Synaptic Mechanisms of Memory Research Paper

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Memory has fascinated Western thinkers since the era of the pre-Socratic philosophers. With time, however, the focus of interest in memory has shifted first from philosophy to psychology and, more recently, from psychology to neural science. The reason that memory has so occupied scholarship is that memory is a bridge between the humanities, concerned with the nature of human experience, and the natural sciences, concerned with the mechanistic basis of that experience. Memory is the glue that binds mental processes together across time and that gives continuity and coherence to our lives. Many of the characteristics that make each of us unique arise from the enduring effects of our individual experience.

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The shift from philosophical to empirical investigation into memory occurred in the nineteenth century and involved three fundamental distinctions. At the end of the nineteenth century, as academics gained increasing faith in the scope and power of empirical scientific research, they became emboldened to apply experimental techniques to mental processes such as learning and memory. The first steps were taken in 1885 by the German philosopher Hermann Ebbinghaus, who transformed philosophical speculation about memory into an experimental science. Ebbinghaus was much influenced by the work of Weber, Fechner, and Wundt in the psychophysical study of sensation. These scientists showed that one could apply objective experimental techniques to the study of a behavioral process. Although the measurement was the subject’s subjective response, these responses proved to be quite reliable when the probe— the stimulus used to elicit the response—was objective and quantifiable.

In trying to develop a probe for memory, Ebbinghaus hit upon the use of three-letter nonsense words that had no relation to any language, thereby preventing previous associations or experience from affecting the process of learning and recall. By memorizing syllable lists of varying length and by testing his recall at different points in time, Ebbinghaus was able to deduce two important principles about memory storage. First, he found that memory is graded—that practice makes perfect. There was a linear relationship between the number of training repetitions and the extent of recall on the following day. Second, Ebbinghaus anticipated the distinction between short and long-term memory that has dominated modern thinking by noting that whereas a list of six or seven items could be learned and retained in only one presentation, longer lists required repeated presentation. The same distinction between short and long-term memory was apparent when Ebbinghaus plotted a ‘forgetting curve,’ which he found to be biphasic: he rapidly forgot information during the hour after training, but forgetting was much more gradual after that, out to periods as long as a month.

At the beginning of the twentieth century a second important distinction was introduced into thinking about memory by the theorist Richard Semon. Semon divided memory into three components: (a) encoding or acquisition of new information, (b) storage of that information over time (in the form of what he termed the engram), and (c) retrieval or decoding of the information in a behaviorally conducive context (Semon 1909–1923). Of these three components, the engram, or the storage mechanism, has proven most amenable to a biological line of inquiry.

A third distinction—not between temporal phases or components of a given memory but between different types of memory and the brain systems that mediate them—emerged only in the latter half of the twentieth century. Studies by Brenda Milner and others of patients with lesions of the brain in the hippocampal formation and medial temporal lobe have made it clear that memory is not a unitary faculty of mind but can be divided into at least two functionally distinct forms: explicit (or declarative) memory which, at least in humans, involves conscious recall and can be put into words; and implicit (nondeclarative or procedural) memory, which is revealed by a lasting, unconscious change in behavior (Milner et al. 1998).

Despite the existence of these two fundamentally different forms of memory, both Ebbinghaus’ distinction between short and long-term memory and Semon’s distinction between encoding, storage, and retrieval are quite general and apply to both. The differences between implicit and explicit memory arise from the way the molecular mechanisms for short and long-term memory storage are embedded in the brain systems that mediate the different forms of memory.

Here we will focus primarily on the mechanistic aspects of memory, and specifically on the mechanisms of storage.

1. How Memory is Stored: The Cellular Mechanisms of the Engram

In the early part of the twentieth century, Santiago Ramon y Cajal, the great Spanish neuroanatomist, introduced a theory about memory storage that is now almost universally accepted. Cajal proposed that synapses, the connections between neurons, are plastic—that is, they can change over time and are sensitive to their history. As a result, information can be stored in the brain by changing the strength of preexisting synaptic connections between neurons (Ramon y Cajal 1893). Cajal further suggested that the change in the strength of connections between neurons results from anatomical changes in the shape of individual dendritic spines, the protuberances from the dendrites of excitatory neurons on which many synapses form.

In the subsequent decades there have been two major elaborations of Cajal’s ideas, the first by Donald Hebb in 1949 and the second by Eric Kandel and Ladislau Tauc in 1965. In his oft-cited book, Hebb (1949) proposed a homosynaptic rule for strengthening synaptic connections, according to which the events that trigger synaptic strengthening occur at the strengthened synapse itself. Hebb hypothesized that ‘when an action of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A’s efficiency, as one of the cells firing B, is increased.’ Because the strength of the connection between a pre and postsynaptic neuron is increased when the firing of the postsynaptic neuron is correlated or associated with the firing of the presynaptic neuron, this sort of synaptic strengthening has been termed associative.

After such an event, when the first of the two neurons is activated (perhaps by a stimulus that resembles the one to which it fired earlier) it has an increased chance of leading to the firing of the second. In addition to being homosynaptic and associative, Hebb proposed that the synaptic strengthening be input-specific: when two neurons fire coincidentally the synapse between them should be strengthened, but other synapses on either neuron should remain unchanged.

Kandel and Tauc proposed in 1965 an additional, heterosynaptic rule for strengthening synaptic connections. They further proposed that this heterosynaptic strengthening could be of two sorts, nonassociative or associative. In nonassociative heterosynaptic facilitation, a synapse could be strengthened without any change in the firing of either the presynaptic or the postsynaptic neuron. This occurs as a result of the firing of yet a third neuron, a modulatory interneuron, that acts on the synapse to increase its strength. In associative heterosynaptic facilitation, the strengthening effect of the modulatory neuron is further enhanced when the firing of the modulatory input is associated in time with the firing of the presynaptic neuron. Kandel and Tauc demonstrated homosynaptic and both types of heterosynaptic plasticity in the mollusc Aplysia by manipulating one and two inputs to a single cell (Kandel and Tauc (1965).

The plastic change hypothesis of Cajal and its elaboration by Hebb and by Kandel and Tauc, however, represent only one of two competing theories of the nature of the engram. An alternative to plastic change at the synapse as the principle for information storage was the idea of dynamic change, advanced by Alexander Forbes and Lorente de No. According to their idea, information could be stored in neural circuits without altering the synapses as a result of the firing of reverberant networks of neurons or pairs of mutually excitatory cells (Delisle Burns 1958).

Tests of these competing ideas in the 1960s showed that it was difficult to establish reverberating activity in the brain because of the abundance of inhibitory interneurons that prevent the continuous cycling of activity in practically every neural circuit. By contrast, exploration of synapses showed that most chemical synapses in the vertebrate brain as well as in invertebrates have remarkable plastic properties. Beginning in 1965 with the developmental studies of Hubel and Wiesel and the studies of Kandel and Tauc, and the work of Bliss and Lømo (to which we will return below) several years later, a variety of forms of synaptic plasticity were demonstrated in different neuronal systems. It soon became clear that built into the molecular architecture of many chemical synapses is a remarkable capacity for modification.

2. Homo- and Heterosynaptic Plasticity are Recruited by Learning and Serve for Memory Storage

Showing that chemical synapses are plastic was one thing; showing that such plastic changes are induced in a behavioral context by learning is another. The first rigorous experiment designed to explore whether or not plastic mechanisms are induced by learning was carried out in 1970 by Vincent Castellucci, Irving Kupferman and their colleagues in Aplysia (Castellucci et al. 1970). They identified a neural circuit mediating a simple reflex—the gill withdrawal reflex to stimulation of the siphon—and showed that it can be modified by two simple forms of learning, habituation and sensitization. In habituation, repeated presentation of a novel stimulus leads to a gradual decrease in the animal’s reflex withdrawal response as it learns that the stimulus is innocuous. Habituation of this gillwithdrawal reflex was accompanied by a homosynaptic decrease in the strength of the connection between the siphon sensory neuron and the gill motor neuron in the circuit. Sensitization is a form of learned fear in which the animal recognizes a stimulus, such as a shock to the tail, as being aversive and learns to enhance its gill withdrawal response to a previously neutral stimulus, such as a weak tactile stimulus to the siphon. Sensitization of the gill withdrawal reflex was accompanied by a nonassociative, heterosynaptic increase in the strength of the same synaptic connection between sensory and motor cells, brought about by the activity in modulatory interneurons induced by the noxious tail stimulus. Later studies at the same synapse by Thomas Carew, Robert Hawkins, Tom Abrams and their colleagues demonstrated that classical conditioning gives rise to associative heterosynaptic facilitation. These several studies show that multiple mechanisms of plasticity can coexist at a single synapse and can be recruited by different forms of learning.

In 1973, Bliss and Lømo described a long-lasting Hebbian form of homosynaptic plasticity in the mammalian brain with potential relevance for explicit forms of memory (Bliss and Lømo 1973). They found that when the perforant path, a fiber track in the hippocampal formation in the temporal lobe, was repetitively stimulated in an anaesthetized animal, subsequent responses in the dentate gyrus to single stimuli were enhanced: the perforant path synapse had been strengthened. This result was important for several reasons. First, it showed that an enduring form of plasticity exists in the adult mammalian brain. Second, the hippocampus had been clearly implicated in work by Penfield and Perot (1963) and by Scoville and Milner (1957) to be involved in human explicit memory, so finding plasticity here was particularly intriguing. Third, the plasticity was homosynaptic. Further investigation of this form of plasticity (generically termed Long-Term Potentiation, or LTP) showed that in most cases it is dependent on coincident pre and postsynaptic firing and is input-specific. It thus has all the characteristics of a Hebb synapse.

More recent studies have revealed that the distinction between heterosynaptic and homosynaptic mechanisms of facilitation is not absolute and that both can commonly occur at a plastic synapse. For example, detailed studies of classical conditioning in Aplysia by Glanzman, Hawkins and their colleagues revealed both associative heterosynaptic and homosynaptic mechanisms; interfering with either can disrupt synaptic plasticity (Bao et al. 1997). In the hippocampus, LTP can be induced in a purely homosynaptic way, without heterosynaptic participation. But for the potentiation to persist for more than a few hours in duration, heterosynaptic modulatory processes seem to be required (Bailey et al. 2000). Such observations suggest that memory storage often requires both forms of plasticity. Whereas homosynaptic plasticity can serve as a learning mechanism and as a mechanism of short-term memory, heterosynaptic mechanisms are often required for persistence of long-term memory. This combinatorial utilization of homo and heterosnaptic plasticity is emerging as a major point in the study of synaptic plasticity, to which we will return below.

3. Molecular Mechanisms of Plasticity in Specific Model Systems

The experimental elimination of dynamic changes as a major contributor to memory storage focused attention on the chemical synapse as a site of information storage in the brain, a focus that allowed a concerted attack on its molecular mechanisms. As a result of the classic early work of Bernard Katz and Paul Fatt and a long list of others more recently, we now know a great deal about the cell and molecular mechanisms of synaptic transmission. This large body of knowledge is now being brought to bear on the synaptic mechanisms of memory storage and represents the starting point of all subsequent studies of the mechanisms of plastic change.

The molecular mechanisms of plasticity and the relationship of plasticity to simple forms of memory were first studied in Aplysia (Kandel 1976). Studies of the gill withdrawal reflex in the intact animal and studies of components of the neural circuit in cell culture have revealed several mechanistic themes that seem to be of general importance. First, just as memory has at least two temporal phases, many forms of synaptic plasticity have an early and a late phase.

These phases are pharmacologically dissociable: the early phase does not require new protein synthesis, whereas the late phase is blocked by inhibitors of either protein or mRNA synthesis. This implies that the induction of synaptic plasticity recruits two distinct signaling pathways, one of which operates rapidly at the synapse and the other of which operates more slowly and transmits a signal to the nucleus, where it induces the activation of new genes required for longlasting plastic change. These two temporal phases of synaptic plasticity seem to correspond to the two temporal phases of memory described by Ebbinghaus. The early phase of heterosynaptic plasticity in Aplysia is initiated by tail stimuli that activate modulatory interneurons, some of which release the neurotransmitter serotonin. This serotonin activates serotonergic receptors in the sensory neurons of the reflex, which in turn activate an enzyme, adenylyl cyclase, that increases the amount of the small intracellular signaling molecule cAMP in the cell. cAMP leads to early-phase enhancement of synaptic transmission both by alteration of the electrical properties of the sensory cell and by changes in the synaptic machinery. Repeated activation of the modulatory interneurons initiates the same category of events but also leads to late-phase plasticity, which can last days and is characterized by demonstrable structural alterations at the synapse. Stimuli that induce late-phase plasticity lead to the translocation of several different signaling molecules to the nucleus of the presynaptic cell (Bailey et al. 1996).

Despite the involvement of events in the nucleus, late-phase plasticity in Aplysia and in other systems retains its synapse specificity. This implies that the products of the new genes that are activated during the induction of enduring plasticity are somehow specifically targeted to the relevant synapse(s). The leading hypothesis for this phenomenon at the beginning of the twenty-first century involves synaptic tagging: the synapses where plasticity is induced are somehow marked such that the products of the relevant induced genes are effective only at those synapses. A consequence of this hypothesis is the phenomenon of synaptic capture, in which weak stimulation of one synapse can lead to lasting potentiation if the stimulation occurs during a window after strong stimulation of a separate synapse on the same cell. Synaptic capture has been observed in Aplysia by Kelsey Martin and her colleagues (Martin et al. 1997) and in mice by Uwe Frey and Richard Morris (Frey and Morris 1997). Since synaptic capture in either homosynaptic or heterosynaptic plasticity represents a specific breakdown of synapse specificity, synaptic capture may have significant consequences for the encoding and storage of information, but the role of this phenomenon remains unclear.

Parallel work has been carried out in the fruit fly Drosophila by Ron Davis, Chip Quinn, Tim Tully, and their colleagues. Genetic screens have revealed that many of the molecules implicated in synaptic plasticity in Aplysia are also involved in learning in Drosophila. For example, modulatory neurotransmitter receptors and components of the cAMP second messenger system have been associated with learning in this organism. Such results suggest that not only the general principles but also some of the details of the mechanisms that emerge from study of an organism such as Aplysia may be very generally applicable (Davis 1996). Synaptic plasticity in mammals is best characterized in the hippocampus. The most work has been done at the Schaeffer collateral synapse, distinct from the perforant path synapse first studied by Bliss and Lømo (1973). At the Schaeffer collateral synapse, LTP can be induced by various patterns of repetitive stimulation of the axons coming into the synapse or by simultaneous brief stimulation of the axons and depolarization of the postsynaptic cell; both instances conform to Hebb’s requirements. Hippocampal LTP has an early and a late phase; the intracellular messenger cAMP seems to be critical for the late phase but less so for the early, which is induced by calcium influx. Synapse specificity and synaptic capture have been demonstrated. There remains considerable controversy as to the precise molecular changes that accompany plasticity at this synapse; it is likely that changes in both the presynaptic and the postsynaptic cell contribute, with the balance of contributors shifting depending on the specifics of the inducing stimulus.

While this form of homosynaptic plasticity has been well studied, there is considerable evidence that heterosynaptic plasticity also has an important role at the same synapses. Intracellular cAMP can be produced either by appropriate patterns of calcium buildup or by modulatory neurotransmitters in a heterosynaptic fashion, and there is good evidence that both contribute. As we note above, modulatory neurotransmitters can enhance the capacity for plasticity or even induce it in the absence of neuronal stimulation, and blockade of modulatory neurotransmitters blocks the late phase of LTP at most synapses in the hippocampus and amygdala. Blockade of modulatory neurotransmitters in intact animals and in people can interfere with the formation of memories under certain circumstances (Cahill et al. 1994). Such observations once again suggest that homosynaptic and heterosynaptic plasticity interact importantly at a variety of synapses in the hippocampus and elsewhere in the formation of memories.

Plasticity has been described in many other places in the mammalian brain. In particular, LTP has been described at the other synapses in the hippocampus, in the amygdala, the neocortex, and the striatum. A conjugate phenomenon, long-term depression (LTD), has also been described in many of these structures as well as in the cerebellum. In many of these cases the characteristics emphasized above are retained: early and late phases of plasticity, a critical role for calcium influx, and the participation of second messengers like cAMP. It seems likely that a set of common molecular themes exists for most or all forms of synaptic change.

4. Correlating Synaptic Change with Behavior

The postulate that synaptic change underlies various forms of learning in invertebrates and in mammals is difficult to demonstrate in more than a correlative way. In many cases, manipulations that disrupt synaptic plasticity also disrupt related forms of learning. This is particularly so in the correlation between LTP at the Schaeffer collateral synapse in the hippocampus and forms of complex, hippocampus-dependent spatial learning in rodents (Martin et al. 2000). While such correlations become impressive as their number increases, there are some documented exceptions. Furthermore, the manipulations involved are rarely definitive. Whether by lesion, drug application, or genetic change, any manipulation that affects synaptic plasticity is likely to also have subtle effects on normal synaptic function and on the properties of neurons away from the synapse specifically being studied.

Such correlational studies suggest that synaptic plasticity is necessary for at least some forms of learning. Two other modes of investigation of the connection between synaptic strengthening and learning are required to substantiate the hypothesis. First, specific changes in the strength of a defined synapse or set of synapses should be able to mimic learning and thus to have a defined effect on the animal’s behavior—that is, induction of plasticity should be sufficient for learning. Second, learning in a normal animal should in principle lead to changes in the strength of some specific set of synapses. These two types of experiment have been more challenging than simple correlation of synaptic plasticity with capacity for learning.

The first approach, changing behavior in a way that resembles learning by altering the strength of a synapse, has best been attempted in the cerebellum. The cerebellum is involved in learning of coordinated motor patterns and in the acquisition of certain classically conditioned responses to arbitrary stimuli. The core of the cerebellum’s neural architecture is the Purkinje cell, which receives strong input from a single climbing fiber(or a few of them) and weak input from as many as 100,000 parallel fibers. The Purkinje cell is thus ideally suited to learn associations between a single, specific stimulus (represented by the climbing fiber) and any of a large number of arbitrary stimuli (represented by the parallel fibers). Learning in this circuit is thought to be mediated in large part by alteration in the strength of the synapses between the parallel fibers and the Purkinje cell, an alteration which is controlled by the relative timing of climbing fiber and mossy fiber activation.

In an early, pioneering study, Brogden and Gantt showed that (a) when they stimulated the cerebellar white matter they could sometimes produce an identifiable motor output, and (b) when they paired this stimulation with a tone, that tone came to induce the motor output independent of neural stimulation (Krupa et al. 1993). This means that the direct stimulation of the cerebellar white matter can substitute for the unconditioned stimulus in a classical conditioning paradigm. In an elegant series of studies using electrophysiological recording, lesions, stimulation, and reversible inactivation, Thompson and his colleagues have identified the climbing fiber of the cerebellum as the critical white matter component that can encode the unconditioned stimulus and they have developed very strong evidence that the essential memory trace for certain forms of classical conditioning is indeed formed and stored in the cerebellum (Krupa et al. 1993). While such studies do not specifically demonstrate a change in synaptic strength, they do demonstrate that stimulation conditions known to induce changes in synaptic strength can mimic one or both of the stimuli in a learning paradigm.

The most difficult aspect of the connection between synaptic plasticity and learning is the demonstration of changes in synaptic strength after demonstrable learning has occurred in a normal animal. This has been demonstrated in Aplysia and in the rat amygdala. In Aplysia, sensitization, habituation, and classical conditioning, three simple learning processes by which the reflex response to a light touch is modulated, have been shown to result in changes in the functional strength of a specific synapse in the circuit that underlies the reflex (Kandel 1976, Murphy and Glanzman 1997). Such results greatly strengthen the idea that synaptic change underlies learning in this organism.

The rat amygdala is required for fear conditioning to a tone—that is, for learning to associate a previously neutral audible tone with a foot shock. Part of the circuit underlying this learning phenomenon consists of the projections from the auditory portion of the thalamus, which relays auditory information about the tone, to the lateral subnucleus of the amygdala. There is some controversy as to whether the amygdala then stores this information or simply plays a critical role in orchestrating the storage of the tone-shock pairing in other structures (Cahill et al. 1999). If the former is the case, the synaptic plasticity concept would predict a measurable change in synaptic strength in the amygdala after fear conditioning. Joseph LeDoux and Michael Rogan have demonstrated LTP in i o at the synapse between the thalamic projections and the lateral amygdala, and, importantly, they have demonstrated change at this synapse after a specific tone-shock pairing (Rogan et al. 1997). This result lends critical support to the notion that learning leads to plasticity of specific synapses.

5. Top-down and Bottom-up Approaches to Learning and Plasticity

It is not coincidental that the clearest demonstrations of a connection between learning and plasticity come from Aplysia and from the amygdala, rather than from the intensively studied hippocampus. The Aplysia reflex circuit and the amygdala fear conditioning circuit represent simpler neural systems in which to study this connection, because the circuit that mediates learning can (at least in principle) be clearly identified. This allows one to start with a defined learning behavior, delineate the circuit that mediates it, and thus identify a relatively small number of synapses at which the relevant plasticity may be occurring. By examining only these synapses, one can maximize the chance of finding meaningful synaptic change. In brief, in simple systems, it is possible to identify where to look. This sort of approach, where the behavior comes first and the synapses are examined later, can be called a top-down approach to the study of learning.

The case is quite different in the hippocampus. In this case, plasticity was described first (albeit in a structure known to be required for certain forms of learning), and behavioral tasks were tested later to look for correlates to disruptions of that plasticity: the approach is bottom-up. Furthermore, the type of learning task in which the hippocampus is involved (explicit or spatial learning) is vastly more complicated than the simple associations studied in Aplysia and in the amygdala, and the representation of information in the hippocampus is likely to be more abstract. While the Schaeffer collateral synapse is often referred to as a single site, it actually represents approximately 1,000,000,000 individual synapses from cells in the CA3 field of the hippocampus on to cells in the CA1 field. Even if the idea that plasticity at this synapse is important for hippocampus-dependent learning is correct, only a small subset of these synapses is likely to be meaningfully altered in a given learning task: it is not remotely clear where to look for the relevant changes. For this reason, compelling demonstration of the role hippocampal synaptic plasticity in learning has proven difficult to achieve.

Plasticity in the cerebellum is perhaps an intermediate case. The cerebellum’s role in learning was described before plasticity, and we have a fairly clear model of how information is encoded: in a classical conditioning task, the climbing fiber encodes the unconditioned stimulus, the parallel fiber encodes the conditioned stimulus, and the Purkinje cell output modulates a motor response. This gives one an idea of where to look for meaningful synaptic change. However, there are millions of Purkinje cells, and each receives as many as 200,000 synapses from individual parallel fibers. While there is strong evidence that change at some parallel fiber-Purkinje cell synapses is important, identifying the specific site (or sites) where plasticity occurs in a given learning task is a daunting task indeed and may be no easier than in the hippocampus.

6. A Broader View

We have emphasized the two central models of how synaptic plasticity may store information: homosynaptic plasticity and heterosynaptic plasticity. We have also described evidence that the two may operate both independently and in tandem at certain important synapses in the mammalian brain. A critical current question in the biology of synaptic plasticity is the relation between the two. While homosynaptic plasticity seems to have a greater capacity for information storage because of its greater specificity, heterosynaptic plasticity, at least in most systems, leads to more long-lasting change. One clue to their relationship comes from studies of the role of modulatory neurotransmitters in the hippocampus. In general, modulatory neurotransmitters have an effect on the late phase of plasticity but not on the early phase: enhancing modulatory transmitters can increase the capacity for long-lasting change, and blocking them can truncate potentiation to just the early phase. One possibility is that whereas homosynaptic plasticity, with all its potential for specificity of connections, contributes primarily to learning and short-term memory, heterosynaptic plasticity determines what information is destined to enter into long-term storage: it is the mechanism of memory.

We began this research paper with the suggestion that memory has become a particularly attractive field for the biologically minded neuroscientist because the means of information storage have proven amenable to analysis even without an understanding of the very complicated processes by which behavioral information is encoded into memory. The concept that information can be stored in the changing strength of individual synapses is an entree into this biological mechanism. However, as we have seen, the complexity of information encoding cannot be escaped for long: it is only in Aplysia and in maximally simplified mammalian systems like the amygdala that it is at all clear where to look for the plasticity that accompanies learning. Correlative studies can increase our confidence that forms of synaptic plasticity in the hippocampus and elsewhere do matter for learning, but a definitive demonstration will have to wait for a fuller understanding of the more abstract encoding of memory in these circuits.


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