagging and capture, cross-tagging, and the late phases of LTP and LTD. Moreover, the model accounts for the dependence of LTP and LTD induction on voltage and presynaptic stimulation frequency. The stabilization of potentiated synapses during the transition from early to late LTP occurs by protein synthesis dynamics that are shared by groups of synapses. The functional consequence of this shared process is that previously stabilized patterns of strong or weak synapses onto the same postsynaptic neuron are well protected against later changes induced by LTP/LTD protocols at individual synapses.

Strength through diversity

The remarkable versatility of the mammalian brain is made possible by a huge diversity of cellular plasticity mechanisms. These include long-term potentiation and depression at both excitatory and inhibitory synapses, as well as a variety of intrinsic and homeostatic plasticity mechanisms. A fundamental challenge for the field is to assemble our detailed knowledge of these specific mechanisms into a coherent picture of how plasticity within cortical circuits works to tune network properties.

Insulin resistance and amyloidogenesis as common molecular foundation for type 2 diabetes and Alzheimer's disease

Characterized as a peripheral metabolic disorder and a degenerative disease of the central nervous system respectively, it is now widely recognized that type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) share several common abnormalities including impaired glucose metabolism, increased oxidative stress, insulin resistance and amyloidogenesis. Several recent studies suggest that this is not an epiphenomenon, but rather these two diseases disrupt common molecular pathways and each disease compounds the progression of the other. For instance, in AD the accumulation of the amyloid-beta peptide (Abeta), which characterizes the disease and is thought to participate in the neurodegenerative process, may also induce neuronal insulin resistance. Conversely, disrupting normal glucose metabolism in transgenic animal models of AD that over-express the human amyloid precursor protein (hAPP) promotes amyloid-peptide aggregation and accelerates the disease progression. Studying these processes at a cellular level suggests that insulin resistance and Abeta aggregation may not only be the consequence of excitotoxicity, aberrant Ca(2+) signals, and proinflammatory cytokines such as TNF-alpha, but may also promote these pathological effectors. At the molecular level, insulin resistance and Abeta disrupt common signal transduction cascades including the insulin receptor family/PI3 kinase/Akt/GSK3 pathway. Thus both disease processes contribute to overlapping pathology, thereby compounding disease symptoms and progression.

A positive feedback signal transduction loop determines timing of cerebellar long-term depression

Synaptic activity produces short-lived second messengers that ultimately yield a long-term depression (LTD) of cerebellar Purkinje cells. Here, we test the hypothesis that these brief second messenger signals are translated into long-lasting biochemical signals by a positive feedback loop that includes protein kinase C (PKC) and mitogen-activated protein kinase. Histochemical "epistasis" experiments demonstrate the reciprocal activation of these kinases, and physiological experiments--including the use of a light-activated protein kinase--demonstrate that such reciprocal activation is required for LTD. Timed application of enzyme inhibitors reveals that this positive feedback loop causes PKC to be active for more than 20 min, allowing sufficient time for LTD expression. Such regenerative mechanisms may sustain other long-lasting forms of synaptic plasticity and could be a general mechanism for prolonging signal transduction networks.

Spike timing-dependent plasticity: a Hebbian learning rule

Spike timing-dependent plasticity (STDP) as a Hebbian synaptic learning rule has been demonstrated in various neural circuits over a wide spectrum of species, from insects to humans. The dependence of synaptic modification on the order of pre- and postsynaptic spiking within a critical window of tens of milliseconds has profound functional implications. Over the past decade, significant progress has been made in understanding the cellular mechanisms of STDP at both excitatory and inhibitory synapses and of the associated changes in neuronal excitability and synaptic integration. Beyond the basic asymmetric window, recent studies have also revealed several layers of complexity in STDP, including its dependence on dendritic location, the nonlinear integration of synaptic modification induced by complex spike trains, and the modulation of STDP by inhibitory and neuromodulatory inputs. Finally, the functional consequences of STDP have been examined directly in an increasing number of neural circuits in vivo.

The effects of cholinergic neuromodulation on neuronal phase-response curves of modeled cortical neurons

The response of an oscillator to perturbations is described by its phase-response curve (PRC), which is related to the type of bifurcation leading from rest to tonic spiking. In a recent experimental study, we have shown that the type of PRC in cortical pyramidal neurons can be switched by cholinergic neuromodulation from type II (biphasic) to type I (monophasic). We explored how intrinsic mechanisms affected by acetylcholine influence the PRC using three different types of neuronal models: a theta neuron, single-compartment neurons and a multi-compartment neuron. In all of these models a decrease in the amount of a spike-frequency adaptation current was a necessary and sufficient condition for the shape of the PRC to change from biphasic (type II) to purely positive (type I).

Dendritic excitability and synaptic plasticity

Most synaptic inputs are made onto the dendritic tree. Recent work has shown that dendrites play an active role in transforming synaptic input into neuronal output and in defining the relationships between active synapses. In this review, we discuss how these dendritic properties influence the rules governing the induction of synaptic plasticity. We argue that the location of synapses in the dendritic tree, and the type of dendritic excitability associated with each synapse, play decisive roles in determining the plastic properties of that synapse. Furthermore, since the electrical properties of the dendritic tree are not static, but can be altered by neuromodulators and by synaptic activity itself, we discuss how learning rules may be dynamically shaped by tuning dendritic function. We conclude by describing how this reciprocal relationship between plasticity of dendritic excitability and synaptic plasticity has changed our view of information processing and memory storage in neuronal networks.

Aphasia therapy on a neuroscience basis

BACKGROUND: Brain research has documented that the cortical mechanisms for language and action are tightly interwoven and, concurrently, new approaches to language therapy in neurological patients are being developed that implement language training in the context of relevant linguistic and non-linguistic actions, therefore taking advantage of the mutual connections of language and action systems in the brain. A further well-known neuroscience principle is that learning at the neuronal level is driven by correlation; consequently, new approaches to language therapy emphasise massed practice in a short time, thus maximising therapy quantity and frequency and, therefore, correlation at the behavioural and neuronal levels. Learned non-use of unsuccessful actions plays a major role in the chronification of neurological deficits, and behavioural approaches to therapy have therefore employed shaping and other learning techniques to counteract such non-use. AIMS: Advances in theoretical and experimental neuroscience have important implications for clinical practice. We exemplify this in the domain of aphasia rehabilitation. MAIN CONTRIBUTION: Whereas classical wisdom had been that aphasia cannot be significantly improved at a chronic stage, we here review evidence that one type of intensive language-action therapy (ILAT)-constraint-induced aphasia therapy-led to significant improvement of language performance in patients with chronic aphasia. We discuss perspectives for further improving speech-language therapy, including drug treatment that may be particularly fruitful when applied in conjunction with behavioural treatment. In a final section we highlight intensive and rapid therapy studies in chronic aphasia as a unique tool for exploring the cortical reorganisation of language. CONCLUSIONS: We conclude that intensive language action therapy is an efficient tool for improving language functions even at chronic stages of aphasia. Therapy studies using this technique can open new perspectives for research into the plasticity of human language circuits.

Phenomenological models of synaptic plasticity based on spike timing

Synaptic plasticity is considered to be the biological substrate of learning and memory. In this document we review phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP). The aim of the document is to provide a framework for classifying and evaluating different models of plasticity. We focus on phenomenological synaptic models that are compatible with integrate-and-fire type neuron models where each neuron is described by a small number of variables. This implies that synaptic update rules for short-term or long-term plasticity can only depend on spike timing and, potentially, on membrane potential, as well as on the value of the synaptic weight, or on low-pass filtered (temporally averaged) versions of the above variables. We examine the ability of the models to account for experimental data and to fulfill expectations derived from theoretical considerations. We further discuss their relations to teacher-based rules (supervised learning) and reward-based rules (reinforcement learning). All models discussed in this paper are suitable for large-scale network simulations.

State-dependent bidirectional modification of somatic inhibition in neocortical pyramidal cells

Cortical pyramidal neurons alter their responses to input signals depending on behavioral state. We investigated whether changes in somatic inhibition contribute to these alterations. In layer 5 pyramidal neurons of rat visual cortex, repetitive firing from a depolarized membrane potential, which typically occurs during arousal, produced long-lasting depression of somatic inhibition. In contrast, slow membrane oscillations with firing in the depolarized phase, which typically occurs during slow-wave sleep, produced long-lasting potentiation. The depression is mediated by L-type Ca2+ channels and GABA(A) receptor endocytosis, whereas potentiation is mediated by R-type Ca2+ channels and receptor exocytosis. It is likely that the direction of modification is mainly dependent on the ratio of R- and L-type Ca2+ channel activation. Furthermore, somatic inhibition was stronger in slices prepared from rats during slow-wave sleep than arousal. This bidirectional modification of somatic inhibition may alter pyramidal neuron responsiveness in accordance with behavioral state.

A neuroanatomically grounded Hebbian-learning model of attention-language interactions in the human brain

Meaningful familiar stimuli and senseless unknown materials lead to different patterns of brain activation. A late major neurophysiological response indexing ‘sense’ is the negative component of event-related potential peaking at around 400 ms (N400), an event-related potential that emerges in attention-demanding tasks and is larger for senseless materials (e.g. meaningless pseudowords) than for matched meaningful stimuli (words). However, the mismatch negativity (latency 100–250 ms), an early automatic brain response elicited under distraction, is larger to words than to pseudowords, thus exhibiting the opposite pattern to that seen for the N400. So far, no theoretical account has been able to reconcile and explain these findings by means of a single, mechanistic neural model. We implemented a neuroanatomically grounded neural network model of the left perisylvian language cortex and simulated: (i) brain processes of early language acquisition and (ii) cortical responses to familiar word and senseless pseudoword stimuli. We found that variation of the area-specific inhibition (the model correlate of attention) modulated the simulated brain response to words and pseudowords, producing either an N400- or a mismatch negativity-like response depending on the amount of inhibition (i.e. available attentional resources). Our model: (i) provides a unifying explanatory account, at cortical level, of experimental observations that, so far, had not been given a coherent interpretation within a single framework; (ii) demonstrates the viability of purely Hebbian, associative learning in a multilayered neural network architecture; and (iii) makes clear predictions on the effects of attention on latency and magnitude of event-related potentials to lexical items. Such predictions have been confirmed by recent experimental evidence.

Target-cell-specific bidirectional synaptic plasticity at hippocampal output synapses

It is commonly accepted that the hippocampus is critically involved in the explicit memory formation of mammals. The subiculum is the principal target of CA1 pyramidal cells and thus serves as the major relay station for the outgoing hippocampal information. Pyramidal cells in the subiculum can be classified according to their firing properties into burst-spiking and regular-spiking cells. In the present study we demonstrate that burst-spiking and regular-spiking cells show fundamentally different forms of low frequency-induced synaptic plasticity in rats. In burst-spiking cells, low-frequency stimulation (at 0.5-5 Hz) induces frequency-dependent long-term depression (LTD) with a maximum at 1 Hz. This LTD is dependent on the activation of NMDAR and masks an mGluR-dependent long-term potentiation (LTP). In contrast, in regular-spiking cells low-frequency stimulation induces an mGluR-dependent LTP that masks an NMDAR-dependent LTD. Both processes depend on postsynaptic Ca(2+)-signaling as BAPTA prevents the induction of synaptic plasticity in both cell types. Thus, mGluR-dependent LTP and NMDAR-dependent LTD occur simultaneously at CA1-subiculum synapses and the predominant direction of synaptic plasticity relies on the cell type investigated. Our data indicate a novel mechanism for the sliding-threshold model of synaptic plasticity, in which induction of LTP and LTD seems to be driven by the relative activation state of NMDAR and mGluR. Our observation that the direction of synaptic plasticity correlates with the discharge properties of the postsynaptic cell reveals a novel and intriguing mechanism of target specificity that may serve in tuning the significance of neuronal information by trafficking hippocampal output onto either subicular burst-spiking or regular-spiking cells.

Group S8A serine proteases, including a novel enzyme cadeprin, induce long-lasting, metabotropic glutamate receptor-dependent synaptic depression in rat hippocampal slices

Long-term potentiation and long-term depression (LTD) are forms of synaptic plasticity in the central nervous system. We now report that a group of chymotrypsin-like serine proteases, especially members of the S8A subfamily, induce LTD of evoked potentials in rat hippocampal slices. The proteolytic activity of these enzymes is required for the induction of LTD, as serine protease inhibitors prevent the effect. The depression is partly mediated by the suppression of transmitter release from glutamatergic terminals but also involves an elevation of action potential threshold with no change of post-synaptic membrane potential or input resistance. We have also isolated a novel and more potent related enzyme, cadeprin, from Aspergillus. The LTD produced by all of these proteases is not dependent on receptors for several transmitter systems, including N-methyl-d-aspartate or adenosine receptors, but is prevented by blocking group I metabotropic glutamate receptors. The activity of cadeprin, subtilisin and other S8A serine proteases may shed light on the mechanisms of LTD and a related endogenous molecule could have a physiological or pathological role as a modulator of synaptic plasticity in the mammalian hippocampus.

Differential effects of tactile high- and low-frequency stimulation on tactile discrimination in human subjects

Background

Long-term potentiation (LTP) and long-term depression (LTD) play important roles in mediating activity-dependent changes in synaptic transmission and are believed to be crucial mechanisms underlying learning and cortical plasticity. In human subjects, however, the lack of adequate input stimuli for the induction of LTP and LTD makes it difficult to study directly the impact of such protocols on behavior.

Results

Using tactile high- and low-frequency stimulation protocols in humans, we explored the potential of such protocols for the induction of perceptual changes. We delivered tactile high-frequency and low-frequency stimuli (t-HFS, t-LFS) to skin sites of approximately 50 mm² on the tip of the index finger. As assessed by 2-point discrimination, we demonstrate that 20 minutes of t-HFS improved tactile discrimination, while t-LFS impaired performance. T-HFS-effects were stable for at least 24 hours whereas t-LFS-induced changes recovered faster. While t-HFS changes were spatially very specific with no changes on the neighboring fingers, impaired tactile performance after t-LFS was also observed on the right middle-finger. A central finding was that for both t-LFS and t-HFS perceptual changes were dependent on the size of the stimulated skin area. No changes were observed when the stimulated area was very small (< 1 mm²) indicating special requirements for spatial summation.

Conclusion

Our results demonstrate differential effects of such protocols in a frequency specific manner that might be related to LTP- and LTD-like changes in human subjects.

Tyrosine phosphorylation sites in ephrinB2 are required for hippocampal long-term potentiation but not long-term depression

Long-lasting changes in synaptic function are thought to be the cellular basis for learning and memory and for activity-dependent plasticity during development. Long-term potentiation (LTP) and long-term depression (LTD) are two opposing forms of synaptic plasticity that help fine tune neural connections and possibly serve to store information in the brain. Eph receptor tyrosine kinases and their transmembrane ligands, the ephrinBs, have essential roles in certain forms of synaptic plasticity. At the CA3-CA1 hippocampal synapse, EphB2 and EphA4 receptors are critically involved in long-term plasticity independent of their cytoplasmic domains, suggesting that ephrinBs are the active signaling partners. In cell-based assays, ephrinB reverse signaling was previously shown to involve phosphotyrosine-dependent and postsynaptic density-95/Discs large/zona occludens-1 (PDZ) domain interaction-dependent pathways. Which reverse signaling mode is required at hippocampal synapses is unknown. To address this question, we used knock-in mice expressing mutant isoforms of ephrinB2 that are deficient in specific aspects of reverse signaling. Our analysis revealed that tyrosine phosphorylation sites in ephrinB2 are required to mediate normal hippocampal LTP, but not for LTD. Conversely, ephrinB2 lacking the C-terminal PDZ interaction site, but competent to undergo tyrosine phosphorylation, cannot mediate either form of long-term plasticity. Our results provide the first evidence for phosphotyrosine-dependent ephrinB reverse signaling in a neuronal network and for differential ephrinB2 reverse signaling in two forms of synaptic plasticity.

Simple spontaneously active Hebbian learning model: homeostasis of activity and connectivity, and consequences for learning and epileptogenesis

A spontaneously active neural system that is capable of continual learning should also be capable of homeostasis of both firing rate and connectivity. Experimental evidence suggests that both types of homeostasis exist, and that connectivity is maintained at a state that is optimal for information transmission and storage. This state is referred to as the critical state. We present a simple stochastic computational Hebbian learning model that incorporates both firing rate and critical homeostasis, and we explore its stability and connectivity properties. We also examine the behavior of our model with a simulated seizure and with simulated acute deafferentation. We argue that a neural system that is more highly connected than the critical state (i.e., one that is "supercritical") is epileptogenic. Based on our simulations, we predict that the postseizural and postdeafferentation states should be supercritical and epileptogenic. Furthermore, interventions that boost spontaneous activity should be protective against epileptogenesis.