Elements of a neurobiological theory of the hippocampus: the role of activity-dependent synaptic plasticity in memory

The hypothesis that synaptic plasticity is a critical component of the neural mechanisms underlying learning and memory is now widely accepted. In this article, we begin by outlining four criteria for evaluating the 'synaptic plasticity and memory (SPM)' hypothesis. We then attempt to lay the foundations for a specific neurobiological theory of hippocampal (HPC) function in which activity-dependent synaptic plasticity, such as long-term potentiation (LTP), plays a key part in the forms of memory mediated by this brain structure. HPC memory can, like other forms of memory, be divided into four processes: encoding, storage, consolidation and retrieval. We argue that synaptic plasticity is critical for the encoding and intermediate storage of memory traces that are automatically recorded in the hippocampus. These traces decay, but are sometimes retained by a process of cellular consolidation. However, we also argue that HPC synaptic plasticity is not involved in memory retrieval, and is unlikely to be involved in systems-level consolidation that depends on HPC-neocortical interactions, although neocortical synaptic plasticity does play a part. The information that has emerged from the worldwide focus on the mechanisms of induction and expression of plasticity at individual synapses has been very valuable in functional studies. Progress towards a comprehensive understanding of memory processing will also depend on the analysis of these synaptic changes within the context of a wider range of systems-level and cellular mechanisms of neuronal transmission and plasticity.     

Reversible plasticity of fear memory-encoding amygdala synaptic circuits even after fear memory consolidation

It is generally believed that after memory consolidation, memory-encoding synaptic circuits are persistently modified and become less plastic. This, however, may hinder the remaining capacity of information storage in a given neural circuit. Here we consider the hypothesis that memory-encoding synaptic circuits still retain reversible plasticity even after memory consolidation. To test this, we employed a protocol of auditory fear conditioning which recruited the vast majority of the thalamic input synaptic circuit to the lateral amygdala (T-LA synaptic circuit; a storage site for fear memory) with fear conditioning-induced synaptic plasticity. Subsequently the fear memory-encoding synaptic circuits were challenged with fear extinction and re-conditioning to determine whether these circuits exhibit reversible plasticity. We found that fear memory-encoding T-LA synaptic circuit exhibited dynamic efficacy changes in tight correlation with fear memory strength even after fear memory consolidation. Initial conditioning or re-conditioning brought T-LA synaptic circuit near the ceiling of their modification range (occluding LTP and enhancing depotentiation in brain slices prepared from conditioned or re-conditioned rats), while extinction reversed this change (reinstating LTP and occluding depotentiation in brain slices prepared from extinguished rats). Consistently, fear conditioning-induced synaptic potentiation at T-LA synapses was functionally reversed by extinction and reinstated by subsequent re-conditioning. These results suggest reversible plasticity of fear memory-encoding circuits even after fear memory consolidation. This reversible plasticity of memory-encoding synapses may be involved in updating the contents of original memory even after memory consolidation.     

Structural Components of Synaptic Plasticity and Memory Consolidation

Consolidation of implicit memory in the invertebrate Aplysia and explicit memory in the mammalian hippocampus are associated with remodeling and growth of preexisting synapses and the formation of new synapses. Here, we compare and contrast structural components of the synaptic plasticity that underlies these two distinct forms of memory. In both cases, the structural changes involve time-dependent processes. Thus, some modifications are transient and may contribute to early formative stages of long-term memory, whereas others are more stable, longer lasting, and likely to confer persistence to memory storage. In addition, we explore the possibility that trans-synaptic signaling mechanisms governing de novo synapse formation during development can be reused in the adult for the purposes of structural synaptic plasticity and memory storage. Finally, we discuss how these mechanisms set in motion structural rearrangements that prepare a synapse to strengthen the same memory and, perhaps, to allow it to take part in other memories as a basis for understanding how their anatomical representation results in the enhanced expression and storage of memories in the brain.Santiago Ramón y Cajal (1894) used the insights provided by his remarkable light microscopic observations of neurons selectively stained with the Golgi method to propose the first cellular theory of memory storage as an anatomical change in the functional connections between nerve cells, later called synapses (Sherrington 1897). For most of the last century, chemical synapses were thought to convey information in only one direction—from the presynaptic to the postsynaptic neuron. It now is clear that synaptic transmission is a bidirectional and self-modifiable form of cell–cell communication (Peters et al. 1976; Jessell and Kandel 1993). This appreciation of reciprocal signaling between pre- and postsynaptic elements is consistent with other forms of intercellular communication and provides a conceptual framework for understanding memory-induced changes in the structure of the synapse. Indeed, an increasing body of evidence suggests that trans-synaptic signaling and coordinated recruitment of pre- and postsynaptic mechanisms underlie consolidation of both implicit and explicit forms of memory storage (Marrone 2005; Hawkins et al. 2006; Bailey et al. 2008).Studies in a variety of systems have found that molecular mechanisms of consolidation and long-term storage of memory begin at the level of the synapse. Existing proteins are modified, signals are sent back to the nucleus so that specific genes are expressed, and gene products are transported back to the synapse where the local synthesis of new protein is triggered to allow for the remodeling, addition, and elimination of synapses (Bailey and Kandel 1985; Bailey et al. 1996; Kandel 2001; Bourne and Harris 2008, 2012). These structural components of synaptic plasticity are thought to represent a cellular change that contributes to both implicit and explicit memory consolidation (Greenough and Bailey 1988; Bailey and Kandel 1993; Bailey et al. 2005; Bourne and Harris 2008, 2012). The association between alterations in the structure and/or number of synapses and memory storage has led to numerous studies regarding the signaling pathways that might couple molecular changes to structural changes. In addition, parallel homeostatic mechanisms have been identified that can trigger synaptic scaling, which serves to stabilize the strengthened synapses while weakening or eliminating other synapses, thus providing specificity during memory consolidation (Bourne and Harris 2011; Schacher and Hu 2014).In this review, we compare and contrast structural changes at the synapse during both implicit and explicit memory consolidation, as well as the molecular signaling pathways that initiate the learning-induced structural changes versus those that serve to maintain these changes over time. Toward that end, we will focus on two experimental model systems and several prototypic forms of synaptic plasticity that we have worked on and that have been extensively studied as representative examples of memory storage: long-term habituation and sensitization of the gill-withdrawal reflex in Aplysia. These are examples of implicit memory consolidation and hippocampal-based long-term potentiation (LTP) and long-term depression (LTD), as candidate mechanisms for the synaptic plasticity underlying explicit memory storage in mammals. These will serve as useful points of comparison to consider similarities, differences, and still-existing limitations in our understanding of the functional significance of the structural synaptic plasticity recruited during the consolidation of both implicit and explicit forms of memory.     

Efficient Partitioning of Memory Systems and Its Importance for Memory Consolidation

Long-term memories are likely stored in the synaptic weights of neuronal networks in the brain. The storage capacity of such networks depends on the degree of plasticity of their synapses. Highly plastic synapses allow for strong memories, but these are quickly overwritten. On the other hand, less labile synapses result in long-lasting but weak memories. Here we show that the trade-off between memory strength and memory lifetime can be overcome by partitioning the memory system into multiple regions characterized by different levels of synaptic plasticity and transferring memory information from the more to less plastic region. The improvement in memory lifetime is proportional to the number of memory regions, and the initial memory strength can be orders of magnitude larger than in a non-partitioned memory system. This model provides a fundamental computational reason for memory consolidation processes at the systems level.     

Altered cortical synaptic morphology and impaired memory consolidation in forebrain- specific dominant-negative PAK transgenic mice

Molecular and cellular mechanisms for memory consolidation in the cortex are poorly known. To study the relationships between synaptic structure and function in the cortex and consolidation of long-term memory, we have generated transgenic mice in which catalytic activity of PAK, a critical regulator of actin remodeling, is inhibited in the postnatal forebrain. Cortical neurons in these mice displayed fewer dendritic spines and an increased proportion of larger synapses compared to wild-type controls. These alterations in basal synaptic morphology correlated with enhanced mean synaptic strength and impaired bidirectional synaptic modifiability (enhanced LTP and reduced LTD) in the cortex. By contrast, spine morphology and synaptic plasticity were normal in the hippocampus of these mice. Importantly, these mice exhibited specific deficits in the consolidation phase of hippocampus-dependent memory. Thus, our results provide evidence for critical relationships between synaptic morphology and bidirectional modifiability of synaptic strength in the cortex and consolidation of long-term memory.     

Interplay between Short- and Long-Term Plasticity in Cell-Assembly Formation

Various hippocampal and neocortical synapses of mammalian brain show both short-term plasticity and long-term plasticity, which are considered to underlie learning and memory by the brain. According to Hebb’s postulate, synaptic plasticity encodes memory traces of past experiences into cell assemblies in cortical circuits. However, it remains unclear how the various forms of long-term and short-term synaptic plasticity cooperatively create and reorganize such cell assemblies. Here, we investigate the mechanism in which the three forms of synaptic plasticity known in cortical circuits, i.e., spike-timing-dependent plasticity (STDP), short-term depression (STD) and homeostatic plasticity, cooperatively generate, retain and reorganize cell assemblies in a recurrent neuronal network model. We show that multiple cell assemblies generated by external stimuli can survive noisy spontaneous network activity for an adequate range of the strength of STD. Furthermore, our model predicts that a symmetric temporal window of STDP, such as observed in dopaminergic modulations on hippocampal neurons, is crucial for the retention and integration of multiple cell assemblies. These results may have implications for the understanding of cortical memory processes.     

Hebbian plasticity in parallel synaptic pathways: A circuit mechanism for systems memory consolidation

Systems memory consolidation involves the transfer of memories across brain regions and the transformation of memory content. For example, declarative memories that transiently depend on the hippocampal formation are transformed into long-term memory traces in neocortical networks, and procedural memories are transformed within cortico-striatal networks. These consolidation processes are thought to rely on replay and repetition of recently acquired memories, but the cellular and network mechanisms that mediate the changes of memories are poorly understood. Here, we suggest that systems memory consolidation could arise from Hebbian plasticity in networks with parallel synaptic pathways—two ubiquitous features of neural circuits in the brain. We explore this hypothesis in the context of hippocampus-dependent memories. Using computational models and mathematical analyses, we illustrate how memories are transferred across circuits and discuss why their representations could change. The analyses suggest that Hebbian plasticity mediates consolidation by transferring a linear approximation of a previously acquired memory into a parallel pathway. Our modelling results are further in quantitative agreement with lesion studies in rodents. Moreover, a hierarchical iteration of the mechanism yields power-law forgetting—as observed in psychophysical studies in humans. The predicted circuit mechanism thus bridges spatial scales from single cells to cortical areas and time scales from milliseconds to years.     

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.     

Ubiquitous plasticity and memory storage

To date, most hypotheses of memory storage in the mammalian brain have focused upon long-term synaptic potentiation and depression (LTP and LTD) of fast glutamatergic excitatory postsynaptic currents (EPSCs). In recent years, it has become clear that many additional electrophysiological components of neurons, from electrical synapses to glutamate transporters to voltage-sensitive ion channels, can also undergo use-dependent long-term plasticity. Models of memory storage that incorporate this full range of demonstrated electrophysiological plasticity are better able to account for both the storage of memory in neuronal networks and the complexities of memory storage, indexing, and recall as measured behaviorally.     

Role of Synaptic Structural Plasticity in Impairments of Spatial Learning and Memory Induced by Developmental Lead Exposure in Wistar Rats

Lead (Pb) is found to impair cognitive function. Synaptic structural plasticity is considered to be the physiological basis of synaptic functional plasticity and has been recently found to play important roles in learning and memory. To study the effect of Pb on spatial learning and memory at different developmental stages, and its relationship with alterations of synaptic structural plasticity, postnatal rats were randomly divided into three groups: Control; Pre-weaning Pb (Parents were exposed to 2 mM PbCl₂ 3 weeks before mating until weaning of pups); Post-weaning Pb (Weaned pups were exposed to 2 mM PbCl₂ for 9 weeks). The spatial learning and memory of rats was measured by Morris water maze (MWM) on PND 85–90. Rat pups in Pre-weaning Pb and Post-weaning Pb groups performed significantly worse than those in Control group (p<0.05). However, there was no significant difference in the performance of MWM between the two Pb-exposure groups. Before MWM (PND 84), the number of neurons and synapses significantly decreased in Pre-weaning Pb group, but not in Post-weaning Pb group. After MWM (PND 91), the number of synapses in Pre-weaning Pb group increased significantly, but it was still less than that of Control group (p<0.05); the number of synapses in Post-weaning Pb group was also less than that of Control group (p<0.05), although the number of synapses has no differences between Post-weaning Pb and Control groups before MWM. In both Pre-weaning Pb and Post-weaning Pb groups, synaptic structural parameters such as thickness of postsynaptic density (PSD), length of synaptic active zone and synaptic curvature increased significantly while width of synaptic cleft decreased significantly compared to Control group (p<0.05). Our data demonstrated that both early and late developmental Pb exposure impaired spatial learning and memory as well as synaptic structural plasticity in Wistar rats.     

Arc/Arg3.1 mediates homeostatic synaptic scaling of AMPA receptors

Homeostatic plasticity may compensate for Hebbian forms of synaptic plasticity, such as long-term potentiation (LTP) and depression (LTD), by scaling neuronal output without changing the relative strength of individual synapses. This delicate balance between neuronal output and distributed synaptic weight may be necessary for maintaining efficient encoding of information across neuronal networks. Here, we demonstrate that Arc/Arg3.1, an immediate-early gene (IEG) that is rapidly induced by neuronal activity associated with information encoding in the brain, mediates homeostatic synaptic scaling of AMPA type glutamate receptors (AMPARs) via its ability to activate a novel and selective AMPAR endocytic pathway. High levels of Arc/Arg3.1 block the homeostatic increases in AMPAR function induced by chronic neuronal inactivity. Conversely, loss of Arc/Arg3.1 results in increased AMPAR function and abolishes homeostatic scaling of AMPARs. These observations, together with evidence that Arc/Arg3.1 is required for memory consolidation, reveal the importance of Arc/Arg3.1's dynamic expression as it exerts continuous and precise control over synaptic strength and cellular excitability.     

Brief Subthreshold Events Can Act as Hebbian Signals for Long-Term Plasticity

Background

Action potentials are thought to be determinant for the induction of long-term synaptic plasticity, the cellular basis of learning and memory. However, neuronal activity does not lead systematically to an action potential but also, in many cases, to synaptic depolarizing subthreshold events. This is particularly exemplified in corticostriatal information processing. Indeed, the striatum integrates information from the whole cerebral cortex and, due to the membrane properties of striatal medium spiny neurons, cortical inputs do not systematically trigger an action potential but a wide range of subthreshold postsynaptic depolarizations. Accordingly, we have addressed the following question: does a brief subthreshold event act as a Hebbian signal and induce long-term synaptic efficacy changes?

Methodology/Principal Findings

Here, using perforated patch-clamp recordings on rat brain corticostriatal slices, we demonstrate, that brief (30 ms) subthreshold depolarizing events in quasi-coincidence with presynaptic activity can act as Hebbian signals and are sufficient to induce long-term synaptic plasticity at corticostriatal synapses. This “subthreshold-depolarization dependent plasticity” (SDDP) induces strong, significant and bidirectional long-term synaptic efficacy changes at a very high occurrence (81%) for time intervals between pre- and postsynaptic stimulations (Δt) of −110<Δt<+110 ms. Such subthreshold depolarizations are able to induce robust long-term depression (cannabinoid type-1 receptor-activation dependent) as well as long-term potentiation (NMDA receptor-activation dependent).

Conclusion/Significance

Our data show the existence of a robust, reliable and timing-dependent bidirectional long-term plasticity induced by brief subthreshold events paired with presynaptic activity. The existence of a subthreshold-depolarization dependent plasticity extends considerably, beyond the action potential, the neuron''s capabilities to express long-term synaptic efficacy changes.     

Nucleolar Integrity Is Required for the Maintenance of Long-Term Synaptic Plasticity

Long-term memory (LTM) formation requires new protein synthesis and new gene expression. Based on our work in Aplysia, we hypothesized that the rRNA genes, stimulation-dependent targets of the enzyme Poly(ADP-ribose) polymerase-1 (PARP-1), are primary effectors of the activity-dependent changes in synaptic function that maintain synaptic plasticity and memory. Using electrophysiology, immunohistochemistry, pharmacology and molecular biology techniques, we show here, for the first time, that the maintenance of forskolin-induced late-phase long-term potentiation (L-LTP) in mouse hippocampal slices requires nucleolar integrity and the expression of new rRNAs. The activity-dependent upregulation of rRNA, as well as L-LTP expression, are poly(ADP-ribosyl)ation (PAR) dependent and accompanied by an increase in nuclear PARP-1 and Poly(ADP) ribose molecules (pADPr) after forskolin stimulation. The upregulation of PARP-1 and pADPr is regulated by Protein kinase A (PKA) and extracellular signal-regulated kinase (ERK)—two kinases strongly associated with long-term plasticity and learning and memory. Selective inhibition of RNA Polymerase I (Pol I), responsible for the synthesis of precursor rRNA, results in the segmentation of nucleoli, the exclusion of PARP-1 from functional nucleolar compartments and disrupted L-LTP maintenance. Taken as a whole, these results suggest that new rRNAs (28S, 18S, and 5.8S ribosomal components)—hence, new ribosomes and nucleoli integrity—are required for the maintenance of long-term synaptic plasticity. This provides a mechanistic link between stimulation-dependent gene expression and the new protein synthesis known to be required for memory consolidation.     

A clustered plasticity model of long-term memory engrams

Long-term memory and its putative synaptic correlates the late phases of both long-term potentiation and long-term depression require enhanced protein synthesis. On the basis of recent data on translation-dependent synaptic plasticity and on the supralinear effect of activation of nearby synapses on action potential generation, we propose a model for the formation of long-term memory engrams at the single neuron level. In this model, which we call clustered plasticity, local translational enhancement, along with synaptic tagging and capture, facilitates the formation of long-term memory engrams through bidirectional synaptic weight changes among synapses within a dendritic branch.     

Structural Synaptic Plasticity Has High Memory Capacity and Can Explain Graded Amnesia,Catastrophic Forgetting,and the Spacing Effect

Although already William James and, more explicitly, Donald Hebb''s theory of cell assemblies have suggested that activity-dependent rewiring of neuronal networks is the substrate of learning and memory, over the last six decades most theoretical work on memory has focused on plasticity of existing synapses in prewired networks. Research in the last decade has emphasized that structural modification of synaptic connectivity is common in the adult brain and tightly correlated with learning and memory. Here we present a parsimonious computational model for learning by structural plasticity. The basic modeling units are “potential synapses” defined as locations in the network where synapses can potentially grow to connect two neurons. This model generalizes well-known previous models for associative learning based on weight plasticity. Therefore, existing theory can be applied to analyze how many memories and how much information structural plasticity can store in a synapse. Surprisingly, we find that structural plasticity largely outperforms weight plasticity and can achieve a much higher storage capacity per synapse. The effect of structural plasticity on the structure of sparsely connected networks is quite intuitive: Structural plasticity increases the “effectual network connectivity”, that is, the network wiring that specifically supports storage and recall of the memories. Further, this model of structural plasticity produces gradients of effectual connectivity in the course of learning, thereby explaining various cognitive phenomena including graded amnesia, catastrophic forgetting, and the spacing effect.     

Translational control of synaptic plasticity

Synapses, points of contact between axons and dendrites, are conduits for the flow of information in the circuitry of the central nervous system. The strength of synaptic transmission reflects the interconnectedness of the axons and dendrites at synapses; synaptic strength in turn is modified by the frequency with which the synapses are stimulated. This modulation of synaptic strength, or synaptic plasticity, probably forms the cellular basis for learning and memory. RNA metabolism, particularly translational control at or near the synapse, is one process that controls long-lasting synaptic plasticity and, by extension, memory formation and consolidation. In the present paper, I review some salient features of translational control of synaptic plasticity.     

Long-term potentiation and olfactory memory formation in the carp (<Emphasis Type="Italic">Cyprinus carpio</Emphasis> L.) olfactory bulb

Long-term potentiation of synaptic transmission is considered to be an elementary process underlying the cellular mechanism of memory formation. In the present study we aimed to examine whether or not the dendrodendritic mitral-to-granule cell synapses in the carp olfactory bulb show plastic changes after their repeated activation. It was found that: (1) the dendrodendritic mitral-to-granule cell synapses showed three types of plasticity after tetanic electrical stimulation applied to the olfactory tract—long-term potentiation (potentiation lasting >1 h), short-term potentiation (potentiation lasting <1 h) and post-tetanic potentiation (potentiation lasting <10 min); (2) Long-term potentiation was generally induced when both the dendrodendritic mitral-to-granule cell synapses and centrifugal fiber-to-granule cell synapses were repeatedly and simultaneously activated; (3) long-term enhancement (>1 h) of the odor-evoked bulbar response accompanied the electrically-induced LTP, and; (4) repeated olfactory stimulation enhanced dendrodendritic mitral-to-granule cell transmission. Based on these results, it was proposed that long-term potentiation (as well as olfactory memory) occurs at the dendrodendritic mitral-to-granule cell synapses after strong and long-lasting depolarization of granule cells, which follows repeated and simultaneous synaptic activation of both the peripheral and deep dendrites (or somata).     

Soft-bound Synaptic Plasticity Increases Storage Capacity

Accurate models of synaptic plasticity are essential to understand the adaptive properties of the nervous system and for realistic models of learning and memory. Experiments have shown that synaptic plasticity depends not only on pre- and post-synaptic activity patterns, but also on the strength of the connection itself. Namely, weaker synapses are more easily strengthened than already strong ones. This so called soft-bound plasticity automatically constrains the synaptic strengths. It is known that this has important consequences for the dynamics of plasticity and the synaptic weight distribution, but its impact on information storage is unknown. In this modeling study we introduce an information theoretic framework to analyse memory storage in an online learning setting. We show that soft-bound plasticity increases a variety of performance criteria by about 18% over hard-bound plasticity, and likely maximizes the storage capacity of synapses.