Structural plasticity of spines at giant mossy fiber synapses

The granule cells of the dentate gyrus give rise to thin unmyelinated axons, the mossy fibers. They form giant presynaptic boutons impinging on large complex spines on the proximal dendritic portions of hilar mossy cells and CA3 pyramidal neurons. While these anatomical characteristics have been known for some time, it remained unclear whether functional changes at mossy fiber synapses such as long-term potentiation (LTP) are associated with structural changes. Since subtle structural changes may escape a fine-structural analysis when the tissue is fixed by using aldehydes and is dehydrated in ethanol, rapid high-pressure freezing (HPF) of the tissue was applied. Slice cultures of hippocampus were prepared and incubated in vitro for 2 weeks. Then, chemical LTP (cLTP) was induced by the application of 25 mM tetraethylammonium (TEA) for 10 min. Whole-cell patch-clamp recordings from CA3 pyramidal neurons revealed a highly significant potentiation of mossy fiber synapses when compared to control conditions before the application of TEA. Next, the slice cultures were subjected to HPF, cryosubstitution, and embedding in Epon for a fine-structural analysis. When compared to control tissue, we noticed a significant decrease of synaptic vesicles in mossy fiber boutons and a concomitant increase in the length of the presynaptic membrane. On the postsynaptic side, we observed the formation of small, finger-like protrusions, emanating from the large complex spines. These short protrusions gave rise to active zones that were shorter than those normally found on the thorny excrescences. However, the total number of active zones was significantly increased. Of note, none of these cLTP-induced structural changes was observed in slice cultures from Munc13-1 deficient mouse mutants showing severely impaired vesicle priming and docking. In conclusion, application of HPF allowed us to monitor cLTP-induced structural reorganization of mossy fiber synapses.

Structural plasticity of hippocampal mossy fiber synapses as revealed by high-pressure freezing

Despite recent progress in fluorescence microscopy techniques, electron microscopy (EM) is still superior in the simultaneous analysis of all tissue components at high resolution. However, it is unclear to what extent conventional fixation for EM using aldehydes results in tissue alteration. Here we made an attempt to minimize tissue alteration by using rapid high-pressure freezing (HPF) of hippocampal slice cultures. We used this approach to monitor fine-structural changes at hippocampal mossy fiber synapses associated with chemically induced long-term potentiation (LTP). Synaptic plasticity in LTP has been known to involve structural changes at synapses including reorganization of the actin cytoskeleton and de novo formation of spines. While LTP-induced formation and growth of postsynaptic spines have been reported, little is known about associated structural changes in presynaptic boutons. Mossy fiber synapses are assumed to exhibit presynaptic LTP expression and are easily identified by EM. In slice cultures from wildtype mice, we found that chemical LTP increased the length of the presynaptic membrane of mossy fiber boutons, associated with a de novo formation of small spines and an increase in the number of active zones. Of note, these changes were not observed in slice cultures from Munc13-1 knockout mutants exhibiting defective vesicle priming. These findings show that activation of hippocampal mossy fibers induces pre- and postsynaptic structural changes at mossy fiber synapses that can be monitored by EM.

Fine structure of hippocampal mossy fiber synapses following rapid high-pressure freezing

Synapses of hippocampal neurons play important roles in learning and memory processes and are involved in aberrant hippocampal function in temporal lobe epilepsy. Major neuronal types in the hippocampus as well as their input and output synapses are well known, but it has remained an open question to what extent conventional electron microscopy (EM) has provided us with the real appearance of synaptic fine structure under in vivo conditions. There is reason to assume that conventional aldehyde fixation and dehydration lead to protein denaturation and tissue shrinkage, likely associated with the occurrence of artifacts. However, realistic fine-structural data of synapses are required for our understanding of the transmission process and for its simulation. Here, we used high-pressure freezing and cryosubstitution of hippocampal tissue that was not subjected to aldehyde fixation and dehydration in ethanol to monitor the fine structure of an identified synapse in the hippocampal CA3 region, that is, the synapse between granule cell axons, the mossy fibers, and the proximal dendrites of CA3 pyramidal neurons. Our results showed that high-pressure freezing nicely preserved ultrastructural detail of this particular synapse and allowed us to study rapid structural changes associated with synaptic plasticity.

New ways of looking at synapses

Current concepts of synaptic fine-structure are derived from electron microscopic studies of tissue fixed by chemical fixation using aldehydes. However, chemical fixation with glutaraldehyde and paraformaldehyde and subsequent dehydration in ethanol result in uncontrolled tissue shrinkage. While electron microscopy allows for the unequivocal identification of synaptic contacts, it cannot be used for real-time analysis of structural changes at synapses. For the latter purpose advanced fluorescence microscopy techniques are to be applied which, however, do not allow for the identification of synaptic contacts. Here, two approaches are described that may overcome, at least in part, some of these drawbacks in the study of synapses. By focusing on a characteristic, easily identifiable synapse, the mossy fiber synapse in the hippocampus, we first describe high-pressure freezing of fresh tissue as a method that may be applied to study subtle changes in synaptic ultrastructure associated with functional synaptic plasticity. Next, we propose to label presynaptic mossy fiber terminals and postsynaptic complex spines on CA3 pyramidal neurons by different fluorescent dyes to allow for the real-time monitoring of these synapses in living tissue over extended periods of time. We expect these approaches to lead to new insights into the structure and function of central synapses.

Non-Hebbian Long-Term Potentiation of Inhibitory Synapses in the Thalamus

The thalamus integrates and transmits sensory information to the neocortex. The activity of thalamocortical relay (TC) cells is modulated by specific inhibitory circuits. Although this inhibition plays a crucial role in regulating thalamic activity, little is known about long-term changes in synaptic strength at these inhibitory synapses. Therefore, we studied long-term plasticity of inhibitory inputs to TC cells in the posterior medial nucleus of the thalamus by combining patch-clamp recordings with two-photon fluorescence microscopy in rat brain slices. We found that specific activity patterns in the postsynaptic TC cell induced inhibitory long-term potentiation (iLTP). This iLTP was non-Hebbian because it did not depend on the timing between presynaptic and postsynaptic activity, but it could be induced by postsynaptic burst activity alone. iLTP required postsynaptic dendritic Ca2+ influx evoked by low-threshold Ca2+ spikes. In contrast, tonic postsynaptic spiking from a depolarized membrane potential (−50 mV), which suppressed these low-threshold Ca2+ spikes, induced no plasticity. The postsynaptic dendritic Ca2+ increase triggered the synthesis of nitric oxide that retrogradely activated presynaptic guanylyl cyclase, resulting in the presynaptic expression of iLTP. The dependence of iLTP on the membrane potential and therefore on the postsynaptic discharge mode suggests that this form of iLTP might occur during sleep, when TC cells discharge in bursts. Therefore, iLTP might be involved in sleep state-dependent modulation of thalamic information processing and thalamic oscillations.

Capture of activity-induced ultrastructural changes at synapses by high-pressure freezing of brain tissue.

Electron microscopy (EM) allows for the simultaneous visualization of all tissue components at high resolution. However, the extent to which conventional aldehyde fixation and ethanol dehydration of the tissue alter the fine structure of cells and organelles, thereby preventing detection of subtle structural changes induced by an experiment, has remained an issue. Attempts have been made to rapidly freeze tissue to preserve native ultrastructure. Shock-freezing of living tissue under high pressure (high-pressure freezing, HPF) followed by cryosubstitution of the tissue water avoids aldehyde fixation and dehydration in ethanol; the tissue water is immobilized in ∼50 ms, and a close-to-native fine structure of cells, organelles and molecules is preserved. Here we describe a protocol for HPF that is useful to monitor ultrastructural changes associated with functional changes at synapses in the brain but can be applied to many other tissues as well. The procedure requires a high-pressure freezer and takes a minimum of 7 d but can be paused at several points.

Fine structure of synapses on dendritic spines

Camillo Golgi's "Reazione Nera" led to the discovery of dendritic spines, small appendages originating from dendritic shafts. With the advent of electron microscopy (EM) they were identified as sites of synaptic contact. Later it was found that changes in synaptic strength were associated with changes in the shape of dendritic spines. While live-cell imaging was advantageous in monitoring the time course of such changes in spine structure, EM is still the best method for the simultaneous visualization of all cellular components, including actual synaptic contacts, at high resolution. Immunogold labeling for EM reveals the precise localization of molecules in relation to synaptic structures. Previous EM studies of spines and synapses were performed in tissue subjected to aldehyde fixation and dehydration in ethanol, which is associated with protein denaturation and tissue shrinkage. It has remained an issue to what extent fine structural details are preserved when subjecting the tissue to these procedures. In the present review, we report recent studies on the fine structure of spines and synapses using high-pressure freezing (HPF), which avoids protein denaturation by aldehydes and results in an excellent preservation of ultrastructural detail. In these studies, HPF was used to monitor subtle fine-structural changes in spine shape associated with chemically induced long-term potentiation (cLTP) at identified hippocampal mossy fiber synapses. Changes in spine shape result from reorganization of the actin cytoskeleton. We report that cLTP was associated with decreased immunogold labeling for phosphorylated cofilin (p-cofilin), an actin-depolymerizing protein. Phosphorylation of cofilin renders it unable to depolymerize F-actin, which stabilizes the actin cytoskeleton. Decreased levels of p-cofilin, in turn, suggest increased actin turnover, possibly underlying the changes in spine shape associated with cLTP. The findings reviewed here establish HPF as an appropriate method for studying the fine structure and molecular composition of synapses on dendritic spines.

Angiotensinergic and noradrenergic neurons in the rat and human heart

Although the physiological and pharmacological evidences suggest a role for angiotensin II (Ang II) with the mammalian heart, the source and precise location of Ang II are unknown. To visualize and quantitate Ang II in atria, ventricular walls and interventricular septum of the rat and human heart and to explore the feasibility of local Ang II production and function, we investigated by different methods the expression of proteins involved in the generation and function of Ang II. We found mRNA of angiotensinogen (Ang-N), of angiotensin converting enzyme, of the angiotensin type receptors AT(1A) and AT(2) (AT(1B) not detected) as well as of cathepsin D in any part of the hearts. No renin mRNA was traceable. Ang-N mRNA was visualized by in situ hybridization in atrial ganglial neurons. Ang II and dopamine- -hydroxylase (D H) were either colocalized inside the same neuronal cell or the neurons were specialized for Ang II or D H. Within these neurons, the vesicular acetylcholine transporter (VAChT) was neither colocalized with Ang II nor D H, but VAChT-staining was found with synapses en passant encircle these neuronal cells. The fibers containing Ang II exhibited with blood vessels and with cardiomyocytes supposedly angiotensinergic synapses en passant. In rat heart, right atrial median Ang II concentration appeared higher than septal and ventricular Ang II. The distinct colocalization of neuronal Ang II with D H in the heart may indicate that Ang II participates together with norepinephrine in the regulation of cardiac functions: Produced as a cardiac neurotransmitter Ang II may have inotropic, chronotropic or dromotropic effects in atria and ventricles and contributes to blood pressure regulation.

Intraneuronal angiotensinergic system in rat and human dorsal root ganglia

To elucidate the local formation of angiotensin II (Ang II) in the neurons of sensory dorsal root ganglia (DRG), we studied the expression of angiotensinogen (Ang-N)-, renin-, angiotensin converting enzyme (ACE)- and cathepsin D-mRNA, and the presence of protein renin, Ang II, Substance P and calcitonin gene-related peptide (CGRP) in the rat and human thoracic DRG. Quantitative real time PCR (qRT-PCR) studies revealed that rat DRG expressed substantial amounts of Ang-N- and ACE mRNA, while renin mRNA as well as the protein renin were untraceable. Cathepsin D-mRNA and cathepsin D-protein were detected in the rat DRG indicating the possibility of existence of pathways alternative to renin for Ang I formation. Angiotensin peptides were successfully detected with high performance liquid chromatography and radioimmunoassay in human DRG extracts. In situ hybridization in rat DRG confirmed additionally expression of Ang-N mRNA in the cytoplasm of numerous neurons. Intracellular Ang II staining could be shown in number of neurons and their processes in both the rat and human DRG. Interestingly we observed neuronal processes with angiotensinergic synapses en passant, colocalized with synaptophysin, within the DRG. In the DRG, we also identified by qRT-PCR, expression of Ang II receptor AT(1A) and AT(2)-mRNA while AT(1B)-mRNA was not traceable. In some neurons Substance P and CGRP were found colocalized with Ang II. The intracellular localization and colocalization of Ang II with Substance P and CGRP in the DRG neurons may indicate a participation and function of Ang II in the regulation of nociception. In conclusion, these results suggest that Ang II may be produced locally in the neurons of rat and human DRG and act as a neurotransmitter.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior. But behavioral decision making is likely to involve the integration of many synaptic events in space and time. So in using a single reinforcement signal to modulate synaptic plasticity a twofold problem arises. Different synapses will have contributed differently to the behavioral decision and, even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward but by a population feedback signal as well. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second one involves an action sequence which is itself extended in time and reward is only delivered at the last action, as is the case in any type of board-game. The third is the inspection game that has been studied in neuroeconomics. It only has a mixed Nash equilibrium and exemplifies that the model also copes with stochastic reward delivery and the learning of mixed strategies.

Reinforcement learning in dendritic structures

The discovery of binary dendritic events such as local NMDA spikes in dendritic subbranches led to the suggestion that dendritic trees could be computationally equivalent to a 2-layer network of point neurons, with a single output unit represented by the soma, and input units represented by the dendritic branches. Although this interpretation endows a neuron with a high computational power, it is functionally not clear why nature would have preferred the dendritic solution with a single but complex neuron, as opposed to the network solution with many but simple units. We show that the dendritic solution has a distinguished advantage over the network solution when considering different learning tasks. Its key property is that the dendritic branches receive an immediate feedback from the somatic output spike, while in the corresponding network architecture the feedback would require additional backpropagating connections to the input units. Assuming a reinforcement learning scenario we formally derive a learning rule for the synaptic contacts on the individual dendritic trees which depends on the presynaptic activity, the local NMDA spikes, the somatic action potential, and a delayed reinforcement signal. We test the model for two scenarios: the learning of binary classifications and of precise spike timings. We show that the immediate feedback represented by the backpropagating action potential supplies the individual dendritic branches with enough information to efficiently adapt their synapses and to speed up the learning process.

Reinforcement learning in dendritic structures

The discovery of binary dendritic events such as local NMDA spikes in dendritic subbranches led to the suggestion that dendritic trees could be computationally equivalent to a 2-layer network of point neurons, with a single output unit represented by the soma, and input units represented by the dendritic branches. Although this interpretation endows a neuron with a high computational power, it is functionally not clear why nature would have preferred the dendritic solution with a single but complex neuron, as opposed to the network solution with many but simple units. We show that the dendritic solution has a distinguished advantage over the network solution when considering different learning tasks. Its key property is that the dendritic branches receive an immediate feedback from the somatic output spike, while in the corresponding network architecture the feedback would require additional backpropagating connections to the input units. Assuming a reinforcement learning scenario we formally derive a learning rule for the synaptic contacts on the individual dendritic trees which depends on the presynaptic activity, the local NMDA spikes, the somatic action potential, and a delayed reinforcement signal. We test the model for two scenarios: the learning of binary classifications and of precise spike timings. We show that the immediate feedback represented by the backpropagating action potential supplies the individual dendritic branches with enough information to efficiently adapt their synapses and to speed up the learning process.