Jump to ContentJump to Main Navigation
Cerebral PlasticityNew Perspectives$

Leo M. Chalupa, Nicoletta Berardi, Matteo Caleo, Lucia Galli-Resta, and Tommaso Pizzorusso

Print publication date: 2011

Print ISBN-13: 9780262015233

Published to MIT Press Scholarship Online: August 2013

DOI: 10.7551/mitpress/9780262015233.001.0001

Show Summary Details
Page of

PRINTED FROM MIT PRESS SCHOLARSHIP ONLINE (www.mitpress.universitypressscholarship.com). (c) Copyright The MIT Press, 2018. All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single chapter of a monograph in MITSO for personal use (for details see http://www.mitpress.universitypressscholarship.com/page/privacy-policy). Subscriber: null; date: 17 August 2018

Determinants of Synaptic and Circuit Plasticity in the Cerebral Cortex: Implications for Neurodevelopmental Disorders

Determinants of Synaptic and Circuit Plasticity in the Cerebral Cortex: Implications for Neurodevelopmental Disorders

(p.75) 7 Determinants of Synaptic and Circuit Plasticity in the Cerebral Cortex: Implications for Neurodevelopmental Disorders
Cerebral Plasticity

Wilson Nathan R.

Mriganka Sur

The MIT Press

Abstract and Keywords

This chapter deals with the control signals that command adjustments in the cortical circuits’ “plasticity status.” It outlines several “feedforward” mechanisms that can initiate circuit change, together with a host of emerging “feedback” network processes that respond to those changes. This chapter shows a rich array of mechanisms by which changes in input activity lead to changes in the structure and function of the synapses, cells, and circuits of the cortex. It then discusses several disorders of brain development, namely Rett syndrome, tuberous sclerosis, and Fragile X.

Keywords:   cortical circuits, synapses, cells, cortex, Rett syndrome, tuberous sclerosis, Fragile X

“Cortical plasticity” encompasses a broad set of mechanisms through which cortical circuits adapt their responsiveness to their history of input. In several brain systems, the field has now distilled robust regimes for examining and demonstrating plasticity at the circuit level. In recent years there has also been a rough consensus on cellular and signaling changes which can account for circuit plasticity. In contrast, the control signals that command adjustments in the circuit’s “plasticity status” remain largely unknown, as do the specific cues that they monitor—candidate frameworks for these are emerging and are detailed below. A clear articulation of the phenomena, rules, and mechanisms that govern cortical plasticity during development is critical for understanding their misregulation in specific neurodevelopmental disorders. This far-reaching vision, that mechanisms of developmental plasticity can be used to reveal mechanisms of brain disorders and even treat them, owes much to the work and scientific insights of Lamberto Maffei, whom this volume honors.

The Visual Cortex as a Model System for Experience-Dependent Plasticity

Many critical observations on plasticity in the nervous system have been made in the visual cortex. Wiesel and Hubel (1963) had the original insight that the two eyes represent distinct input sources which can be driven differentially with light to evaluate how a circuit responds over time. In a sense, it remains the most straightforward junction for probing the complex circuitry of the cerebral cortex with well-characterized sensory stimuli. More recently, progress in detailing the phenomena and mechanisms of cortical plasticity has been augmented through transgenic mice, which has allowed for the elucidation of a growing network of proteins and pathways, isolated to specific regions and distinct cell types.

Another useful property of the visual cortex for studies of plasticity is the enormous dynamic range of plasticity that it expresses during the course of development and with experience (Katz and Callaway, 1992). Over the life span of cortical circuits, synaptic refinement leads to an increase in organization and correlated activity, while the malleability of the circuit is decreased concomitantly. Through cell-specific rules of plasticity (Desai et al., 2002), a large number of weak synapses with motile spines (the sites of excitatory synapses on cortical neurons) are (p.76) sculpted into a refined number of strong synapses with stable spines (Majewska and Sur, 2003; Oray et al., 2004). As excitatory transmission is consolidated, it contributes to the release of feedback signals such as brain-derived neurotrophic factor (BDNF; Bonhoeffer, 1996), which eventually attains a critical level for the activation of inhibitory signaling (Buonomano and Merzenich, 1998). This onset of inhibition initiates a brief time frame of exceptional plasticity known as the “critical period” in which the pattern of cortical input is particularly important for organizing and strengthening a functional architecture for future processing (Hensch, 2004). As the synaptic architecture underlying this organization stabilizes, it comes to resist further change (Abraham and Bear, 1996; Bi and Poo, 1998), the specific balance of excitation and inhibition becomes important for delimiting plasticity (Artola and Singer, 1987; Maya Vetencourt et al., 2008), and a network of extracellular matrix proteins begins to entangle the entire circuit to provide an additional measure of circuit stability (Berardi et al., 2004).

Parameterizing Cortical Plasticity

Across development, circuit plasticity itself is modulated by the level of input drive, which stimulates key molecular pathways to reconfigure circuit properties. Received activity is coupled to downstream and intercellular molecular events, and this allows activity at input locations to impact circuit function and plasticity at multiple loci. Here we will review several “feedforward” mechanisms that can initiate circuit change, together with a host of emerging “feedback” network processes that respond to those changes.

Feedforward Synaptic Plasticity

Feedforward changes are initiatory events where input activity to a circuit triggers direct synaptic changes across its synapses, with subsequent reverberatory consequences elsewhere in the circuit. A cardinal example of a feedforward change is long-term potentiation (LTP), in which a pattern of robust input activity triggers the long-term strengthening of that same input to further stabilize its postsynaptic influence over the circuit (Bliss et al., 2003). LTP also provides a link between synaptic changes and the formation and maintenance of cortical maps (Buonomano and Merzenich, 1998). Its sister process is long-term depression (LTD), in which weak activity across a synapse leads to the long-term weakening of that synapse, and loss of influence over the circuit. LTD has also been advanced as a basis for cortical phenomena such as ocular dominance plasticity (Smith et al., 2009). LTP and LTD are further complemented by mechanisms such as spike-timing dependent plasticity, which trigger synaptic plasticity based on how well matched the timing of an input is to firing of the postsynaptic cell (and circuit) on which it impinges (Song and Abbott, 2001; Dan and Poo, 2006). Together these canonical mechanisms lay a foundation for focal circuit changes upon and between cells that depend only on the magnitude and timing of the input itself, independent of the other inputs in the circuit. However, as we will see below, inputs across the cortical circuit are intimately connected via (p.77) multiple pathways and time courses which add richness to a simple “push-pull” dissection of cortical plasticity phenomena.

Molecular Pathways of Feedforward Plasticity

Modifications to the strengths of excitatory synapses are likely to be enacted via postsynaptic changes in AMPA receptor number and conductance (Malenka and Bear, 2004), and/or presynaptic changes in probability of release (Bolshakov and Siegelbaum, 1995) and vesicular glutamate content (Edwards, 2007). Input strength can also be adjusted via synaptogenesis and synaptic elimination. However, the degree to which such plasticity occurs is gated by a host of molecular pathways that determine the “plasticity status” of the synapse, cell, and circuit.

The NR2B/NR2A Switch

Plasticity is prominently gated by the activation of N-methyl-D-as-partate (NMDA) receptors, which respond to excitatory synaptic transmission by enabling calcium flux into the target synapse and its neuron, with more calcium triggering more plasticity and rearrangement. However, the receptor’s capacity to drive plasticity depends on its subunit composition. Some receptors are built from “NR2B” subunits, which enable a high calcium permeability and thus enhanced plasticity, and some are built from “NR2A” subunits, which have a reduced calcium flux (Flint et al., 1997). The ratio of NR2B/NR2A receptors in the synapse and the neuron thus has a pivotal effect on the overall calcium flux upon synaptic activation and determines the capacity for plasticity in response to arriving input.

Here again, a crucial determinant of plasticity is itself regulated by the activity level of the circuit. As animals are exposed to visual experience, the NR2B/NR2A ratio declines (Quinlan et al., 1999), thus reducing the capacity for further plasticity, whereas placing animals in the dark for extended periods recovers the NR2B/NR2A ratio (Chen and Bear, 2007), thereby restoring the capacity for plasticity. Thus, the molecular composition of NMDA receptors is a critical determinant of calcium-mediated cellular plasticity that is directly responsive to activity levels.

Calcium-Calmodulin Kinase II Signaling

Calcium entry at synaptic sites upon activation leads to eventual synaptic change, prominently via calcium-calmodulin kinase II (CaMKII), which is extraordinarily abundant and accounts for 1% to 2% of the total protein found in neurons (Fink and Meyer, 2002). CaMKII is spatially positioned in the synaptic spine to directly sense NMDA-mediated calcium fluxes (Bayer et al., 2001) and respond by mobilizing additional AMPA receptors to synapses (Hayashi et al., 2000). Moreover, its binding and activation is directly specified by the NR2B/NR2A subunit composition described above (Barria and Malinow, 2005). a-CaMKII has been shown to be critical for cortical LTP, as well as for the consolidation of cortical memory traces (Frankland et al., 2001). It also has the interesting property of autophosphorylation, which allows it to undergo long-term modification, and has led to the proposal that it could provide a (p.78) sort of “molecular memory” of synaptic activity (Lisman, 1994): persistently active CaMKII can indeed bring about LTP effects (Pettit et al., 1994). Interestingly, CaMKII seems be critical for synaptic plasticity yet without impacting large-scale cortical architecture, as its mutations prevent the consolidation of sensory plasticity without disrupting the topography of sensory cortex (Glazewski et al., 1996; Gordon et al., 1996).

The ERK/MAPK Pathway

Stimulation at the synaptic and cellular level drives the Raf/MEK/ ERK pathway, which also serves to promote synapse stabilization (Sweatt, 2001). A direct link has been established between its downstream effector, extracellular signal-regulated kinase 1,2 (ERK, also called p42/44 mitogen-activated protein kinase) and insertion of AMPA receptors into activated synapses (Zhu et al., 2002). The degree of ERK activation also determines the magnitude of LTP in visual cortex and is required for ocular dominance plasticity (Di Cristo et al., 2001). As with several of the plasticity cues described above, the ERK pathway is responsive to activity levels (Fiore et al., 1993), as well as NMDA receptor-mediated calcium levels (Hardingham et al., 2001), and plasticity cues such as BDNF (Patterson et al., 2001). Its down-stream targets include critical plasticity triggers such as cyclic AMP response element binding protein (CREB; Impey et al., 1998) and Arc (Ying et al., 2002), and transcription factors that regulate the expression of activity-dependent immediate early genes (Xia et al., 1996). Activity within the ERK pathway therefore offers a number of channels through which NMDA activation can stimulate cell-wide changes in synaptic function, thus promoting coherent integration of inputs between cells and networks (Thomas and Huganir, 2004).

The PI3K/Akt/mTOR Pathway

Along with the now-canonical plasticity pathways listed above, increasing attention has been paid to another protein kinase called mammalian target of rapa-mycin (mTOR). It is driven by both synaptic stimulation (Cammalleri et al., 2003) and PI3K/ Akt activation (Jaworski and Sheng, 2006), which is known to strengthen synapses by delivering PSD-95 (a critical post-synaptic density protein) into dendrites (Yoshii and Constantine-Paton, 2007). Functionally, increased mTOR activity has been linked to larger and fewer spines with larger AMPA currents (Tavazoie et al., 2005) and seems to serve to facilitate and accentuate LTP (Ehninger et al., 2008b; Hoeffer et al., 2008). Consequently, mTOR signaling seems well placed for stimulating growth, elevating excitatory drive, and forging stronger and more stable synaptic circuits.

Feedback/Homeostatic Plasticity

When a change is exerted at one or more synaptic pathways via the mechanisms described above, a concurrent group of normative processes may arise to rebalance the net function of the circuit. These mechanisms are considered “homeostatic” or “feedback” events because they appear aimed at restoring the net excitability of the circuit back toward its original state prior to plasticity induction (Turrigiano and Nelson, 2000; Davis and Bezprozvanny, 2001).

(p.79) Sites of Feedback Regulation

Feedback processes that rebalance the strength of excitatory synapses have been identified which operate postsynaptically, via AMPA receptor number and conductance (Turrigiano, 2008), and presynaptically, via probability of release (Murthy et al., 2001) and vesicular glutamate content (Wilson et al., 2005), among others. An input may also be renormalized by scaling its number of connections. Feedback processes that might rebalance at a network level beyond the excitatory synapse include modifications to inhibitory synapses (Maffei et al., 2006), homeo-static modifications to a cell’s intrinsic excitability (Pratt and Aizenman, 2007), and changes to the excitatory drive onto inhibitory neurons (Wilson et al., 2007). Feedback regulation within cortical circuits has even been demonstrated to extend from one sensory modality to another (Goel et al., 2006).

Positive Feedback Regulation via TNF-Alpha

What are the signals that control feedback regulation? One molecule that has been shown to be both necessary and sufficient for the activity-dependent scaling up of AMPA receptor function is the tumor necrosis factor TNF-alpha (Stellwagen and Malenka, 2006). Still more recently, the scaling up of open-eye responses following light deprivation in visual cortex was shown to require TNF-alpha (Kaneko et al., 2008). A particularly intriguing possibility is that the excitatory/inhibitory balance is coordinated via a few or even a single molecular control point. Indeed, increases to TNF-alpha signaling have been shown to coordinately increase AMPA receptor surface expression while simultaneously decreasing GABA receptor surface expression (Stellwagen et al., 2005).

Negative Feedback Regulation via CDK5 and Arc

What is responsible for the scaling down of excitability? One pathway that is emerging for rebalancing high levels of activity is CDK5/Polo-like kinase 2 (Plk2; Seeburg et al., 2008). Another likely possibility is the immediate-early gene Arc, the expression of which is regulated by activity, triggers AMPA receptor endocytosis (Chowdhury et al., 2006) and is required for synaptic scaling (Shepherd et al., 2005). Perhaps through its known homeostatic role, Arc has been found to be important for organizing representations in visual cortex (Wang et al., 2006) and has recently been found to underpin the loss of cortical responses that occurs during ocular dominance plasticity (McCurry et al., 2010). The scaling down of input strength mediated by Arc could also lead to the functional elimination of extraneous inputs during cortical refinement; indeed, mice that lack Arc exhibit visual cortical neurons that are less precisely tuned (Wang et al., 2006).

Inhibition as a Plasticity Gate

Inhibitory neurons are widespread in the cortex and may be even more diverse in morphology and function than excitatory neurons (Markram et al., 2004). The balance of excitation and inhibition appears to be dynamically maintained at the level of dendritic branches (Liu, 2004) (p.80) and neurons (Cline, 2005). In cortical dynamics, stimuli that elicit maximal excitation to neurons also elicit maximal inhibition at those same neurons (Marino et al., 2005; Okun and Lampl, 2008), ensuring that functional responses always result from a precise balance of excitatory and inhibitory drive.

In addition to balancing the firing rates of circuits, inhibition may have a complementary role in controlling the plasticity of circuits. Preventing the activation of inhibition prevents the critical period of plasticity from happening until inhibition is enabled (Hensch et al., 1998). Conversely, augmenting inhibitory signaling prematurely launches the critical period prematurely (Iwai et al., 2003). Once inhibition is developed to adult levels, however, it may become an obstacle to cortical plasticity. Inhibition in the cortex has long been claimed to gate adult LTP, wherein robust LTP was only observable when suppressing inhibition pharmacologically with bicuculline (Artola and Singer, 1987). In the adult visual system of the rat, ocular dominance plasticity is greatly reduced compared to juvenile levels but can be restored to juvenile levels by suppressing inhibition with the antidepressant fluoxetine (Maya Vetencourt et al., 2008).

The Role of Neurotrophins

Neurotrophins such as BDNF have emerged as an ideal candidate for communicating the status of activity across the circuit to regulate plasticity. Neuronal activity has a positive feedback relationship with the transcription of the BDNF gene, the transport of its protein into dendrites, and its secretion at synapses (Lu, 2003). At the cellular level, BDNF is known to support growth and strengthening of synapses during development (Cellerino and Maffei, 1996) and is critical for the proper establishment of excitatory synaptic transmission (Schuman, 1999).

BDNF also seems to play an instructive role in a host of processes relevant to circuit development. BDNF triggers the maturation of inhibition that initiates the critical period as described above (Huang et al., 1999), and expressing it prematurely accelerates the timing of the critical period (Hanover et al., 1999). BDNF also triggers the release of tPA (Fiumelli et al., 1999), which as described below is important for liberating structural plasticity. In homeostatic plasticity, BDNF has been identified as a signal that triggers the reactive scaling of excitatory and inhibitory synapses to offset recent elevations in activity levels (Rutherford et al., 1998).

Extraneuronal Influences: Astrocytes and Perineuronal Nets

Astrocytes constitute more than half of all cortical cells (Nedergaard et al., 2003) and have now been shown to exhibit functional responses to stimuli and organize into maps that are just as exquisitely defined as those of the neurons (Schummers et al., 2008). Astrocytes receive synaptic inputs, express neurotransmitter receptors, and can directly modulate the reliability of neuronal synapses (Perea and Araque, 2007). Furthermore, many of the factors critical for circuit plasticity may be stored by astrocytes and released onto neurons in response to functional events. For example, the TNF alpha described above as a potentially pivotal homeostatic signal is expressed in and released by astrocytes (Stellwagen and Malenka, 2006).

(p.81) Extraneuronal circuit changes are also reinforced by “perineuronal nets” (PNNs), which are lattice-like structures, comprised of chondroitin-sulfate proteoglycans (CSPGs) and other extra-cellular components, that condense and entangle cortical cells and synapses. These lattices restrict further movement and growth and provide an obstacle to structural and functional plasticity (Berardi et al., 2004). Compounds that degrade CSPGs, such as chondroitinase ABC, have been shown to restore ocular dominance plasticity to adult mice (Pizzorusso et al., 2002). Similarly, the extracellular protease tissue-type plasminogen activator (tPA), which also target CSPGs, has been shown to be most highly expressed at periods of maximal plasticity (Mataga et al., 2004) and play a key permissive role in enabling circuit remodeling during ocular dominance plasticity (Muller and Griesinger, 1998; Mataga et al., 2002; Oray et al., 2004). Recently, it has been shown that fear memories in adult mice, which are typically permanent features that are resilient to erasure, can be made susceptible to erasure via degradation of PNNs (Gogolla et al., 2009). These studies suggest that PNNs provide a form of “hard wiring” that can be dissolved or strengthened in order to modulate circuit flexibility.

Together, these findings demonstrate a rich array of mechanisms by which changes in input activity lead to changes in the structure and function of synapses, cells, and circuits of the cortex. Some of these same mechanisms come into play during disorders of brain development—which can thus be understood as disorders of cortical plasticity.

Disorders of Brain Development

Rett Syndrome

Rett syndrome (RTT) is a subset of autism and an X-linked neurological disorder affecting 1 in every 10,000–15,000 live births (Chahrour and Zoghbi, 2007). Unlike many neurodevelopmental disorders, the basis of RTT is straightforward and in approximately 90% of patients suffering from RTT has been traced to a single gene coding for methyl CpG-binding protein 2 (MeCP2; Amir et al., 1999; Guy et al., 2001). Combining a molecular understanding of RTT with a circuit perspective that links activity levels to plasticity could help pave the way for effective treatments (Zoghbi, 2003).

RTT is characterized by a profound reduction in cortical circuit activity (Dani et al., 2005), owing to a negative tilt in the balance of excitatory and inhibitory transmission (Dani et al., 2005; Chao et al., 2007; Tropea et al., 2009). Neurons are smaller (Chen et al., 2001), dendrites exhibit reduced elaboration (Armstrong et al., 1998; Kishi and Macklis, 2004), and spine density is reduced in key areas (Chao et al., 2007; Tropea et al., 2009). Plasticity, meanwhile, remains in an immature state, with impairments to LTP (Moretti and Zoghbi, 2006), and ocular dominance plasticity that aberrantly persist into adulthood (Tropea et al., 2009).

Viewed through this lens, RTT seems to arise from a failure of brain circuitry to mature or sustain a mature phenotype (Magee and Johnston, 1997; Moretti and Zoghbi, 2006). This failure has been shown to be reversible by driving pathways that promote circuit maturation and stabi-lization such as BDNF (Guy et al., 2007), which stimulates synaptic strengthening via PI3K/ (p.82) pAkt/PSD-95 and MAPK signaling (Carvalho et al., 2008). A similar stimulus to circuit maturation may also be derived through the systemic delivery of other neurotrophic factors such as insulin-like growth factor 1 (Tropea et al., 2009) that are capable of crossing the blood-brain barrier (Aberg et al., 2000; Lopez-Lopez et al., 2004; Jaworski et al., 2005) and which stimulate these same pathways (Zheng and Quirion, 2004; Tropea et al., 2006). Thus, RTT offers a prime example for how an understanding of circuit plasticity may aid in elucidating pathways for targeted intervention.

Tuberous Sclerosis

Tuberous sclerosis (TSC) is another neurodevelopmental disorder associated with cognitive impairment, seizures, perseverative behavior, and other disabilities similar to autism (Ehninger et al., 2008a). It has been linked to specific heterozygous mutations in 2 genes—TSC1 and TSC2. TSC may offer an excellent model for how too much synaptic potentiation can lead to cortical rigidity. Disruption of TSC1/2 brings about a fundamental shift in spine morphology—converting numerous small spines into fewer large spines, with stronger excitatory transmission (Tavazoie et al., 2005). A likely reason for this is that TSC results in enhanced mTOR signaling (Ehninger et al., 2008a; Meikle et al., 2008), which lowers the threshold for plasticity and makes long-lasting LTP more likely to occur, thus pathologically stabilizing synaptic pathways (Hoeffer et al., 2008). Compatible with this interpretation, application of mTOR inhibitors in a mouse model of TSC suppresses seizures, rescues the aberrantly stable synaptic potentiation, and reverses neurocognitive deficits (Ehninger et al., 2008b).

Fragile X

Fragile X is a condition of moderate to severe mental retardation (Loesch et al., 2002) that has been methodically linked to pathologies in cortical circuits (Bear, 2005). In mouse models of the disorder, circuits are characterized by an increased spine density (Grossman et al., 2006), comprised of weaker spines (Hinton et al., 1991; Irwin et al., 2001) with fewer AMPA receptors (Li et al., 2002) that are functionally “hyperplastic” in terms of synaptic changes (Bear et al., 2004) and cortical plasticity (Dolen et al., 2007). According to one hypothesis, increased translation of fragile X mental retardation protein (FMRP) underlies enhanced LTD in the mouse model for the disorder, and blockade of metabotropic glutamate receptors would act as a corrective. Indeed, a genetic rescue of multiple phenotypes of fragile X in the mouse model demonstrates the feasibility of this hypothesis (Dolen et al., 2007).

Conclusion and Future Directions

The development of effective interventions for disorders of cortical plasticity will require tools for rapidly assessing the plasticity status of a circuit in a manner that goes beyond single synapse measures to take into account the host of network influences described above. Promisingly, new imaging methods are allowing more subtle changes in circuit function to be measured optically, (p.83) including in the intact animal (Grinvald and Hildesheim, 2004; Pologruto et al., 2004; Schummers et al., 2008). Another promising tool is the advent of optical probes of plasticity (Wang et al., 2006; Hayashi et al., 2009), which offer the potential of reporting either the plasticity event or the plasticity status of cells within a circuit. Assays are also becoming available that can detect changes in protein levels in response to specific activity paradigms or plasticity and connect those into functional pathways that might drive or be driven by the plasticity (Tropea et al., 2006). Finally, advances in virally mediated gene transfer and optogenetics continue to provide increasingly pinpointed experimental control over specific cells’ genetic makeup and electrical input (Zhang et al., 2007).

As these tools are brought into play, they are revealing that plasticity is not merely a synaptic phenomenon but one that results from the coordinated interplay of excitatory, inhibitory, and glial cells, operating in tandem via feedforward and feedback mechanisms to regulate the plas-ticity tone of the circuit. Perhaps the greatest challenge in the coming years will be to devise methods for selectively understanding these network components to comprehend how they give rise to the choreographed processes of development and disease.


Bibliography references:

Aberg MA, Aberg ND, Hedbacker H, Oscarsson J, Eriksson PS. 2000. Peripheral infusion of IGF-I selectively induces neurogenesis in the adult rat hippocampus. J Neurosci 20: 2896–2903.

Abraham WC, Bear MF. 1996. Metaplasticity: the plasticity of synaptic plasticity. Trends Neurosci 19: 126–130.

Amir RE, Van den Veyver IB, Wan M, Tran CQ, Francke U, Zoghbi HY. 1999. Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2. Nat Genet 23: 185–188.

Armstrong DD, Dunn K, Antalffy B. 1998. Decreased dendritic branching in frontal, motor and limbic cortex in Rett syndrome compared with trisomy 21. J Neuropathol Exp Neurol 57: 1013–1017.

Artola A, Singer W. 1987. Long-term potentiation and NMDA receptors in rat visual cortex. Nature 330: 649–652.

Barria A, Malinow R. 2005. NMDA receptor subunit composition controls synaptic plasticity by regulating binding to CaMKII. Neuron 48: 289–301.

Bayer KU, De Koninck P, Leonard AS, Hell JW, Schulman H. 2001. Interaction with the NMDAreceptor locks CaMKII in an active conformation. Nature 411: 801–805.

Bear MF. 2005. Therapeutic implications of the mGluR theory of fragile X mental retardation. Genes Brain Behav 4: 393–398.

Bear MF, Huber KM, Warren ST. 2004. The mGluR theory of fragile X mental retardation. Trends Neurosci 27: 370–377.

Berardi N, Pizzorusso T, Maffei L. 2004. Extracellular matrix and visual cortical plasticity: freeing the synapse. Neuron 44: 905–908.

Bi GQ, Poo MM. 1998. Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J Neurosci 18: 10464–10472.

Bliss TV, Collingridge GL, Morris RG. 2003. Introduction. Long-term potentiation and structure of the issue. Philos Trans R Soc Lond B Biol Sci 358: 607–611.

Bolshakov VY, Siegelbaum SA. 1995. Regulation of hippocampal transmitter release during development and long-term potentiation. Science 269: 1730–1734.

Bonhoeffer T. 1996. Neurotrophins and activity-dependent development of the neocortex. Curr Opin Neurobiol 6: 119–126.

Buonomano DV, Merzenich MM. 1998. Cortical plasticity: from synapses to maps. Annu Rev Neurosci 21: 149–186.

(p.84) Cammalleri M, Lutjens R, Berton F, King AR, Simpson C, Francesconi W, Sanna PP. 2003. Time-restricted role for dendritic activation of the mTOR-p70S6K pathway in the induction of late-phase long-term potentiation in the CA1. Proc Natl Acad Sci USA 100: 14368–14373.

Carvalho AL, Caldeira MV, Santos SD, Duarte CB. 2008. Role of the brain-derived neurotrophic factor at glutamatergic synapses. BrJPharmacol 153 (Suppl. 1): S310–324.

Cellerino A, Maffei L. 1996. The action of neurotrophins in the development and plasticity of the visual cortex. Prog Neurobiol 49(1): 53–71.

Chahrour M, Zoghbi HY. 2007. The story of Rett syndrome: from clinic to neurobiology. Neuron 56: 422–437.

Chao HT, Zoghbi HY, Rosenmund C. 2007. MeCP2 controls excitatory synaptic strength by regulating glutamatergic synapse number. Neuron 56: 58–65.

Chen RZ, Akbarian S, Tudor M, Jaenisch R. 2001. Deficiency of methyl-CpG binding protein-2 in CNS neurons results in a Rett-like phenotype in mice. Nat Genet 27: 327–331.

Chen WS, Bear MF. 2007. Activity-dependent regulation of NR2B translation contributes to metaplasticity in mouse visual cortex. Neuropharmacology 52 (1): 200–214.

Chowdhury S, Shepherd JD, Okuno H, Lyford G, Petralia RS, Plath N, Kuhl D, Huganir RL, Worley PF. 2006. Arc/Arg3.1 interacts with the endocytic machinery to regulate AMPA receptor trafficking. Neuron 52: 445–459.

Cline H. 2005. Synaptogenesis: a balancing act between excitation and inhibition. Curr Biol 15: R203–R205.

Dan Y, Poo MM. 2006. Spike timing-dependent plasticity: from synapse to perception. Physiol Rev 86: 1033–1048.

Dani VS, Chang Q, Maffei A, Turrigiano GG, Jaenisch R, Nelson SB. 2005. Reduced cortical activity due to a shift in the balance between excitation and inhibition in a mouse model of Rett syndrome. Proc Natl Acad Sci USA 102: 12560–12565.

Davis GW, Bezprozvanny I. 2001. Maintaining the stability of neural function: a homeostatic hypothesis. Annu Rev Physiol 63: 847–869.

Desai NS, Cudmore RH, Nelson SB, Turrigiano GG. 2002. Critical periods for experience-dependent synaptic scaling in visual cortex. Nat Neurosci 5: 783–789.

Di Cristo G, Berardi N, Cancedda L, Pizzorusso T, Putignano E, Ratto GM, Maffei L. 2001. Requirement of ERK activation for visual cortical plasticity. Science 292: 2337–2340.

Dolen G, Osterweil E, Rao BS, Smith GB, Auerbach BD, Chattarji S, Bear MF. 2007. Correction of fragile X syndrome in mice. Neuron 56: 955–962.

Edwards RH. 2007. The neurotransmitter cycle and quantal size. Neuron 55: 835–858.

Ehninger D, Li W, Fox K, Stryker MP, Silva AJ. 2008a. Reversing neurodevelopmental disorders in adults. Neuron 60: 950–960.

Ehninger D, Han S, Shilyansky C, Zhou Y, Li W, Kwiatkowski DJ, Ramesh V, Silva AJ. 2008b. Reversal of learning deficits in a Tsc2 +/− mouse model of tuberous sclerosis. Nat Med 14: 843–848.

Fink CC, Meyer T. 2002. Molecular mechanisms of CaMKII activation in neuronal plasticity. Curr Opin Neurobiol 12: 293–299.

Fiore RS, Murphy TH, Sanghera JS, Pelech SL, Baraban JM. 1993. Activation of p42 mitogen-activated protein kinase by glutamate receptor stimulation in rat primary cortical cultures. J Neurochem 61: 1626–1633.

Fiumelli H, Jabaudon D, Magistretti PJ, Martin JL. 1999. BDNF stimulates expression, activity and release of tissue-type plasminogen activator in mouse cortical neurons. Eur J Neurosci 11: 1639–1646.

Flint AC, Maisch US, Weishaupt JH, Kriegstein AR, Monyer H. 1997. NR2A subunit expression shortens NMDA receptor synaptic currents in developing neocortex. J Neurosci 17: 2469–2476.

Frankland PW, O’Brien C, Ohno M, Kirkwood A, Silva AJ. 2001. Alpha-CaMKII-dependent plasticity in the cortex is required for permanent memory. Nature 411: 309–313.

Glazewski S, Chen CM, Silva A, Fox K. 1996. Requirement for alpha-CaMKII in experience-dependent plasticity of the barrel cortex. Science 272: 421–423.

Goel A, Jiang B, Xu LW, Song L, Kirkwood A, Lee HK. 2006. Cross-modal regulation of synaptic AMPA receptors in primary sensory cortices by visual experience. Nat Neurosci 9: 1001–1003.

(p.85) Gogolla N, Caroni P, Luthi A, Herry C. 2009. Perineuronal nets protect fear memories from erasure. Science 325: 1258–1261.

Gordon JA, Cioffi D, Silva AJ, Stryker MP. 1996. Deficient plasticity in the primary visual cortex of alpha-calcium/calmodulin-dependent protein kinase II mutant mice. Neuron 17: 491–499.

Grinvald A, Hildesheim R. 2004. VSDI: a new era in functional imaging of cortical dynamics. Nat Rev Neurosci 5: 874–885.

Grossman AW, Aldridge GM, Weiler IJ, Greenough WT. 2006. Local protein synthesis and spine morphogenesis: fragile X syndrome and beyond. J Neurosci 26: 7151–7155.

Guy J, Hendrich B, Holmes M, Martin JE, Bird A. 2001. A mouse Mecp2-null mutation causes neurological symptoms that mimic Rett syndrome. Nat Genet 27: 322–326.

Guy J, Gan J, Selfridge J, Cobb S, Bird A. 2007. Reversal of neurological defects in a mouse model of Rett syndrome. Science 315: 1143–1147.

Hanover JL, Huang ZJ, Tonegawa S, Stryker MP. 1999. Brain-derived neurotrophic factor overexpression induces precocious critical period in mouse visual cortex. J Neurosci 19: RC40.

Hardingham GE, Arnold FJ, Bading H. 2001. A calcium microdomain near NMDA receptors: on switch for ERK-dependent synapse-to-nucleus communication. Nat Neurosci 4: 565–566.

Hayashi Y, Shi SH, Esteban JA, Piccini A, Poncer JC, Malinow R. 2000. Driving AMPA receptors into synapses by LTP and CaMKII: requirement for GluR1 and PDZ domain interaction. Science 287: 2262–2267.

Hayashi Y, Mower AF, Kwok S, Yu H, Majewska A, Okamoto K, Sur M. 2009. Eye domain-specific synaptic CaMKII activation during ocular dominance plasticity in vivo. In: Society for Neuroscience Abstracts, p. 167.116/V135. Annual Meeting: Chicago.

Hensch TK. 2004. Critical period regulation. Annu Rev Neurosci 27: 549–579.

Hensch TK, Fagiolini M, Mataga N, Stryker MP, Baekkeskov S, Kash SF. 1998. Local GABA circuit control of experience-dependent plasticity in developing visual cortex. Science 282: 1504–1508.

Hinton VJ, Brown WT, Wisniewski K, Rudelli RD. 1991. Analysis of neocortex in three males with the fragile X syndrome. AmJMed Genet 41: 289–294.

Hoeffer CA, Tang W, Wong H, Santillan A, Patterson RJ, Martinez LA, Tejada-Simon MV, Paylor R, Hamilton SL, Klann E. 2008. Removal of FKBP12 enhances mTOR-Raptor interactions, LTP, memory, and perseverative/repetitive behavior. Neuron 60: 832–845.

Huang ZJ, Kirkwood A, Pizzorusso T, Porciatti V, Morales B, Bear MF, Maffei L, Tonegawa S. 1999. BDNF regulates the maturation of inhibition and the critical period of plasticity in mouse visual cortex. Cell 98: 739–755.

Impey S, Obrietan K, Wong ST, Poser S, Yano S, Wayman G, Deloulme JC, Chan G, Storm DR. 1998. Cross talk between ERK and PKA is required for Ca2+ stimulation of CREB-dependent transcription and ERK nuclear translocation. Neuron 21: 869–883.

Irwin SA, Patel B, Idupulapati M, Harris JB, Crisostomo RA, Larsen BP, Kooy F, et al. 2001. Abnormal dendritic spine characteristics in the temporal and visual cortices of patients with fragile-X syndrome: a quantitative examination. Am J Med Genet 98: 161–167.

Iwai Y, Fagiolini M, Obata K, Hensch TK. 2003. Rapid critical period induction by tonic inhibition in visual cortex. J Neurosci 23: 6695–6702.

Jaworski J, Sheng M. 2006. The growing role of mTOR in neuronal development and plasticity. Mol Neurobiol 34: 205–219.

Jaworski J, Spangler S, Seeburg DP, Hoogenraad CC, Sheng M. 2005. Control of dendritic arborization by the phosphoinositide-3’-kinase-Akt-mammalian target of rapamycin pathway. J Neurosci 25: 11300–11312.

Kaneko M, Stellwagen D, Malenka RC, Stryker MP. 2008. Tumor necrosis factor-alpha mediates one component of competitive, experience-dependent plasticity in developing visual cortex. Neuron 58: 673–680.

Katz LC, Callaway EM. 1992. Development of local circuits in mammalian visual cortex. Annu Rev Neurosci 15: 31–56.

Kishi N, Macklis JD. 2004. MECP2 is progressively expressed in post-migratory neurons and is involved in neuronal maturation rather than cell fate decisions. Mol Cell Neurosci 27: 306–321.

(p.86) Li J, Pelletier MR, Perez Velazquez JL, Carlen PL. 2002. Reduced cortical synaptic plasticity and GluR1 expression associated with fragile X mental retardation protein deficiency. Mol Cell Neurosci 19: 138–151.

Lisman J. 1994. The CaM kinase II hypothesis for the storage of synaptic memory. Trends Neurosci 17: 406–412.

Liu G. 2004. Local structural balance and functional interaction of excitatory and inhibitory synapses in hippocampal dendrites. Nat Neurosci 7: 373–379.

Loesch DZ, Huggins RM, Bui QM, Epstein JL, Taylor AK, Hagerman RJ. 2002. Effect of the deficits of fragile X mental retardation protein on cognitive status of fragile X males and females assessed by robust pedigree analysis. J Dev Behav Pediatr 23: 416–423.

Lopez-Lopez C, LeRoith D, Torres-Aleman I. 2004. Insulin-like growth factor I is required for vessel remodeling in the adult brain. Proc Natl Acad Sci USA 101: 9833–9838.

Lu B. 2003. BDNF and activity-dependent synaptic modulation. Learn Mem 10: 86–98.

Maffei A, Nataraj K, Nelson SB, Turrigiano GG. 2006. Potentiation of cortical inhibition by visual deprivation. Nature 443: 81–84.

Magee JC, Johnston D. 1997. A synaptically controlled, associative signal for Hebbian plasticity in hippocampal neurons. Science 275: 209–213.

Majewska A, Sur M. 2003. Motility of dendritic spines in visual cortex in vivo: changes during the critical period and effects of visual deprivation. Proc Natl Acad Sci USA 100: 16024–16029.

Malenka RC, Bear MF. 2004. LTP and LTD: an embarrassment of riches. Neuron 44: 5–21.

Marino J, Schummers J, Lyon DC, Schwabe L, Beck O, Wiesing P, Obermayer K, Sur M. 2005. Invariant computations in local cortical networks with balanced excitation and inhibition. Nat Neurosci 8: 194–201.

Markram H, Toledo-Rodriguez M, Wang Y, Gupta A, Silberberg G, Wu C. 2004. Interneurons of the neocortical inhibitory system. Nat Rev Neurosci 5: 793–807.

Mataga N, Nagai N, Hensch TK. 2002. Permissive proteolytic activity for visual cortical plasticity. Proc Natl Acad Sci USA 99: 7717–7721.

Mataga N, Mizuguchi Y, Hensch TK. 2004. Experience-dependent pruning of dendritic spines in visual cortex by tissue plasminogen activator. Neuron 44: 1031–1041.

Maya Vetencourt JF, Sale A, Viegi A, Baroncelli L, De Pasquale R, O’Leary OF, Castren E, Maffei L. 2008. The antidepressant fluoxetine restores plasticity in the adult visual cortex. Science 320: 385–388.

McCurry CL, Shepherd JD, Tropea D, Wang KH, Bear MF, Sur M. 2010. Loss of Arc renders the visual cortex impervious to the effects of sensory experience or deprivation. Nat Neurosci 13: 450–457.

Meikle L, Pollizzi K, Egnor A, Kramvis I, Lane H, Sahin M, Kwiatkowski DJ. 2008. Response of a neuronal model of tuberous sclerosis to mammalian target of rapamycin (mTOR) inhibitors: effects on mTORC1 and Akt signaling lead to improved survival and function. J Neurosci 28: 5422–5432.

Moretti P, Zoghbi HY. 2006. MeCP2 dysfunction in Rett syndrome and related disorders. Curr Opin Genet Dev 16: 276–281.

Muller CM, Griesinger CB. 1998. Tissue plasminogen activator mediates reverse occlusion plasticity in visual cortex. Nat Neurosci 1: 47–53.

Murthy VN, Schikorski T, Stevens CF, Zhu Y. 2001. Inactivity produces increases in neurotransmitter release and synapse size. Neuron 32: 673–682.

Nedergaard M, Ransom B, Goldman SA. 2003. New roles for astrocytes: redefining the functional architecture of the brain. Trends Neurosci 26: 523–530.

Okun M, Lampl I. 2008. Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities. NatNeurosci 11: 535–537.

Oray S, Majewska A, Sur M. 2004. Dendritic spine dynamics are regulated by monocular deprivation and extracellular matrix degradation. Neuron 44: 1021–1030.

Patterson SL, Pittenger C, Morozov A, Martin KC, Scanlin H, Drake C, Kandel ER. 2001. Some forms of cAMP-mediated long-lasting potentiation are associated with release of BDNF and nuclear translocation of phospho-MAP kinase. Neuron 32: 123–140.

Perea G, Araque A. 2007. Astrocytes potentiate transmitter release at single hippocampal synapses. Science 317: 1083–1086.

(p.87) Pettit DL, Perlman S, Malinow R. 1994. Potentiated transmission and prevention of further LTP by increased CaMKII activity in postsynaptic hippocampal slice neurons. Science 266: 1881–1885.

Pizzorusso T, Medini P, Berardi N, Chierzi S, Fawcett JW, Maffei L. 2002. Reactivation of ocular dominance plasticity in the adult visual cortex. Science 298: 1248–1251.

Pologruto TA, Yasuda R, Svoboda K. 2004. Monitoring neural activity and [Ca2+] with genetically encoded Ca2+ indicators. J Neurosci 24: 9572–9579.

Pratt KG, Aizenman CD. 2007. Homeostatic regulation of intrinsic excitability and synaptic transmission in a developing visual circuit. J Neurosci 27: 8268–8277.

Quinlan EM, Philpot BD, Huganir RL, Bear MF. 1999. Rapid, experience-dependent expression of synaptic NMDA receptors in visual cortex in vivo. Nat Neurosci 2: 352–357.

Rutherford LC, Nelson SB, Turrigiano GG. 1998. BDNF has opposite effects on the quantal amplitude of pyramidal neuron and interneuron excitatory synapses. Neuron 21: 521–530.

Schuman EM. 1999. Neurotrophin regulation of synaptic transmission. Curr Opin Neurobiol 9: 105–109.

Schummers J, Yu H, Sur M. 2008. Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex. Science 320: 1638–1643.

Seeburg DP, Feliu-Mojer M, Gaiottino J, Pak DT, Sheng M. 2008. Critical role of CDK5 and Polo-like kinase 2 in homeostatic synaptic plasticity during elevated activity. Neuron 58: 571–583.

Shepherd GM, Stepanyants A, Bureau I, Chklovskii D, Svoboda K. 2005. Geometric and functional organization of cortical circuits. Nat Neurosci 8: 782–790.

Smith GB, Heynen AJ, Bear MF. 2009. Bidirectional synaptic mechanisms of ocular dominance plasticity in visual cortex. Philos Trans R Soc Lond B Biol Sci 364: 357–367.

Song S, Abbott LF. 2001. Cortical development and remapping through spike timing-dependent plasticity. Neuron 32: 339–350.

Stellwagen D, Malenka RC. 2006. Synaptic scaling mediated by glial TNF-alpha. Nature 440: 1054–1059.

Stellwagen D, Beattie EC, Seo JY, Malenka RC. 2005. Differential regulation of AMPA receptor and GABA receptor trafficking by tumor necrosis factor-alpha. J Neurosci 25: 3219–3228.

Sweatt JD. 2001. The neuronal MAP kinase cascade: a biochemical signal integration system subserving synaptic plasticity and memory. J Neurochem 76 (1): 1–10.

Tavazoie SF, Alvarez VA, Ridenour DA, Kwiatkowski DJ, Sabatini BL. 2005. Regulation of neuronal morphology and function by the tumor suppressors Tsc1 and Tsc2. Nat Neurosci 8: 1727–1734.

Thomas GM, Huganir RL. 2004. MAPK cascade signalling and synaptic plasticity. Nat Rev Neurosci 5: 173–183.

Tropea D, Kreiman G, Lyckman A, Mukherjee S, Yu H, Horng S, Sur M. 2006. Gene expression changes and molecular pathways mediating activity-dependent plasticity in visual cortex. Nat Neurosci 9: 660–668.

Tropea D, Giacometti E, Wilson NR, Beard C, McCurry C, Fu DD, Flannery R, Jaenisch R, Sur M. 2009. Partial reversal of Rett syndrome-like symptoms in MeCP2 mutant mice. Proc Natl Acad Sci USA 106: 2029–2034.

Turrigiano GG. 2008. The self-tuning neuron: synaptic scaling of excitatory synapses. Cell 135: 422–435.

Turrigiano GG, Nelson SB. 2000. Hebb and homeostasis in neuronal plasticity. Curr Opin Neurobiol 10: 358–364.

Wang KH, Majewska A, Schummers J, Farley B, Hu C, Sur M, Tonegawa S. 2006. In vivo two-photon imaging reveals a role of Arc in enhancing orientation specificity in visual cortex. Cell 126: 389–402.

Wiesel TN, Hubel DH. 1963. Single-cell responses in striate cortex of kittens deprived of vision in one eye. J Neurophysiol 26: 1003–1017.

Wilson NR, Ty MT, Ingber DE, Sur M, Liu G. 2007. Synaptic reorganization in scaled networks of controlled size. J Neurosci 27: 13581–13589.

Wilson NR, Kang J, Hueske EV, Leung T, Varoqui H, Murnick JG, Erickson JD, Liu G. 2005. Presynaptic regulation of quantal size by the vesicular glutamate transporter VGLUT1. J Neurosci 25: 6221–6234.

Xia Z, Dudek H, Miranti CK, Greenberg ME. 1996. Calcium influx via the NMDA receptor induces immediate early gene transcription by a MAP kinase/ERK-dependent mechanism. J Neurosci 16: 5425–5436.

(p.88) Ying SW, Futter M, Rosenblum K, Webber MJ, Hunt SP, Bliss TV, Bramham CR. 2002. Brain-derived neurotrophic factor induces long-term potentiation in intact adult hippocampus: requirement for ERK activation coupled to CREB and upregulation of Arc synthesis. J Neurosci 22: 1532–1540.

Yoshii A, Constantine-Paton M. 2007. BDNF induces transport of PSD-95 to dendrites through PI3K-AKT signaling after NMDA receptor activation. Nat Neurosci 10: 702–711.

Zhang F, Aravanis AM, Adamantidis A, de Lecea L, Deisseroth K. 2007. Circuit-breakers: optical technologies for probing neural signals and systems. Nat Rev Neurosci 8: 577–581.

Zheng WH, Quirion R. 2004. Comparative signaling pathways of insulin-like growth factor-1 and brain-derived neurotrophic factor in hippocampal neurons and the role of the PI3 kinase pathway in cell survival. J Neurochem 89: 844–852.

Zhu JJ, Qin Y, Zhao M, Van Aelst L, Malinow R. 2002. Ras and Rap control AMPA receptor trafficking during synaptic plasticity. Cell 110: 443–455.

Zoghbi HY. 2003. Postnatal neurodevelopmental disorders: meeting at the synapse? Science 302: 826–830.