“Brain networks have a remarkable ability to store information in memory, on time scales ranging from seconds to years. Over the last decades, a theoretical scenario has progressively emerged that describes qualitatively the process of information storage and retrieval. In this scenario, sensory stimuli to be memorized drive specific patterns of neuronal activity in relevant neural circuits. These patterns of neuronal activity lead in turn to changes in synaptic connectivity, thanks to synaptic or structural plasticity mechanisms. These changes in synaptic connectivity allow the network to stabilize a specific pattern of activity associated with the sensory stimulus, and they can also allow the network to retrieve this specific pattern, based on partial or noisy cues.”

“Somewhere in the skull, between the locus of the fully pre-processed stimulus and before the beginning of a generation of a response, there must be stations storing, passively, many memories. Those are the things we know and remember. They are, most likely, stored in the synaptic structure of each station.”

“Hebbian plasticity, as represented by long-term potentiation (LTP) and long-term depression (LTD) of synapses, has been the most influential hypothesis to account for encoding of memories. The evidence for the physiological relevance of LTP is indisputable.”

“Memory is the canvas upon which we paint the portrait of our lives, and research in the past half-century has provided tremendous insight into this canvas. We now know that the consolidation of long-term memories requires synaptic plasticity; that this plasticity depends on key molecular signaling cascades; and that these cascades serve to strengthen particular synaptic connections to consolidate memories in discrete brain networks.”

“We present a framework for understanding how the hippocampus, neocortex, and basal ganglia work together to support cognitive and behavioral function in the mammalian brain… [A]ny given memory is encoded in synapses distributed throughout the entire system, and all areas participate in some way in representing most memories.”-

“Perhaps the most striking finding in the cell biology of memory is that the consolidation and long-term storage of memory involves transcription in the nucleus and structural changes at the synapse. These structural components of learning-related synaptic plasticity can be grouped into two general categories: (1) remodeling and enlargement of preexisting synapses, and (2) alterations in the number of synapses, including both the addition and elimination of synaptic connections.”

“The classic view is that items are embedded in long term memory via specific synaptic modifications, and presentation of these items leads to activation of stable activity patterns in the network (‘attractors’).”

“Excitatory synapses on dendritic spines of hippocampal pyramidal neurons have a wide range of sizes. Anatomical measurements of the spine size, the area of the postsynaptic density (PSD), the number of AMPA receptors, the area of the presynaptic active zone and the number of docked vesicles in the presynaptic terminal are all highly correlated with each other and with physiological measurements of the release probability and the efficacy of the synapse. Thus, each of these individual characteristics is a correlate of synaptic strength.”

“Alterations in neuronal morphology especially of dendritic spines have been suggested to underlie the formation of memory and their stabilization the maintenance of memory. In this review we show evidence indicating that changes in actin cytoskeleton subserves spine morphogenesis induced by learning and that preserving these actin cytoskeleton alterations is involved in maintaining spine morphology and memory for a long period of time.”

“Among the insights attributed to Hebb are the notions that memories of sensory experiences are stored by synaptic modifications, and that these changes occur in the same regions of the brain that are used to process sensory information. Thus, memories of visual experiences would be stored in visual cortex, auditory experiences would be stored in auditory cortex, and so on. Within each of these regions of cortex, memory of a sensory event would result from the permanent modification of the synapses between the cortical neurons that are activated by that event.”

“Enhancement of synaptic efficacy is investigated via long-term potentiation (LTP), which is widely thought to involve the same cellular mechanisms as those engaged during learning and memory.”

“[I]n vivo time-lapse imaging of dendritic spines in the cerebral cortex suggests that, although spines are highly plastic during development, they are remarkably stable in adulthood, and most of them last throughout life. Therefore, dendritic spines may provide a structural basis for lifelong information storage, in addition to their well-established role in brain plasticity.”-

“Learning is primarily mediated by activity-dependent modifications of synaptic strength within neuronal circuits.”

“Using EM jointed with gold immunolabeling it has been shown that PSD area is proportional to the overall number of AMPA and NMDA receptors, however the relationship for AMPA receptor subunit GluR1 has been reported to be supralinear. Moreover, small PSDs (<180 nm in diameter) typically have no AMPA receptors and can be considered silent synapse. Thus, PSD area can be treated as a readout of synaptic strength.”

“There is a positive correlation between the spine head volume, the PSD area, the presynaptic active zone area, the number of AMPA-type glutamate receptors, and the synaptic strength. These correlations suggest that spine structure is tightly coupled to synaptic function.”

“[The] ability of synapses to individually change their structure and composition in a long-lasting way is an essential mechanism for synaptic plasticity and represents the cellular basis of learning and memory.”-

“Mushroom spines have larger postsynaptic densities (PSDs), which anchor more AMPA glutamate receptors and make these synapses functionally stronger. Mushroom spines are more likely than thin spines to contain smooth endoplasmic reticulum, which can regulate Ca2+ locally, and spines that have larger synapses are also more likely to contain polyribosomes for local protein synthesis. Furthermore, large but not small spines have perisynaptic astroglial processes, which can provide synaptic stabilization and regulate levels of glutamate and other substances. These features suggest that mushroom spines are more stable ‘memory spines’.

“Structural synaptic plasticity is thought to be an essential feature of long-term potentiation (LTP), a cellular mechanism of learning and memory.”

“Release probability (p) is a fundamental presynaptic parameter which is critical in defining synaptic strength… Here we outline a powerful methodology based on using FM-styryl dyes, photoconversion and correlative ultrastructural analysis in dissociated hippocampal cultured neurons, which provides both a direct readout of p as well as nanoscale detail on synaptic organization and structure…. Previous studies have revealed a positive correlation between p and the size of the readily releasable pool determined by fluorescence measurements, and between the readily releasable pool size and the number of anatomically docked vesicles, established ultrastructurally. This implies that p and the number of docked vesicles should be related and our findings here provide direct support for this, revealing a significant positive correlation between these parameters.”

“Today, it is generally accepted that the neurobiological substrate of memories resides in activity driven modifications of synaptic strength and structural remodeling of neural networks activated during learning.”

“This suggests synaptic connectivity in cortex is optimized to store a large number of attractor states in a robust fashion.”

“Recent studies have provided long-sought evidence that behavioural learning involves specific synapse gain and elimination processes, which lead to memory traces that influence behaviour.”

“The substrate of LTM [long-term memory] is persistent or lasting synaptic change, according to the central dogma of neuroscience, which dates back to Ramón y Cajal and others. Indeed in experiments, LTM is associated with stable changes in synaptic weights and structure…”

“Among all the different types of synapses, glutamatergic synapses are the predominant excitatory synapse in mammalian brain. Much is known about their composition, development, maturation, physiology, elimination and dysregulation. Glutamatergic synapses are subjected to constant bidirectional changes in response to external stimuli or environmental cues. This is termed synaptic plasticity, which is considered the molecular basis underlying many brain functions, such as learning and memory.”

“In layer 2/3 pyramidal neurons of the mouse visual cortex, GCaMP6 reliably detected single action potentials in neuronal somata and orientation-tuned synaptic calcium transients in individual dendritic spines… Orientation tuning averaged across spine populations predicted the tuning of their parent cell.”

“The human brain consists of 10^11 neurons connected by 10^15 synapses. This awesome network has a remarkable capacity to translate experiences into vast numbers of memories, some of which can last an entire lifetime. These long-term memories survive surgical anaesthesia and epileptic episodes, and thus must involve modifications of neural circuits, most likely at synapses.

“Memory resides in engram cells distributed across the brain… We found an increased number and size of spines on CA1 engram cells receiving input from CA3 engram cells… These results indicate that enhanced structural and functional connectivity between engram cells across two directly connected brain regions forms the synaptic correlate for memory formation.”

“One remarkable feature of the brain is to encode and store new information continuously without disrupting previously acquired memories. It is believed that experience-dependent changes in synaptic strength are crucial for information storage in the brain.”

“[T]he collective work of numerous authors have shown that dendritic spines are the major targets of excitatory connections in the cerebral cortex and that they seem to be key elements in learning, memory, and cognition”

“It is widely believed that changes in synaptic strength through Hebbian plasticity form the cellular basis of learning and memory… A primary mechanism in the control of synaptic strength during plasticity is an alteration in the number, composition, and biophysical properties of AMPAtype glutamate receptors (AMPARs) in the postsynaptic membrane.”

“These properties strongly suggest that the information coding in the cerebral cortical areas are established by the unsupervised learning paradigm in which the activity is determined by a relaxation dynamics and the synapses are update by a Hebbian rule.”-

“ ‘Synaptic consolidation’ (also cellular consolidation, local consolidation) refers to the post-encoding transformation of information into a long-term form at local synaptic and cellular nodes in the neural circuit that encodes the memory. The current central dogma of synaptic consolidation is that it involves stimulus (‘‘teacher’’)-induced activation of intracellular signaling cascades, resulting in posttranslational modifications, modulation of gene expression and synthesis of gene products that alter synaptic efficacy.”

“Long-term memories are believed to be stored in the connections of cortical neuronal networks. While it is often assumed that the synaptic connectivity remains stable after memory formation, there is an increasing body of evidence that connectivity changes substantially on a daily basis… Here, we show that the combination of structural plasticity, synaptic plasticity and self-generated reactivation, even for a just short period every day, can not only stabilize assemblies against synaptic turnover but even enhance their connectivity and associative memory.”

“Recent work shows that during engram formation, there is a specific increase in synapses between ‘engram cells’… The general picture emerging from this work is that engrams can differ in their degree of accessibility and that changes in accessibility reflect underlying changes in synaptic organization.”

“We revisit our quantitative analysis of synaptic AMPAR by highly sensitive freeze-fracture replica labeling in eight different [synapse types]. All of these connections showed linear correlation between synapse size and AMPAR number indicating a common intra-synapse-type relationship in CNS synapses.”

“The acquisition of memory basically consists in the modulation of synaptic contacts between nerve cells. …[T]he empirical evidence thus far indicates that, in humans and nonhuman primates, memory is stored in overlapping and widely distributed networks of interconnected cortical neurons. Because cortical connectivity can serve practically infinite potential associations, potential networks are practically infinite, and this fact confers uniqueness to the cognitive memory of a given individual.”

“It is clear that the structural plasticity of dendritic spines is related to changes in synaptic efficacy, learning and memory and other cognitive processes.”

“Long-lasting changes in the synaptic connectivity between neurons are generally accepted to be crucial for the establishment and maintenance of memories.”

“We found that Arc-expressing neurons have enhanced intrinsic excitability and are preferentially recruited into newly encoded memory traces… [T]hese results establish a model of fear memory formation in which intrinsic excitability determines neuronal selection, whereas learning-related encoding is governed by synaptic plasticity.”

“In young mice, within the ‘critical period’ for visual cortex development, ~73% of spines remain stable over a one-month interval. In contrast, in adult mice, the overwhelming majority of spines (~96%) remain stable over the same interval with a half-life greater than 13 months. These results indicate that spines, initially plastic during development, become remarkably stable in the adult, providing a potential structural basis for long-term information storage.”

“The formation and elimination of dendritic spines are the basis for structural remodeling of neuronal networks and take place in response to experience and learning… We found that the spine density in stratum radiatum (~1.1 per micrometer) remained stable over weeks. However, a small fraction (3.4%) of spines were formed and eliminated between imaging sessions, which demonstrated that spines of CA1 neurons exhibit structural plasticity in adult mice.”

By now, LTP is considered as one of the fundamental cellular mechanisms for memory storage in the brain… With the application of advanced research tools in neuroscience, direct evidences gradually emerged and showed that LTP and synaptic plasticity were sufficient and required for the encoding and recall of memory…”

“As formalized by Morris and colleagues, the synaptic plasticity and memory (SPM) hypothesis states that the modification of the pattern of synaptic connections mediated by synaptic plasticity is the mechanism whereby the brain stores memory… In bridging the two different theories of memory (engram cells and SPM), a straightforward prediction is that synaptic plasticity in a subset of neurons (engram cells) underpins memory… In the last decade, accumulating evidence has indicated synaptic plasticity in engram cells as a potential mechanism supporting memory.”-

“Synaptic plasticity is the cellular basis of learning and memory… In the majority of excitatory synapses in the mammalian brain, axonal boutons contact with dendritic spines, and the size of the dendritic spines correlates strongly with the excitatory postsynaptic response. Many spines are maintained for a long period of time and probably play critical roles in lifelong memory storage.”

“Using two-photon uncaging of glutamate to stimulate single, identified dendritic spines, Noguchi et al. confirm and extend previous findings showing that both AMPA and NMDA currents scale linearly with spine head size…. A short burst of stimulation, typically inducing LTP, shifts the equilibrium of F-actin/G-actin toward F-actin. The increased amount of postsynaptic F-actin enlarges the postsynaptic spine and provides a binding site for other proteins.”

“Dendritic spines are the major loci of synaptic plasticity and are considered as possible structural correlates of memory… [O]ur results demonstrate that a newly acquired motor skill depends on the formation of a task-specific dense synaptic ensemble.”

“How can a delayed reward gate plasticity in synapses that were transiently activated by the predictive stimulus? A theoretical solution proposed decades ago to bridge the temporal gap between stimulus and reward, the so-called credit assignment problem, is the notion that neural activity generates silent and transient ‘‘synaptic eligibility traces’’ that can be transformed into long-term changes in synaptic strength by reward-linked neuromodulators… We have provided direct physiological support for the theoretical concept of synaptic eligibility traces. We demonstrate that there are two eligibility traces, one for LTP and one for LTD, with different dynamics. The transformation of these transient traces into synaptic plasticity is accomplished by specific monoamine receptors that are anchored at the synapse.”

“Dendritic spines are the most important postsynaptic compartment of excitatory neurons in the brain and are essential for synaptic transmission and plasticity. Stubby spines are thought to represent an immature type, as they tend to disappear during development, while mushroom spines are the ones responsible for information transmission and learning in the adult… [I]maging at super-resolution more than 100 proteins in dendritic spines, spanning many important protein classes… We found that the two spine classes are very similar on average, but that the composition of the mushroom spines correlates much more strongly to synaptic strength.”

“Sensation, action and even our personal memories are produced by connected neurons in distributed neural pathways that transduce outward experiences into perception, give rise to memories and allow us to act on the world in adaptive ways… [T]echnical advances have allowed researchers to dissect with unprecedented precision the contribution of neural circuits and cellular coding to behavioral learning and memory… From many studies, it has become clear that auditory thalamic and cortical synapses onto [lateral nucleus of the amygdala] neurons are strengthened during fear learning.”-

“Considerable evidence supports long-term potentiation (LTP) as a key cellular mechanism that underlies learning and memory… Our findings demonstrate for the first time that, in addition to enhancing the efficacy of preexisting synapses, LTP-inducing stimuli promote the transition of nascent spines from a short-lived, transient state to a longer-lived, persistent state.”

“It is generally believed that changes in the synaptic connections between neurons play a major role in learning and memory formation. While short-term memory might rely mainly on the strengthening and weakening of pre-existing synapses, long-term storage of information is thought to require structural reorganization of neuronal networks, the formation of new synapses and the loss of existing connections.”

“We find a linear relationship between synapse size and strength, providing the missing link in assigning physiological weights to synapses reconstructed from electron microscopy.”

“Long-term memory consolidation is thought to involve long-lasting changes in the efficacy of pre-existing synaptic connections, as well as formation of new synapses and elimination of pre-existing synapses.”-

“[T]here is increasing evidence that experience dependent plasticity of specific circuits in the somatosensory and visual cortex involves cell type-specific structural plasticity: some boutons and dendritic spines appear and disappear, accompanied by synapse formation and elimination, respectively”

“With the application of the latest research tools, direct evidence shows that structural plasticity of the dendritic spines is required for the recall of memory… There is a strong positive correlation among the spine head size, the postsynaptic density (PSD) area, the presynaptic active zone area, and the amplitude of AMPA receptor-mediated excitatory postsynaptic currents (EPSCs) recorded in the spine.”

“Here, using STED imaging, we demonstrate that spine synapses in vitro and in vivo are composed of discrete, aligned pre- and postsynaptic protein nanomodules of uniform size, whose number, not size, scales with the size of dendritic spines.”

“Since their early characterization by Ramon y Cajal, dendritic spines have been demonstrated to undergo changes in size, density and shape, and they are postulated to underlie the anatomical locus of plasticity. The size of a dendritic spine has long been considered a proxy for synaptic strength, as it is proportional to the size of its postsynaptic density (PSD) and number of glutamate receptors that, in large part, define the efficacy of synaptic transmission. Indeed, large PSDs and spines have been observed to contain more AMPA and NMDA receptors than small ones.”

“[W]e determine the organization of excitatory synaptic inputs responding to different locations in the visual scene by mapping spatial receptive fields in dendritic spines of mouse visual cortex neurons using two-photon calcium imaging… [T]he connectivity between neurons with displaced receptive fields obeys a specific rule, whereby they connect preferentially when their receptive fields are co-oriented and co-axially aligned. This organization of synaptic connectivity is ideally suited for the amplification of elongated edges, which are enriched in the visual environment, and thus provides a potential substrate for contour integration and object grouping.”

“[A]n emerging concept is that a given memory is supported by an engram complex, composed of functionally connected engram cell ensembles dispersed across multiple brain regions, with each ensemble supporting a component of the overall memory.

“Memories are thought to be encoded as enduring physical changes in the brain, or engrams. Most neuroscientists agree that the formation of an engram involves strengthening of synaptic connections between populations of neurons”

“Synaptic plasticity, the activity dependent change in synaptic strength, forms the molecular foundation of learning and memory. Synaptic plasticity includes structural changes, with spines changing their size to accommodate insertion and removal of postynaptic receptors, which are correlated with functional changes.”

“One of the chief ideas we shall develop in this book is that the specificity of the synaptic connections established during development underlie perception, action, emotion, and learning.”

“Spines with large heads are stable, express large numbers of AMPA-type glutamate receptors, and contribute to strong synaptic connections. By contrast, spines with small heads are motile and unstable and contribute to weak or silent synaptic connections. …Recent progress in biophysical techniques and molecular biology has provided insight into the structurefunction relationships of dendritic spines in the cerebral cortex, as well as support for the century-old hypothesis that spine structure is the basis for memory in the brain.”

“[G]lutamate uncaging has demonstrated the tight correlation between the spine-head size and the functional expression of fast AMPA-type glutamate receptors (AMPARs), a major determinant of synaptic weight. The results agree with electron microscopy studies showing that the spine-head sizes are proportional to PSD area and AMPAR contents, while a recent study reported a direct correlation between synaptic strength and ultrastructure. These findings imply that structural alterations are inevitably associated with functional modifications. Moreover, given their nature, structural alterations are probably the most likely means for implementing long-lasting functional modifications.”

“Using a combined approach of neural activity-dependent behavioral labeling, optogenetic stimulations, and electrophysiological recordings, we found that postsynaptically expressed LTP was induced selectively in the CS-specific ACx/MGN-LA pathways after auditory discriminative fear conditioning in mice, whereas LTP was not detected in randomly selected ACx/MGN-LA pathways. Moreover, optogenetically induced depotentiation of the CS-specific ACx/MGN-LA pathways prevented the recall of fear memory for the auditory CS. Thus, input-specific LTP in the LA could contribute to fear memory specificity, enabling adaptive fear responses only to the relevant sensory cue.”

“When an episode is encoded, different brain areas host components of the experience, for instance, the faces and voices one encounters in the context of a scientific meeting. The hippocampus is assumed to bind these components into one unique episodic memory. Consequently, the memory starts out highly dependent on the hippocampus. During sleep, the hippocampal neuronal representation is repeatedly reactivated, with these reactivations propagating across the associated memory network and simultaneously reactivating its distributed neocortical components. Synaptic consolidation processes triggered by this coactivation strengthen the memory representations in the neocortex and thus allow the slowly learning neocortex to integrate them into pre-existing long-term memories.”

“The dorsal striatum… receives convergent excitatory afferents from cortex and thalamus and forms the origin of the direct and indirect pathways, which are distinct basal ganglia circuits involved in motor control. It is also a major site of activity-dependent synaptic plasticity. Striatal plasticity alters the transfer of information throughout basal ganglia circuits and may represent a key neural substrate for adaptive motor control and procedural memory.”

“Synaptic plasticity is the fundamental cellular correlate of learning. By the strengthening and weakening of specific connections, information processing in the brain is changed and memories are formed… The expression of LTP in a single synapse is measured by quantifying the increase in uEPSC amplitude and/or in spine size, which are highly correlated with one another.”

“Synaptic plasticity is generally accepted as the principal implementation of information storage in neural systems.”

“Networks of strongly connected neurons form the physical trace of declarative, non-declarative and emotional memories as well as habits, sensory associations and motor function… Indeed, in vivo visualization of specific synapses modified by a learning event has recently been achieved. The engram is therefore dependent upon mechanisms which can selectively enhance and refine the synaptic connectivity of neurons.”

“Much evidence indicates that, after learning, memories are created by alterations in glutamate-dependent excitatory synaptic transmission. These modifications are then actively stabilized, over hours or days, by structural changes at postsynaptic sites on dendritic spines.”

“Synapses have long been thought to hold the biological correlates of memory, called ‘memory engrams’. Extensive evidence has shown that the formation of new memories corresponds to morphological changes in dendritic spines—small, specialized compartments containing most of the excitatory post-synaptic structure.”

“The bottom line of this book is ‘You are your synapses’… Given the importance of synaptic transmission in brain function, it should practically be a truism to say that the self is synaptic. What else could it be?”

“[P]hysiological evidence indicates that the changes during long-term potentiation are both pre- and postsynaptic. Similarly, several lines of anatomical evidence suggest that plasticity affects the structure of both the pre- and postsynaptic elements. The detailed registration of structures across the synapse and the physical linkage between pre- and postsynaptic elements suggest a ‘structural unit hypothesis’ for coordinating pre- and postsynaptic modifications.”

“[The] predicate… of all modern neuroscience is that cognitively important functions can be explained as an emergent property of neurons and their network connections.”

“The connection between LTP and memory is now supported by multiple lines of evidence… [A]nalysis of LTP has shown that it enables the storage of vast amounts of information. Each of the over 10,000 synapses on a cell can be modified by LTP in a synapse-specific manner. Gradations in synaptic strength vary over a 10-fold range (~ 3 bits of information). Therefore, if one considers just the CA3 region of the hippocampus, a region strongly implicated in episodic memory, the 3 million CA3 pyramidal cells in humans contain about 30 billion synapses, thus making the storage of 100 billion bits of information possible.”

“[R]ecent evidence using super-resolution microscopy has revealed that synapses are composed of stereotyped nanoclusters of AMPA receptors and scaffolding proteins; furthermore, synapse size varies linearly with the number of nanoclusters… [A]nalysis of EM images suggests that the growth of a synapse involves an expansion of both the PSD and a presynaptic structure called the presynaptic grid. These two structures are exactly in register and covary in size over a large size range. Thus, growth of a synapse is a trans-synaptic process… This leads us to the conclusion that synapses may grow by quantal addition of trans-synaptic modules”

“[I]t is thought that the ability to store memories for long periods of time depends on the stability of specific patterns of synaptic connections… Turnover characterized by a power law implies that despite substantial spine elimination, a considerable fraction of spines will last for a long period of time. For example, according to the power law model with γ=1.384, half of the spines that were present throughout the experiment (lifetime >20 days) were expected to survive for at least another 110 days. Indeed, there is direct experimental evidence for spines in mouse neocortex that are stably maintained for more than a year.”

“In the quest for the physical substrate of learning and memory, a consensus gradually emerges that memory traces are stored in specific neuronal populations and the synaptic circuits that connect them.”

“Presently, there is substantial evidence supporting the Synaptic PlasticityMemory (SPM) hypothesis in relation to the mechanisms underlying the acquisition, retention, and extinction of conditioned fear memory… The mechanisms of synaptic plasticity in fear circuits… satisfy all four SPM criteria—detectability, anterograde alteration, retrograde alteration, and mimicry… The reviewed findings, accumulated over the last two decades, provide support for both necessity and sufficiency of synaptic plasticity in fear circuits for fear memory acquisition and retention…”

“From a neural circuit point of view, learning is a process to transform a neural network to adapt to the environment, and memory is the state of maintaining such a network… Various forms of synaptic plasticity, the persistent change in synaptic efficacy, are widely believed to be the cellular substrate underlying learning and memory. Among them, long-term potentiation (LTP) and long-term depression (LTD), two opposite forms of synaptic plasticity, have been studied most extensively. LTP and LTD were initially discovered by electrophysiological recording, but subsequent research has revealed accompanying morphological changes in dendritic spines.”

“Understanding the ultra-structure of dendritic spines is a crucial step in determining the synaptic strength or efficiency of a synapse… The head is the most critical part of spine, due to its abundance of most of the neurotransmitter receptors and signaling molecules that are required for synaptic transmission. The outer surface of spine head is composed of several receptors, adaptor and cytoskeletal proteins, including numerous signaling molecules involved in synaptic plasticity. In general, scientists believe that a larger spine head means stronger synaptic contacts.”

“Technical advancements in optogenetics and in vivo recordings have uncovered the causal nature of [the cellular mechanisms that underlie learning and memory] in unprecedented detail: behavioural learning results in alterations of synapse strength, and manipulating synapse strength alters information stored in memory. In rodent brain, memories are encoded by relatively small populations of neurons, the activation of which are both necessary and sufficient for memory retrieval. Synaptic connections between neurons that are part of a memory engram are more common and stronger than connections with neurons not part of the engram. Strengthening of synapses by mechanisms of synaptic plasticity contributes to both the formation of memory engrams and their reactivation during memory recall.”

“It is widely believed that encoding and storing memories in the brain requires changes in the number, structure, or function of synapses. … This axiomatic view that synaptic plasticity is critical for learning and memory is supported by data derived from many different memory systems, neural circuits, and molecular pathways mediating an array of different behaviors.”

“With a remarkable amount of prescience, Ramon y Cajal also speculated that memories were stored as increases in the numbers of connections between neurons. This idea forms the basis of learning-related synaptic plasticity—the idea that memories are stored as changes in the number and strength of synapses between neurons—a framework that has endured as a model for understanding the biology of memory.”

“Changing the strength of connections between neurons is widely assumed to be the mechanism by which memory traces are encoded and stored in the central nervous system… We conclude that a wealth of data supports the notion that synaptic plasticity is necessary for learning and memory…”

“Our data indicate that distribution of functional AMPA receptors is tightly correlated with spine geometry and that receptor activity is independently regulated at the level of single spines.”

“Dendritic spines of pyramidal neurons in the cerebral cortex undergo activity-dependent structural remodeling that has been proposed to be a cellular basis of learning and memory… Our results thus indicate that spines individually follow Hebb’s postulate for learning. They further suggest that small spines are preferential sites for long-term potentiation induction, whereas large spines might represent physical traces of long-term memory.”

“The central nervous system functions primarily to convert patterns of activity in sensory receptors into patterns of muscle activity that constitute appropriate behavior. At the anatomical level this requires two complementary processes: a set of genetically encoded rules for building the basic network of connections, and a mechanism for subsequently fine tuning these connections on the basis of experience. Identifying the locus and mechanism of these structural changes has long been among neurobiology’s major objectives. Evidence has accumulated implicating a particular class of contacts, excitatory synapses made onto dendritic spines, as the sites where connective plasticity occurs.”

“We now understand in considerable molecular detail the mechanisms underlying long-term synaptic plasticity and the importance that such plastic changes play in memory storage, across a broad range of species and forms of memory. One surprising finding is the remarkable degree of conservation of memory mechanisms in different brain regions within a species and across species widely separated by evolution.”

“Evidence that drugs can selectively block either short-term (seconds to hours) or long-term memory (hours to months) suggests that time-dependent stages of memory are based on independent processes acting in parallel. Later stages of consolidation resulting in memory lasting a lifetime likely involve interaction of brain systems in reorganizing and stabilizing distributed connections.”

“The remarkable competence of the nervous system to adapt, learn, and form memories is considered to be based on activity-dependent modifications of synaptic connections. It is by now well established that functional activity-dependent changes are paralleled by structural alterations… Subsynaptic structures such as bouton, active zone, postsynaptic density (PSD) and dendritic spine, are highly correlated in their dimensions and also correlate with synapse strength.”

“[S]ynaptic plasticity has been considered as the experimental paradigm most likely to provide us with an understanding of how information is stored in the vertebrate brain. Various types have been demonstrated over these past 45 years, most notably long-term potentiation and long-term depression, and their established characteristics as well as their induction and consolidation requirements are highly indicative of this plasticity being the substrate for skills acquisition and mnemonic engraving.”

“The connectivity patterns among neurons are a key determinant of brain computations.”

“Memories are believed to be stored as long-lasting structural changes in synapses. We tested the hypothesis that formation of a tone-shock association induces changes in the mouse auditory cortex by combining chronic in vivo imaging of dendritic spines with auditory fear conditioning. We find that memory formation is correlated with a transient increase in spine formation that leaves a long-lasting trace in the network.”

“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… During learning, spatio-temporal patterns of neural activity that represent events cause long-lasting changes in the strength of synaptic connections within the brain. Later reactivation of these altered connections causes patterns of cell firing that collectively constitute the experience of memory for these events or the expression of learned changes in behaviour triggered by them. These statements are the essence of the SPM hypothesis.”

“[A]ccumulating evidence indicates that induction of plasticity is… associated with an important structural reorganization of synaptic connectivity… This structural synaptic reorganization has strong potential implications for our understanding of brain development and learning and memory mechanisms and suggests notably that structural modifications of brain circuits could represent the substrate of acquired new skills and of long-lasting memory traces.”

“It has been proposed that memories are encoded by modification of synaptic strengths through cellular mechanisms such as long-term potentiation (LTP) and long-term depression (LTD)… [W]e have engineered inactivation and reactivation of a memory using LTD and LTP, supporting a causal link between these synaptic processes and memory.”

“[S]imple and informative relationships have been uncovered between the sizes of dendritic spines and anatomical parameters thought to be related to synaptic strength. Spine volumes are proportional to the areas of PSDs. Immunogold labeling studies have shown that the density of AMPA and NMDA receptors is constant within the PSD, and thus the number of receptors per synapse is proportional to PSD area and spine volume. On the presynaptic side, the area of the active zone is proportional to PSD area. In addition, the area of the active zone is proportional to the number of docked vesicles (45), which is a good correlate of the quantity of neurotransmitter release per action potential. Thus in terms both of transmitter release and postsynaptic sensitivity, large spines are the sites of strong synapses.”

“The structural plasticity of dendritic spines is considered to be essential for various forms of synaptic plasticity, learning, and memory.”

“Automated 3-D mapping of glutamate sensitivities demonstrated that expression of functional AMPA-type glutamate receptors was stable over many minutes, and is proportional to the spine volume in adult pyramidal neurons in vivo”

“Synaptic plasticity is a cellular mechanism putatively underlying learning and memory… [W]e have demonstrated that presynaptic potentiation occurs specifically in neurons that are recruited into a fear memory trace. This synaptic plasticity likely contributes to the ensemble reorganization, an event that positively correlated with the strength of fear memory expression.”

“Coincident activation of neurons results in a strengthening in synaptic efficacy between those neurons. These sets of neurons become wired together through enhanced synaptic efficacy. This mechanism is thought to underlie the generation of a neuronal ensemble that encodes a particular memory.”

“We observed bidirectional changes in LA [lateral amygdala] synapse size corresponding to the value of a fear association, confirming that learning is indeed reflected in synaptic ultrastructure in intact adult animals.”

“Principle 7 (Synaptic weights encode knowledge, and adapt to support learning): Synaptic inputs vary in strength as a function of sender and receiver neuron activity, and this variation in strength can encode knowledge, by shaping the pattern that each neuron detects. There is now copious empirical evidence supporting this principle and it can probably be considered uncontroversial in the neuroscience community at this point.”

“[E]verything you know is encoded in the patterns of your synaptic weights…”

“The physical changes underlying learning and memory likely involve alterations in the strength and/or number of synaptic connections.”

“There is now general consensus that persistent modification of the synaptic strength via LTP and LTD of pre-existing connections represents a primary mechanism for the formation of memory engrams… There is a clear consensus on where the memory engram is stored—specific assemblies of synapses activated or formed during memory acquisition…”

“Donald Hebb posited a physiological correlate for learning and recollection: The process of learning strengthens the connections, or synapses, between neurons, which leads to the development of brain-wide cell assemblies that undergo changes in their structural and functional connectivity… The advances in modulating memories in mice have been extraordinary: Researchers have been able to visualize stable neural correlates of memory, to allocate and erase a specific memory, to reactivate a memory, to temporarily inhibit a memory, to connect and create artificial memories and spatial maps, and to bring back memories once thought to be lost to amnesia.”

“We present evidence that neuronal structural changes, i.e., dendritic spine growth, develop sequentially in the hippocampus and anterior cingulate cortex during the formation of recent and remote contextual fear memory… These findings reveal that gradual structural changes modifying connectivity in hippocampalcortical networks underlie the formation and expression of remote memory, and that the hippocampus plays a crucial but time-limited role in driving structural plasticity in the cortex.”

“[S]tudies show that forms of synaptic strengthening thought to underlie learning are accompanied by an increase in the stability, number and size of dendritic spines, which are the major sites of excitatory synaptic transmission in the vertebrate brain.”

“Ultrastructural studies have shown a correlation between the size of the PSD, the spine head volume and the number of vesicles in presynaptic terminals in CA1 pyramidal neurons, cerebellar Purkinje cells and in the olfactory cortex. These results led to the idea of a causal link hypothesis between spine structure and the function of spine synapses. This was further supported by studies of calcium dynamics in spines, which revealed a close relationship between spine morphology and function. Later, by using glutamate uncaging on single spines, it was demonstrated that spine morphology—mushroom compared with thin spines—correlates directly with the number of AMPA receptors, and that the spineneck geometry is an important determinant of NMDA receptor-dependent calcium signaling in spine heads and dendritic shafts. Furthermore, there is evidence that the induction of long-term potentiation (LTP) correlates with spine enlargement.”

“The evidence that CaMKII can serve as a molecular memory now opens the door to addressing the relationship of CaMKII to other major problems in memory research. Recent work shows that late LTP involves trans-synaptic enlargement of synapses. Thus, a key question for future investigation is to understand how CaMKII could organize this enlargement.

“The selectivity of neuronal responses arises from the architecture of excitatory and inhibitory connections… We have revealed a precise spatial patterning of excitatory and inhibitory connections to L2/3 [primary visual cortex] neurons, which can strengthen orientation tuning and establish direction selectivity…”

“These findings suggest that memory engrams are formed as stable and persistent connectivity patterns that connect sparse ensemble across relevant brain regions.”-

“Ever since their first detection by Ramon y Cajal, dendritic spines have been postulated to underlie the neuronal locus of plasticity, where short-term alterations in synaptic strength are assumed to be converted to long-lasting memories that are embedded in stable morphological changes.”

“[W]e measure the strengths of functionally characterized excitatory inputs contacting single pyramidal neurons in ferret primary visual cortex by combining in vivo two-photon synaptic imaging and post hoc electron microscopy. Using electron microscopy reconstruction of individual synapses as a metric of strength, we find no evidence that strong synapses have a predominant role in the selectivity of cortical neuron responses to visual stimuli. Instead, selectivity appears to arise from the total number of synapses activated by different stimuli.”

“Long term memory has always been intuitively associated with morphological changes in the brain. Ever since their first description by Ramon Y Cajal, dendritic spines have been demonstrated to undergo significant changes in size, density and shape, relative to other organelles, and consequently they have been postulated to underlie the anatomical locus of plasticity. Thus, short term dynamic alterations in synaptic strength are assumed to be converted to long lasting stable morphological changes which underlie the ‘memory trace’.”

“Long-term potentiation (LTP) at excitatory synapses is thought to be the basis of learning and memory… [LTP] events cause long-lasting spine enlargement called structural LTP and functional LTP associated with accumulation of AMPA-type glutamate receptors in the PSD… The necessity of CaMKII for LTP has been extensively studied… However, it has been impossible to explore the sufficiency of CaMKII. We describe a new genetically encoded single-molecule-type paCaMKII [photoactivatable CaMKII], which can be activated in single spines using two-photon excitation. paCaMKII activation is sufficient to induce synaptic plasticity at the single synapse level both in vitro and in vivo…”

“Excitatory synapses can undergo long-lasting increases in synaptic strength in response to short periods of elevated activity. This process, known as long-term potentiation (LTP), is thought to underlie the formation of memories at the cellular level… These changes are typically associated with both ultrastructural changes in synapses and functional enhancements of glutamate receptors.”

“[I]n the last 10 years findings from this field have provided key contributions towards establishing the idea that stable, long-lasting changes in synaptic function underlie learning and memory.”

“LTP correlates with structural remodeling at synapses… including persistent enlargement and stabilization of postsynaptic dendritic spines. Spine volume and synaptic weight are positively correlated.”-

“Most neuroscientists believe that memories are encoded by changing the strength of synaptic connections between neurons… The great success of deep learning systems based on units connected by modifiable synaptic weights has greatly increased the confidence that this type of computational structure is a powerful paradigm for learning.”

“Systems consolidation is typically, and accurately, described as the process by which memories, initially dependent on the hippocampus, are reorganized as time passes. By this process, the hippocampus gradually becomes less important for storage and retrieval, and a more permanent memory develops in distributed regions of the neocortex… It has been proposed that consolidation occurs specifically during NREM [“non”rapid eye movement] sleep… “replay,” the reactivation of patterns of network activity that had occurred during previous experience and that are thought to lead to potentiation of relevant synaptic connections in the cortex. Replay starts in the hippocampus and propagates to the cortex…”

“Synapses on spines of principal neurons are a major locus of memory formation and maintenance in cortical circuits. To serve this function, spine synapses… must be dynamic to change during learning and experience and simultaneously exhibit features of long-term persistence to maintain memory traces.”

“The formation, stabilization, and elimination of neural connections are thought to be critical for learning… Spine size is correlated with synaptic strength, and spine addition and elimination contribute to the refinement of neural networks during development and throughout adulthood.

Changes in synaptic connectivity patterns through the formation and elimination of dendritic spines may contribute to structural plasticity in the brain. We characterize this contribution quantitatively by estimating the number of different synaptic connectivity patterns attainable without major arbor remodeling. This number depends on the ratio of the synapses on a dendrite to the axons that pass within a spine length of that dendrite. We call this ratio the filling fraction… This number places an upper bound on the plasticity potential, or memory capacity, associated with the formation and elimination of dendritic spines.”-

“The hippocampus also expands because memories are stored by strengthening synapses, which require them to enlarge.”- (Chapter 14)

“The obvious site to compactly store information is at the synapse. Storage occurs by changing its transfer “weight,” that is, its ability to excite or inhibit a postsynaptic neuron. Since the synapse is the key site for processing information, storing it there avoids additional wire for relay. Moreover, information stored directly at a synapse can be retrieved directly—also avoiding additional wire. In short, as we peruse a blueprint of brain design, we should not seek a special organ for “information storage”—it is stored, as it should be, in every circuit.” (Chapter 14)

“[I]nformation is stored and retrieved at synapses. Storage occurs by increasing synaptic weight, that is, its contribution to firing the postsynaptic neuron. Space for synapses is already constrained by competing needs for local wires and long tracts, and cortical synapses are already as small as they can be (chapter 13), so memory capacity cannot increase by shrinking them further. In fact, to increase its synaptic strength, a synapse must enlarge. The presynaptic terminal enlarges to accommodate more vesicles and more active zones for release. The postsynaptic structure, typically a dendritic spine, also enlarges to accommodate more transmitter receptors, more synaptic scaffold proteins, and more regulatory proteins.”- (Chapter 14)

“Of all these adjustments, the more stable and costly are classified as ‘learning’. Neuroscience is still learning about learning; yet it is already evident that learning—stable changes in functional architecture of synapses in response to their signaling history—is ubiquitous in the brain, from early sensory stages to cortex and final motor outputs.” (Chapter 15)

“[N]eurons form spines to maximize connectivity and minimize volume… [M]emories are stored at synapses, which always fill their allotted space. Even if some fraction of synapses were held in reserve, the reserve pool belongs to the overall design. So our memory banks are effectively full, and new memories can be stored only by pruning old ones.”- (Chapter 15)

“The postsynaptic terminals of most excitatory synapses in the CNS are found on dendritic spines—small, mushroom-shaped membrane protrusions that act as isolated biochemical signaling units. The functional properties of spines are thought to be influenced by their specific morphology, and changes in synaptic efficiency are associated with structural changes of the spine itself… [Recent] studies apply time-lapse two photon imaging of fluorescently labeled synaptic marker proteins, combined with electron microscopy, to examine the spatiotemporal changes in synaptic morphology and underlying signaling mechanisms. Together, they reveal details of the step-by-step sequence by which new proteins are incorporated in the growing spine and postsynaptic density.”

“Engrams of individual memories are the long-lasting biological changes that take place in the brain to encode specific experiences. Each engram is thought to contain a sparse population of neurons that are activated by the specific learning experience, undergo long-lasting synaptic modifications, and mediate the expression of the encoded memory.”

“Considerable evidence suggests that the formation of long-term memories requires a critical period of new protein synthesis… Studies in mammals have demonstrated that bidirectional changes in synaptic growth accompany synaptic plasticity.

“Probably more than 70% of the synaptic contacts in the cerebral cortex, and a substantial proportion of those in other parts of the brain such as hippocampus, cerebellum, basal ganglia and thalamus, involve dendritic spines… [S]pines can be seen as morphological devices that allow axons and dendrites to pursue economically straight courses through the neuropile, and at the same time permit both a high density and specificity of connections.”

“Long-term potentiation (LTP) is the mechanism for the activity-dependent strengthening of synapses that is thought to contribute to learning. GluA1 homomeric receptors are delivered into synapses at the early phase of LTP, and this delivery is required for LTP maintenance, presumably by providing Ca2+ through GluA1 homomeric receptors; Ca2+ is critical for protein synthesis. In this study, we inactivated GluA1 homomeric receptors by in vivo CALI [Chromophore-Assisted Light Inactivation] 1 h after conditioning and erased contextual fear memory.”

“Evidence derived using optical imaging, molecular-genetic and optogenetic techniques in conjunction with appropriate behavioural analyses continues to offer support for the idea that changing the strength of connections between neurons is one of the major mechanisms by which engrams are stored in the brain.”

“The aim of this study was to gain a better understanding of the native ultrastructure of dendritic spines and to investigate if chemical fixation alters the morphology of dendritic spines… We found that the volume of spine heads and the length of spine necks are unaltered by chemical fixation, and only the size of the spine neck is changed, being 42% thicker in diameter in chemically fixed tissue compared to cryo-fixed tissue. The thinner spine necks observed in cryo-fixed tissue suggest a larger electrical resistance coupling spines to parent dendrites than previously indicated from analysis of chemically fixed tissue.”

“Long-term potentiation (LTP) at glutamatergic synapses is considered to underlie learning and memory and is associated with the enlargement of dendritic spines.”

“Our SDS-digested freeze-fracture replica immunolabeling method (SDS-FRL) has almost one-to-one detection sensitivity to AMPARs… The number of immunoparticles for AMPARs in individual [dLGN retinogeniculate] synapses was positively correlated with the synaptic area… Our results indicate that the average AMPAR response is primarily proportional to the number of AMPARs in individual synapses, and thus, where the number of AMPARs is proportional to the synaptic area, the strength of the synapse can be approximately estimated by the size of the synapse.”

“All of these experiments seem to point strongly towards the notion that spines or synapses (and not entire cells) may be the smallest unit of memory storage in the brain and it may, therefore, be most appropriate to say that the “engram” of a memory is laid down in the set of spines or synapses that are changed when specific information is stored.”

“Converging evidence from multiple lines of study suggests that neocortical activity, particularly within the mPFC, during learning and the gradual strengthening of neocortical connections over time support long-lasting memory and the process of systems consolidation… It has been suggested that the role of the mPFC in remote episodic memories is equivalent to that of the hippocampus for recent memory.”-

“A major problem in understanding memory is how it can be very long-lasting and stable from early childhood until death, despite massive interruptions in brain state as extreme as prolonged comas. Current prominent candidates for molecular substrates for long-term memory storage have focused on macromolecules such as calmodulin-dependent protein kinase II (CaMKII) coupled with the NMDA receptor (1) and protein phosphatase 2A (2), protein kinase M zeta (PKMζ) (3), and cytoplasmic polyadenylation element binding protein (CPEB) (4), all of which are inside postsynaptic spines.”

“[T]here is a broad consensus that the size of the spine head scales with the size of the PSD, and the amplitude of the excitatory postsynaptic current (EPSC). Accordingly, the induction of synaptic long-term potentiation (LTP) leads to spine head enlargement that scales with the potentiation of the EPSC… Conversely, electrical induction of long-term depression (LTD) leads to shrinkage of the spine… [T]hese studies support the view that during synaptic plasticity spine heads undergo size changes followed by remodeling of the PSD to accommodate a higher or lower number of receptors…”

“Long-term memories are thought to be represented by changes in the strength of connections among neurons in the brain… [L]ong-term memories are thought to be distributed, and depend on the collective activity of groups of neurons (or cell assemblies) across a broad network of cortical and subcortical brain regions.”

“[W]e used in vivo two-photon calcium imaging to characterize the orientation tuning and spatial arrangement of synaptic inputs to the dendritic spines of individual pyramidal neurons in layer 2/3 of ferret visual cortex. The summed synaptic input to individual neurons reliably predicted the neuron’s orientation preference… Dendritic branches with more co-tuned synaptic clusters exhibited greater rates of local dendritic calcium events, supporting a prominent role for functional clustering of synaptic inputs in dendritic nonlinearities that shape orientation selectivity.”

“At the molecular level, the formation and consolidation of long-term memory are thought to be ultimately expressed in the form of structural changes at synapses.”

“In the superficial layer of several cortical regions in adult mice, dendritic spines imaged through a thinned-skull window are remarkably stable with 12% turnover over 3 d, ~5% over 1 month and ~2026% over 19 months.”

“Our findings reveal that rapid, but long-lasting, synaptic reorganization is closely associated with motor learning. The data also suggest that stabilized neuronal connections are the foundation of durable motor memory.”

“Our data suggest that reinforcement plasticity occurs at the single spine level… in such a way that dopamine regulates the gain of NMDAR dependent Hebbian plasticity via CaMKII activity… Thus, we have clarified a molecular and cellular basis of reinforcement plasticity at the level of single dendritic spines.”

“Changes in synaptic connections are considered essential for learning and memory formation… These studies indicate that learning and daily sensory experience leave minute but permanent marks on cortical connections and suggest that lifelong memories are stored in largely stably connected synaptic networks.”

“[W]e observed that in some cases (n = 31) a new bouton (or spine) added to an existing synapse was initiated by the same axon (or dendrite) that harbored the existing synapse, thus strengthening the connections between existing neuronal partners. This result is consistent with previous findings that, after LTP induction, multiple spines from the same dendrite made contacts with the same presynaptic axon bouton. Such synapse addition could also lead to spatially clustered spines that are more likely to be coactive, providing a potential explanation for spatial clustering of learning-induced new spine formation.”

“Spine head volume is linearly related with the size of the PSD and the sensitivity of spines to glutamate. Thus, it is widely accepted that change in the volume of dendritic spines is the structural correlate of change in synaptic efficacy.”

“The currently available data show a strong correlation between synaptic plasticity and morphological changes in spines… We now know that the volume of the spine-head is directly proportional to the number of postsynaptic receptors and to the presynaptic number of docked vesicles.”

“This suggests that it might be possible to calculate the synaptic strength of a synapse from the morphology of a spine. Specifically using the correlations between spine head volume and PSD size and between spine neck length and spine potential, one should be able to calculate the amplitude of the synaptic potential, knowing the spine head volume and neck length (and ideally also the neck diameter). Thus, it could become possible to analyze the morphology of a dendritic tree and reveal its functional input map.” (Chapter 10)

“I concur with those that hypothesize that LTP leads to an increase in spine size… Indeed, the increases in spine size during LTP nicely explain the relation between spine size and synaptic strength… I discuss the correlation between the size of a spine head and the strength of the synapse, by which larger spines appear to inject larger currents into the dendrite than smaller spines. An additional, inverse correlation appears between the length of the spine neck and synaptic strength. Both correlations, beautifully demonstrating the marriage of form and function, are so clear that spine morphology might be used to calculate synaptic strength.” (Chapter 1)

“[N]eural networks, first proposed as purely theoretical entities in the 1940s, are distributed circuits where the computation becomes an emergent property of the connectivity matrix and the temporal dynamics it can sustain. By using spines, biological circuits could make this strategy possible… My hypothesis is that all previously discussed functions, including synaptic plasticity, are part of this larger common design plan and that spine-laden circuits are biological neural networks.” (Chapter 1)

“In fact, I would go so far as proposing that that pyramidal cells (or spiny neurons), form the “skeleton” of the circuit, which carries out the basic computation, whereas interneurons play a secondary, yet perhaps crucial, role in helping principal cells operate in their overall integrative regime. From this point of view, one should be able to understand the basic computational structure, or transfer function, of a circuit without discussing interneurons.” (Chapter 10)

“[M]y proposal is that these functions are exactly the ones that make circuits with spines behave as neural networks. Spines could be viewed as the anatomical signatures of linearly integrating, distributed neural networks. Spines would endow neural circuits with the ability to perform Boolean logic, to implement associative memory, to have multistable dynamics, to become self-organized, and to become veritable learning machines.” (Chapter 10)

“According to Hebb, these recursive and reverberating patterns of neuronal activation, firing in closed loops, would be responsible for generating functional states of the brain, such as memories or specific behaviours. He proposed that synaptic connections between neurons could be altered by a learning rule (a local change in synaptic strength governed by correlated patterns of activity), thus linking neurons into an assembly. In doing so, the circuit has ‘learned’ a pattern of activity, storing it into its altered repertoire of synaptic connections.”

“The basal expression of SEP-GluA1 in spines in vivo had a wide distribution and was correlated with spine size, consistent with previous findings that the number of postsynaptic AMPARs is strongly correlated with spine size and most likely is a determinant of synaptic strength.”