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Bermúdez-Rattoni F, editor. Neural Plasticity and Memory: From Genes to Brain Imaging. Boca Raton (FL): CRC Press/Taylor & Francis; 2007.

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Neural Plasticity and Memory: From Genes to Brain Imaging.

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Chapter 5Presynaptic Structural Plasticity and Long-Lasting Memory: Focus on Learning-Induced Redistribution of Hippocampal Mossy Fibers

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5.1. LEARNING AND STRUCTURAL PLASTICITY

The fundamental problem of whether learning-dependent morphological malleability is related to long-lasting memory, as originally articulated by Cajal and Hebb, remains a galvanizing issue in neuroscience. In 1906, Ramon y Cajal1 stated that “… new pathways are established through continued branching and growth of dendritic and axonal arborizations. The hypothesis that new communication pathways … only takes place after long efforts requiring attention and reflection, as well as the reorganization of mnemonic areas” (p. 724). Hebb2 espoused a similar view, noting that the increased efficacy of synapses was likely due to “growth or metabolic change” that would take place at the synapse “in one or both cells” (p. 62). While there is an emphasis on changes occurring at both the pre- (axonal) and post-(dendritic) synaptic components following learning in both passages, the question remains whether the data truly support these theories.

5.1.1. Postsynaptic Plasticity

Post-synaptically, dendritic spines exhibit motility and are responsive to activity, making them ideal substrates for information storage.3,4 Rapid increases in spine density have been observed as soon as 30 minutes after induction of long-term potentiation (LTP)5 in CA1 neurons undergoing stimulation in hippocampal slice culture.6

Spatial learning has also been shown to increase the density of dendritic spines in the hippocampus.7 Training rats to find a hidden platform in a water maze, a hippocampal-dependent task,8 increases the density of dendritic spines on the basal dendrites of CA17 and the surface area, volume, and number of perforated post-synaptic densities of CA3 thorny excrescences.9

Trace eye-blink conditioning, which like the water maze is hippocampal-dependent,10 increases the number of multisynaptic boutons (MSBs) in the CA1 stratum radiatum.11 Because MSBs are presynaptic terminals that form synapses with two or more post-synaptic spines,11 an increment in the proportion of MSBs suggests the occurrence of structural modifications of existing spines. Furthermore, learning-induced structural modifications to dendritic spine synapses are not restricted to the hippocampus, but have also been observed in the cerebellum,12–14 motor cortex,15 amygdala,16 striatum,17 and olfactory bulbs18 of trained rodents.

5.1.2. Presynaptic Plasticity

While we can cite a number of examples of postsynaptic structural plasticity (see above and Harris and Kater19 for an earlier review and Kasai et al.20 for a recent review), there is a paucity of examples of learning-related presynaptic structural plasticity. The current status of our knowledge of presynaptic structural plasticity is epitomized in this quote from Chklovskii et al.21:

“… cortical axons maintain the capacity to grow and elaborate in the adult brain. However, axonal remodeling has only been observed in response to prolonged (months to years) injury. In addition, such lesions are at least in some cases associated with massive subcortical changes, including transneuronal atrophy. Such pathological subcortical changes might release mechanisms of cortical rewiring that are not normally observed in the brain. Clearly, our understanding of axonal plasticity in the adult brain remains in its infancy. How plastic are axonal arbors in the adult brain and what is the spatial range of growth? Do axons grow in response to learning, or only with injury?” (p. 786).

This chapter offers affirmative answers to both the question of whether there is plasticity of axonal arbor in the adult and the issue of learning-dependent axonal growth.

5.1.2.1. Invertebrate Presynaptic Structural Plasticity

Perhaps the best examples of learning-induced structural plasticity in the invertebrate domain have been observed in the slug Aplysia californicus. Long-term sensitization of a gill withdrawal reflex in Aplysia increases the size and number of active zones as well as the number of vesicles per active zone.22 This change is likely a result of incremental axonal branching and increases in the number of presynaptic boutons of trained animals.23 Such morphological changes appear to be bidirectionally influenced by learning as long-term habituation decreases multiple indices of presynaptic structural alterations.22,24 Thus, it is believed that changes in the total number of synapses as mediated by presynaptic remodeling underlie associative learning in Aplysia.24 What is more, such changes can be quite rapid, due in part to post-translational modifications of the actin cytoskeleton.25

Are learning-induced presynaptic changes restricted to the invertebrate nervous system? In the remainder of this chapter, we will examine the best evidence for learning-induced growth of presynaptic terminals in mammals. These data come from studies examining learning-induced growth of axonal projections — the hippocampal mossy fibers.

5.1.2.2. Mammalian Presynaptic Structural Plasticity

In mammals, increased expression of a protein or gene associated with structural remodeling is often taken as evidence for presynaptic morphological changes. For instance, increased expression of SNAP-25, a protein associated with reactive synaptogenesis,26 has been observed to change with learning and memory.27 However, SNAP-25 is also a critical component of the vesicle release machinery, the SNARE complex,28 and thus, functional rather than structural effects cannot be ruled out.29 Rather than merely observing changes in protein or gene expression, another approach is to directly manipulate the levels of a presynaptic protein and examine subsequent effects on learning and memory. Unfortunately, without sufficient information regarding the biochemical and cell biological role of a given protein, this approach can yield results that are difficult to interpret.30

A notable exception to the “knock out first, interpret later” approach to current neurobiological research is found in the body of work examining the effects of modifying the levels of the presynaptic growth protein, GAP-43, on information processing. In addition to learning-induced increases in protein levels,31,32 two studies using genetically-engineered mice demonstrated bidirectional regulation of memory storage by this axonal growth protein. On a radial arm maze task requiring the hippocampus, transgenic mice overexpressing GAP-43 exhibited superior learning relative to wild type littermates33 while heterozygous GAP-43 knockout mice trained on a hippocampal-dependent aversive conditioning task exhibited impairments.34 Coupled with the wealth of evidence for the role of GAP-43 in axonal growth both in vivo and in vitro (for review see Benowitz and Routtenberg35), these data can be taken as strong support for the role of presynaptic structural plasticity in learning and memory.

Despite evidence for molecular control of learning and memory by a presynaptic growth protein such as GAP-43, there remains a dearth of direct evidence linking information processing with specific cellular morphological changes. A number of reports of reactive presynaptic sprouting after lesion (Hardman et al.36), neurotransmitter blockade (e.g., using APV; Colonnese and Constantine-Paton37), and pathological insult38 examined expression of presynaptic markers and (importantly) directly compared measurements of the number of presynaptic terminals with and without a given experimental treatment. Thus, sufficient evidence suggests that presynaptic structural plasticity may underlie nonpathological forms of activity such as learning.39 Recently evidence has begun to accumulate that demonstrates learning-induced presynaptic structural plasticity in the mossy fiber system of the hippocampus. Before discussing the empirical support for structural plasticity of mossy fiber pathways, the anatomy of this system will be reviewed.

5.2. HIPPOCAMPAL GRANULE CELL AXON TERMINALS AND LEARNING

5.2.1. Granule Cell Mossy Fiber Anatomy

Granule cells of the dentate gyrus give rise to the mossy fiber axons1,40 that contain the heavy metal, zinc.41 Zincergic presynaptic mossy fiber terminals are readily identified using the Timm’s staining method for heavy metals.42 Mossy fiber boutons synapse on large thorny excrescences of CA3 pyramidal neurons40 and on mossy fiber-associated inhibitory interneurons.43,44 The glutamatergic mossy fibers provide excitatory input to the apical dendrites of CA3 pyramidal cells in the stratum lucidum. CA3 pyramidal cells also receive major excitatory inputs from other CA3 neurons via recurrent collaterals45,46 and direct cortical input from layer III of the entorhinal cortex via the perforant path.47

Each granule cell mossy fiber makes anywhere from 10 to 18 synapses with CA3 pyramidal cells in the stratum lucidum.48 The sparseness of the granule cell input to CA3 pyramids is highlighted when compared with the number of contacts made by a single CA3 pyramidal neuron axon that can contact 12,000 to 60,000 neighboring pyramidal neurons within the ipsilateral CA3 region.49

5.2.1.1. Mossy Fiber Pathways and Axonal Termination Zones

As illustrated in Figure 5.1, four separate ipsilateral mossy fiber pathways terminate on CA3 pyramidal cells: the suprapyramidal (SP) mossy fiber pathway (A in Figure 5.1), the infra-intra-pyramidal (IIP) mossy fiber pathway (B), the distal stratum oriens (dSO) pathway (C) that projects to CA3 basal dendrites. and the descending longitudinal pathway (DP) of the mossy fibers (D) that projects septo-temporally to other CA3 lamella.

FIGURE 5.1. The rat hippocampus has four mossy fiber projections to CA3 pyramidal cells.

FIGURE 5.1

The rat hippocampus has four mossy fiber projections to CA3 pyramidal cells. The figure shows the four mossy fiber projections from granule cells (red) to CA3 pyramidal neurons (green). Note that the basal distribution of Timm’s staining used (more...)

SP pathway

This pathway is responsible for the majority of granule cell synapses on CA3 pyramids and is derived from granule cells located throughout both the internal (dorsal) and external (ventral) blades as well as the crest of the dentate gyrus.48,50 SPMF boutons terminate in the stratum lucidum (SL) on the proximal (to the soma) 100 μm of CA3 pyramidal cell apical dendrites.51 This projection innervates CA3c through CA3a pyramidal cells, terminating at the border of CA3a at the boundary with the large pyramids of CA2.45,50

IIP pathway

Primarily originating from granule cells of the ventral (external) blade, this pathway contacts the basal dendrites of superficial and the apical dendrites of deep-lying pyramidal cells in CA3b and CA3c.

dSO pathway

Mossy fiber terminals located in this pathway are axon collaterals and presynaptic expansions from the SP that cross the pyramidal cell layer to contact the basal dendrites of CA3 pyramidal neurons.50 These terminals are derived from granule cells throughout the entire extent of the dentate gyrus, although it is not known whether a subset of granule cells are marked for the dSO projection only. Both the IIP and the dSO have been observed to continue to grow for well over 1 year after birth.40

DP

While pathways A through C are arranged in a lamellar organization,47,52 the DP courses along the longitudinal axis of the hippocampus, traveling from the granule cell layer transversely through the stratum lucidum before abruptly turning ventrally at the tip of the stratum lucidum proximal to the border with CA2.45,50 The descending pathway then synapses on more temporally located CA3 cells,40 sometimes traveling as far as 2 mm in the temporal direction.52

5.2.1.2. Role of Mossy Fibers in Learning and Processing of Spatial Information

Much of the initial identification of the mossy fibers as important for the learning process was conducted by Dr. Hans-Peter Lipp and colleagues who focused on correlations between the basal size of the IIP and various forms of hippocampal-dependent learning.53,54 Because hippocampal function is associated with the formation of spatial maps,55 Lipp and colleagues investigated whether increased distribution of IIPs found in some mammals might be correlated with superior spatial learning.

Consistent with this view, the length of rat hippocampal IIP mossy fibers is positively correlated with performance on spatial navigation using the Morris water maze.56 Similarly, differences in the distribution of the IIP pathways in various inbred strains of mice predicted performance on tests of hippocampal function.54 For example, on two different hippocampal-dependent tasks, significant positive correlations between the extent of the IIP pathway in DBA and C57 inbred mice and task performance have been described.57,58

Reversible inactivation of CA3 MF-terminal fields with injections of diethyldithiocarbamate (DDC) during the acquisition phase of a hidden platform water maze task-impaired retention of the platform location as shown by a lack of a spatial preference during a probe test.59 A similar study found that the DDC-impairing effect was selective for spatial but not nonspatial water maze tasks.60 In a spatial object recognition task, injections of DDC into the CA3 region during the acquisition phase did not affect acquisition of the task but did impair recall of the spatially displaced object.61 These data indicate a causal relationship between MF function and spatial information processing.

Although studies by Lipp and colleagues demonstrates the importance of the IIP to learning and memory, their work was primarily concerned with how anatomical differences conveyed by development and genetics correlate with cognitive differences and not with the plasticity of this or other mossy fiber pathways. Non-pathological structural plasticity of mossy fiber pathways was first demonstrated by Ramirez-Amaya and colleagues, who observed that training adult Wistar rats in the Morris water maze resulted in an increased distribution of Timm’s-stained mossy fiber terminal fields (MFTFs) in the stratum oriens (SO) sublayer of the CA3 region of the hippocampus.62,63 The change in Timm’s staining that they reported required several days (>3) of training and persisted for at least 30 days.63 Despite the implications of these results, both studies have remained largely overlooked. For example, no mention of these findings is made in two recent articles, one on cortical axonal remodeling21 and the other on mossy fibers.64 Possible reasons for the obscurity of these reports include (1) the lack of replication by independent laboratories, (2) reliance upon the Timm’s stain to identify growth, (3) the implication that this growth was pathological because mossy fiber sprouting has traditionally been linked with epilepsy, and (4) lack of adequate controls to establish dependence upon hippocampal function.

Building upon the paradigm first described by Ramirez-Amaya et al.,62,63 we subsequently found that MFTF area is indeed significantly increased in Wistar rats (WRs) trained to find a hidden platform compared to yoked swim controls that swam in the water maze for a similar amount of time but with no platform present.65,66 Importantly, no changes in the area of MFTFs were observed in WRs trained to find a cued visible platform, which does not require the hippocampus.8 Thus, the learning-induced presynaptic growth that we observed 7 days after the fifth day of water maze training was a direct result of learning that specifically recruited the hippocampus. The observed growth was also independent of any stress-related responses that may have resulted from exposure to the water maze. What is more, the growth process appeared to be protracted, as we did not observe significant increments in MFTF area when animals were sacrificed 2 (rather than 7) days after the fifth day of training.65

To confirm the presynaptic localization and mossy fiber identity of learning-specific increments in Timm’s histological staining, we immunostained hippocampal tissue from hidden platform-trained rats and swim controls for Tau and ZnT3, respectively, and found corresponding increments in immunoreactivity for both proteins in the SOs of hidden platform-trained rats.66

We also found that another strain, Long Evans rats, learned and retained water maze tasks more rapidly than Wistar rats. To demonstrate a possible difference in mossy fiber morphology, we examined the distribution of IIP in non-trained animals and found that consistent with the findings of Lipp and others, the better-learning Long Evans strain possessed a greater basal distribution of mossy fibers. We also observed spatial learning-specific expansion of MFTFs in Long Evans rats. Interestingly, the rapidity with which Long Evans rats recalled the location of a hidden platform was reflected in their equally rapid expansion of stratum oriens MFTFs. Significant increments in learning-induced MFTF expansion were observed as soon as 24 hours after end of the fifth day of training.66

Thus, we have demonstrated that learning can actually induce a remodeling of the presynaptic input circuitry within a specific portion of the hippocampus. Furthermore, this phenomenon is not restricted to a particular strain of rat but is found even in animals that begin training with a prominent distribution of mossy fibers (e.g., Long Evans rats). Because mossy fibers primarily terminate in the stratum lucidum (SL in Figure 5.2c), the observed learning-induced increment in the SO likely represents increased innervation of CA3 basal dendrites by granule cell mossy fiber terminals (Figure 5.2d).

FIGURE 5.2. Learning-induced expansion of mossy fiber terminal fields.

FIGURE 5.2

Learning-induced expansion of mossy fiber terminal fields. (a). Cartoon of the hippocampus, demonstrating mossy fiber pathways between dentate gyrus granule cells (black/gray circles) and CA3 pyramidal neurons (white triangles). Mossy fibers primarily (more...)

Indeed, an expansion of mossy fiber terminals on the basal dendrites of CA3 pyramids may impact learning by positively influencing future encoding by increasing the granule cell input to a given pyramidal cell. Clusters of thorny excrescences on basal dendrites of CA3 neurons are located closer (27 ± 3.1 versus 77 ± 1.9 μm) to pyramidal cell bodies than clusters on apical dendrites.67,68 Because any MF input to basal dendrites would be substantially closer to the soma than corresponding input to apical dendrites, Gonzales et al. hypothesized, using the logic outlined in Carnevale et al.,67 that mossy fiber–basal dendritic synapses may hold greater influence over somatic voltages than mossy fiber–apical dendritic synapses.68 Given the sparseness of mossy fiber–CA3 coding, increasing the efficacy of individual synaptic contacts would facilitate the ability of individual groups of mossy fibers to act as “detonators”69 and thereby enhance the encoding of spatial information.70

5.3. MECHANISMS OF PRESYNAPTIC STRUCTURAL PLASTICITY

Presynaptic structural plasticity, such as is observed in the learning-specific expansion of hippocampal MFTFs, can manifest in a number of different ways. One possibility is that prior to learning there are a number of presynaptic filopodia or “pioneer” terminals that continually seek out prospective postsynaptic partners. With sustained, correlated activity, as is presumed to take place with learning, extracellular signaling could then induce filopodial differentiation to mature, active terminals.64,71

Another possibility is the actual learning-induced growth of presynaptic terminals. This growth can take several forms. First, there is a possibility that sustained activity results in the sprouting of new presynaptic terminals that are likely to synapse with existing dendritic spines. It is interesting to note that although learning-induced synaptogenesis could result in a net increment in the number of boutons, it does not have to result in changes in the actual density of active zones.72 Alternatively, an activity-induced remodeling of the presynaptic terminal is possible. This remodeling would not result in any changes in the number of terminals per se but would increase the effective number of active zones and neurotransmitter release sites. Such remodeling may be considered growth as it would require substantial cytoskeletal and intracellular remodeling.73

5.3.1. Molecular Determinants of Presynaptic Structural Plasticity

The types of morphological changes discussed in the preceding section require mobilization by specific growth-related molecules. Presynaptic structural plasticity is thus likely the result of coordinated increments in trophic factors and decrements in chemorepellants. Candidate growth factors include neurotrophin-374 nerve growth factor.75 Particularly attractive is the neurotrophin brain-derived neurotrophic factor (BDNF) shown to be important for axonal outgrowth76 and playing a role in synaptic plasticity77,78 (but see Qiao et al.79). For example, BDNF is up-regulated in granule cells after seizures79,80 and is observed in sprouting mossy fibers.79 Application of BDNF and bFGF to cultured rat dentate granule cell explants resulted in marked increases in axon number and extension.81 Furthermore, BDNF knockout mice, unlike wild types, do not display seizure-induced mossy fiber sprouting.82 Thus, BDNF may be necessary for structural plasticity of axons and mossy fiber terminals in particular.

As mentioned previously, the presynaptic growth protein, GAP-43, may mediate presynaptic plasticity; however, interestingly it may not do so in the mossy fiber system as it contains little or no endogenous GAP-43 in the adult.83 Unlike the neurotrophins, GAP-43 is restricted to presynaptic processes and is probably part of membrane-associated lipid rafts84 where it likely influences cytoskeletal dynamics.85 However, the role of GAP-43 in neuronal axonal growth in vivo may be one of pathfinding rather than outgrowth or extension per se.86–88 Up-regulation of GAP-43 after experimental induction of status epilepticus appears to be a critical factor in pathological supragranular mossy fiber sprouting.89–92

Any increment in a trophic factor is likely coordinated with a reduction in chemorepellants. For example, with KA-induced seizures, supragranular sprouting was only evident when accompanied by decrements in the expression of the chemorepellant semaphorin3A.93 KA-induced GAP-43 up-regulation was insufficient to induce supragranular sprouting in the absence of diminished levels of semaphorin3A.93 In fact, an accumulating body of evidence suggests that the semaphorins are critical determinants of axonal outgrowth and patterning during development of the nervous system.

Neuropilin-1 is a transmembrane receptor for the extracellular chemorepellant semaphorin 3A.94,95 In the adult mouse, the highest expression of neuropilin-1 in the hippocampus is in mossy fiber axonal terminals.96 Although highly expressed relative to surrounding molecular layers, neuropilin-2 expression is substantially lower in the adult. Recent evidence links reductions in semaphorin 3A expression in the rat with mossy fiber sprouting in kainate models of epilepsy.93 In addition, neuropilin-2 knockout mice showed robust hypertrophy of the IIPMF.97 Furthermore, 7 days after kainic acid-induced seizures, expression of sema3A mRNA in CA3 pyramids was shown to decrease by 67%.98 Although Barnes et al. did not assess mossy fiber sprouting in their kainic acid-treated animals, such dramatic reductions in expression of a chemorepellant are temporally and regionally consistent with increments in MF staining in CA3 after KA and pilocarpine-induced seizures.99,100

Adhesion molecules may also transduce learning into morphological change, possibly by coordinating pre- and postsynaptic changes. The polysialylated form of the neural cell adhesion molecule (PSA-NCAM) is a marker of immature terminals that is enriched during development.101 Following kainate administration, immunoreactivity for PSA-NCAM is enriched on the cytoplasmic membranes of axon shafts.102 Removal of PSA from NCAM via either enzymatic degradation or genetic manipulation using NCAM-180 mice (engineered not to polysialylate NCAM) reveals an aberrant and persistent innervation of the pyramidal cell layer by granule cell mossy fibers, including a defasciculation of processes.103

The cadherins are adhesion molecules that are precisely and specifically up-regulated in sprouting terminals, both during development and in adults.104 Expression of the neural adhesion molecule, n-cadherin, is also increased after seizures and is believed to contribute to epileptic axonal reorganization.105 Additionally, cadherin-9 is known to play a major role in cellular adhesion during the development of connectivity.106

5.4. PRESYNAPTIC DISPARITY: ANTI-BOUTONISM OR BIOLOGICAL REALITY?

Based on the literature reviewed in preceding sections, it seems worthwhile to inquire as to the reason for the strong emphasis on the role played by the postsynaptic element. It may be that presynaptic structural plasticity is a phenomenon that is specific to only a subset of axons in the mature nervous system.

Certainly the mossy fibers and their neurons of origin, dentate gyrus granule cells, can be considered a unique cellular population within the brain.47 As one of only a few consensus neurogenic sites in the adult animal, over 9000 new neurons are produced per day in the rat dentate gyrus.107,108 Because hippocampal-dependent learning enhances the survival of adult-derived granule cells,109 the contribution of neurogenesis to learning-induced expansion of MFTFs must be considered. However, a comparison of the rapidity with which learning-induced presynaptic growth is observed in Long Evans rats with the time required for axonal extension of nascent granule cells66,110 strongly suggests that synaptogenesis of existing terminals plays a part in learning-induced growth of mossy fiber terminals in the adult.

A more likely reason for the pre- versus postsynaptic disparity is that learning-induced growth of presynaptic terminals can also result in retraction of inactive or redundant terminals.111 Indeed, a highly transient population of presynaptic terminals64 would be congruent with theories of homeostatic plasticity,112 suggesting that although there may be local fluctuations in the number of synapses, the total synaptic weight in a given region of the brain remains largely the same, irrespective of activity. Thus, for every increment in the number of synaptic inputs from a given cell population, there is likely a roughly equal decrement in inputs from a different source. Such mechanisms would account for the lack of quantitative data demonstrating activity-induced changes in the number of presynaptic terminals because merely measuring the number of terminals in a region of fixed neuropil would produce numbers that belie the dynamic processes taking place in living tissue.

With improved and more readily accessible application of technologies, such as 2-photon microscopy (e.g., Engert and Bonhoeffer6), researchers in the not-so-distant future will be able to visualize individual presynaptic terminals in vivo and study their real-time responses to activities. Indeed, the giant mossy fiber terminals may be the ideal systems for exploring this exciting possibility. Thus future studies may allow direct observation of actual presynaptic plasticity mechanisms and would provide insight into how they regulate learning and memory in vivo.113

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