At specific maturational stages, neural circuits enter sensitive periods of heightened plasticity, during which the development of both brain and behavior are highly receptive to particular experiential information. A relatively advanced understanding of the regulatory mechanisms governing the initiation, closure, and reinstatement of sensitive period plasticity has emerged from extensive research examining the development of the visual system. In this article, we discuss a large body of work characterizing the pronounced nonlinear changes in fear learning and extinction that occur from childhood through adulthood, and their underlying neural substrates. We draw upon the model of sensitive period regulation within the visual system, and present burgeoning evidence suggesting that parallel mechanisms may regulate the qualitative changes in fear learning across development.
Across development, both the brain circuits and behavioral capabilities of an organism undergo pronounced maturational changes. Two distinct types of developmental adaptation occur simultaneously. An evolutionarily refined genetic program of development coordinates the emergence of the array of behaviors typically present at a given life stage. Alongside this species-typical course of development, a simultaneous process of specialization occurs in response to the unique experiences of the individual. This experience-dependent plasticity enables the refinement of brain and behavior in accordance with the specific informational landscape and functional demands of a given individual’s environment. This tailoring of brain development to the needs of the individual occurs in a sequential and hierarchically organized manner, with the maturation of lower level functions preceding that of higher-order processes. Each functional process, and its underlying brain circuit, undergoes a temporally limited ‘sensitive period’ of heightened plasticity during which neural development is especially receptive to particular types of experience.
Such sensitive periods have been identified across species in the development of perceptual and motor systems, as well as in cognitive, affective, and social capabilities. As a sensitive period closes, the organization of neural circuits becomes increasingly stable, yielding a corresponding stability in the behavioral functions they implement. Atypical experience during a sensitive developmental window can lead to persistent functional abnormalities. The term ‘critical period’ has been used to refer to windows of extreme interdependence between experience and development, after which a decrease in neural plasticity typically renders the behavioral outcome irreversible. However, recent research has identified mechanisms through which plasticity can be reinstated beyond the closure of a critical period, suggesting that aberrant neurodevelopmental outcomes may not necessarily be immutable. A provisional model of the regulatory mechanisms governing the initiation of sensitive period plasticity, its closure, and more recently, its reinstatement has emerged through extensive research examining the development of the visual, auditory, and motor systems. This model also appears to generalize to developmental plasticity in neural circuits within other modalities (Nabel and Morishita, 2013).
Although our understanding of mechanisms governing sensitive period changes in plasticity stems primarily from research in sensory and motor systems, there is also abundant evidence for sensitive periods in affective development. In contrast to the development of sensory and motor systems, structural and functional changes within affective neural circuits continue well into young adulthood. The neurocircuitry supporting affective learning and regulation comprises a network of cortical and subcortical regions that exhibit extended maturational trajectories (Gogtay et al, 2004; Raznahan et al, 2014). Variation in early-life experience can persistently alter the development and function of these circuits (Lupien et al, 2009), highlighting the important role of experience-dependent plasticity in determining adult affective outcomes. Many psychiatric and behavioral disorders that are thought to involve dysregulated affective learning typically exhibit adolescent onsets, including anxiety and substance abuse (Kessler et al, 2005; Wagner and Anthony, 2002). An improved understanding of the factors that regulate affective plasticity may ultimately provide a foundation for potential interventions that might alter such maladaptive neurodevelopmental outcomes through the reinstatement of sensitive period plasticity.
In this article, we attempt to synthesize a body of work characterizing pronounced nonlinear changes in fear learning and its underlying neural substrates from birth until adulthood. We draw upon the relatively sophisticated understanding of the mechanisms governing critical period regulation within the visual system and discuss how similar neuroplastic changes might underlie qualitative maturational changes in fear learning. We begin by reviewing the molecular mechanisms that govern the opening, closure, and reinstatement of critical periods for the development of ocular dominance in visual cortex. We then turn our attention to affective development, first describing the well-characterized neurocircuitry underlying fear learning and regulation in adulthood, and then presenting the qualitative behavioral and neural changes in this functional system from infancy through adulthood. We then discuss the mechanisms known to regulate plasticity in the fear neurocircuitry, highlighting the clear parallels between regulators of plasticity within the visual system and those influencing juvenile maturation of fear learning. We present burgeoning evidence suggesting that similar mechanisms may contribute to nonlinear behavioral changes in fear expression during adolescence. We conclude with a discussion of how multiple interventions that have been shown to reintroduce neural plasticity beyond the closing of a critical period may similarly be able to alter the function of fear-learning neurocircuitry. The potential to promote plastic changes in the function of affective circuits beyond normal sensitive periods holds promise for the treatment of anxiety, as well as other behavioral and psychiatric disorders in which atypical early affective experience might play a central etiological role.
REGULATION OF CRITICAL PERIOD PLASTICITY WITHIN THE VISUAL SYSTEM: ONSET, CLOSURE, AND REINSTATEMENT
Our understanding of critical periods in brain plasticity stems largely from research on the development of sensory systems (Hensch, 2004; Knudsen, 2004). The organization of the visual systems is established early in development. Work by Hubel and Wiesel demonstrated that binocular visual experience during early life is critical for the development of normal vision. They found that temporarily obstructing visual input to one eye during a time window early in life results in altered organization of primary visual cortex. When occlusion of one eye occurred during a temporally limited period early in development, cortical columns within the occipital cortex representing information from the affected eye decreased in size, ceding their cortical area to neurons encoding information from the functional eye. As a result, vision in the occluded eye is impaired, a condition termed amblyopia. Restoration of input to the eye following the critical period fails to normalize vision. Monocular deprivation in adulthood fails to engender these neural and functional alterations, providing evidence of a critical period for experience-dependent plasticity in the visual system. Deprivation of visual experience early in life in rodents has served as a model for probing the molecular mechanisms that govern the opening and closing of critical periods.
Neuronal signaling in the neonatal brain is predominantly excitatory, with inhibitory neurotransmission increasing as the organism matures. Within the visual system, this increase in inhibitory signaling initiates the opening of a critical period for ocular dominance (Bavelier et al, 2010; Hensch, 2004). The balance between excitatory and inhibitory signaling appears to be a primary regulator of the onset of critical period plasticity. Gamma aminobutyric acid (GABA) is the primary inhibitory neurotransmitter in the vertebrate brain. The normal developmental increase in GABA neurotransmission can be prevented by genetically disrupting GABA synthesis in the rodent. This manipulation prevents the onset of the critical period for ocular dominance. Administration of benzodiazepines, which enhance GABA signaling, induced critical period plasticity in these genetically altered mice, such that monocular deprivation produced the typical neural and functional alterations in ocular dominance (Hensch et al, 1998). This restoration of plasticity occurred even in adult animals. Similarly, administration of benzodiazepine, or other manipulations that increase GABAergic inhibitory neurotransmission, prematurely advances the onset of critical periods in typically developing animals (Di Cristo et al, 2007; Fagiolini and Hensch, 2000; Sugiyama et al, 2008). Benzodiazepine administration subsequent to the closure of a critical period fails to reintroduce neuroplasticity (Fagiolini and Hensch, 2000), suggesting that the initial maturation of inhibitory signaling exerts a unique influence on the wiring of neural circuits.
The closure of critical period plasticity in visual cortex is accompanied by maturational changes in the extracellular matrix surrounding a class of GABAergic neurons that express parvalbumin (PV). The formation of perineuronal nets, an organized form of chondroitin sulfate proteoglycan-containing extracellular matrix, coincides with the end of the critical period for ocular dominance (Galtrey and Fawcett, 2007; Pizzorusso et al, 2002). The organization of perineuronal nets is delayed by dark-rearing, an environmental condition that extends the duration of the critical period, and degradation of PNNs in the adult rodent reinstates critical period plasticity in visual cortex (Pizzorusso et al, 2002). This work suggests that the formation of perineuronal nets is a molecular mechanism that functions as a ‘brake’ on critical period plasticity (Bavelier et al, 2010).
Other structural mechanisms such as myelination and synaptic pruning may also act as structural regulators of critical period plasticity. In the human brain, myelination begins in the brainstem at approximately 6 months of age, with a regional progression from posterior to anterior and inferior to superior (Lenroot and Giedd, 2006). White matter tracts throughout the majority of the brain are myelinated by early childhood; however, myelination of axons in several cortical areas continues into young adulthood, suggesting an extended period of neuroplasticity in these circuits (Yakovlev and Lecours, 1967). With the closing of the visual critical period, cortical myelin matures and myelin associated inhibitors including NogoA, myelin-associated glycoprotein (MAG), and oligodendrocyte-myelinglycopretein (OMgp) are expressed and act upon a common Nogo receptor NgR, which is involved in limiting plasticity (Akbik et al, 2012). NgR knockout mice display prolonged visual plasticity, suggesting its requirement for closure of the critical period (McGee et al, 2005).
The term critical period was introduced to capture the strong temporal limitation on experience-dependent neurodevelopmental outcomes. However, subsequent to the delineation of the molecular mechanisms governing critical period plasticity, continued research has identified a range of manipulations that can reintroduce plasticity in the visual beyond the critical developmental period (Bavelier et al, 2010). In general, these interventions work by removing structural barriers to plasticity, including perineuronal nets and myelin-associated inhibitory proteins or by altering the balance between local excitatory and inhibitory neurotransmission. Directly reducing GABA transmission in adulthood can partially reactivate ocular dominance plasticity (Harauzov et al, 2010). In addition, neuromodulators of excitatory-inhibitory circuit balance such as serotonin can also reset this balance and promote the recovery of visual functions in adult amblyopic animals (Vetencourt et al, 2008). Acetylcholine transmission also modulates plasticity within the visual system. A novel membrane-associated protein, Lynx1, binds to the nicotinic acetylcholine receptor (nAChR) and attenuates nicotinic cholinergic transmission and has been shown to have increased expression as the visual critical period closes (Morishita et al, 2010). Genetic deletion of Lynx1 led to increases in nicotinic transmission and allows the critical period to remain open into adulthood (Morishita et al, 2010).
A key question is whether these mechanisms governing the opening and closing of critical period plasticity in the visual system also apply to developmental periods of plasticity in affective function, most notably fear regulation, which exhibits marked functional changes well into young adulthood (Casey et al, 2012; Shechner et al, 2014).
PAVLOVIAN FEAR LEARNING AND EXTINCTION
The ability to recognize and respond appropriately to threats in the environment is critical to an organism’s survival. This adaptive function relies on the ability to rapidly and persistently learn associations between previously experienced negative events and the cues and contexts that predicted their occurrence. Experimental studies typically model this real-world associative learning using Pavlovian conditioning paradigms, in which a neutral cue is paired with an intrinsically aversive stimulus. This pairing produces a learned association between the previously neutral cue, now the conditioned stimulus (CS), and the aversive unconditioned stimulus (US), which enables the CS to elicit a range of physiological and behavioral conditioned responses (CRs) to the anticipated threat. In experimental studies of rodents, the most typical CR assessed is freezing. In humans, common CRs include changes in skin conductance, startle responses, and pupil dilation. Fear learning is rapid and long-lasting, typically requiring only a few pairings of the CS and US and persisting for long periods after the initial association is formed. Learned fear often extends to the broader context in which an aversive experience occurs. Contextual fear is assessed by measuring conditioned responses to the original fear-learning context, in the absence of the conditioned cue.
Although learned fear memories are persistent, their expression can be inhibited through new learning that a once threatening stimulus is now safe. Experimentally, this process of extinction learning is modeled by repeatedly presenting the CS without the aversive US, which is typically accompanied by a gradual decrease in the expression of the CR. This mitigation in fear responding does not reflect unlearning of the original fear association, but instead appears to reflect the formation of a new competing association between the CS and safety. The persistence of the original fear memory is evidenced by the fact that extinguished fear often returns under a number of circumstances including a change in context (renewal), exposure to an aversive stimulus (reinstatement), or the mere passage of time (spontaneous recovery) (Bouton, 2004).
NEURAL CIRCUITS UNDERLYING FEAR LEARNING AND REGULATION IN ADULTHOOD
Studies in animal models employing Pavlovian fear conditioning and extinction paradigms have elucidated a detailed model of the brain circuitry underlying fear learning and regulation in adulthood. The amygdala plays a central role in the acquisition, storage, and expression of fear learning. The amygdala is a heterogeneous structure consisting of multiple functionally distinct subnuclei. The lateral nucleus of the amygdala (LA) receives convergent sensory and somatosensory input carrying information about CS and US presentation (Amaral, 1986; McDonald et al, 1996; Price, 2003). Plasticity within the LA following the paring of these stimuli results in the formation of the learned fear memory (Quirk et al, 1997; Quirk et al, 1995). Upon subsequent CS presentations, stimulus-evoked firing within the LA activates the central nucleus of the amygdala (CE), triggering the expression of the fear response via descending to brainstem and hypothalamic regions (Davis, 2000). The LA maintains a long-term representation of this fear memory (Repa et al, 2001), regardless of whether or not the behavioral fear response is expressed. This persistent fear encoding within the LA likely enables the return of fear, even when fear expression has been inhibited through extinction learning (Bouton, 2004). Although the LA exhibits transient responses to CS presentation, involvement of the prelimbic region of the medial prefrontal cortex (PL) appears to be necessary for the sustained expression of fear (Corcoran and Quirk, 2007). Neurons in the PL exhibited sustained firing in response to CS presentation that mirrors the duration of the freezing response itself (Burgos-Robles et al, 2009). The PL receives afferent input from the LA (McDonald, 1991) and projects to CE, via the basal nucleus of the amygdala. Following CS presentation, phasic signals from the LA may initiate sustained prelimbic firing that directly influences fear expression through its CE projections.
The contextual learning that occurs during fear conditioning depends upon interaction between the amygdala and the hippocampus (Fanselow, 2000; Maren et al, 2013). Whereas amygdala damage subsequent to conditioning abolishes both cued and contextual fear, a lesion localized to the hippocampus selectively impairs fear expression to the context (Kim and Fanselow, 1992). The hippocampus is thought to support the construction of a contextual representation, which becomes associated with the aversive stimulus through synaptic plasticity in the amygdala (Maren and Fanselow, 1995; Maren et al, 2013). Expression of contextual fear is also dependent on the PL (Corcoran and Quirk, 2007), which receives afferent projections from the hippocampus (Condé et al, 1995). This network of regions, with the amygdala at its center, interacts to support the acquisition of fear learning during adulthood.
The acquisition, consolidation, and retrieval of initial extinction learning involve a dynamic interaction between the amygdala and the infralimbic subregion of the medial prefrontal cortex (IL) (Quirk and Mueller, 2007). The amygdala is necessary for the initial acquisition of extinction learning (Herry et al, 2006; Kim et al, 2007a; Sotres-Bayon et al, 2007). During extinction learning, a population of cells within the basal nucleus (BA) of the amygdala increases in firing rate in response to unreinforced CS presentations (Herry et al, 2008). These neurons have reciprocal connections with the IL, which plays a critical role in extinction learning, consolidation, and retrieval (Burgos-Robles et al, 2007; Morgan and LeDoux, 1995; Morgan et al, 1993; Quirk et al, 2000). Following extinction training, presentation of the CS evokes activity within IL neurons that is associated with reduced conditioned fear expression (Milad and Quirk, 2002). This cortical activity is thought to modulate fear expression via the intercalated cell masses (ITC). The ITC is a population of inhibitory cells interposed between the BA/LA and CE. Activation of these cells via increased firing in IL inhibits the LA signals to the CE, decreasing the expression of conditioned fear responses (Berretta, 2005; Likhtik et al, 2008). In contrast to the IL, the neighboring PL opposes extinction recall, driving the expression of fear responses (Corcoran and Quirk, 2007; Sierra-Mercado et al, 2011; Sotres-Bayon et al, 2012). During extinction training, CS-evoked activity within PL predicts the subsequent failure of extinction retrieval (Burgos-Robles et al, 2009), suggesting that the dynamic interaction between the amygdala and IL and PL cortical regions determines the success or failure of extinction learning. Projections from the hippocampus to both the IL and PL, as well as the amygdala, appear to mediate the context-dependent expression of extinction (Ji and Maren, 2005; Sotres-Bayon et al, 2012), providing contextual information that influences whether extinction learning is retrieved, or the original fear memory returns (Bouton, 2004; Fanselow, 2000; Maren et al, 2013).
Fear-conditioning studies in adult humans suggest that the neurocircuitry underlying fear learning and extinction is highly evolutionarily conserved (Hartley and Phelps, 2013; Phelps and LeDoux, 2005). Human lesion and neuroimaging studies reveal a central role for the amygdala in fear conditioning (Bechara et al, 1995; Büchel et al, 1998; Cheng et al, 2006; LaBar et al, 1998; LaBar et al, 1995). In addition to the engagement of the amygdala, functional magnetic resonance imaging (fMRI) studies of fear conditioning commonly report CS-evoked increases in blood oxygen level-dependent (BOLD) activation in the dorsal anterior cingulate cortex (dACC). CS-evoked BOLD activation as well as cortical thickness in this region correlates positively with the magnitude of conditioned fear expression, motivating the suggestion that this region may be a human homologue of the rodent PL (Hartley and Phelps, 2013; Milad et al, 2007a; Milad and Quirk, 2012). Human imaging studies that dissociate neural responses to conditioned cues and contexts corroborate the involvement of the hippocampus in contextual fear learning (Alvarez et al, 2008; Marschner et al, 2008).
Functional imaging studies of extinction report increases in BOLD signal in a subgenual anterior cingulate/vmPFC region during initial extinction learning, as well as a corresponding decrease in amygdala BOLD activation (Kalisch et al, 2006; Milad et al, 2007b; Phelps et al, 2004). Increases in BOLD activation are also observed during extinction recall (Phelps et al, 2004). Both the magnitude of vmPFC BOLD signal as well as the thickness of the cortex in this region have been found to correlate with the degree of extinction retrieval (Hartley et al, 2011; Milad et al, 2005; Milad et al, 2007b). On the basis of these findings, the subgenual vmPFC region has been proposed to be a potential human homologue of the rodent IL region (Hartley and Phelps, 2013; Milad et al, 2007a; Milad and Quirk, 2012), and may diminish fear expression via its projections to the amygdala. Context-dependent retrieval of extinction is associated with increased BOLD activation in the hippocampus (Kalisch et al, 2006; Milad et al, 2007b), and hippocampal lesions impair context-dependent fear reinstatement (LaBar and Phelps, 2005), a finding that parallels observations in rodents (Wilson et al, 1995).
DEVELOPMENTAL CHANGES IN FEAR-LEARNING CIRCUITS
Although research across species has delineated a fairly detailed model of the neurocircuitry supporting fear learning and extinction during adulthood, there has been much less study of the neurocognitive development of these processes. The prefrontal and subcortical circuitry implicated in adult fear learning undergoes substantial developmental change from childhood through adulthood (Gogtay et al, 2004; Lenroot and Giedd, 2006; Raznahan et al, 2014). Mirroring these pronounced changes in the brain, numerous studies to date suggest that fear learning and regulation exhibit qualitative changes across development (Figure 1).
In rodents, fear learning emerges early in postnatal development and appears to track the functional maturation of the amygdala (Landers and Sullivan, 2012). Prior to postnatal day 10 (P10), infant rats exhibit attenuated amygdala responses to aversive stimuli. Behaviorally, these animals exhibit a paradoxical approach response to an odor stimulus previously paired with shock (Camp and Rudy, 1988; Sullivan et al, 2000). This early neonatal period corresponds to a sensitive period for attachment learning, and the suppression of fear responding during this period may functionally promote attachment between the infant and caregiver, even if the quality of care received is poor (Landers and Sullivan, 2012). After P10, the odor-shock conditioning produces a conditioned odor aversion, reflecting the emergence of cued fear learning. This behavioral change coincides with the onset of learning-induced synaptic plasticity within the amygdala (Thompson et al, 2008). The timing of the functional maturation of the amygdala appears to be experience-dependent. Through suppression of pup corticosterone levels, maternal presence delays the onset of fear conditioning whereas maternal separation promotes earlier maturation of aversive learning (Moriceau and Sullivan, 2006). Even once animals have developed the ability to learn conditioned aversion, infant fear memories remain qualitatively different from those of adults in that they are not as persistent. Conditioned fear learned at P17 is typically forgotten within 10 days (Callaghan and Richardson, 2012). Notably, this infantile amnesia for fear memories is also experience-dependent, and is attenuated under conditions of early-life stress. Animals that have experienced chronic maternal separation at P17 exhibit full recall of fear 10 days later (Callaghan and Richardson, 2012).
Contextual fear conditioning in rodents emerges later than cued fear learning (Rudy, 1993). Whereas pre-weanling (P17) rats do not appear to extend learned fear associations to the broader surrounding environment, adult-like contextual fear conditioning emerges by P24. The emergence of contextual fear learning may reflect increased maturation of the hippocampus and its connections to the amygdala in the post-weanling animals (Raineki et al, 2010). Contextual fear memories in this juvenile, pre-adolescent phase are also labile, and undergo forgetting with the passage of time (Akers et al, 2014). This infantile amnesia stems from heightened hippocampal neurogenesis, which is thought to induce reconfiguration of the neural circuits that encode hippocampal-dependent memories (Akers et al, 2014). In contrast, during adolescence, once contextual fear learning is acquired, its expression undergoes a temporary suppression (Pattwell et al, 2011). In mice, contextual fear memories learned during or prior to adolescence (P29) are not expressed during this developmental stage; however, these memories reemerge during the transition into adulthood (>P45). This temporary suppression of contextual fear expression is proposed to foster exploratory behavior that would be necessary to support the typical transition from maternal care into independence during this developmental stage.
As with fear learning, the acquisition and expression of extinction learning also changes markedly across development. Extinction training in pre-weanling animals (prior to P24) produces the typical decrease in fear expression. However, unlike adult animals, these animals do not exhibit the fear re-emergence phenomena that typically occur following extinction training (Gogolla et al, 2009; Kim and Richardson, 2007b; Yap and Richardson, 2007). This resistance of extinction to spontaneous recovery, reinstatement, and renewal suggests that extinction training at this developmental stage may evoke a process akin to unlearning of the original fear memory, as opposed to the formation of a new competing safety memory. Consistent with this interpretation, extinction learning in these pre-weanling animals does not depend upon engagement of the IL, but instead appears to be amygdala-dependent (Kim et al, 2009; Kim and Richardson, 2008). This suggests that early-life extinction may effectively yield fear erasure. Paralleling the influence of stress on the maturation of fear learning, separation from the mother advances the onset of adult-like extinction learning, from which fears reemerge (Callaghan and Richardson, 2011). In contrast to the ease with which fears are diminished in these younger animals, both fear extinction learning and retention are attenuated during adolescence (Kim et al, 2011; McCallum et al, 2010; Pattwell et al, 2012). Relative to pre- and post-adolescent animals, adolescents exhibit diminished fear extinction learning that is paralleled by an absence of fear-learning-induced synaptic plasticity within the PL and extinction-learning-induced plasticity within the IL (Pattwell et al, 2012).
These studies suggest that the development of both cued fear extinction and contextual fear expression progress in a nonlinear manner, with adolescents showing diminished abilities relative to preadolescents and adults. Adolescence is a time of exploration when one must leave the safety and stability of his or her familial environment in order to attain reproductive success; thus, a suppression of contextual fear may contribute to the fearlessness required for exploring new environments that is typically seen with this age group (Casey et al, 2010; Spear, 2000). As specific danger cues remain relevant during this novelty-seeking period, cued fear expression remains intact and is resistant to extinction during adolescence. Combined, these behaviors would enable the adolescent to remain both exploratory and cautious, optimizing chances for survival and reproductive success. The circuit-level changes in the brain underlying these developmental discontinuities in fear expression have yet to be clearly delineated. However, the pronounced structural remodeling of subcortical-prefrontal connections (eg myelination, synaptic pruning) that occurs during adolescence is likely to contribute to these qualitative shifts in fear expression (Somerville and Casey, 2010; Spear, 2000). For example, there is substantial pruning of neurons projecting from the IL to the basal amygdala from adolescence to adulthood (Cressman et al, 2010). Changes in connectivity between both the amygdala and the hippocampus, and the IL and PL during adolescence may initiate the shift from the restricted subcortical circuitry governing fear learning in juvenile stages, toward the more flexible and expansive circuit for fear regulation that is evident in adulthood. Clarifying precisely how these transitions in the fear neurocircuitry during adolescence yield pronounced nonlinearity in fear learning and extinction remains an important area for future investigation.
Human studies of fear learning across development have been somewhat limited by the methodological constraints involved in designing effective aversive learning paradigms that are ethical to conduct in children. Typically, these paradigms use unconditioned stimuli such as white noise, unpleasant images, or a combination of the two (Shechner et al, 2014). Developmental studies of human fear learning corroborate findings in animals of the early maturation of fear learning. Children as young as 3 years show evidence of fear acquisition (Gao et al, 2010), with discrimination between an aversively conditioned and a neutral stimulus (CS+>CS−) improving with age (Gao et al, 2010; Glenn et al, 2012). This increased discrimination ability with age continues into adulthood, and is associated with distinct developmental patterns of neural activity during fear learning (Lau et al, 2011). Consistent developmental changes in fear extinction learning have been observed across species. As in rodents, fear extinction in humans is also selectively attenuated during adolescence relative to children and adults (Pattwell et al, 2012). Although there have not been functional imaging studies to date of fear extinction across development, a recent fMRI study examining developmental changes in connectivity between the medial prefrontal cortex and the amygdala found that although BOLD activity within the vmPFC and the amygdala are inversely correlated in adolescence and adulthood, activity in these regions is positively correlated during childhood (Gee et al, 2013b). Although these functional connectivity measures do not directly reflect the non-linear developmental pattern observed in fear extinction and associated synaptic plasticity (Pattwell et al, 2012), they provide an indication of the pronounced maturational changes in the dynamic interaction between these regions. Interestingly, mirroring the early maturation of the fear neurocircuitry induced by maternal separation in the rodent (Callaghan and Richardson, 2011), institutionally-reared children who experienced early maternal deprivation show the more mature pattern of positive vmPFC-amygdala coupling (Gee et al, 2013a). This suggests that, as in rodents, the maturational trajectory of human fear neurocircuitry is also highly sensitive to experiential variation during early development (Tottenham, 2013).
DEVELOPMENTAL REGULATION OF FEAR-RELATED PLASTICITY
The molecular mechanisms governing sensitive period plasticity within affective circuits have not been characterized in the same detail as those that influence the development of the visual system. However, burgeoning evidence suggests that changes in the balance between excitatory and inhibitory signaling and structural changes in the brain including the formation of perineuronal nets, synaptic pruning, and myelination of white matter tracts also modulate affective neuroplasticity, regulating the opening and closure of sensitive periods for fear and extinction learning (Figure 1).
Early in development, neuronal communication is predominantly excitatory. The increase in inhibitory signaling that initiates the onset of critical periods is mediated by activity at the GABAA receptor (Hensch, 2005). At birth, the GABAA receptor is excitatory, with a shift to inhibitory action occurring early in development (Ben-Ari et al, 2012; Le Magueresse and Monyer, 2013). Several elements of the GABAergic system continue to exhibit marked developmental change through adolescence and early adulthood (Kilb, 2012; Le Magueresse and Monyer, 2013). GABAergic synapse proliferation, GABA receptor and transporter distribution, and metabolic enzyme production, all modulate GABAergic tone. Each of these components contribute to the fine tuning of the excitatory/inhibitory balance in the brain and are likely to play important roles in regulating developmental stage-specific alterations in neural plasticity and behavior. Within the amygdala, a number of changes in GABAergic function occur during pre-adolescence, including the emergence and maturation of parvalbumin-expressing GABAergic interneurons, as well as decreases in the density of GABAergic cell bodies and increases in the density of GABAergic fibers (Ehrlich et al, 2013). These changes appear to play a critical role in several of the qualitative changes in fear learning that occur during this stage. The switch from approach to avoidance responding to a conditioned stimulus that typically occurs at P10 in the rat is prevented by GABAA blockade (Sullivan et al, 2000; Thompson et al, 2008). Similarly, the rapid forgetting of fear learning early in development, referred to as infantile amnesia, is mediated by the GABAA receptor (Kim et al, 2006). Unlike adult fear extinction, extinction learning at P17, when fear recovery is absent, is not GABA-dependent (Kim and Richardson, 2010).
The formation of perineuronal nets surrounding GABAergic interneurons acts as structural brakes that contribute to the closure of sensitive periods in ocular dominance plasticity (Pizzorusso et al, 2002). Similarly, PNNs appear to play a critical role in enabling the stability to fear memories. The formation of PNNs within the amygdala appear to support the transition from the infantile extinction that resembles fear erasure, to the more adult-like state in which recovery of extinguished fear typically occurs (Gogolla et al, 2009; Gundelfinger et al, 2010). Moreover, structural degradation of these PNNs in adulthood reintroduces a juvenile-like state in which extinction results in a persistent attenuation of fear memory (Gogolla et al, 2009). There are two possible mechanisms by which degradation of PNNs might enable fear memory erasure. PNNs may stabilize fear memories by rendering potentiated synapses resistant to reversal of long-term potentiation, or PNN degradation might give rise to changes in local GABA-mediated inhibition. The latter mechanism is plausible given that PNNs form primarily around parvalbumin-positive GABAergic interneurons and that GABAergic neurotransmission mediates several forms of BLA synaptic plasticity (Gogolla et al, 2009).
Although inhibitory signaling in the amygdala matures in a juvenile developmental stage, GABAergic maturation in other brain regions continues well beyond this period. In particular, inhibitory neurotransmission in the prefrontal cortex increases throughout adolescence and does not reach peak levels until young adulthood (Kilb, 2012; Le Magueresse and Monyer, 2013). GABA signaling is not only involved in inhibitory synaptic transmission, but also regulates synapse elimination and axonal pruning (Wu et al, 2012). Thus, increases in prefrontal GABA may play an important organizing role in the restructuring of prefrontal-subcortical connectivity that occurs during adolescence. Brain-derived neurotrophic factor (BDNF) has been implicated in the promotion of GABAergic transmission in the cortex (Hong et al, 2008; Sakata et al, 2009). Cortical BDNF levels reach peak levels during early adolescence (Katoh-Semba et al, 1997), which may represent a mechanism regulating the timing of GABA maturation. Perineuronal nets also form later in the prefrontal cortex than in the amygdala, reaching peak levels in early adulthood (Mauney et al, 2013). As in the amygdala, PNN formation may terminate plastic changes in prefrontal circuitry once the mature adult state is attained. Collectively, these neuroplastic changes in the cortex during adolescence coincide with a transitional phase spanning the juvenile stage in which fear learning and extinction are independent of the cortex and the mature adult stage in which these processes are dynamically regulated by vmPFC-subcortical circuitry (Baker et al, 2013) (Sotres-Bayon and Quirk, 2010). Elucidating the precise manner in which these changes in prefrontal plasticity during adolescence influence fear expression remains an important area for future investigation.
Although our present understanding of the mechanisms governing developmental changes in fear learning is rudimentary, there is clear evidence for common regulators of neural plasticity in both visual and affective brain circuits. The regulatory mechanisms discussed here are by no means exhaustive. For example, sex hormones also exert organizing effects on adolescent neurodevelopment (Spear, 2000) and modulate fear expression (Zeidan et al, 2011). Moreover, it is likely that a combination of cross-modal and domain-specific regulatory mechanisms shape brain development. Finally, although we focused here on the common regulators of neuroplasticity in both the visual system and the aversive learning neurocircuitry, similar mechanisms may also regulate developmental changes in reward learning and the associated corticostriatal circuitry (Haber and Knutson, 2009). Understanding the developmental regulation of neuroplasticity in reward-related circuits is especially important in light of the heightened vulnerability to addiction during adolescence (Chambers et al, 2003).
RENEWING PLASTICITY AS A MECHANISM TO CHANGE FEAR
One of the best examples of parallel mechanisms for renewing plasticity in both visual and fear-related plasticity comes from studies involving modulation of the serotonin system. Chronic administration of a selective serotonin reuptake inhibitor, fluoxetine, has been shown to reinstate ocular dominance plasticity in adulthood and promotes the recovery of visual functions in adult amblyopic animals (Vetencourt et al, 2008). Interestingly, fluoxetine administration to adult animals also produces enhanced extinction that resembles fear erasure (Karpova et al, 2011), similar to the learning observed in pre-adolescent mice prior to the initiation of the molecular ‘brakes’ that stabilize fear memories (Gogolla et al, 2009). In the fluoxetine-treated mice, levels of the growth factor BDNF were increased in the amygdala, and synaptic plasticity within the amygdala was enhanced, similar to what has been observed in the visual cortex. In addition, fluoxetine treatment led to a reduction in the number of PNNs in neurons expressing parvalbumin in the BLA, suggesting a shift to a more immature state, leading to changes in the local inhibitory neurons in this region.
A recent behavioral intervention termed reconsolidation update, which relies upon presenting extinction training within a temporal window opened by an isolated CS presentation, also leads to persistent attenuation of the fear memory (Monfils et al, 2009; Schiller et al, 2009). This intervention suggests that the original fear memory trace may be significantly altered to incorporate the CS–no US learning before re-storage. The result is thought to be a modified memory trace representing the new significance of the CS, which does not promote the return of fear. The molecular mechanisms underlying this form of memory erasure has involved synaptic removal of calcium-AMPA receptor in the lateral amygdala (Clem and Huganir, 2010). In addition, it has recently been shown that this updating procedure epigenetically regulates the expression of a number of plasticity genes in the hippocampus, some which may downregulate molecular ‘brakes’ on plasticity (Gräff et al, 2014). Interestingly, administration of an HDAC2 inhibitor during reconsolidation led to erasure of not only recent but also remote fear memories. These latter studies indicate that pharmacological agents that alter epigenetic regulation of fear memory may constitute another strategy to renew plasticity to permanently attenuate fear memories.
Fear conditioning has been proposed as a model for the real-world learning processes through which cues and contexts associated with traumatic events come to evoke fear. Consistent with this model, patients with anxiety disorders have been found to exhibit altered fear learning and extinction (Lissek et al, 2005; Milad et al, 2008; Milad et al, 2009). Anxiety disorders typically have their onset in adolescence (Kessler et al, 2005), highlighting the importance of understanding the mechanisms underlying both the typical and dysregulated development of the fear neurocircuitry. The basic mechanistic understanding of critical periods within the visual system have informed developmentally timed treatments for disorders such as amblyopia. Similarly, treatments for fear-related disorders such as post-traumatic stress disorder might be tailored as a function of age to employ specific interventions at a developmental stage when they may be most effective. As an example, the attenuation of fear extinction associated with adolescent development may hinder responses to traditional psychotherapy, such as cognitive behavioral therapy (CBT). Because CBT desensitizes an individual to anxiogenic stimuli through repeated exposures (ie extinction learning), future studies aimed at examining whether this treatment is effective during adolescence, when extinction learning is attenuated, may provide insight into how to optimize treatment strategies for anxious individuals. Finally, gaining better understanding of the molecular ‘brakes’ on fear-related plasticity will inform future targeted pharmacological interventions that could be used in combination with the behavioral intervention to reopen windows of plasticity to attenuate fear and anxiety-symptoms, which are core features of numerous psychiatric disorders.
FUNDING AND DISCLOSURE
Drs Hartley and Lee do not have any conflict of interests in relation to the material presented in this review article. Drs Hartley and Lee do not have any financial disclosures or income derived from organizations other than their employer (WCMC) or government and private funding agencies.
Akbik F, Cafferty WB, Strittmatter SM (2012). Myelin associated inhibitors: a link between injury-induced and experience-dependent plasticity. Exp Neurol 235: 43–52.
Akers KG, Martinez-Canabal A, Restivo L, Yiu AP, De Cristofaro A, Hsiang H-LL et al (2014). Hippocampal neurogenesis regulates forgetting during adulthood and infancy. Science 344: 598–602.
Alvarez RP, Biggs A, Chen G, Pine DS, Grillon C (2008). Contextual fear conditioning in humans: cortical-hippocampal and amygdala contributions. J Neurosci 28: 6211–6219.
Amaral DG (1986). Amygdalohippocampal and amygdalocortical projections in the primate brain. Adv Exp Med Biol 203: 3–17.
Baker KD, Den ML, Graham BM, Richardson R (2013). A window of vulnerability: Impaired fear extinction in adolescence. Neurobiol Learn Mem 113: 90–100.
Bavelier D, Levi DM, Li RW, Dan Y, Hensch TK (2010). Removing brakes on adult brain plasticity: from molecular to behavioral interventions. J Neurosci 30: 14964–14971.
Bechara A, Tranel D, Damasio H, Adolphs R, Rockland C, Damasio AR (1995). Double dissociation of conditioning and declarative knowledge relative to the amygdala and hippocampus in humans. Science 269: 1115–1118.
Ben-Ari Y, Khalilov I, Kahle KT, Cherubini E (2012). The GABA excitatory/inhibitory shift in brain maturation and neurological disorders. Neuroscientist 18: 467–486.
Berretta S (2005). Cortico-amygdala circuits: Role in the conditioned stress response. Stress 8: 221–232.
Bouton M (2004). Context and behavioral processes in extinction. Learn Mem 11: 485–494.
Büchel C, Morris J, Dolan RJ, Friston KJ (1998). Brain systems mediating aversive conditioning: an event-related fMRI study. Neuron 20: 947–957.
Burgos-Robles A, Vidal-Gonzalez I, Quirk GJ (2009). Sustained conditioned responses in prelimbic prefrontal neurons are correlated with fear expression and extinction failure. J Neurosci 29: 8474–8482.
Burgos-Robles A, Vidal-Gonzalez I, Santini E, Quirk GJ (2007). Consolidation of fear extinction requires NMDA receptor-dependent bursting in the ventromedial prefrontal cortex. Neuron 53: 871–880.
Callaghan B, Richardson R (2012). The effect of adverse rearing environments on persistent memories in young rats: removing the brakes on infant fear memories. Transl Psychiatry 2: e138.
Callaghan BL, Richardson R (2011). Maternal separation results in early emergence of adult-like fear and extinction learning in infant rats. Behav Neurosci 125: 20–28.
Camp LL, Rudy JW (1988). Changes in the categorization of appetitive and aversive events during postnatal development of the rat. Dev Psychobiol 21: 25–42.
Casey B, Duhoux S, Cohen MM (2010). Adolescence: what do transmission, transition, and translation have to do with it? Neuron 67: 749–760.
Casey BJ, Pattwell SS, Glatt CE, Lee FS (2012). Treating the developing brain: implications from human imaging and mouse genetics. Annu Rev Med 64: 427–439.
Chambers RA, Taylor JR, Potenza MN (2003). Developmental neurocircuitry of motivation in adolescence: a critical period of addiction vulnerability. Am J Psychiatry 160: 1041–1052.
Cheng DT, Knight DC, Smith CN, Helmstetter FJ (2006). Human amygdala activity during the expression of fear responses. Behav Neurosci 120: 1187–1195.
Clem RL, Huganir RL (2010). Calcium-permeable AMPA receptor dynamics mediate fear memory erasure. Science 330: 1108–1112.
Condé F, Maire–lepoivre E, Audinat E, Crepel F (1995). Afferent connections of the medial frontal cortex of the rat. II. Cortical and subcortical afferents. J Comp Neurol 352: 567–593.
Corcoran KA, Quirk GJ (2007). Activity in prelimbic cortex is necessary for the expression of learned, but not innate, fears. J Neurosci 27: 840–844.
Cressman VL, Balaban J, Steinfeld S, Shemyakin A, Graham P, Parisot N et al (2010). Prefrontal cortical inputs to the basal amygdala undergo pruning during late adolescence in the rat. J Comp Neurol 518: 2693–2709.
Davis M (2000). The role of the amygdala in conditioned and unconditioned fear and anxiety. In JP A, (eds). The Amygdala. Oxford UP: Oxford, UK, Vol 2 pp 213–287.
Di Cristo G, Chattopadhyaya B, Kuhlman SJ, Fu Y, Bélanger M-C, Wu CZ et al (2007). Activity-dependent PSA expression regulates inhibitory maturation and onset of critical period plasticity. Nat Neurosci 10: 1569–1577.
Ehrlich DE, Ryan SJ, Hazra R, Guo J-D, Rainnie DG (2013). Postnatal maturation of GABAergic transmission in the rat basolateral amygdala. J Neurophysiol 110: 926–941.
Fagiolini M, Hensch TK (2000). Inhibitory threshold for critical-period activation in primary visual cortex. Nature 404: 183–186.
Fanselow MS (2000). Contextual fear, gestalt memories, and the hippocampus. Behav Brain Res 110: 73–81.
Galtrey CM, Fawcett JW (2007). The role of chondroitin sulfate proteoglycans in regeneration and plasticity in the central nervous system. Brain Res Rev 54: 1–18.
Gao Y, Raine A, Venables PH, Dawson ME, Mednick SA (2010). The development of skin conductance fear conditioning in children from ages 3 to 8 years. Dev Sci 13: 201–212.
Gee DG, Gabard-Durnam LJ, Flannery J, Goff B, Humphreys KL, Telzer EH et al (2013a). Early developmental emergence of human amygdala-prefrontal connectivity after maternal deprivation. Proc Natl Acad Sci USA 110: 15638–15643.
Gee DG, Humphreys KL, Flannery J, Goff B, Telzer EH, Shapiro M et al (2013b). A developmental shift from positive to negative connectivity in human amygdala–prefrontal circuitry. J Neurosci 33: 4584–4593.
Glenn CR, Klein DN, Lissek S, Britton JC, Pine DS, Hajcak G (2012). The development of fear learning and generalization in 8–13 year-olds. Dev Psychobiol 54: 675–684.
Gogolla N, Caroni P, Luthi A, Herry C (2009). Perineuronal nets protect fear memories from erasure. Science 325: 1258–1261.
Gogtay N, Giedd JN, Lusk L, Hayashi KM, Greenstein D, Vaituzis AC et al (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proc Natl Acad Sci US A 101: 8174–8179.
Gräff J, Joseph NF, Horn ME, Samiei A, Meng J, Seo J et al (2014). Epigenetic priming of memory updating during reconsolidation to attenuate remote fear memories. Cell 156: 261–276.
Gundelfinger ED, Frischknecht R, Choquet D, Heine M (2010). Converting juvenile into adult plasticity: a role for the brain’s extracellular matrix. Eur J Neurosci 31: 2156–2165.
Haber SN, Knutson B (2010). The reward circuit: linking primate anatomy and human imaging. Neuropsychopharmacology 35: 4–26.
Harauzov A, Spolidoro M, DiCristo G, De Pasquale R, Cancedda L, Pizzorusso T et al (2010). Reducing intracortical inhibition in the adult visual cortex promotes ocular dominance plasticity. J Neurosci 30: 361–371.
Hartley CA, Fischl B, Phelps EA (2011). Brain structure correlates of individual differences in the acquisition and inhibition of conditioned fear. Cerebral Cortex 21: 1954–1962.
Hartley CA, Phelps EA (2013). Fear models in animals and humans. Pediatric Anxiety Disorders. Springer: NY. pp 3–21.
Hensch TK (2004). Critical period regulation. Annu Rev Neurosci 27: 549–579.
Hensch TK (2005). Critical period plasticity in local cortical circuits. Nat Rev Neurosci 6: 877–888.
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.
Herry C, Ciocchi S, Senn V, Demmou L, Müller C, Lüthi A (2008). Switching on and off fear by distinct neuronal circuits. Nature 454: 600–606.
Herry C, Trifilieff P, Micheau J, Lüthi A, Mons N (2006). Extinction of auditory fear conditioning requires MAPK/ERK activation in the basolateral amygdala. Eur J Neurosci 24: 261–269.
Hong EJ, McCord AE, Greenberg ME (2008). A biological function for the neuronal activity-dependent component of< i> bdnf</i> transcription in the development of cortical inhibition. Neuron 60: 610–624.
Ji J, Maren S (2005). Electrolytic lesions of the dorsal hippocampus disrupt renewal of conditional fear after extinction. Learn Mem 12: 270–276.
Kalisch R, Korenfeld E, Klaas S, Weiskopf N, Seymour B, Dolan R (2006). Context-dependent human extinction memory is mediated by a ventromedial prefrontal and hippocampal network. J Neurosci 26: 9503–9511.
Karpova NN, Pickenhagen A, Lindholm J, Tiraboschi E, Kulesskaya N, Agustsdottir A et al (2011). Fear erasure in mice requires synergy between antidepressant drugs and extinction training. Science 334 1731–1734.
Katoh-Semba R, Takeuchi IK, Semba R, Kato K (1997). distribution of brain-derived neurotrophic factor in rats and its changes with development in the brain. J Neurochem 69: 34–42.
Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry 62: 593–602.
Kilb W (2012). Development of the GABAergic system from birth to adolescence. Neuroscientist 18: 613–630.
Kim J, Lee S, Park H, Song B, Hong I, Geum D et al (2007a). Blockade of amygdala metabotropic glutamate receptor subtype 1 impairs fear extinction. Biochem Biophys Res Commun 355: 188–193.
Kim JH, Hamlin AS, Richardson R (2009). Fear extinction across development: the involvement of the medial prefrontal cortex as assessed by temporary inactivation and immunohistochemistry. J Neurosci 29: 10802–10808.
Kim JH, Li S, Richardson R (2011). Immunohistochemical analyses of long-term extinction of conditioned fear in adolescent rats. Cereb Cortex 21: 530–538.
Kim JH, McNally GP, Richardson R (2006). Recovery of fear memories in rats: role of gamma-amino butyric acid (GABA) in infantile amnesia. Behav Neurosci 120: 40.
Kim JH, Richardson R (2007b). A developmental dissociation in reinstatement of an extinguished fear response in rats. Neurobiol Learn Mem 88: 48–57.
Kim JH, Richardson R (2008). The effect of temporary amygdala inactivation on extinction and reextinction of fear in the developing rat: unlearning as a potential mechanism for extinction early in development. J Neurosci 28: 1282–1290.
Kim JH, Richardson R (2010). New findings on extinction of conditioned fear early in development: theoretical and clinical implications. Biol Psychiatry 67: 297–303.
Kim JJ, Fanselow MS (1992). Modality-specific retrograde amnesia of fear. Science 256: 675–677.
Knudsen EI (2004). Sensitive periods in the development of the brain and behavior. J Cogn Neurosci 16: 1412–1425.
LaBar K, Gatenby J, Gore J, LeDoux J (1998). Human amygdala activation during conditioned fear acquisition and extinction: a mixed-trial fMRI study. Neuron 20: 937–945.
LaBar KS, LeDoux JE, Spencer DD, Phelps EA (1995). Impaired fear conditioning following unilateral temporal lobectomy in humans. J Neurosci 15: 6846–6855.
LaBar KS, Phelps EA (2005). Reinstatement of conditioned fear in humans is context dependent and impaired in amnesia. Behav Neurosci 119: 677–686.
Landers MS, Sullivan RM (2012). The development and neurobiology of infant attachment and fear. Dev Neurosci 34: 101–114.
Lau JY, Britton JC, Nelson EE, Angold A, Ernst M, Goldwin M et al (2011). Distinct neural signatures of threat learning in adolescents and adults. Proc Natl Acad Sci USA 108: 4500–4505.
Le Magueresse C, Monyer H (2013). GABAergic interneurons shape the functional maturation of the cortex. Neuron 77: 388–405.
Lenroot RK, Giedd JN (2006). Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neurosci Biobehav Rev 30: 718–729.
Likhtik E, Popa D, Apergis-Schoute J, Fidacaro GA, Paré D (2008). Amygdala intercalated neurons are required for expression of fear extinction. Nature 454: 642–645.
Lissek S, Powers AS, McClure EB, Phelps EA, Woldehawariat G, Grillon C et al (2005). Classical fear conditioning in the anxiety disorders: a meta-analysis. Behav Res Ther 43: 1391–1424.
Lupien SJ, McEwen BS, Gunnar MR, Heim C (2009). Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nat Rev Neurosci 10: 434–445.
Maren S, Fanselow MS (1995). Synaptic plasticity in the basolateral amygdala induced by hippocampal formation stimulation in vivo. J Neurosci 15: 7548–7564.
Maren S, Phan KL, Liberzon I (2013). The contextual brain: implications for fear conditioning, extinction and psychopathology. Nat Rev Neurosci 14: 417–428.
Marschner A, Kalisch R, Vervliet B, Vansteenwegen D, Buchel C (2008). Dissociable roles for the hippocampus and the amygdala in human cued versus context fear conditioning. J Neurosci 28: 9030–9036.
Mauney SA, Athanas KM, Pantazopoulos H, Shaskan N, Passeri E, Berretta S et al (2013). Developmental pattern of perineuronal nets in the human prefrontal cortex and their deficit in schizophrenia. Biol Psychiatry 74: 427–435.
McCallum J, Kim JH, Richardson R (2010). Impaired extinction retention in adolescent rats: effects of D-cycloserine. Neuropsychopharmacology 35: 2134–2142.
McDonald AJ (1991). Organization of amygdaloid projections to the prefrontal cortex and associated striatum in the rat. Neuroscience 44: 1–14.
McDonald AJ, Mascagni F, Guo L (1996). Projections of the medial and lateral prefrontal cortices to the amygdala: a Phaseolus vulgaris leucoagglutinin study in the rat. Neuroscience 71: 55–75.
McGee AW, Yang Y, Fischer QS, Daw NW, Strittmatter SM (2005). Experience-driven plasticity of visual cortex limited by myelin and Nogo receptor. Science 309: 2222–2226.
Milad M, Quinn B, Pitman R, Orr S, Fischl B (2005). Thickness of ventromedial prefrontal cortex in humans is correlated with extinction memory. Proc Natl Acad Sci USA 102: 10706–10711.
Milad M, Quirk G, Pitman R, Orr S, Fischl B (2007a). A role for the human dorsal anterior cingulate cortex in fear expression. Biol Psychiatry 62: 1191–1194.
Milad MR, Orr SP, Lasko NB, Chang Y, Rauch SL, Pitman RK (2008). Presence and acquired origin of reduced recall for fear extinction in PTSD: results of a twin study. J Psychiatr Res 42: 515–520.
Milad MR, Pitman RK, Ellis CB, Gold AL, Shin LM, Lasko NB et al (2009). Neurobiological basis of failure to recall extinction memory in posttraumatic stress disorder. Biol Psychiatry 66: 1075–1082.
Milad MR, Quirk GJ (2002). Neurons in medial prefrontal cortex signal memory for fear extinction. Nature 420: 70–74.
Milad MR, Quirk GJ (2012). Fear extinction as a model for translational neuroscience: ten years of progress. Annu Rev Psychol 63: 129–151.
Milad MR, Wright CI, Orr SP, Pitman RK, Quirk GJ, Rauch SL (2007b). Recall of fear extinction in humans activates the ventromedial prefrontal cortex and hippocampus in concert. Biol Psychiatry 62: 446–454.
Monfils M-H, Cowansage KK, Klann E, Ledoux JE (2009). Extinction-reconsolidation boundaries: key to persistent attenuation of fear memories. Science 324: 951–955.
Morgan MA, LeDoux JE (1995). Differential contribution of dorsal and ventral medial prefrontal cortex to the acquisition and extinction of conditioned fear in rats. Behav Neurosci 109: 681–688.
Morgan MA, Romanski LM, LeDoux JE (1993). Extinction of emotional learning: contribution of medial prefrontal cortex. Neurosci Lett 163: 109–113.
Moriceau S, Sullivan RM (2006). Maternal presence serves as a switch between learning fear and attraction in infancy. Nat Neurosci 9: 1004–1006.
Morishita H, Miwa JM, Heintz N, Hensch TK (2010). Lynx1, a cholinergic brake, limits plasticity in adult visual cortex. Science 330: 1238–1240.
Nabel EM, Morishita H (2013). Regulating critical period plasticity: insight from the visual system to fear circuitry for therapeutic interventions. Front Psychiatry 4: 146.
Pattwell SS, Bath KG, Casey BJ, Ninan I, Lee FS (2011). From the Cover: Selective early-acquired fear memories undergo temporary suppression during adolescence. Proc Natl Acad Sci USA 108: 1182–1187.
Pattwell SS, Duhoux S, Hartley CA, Johnson DC, Jing D, Elliott MD et al (2012). Altered fear learning across development in both mouse and human. Proc Natl Acad Sci USA 109: 16318–16323.
Phelps E, Delgado M, Nearing K, LeDoux J (2004). Extinction learning in humans: role of the amygdala and vmPFC. Neuron 43: 897–905.
Phelps E, LeDoux J (2005). Contributions of the amygdala to emotion processing: from animal models to human behavior. Neuron 48: 175–187.
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.
Price JL (2003). Comparative aspects of amygdala connectivity. Ann NY Acad Sci 985: 50–58.
Quirk G, Russo G, Barron J, Lebron K (2000). The role of ventromedial prefrontal cortex in the recovery of extinguished fear. J Neurosci 20: 6225–6231.
Quirk GJ, Armony JL, LeDoux JE (1997). Fear conditioning enhances different temporal components of tone-evoked spike trains in auditory cortex and lateral amygdala. Neuron 19: 613–624.
Quirk GJ, Mueller D (2007). Neural mechanisms of extinction learning and retrieval. Neuropsychopharmacology 33: 56–72.
Quirk GJ, Repa C, LeDoux JE (1995). Fear conditioning enhances short-latency auditory responses of lateral amygdala neurons: parallel recordings in the freely behaving rat. Neuron 15: 1029–1039.
Raineki C, Holman PJ, Debiec J, Bugg M, Beasley A, Sullivan RM (2010). Functional emergence of the hippocampus in context fear learning in infant rats. Hippocampus 20: 1037–1046.
Raznahan A, Shaw PW, Lerch JP, Clasen LS, Greenstein D, Berman R et al (2014). Longitudinal four-dimensional mapping of subcortical anatomy in human development. Pro Natl Acad Sci USA 111: 1592–1597.
Repa JC, Muller J, Apergis J, Desrochers TM, Zhou Y, LeDoux JE (2001). Two different lateral amygdala cell populations contribute to the initiation and storage of memory. Nat Neurosci 4: 724–731.
Rudy JW (1993). Contextual conditioning and auditory cue conditioning dissociate during development. Behav Neurosci 107: 887–891.
Sakata K, Woo NH, Martinowich K, Greene JS, Schloesser RJ, Shen L et al (2009). Critical role of promoter IV-driven BDNF transcription in GABAergic transmission and synaptic plasticity in the prefrontal cortex. Pro Natl Acad Sci USA 106: 5942–5947.
Schiller D, Monfils M-H, Raio CM, Johnson DC, Ledoux JE, Phelps EA (2009). Preventing the return of fear in humans using reconsolidation update mechanisms. Nature 463: 49–53.
Shechner T, Hong M, Britton JC, Pine DS, Fox NA (2014). Fear conditioning and extinction across development: Evidence from human studies and animal models. Biol Psychol 100C: 1–12.
Sierra-Mercado D, Padilla-Coreano N, Quirk GJ (2011). Dissociable roles of prelimbic and infralimbic cortices, ventral hippocampus, and basolateral amygdala in the expression and extinction of conditioned fear. Neuropsychopharmacology 36: 529–538.
Somerville LH, Casey B (2010). Developmental neurobiology of cognitive control and motivational systems. Curr Opin Neurobiol 20: 236–241.
Sotres-Bayon F, Bush DEA, Ledoux JE (2007). Acquisition of fear extinction requires activation of NR2B-containing nmda receptors in the lateral amygdala. Neuropsychopharmacology 32: 1929–1940.
Sotres-Bayon F, Quirk GJ (2010). Prefrontal control of fear: more than just extinction. Curr Opin Neurobiol 20: 231–235.
Sotres-Bayon F, Sierra-Mercado D, Pardilla-Delgado E, Quirk GJ (2012). Gating of fear in prelimbic cortex by hippocampal and amygdala inputs. Neuron 76: 804–812.
Spear LP (2000). The adolescent brain and age-related behavioral manifestations. Neurosci Biobehav Rev 24: 417–463.
Sugiyama S, Di Nardo AA, Aizawa S, Matsuo I, Volovitch M, Prochiantz A et al (2008). Experience-dependent transfer of Otx2 homeoprotein into the visual cortex activates postnatal plasticity. Cell 134: 508–520.
Sullivan RM, Landers M, Yeaman B, Wilson DA (2000). Neurophysiology: Good memories of bad events in infancy. Nature 407: 38–39.
Thompson JV, Sullivan RM, Wilson DA (2008). Developmental emergence of fear learning corresponds with changes in amygdala synaptic plasticity. Brain Res 1200: 58–65.
Tottenham N (2013). The importance of early experiences for neuro-affective development. Curr Top Behav Neurosci 16: 109–129.
Vetencourt JFM, Sale A, Viegi A, Baroncelli L, De Pasquale R, O'Leary OF et al (2008). The antidepressant fluoxetine restores plasticity in the adult visual cortex. Science 320: 385–388.
Wagner FA, Anthony JC (2002). From first drug use to drug dependence: developmental periods of risk for dependence upon marijuana, cocaine, and alcohol. Neuropsychopharmacology 26: 479–488.
Wilson A, Brooks DC, Bouton ME (1995). The role of the rat hippocampal system in several effects of context in extinction. Behav Neurosci 109: 828–836.
Wu X, Fu Y, Knott G, Lu J, Di Cristo G, Huang ZJ (2012). GABA signaling promotes synapse elimination and axon pruning in developing cortical inhibitory interneurons. J Neurosci 32: 331–343.
Yakovlev PI, Lecours A-R (1967). The myelogenetic cycles of regional maturation of the brain. Regional development of the brain in early life. Minkowski A (ed.), Blackwell: Oxford, UK, pp 3–70.
Yap CS, Richardson R (2007). Extinction in the developing rat: an examination of renewal effects. Dev Psychobiol 49: 565–575.
Zeidan MA, Igoe SA, Linnman C, Vitalo A, Levine JB, Klibanski A et al (2011). Estradiol modulates medial prefrontal cortex and amygdala activity during fear extinction in women and female rats. Biol Psychiatry 70: 1–8.
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Hartley, C., Lee, F. Sensitive Periods in Affective Development: Nonlinear Maturation of Fear Learning. Neuropsychopharmacol 40, 50–60 (2015). https://doi.org/10.1038/npp.2014.179