Spike-Timing Theory of Working Memory

Working memory (WM) is the part of the brain''s memory system that provides temporary storage and manipulation of information necessary for cognition. Although WM has limited capacity at any given time, it has vast memory content in the sense that it acts on the brain''s nearly infinite repertoire of lifetime long-term memories. Using simulations, we show that large memory content and WM functionality emerge spontaneously if we take the spike-timing nature of neuronal processing into account. Here, memories are represented by extensively overlapping groups of neurons that exhibit stereotypical time-locked spatiotemporal spike-timing patterns, called polychronous patterns; and synapses forming such polychronous neuronal groups (PNGs) are subject to associative synaptic plasticity in the form of both long-term and short-term spike-timing dependent plasticity. While long-term potentiation is essential in PNG formation, we show how short-term plasticity can temporarily strengthen the synapses of selected PNGs and lead to an increase in the spontaneous reactivation rate of these PNGs. This increased reactivation rate, consistent with in vivo recordings during WM tasks, results in high interspike interval variability and irregular, yet systematically changing, elevated firing rate profiles within the neurons of the selected PNGs. Additionally, our theory explains the relationship between such slowly changing firing rates and precisely timed spikes, and it reveals a novel relationship between WM and the perception of time on the order of seconds.     

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.     

Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation

Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling – a slow process usually associated with the maintenance of activity homeostasis – combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.     

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.     

Spermidine boosts autophagy to protect from synapse aging

All animals form memories to adapt their behavior in a context-dependent manner. With increasing age, however, forming new memories becomes less efficient. While synaptic plasticity promotes memory formation, the etiology of age-induced memory formation remained enigmatic. Previous work showed that simple feeding of polyamine spermidine protects from age-induced memory impairment in Drosophila. Most recent work now shows that spermidine operates directly at synapses, allowing for an autophagy-dependent homeostatic regulation of presynaptic specializations. How exactly autophagic regulations intersect with synaptic plasticity should be an interesting subject for future research.     

Bidirectional, activity-dependent regulation of glutamate receptors in the adult hippocampus in vivo

Experience-dependent regulation of synaptic strength has been suggested as a physiological mechanism by which memory storage occurs in the brain. Although modifications in postsynaptic glutamate receptor levels have long been hypothesized to be a molecular basis for long-lasting regulation of synaptic strength, direct evidence obtained in the intact brain has been lacking. Here we show that in the adult brain in vivo, synaptic glutamate receptor trafficking is bidirectionally, and reversibly, modified by NMDA receptor-dependent synaptic plasticity and that changes in glutamate receptor protein levels accurately predict changes in synaptic strength. These findings support the idea that memories can be encoded by the precise experience-dependent assignment of glutamate receptors to synapses in the brain.     

A model of late long-term potentiation simulates aspects of memory maintenance

Late long-term potentiation (L-LTP) denotes long-lasting strengthening of synapses between neurons. L-LTP appears essential for the formation of long-term memory, with memories at least partly encoded by patterns of strengthened synapses. How memories are preserved for months or years, despite molecular turnover, is not well understood. Ongoing recurrent neuronal activity, during memory recall or during sleep, has been hypothesized to preferentially potentiate strong synapses, preserving memories. This hypothesis has not been evaluated in the context of a mathematical model representing ongoing activity and biochemical pathways important for L-LTP. In this study, ongoing activity was incorporated into two such models - a reduced model that represents some of the essential biochemical processes, and a more detailed published model. The reduced model represents synaptic tagging and gene induction simply and intuitively, and the detailed model adds activation of essential kinases by Ca(2+). Ongoing activity was modeled as continual brief elevations of Ca(2+). In each model, two stable states of synaptic strength/weight resulted. Positive feedback between synaptic weight and the amplitude of ongoing Ca(2+) transients underlies this bistability. A tetanic or theta-burst stimulus switches a model synapse from a low basal weight to a high weight that is stabilized by ongoing activity. Bistability was robust to parameter variations in both models. Simulations illustrated that prolonged periods of decreased activity reset synaptic strengths to low values, suggesting a plausible forgetting mechanism. However, episodic activity with shorter inactive intervals maintained strong synapses. Both models support experimental predictions. Tests of these predictions are expected to further understanding of how neuronal activity is coupled to maintenance of synaptic strength. Further investigations that examine the dynamics of activity and synaptic maintenance can be expected to help in understanding how memories are preserved for up to a lifetime in animals including humans.     

A Novel Whole-Cell Mechanism for Long-Term Memory Enhancement

Olfactory-discrimination learning was shown to induce a profound long-lasting enhancement in the strength of excitatory and inhibitory synapses of pyramidal neurons in the piriform cortex. Notably, such enhancement was mostly pronounced in a sub-group of neurons, entailing about a quarter of the cell population. Here we first show that the prominent enhancement in the subset of cells is due to a process in which all excitatory synapses doubled their strength and that this increase was mediated by a single process in which the AMPA channel conductance was doubled. Moreover, using a neuronal-network model, we show how such a multiplicative whole-cell synaptic strengthening in a sub-group of cells that form a memory pattern, sub-serves a profound selective enhancement of this memory. Network modeling further predicts that synaptic inhibition should be modified by complex learning in a manner that much resembles synaptic excitation. Indeed, in a subset of neurons all GABA_A-receptors mediated inhibitory synapses also doubled their strength after learning. Like synaptic excitation, Synaptic inhibition is also enhanced by two-fold increase of the single channel conductance. These findings suggest that crucial learning induces a multiplicative increase in strength of all excitatory and inhibitory synapses in a subset of cells, and that such an increase can serve as a long-term whole-cell mechanism to profoundly enhance an existing Hebbian-type memory. This mechanism does not act as synaptic plasticity mechanism that underlies memory formation but rather enhances the response of already existing memory. This mechanism is cell-specific rather than synapse-specific; it modifies the channel conductance rather than the number of channels and thus has the potential to be readily induced and un-induced by whole-cell transduction mechanisms.     

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.     

Activity dependent protein degradation is critical for the formation and stability of fear memory in the amygdala

Protein degradation through the ubiquitin-proteasome system [UPS] plays a critical role in some forms of synaptic plasticity. However, its role in memory formation in the amygdala, a site critical for the formation of fear memories, currently remains unknown. Here we provide the first evidence that protein degradation through the UPS is critically engaged at amygdala synapses during memory formation and retrieval. Fear conditioning results in NMDA-dependent increases in degradation-specific polyubiquitination in the amygdala, targeting proteins involved in translational control and synaptic structure and blocking the degradation of these proteins significantly impairs long-term memory. Furthermore, retrieval of fear memory results in a second wave of NMDA-dependent polyubiquitination that targets proteins involved in translational silencing and synaptic structure and is critical for memory updating following recall. These results indicate that UPS-mediated protein degradation is a major regulator of synaptic plasticity necessary for the formation and stability of long-term memories at amygdala synapses.     

Interrogating structural plasticity among synaptic engrams

Our daily experiences and learnings are stored in the form of memories. These experiences trigger synaptic plasticity and persistent structural and functional changes in neuronal synapses. Recently, cellular studies of memory storage and engrams have emerged over the last decade. Engram cells reflect interconnected neurons via modified synapses. However, we were unable to observe the structural changes arising from synaptic plasticity in the past, because it was not possible to distinguish the synapses between engram cells. To overcome this barrier, dual-eGRASP (enhanced green fluorescent protein reconstitution across synaptic partners) technology can label specific synapses among multiple synaptic ensembles. Selective labeling of engram synapses elucidated their role by observing the structural changes in synapses according to the memory state. Dual-eGRASP extends cellular level engram studies to introduce the era of synaptic level studies. Here, we review this concept and possible applications of the dual-eGRASP, including recent studies that provided visual evidence of structural plasticity at the engram synapse.     

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.     

Making memories stick: cell-adhesion molecules in synaptic plasticity

Synapses are adhesive junctions highly specialized for interneuronal signalling in the central nervous system. The strength of the synaptic signal can be modified (synaptic plasticity), a key feature of the cellular changes thought to underlie learning and memory. Cell-adhesion molecules are important constituents of synapses, with well-recognized roles in building and maintaining synaptic structure during brain development. However, growing evidence indicates that cell-adhesion molecules also play important and diverse roles in regulating synaptic plasticity and learning and memory. This review focuses on recent advances in understanding the molecular mechanisms through which adhesion molecules might regulate synaptic plasticity.     

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.     

Memory Maintenance in Synapses with Calcium-Based Plasticity in the Presence of Background Activity

Most models of learning and memory assume that memories are maintained in neuronal circuits by persistent synaptic modifications induced by specific patterns of pre- and postsynaptic activity. For this scenario to be viable, synaptic modifications must survive the ubiquitous ongoing activity present in neural circuits in vivo. In this paper, we investigate the time scales of memory maintenance in a calcium-based synaptic plasticity model that has been shown recently to be able to fit different experimental data-sets from hippocampal and neocortical preparations. We find that in the presence of background activity on the order of 1 Hz parameters that fit pyramidal layer 5 neocortical data lead to a very fast decay of synaptic efficacy, with time scales of minutes. We then identify two ways in which this memory time scale can be extended: (i) the extracellular calcium concentration in the experiments used to fit the model are larger than estimated concentrations in vivo. Lowering extracellular calcium concentration to in vivo levels leads to an increase in memory time scales of several orders of magnitude; (ii) adding a bistability mechanism so that each synapse has two stable states at sufficiently low background activity leads to a further boost in memory time scale, since memory decay is no longer described by an exponential decay from an initial state, but by an escape from a potential well. We argue that both features are expected to be present in synapses in vivo. These results are obtained first in a single synapse connecting two independent Poisson neurons, and then in simulations of a large network of excitatory and inhibitory integrate-and-fire neurons. Our results emphasise the need for studying plasticity at physiological extracellular calcium concentration, and highlight the role of synaptic bi- or multistability in the stability of learned synaptic structures.     

Calcium stores and synaptic plasticity

Chemical transmission at central synapses is known to be highly plastic; the strength of synaptic connections can be modified bi-directionally as a result of activity at individual synapses. Long-term changes in synaptic efficacy, both increases and decreases, are thought to be involved in the development of the nervous system, and in ongoing changes in response to external cues such as during learning and addiction. Other, shorter lasting changes in synaptic transmission are also likely to be important in normal functioning of the CNS. Calcium mobilisation is an important step in multiple forms of plasticity and, although entry into neurones from the extracellular space is often the initial trigger for plasticity changes, release of calcium from intracellular stores also has an important part to play in a variety of forms of synaptic plasticity.     

Hippocampal long term potentiation: silent synapses and beyond.

Long-term, activity-driven synaptic plasticity allows neuronal networks to constantly and durably adjust synaptic gains between synaptic partners. These processes have been proposed to serve as a substrate for learning and memory. Long-term synaptic potentiation (LTP) has been observed at many central excitatory synapses and perhaps most extensively studied at Schaffer collaterals synapses onto hippocampal CA1 neurons. Multiple contradictory models were proposed to account for this form of LTP. However, recent evidence suggests that some synapses are initially devoid of functional AMPA receptors which can be incorporated during LTP. This new model appears to account for most, but not all, properties of this form of plasticity. Indeed, several mechanisms seem to act in parallel to specifically enhance AMPA-receptor mediated synaptic transmission.     

Cascade models of synaptically stored memories

Storing memories of ongoing, everyday experiences requires a high degree of plasticity, but retaining these memories demands protection against changes induced by further activity and experience. Models in which memories are stored through switch-like transitions in synaptic efficacy are good at storing but bad at retaining memories if these transitions are likely, and they are poor at storage but good at retention if they are unlikely. We construct and study a model in which each synapse has a cascade of states with different levels of plasticity, connected by metaplastic transitions. This cascade model combines high levels of memory storage with long retention times and significantly outperforms alternative models. As a result, we suggest that memory storage requires synapses with multiple states exhibiting dynamics over a wide range of timescales, and we suggest experimental tests of this hypothesis.     

Integration of biochemical signalling in spines

Short-term and long-term changes in the strength of synapses in neural networks underlie working memory and long-term memory storage in the brain. These changes are regulated by many biochemical signalling pathways in the postsynaptic spines of excitatory synapses. Recent findings about the roles and regulation of the small GTPases Ras, Rap and Rac in spines provide new insights into the coordination and cooperation of different pathways to effect synaptic plasticity. Here, we present an initial working representation of the interactions of five signalling cascades that are usually studied individually. We discuss their integrated function in the regulation of postsynaptic plasticity.     

Synapses and Memory Storage

The synapse is the functional unit of the brain. During the last several decades we have acquired a great deal of information on its structure, molecular components, and physiological function. It is clear that synapses are morphologically and molecularly diverse and that this diversity is recruited to different functions. One of the most intriguing findings is that the size of the synaptic response in not invariant, but can be altered by a variety of homo- and heterosynaptic factors such as past patterns of use or modulatory neurotransmitters. Perhaps the most difficult challenge in neuroscience is to design experiments that reveal how these basic building blocks of the brain are put together and how they are regulated to mediate the information flow through neural circuits that is necessary to produce complex behaviors and store memories. In this review we will focus on studies that attempt to uncover the role of synaptic plasticity in the regulation of whole-animal behavior by learning and memory.The idea that learning results from changes in the strength of the synapse was first suggested by Santiago Ramon y Cajal (1894) based on insights from his anatomical studies. That modulation of synaptic connectivity is a critical mechanism of learning was incorporated into more refined models by Hebb in the 1940s and 1950s. The experimental investigation of these intriguing conjectures required the development of behavioral systems in which one could examine changes in the neuronal components of a specific behavior during or after the modification of that behavior with learning (Kandel and Spencer 1968).