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Neuron. Author manuscript; available in PMC 2011 September 9.
Published in final edited form as:
PMCID: PMC2940830

The clinical-basic interface in defining pathogenesis in disorders of neurodevelopmental origin


Human cognitive and social-emotional behaviors are heterogeneous, underscoring the challenges in modeling pathogenesis in disorders of neurodevelopmental origin in which these domains are dysfunctional. In general, animal models for these disorders are built to emulate our understanding of the clinical diagnosis, with mixed results. We suggest the utility of model systems lies in the use of different strategies to perturb hierarchical circuit development, to examine the behavioral dimensions that are most impacted, and to discern the capacity for, and heterogeneity of, neuroadaptation that will then inform treatment strategies.


The traditional role of basic scientific discoveries in understanding childhood and adult-onset disorders of neurodevelopmental origin is generating testable hypotheses regarding the etiology (genetic, environmental, and interactions between the two) and determining how underlying neurobiological mechanisms generate a particular disorder. The ultimate goal of interfacing basic and clinical research findings, therefore, is to generate new strategies for treatment options (e.g. behavioral, pharmaceutical, combination of both), which is currently underrepresented. Although the cognitive and psychiatric disorders under discussion are uniquely human (and we note that not all psychiatric disorders have been shown to have a neurodevelopmental basis), clinical research of what we will refer to collectively as neurodevelopmental disorders is limited in its capacity for determining etiology, and in understanding the biological consequences of the disorder on the brain (limited mostly to descriptive genetics, imaging and post-mortem studies). There are recent, high quality reviews on the topic of animal models of specific, developmentally based cognitive and psychiatric disorders (Ehninger et al., 2008; Fisch, 2007; Flint and Shifman, 2008; Insel, 2007; Kellendonk et al., 2009), and many more peer-review studies. The sheer number and rapidity of appearance of new findings in models is staggering. Here, we have elected not to provide a traditional review. Rather, we inventory fundamental strengths and weaknesses of specific strategies, and emphasize the gains to be made in understanding disorder pathogenesis by addressing the developmental nature of early and adult-onset dysfunction. Experimental strategies targeting the clinical-basic interface provide opportunities to probe deeper into the hierarchical and integrative nature of circuit development, the impact that developmental disturbances have on these processes, and the adaptive capacity to manage the influences of gene and environmental insults.

How do we make the fundamental connections through animal research? First, it is worthwhile noting that while continuing to be long on clinical descriptions, recently, a more fundamental understanding of neurodevelopmental disorders has occurred in part through the rapid introduction of genetic models that parallel discoveries in human genetics of specific syndromic mutations and copy number or idiopathic genetic variations (Chen et al., 2001; Nakatani et al., 2009). Yet, the strategies have been mechanistically limited, and there is instead a dearth of studies focusing on developmental time periods. These time periods represent either disorder onset or, for certain adult psychiatric disorders, such as schizophrenia, an altered developmental trajectory (Lewis and Levitt, 2002; Paus et al., 2008) and the accompanying acute and long-term allostatic load (McEwen and Wingfield, 2003) that leads to psychopathology (Thompson and Levitt, 2010). This concept of importance of development extends beyond the classic diathesis-stress model of mental illness focusing on adult life events that interact with heritable risk (Holmes and Rahe, 1967; Lieberman et al., 2001). Yet, even without mechanistic data, we recognize the existence of developmental phenomena that establish early vulnerabilities. For example, population studies in humans illustrate the influence of early toxic stress (in the form of abuse, neglect, exposure to toxins and drugs of abuse, maternal depression) in creating a lifetime of increased risk for developing both psychiatric and systemic (e.g. cancer, cardiovascular) disorders (Edwards et al., 2003; Felitti et al., 1998), and genetic mediators of risk titration (Caspi et al., 2002; Caspi et al., 2003). In animals, genetic models have illustrated a similar biological phenomena, in which early disruption of particular genes, such as 5HT1aR (Gross et al., 2002), DISC1 (Hikida et al., 2007; Niwa et al., 2010) and TGF-α (Koshibu and Levitt, 2008), results in late adolescence or adult-onset dysfunction. From this perspective therefore, we emphasize that whether models systems are designed to study the early onset of dysfunction, the culmination of developmental perturbation post-adolescence, or adult contributions to pathophysiology, clinical advances will come from defining mechanisms that tie timing of disruption to poor circuit adaptation, the impact of allostatic load on neurodevelopmental processes, and basic or complex functional problems.

Even for defined syndromic neurodevelopmental disorders, with known biomarkers, introducing a causal mutation and the resulting pathophysiology within neurobiological substrates can be highly varied (see below). Perhaps this should not be surprising, given the clinical heterogeneity of disorders defined by single gene mutations. However, one view of the strength of model systems is the ability to provide phenotypic consistency and reproducibility while deciphering biological mechanisms. Yet there remain practical pressures of defining more biomarkers, particularly for disorders in which such features currently are lacking (psychosis, autism), and testing their validity as disorder-causing in model systems. How, then, can advances in pathogenesis be made via the basic-clinical interface? We suggest that addressing how risk factors, both genetic and environmental, modify the fundamental, evolutionary conserved process of hierarchical circuit and skill development is ripe for discovery. This also has the possibility of leading to the identification of sub-clinical, intermediate endophenotypes which, when translated into clinical populations, may be useful in assessing developmental trajectory and intervention outcomes, either as treatments that redirect development or as preventive measures. For example, in early ASD interventions, targeted environmental enrichment is used to positively influence socially relevant sensory information processing that is critical for later developing social cognition (Vismara and Rogers, 2010).

Neurodevelopment Hierarchies as a Focus for Understanding Disorder Pathogenesis

Neurodevelopmental disorders are often systemic in nature – that is, peripheral organ disruptions, dysmorphologies and primary sensory and motor dysfunctions are common in both syndromic and idiopathic disorders (Carvill, 2001; Cooper-Brown et al., 2008; Geschwind, 2009). Despite this however, the cerebral cortex and associated forebrain circuits have been the foci of intensive developmental and clinical investigations. This focus is expected, given the complexity of the cognitive and social-emotional regulatory disturbances that characterize neurodevelopmental disorders, the utilization of pathophysiologic phenotypes in these functional domains as diagnostic features for each disorder, and the well-documented role of neocortical circuitry in higher order information processing. The developmental events in humans, monkeys and model vertebrates that define the assembly of a subset of dorsal pallial structures, including neo- and association cortices and hippocampus, are extraordinarily well-detailed across species (Rakic, 2009). We know when and where neurogenesis, cell migration, tract formation and neuronal specialization occur. We have a reasonable view of synaptogenesis, though not in nearly the same detail. Furthermore, we know that at some point in time during development, genes that comprise nearly the entire genome are expressed in the brain (Ramskold et al., 2009), and many of the gene products are functionally pleiotropic. This reflects a combinatorial molecular system that is far more complex than the linear strategies used for perturbation of one gene at a time in animal models. Candidate gene products that are involved in individual histogenic events are plentiful (literally in the thousands), and we know much about their expression patterns in rodents. Knowledge in gyrencephalic animals lags significantly, but new mapping and next generation sequencing methods will provide even more insight into the unique molecular properties of the primate brain. However, even with this additional knowledge, the gaps in mechanistic insight remain significant, and we suggest serve as the primary source of challenges in gaining pathogenic insight of neurodevelopmental disorders.

With a diversity of anatomical and molecular targets on which to focus, it makes sense to highlight the principle information processing unit, the cortical minicolumn (Mountcastle, 1997), which is both highly conserved in vertebrate evolution, and likely to be a primary or secondary target of disruption based on limited neuropathological studies in a variety of neurodevelopmental disorders (Casanova et al., 2003; Casanova et al., 2008; Courchesne and Pierce, 2005). The importance of deciphering these mechanisms is highlighted by the recent discovery that Eph-ephrin-A signaling mediates the dispersion of clonally related neurons destined for neocortical columns (Torii et al., 2009). This recent finding is consistent with specific EphA receptors as risk genes for psychosis (Purcell et al., 2009). It also is an example of a basic-clinical interface that could postulate that in schizophrenia, there is an early disruption of the organization of the key cortical information-processing unit. Expression patterns of EphAs during primate corticogenesis (Donoghue and Rakic, 1999) can help determine the temporal and spatial vulnerability of specific circuits that, if disrupted during development, can result in psychiatric disorders.

The example referenced above reflects a strategy of addressing core pathogenic mechanisms of neurodevelopmentally based disorders through investigation of the developmental assembly and integrity of both architectural and ultimately functional hierarchies. This approach acknowledges a fundamental property of the nervous system – that basic circuitry components that underlie the organisms ability to utilize sensory information from its environment to respond appropriately and maintain homeostatic balance are built first, followed by an integration of this basic information into complex circuit hierarchies that process demanding information (Hammock and Levitt, 2006). In fact, this view is supported more by functional studies rather than neurodevelopmental analyses of complex circuitry. Simply stated, we know little about the development of circuit hierarchies from neuroanatomical and molecular perspectives. Instead, data are much more robust regarding functional, fundamental sensory and motor development across vertebrates, and emotional and cognitive development in humans. The hierarchical nature of the emergence of primary sensory modalities, language and then top-down frontal cortical control (executive function) in humans is well reviewed (Fox et al., 2010). In the structural and molecular domains, however, there are few studies that have examined directly the development of key circuitry involved in higher order information processing. For example knowledge regarding the ontogeny of cortico-thalamic (Auladell et al., 2000; Torii and Levitt, 2005), and cortico-striatal connectivity (Sharpe and Tepper, 1998) (not simply axon penetration into targets) is minimal, despite existing techniques that could probe these connections. Yet the cortex provides the vast majority of the synapses to these sub-cortical structures (Jones, 2002). Using pseudorabies virus tracing to monitor the onset of synapse formation within the central circuitry that is involved in integrating autonomic and hypothalamo-pituitary-adrenal (HPA) functions, we showed that brainstem to peripheral structure connectivity, and hypothalamus to brainstem connectivity are assembled in the rodent by birth (Rinaman et al., 2000). While the descending axonal input to brainstem targets from the amygdala and frontal cortex are present during the first few days after birth, the onset of synaptogenesis is delayed by almost one week (Rinaman et al., 2000). This coincides with the period of time when maternal influences on pup physiology and behavior are most profound (Moriceau et al., 2006; Shionoya et al., 2007). In fact, introduction of stressors can change the timing of onset of synapse formation in the higher order, later developing circuits, while having no impact on the basic hypothalamo-brainstem connections (Banihashemi and Rinaman, 2010; Card et al., 2005). Molecular physiology methods can be adapted for examining developmental trajectory of circuitry. For example, lentivirustransduced channelrhodopsin could be used to selectively activate anatomically defined circuits. This would allow monitoring of postsynaptic responsiveness, and perhaps even adaptations following particular interventions in animal models (Cruikshank et al., 2010). The improved resolution of methods used for live imaging provides opportunities to examine circuit function and plasticity over developmental epochs (Cruz-Martin et al., 2010; Trachtenberg et al., 2002). These approaches provide opportunities to reveal the importance of timing in terms of disrupting the hierarchical nature of circuit development, and the analysis of the basic elements that comprise more complex behavioral dimensions such as social cognition and executive function (Hammock and Levitt, 2006). Early alterations to the circuitry underlying a specific functional modality can lead to more widespread disruptions (e.g. autonomic nervous system disruption and systemic dysautonomia (Axelrod et al., 2002), whereas later perturbations may lead to more specific disruptions within a particular skill set, but may not necessarily have a broad impact (e.g. postnatal toxic stressors and emotional dysregulation (Caspi et al., 2003; Plotsky and Meaney, 1993)). Thus, the same insult, but presented at different times during development, is likely to lead to very different outcomes (Figure 1) based on the relative degree of maturation of neural circuits (i.e. the breadth of connections) and the particular role played by a molecular component present during development compared to the adult. In fact, in animal studies examining structure-function effects of prenatal cocaine exposure, timing of exposure was one of several key variables in explaining variance across models (Stanwood and Levitt, 2008). Similarly, deletion of 5HT1aR only during development results in very distinct adult-onset emotion regulation outcomes compared to deletion of the gene encoding the receptor in the adult mouse (Gross et al., 2002). How this temporally circumscribed manipulation results in long-term changes remains unknown. One hypothesis is that this receptor modulates the assembly of relevant circuits during development, and then switches its role as a traditional biogenic aminergic neurotransmitter in the adult. Therefore, disrupting this receptor during development could directly alter neural circuitry. There is precedence for 5-HT serving this novel developmental role (Bonnin et al., 2007), but relevant studies examining the ontogeny of amygdala and related circuits in the 5HT1aR conditional null mouse should assess this directly.

Figure 1
Animal model examination of neural circuit and functional hierarchies related to disorder pathogenesis

Developmental perturbation and neural (mal)adaptation as a disorder target

Adaptive capacities are well-described in stable, adult states that define homeostatic balance. Homeostasis is not a new concept, defining how external stimuli act upon neural systems in a dynamic way. Whereas a potent single event has the potential to disrupt the development of hierarchical skills, weak repeated stimuli also can lead to permanent changes to the system. Neural circuits are fine-tuned by experience to be resilient to a wide range of external stimuli. These circuits demonstrate adaptive capacity through homeostatic regulation (Knudsen et al., 2006). This classic concept includes physiological understanding of neuroadaptation. Moreover, the mechanisms underlying adaptive responses are significantly advanced and complex. Homeostatic adaptation is responsible for driving multiple cellular (e.g. pH and ATP stability) and whole animal behaviors (e.g. food foraging). Behavioral homeostasis regulates both survival and non-essential behaviors, and is the basis for adaptive processes as wide-ranging as color vision (Hurvich and Jameson, 1957), hedonism (Solomon and Corbit, 1974), and drug addiction (Koob and Le Moal, 2001). Repeated challenges to a system in homeostatic balance can result in system break-down. This chronic challenge to homeostasis results in allostatic states, culminating in allostatic load that leads to permanent changes in homeostasis (McEwen, 2000; McEwen and Wingfield, 2003). In fact, new allostasis may exist outside the typical boundaries for homeostasis (allostatic overload) (Figure 2).

Figure 2
Adult-onset and developmentally expressed disorders involve distinct adaptive responses to genetic and environmental challenges

The developmental impact of allostatic load, however, is under-investigated, and may be quite different from what is reported in the adult (Lupien et al., 2009; McEwen, 2001). Chronic high levels of glucocorticoids in the adult rodent or non-human primate can permanently damage prefrontal cortical and hippocampal neurons (Radley et al., 2004; Sapolsky et al., 1985; Uno et al., 1989). During development, this same challenge may also alter the fundamental wiring of circuits that mediate the stress response (Plotsky and Meaney, 1993; Wei et al., 2007). Thus, in the context of adult-onset disorders that originate in development, allostatic overload may result in an altered developmental trajectory (Thompson and Levitt, 2010). This changed trajectory alone, or in combination with other environmental challenges, could possibly lead to a diseased/disordered system, for example schizophrenia. As such, behavioral and etiological heterogeneity within each disorder is easier to understand, as disorder onset would require multiple events (environmental, genetic, interactions) to occur, and does not necessitate identical causality, nor the identical trajectory of biological development even within a single clinical population. Mechanistically, this has emerged through the long-held concept of ‘early life programming’, with the growth of epigenetic studies examining the permanent and transient nature of genomic modifications (Bale et al., 2010; Weaver et al., 2004). The concept of early allostatic overload is not without precedence. For example, allostatic overload is likely to occur in premature onset of adult hypertension, where reduction in the number of kidney glomeruli, established prenatally, is accompanied by a maladaptive pathological increase in glomerular size, correlating with disease vulnerability (Keller et al., 2003). Rather than focusing on end state, examining developmental changes following genetic and/or environmental perturbations in animal models will provide fundamental information regarding the maladaptive nature of the fundamental molecular and structural architecture in the brain that underlies a particular disorder pathophysiology, especially for childhood-onset disorders. This also provides opportunities to examine normal system interactions as skills are built, thus introducing more naturalistic, integrated strategies.

The Heterogeneity of Neurodevelopmental Disorders

The collection of symptoms, subjectively reported and observed (positive and negative symptoms in the case of schizophrenia, or the triad of symptoms for ASD) defines a single disorder category, in accordance with the existing diagnostic manuals. The well-documented clinical heterogeneity that characterizes even single gene, syndromic disorders such as Rett (Chahrour and Zoghbi, 2007; Dragich et al., 2000) or Fragile X (Loesch et al., 2004), is presumably due to underlying neurobiological heterogeneity of overlapping, but not identical pathophysiology. This is an important consideration not only for the design of future diagnostic tools, but also for current and future strategies of modeling the biological bases of neurodevelopmental disorders. The concept of using a more discrete approach in studying psychiatric disorders is gaining momentum for both the neuroscience and clinical psychology research fields (Bale et al., 2010; Insel, 2007; Insel, 2009). Though there are debates regarding the advantages of studying discrete or dimensional behavioral states (Mendl et al., 2010), here we emphasize that methods should be developed focusing on the development of structure-function relations between component parts comprising cognitive and social-emotional skills, specifically, those that are often disrupted in neurodevelopmental disorders. Ultimately, this will be more productive than debating the validity of whether a model truly replicates a clinical state. A complexity to this, of course, is that individual disrupted dimensions are often shared across multiple disorders. For example, prepulse inhibition, a type of sensorimotor gating, is deficient in both autism and schizophrenia (Braff et al., 1978; Grillon et al., 1992; Perry et al., 2007). Additionally, generalized anxiety disorder appears in a number of neurodevelopmental disorders of distinct genetic etiology including Williams Syndrome, ASD, and schizophrenia (Davis et al., 2008; Dykens, 2003; Tibbo et al., 2003). Although mostly studied in the adult genetically manipulated animal models for each disorder, the developmental trajectory of sensorimotor gating or emotional regulation may provide more insight regarding hierarchical events that may be differentially disrupted in disorders. For example, these hierarchical events may be acutely disrupted in autism, yet more chronically, though perhaps initially more subtly, disrupted in schizophrenia.

Adding to the complexity of disorder heterogeneity based on clinical observation, is clear evidence for multiple genetic mechanisms (Geschwind, 2009) contributing to idiopathic disorders such as ASD (see review by State, this volume) and schizophrenia (Owen et al., 2010). Both very small or modest contributors to disorders, like common polymorphisms (Campbell et al., 2006) (Anney et al., 2010; Stefansson et al., 2009; Wang et al., 2009), and potentially major contributors, such as rare coding mutations and copy number variations (Christian et al., 2008; Glessner et al., 2009; Merikangas et al., 2009; Sebat et al., 2007; Weiss et al., 2008) are themselves heterogeneous in disorder impact. Common risk alleles are, by themselves, only moderators of physiological states. Moreover, there are now several descriptions in which well-defined mutations present in neurotypical individuals within a family that also include an affected person with the mutation (Sebat et al., 2007). Emerging from these genetic studies is a perspective emphasizing the importance of defining the molecular and neurobiological pathways that are disrupted (Akil et al., 2010; Bill and Geschwind, 2009; El-Fishawy and State, 2010; Levitt and Campbell, 2009). This parallels an initial conceptualization, put forth in previous gene microarray studies (Mirnics et al., 2000; Mirnics et al., 2001), of targeting defined molecular networks that are specific to a particular disorder, though achievable through different genetic and environmental mechanisms across subjects, that therefore introduces clinical heterogeneity.

The Clinical-Basic Interface in Designing Animal Models

How does the field cope with, and characterize the phenotypic and etiological heterogeneity that are recognized as underlying neurodevelopmental disorders? Additional challenges include the complexity of relating models to diagnostic criteria (e.g. in DSM, ICD or other instruments) that may include clinical symptoms only, or in addition, etiological information, such as neuropathological markers. Animal models, however, are controllable, and thus, provide unique experimental substrates for investigating neurobiological mechanisms and consequences of neurodevelopmental disorders beyond what is possible in clinical populations. Furthermore, animal models need not mimic the human disorder, not just because it cannot, but because it need not to be useful. For example, Rett Syndrome afflicts girls almost exclusively. Yet introduction of a mutation in the gene encoding MeCP2, the gene that causes the disorder, into mice generates severe functional phenotypes in male mice (Chen et al., 2001; Guy et al., 2001; Shahbazian et al., 2002). A search for the presumed genetic modifiers or unique aspects of mosaicism in humans and mice will be useful. The animal model itself, which does not mimic a fundamental aspect of the clinical disorder (sex bias), nonetheless has allowed for a greater understanding of MeCP2 in neurodevelopmental processes and in designing and implementing pre-clinical pharmacological treatments for reversing the resultant phenotypes (Guy et al., 2007; Tropea et al., 2009). Another example is that of a rare mutation in neuroligin 3. The coding variant, introduced in one mouse line, produced interesting cognitive phenotypes (Tabuchi et al., 2007) that were not replicated when the identical mutation was used by another laboratory to create an independent mouse line using a congenic rather than hybrid mouse strain (Chadman et al., 2008). It may be that these genetic models are more useful for dissecting the presence or absence of adaptive capacities of specific developing synapses, or identifying genetic background modifiers or environmental factors (that may differ between laboratories) as phenotype modifiers, rather than promoting them as clinical models, per se.

Modeling a biological process that is disrupted in the disorder, rather than producing ‘the’ clinical model is achievable. Nine factors, not exhaustive in nature, are presented here as considerations for the design and utilization of experimental animal models of neurodevelopmental disorders (Figure 3). This is presented in the spirit of moving away from the need to design models that mimic the diagnostic criteria of an early- or late-onset disorder, to instead, approaches that may provide more relevant experimental data, and thus, inform better intervention designs. Moreover, this allows for individual behaviors to be studied, which when disrupted, are often shared across multiple neurodevelopmental disorders. Understanding the developmental disruptions that lead to aberrant behavior provides insight into common circuit problems and possible treatment strategies that can be shared across these disorders. The nine considerations: 1) ethologically appropriate behavior. Insight can be gained either from probing functions that are conserved across species boundaries (e.g. sensorimotor gating (Powell et al., 2009)) or common functions that are expressed in distinct, species-relevant ways. Regarding the latter, for example, unique aspects of maternal care, use of particular sensory modalities, or unique predator-prey relationships are features that can be used to an advantage in designing models. The stressors introduced by intermittent removal of offspring from the dam reflect careful design of an environmental factor that takes advantage of species-unique characteristics (Mendoza et al., 1978; Plotsky and Meaney, 1993; Suchecki et al., 1993). These studies in turn have led to common themes of epigenetic modulation of the impact of early stress on brain development and function in animal models (Weaver et al., 2004) and humans (McGowan et al., 2009); 2) the presence of species-specific genetic modifiers. The emergence of more detailed information regarding genetic modulatory factors will lead to better model design to probe similarities and differences between a clinical dimension of a disorder and phenotypes in models using the same mutations. For example, the rare coding mutation in the human serotonin transporter (SERT) associated with ASD and co-morbid with obsessive-compulsive behavior is an intrinsic variant to the C57BL6J mouse (Carneiro et al., 2009), which may impact specific behavioral traits of the wild type mouse. However, while this strain is used in the majority of gene targeting studies, and the presence of the SERT variant could impact phenotypes, the wild type strain is not used as a model of either ASD or OCD; 3) species-specific timing of histogenic events. Cortical synaptogenesis, for example, begins in earnest during the third trimester in primate species, but postnatally in rodents (Thompson et al., 2009). This detail impacts the design of environmental manipulations for perturbing this developmental process; 4) species dependent regulation and patterning of gene expression. Information on transcriptional regulation of risk genes, detailed spatio-temporal developmental expression patterns, and their genetic modifiers provides a foundation for relating genetic manipulations in animal models to human. However, the limited data to date poses problems for designing appropriate studies. Constitutive or conditional introduction of gene mutations, disorder-specific rare variants, manipulation of expression via RNAi or shRNA transfer, or viral expression vectors all promote the examination of genetic mechanisms that may underlie a pathophysiological state. Each technique has strengths and weaknesses, and none, even those that introduce a clinically-defined mutation, need to phenocopy the disorder to make valuable contributions to understanding neurodevelopmental pathogenic processes; 5) species-specific representation of circuits and their individual components. The debate regarding the presence or absence of prefrontal cortex in rodents notwithstanding, consideration of structure-function relations from a developmental perspective enhances animal model studies. Recent history however reflects oversight of this consideration, for genes are introduced, behaviors measured, and drugs given to reverse one or two elements of a phenotype. Studies of neurodevelopmental disorders incorporating relationships between neuroanatomical substrates may provide more comprehensive intervention strategies, specifically targeting these circuits and substrates using pharmacological and experience-based approaches; 6) species-relevant environmental impact. Similar to selecting ethologically appropriate behavioral tasks putative environmental factors that impact developing systems should also be considered; 7) species-unique metabolic and homeostatic systems. Allostatic load and developmental homeostatic challenges are impacted by species-unique mechanisms responsible for controlling metabolic and physiologic states. This also can be used to an advantage in designing animal model studies; 8) species-unique neural and non-neural system interactions. Animal models could be designed to explore these relationships, which may be useful for understanding pathogenesis and treatment approaches. For example, there is substantial co-occurrence of seizures in multiple neurodevelopmental disorders (Gaitatzis et al., 2004; Matsuo et al.), though this particular pathophysiology may not be represented or focused upon in model systems designed to mirror the clinical disorder. Additionally, gastrointestinal disorders are prevalent among individuals with ASD (Buie et al., 2010; Campbell et al., 2009), but are not currently examined in animal models of ASD; 9) species-specific onset and regulation of puberty. This is specifically relevant for addressing sensitive and critical periods of development that transition through puberty, which, when perturbed can lead to adult-onset psychiatric disorders. Mechanistically, experimental approaches in animal models will assist in clarifying potential factors that influence post-pubertal pathophysiology emergence.

Figure 3
A short list of considerations informing the design of relevant animal models to study the etiology and pathophysiology of neurodevelopmental disorders

A Concluding Perspective on Animal Models and Neurodevelopmental Disorders

The concept of probing early disruptions in development is gaining momentum (Koshibu and Levitt, 2008; Moriceau et al., 2006; Niwa et al.; Shionoya et al., 2007). Partly responsible for the limited number of studies to date is the lack of sufficiently sophisticated behavioral and neuroanatomical probes relevant for a young or developing animal. The field of animal models is not alone in this challenge, as developmental psychologists also must establish age-appropriate experimental designs that probe typical development, as well as clinical disorders. Not surprisingly, similar to the development of complex circuits, the emergence of complex behaviors also takes time. An early postnatal mouse pup will devote a significant amount of time and energy seeking warmth and food from mom, whereas a pre-weanling animal begins to explore and gain independence as they forage for themselves. Therefore, a two-bottle choice test might be an appropriate behavioral probe for sucrose preference and motivation in a post-weanling animal, but will not provide insight into the motivational systems of a young pup - despite intact reward circuitry. Defining and utilizing species and developmental stage-specific behaviors will facilitate the probing of functional consequences of early disruptions of developing circuits.

Emergence of disorder risk during development is a challenge that the field will have to address more as we become more adept at monitoring developmental trajectory. The relationship between the dynamic structural changes of the cerebral cortex in children and IQ measures, rather than end-state, or cross-sectional assays, illustrates the insight to be gained by monitoring intermediate states of development (Castellanos et al., 2002; Shaw et al., 2006; Sowell et al., 2001). In an animal model, experiments introducing a transient disruption of Disrupted in Schizophrenia-1 (DISC 1) early in development (Niwa et al., 2010) were able to dissociate early perturbations of neuronal architecture and molecular systems from post-pubertal onset of altered cognitive and emotional behavior performance. While the specific human translocation associated with schizophrenia was not reproduced in mice, the study highlights a genetic strategy for modeling intermediate phenotypes and a developmental emergence of dysfunctional behavioral dimensions relevant also in schizophrenia.

Striving to phenocopy neurodevelopmental disorders in animal models, or ignoring models that do not phenocopy disorders, diminishes the value of the resultant phenotypes that may still lead to biological insight relevant to the disorder. For example, the paternally-inherited chromosome 15q11-13 duplication (Nakatani et al., 2009) in mice leads to important molecular and behavioral changes that are similarly demonstrated in ASD, yet the duplication in humans that results in ASD diagnosis is maternally inherited. While not a genetic phenocopy, the mouse model is nonetheless an important step for introducing genetically engineered chromosomal loci and for assessing the developmental impact that this type of duplication has on emerging neural circuits. Additionally, maternally inherited deletion of Ube3a, the gene holding the causal mutation for Angelman Syndrome, generates a variety of interesting phenotypes, including altered visual plasticity (Sato and Stryker, 2010; Yashiro et al., 2009), learning and LTP deficits (Jiang et al., 1998; Weeber et al., 2003), and even loss of midbrain dopamine neurons (Mulherkar and Jana, 2010). In the mouse, however, the reported imprinting of human gene expression within a very limited number of structures does not occur (Gustin et al., 2010). This reflects a challenge in mechanistic interpretations, but these mice remain of considerable interest for understanding Ube3a function in the developing brain. Lack of expression of the FMR1 gene causes Fragile X Syndrome, a highly heritable form of mental retardation. Mice lacking this gene show significant disruptions in cortical morphology and behavioral performance similar to those demonstrated in Fragile X Syndrome, and the reversal of some of these phenotypes by downstream intervention strategies in adult mice (de Vrij et al., 2008; Dolen et al., 2007; Hayashi et al., 2007) has led to rapid development of clinical trials (, 2010a;, 2010b). Nonetheless, different mouse strains with the identical, well-known FMR1 mutation can create experimental havoc, producing opposite changes in the auditory acoustic startle phenotype from one generation to the next. Perhaps being problematic as a clinical phenocopy, the strain-specific differences have led to the discovery of a limited number of genetic loci that may serve as modifiers of the FMR1 mutation in mice (Errijgers et al., 2008). This discovery also can be examined in humans for potential relevance to clinical heterogeneity in Fragile X Syndrome.

Trying not to cast too broad a net, once identified as particular risk or disorder-causing factors, we would argue that models in which specific genetic or environmental manipulations are introduced will be clinically relevant. The specificity and sensitivity of a particular model relies on defining ethologically relevant strategies for probing specific molecular and neural elements that contribute to phenotype. For example, deciphering the impact of a particular allelic variant in ASD on basic associative learning skills integral to more complex social and emotional regulation may provide novel insight that will lead to understanding the trajectory that a developing system may endure as a result of the disorder. The resulting long-term challenges to the circuits and behavioral hierarchies, discovered through animal model studies, can ultimately become targets of therapeutic strategies that engage the system at its most readily responsive time for clinical treatment or even prevention.


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  • Akil H, Brenner S, Kandel E, Kendler KS, King MC, Scolnick E, Watson JD, Zoghbi HY. Science. 2010;327:1580–1581. [PMC free article] [PubMed]
  • Anney R, Klei L, Pinto D, Regan R, Conroy J, Magalhaes TR, Correia C, Abrahams BS, Sykes N, Pagnamenta AT, et al. Hum Mol Genet. 2010 [PMC free article] [PubMed]
  • Auladell C, Perez-Sust P, Super H, Soriano E. Anat Embryol (Berl) 2000;201:169–179. [PubMed]
  • Axelrod FB, Goldberg JD, Ye XY, Maayan C. J Pediatr. 2002;141:518–523. [PubMed]
  • Bale TL, Baram TZ, Brown AS, Goldstein JM, Insel TR, McCarthy MM, Nemeroff CB, Reyes TM, Simerly RB, Susser ES, Nestler EJ. Biol Psychiatry. 2010;68:314–319. [PMC free article] [PubMed]
  • Banihashemi L, Rinaman L. Neuroscience. 2010;165:265–277. [PMC free article] [PubMed]
  • Bill BR, Geschwind DH. Curr Opin Genet Dev. 2009;19:271–278. [PMC free article] [PubMed]
  • Bonnin A, Torii M, Wang L, Rakic P, Levitt P. Nat Neurosci. 2007;10:588–597. [PubMed]
  • Braff D, Stone C, Callaway E, Geyer M, Glick I, Bali L. Psychophysiology. 1978;15:339–343. [PubMed]
  • Buie T, Campbell DB, Fuchs GJ, 3rd, Furuta GT, Levy J, Vandewater J, Whitaker AH, Atkins D, Bauman ML, Beaudet AL, et al. Pediatrics. 2010;125(Suppl 1):S1–18. [PubMed]
  • Campbell DB, Buie TM, Winter H, Bauman M, Sutcliffe JS, Perrin JM, Levitt P. Pediatrics. 2009;123:1018–1024. [PubMed]
  • Campbell DB, Sutcliffe JS, Ebert PJ, Militerni R, Bravaccio C, Trillo S, Elia M, Schneider C, Melmed R, Sacco R, et al. Proc Natl Acad Sci U S A. 2006;103:16834–16839. [PubMed]
  • Card JP, Levitt P, Gluhovsky M, Rinaman L. J Neurosci. 2005;25:9102–9111. [PubMed]
  • Carneiro AM, Airey DC, Thompson B, Zhu CB, Lu L, Chesler EJ, Erikson KM, Blakely RD. Proc Natl Acad Sci U S A. 2009;106:2047–2052. [PubMed]
  • Carvill S. J Intellect Disabil Res. 2001;45:467–483. [PubMed]
  • Casanova MF, Buxhoeveden D, Gomez J. Neuroscientist. 2003;9:496–507. [PubMed]
  • Casanova MF, Kreczmanski P, Trippe J, 2nd, Switala A, Heinsen H, Steinbusch HW, Schmitz C. Psychiatry Res. 2008;158:267–277. [PubMed]
  • Caspi A, McClay J, Moffitt TE, Mill J, Martin J, Craig IW, Taylor A, Poulton R. Science. 2002;297:851–854. [PubMed]
  • Caspi A, Sugden K, Moffitt TE, Taylor A, Craig IW, Harrington H, McClay J, Mill J, Martin J, Braithwaite A, Poulton R. Science. 2003;301:386–389. [PubMed]
  • Castellanos FX, Lee PP, Sharp W, Jeffries NO, Greenstein DK, Clasen LS, Blumenthal JD, James RS, Ebens CL, Walter JM, et al. Jama. 2002;288:1740–1748. [PubMed]
  • Chadman KK, Gong S, Scattoni ML, Boltuck SE, Gandhy SU, Heintz N, Crawley JN. Autism Res. 2008;1:147–158. [PMC free article] [PubMed]
  • Chahrour M, Zoghbi HY. Neuron. 2007;56:422–437. [PubMed]
  • Chen RZ, Akbarian S, Tudor M, Jaenisch R. Nat Genet. 2001;27:327–331. [PubMed]
  • Christian SL, Brune CW, Sudi J, Kumar RA, Liu S, Karamohamed S, Badner JA, Matsui S, Conroy J, McQuaid D, et al. Biol Psychiatry. 2008;63:1111–1117. [PMC free article] [PubMed]
  • A Multi-centre, Randomized, Double-blind, Placebo Controlled, Two-period, Crossover Proof-of-concept Study in Male Patients With Fragile X Syndrome to Assess the Efficacy, Safety and Tolerability of Multiple Oral Doses of AFQ056. 2010a
  • A Randomized, Double-blind, Placebo-controlled, Pharmacokinetic, Safety and Tolerability, and Exploratory Efficacy and Pharmacodynamic Effects Study of RO4917523 in Adult Patients With Fragile X Syndrome. 2010b
  • Cooper-Brown L, Copeland S, Dailey S, Downey D, Petersen MC, Stimson C, Van Dyke DC. Dev Disabil Res Rev. 2008;14:147–157. [PubMed]
  • Courchesne E, Pierce K. Curr Opin Neurobiol. 2005;15:225–230. [PubMed]
  • Cruikshank SJ, Urabe H, Nurmikko AV, Connors BW. Neuron. 2010;65:230–245. [PMC free article] [PubMed]
  • Cruz-Martin A, Crespo M, Portera-Cailliau C. J Neurosci. 2010;30:7793–7803. [PMC free article] [PubMed]
  • Davis E, Saeed SA, Antonacci DJ. Psychiatr Q. 2008;79:249–263. [PubMed]
  • de Vrij FM, Levenga J, van der Linde HC, Koekkoek SK, De Zeeuw CI, Nelson DL, Oostra BA, Willemsen R. Neurobiol Dis. 2008;31:127–132. [PMC free article] [PubMed]
  • Dolen G, Osterweil E, Rao BS, Smith GB, Auerbach BD, Chattarji S, Bear MF. Neuron. 2007;56:955–962. [PMC free article] [PubMed]
  • Donoghue MJ, Rakic P. J Neurosci. 1999;19:5967–5979. [PubMed]
  • Dragich J, Houwink-Manville I, Schanen C. Hum Mol Genet. 2000;9:2365–2375. [PubMed]
  • Dykens EM. Dev Neuropsychol. 2003;23:291–316. [PubMed]
  • Edwards VJ, Holden GW, Felitti VJ, Anda RF. Am J Psychiatry. 2003;160:1453–1460. [PubMed]
  • Ehninger D, Li W, Fox K, Stryker MP, Silva AJ. Neuron. 2008;60:950–960. [PMC free article] [PubMed]
  • El-Fishawy P, State MW. Psychiatr Clin North Am. 2010;33:83–105. [PMC free article] [PubMed]
  • Errijgers V, Fransen E, D'Hooge R, De Deyn PP, Kooy RF. Genet Res. 2008;90:341–345. [PubMed]
  • Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, Koss MP, Marks JS. Am J Prev Med. 1998;14:245–258. [PubMed]
  • Fisch GS. Behav Genet. 2007;37:1–10. [PubMed]
  • Flint J, Shifman S. Curr Opin Genet Dev. 2008;18:235–240. [PubMed]
  • Fox SE, Levitt P, Nelson CA., 3rd Child Dev. 2010;81:28–40. [PMC free article] [PubMed]
  • Gaitatzis A, Trimble MR, Sander JW. Acta Neurol Scand. 2004;110:207–220. [PubMed]
  • Geschwind DH. Annu Rev Med. 2009;60:367–380. [PMC free article] [PubMed]
  • Glessner JT, Wang K, Cai G, Korvatska O, Kim CE, Wood S, Zhang H, Estes A, Brune CW, Bradfield JP, et al. Nature. 2009;459:569–573. [PMC free article] [PubMed]
  • Grillon C, Ameli R, Charney DS, Krystal J, Braff D. Biol Psychiatry. 1992;32:939–943. [PubMed]
  • Gross C, Zhuang X, Stark K, Ramboz S, Oosting R, Kirby L, Santarelli L, Beck S, Hen R. Nature. 2002;416:396–400. [PubMed]
  • Gustin RM, Bichell TJ, Bubser M, Daily J, Filonova I, Mrelashvili D, Deutch AY, Colbran RJ, Weeber EJ, Haas KF. Neurobiol Dis. 2010;39:283–291. [PMC free article] [PubMed]
  • Guy J, Gan J, Selfridge J, Cobb S, Bird A. Science. 2007;315:1143–1147. [PubMed]
  • Guy J, Hendrich B, Holmes M, Martin JE, Bird A. Nat Genet. 2001;27:322–326. [PubMed]
  • Hammock EAD, Levitt P. Human Development. 2006;49:294–309.
  • Hayashi ML, Rao BS, Seo JS, Choi HS, Dolan BM, Choi SY, Chattarji S, Tonegawa S. Proc Natl Acad Sci U S A. 2007;104:11489–11494. [PubMed]
  • Hikida T, Jaaro-Peled H, Seshadri S, Oishi K, Hookway C, Kong S, Wu D, Xue R, Andrade M, Tankou S, et al. Proc Natl Acad Sci U S A. 2007;104:14501–14506. [PubMed]
  • Holmes TH, Rahe RH. J Psychosom Res. 1967;11:213–218. [PubMed]
  • Hurvich LM, Jameson D. Psychol Rev. 1957;64(Part 1):384–404. [PubMed]
  • Insel TR. Biol Psychiatry. 2007;62:1337–1339. [PubMed]
  • Insel TR. J Clin Invest. 2009;119:700–705. [PMC free article] [PubMed]
  • Jiang YH, Armstrong D, Albrecht U, Atkins CM, Noebels JL, Eichele G, Sweatt JD, Beaudet AL. Neuron. 1998;21:799–811. [PubMed]
  • Jones EG. Philos Trans R Soc Lond B Biol Sci. 2002;357:1659–1673. [PMC free article] [PubMed]
  • Kellendonk C, Simpson EH, Kandel ER. Trends Neurosci. 2009;32:347–358. [PMC free article] [PubMed]
  • Keller G, Zimmer G, Mall G, Ritz E, Amann K. N Engl J Med. 2003;348:101–108. [PubMed]
  • Knudsen EI, Heckman JJ, Cameron JL, Shonkoff JP. Proc Natl Acad Sci U S A. 2006;103:10155–10162. [PubMed]
  • Koob GF, Le Moal M. Neuropsychopharmacology. 2001;24:97–129. [PubMed]
  • Koshibu K, Levitt P. Neuropsychopharmacology. 2008;33:557–565. [PubMed]
  • Levitt P, Campbell DB. J Clin Invest. 2009;119:747–754. [PMC free article] [PubMed]
  • Lewis DA, Levitt P. Annu Rev Neurosci. 2002;25:409–432. [PubMed]
  • Lieberman JA, Perkins D, Belger A, Chakos M, Jarskog F, Boteva K, Gilmore J. Biol Psychiatry. 2001;50:884–897. [PubMed]
  • Loesch DZ, Huggins RM, Hagerman RJ. Ment Retard Dev Disabil Res Rev. 2004;10:31–41. [PubMed]
  • Lupien SJ, McEwen BS, Gunnar MR, Heim C. Nat Rev Neurosci. 2009;10:434–445. [PubMed]
  • Matsuo M, Maeda T, Sasaki K, Ishii K, Hamasaki Y. Brain Dev. 2010 [PubMed]
  • McEwen BS. Neuropsychopharmacology. 2000;22:108–124. [PubMed]
  • McEwen BS. Ann N Y Acad Sci. 2001;935:42–49. [PubMed]
  • McEwen BS, Wingfield JC. Horm Behav. 2003;43:2–15. [PubMed]
  • McGowan PO, Sasaki A, D'Alessio AC, Dymov S, Labonte B, Szyf M, Turecki G, Meaney MJ. Nat Neurosci. 2009;12:342–348. [PMC free article] [PubMed]
  • Mendl M, Burman OH, Paul ES. Proc Biol Sci. 2010
  • Mendoza SP, Smotherman WP, Miner MT, Kaplan J, Levine S. Dev Psychobiol. 1978;11:169–175. [PubMed]
  • Merikangas AK, Corvin AP, Gallagher L. Trends Genet. 2009;25:536–544. [PubMed]
  • Mirnics K, Middleton FA, Marquez A, Lewis DA, Levitt P. Neuron. 2000;28:53–67. [PubMed]
  • Mirnics K, Middleton FA, Stanwood GD, Lewis DA, Levitt P. Mol Psychiatry. 2001;6:293–301. [PubMed]
  • Moriceau S, Wilson DA, Levine S, Sullivan RM. J Neurosci. 2006;26:6737–6748. [PMC free article] [PubMed]
  • Mountcastle VB. Brain. 1997;120(Pt 4):701–722. [PubMed]
  • Mulherkar SA, Jana NR. Neurobiol Dis. 2010 [PubMed]
  • Nakatani J, Tamada K, Hatanaka F, Ise S, Ohta H, Inoue K, Tomonaga S, Watanabe Y, Chung YJ, Banerjee R, et al. Cell. 2009;137:1235–1246. [PMC free article] [PubMed]
  • Niwa M, Kamiya A, Murai R, Kubo K, Gruber AJ, Tomita K, Lu L, Tomisato S, Jaaro-Peled H, Seshadri S, et al. Neuron. 2010;65:480–489. [PMC free article] [PubMed]
  • Owen MJ, Craddock N, O'Donovan MC. Arch Gen Psychiatry. 2010;67:667–673. [PubMed]
  • Paus T, Keshavan M, Giedd JN. Nat Rev Neurosci. 2008;9:947–957. [PMC free article] [PubMed]
  • Perry W, Minassian A, Lopez B, Maron L, Lincoln A. Biol Psychiatry. 2007;61:482–486. [PubMed]
  • Plotsky PM, Meaney MJ. Brain Res Mol Brain Res. 1993;18:195–200. [PubMed]
  • Powell SB, Zhou X, Geyer MA. Behav Brain Res. 2009;204:282–294. [PMC free article] [PubMed]
  • Purcell SM, Wray NR, Stone JL, Visscher PM, O'Donovan MC, Sullivan PF, Sklar P. Nature. 2009;460:748–752. [PMC free article] [PubMed]
  • Radley JJ, Sisti HM, Hao J, Rocher AB, McCall T, Hof PR, McEwen BS, Morrison JH. Neuroscience. 2004;125:1–6. [PubMed]
  • Rakic P. Nat Rev Neurosci. 2009;10:724–735. [PMC free article] [PubMed]
  • Ramskold D, Wang ET, Burge CB, Sandberg R. PLoS Comput Biol. 2009;5:e1000598. [PMC free article] [PubMed]
  • Rinaman L, Levitt P, Card JP. J Neurosci. 2000;20:2731–2741. [PubMed]
  • Sapolsky RM, Krey LC, McEwen BS. J Neurosci. 1985;5:1222–1227. [PubMed]
  • Sato M, Stryker MP. Proc Natl Acad Sci U S A. 2010;107:5611–5616. [PubMed]
  • Sebat J, Lakshmi B, Malhotra D, Troge J, Lese-Martin C, Walsh T, Yamrom B, Yoon S, Krasnitz A, Kendall J, et al. Science. 2007;316:445–449. [PMC free article] [PubMed]
  • Shahbazian M, Young J, Yuva-Paylor L, Spencer C, Antalffy B, Noebels J, Armstrong D, Paylor R, Zoghbi H. Neuron. 2002;35:243–254. [PubMed]
  • Sharpe NA, Tepper JM. Neuroscience. 1998;84:1163–1175. [PubMed]
  • Shaw P, Greenstein D, Lerch J, Clasen L, Lenroot R, Gogtay N, Evans A, Rapoport J, Giedd J. Nature. 2006;440:676–679. [PubMed]
  • Shionoya K, Moriceau S, Bradstock P, Sullivan RM. Horm Behav. 2007;52:391–400. [PMC free article] [PubMed]
  • Solomon RL, Corbit JD. Psychol Rev. 1974;81:119–145. [PubMed]
  • Sowell ER, Delis D, Stiles J, Jernigan TL. J Int Neuropsychol Soc. 2001;7:312–322. [PubMed]
  • Stanwood GD, Levitt P. The effects of cocaine on the developing nervous system. In: Nelson CA, Luciana M, editors. Handbook of Developmental Cognitive Neuroscience. 2nd edition MIT Press; 2008. pp. 83–94.
  • Stefansson H, Ophoff RA, Steinberg S, Andreassen OA, Cichon S, Rujescu D, Werge T, Pietilainen OP, Mors O, Mortensen PB, et al. Nature. 2009;460:744–747. [PMC free article] [PubMed]
  • Suchecki D, Rosenfeld P, Levine S. Brain Res Dev Brain Res. 1993;75:185–192. [PubMed]
  • Tabuchi K, Blundell J, Etherton MR, Hammer RE, Liu X, Powell CM, Sudhof TC. Science. 2007;318:71–76. [PMC free article] [PubMed]
  • Thompson BL, Levitt P. Neuron. 2010;65:437–439. [PubMed]
  • Thompson BL, Levitt P, Stanwood GD. Nat Rev Neurosci. 2009;10:303–312. [PMC free article] [PubMed]
  • Tibbo P, Swainson J, Chue P, LeMelledo JM. Depress Anxiety. 2003;17:65–72. [PubMed]
  • Torii M, Hashimoto-Torii K, Levitt P, Rakic P. Nature. 2009;461:524–528. [PMC free article] [PubMed]
  • Torii M, Levitt P. Neuron. 2005;48:563–575. [PubMed]
  • Trachtenberg JT, Chen BE, Knott GW, Feng G, Sanes JR, Welker E, Svoboda K. Nature. 2002;420:788–794. [PubMed]
  • Tropea D, Giacometti E, Wilson NR, Beard C, McCurry C, Fu DD, Flannery R, Jaenisch R, Sur M. Proc Natl Acad Sci U S A. 2009;106:2029–2034. [PubMed]
  • Uno H, Tarara R, Else JG, Suleman MA, Sapolsky RM. J Neurosci. 1989;9:1705–1711. [PubMed]
  • Vismara LA, Rogers SJ. Annu Rev Clin Psychol. 2010;6:447–468. [PubMed]
  • Wang K, Zhang H, Ma D, Bucan M, Glessner JT, Abrahams BS, Salyakina D, Imielinski M, Bradfield JP, Sleiman PM, et al. Nature. 2009;459:528–533. [PMC free article] [PubMed]
  • Weaver IC, Cervoni N, Champagne FA, D'Alessio AC, Sharma S, Seckl JR, Dymov S, Szyf M, Meaney MJ. Nat Neurosci. 2004;7:847–854. [PubMed]
  • Weeber EJ, Jiang YH, Elgersma Y, Varga AW, Carrasquillo Y, Brown SE, Christian JM, Mirnikjoo B, Silva A, Beaudet AL, Sweatt JD. J Neurosci. 2003;23:2634–2644. [PubMed]
  • Wei Q, Hebda-Bauer EK, Pletsch A, Luo J, Hoversten MT, Osetek AJ, Evans SJ, Watson SJ, Seasholtz AF, Akil H. J Neurosci. 2007;27:8836–8844. [PubMed]
  • Weiss LA, Shen Y, Korn JM, Arking DE, Miller DT, Fossdal R, Saemundsen E, Stefansson H, Ferreira MA, Green T, et al. N Engl J Med. 2008;358:667–675. [PubMed]
  • Yashiro K, Riday TT, Condon KH, Roberts AC, Bernardo DR, Prakash R, Weinberg RJ, Ehlers MD, Philpot BD. Nat Neurosci. 2009;12:777–783. [PMC free article] [PubMed]