Sridhar Raghavachari

Mechanisms of CaMKII action in long-term potentiation

Long-term potentiation (LTP) of synaptic strength occurs during learning and can last for long periods, making it a probable mechanism for memory storage. LTP induction results in calcium entry, which activates calcium/calmodulin-dependent protein kinase II (CaMKII). CaMKII subsequently translocates to the synapse, where it binds to NMDA-type glutamate receptors and produces potentiation by phosphorylating principal and auxiliary subunits of AMPA-type glutamate receptors. These processes are all localized to stimulated spines and account for the synapse-specificity of LTP. In the later stages of LTP, CaMKII has a structural role in enlarging and strengthening the synapse.

The sequence of events that underlie quantal transmission at central glutamatergic synapses

The properties of synaptic transmission were first elucidated at the neuromuscular junction. More recent work has examined transmission at synapses within the brain. Here we review the remarkable progress in understanding the biophysical and molecular basis of the sequential steps in this process. These steps include the elevation of Ca2+ in microdomains of the presynaptic terminal, the diffusion of transmitter through the fusion pore into the synaptic cleft and the activation of postsynaptic receptors. The results give insight into the factors that control the precision of quantal transmission and provide a framework for understanding synaptic plasticity.

A Unified Model of the Presynaptic and Postsynaptic Changes During LTP at CA1 Synapses

Long-term potentiation (LTP) has been studied extensively at CA1 synapses of the hippocampus, and there is evidence implicating both postsynaptic and presynaptic changes in this process. These changes include (i) addition of AMPA channels to the extrasynaptic membrane and diffusional equilibrium of extrasynaptic receptors with synaptic receptors, (ii) sudden addition of AMPA channels to the synapse in large groups, (iii) a change in the mode of glutamate release (presumably from kiss-and-run to full fusion), and (iv) a delayed increase in the number of vesicles released. However, it remains unclear whether (or how) these changes work together. We have incorporated all of these processes into a structural model of the synapse. We propose that the synapse is composed of transsynaptic modules that function quasi-independently in AMPA-mediated transmission. Under basal conditions, synapses are partially silent; some modules are AMPA-silent (but contribute to NMDA-mediated transmission), whereas others are functional (and contribute to both AMPA- and NMDA-mediated transmission). During LTP, there is both a rapid change in the mode of vesicle fusion and a rapid insertion of a postsynaptic complex (a hyperslot) containing many proteins (slots) capable of binding AMPA channels. The combined effect of these pre- and postsynaptic changes is to convert AMPA-silent modules into functional modules. Slot filling is transiently enhanced by a rapid increase in extrasynaptic GluR1, a form of the AMPA-type receptor. A slower transsynaptic growth process adds AMPA-silent modules to the synapse, enhancing the number of vesicles released and thereby enhancing the NMDA response. This model accounts for a broad range of data, including the LTP-induced changes in quantal parameters. The model also provides a coherent explanation for the diverse effects of GluR1 knockout on basal transmission, LTP, and distance-dependent scaling. Long-term potentiation (LTP) is an activity-dependent process that leads to a long-lasting increase in the strength of synapses. Such changes are thought to underlie the storage of memory in the brain. But what exactly determines the strength of a synapse, and how is its strength enhanced during LTP? We review a large body of work on LTP at synapses in the hippocampal CA1 region, the site at which LTP has been most extensively studied. Experiments indicate that there are both presynaptic processes that enhance the release of neurotransmitter (glutamate) and postsynaptic processes that enhance the response to transmitter. To understand how these processes work together, we developed a structural model according to which the synapse is composed of transsynaptic modules. The synapse can be partially silent, meaning that some modules contribute to AMPA-mediated transmission whereas others do not (although all modules contribute to NMDA-mediated transmission). Within this framework, we have formulated a model that accounts for a large set of data in a unified way.

Calmodulin as a direct detector of Ca2+ signals

Many forms of signal transduction occur when Ca2+ enters the cytoplasm of a cell. It has been generally thought that there is a fast buffer that rapidly reduces the free Ca2+ level and that it is this buffered level of Ca2+ that triggers downstream biochemical processes, notably the activation of calmodulin (CaM) and the resulting activation of CaM-dependent enzymes. Given the importance of these transduction processes, it is crucial to understand exactly how Ca2+ activates CaM. We have determined the rate at which Ca2+ binds to CaM and found that Ca2+ binds more rapidly to CaM than to other Ca2+-binding proteins. This property of CaM and its high concentration support a new view of signal transduction: CaM directly intercepts incoming Ca2+ and sets the free Ca2+ level (that is, it strongly contributes to fast Ca2+ buffering) rather than responding to the lower Ca2+ level set by other buffers. This property is crucial for making CaM an efficient transducer. Our results also suggest that other Ca2+ binding proteins have a previously undescribed role in regulating the lifetime of Ca2+ bound to CaM and thereby setting the gain of signal transduction.

A Physiologically-Inspired Model of Numerical Classification Based on Graded Stimulus Coding

In most natural decision contexts, the process of selecting among competing actions takes place in the presence of informative, but potentially ambiguous, stimuli. Decisions about magnitudes – quantities like time, length, and brightness that are linearly ordered – constitute an important subclass of such decisions. It has long been known that perceptual judgments about such quantities obey Webers Law, wherein the just-noticeable difference in a magnitude is proportional to the magnitude itself. Current physiologically inspired models of numerical classification assume discriminations are made via a labeled line code of neurons selectively tuned for numerosity, a pattern observed in the firing rates of neurons in the ventral intraparietal area (VIP) of the macaque. By contrast, neurons in the contiguous lateral intraparietal area (LIP) signal numerosity in a graded fashion, suggesting the possibility that numerical classification could be achieved in the absence of neurons tuned for number. Here, we consider the performance of a decision model based on this analog coding scheme in a paradigmatic discrimination task – numerosity bisection. We demonstrate that a basic two-neuron classifier model, derived from experimentally measured monotonic responses of LIP neurons, is sufficient to reproduce the numerosity bisection behavior of monkeys, and that the threshold of the classifier can be set by reward maximization via a simple learning rule. In addition, our model predicts deviations from Weber Law scaling of choice behavior at high numerosity. Together, these results suggest both a generic neuronal framework for magnitude-based decisions and a role for reward contingency in the classification of such stimuli.

Neurons in Posterior Cingulate Cortex Signal Exploratory Decisions in a Dynamic Multioption Choice Task

In dynamic environments, adaptive behavior requires striking a balance between harvesting currently available rewards (exploitation) and gathering information about alternative options (exploration). Such strategic decisions should incorporate not only recent reward history, but also opportunity costs and environmental statistics. Previous neuroimaging and neurophysiological studies have implicated orbitofrontal cortex, anterior cingulate cortex, and ventral striatum in distinguishing between bouts of exploration and exploitation. Nonetheless, the neuronal mechanisms that underlie strategy selection remain poorly understood. We hypothesized that posterior cingulate cortex (CGp), an area linking reward processing, attention, memory, and motor control systems, mediates the integration of variables such as reward, uncertainty, and target location that underlie this dynamic balance. Here we show that CGp neurons distinguish between exploratory and exploitative decisions made by monkeys in a dynamic foraging task. Moreover, firing rates of these neurons predict in graded fashion the strategy most likely to be selected on upcoming trials. This encoding is distinct from switching between targets and is independent of the absolute magnitudes of rewards. These observations implicate CGp in the integration of individual outcomes across decision making and the modification of strategy in dynamic environments.

Quantifying the effects of elastic collisions and non-covalent binding on glutamate receptor trafficking in the post-synaptic density

One mechanism of information storage in neurons is believed to be determined by the strength of synaptic contacts. The strength of an excitatory synapse is partially due to the concentration of a particular type of ionotropic glutamate receptor (AMPAR) in the post-synaptic density (PSD). AMPAR concentration in the PSD has to be plastic, to allow the storage of new memories; but it also has to be stable to preserve important information. Although much is known about the molecular identity of synapses, the biophysical mechanisms by which AMPAR can enter, leave and remain in the synapse are unclear. We used Monte Carlo simulations to determine the influence of PSD structure and activity in maintaining homeostatic concentrations of AMPARs in the synapse. We found that, the high concentration and excluded volume caused by PSD molecules result in molecular crowding. Diffusion of AMPAR in the PSD under such conditions is anomalous. Anomalous diffusion of AMPAR results in retention of these receptors inside the PSD for periods ranging from minutes to several hours in the absence of strong binding of receptors to PSD molecules. Trapping of receptors in the PSD by crowding effects was very sensitive to the concentration of PSD molecules, showing a switch-like behavior for retention of receptors. Non-covalent binding of AMPAR to anchored PSD molecules allowed the synapse to become well-mixed, resulting in normal diffusion of AMPAR. Binding also allowed the exchange of receptors in and out of the PSD. We propose that molecular crowding is an important biophysical mechanism to maintain homeostatic synaptic concentrations of AMPARs in the PSD without the need of energetically expensive biochemical reactions. In this context, binding of AMPAR with PSD molecules could collaborate with crowding to maintain synaptic homeostasis but could also allow synaptic plasticity by increasing the exchange of these receptors with the surrounding extra-synaptic membrane.

The Effects of NR2 Subunit-Dependent NMDA Receptor Kinetics on Synaptic Transmission and CaMKII Activation

N-Methyl-d-aspartic acid (NMDA) receptors are widely expressed in the brain and are critical for many forms of synaptic plasticity. Subtypes of the NMDA receptor NR2 subunit are differentially expressed during development; in the forebrain, the NR2B receptor is dominant early in development, and later both NR2A and NR2B are expressed. In heterologous expression systems, NR2A-containing receptors open more reliably and show much faster opening and closing kinetics than do NR2B-containing receptors. However, conflicting data, showing similar open probabilities, exist for receptors expressed in neurons. Similarly, studies of synaptic plasticity have produced divergent results, with some showing that only NR2A-containing receptors can drive long-term potentiation and others showing that either subtype is capable of driving potentiation. In order to address these conflicting results as well as open questions about the number and location of functional receptors in the synapse, we constructed a Monte Carlo model of glutamate release, diffusion, and binding to NMDA receptors and of receptor opening and closing as well as a model of the activation of calcium-calmodulin kinase II, an enzyme critical for induction of synaptic plasticity, by NMDA receptor-mediated calcium influx. Our results suggest that the conflicting data concerning receptor open probabilities can be resolved, with NR2A- and NR2B-containing receptors having very different opening probabilities. They also support the conclusion that receptors containing either subtype can drive long-term potentiation. We also are able to estimate the number of functional receptors at a synapse from experimental data. Finally, in our models, the opening of NR2B-containing receptors is highly dependent on the location of the receptor relative to the site of glutamate release whereas the opening of NR2A-containing receptors is not. These results help to clarify the previous findings and suggest future experiments to address open questions concerning NMDA receptor function.

Quantitative estimates of the cytoplasmic, PSD, and NMDAR-bound pools of CaMKII in dendritic spines☆

CaMKII plays a critical role in long-term potentiation (LTP). The kinase is a major component of the postsynaptic density (PSD); however, it is also contained in the spine cytoplasm. CaMKII can now be monitored optically in living neurons, and it is therefore important to understand the contribution of the PSD and cytoplasmic pools to optical signals. Here, we estimate the size of these pools under basal conditions. From EM immunolabeling data, we calculate that the PSD/cytoplasmic ratio is ~5%. A second independent estimate is derived from measurements indicating that the average mushroom spine PSD contains 90 to 240 holoenzymes. A cytoplasmic concentration of 16 μM (~2590 holoenzymes) in the spine can be estimated from the total measured CaMKII content of hippocampal tissue, the relative volume of different compartments, and the spine-dendrite ratio of CaMKII (2:1). These numbers yield a second estimate (6%) of the PSD/spine ratio in good agreement with the first. The CaMKII bound to the NMDAR is important because preventing the formation of this complex blocks LTP induction. We estimate that the percentage of spine CaMKII held active by binding to the NMDAR is ~0.2%. Implications of the high spine concentration of CaMKII (> 100 μM alpha subunits) and the small fraction within the PSD are discussed. Of particular note, the finding that the CaMKII signal in spines shows only transient activation (open state) after LTP induction is subject to the qualification that it does not reflect the small but important pool bound to the NMDAR.

Biochemical principles underlying the stable maintenance of LTP by the CaMKII/NMDAR complex

Memory involves the storage of information at synapses by an LTP-like process. This information storage is synapse specific and can endure for years despite the turnover of all synaptic proteins. There must, therefore, be special principles that underlie the stability of LTP. Recent experimental results suggest that LTP is maintained by the complex of CaMKII with the NMDAR. Here we consider the specifics of the CaMKII/NMDAR molecular switch, with the goal of understanding the biochemical principles that underlie stable information storage by synapses. Consideration of a variety of experimental results suggests that multiple principles are involved. One switch requirement is to prevent spontaneous transitions from the off to the on state. The highly cooperative nature of CaMKII autophosphorylation by Ca(2+) (Hill coefficient of 8) and the fact that formation of the CaMKII/NMDAR complex requires release of CaMKII from actin are mechanisms that stabilize the off state. The stability of the on state depends critically on intersubunit autophosphorylation, a process that restores any loss of pT286 due to phosphatase activity. Intersubunit autophosphorylation is also important in explaining why on state stability is not compromised by protein turnover. Recent evidence suggests that turnover occurs by subunit exchange. Thus, stability could be achieved if a newly inserted unphosphorylated subunit was autophosphorylated by a neighboring subunit. Based on other recent work, we posit a novel mechanism that enhances the stability of the on state by protection of pT286 from phosphatases. We posit that the binding of the NMNDAR to CaMKII forces pT286 into the catalytic site of a neighboring subunit, thereby protecting pT286 from phosphatases. A final principle concerns the role of structural changes. The binding of CaMKII to the NMDAR may act as a tag to organize the binding of further proteins that produce the synapse enlargement that underlies late LTP. We argue that these structural changes not only enhance transmission, but also enhance the stability of the CaMKII/NMDAR complex. Together, these principles provide a mechanistic framework for understanding how individual synapses produce stable information storage. This article is part of a Special Issue entitled SI: Brain and Memory.