Long-term relationships between cholinergic tone, synchronous bursting and synaptic remodeling

Learning and memory impairment induced by 1,4-butanediol is regulated by ERK1/2-CREB-BDNF signaling pathways in PC12 cells

1,4-butanediol (1,4-BD) is a known γ-hydroxybutyric acid (GHB) precursor which affects the nervous system after ingestion, leading to uncontrolled behavioral consequences. In the present study, we investigated whether 1,4-BD induces oxidative stress and inflammation in PC12 cells and evaluated the toxic effects of 1,4-BD associates with learning and memory. CCK-8 results revealed a dose-effect relationship between the cell viability of PC12 cells and 1,4-BD when the duration of action was 2 h or 4 h. Assay kits results showed that 1,4-BD decreased the levels of Glutathione (GSH), Glutathione peroxidase (GSH-px), Superoxide dismutase (SOD), Acetylcholine (Ach) and increased the levels of Malondialdehyde (MDA), Nitric oxide (NO) and Acetylcholinesterase (AchE). Elisa kits results indicated that 1,4-BD decreased the levels of synaptophysin I (SYN-1), Postsynaptic density protein-95 (PSD-95), Growth associated protein-43 (GAP-43) and increased the levels of Tumor necrosis factor alpha (TNF-α) and Interleukin- 6 (IL-6). RT-PCR results showed that the mRNA levels of PSD-95, SYN-1 and GAP-43 were significantly decreased. The expression of phosphorylation extracellular signal-regulated protein kinase 1/2 (p-ERK1/2), phosphorylation cAMP response element binding protein (p-CREB) and brain-derived neurotrophic factor (BDNF) proteins were significantly decreased in PC12 cells by protein blotting. Overall, these results suggest that 1,4-BD may affect synaptic plasticity via the ERK1/2-CREB-BDNF pathway, leading to Ach release reduction and ultimately to learning and memory impairment. Furthermore, oxidative stress and inflammation induced by 1,4-BD may also result in learning and memory deficits. These findings will enrich the toxicity data of 1.4-BD associated with learning and memory impairment.

Spontaneous and Perturbational Complexity in Cortical Cultures

Dissociated cortical neurons in vitro display spontaneously synchronized, low-frequency firing patterns, which can resemble the slow wave oscillations characterizing sleep in vivo. Experiments in humans, rodents, and cortical slices have shown that awakening or the administration of activating neuromodulators decrease slow waves, while increasing the spatio-temporal complexity of responses to perturbations. In this study, we attempted to replicate those findings using in vitro cortical cultures coupled with micro-electrode arrays and chemically treated with carbachol (CCh), to modulate sleep-like activity and suppress slow oscillations. We adapted metrics such as neural complexity (NC) and the perturbational complexity index (PCI), typically employed in animal and human brain studies, to quantify complexity in simplified, unstructured networks, both during resting state and in response to electrical stimulation. After CCh administration, we found a decrease in the amplitude of the initial response and a marked enhancement of the complexity during spontaneous activity. Crucially, unlike in cortical slices and intact brains, PCI in cortical cultures displayed only a moderate increase. This dissociation suggests that PCI, a measure of the complexity of causal interactions, requires more than activating neuromodulation and that additional factors, such as an appropriate circuit architecture, may be necessary. Exploring more structured in vitro networks, characterized by the presence of strong lateral connections, recurrent excitation, and feedback loops, may thus help to identify the features that are more relevant to support causal complexity.

Astrocyte GluN2C NMDA receptors control basal synaptic strengths of hippocampal CA1 pyramidal neurons in the stratum radiatum

Experience-dependent plasticity is a key feature of brain synapses for which neuronal N-Methyl-D-Aspartate receptors (NMDARs) play a major role, from developmental circuit refinement to learning and memory. Astrocytes also express NMDARs, although their exact function has remained controversial. Here, we identify in mouse hippocampus, a circuit function for GluN2C NMDAR, a subtype highly expressed in astrocytes, in layer-specific tuning of synaptic strengths in CA1 pyramidal neurons. Interfering with astrocyte NMDAR or GluN2C NMDAR activity reduces the range of presynaptic strength distribution specifically in the stratum radiatum inputs without an appreciable change in the mean presynaptic strength. Mathematical modeling shows that narrowing of the width of presynaptic release probability distribution compromises the expression of long-term synaptic plasticity. Our findings suggest a novel feedback signaling system that uses astrocyte GluN2C NMDARs to adjust basal synaptic weight distribution of Schaffer collateral inputs, which in turn impacts computations performed by the CA1 pyramidal neuron.

Spine dynamics in the brain, mental disorders and artificial neural networks

In the brain, most synapses are formed on minute protrusions known as dendritic spines. Unlike their artificial intelligence counterparts, spines are not merely tuneable memory elements: they also embody algorithms that implement the brain's ability to learn from experience and cope with new challenges. Importantly, they exhibit structural dynamics that depend on activity, excitatory input and inhibitory input (synaptic plasticity or 'extrinsic' dynamics) and dynamics independent of activity ('intrinsic' dynamics), both of which are subject to neuromodulatory influences and reinforcers such as dopamine. Here we succinctly review extrinsic and intrinsic dynamics, compare these with parallels in machine learning where they exist, describe the importance of intrinsic dynamics for memory management and adaptation, and speculate on how disruption of extrinsic and intrinsic dynamics may give rise to mental disorders. Throughout, we also highlight algorithmic features of spine dynamics that may be relevant to future artificial intelligence developments.

Site-specific ubiquitination of pathogenic huntingtin attenuates its deleterious effects

Huntington's disease (HD) is a progressive incurable neurodegenerative disorder characterized by motor and neuropsychiatric symptoms. It is caused by expansion of a cytosine-adenine-guanine triplet in the N-terminal domain of exon 1 in the huntingtin (HTT) gene that codes for an expanded polyglutamine stretch in the protein product which becomes aggregation prone. The mutant Htt (mHtt) aggregates are associated with components of the ubiquitin-proteasome system, suggesting that mHtt is marked for proteasomal degradation and that, for reasons still debated, are not properly degraded. We used a novel HD rat model, proteomic analysis, and long-term live neuronal imaging to characterize the effects of ubiquitination on aggregation of mHtt and subsequent cellular responses. We identified two lysine residues, 6 and 9, in the first exon of mHtt that are specifically ubiquitinated in striatal and cortical brain tissues of mHtt-transgenic animals. Expression of mHtt exon 1 lacking these ubiquitination sites in cortical neurons and cultured cells was found to slow aggregate appearance rates and reduce their size but at the same time increase the number of much smaller and less visible ones. Importantly, expression of this form of mHtt was associated with elevated death rates. Proteomic analysis indicated that cellular reactions to mHtt expression were weaker in cells expressing the lysineless protein, possibly implying a reduced capacity to cope with the proteotoxic stress. Taken together, the findings suggest a novel role for ubiquitination-attenuation of the pathogenic effect of mHtt.

Activity Dependent and Independent Determinants of Synaptic Size Diversity

The extraordinary diversity of excitatory synapse sizes is commonly attributed to activity-dependent processes that drive synaptic growth and diminution. Recent studies also point to activity-independent size fluctuations, possibly driven by innate synaptic molecule dynamics, as important generators of size diversity. To examine the contributions of activity-dependent and independent processes to excitatory synapse size diversity, we studied glutamatergic synapse size dynamics and diversification in cultured rat cortical neurons (both sexes), silenced from plating. We found that in networks with no history of activity whatsoever, synaptic size diversity was no less extensive than that observed in spontaneously active networks. Synapses in silenced networks were larger, size distributions were broader, yet these were rightward-skewed and similar in shape when scaled by mean synaptic size. Silencing reduced the magnitude of size fluctuations and weakened constraints on size distributions, yet these were sufficient to explain synaptic size diversity in silenced networks. Model-based exploration followed by experimental testing indicated that silencing-associated changes in innate molecular dynamics and fluctuation characteristics might negatively impact synaptic persistence, resulting in reduced synaptic numbers. This, in turn, would increase synaptic molecule availability, promote synaptic enlargement, and ultimately alter fluctuation characteristics. These findings suggest that activity-independent size fluctuations are sufficient to fully diversify glutamatergic synaptic sizes, with activity-dependent processes primarily setting the scale rather than the shape of size distributions. Moreover, they point to reciprocal relationships between synaptic size fluctuations, size distributions, and synaptic numbers mediated by the innate dynamics of synaptic molecules as they move in, out, and between synapses.SIGNIFICANCE STATEMENT Sizes of glutamatergic synapses vary tremendously, even when formed on the same neuron. This diversity is commonly thought to reflect the outcome of activity-dependent forms of synaptic plasticity, yet activity-independent processes might also play some part. Here we show that in neurons with no history of activity whatsoever, synaptic sizes are no less diverse. We show that this diversity is the product of activity-independent size fluctuations, which are sufficient to generate a full repertoire of synaptic sizes at correct proportions. By combining modeling and experimentation we expose reciprocal relationships between size fluctuations, synaptic sizes and synaptic counts, and show how these phenomena might be connected through the dynamics of synaptic molecules as they move in, out, and between synapses.

Long-Term Activity Dynamics of Single Neurons and Networks

The firing rate of neuronal spiking in vitro and in vivo significantly varies over extended timescales, characterized by long-memory processes and complex statistics, and appears in spontaneous as well as evoked activity upon repeated stimulus presentation. These variations in response features and their statistics, in face of repeated instances of a given physical input, are ubiquitous in all levels of brain-behavior organization. They are expressed in single neuron and network response variability but even appear in variations of subjective percepts or psychophysical choices and have been described as stemming from history-dependent, stochastic, or rate-determined processes.But what are the sources underlying these temporally rich variations in firing rate? Are they determined by interactions of the nervous system as a whole, or do isolated, single neurons or neuronal networks already express these fluctuations independent of higher levels? These questions motivated the application of a method that allows for controlled and specific long-term activation of a single neuron or neuronal network, isolated from higher levels of cortical organization.This chapter highlights the research done in cultured cortical networks to study (1) the inherent non-stationarity of neuronal network activity, (2) single neuron response fluctuations and underlying processes, and (3) the interface layer between network and single cell, the non-stationary efficacy of the ensemble of synapses impinging onto the observed neuron.

Cooperative stochastic binding and unbinding explain synaptic size dynamics and statistics

Synapses are dynamic molecular assemblies whose sizes fluctuate significantly over time-scales of hours and days. In the current study, we examined the possibility that the spontaneous microscopic dynamics exhibited by synaptic molecules can explain the macroscopic size fluctuations of individual synapses and the statistical properties of synaptic populations. We present a mesoscopic model, which ties the two levels. Its basic premise is that synaptic size fluctuations reflect cooperative assimilation and removal of molecules at a patch of postsynaptic membrane. The introduction of cooperativity to both assimilation and removal in a stochastic biophysical model of these processes, gives rise to features qualitatively similar to those measured experimentally: nanoclusters of synaptic scaffolds, fluctuations in synaptic sizes, skewed, stable size distributions and their scaling in response to perturbations. Our model thus points to the potentially fundamental role of cooperativity in dictating synaptic remodeling dynamics and offers a conceptual understanding of these dynamics in terms of central microscopic features and processes.

Neurons communicate through specialized sites of cell–cell contact known as synapses. This vast set of connections is believed to be crucial for sensory processing, motor function, learning and memory. Experimental data from recent years suggest that synapses are not static structures, but rather dynamic assemblies of molecules that move in, out and between nearby synapses, with these dynamics driving changes in synaptic properties over time. Thus, in addition to changes directed by activity or other physiological signals, synapses also exhibit spontaneous changes that have particular dynamical and statistical signatures. Given the immense complexity of synapses at the molecular scale, how can one hope to understand the principles that govern these spontaneous changes and statistical signatures? Here we offer a mesoscopic modelling approach—situated between detailed microscopic and abstract macroscopic approaches—to advance this understanding. Our model, based on simplified biophysical assumptions, shows that spontaneous cooperative binding and unbinding of proteins at synaptic sites can give rise to dynamic and statistical signatures similar to those measured in experiments. Importantly, we find cooperativity to be indispensable in this regard. Our model thus offers a conceptual understanding of synaptic dynamics and statistical features in terms of a fundamental biological principle, namely cooperativity.

Relative Contributions of Specific Activity Histories and Spontaneous Processes to Size Remodeling of Glutamatergic Synapses

The idea that synaptic properties are defined by specific pre- and postsynaptic activity histories is one of the oldest and most influential tenets of contemporary neuroscience. Recent studies also indicate, however, that synaptic properties often change spontaneously, even in the absence of specific activity patterns or any activity whatsoever. What, then, are the relative contributions of activity history-dependent and activity history-independent processes to changes synapses undergo? To compare the relative contributions of these processes, we imaged, in spontaneously active networks of cortical neurons, glutamatergic synapses formed between the same axons and neurons or dendrites under the assumption that their similar activity histories should result in similar size changes over timescales of days. The size covariance of such commonly innervated (CI) synapses was then compared to that of synapses formed by different axons (non-CI synapses) that differed in their activity histories. We found that the size covariance of CI synapses was greater than that of non-CI synapses; yet overall size covariance of CI synapses was rather modest. Moreover, momentary and time-averaged sizes of CI synapses correlated rather poorly, in perfect agreement with published electron microscopy-based measurements of mouse cortex synapses. A conservative estimate suggested that ~40% of the observed size remodeling was attributable to specific activity histories, whereas ~10% and ~50% were attributable to cell-wide and spontaneous, synapse-autonomous processes, respectively. These findings demonstrate that histories of naturally occurring activity patterns can direct glutamatergic synapse remodeling but also suggest that the contributions of spontaneous, possibly stochastic, processes are at least as great.

A Simplified In vitro Experimental Model Encompasses the Essential Features of Sleep

In this paper, we show that neuronal assemblies plated on Micro Electrode Arrays present synchronized, low frequency firing patterns similar to in vivo slow wave oscillations, which are a key parameter of sleep-like state. Although neuronal cultures lack the characteristic high-frequency waves of wakefulness, it is possible to modulate their spontaneous firing pattern through the administration of specific neurotransmitters such as acetylcholine. We thus stimulated the cortical cultures with an agonist of acetylcholine receptor, Carbachol, which caused a desynchronization of the spontaneous firing of the cultures. We recorded and monitored the cultures for a period of over 31 h. We analyzed the electrophysiological signals by exploiting novel methodological approaches, taking into account the different temporal scales of the recorded signals, and considering both spikes and local field potentials. Supporting the electrophysiological analysis results, gene expressions of targeted genes showed the activation of specific markers involved in sleep-wake rhythms. Our results demonstrate that the Carbachol treatment induces desynchronization of neuronal activity, altering sleep-like properties in an in vitro model.

Remodeling and Tenacity of Inhibitory Synapses: Relationships with Network Activity and Neighboring Excitatory Synapses

Glutamatergic synapse size remodeling is governed not only by specific activity forms but also by apparently stochastic processes with well-defined statistics. These spontaneous remodeling processes can give rise to skewed and stable synaptic size distributions, underlie scaling of these distributions and drive changes in glutamatergic synapse size "configurations". Where inhibitory synapses are concerned, however, little is known on spontaneous remodeling dynamics, their statistics, their activity dependence or their long-term consequences. Here we followed individual inhibitory synapses for days, and analyzed their size remodeling dynamics within the statistical framework previously developed for glutamatergic synapses. Similar to glutamatergic synapses, size distributions of inhibitory synapses were skewed and stable; at the same time, however, sizes of individual synapses changed considerably, leading to gradual changes in synaptic size configurations. The suppression of network activity only transiently affected spontaneous remodeling dynamics, did not affect synaptic size configuration change rates and was not followed by the scaling of inhibitory synapse size distributions. Comparisons with glutamatergic synapses within the same dendrites revealed a degree of coupling between nearby inhibitory and excitatory synapse remodeling, but also revealed that inhibitory synapse size configurations changed at considerably slower rates than those of their glutamatergic neighbors. These findings point to quantitative differences in spontaneous remodeling dynamics of inhibitory and excitatory synapses but also reveal deep qualitative similarities in the processes that control their sizes and govern their remodeling dynamics.

Microfluidic Chip for Site-Specific Neuropharmacological Treatment and Activity Probing of 3D Neuronal "Optonet" Cultures

The study introduces a "brain-on-a-chip" microfluidic platform that hosts brain-like 3D cultures ("optonets") whose activity and responses to flowing drugs are recorded optically. Optonets are viable, optically accessible 3D neural networks whose characteristics approximate cortical networks. The results demonstrate the ability to monitor complex 3D activity patterns during extended site-specific, reversible neuropharmacogical exposure, suggesting an interesting potential in drug screening.

Interplay between population firing stability and single neuron dynamics in hippocampal networks

Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules.

DOI:http://dx.doi.org/10.7554/eLife.04378.001

The human brain contains more than 80 billion neurons, which are organised into extensive networks. Changes in the strength of connections between neurons are thought to underlie learning and memory: neuronal networks must therefore be sufficiently stable to allow existing memories to be stored, while remaining flexible enough to enable the brain to form new memories.

Evidence suggests that the stability of neuronal networks is maintained by a process called homeostasis. If properties of the network—such as the average firing rate of all the neurons—deviate from a set point, changes occur to return the network the original set point. However, much less is known about the effects of homeostasis at the level of individual neurons within networks: do their firing rates also remain stable over time?

Slomowitz, Styr et al. have now addressed this question by recording the activity of neuronal networks grown on an array of electrodes. Applying a drug that inhibits neuronal firing caused the average firing rate of the networks to decrease initially, as expected. However, after 2 days, homeostasis had restored the average firing rate to its original value, despite the continued presence of the drug. By contrast, the individual neurons within the networks behaved differently: on day 2 almost 90% of neurons had a firing rate that was different from their original firing rate.

Similar behavior was seen when Slomowitz, Styr et al. studied the degree of synchronization between neurons as they fire: the average value for the network returned to its original value, but this did not happen at the level of individual neurons. Surprisingly, however, the ability of the network to undergo short-lived changes in average strength of the connections between neurons—which is thought to support short-term memory—was not subject to homeostasis. This suggests that the loss of short-term memory that occurs in many brain diseases may be an unfortunate consequence of the efforts of neuronal networks to keep their average responses stable.

DOI:http://dx.doi.org/10.7554/eLife.04378.002

Adaptation to prolonged neuromodulation in cortical cultures: an invariable return to network synchrony

Background

Prolonged neuromodulatory regimes, such as those critically involved in promoting arousal and suppressing sleep-associated synchronous activity patterns, might be expected to trigger adaptation processes and, consequently, a decline in neuromodulator-driven effects. This possibility, however, has rarely been addressed.

Results

Using networks of cultured cortical neurons, acetylcholine microinjections and a novel closed-loop ‘synchrony-clamp’ system, we found that acetylcholine pulses strongly suppressed network synchrony. Over the course of many hours, however, synchrony invariably reemerged, even when feedback was used to compensate for declining cholinergic efficacy. Network synchrony also reemerged following its initial suppression by noradrenaline, but this did not occlude the suppression of synchrony or its gradual reemergence following subsequent cholinergic input. Importantly, cholinergic efficacy could be restored and preserved over extended time scales by periodically withdrawing cholinergic input.

Conclusions

These findings indicate that the capacity of neuromodulators to suppress network synchrony is constrained by slow-acting, reactive processes. A multiplicity of neuromodulators and ultimately neuromodulator withdrawal periods might thus be necessary to cope with an inevitable reemergence of network synchrony.

Electronic supplementary material

The online version of this article (doi:10.1186/s12915-014-0083-3) contains supplementary material, which is available to authorized users.

Synaptic size dynamics as an effectively stochastic process

Long-term, repeated measurements of individual synaptic properties have revealed that synapses can undergo significant directed and spontaneous changes over time scales of minutes to weeks. These changes are presumably driven by a large number of activity-dependent and independent molecular processes, yet how these processes integrate to determine the totality of synaptic size remains unknown. Here we propose, as an alternative to detailed, mechanistic descriptions, a statistical approach to synaptic size dynamics. The basic premise of this approach is that the integrated outcome of the myriad of processes that drive synaptic size dynamics are effectively described as a combination of multiplicative and additive processes, both of which are stochastic and taken from distributions parametrically affected by physiological signals. We show that this seemingly simple model, known in probability theory as the Kesten process, can generate rich dynamics which are qualitatively similar to the dynamics of individual glutamatergic synapses recorded in long-term time-lapse experiments in ex-vivo cortical networks. Moreover, we show that this stochastic model, which is insensitive to many of its underlying details, quantitatively captures the distributions of synaptic sizes measured in these experiments, the long-term stability of such distributions and their scaling in response to pharmacological manipulations. Finally, we show that the average kinetics of new postsynaptic density formation measured in such experiments is also faithfully captured by the same model. The model thus provides a useful framework for characterizing synapse size dynamics at steady state, during initial formation of such steady states, and during their convergence to new steady states following perturbations. These findings show the strength of a simple low dimensional statistical model to quantitatively describe synapse size dynamics as the integrated result of many underlying complex processes.

Systematic review and meta-analysis of noninvasive cranial nerve neuromodulation for nervous system disorders

OBJECTIVE

To systematically review the medical literature and comprehensively summarize clinical research done on rehabilitation with a novel portable and noninvasive electrical stimulation device called the cranial nerve noninvasive neuromodulator in patients suffering from nervous system disorders.

DATA SOURCES

PubMed, MEDLINE, and Cochrane Database of Systematic Reviews from 1966 to March 2013.

STUDY SELECTION

Studies were included if they recruited adult patients with peripheral and central nervous system disorders, were treated with the cranial nerve noninvasive neuromodulator device, and were assessed with objective measures of function.

DATA EXTRACTION

After title and abstract screening of potential articles, full texts were independently reviewed to identify articles that met inclusion criteria.

DATA SYNTHESIS

The search identified 12 publications: 5 were critically reviewed, and of these 5, 2 were combined in a meta-analysis. There were no randomized controlled studies identified, and the meta-analysis was based on pre-post studies. Most of the patients were individuals with a chronic balance dysfunction. The pooled results demonstrated significant improvements in the dynamic gait index postintervention with a mean difference of 3.45 (95% confidence interval, 1.75-5.15; P<.001), Activities-specific Balance Confidence scale with a mean difference of 16.65 (95% confidence interval, 7.65-25.47; P<.001), and Dizziness Handicap Inventory with improvements of -26.07 (95% confidence interval, -35.78 to -16.35; P<.001). Included studies suffered from small sample sizes, lack of randomization, absence of blinding, use of referral populations, and variability in treatment schedules and follow-up rates.

CONCLUSIONS

Given these limitations, the results of the meta-analysis must be interpreted cautiously. Further investigation using rigorous randomized controlled trials is needed to evaluate this promising rehabilitation tool for nervous system disorders.

Presynaptic and Postsynaptic Scaffolds

The development of methods to follow the dynamics of synaptic molecules in living neurons has radically altered our view of the synapse, from that of a generally static structure to that of a dynamic molecular assembly at steady state. This view holds not only for relatively labile synaptic components, such as synaptic vesicles, cytoskeletal elements, and neurotransmitter receptors, but also for the numerous synaptic molecules known as scaffolding molecules, a generic name for a diverse class of molecules that organize synaptic function in time and space. Recent studies reveal that these molecules, which confer a degree of stability to synaptic assemblies over time scales of hours and days, are themselves subject to significant dynamics. Furthermore, these dynamics are probably not without effect; wherever studied, these seem to be associated with spontaneous changes in scaffold molecule content, synaptic size, and possibly synaptic function. This review describes the dynamics exhibited by synaptic scaffold molecules, their typical time scales, and the potential implications to our understanding of synaptic function.

Matching dynamics of presynaptic and postsynaptic scaffolds

Synapses undergo substantial activity-dependent and independent remodeling over time scales of minutes, hours, and days. Presumably, changes in presynaptic properties should be matched by corresponding changes in postsynaptic properties and vice versa. Wherever measured, presynaptic and postsynaptic molecular properties tend to correlate, yet these correlations are often quite imperfect, raising questions as the origins of such mismatches: Are these the outcome of "single snapshot" analyses of asynchronous remodeling processes? Alternatively, do these indicate that synapses genuinely vary in the "stoichiometries" of their presynaptic and postsynaptic molecular contents? If so, are these "stoichiometries" preserved over time? To address these questions, we followed the matching dynamics of the presynaptic active-zone molecule Munc13-1 and the postsynaptic molecule PSD-95 in networks of cultured cortical mouse neurons. We find that presynaptic and postsynaptic remodeling were generally well correlated, but the degree of this correlation was highly variable, with little and even negative correlation observed at some synapses. No evidence was found that remodeling in one compartment consistently preceded remodeling in the other. Interestingly, even though the Munc13-1 and PSD-95 contents of individual synapses changed considerably over 15-22 h, Munc13-1/PSD-95 ratios, which varied over a fourfold range, were well conserved over these durations. These findings indicate that the "stoichiometries" of presynaptic and postsynaptic molecules can genuinely differ among synapses and that synapses can maintain their specific stoichiometries even in face of extensive presynaptic and postsynaptic remodeling.

From neural plate to cortical arousal-a neuronal network theory of sleep derived from in vitro "model" systems for primordial patterns of spontaneous bioelectric activity in the vertebrate central nervous system

In the early 1960s intrinsically generated widespread neuronal discharges were discovered to be the basis for the earliest motor behavior throughout the animal kingdom. The pattern generating system is in fact programmed into the developing nervous system, in a regionally specific manner, already at the early neural plate stage. Such rhythmically modulated phasic bursts were next discovered to be a general feature of developing neural networks and, largely on the basis of experimental interventions in cultured neural tissues, to contribute significantly to their morpho-physiological maturation. In particular, the level of spontaneous synchronized bursting is homeostatically regulated, and has the effect of constraining the development of excessive network excitability. After birth or hatching, this "slow-wave" activity pattern becomes sporadically suppressed in favor of sensory oriented "waking" behaviors better adapted to dealing with environmental contingencies. It nevertheless reappears periodically as "sleep" at several species-specific points in the diurnal/nocturnal cycle. Although this "default" behavior pattern evolves with development, its essential features are preserved throughout the life cycle, and are based upon a few simple mechanisms which can be both experimentally demonstrated and simulated by computer modeling. In contrast, a late onto- and phylogenetic aspect of sleep, viz., the intermittent "paradoxical" activation of the forebrain so as to mimic waking activity, is much less well understood as regards its contribution to brain development. Some recent findings dealing with this question by means of cholinergically induced "aroused" firing patterns in developing neocortical cell cultures, followed by quantitative electrophysiological assays of immediate and longterm sequelae, will be discussed in connection with their putative implications for sleep ontogeny.

Metabolic turnover of synaptic proteins: kinetics, interdependencies and implications for synaptic maintenance

Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics. To date, the turnover kinetics of synaptic proteins have not been studied or analyzed systematically, and thus metabolic demands or the aforementioned relationships remain largely unknown. In the current study we used dynamic Stable Isotope Labeling with Amino acids in Cell culture (SILAC), mass spectrometry (MS), Fluorescent Non-Canonical Amino acid Tagging (FUNCAT), quantitative immunohistochemistry and bioinformatics to systematically measure the metabolic half-lives of hundreds of synaptic proteins, examine how these depend on their pre/postsynaptic affiliation or their association with particular molecular complexes, and assess the metabolic load of synaptic proteostasis. We found that nearly all synaptic proteins identified here exhibited half-lifetimes in the range of 2-5 days. Unexpectedly, metabolic turnover rates were not significantly different for presynaptic and postsynaptic proteins, or for proteins for which mRNAs are consistently found in dendrites. Some functionally or structurally related proteins exhibited very similar turnover rates, indicating that their biogenesis and degradation might be coupled, a possibility further supported by bioinformatics-based analyses. The relatively low turnover rates measured here (∼0.7% of synaptic protein content per hour) are in good agreement with imaging-based studies of synaptic protein trafficking, yet indicate that the metabolic load synaptic protein turnover places on individual neurons is very substantial.