Comments on News and Primary Papers
Primary Papers: Neocortical excitation/inhibition balance in information processing and social dysfunction.Comment by: Patricio O'Donnell, SRF Advisor
Submitted 2 August 2011
Posted 2 August 2011
A question that comes to mind to most when reading an article such as the one Yizhar et al. published online July 27 in Nature is: is this a big step forward or a flashy way to show what we already know? The answer is: both. It has to be.
Optogenetic tools to address neurobiological questions in a well-controlled manner, with selective activation or inactivation of specific brain areas and even cell types, pioneered by Karl Deisseroth’s group, have been around for some time. Deisseroth deserves recognition for developing such a clever tool, but even stronger recognition for proactively sharing these tools with anyone who requests them.
So far, optogenetic tools have been mostly used to address questions for which there were extensive previous studies, albeit with less conclusive techniques. Naturally, some would see that as just a replication of existing knowledge. However, an important first step for a novel tool like this one is to establish credibility, and what better approach than tackling questions for which we know the answer? For example, a couple of papers using optogenetics in 2009 “demonstrated” that parvalbumin (PV) fast-spiking interneurons in cortical circuits are critical for high-frequency oscillations (Cardin et al., 2009; Sohal et al., 2009). Extensive studies had suggested that cortical GABA interneurons are critical for high-frequency oscillations (Atallah and Scanziani, 2009; Puig et al., 2008; Tort et al., 2007; Fries et al., 2007). But the ability to selectively activate or inactivate this neuronal population was not available until the arrival of optogenetics. Addressing an issue with strong data already available was a necessary step, and now we can examine the role of inhibitory cortical neurons in physiology and behavior with well-controlled and reliable tools. One could also place quotation marks around the “we know the answer” in the previous question, since a conclusive causal link between interneuron activity and oscillations, assumed by most, was actually missing. Thus, optogenetic tools may represent flashy confirmations, but one can say the information they have provided so far has nailed old questions in a mechanistic way.
There have been other approaches to establish this type of mechanistic link, including genetic manipulations. For example, knocking out NMDA receptors in PV interneurons yields a number of alterations in adult animals (Belforte et al., 2010), showing that a number of behavioral and electrophysiological properties do depend on interneuron function. These approaches are not mutually exclusive and are quite complementary. Optogenetics allows manipulation of these systems while the animals engage in behaviors, permitting a within-subject comparison, whereas transgenic animals allow the exploration of developmental aspects of interneuron function. Both approaches are here to stay, but are not likely to displace more common and established tools.
In this week’s article, Yizhar et al. provide more than a dramatic confirmation using an array of novel opsins to enhance or suppress activity in pyramidal excitatory neurons or local inhibitory interneurons. Step-function opsins allow lasting depolarizations in either pyramidal neurons or parvalbumin (PV)-positive interneurons in the rat medial prefrontal cortex, enhancing their excitability as a means to alter excitation-inhibition balance within this cortical region while assessing behavioral performance. Shifting excitation-inhibition balance towards increased excitation, but not the other way around, impaired social behaviors and enhanced high-frequency oscillations. There may be some caveats in how physiological a step-function opsin-induced increase in firing may be. A constant depolarization may not be the best way to reproduce firing patterns in fast-spiking interneurons, which rely on a fast and sharp K+ channel-dependent hyperpolarization to rapidly reactivate Na+ channels and allow fast frequencies of firing. Despite this limitation, the authors showed a decrease in pyramidal cell firing following activation of PV neurons, suggesting inhibitory processes were enhanced.
As with other highly visible optogenetic manuscripts, the issue at hand (i.e., whether excitation-inhibition balance is critical for PFC behavior) had been extensively studied. Altered excitation-inhibition balance is a key new element in current views of the pathophysiology of psychiatric disorders, and understanding its link to behavior is certainly critical. We recently showed cognitive deficits in rats with a neonatal ventral hippocampal lesion, a widely used rodent model of major psychiatric disorder that is characterized by loss of activation in prefrontal cortical interneurons (Gruber et al., 2010). However, in ours and all previous studies, the link between interneuron activity or excitation-inhibition balance and behavioral performance was correlational in nature. Yizhar et al. altered behaviors by selectively targeting pyramidal neurons or interneurons, and a causal link could be established. This is both a flashy confirmation and a leap forward. To be able to establish causality where extensive studies have shown strong correlations hinting at causality is a welcome step. Perhaps optogenetics has come of age now, and it is ready to tackle novel questions, but work like what Yizhar et al. produced is indeed an illuminating (a literal blue one) and big step forward.
Atallah BV, Scanziani M. Instantaneous modulation of gamma oscillation frequency by balancing excitation with inhibition. Neuron . 2009 May 28 ; 62(4):566-77. Abstract
Belforte JE, Zsiros V, Sklar ER, Jiang Z, Yu G, Li Y, Quinlan EM, Nakazawa K. Postnatal NMDA receptor ablation in corticolimbic interneurons confers schizophrenia-like phenotypes. Nat Neurosci . 2010 Jan 1 ; 13(1):76-83. Abstract
Cardin JA, Carlén M, Meletis K, Knoblich U, Zhang F, Deisseroth K, Tsai LH, Moore CI. Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature . 2009 Jun 4 ; 459(7247):663-7. Abstract
Fries P, Nikolic D, Singer W. The gamma cycle. Trends Neurosci . 2007 Jul 1 ; 30(7):309-16. Abstract
Gruber AJ, Calhoon GG, Shusterman I, Schoenbaum G, Roesch MR, O'Donnell P. More is less: a disinhibited prefrontal cortex impairs cognitive flexibility. J Neurosci . 2010 Dec 15 ; 30(50):17102-10. Abstract
Puig MV, Ushimaru M, Kawaguchi Y. Two distinct activity patterns of fast-spiking interneurons during neocortical UP states. Proc Natl Acad Sci U S A . 2008 Jun 17 ; 105(24):8428-33. Abstract
Sohal VS, Zhang F, Yizhar O, Deisseroth K. Parvalbumin neurons and gamma rhythms enhance cortical circuit performance. Nature . 2009 Jun 4 ; 459(7247):698-702. Abstract
Tort AB, Rotstein HG, Dugladze T, Gloveli T, Kopell NJ. On the formation of gamma-coherent cell assemblies by oriens lacunosum-moleculare interneurons in the hippocampus. Proc Natl Acad Sci U S A . 2007 Aug 14 ; 104(33):13490-5. Abstract
View all comments by Patricio O'Donnell
Primary Papers: Neocortical excitation/inhibition balance in information processing and social dysfunction.
Comment by: Cynthia Shannon Weickert, SRF Advisor, Duncan Sinclair, Vibeke Catts
Submitted 29 August 2011
Posted 29 August 2011
Optogenetics Stimulates Our Thinking About Cortical Pathology in Schizophrenia
We recently reviewed this paper in the weekly Journal Club at the Schizophrenia Research Laboratory in Sydney, Australia. Here are some brief thoughts from our discussion:
First, we were very impressed with the development of the novel stable step function opsin (SSFO) and the anatomical and temporal precision with which it can be used in the mouse. Particularly powerful is the ability to induce cortical excitation in a time frame long enough to impact behavior without the confound of developmental compensatory change, as may occur in genetically engineered mice. The paper did raise a few questions in our minds about how to best relate this to findings in schizophrenia, especially in light of the ongoing debates as to: 1) whether the cortex is actually overactive or underactive (hyperactivity versus hypoactivity by fMRI); 2) whether the cortex shows increased γ band synchrony (at baseline) or decreased γ band synchrony (induced); and 3) whether there is more or less GABA present (postmortem decrease in GAD67 with possible increase by MRS) in people with schizophrenia.
This paper helps us to understand how an exogenously stimulated increase in overall cortical excitability could interfere with some basic social behaviors. It certainly did seem like the "overexcited" mouse was disinterested in the novel immature mouse and preferred not to socialize. Even though the reasons for a mouse not to engage socially are not known, we do know that people with schizophrenia can report that they are feeling paranoid or nervous around other people. So, it would be tempting to wonder whether these thoughts or feelings may be generated by increased prefrontal pyramidal neuron activity, but this, of course, will be difficult to prove. Exploration of the relationship between positive symptoms—hallucinations and delusions—and overactivity of cortical brain regions (by fMRI and with possible disruption by rTMS), in particular in the temporal lobe, may help to answer this question. Additionally, investigation of localized versus cortex-wide changes in excitation/inhibition could shed light on whether pathology in a particular cortical region is necessary and sufficient to drive behavioral changes or even pathological changes, such as increases in subcortical dopamine (Lisman et al., 2008).
While we were convinced by the lack of clear impact of prefrontal cortical "over-inhibition" on behavior, except in combination with "overexcitation," we had some questions regarding the choice of parvalbumin positive (PV+) neurons for modulation in this study. Certainly, there is accumulating evidence that they are pathological in schizophrenia, but recent evidence suggests that PV+ interneurons can mediate both excitatory and inhibitory effects of GABA, depending on the location of their synapse onto the target cell (Szabadics et al., 2006). A subset of PV+ neurons innervate the axon initial segment and may actually stimulate the pyramidal neurons through excitatory actions of GABA at that particular location, whereas PV+ basket neurons innervate the soma, and mediate inhibitory effects of GABA. Therefore, would basket cells be the more likely mediators of the hyperpolarization and loss of excitation reported in this study? Future studies exploring the excitatory/inhibitory balance in schizophrenia may benefit from more anatomically based evaluations of specific subtypes of interneurons in the postmortem human brain. Furthermore, since this technology has the potential to offer a greater understanding of the potential primacy of pathophysiological events, we wonder whether a channel rhodopsin that gates chloride ions into the cells (provided it could be stabilized, as the SSFO was here) would be a way to test if less activity in the different populations of inhibitory interneurons (i.e., somatostatin compared to parvalbumin) could lead to different types of hyperexcitable states in cortical pyramidal neurons? Also, understanding how these more specific changes could lead to changes in more refined and context-dependent tests of social interaction or working memory would be informative alongside measures of pathological change at the level of neurotransmitter release or molecular signaling. In sum, we thoroughly enjoyed discussing the paper, and it gave us much to consider. We applauded the group and hope to continue to have more great papers to discuss!
Lisman, J. E., Coyle, J. T., Green, R. W., Javitt, D. C., Benes, F. M., Heckers, S. and Grace, A. A., 2008. Circuit-based framework for understanding neurotransmitter and risk gene interactions in schizophrenia. Trends in Neurosciences 31, 234-242. Abstract
Szabadics, J., Varga, C., Molnar, G., Olah, S., Barzo, P., Tamas, G., 2006. Excitatory effect of GABAergic axo-axonic cells in cortical microcircuits. Science 311, 233-235. Abstract
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Comments on Related News
Related News: Commentary Brief: Optogenetics Links Interneurons and γ OscillationsComment by: Guillermo Gonzalez-Burgos
Submitted 24 July 2009
Posted 24 July 2009
Blue light, yellow light, and the role of parvalbumin-positive neurons in the pathophysiology of schizophrenia
Parvalbumin (PV)-positive cells are a prominent subtype of GABA neuron that via perisomatic synapses may strongly inhibit pyramidal cell activity (however, see Szabadics et al., 2006). In schizophrenia, PV neurons have reduced levels of mRNA for PV and for GAD67, the 67 kilodalton form of the GABA-synthesizing enzyme glutamate decarboxylase. The functional consequences of the PV reduction in schizophrenia are poorly understood, but one possibility is that decreased PV partially compensates for a deficit in GABA release caused by the GAD67 reduction. PV is a slow Ca2+ buffer, and so decreasing PV in nerve terminals may facilitate GABA release during repetitive PV cell firing (for a review, see Gonzalez-Burgos and Lewis, 2008).
Why is PV cell-mediated inhibition significant to brain function? What deficits in cortical circuit function may be compensated for (at least partially) by a decrease of PV in schizophrenia? The answers to these questions depend on our knowledge of the functional role of PV neurons in cortical circuits. A leading hypothesis in this regard suggests that PV cells are essential for the production of synchronized oscillations in cortex, particularly in the γ frequency band (Bartos et al., 2007). γ oscillations are thought to be important for the transmission of information within and between neocortical areas (Salinas and Sejnowski, 2001). If so, then γ activity must be important for cognition, which is critically dependent on the flow of information across the neocortex (Singer, 1999; Fuster, 2004). Therefore, cognitive deficits (a key feature of schizophrenia) may result from the impairment of γ oscillations reported in the illness, which in turn could be a consequence of deficits in PV cell-mediated inhibition.
How is PV cell-mediated inhibition linked to the production of γ oscillations? PV neurons alone are not sufficient to produce network oscillations because, although PV cell membranes resonate at γ frequency (Pike et al., 2000), PV neurons actually lack intrinsic pacemaker activity. Therefore, whereas PV cells may be necessary to produce γ oscillations, synaptic interactions with other cell types in the cortical circuit must be necessary as well.
Studying the link between PV neuron activity and γ oscillations is complicated by the lack of tools available to selectively manipulate PV cell activity. Interestingly, two recent studies (Sohal et al., 2009; Cardin et al., 2009) employed novel “optogenetic” methods in mice, to further advance our understanding of how PV neurons are involved in γ oscillations.
Using viral vectors to drive cell type-specific expression of recombinant genes, Sohal and colleagues, as well as Cardin et al., produced expression of microbial opsins (which are light-sensitive ion channel proteins) selectively in specific populations of cortical neurons. Briefly described, modulation of neuronal activity using such optogenetic techniques works as follows: in cells expressing channelrhodopsin-2 (ChR2), illumination with blue light produces a depolarizing current that has excitatory effects (increases cell firing). On the other hand, cells expressing halorhodopsin (eNpHR) respond to yellow light with a hyperpolarizing current that has inhibitory effects (decreases cell firing). In this way, light of different wavelengths can be used to either inhibit or excite PV cells or pyramidal (PYR) neurons in the mouse cortex (in vivo or in vitro) in different experimental designs.
Sohal and colleagues first demonstrated that inhibiting the activity of eNpHR-expressing PV neurons with yellow light suppresses γ oscillations generated in vivo by rhythmic flashes of blue light applied to stimulate nearby ChR2-expressing PYR neurons. Furthermore, they show that non-rhythmic excitation of PYR cells produces non-rhythmic PYR cell firing. However, if the non-rhythmic PYR spikes are used to trigger feedback inhibition by PV neurons (driven by blue light flashes that stimulate ChR2-expressing PV cells), the addition of feedback inhibition induces a γ rhythm in PYR cell output. These results show that by means of recurrent interactions with pyramidal cells (consistent with the so-called PING models of γ rhythms; Whittington et al., 2000), PV cell activity is crucial for γ oscillations.
Finally, the experiments performed by Sohal et al. suggest that γ activity may selectively enhance the flow of information in cortical circuits. For example, their experiments demonstrate that the gain of the neuronal input-output relation (that is, the slope of the curve describing the transformation of inputs into outputs) is specifically enhanced when excitatory inputs onto a PYR cell are modulated rhythmically at γ frequency. Moreover, the amount of information flowing across synapses during interactions between PYR and PV neurons was estimated using concepts derived from information theory. The estimates from Sohal et al. showed that when network activity was driven by trains of blue flashes delivered at γ frequency, information transmission was markedly enhanced.
Using somewhat different genetic engineering approaches, Cardin and colleagues produced cell type-specific expression of ChR2 in PV cells or PYR neurons. Expression of ChR2 in PV cells of the mouse barrel (somatosensory) cortex allowed the activation of PV neurons with rhythmic flashes of light. Such manipulation produced rhythmic population activity (as detected recording local field potentials) more strongly when PV cells were driven at γ frequency compared with other frequencies. They report, in addition, some data showing that manipulation of PV cell activity has an impact on γ oscillations intrinsically generated by the cortical circuits, as opposed to γ rhythms induced by rhythmic stimuli applied by the investigators. For example, brief flashes of blue light applied to stimulate firing of ChR2-expressing PV neurons during spontaneous γ activity were able to reset the phase of the γ rhythm.
Cardin et al. also demonstrate that activation of ChR2-expressing PV neurons can suppress the somatosensory response (to whisker stimulation) of nearby PYR cells. Then they go on to test an important functional role predicted for γ oscillations: that cells in a local network engaged in γ oscillations may respond differently to incoming inputs, depending on the timing of the incoming inputs relative to the phase of the γ cycle (Fries et al., 2007). In an elegant experiment, the investigators paired brief whisker stimulation with rhythmic flashes of blue light which, by stimulating ChR2-expressing PV cells, generate a γ rhythm locally. The crucial finding from this experiment is that the excitatory power of whisker stimulation was strongly dependent on the γ cycle phase at which whisker stimulation was delivered.
The data from these two recent studies briefly summarized above further consolidate the notion that PV-positive GABA neurons are key players in the mechanisms of γ synchrony in cortex. The data from these studies confirm that rhythmic PV neuron firing at γ frequency is sufficient to generate a γ rhythm in the population of postsynaptic neurons. This is not the same, however, as saying that PV neurons alone are sufficient to generate γ. Indeed, the data from these two studies point to the idea that PV neurons work in close interaction, via feedback loops, with nearby pyramidal cells. This makes sense, given that PV neurons are not intrinsic pacemakers. γ rhythms, therefore, seem to originate in complex network interactions that require the coordinated activity of pyramidal neurons, PV cells, and possibly other GABA neuron subtypes as well.
These two studies also highlight the similar importance of PV cell-dependent γ oscillations across different regions of cortex primarily involved in very different functions: Sohal and colleagues studied the role of PV neurons in frontal cortical areas, whereas Cardin et al. manipulated PV cell activity in the primary somatosensory cortex. The similarity of the findings regarding PV neuron function suggests that these neurons probably play a very similar role, at the microcircuit level, in these two very different cortical areas. Interestingly, deficits in GABA transmission, as assessed in postmortem brain studies, appear to be found in multiple areas of cortex simultaneously (Hashimoto et al., 2008). If this is indeed the case, then an impairment of γ oscillations may be present in most cortical areas. Thus, deficits in PV cell-dependent γ rhythms may explain the impairment of not only complex cognitive functions (for example, working memory), but also of more basic sensory processing which, as reviewed elsewhere (Javitt, 2009), is also impaired in schizophrenia. Finding a global deficit of GABA transmission and γ oscillations, as opposed to a deficit restricted to a single cortical area, increases the probability of success in developing pharmacological treatments.
A better understanding of the functional role of PV neurons in normal cortical circuits is crucial to developing better models that could explain how alterations of PV cells (and of other GABA neurons subtypes) originate in schizophrenia. As highlighted elsewhere (Lewis and Gonzalez-Burgos, 2008), any given alteration observed in schizophrenia may represent 1) cause, an upstream factor related to the disease pathogenesis; 2) consequence, a deleterious effect of a cause; 3) compensation, a response to either cause or consequence that helps restore homeostasis; or 4) confound, a product of factors frequently associated with, but not a part of, the disease process, or an artifact of the approach used to obtain the measure of interest. A major challenge for schizophrenia research is therefore determining to which of the four “C” categories each alteration belongs (Lewis and Gonzalez-Burgos, 2008). Certainly, information from basic neuroscience research studies such as those of Sohal et al. and Cardin et al. and many other past and future studies is extremely helpful in achieving this goal.
Szabadics J, Varga C, Molnar G, Olah S, Barzo P, Tamas G: Excitatory effect of GABAergic axo-axonic cells in cortical microcircuits. Science 311:233-235, 2006. Abstract
Gonzalez-Burgos G, Lewis DA: GABA Neurons and the Mechanisms of Network Oscillations: Implications for Understanding Cortical Dysfunction in Schizophrenia. Schizophr Bull 34:944-961, 2008. Abstract
Bartos M, Vida I, Jonas P: Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nat Rev Neurosci 8:45-56, 2007.Abstract
Salinas E, Sejnowski TJ: Correlated neuronal activity and the flow of neural information. Nat Rev Neurosci 2:539-550, 2001. Abstract
Singer W: Neuronal synchrony: a versatile code for the definition of relations? Neuron 24:111-25, 1999. Abstract
Fuster JM: Upper processing stages of the perception-action cycle. Trends Cogn Sci 8:143-145, 2004. Abstract
Pike FG, Goddard RS, Suckling JM, Ganter P, Kasthuri N, Paulsen O: Distinct frequency preferences of different types of rat hippocampal neurones in response to oscillatory input currents. J Physiol 529 Pt 1:205-213, 2000. Abstract
Sohal VS, Zhang F, Yizhar O, Deisseroth K: Parvalbumin neurons and gamma rhythms enhance cortical circuit performance. Nature 2009 Jun 4;459(7247):698-702. Abstract
Cardin JA, Carlen M, Meletis K, Knoblich U, Zhang F, Deisseroth K, Tsai LH, Moore CI: Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 2009 Jun 4;459(7247):663-7. Abstract
Whittington MA, Traub RD, Kopell N, Ermentrout B, Buhl EH: Inhibition-based rhythms: experimental and mathematical observations on network dynamics. Int J Psychophysiol 38:315-336, 2000. Abstract
Fries P, Nikolic D, Singer W: The gamma cycle. Trends Neurosci 30:309-316, 2007. Abstract
Hashimoto T, Bazmi HH, Mirnics K, Wu Q, Sampson AR, Lewis DA: Conserved Regional Patterns of GABA-Related Transcript Expression in the Neocortex of Subjects With Schizophrenia. American Journal of Psychiatry 162:479-489, 2008. Abstract
Javitt DC: When doors of perception close: bottom-up models of disrupted cognition in schizophrenia. Annu Rev Clin Psychol 5:249-275, 2009. Abstract
Lewis DA, Gonzalez-Burgos G: Neuroplasticity of neocortical circuits in schizophrenia. Neuropsychopharmacology 33:141-165, 2008. Abstract
View all comments by Guillermo Gonzalez-Burgos
Related News: Genomic Studies Draw Autism and Schizophrenia Back Toward Each Other
Comment by: Katie Rodriguez
Submitted 7 November 2009
Posted 7 November 2009
If schizophrenia and autism are on a spectrum, how can there be people who are both autistic and schizophrenic? I know of a few people who suffer from both diseases.
View all comments by Katie Rodriguez
Related News: Genomic Studies Draw Autism and Schizophrenia Back Toward Each Other
Comment by: Bernard Crespi
Submitted 12 November 2009
Posted 12 November 2009
One Hundred Years of Insanity: The Relationship Between Schizophrenia and Autism
The great Colombian author Gabriel García Márquez reified the cyclical nature of history in his Nobel Prize-winning 1967 book, One Hundred Years of Solitude. Eugen Bleuler’s less-famous book Dementia Præcox or the Group of Schizophrenias, originally published in 1911, saw first use of the term “autism,” a form of solitude manifest as withdrawal from reality in schizophrenia. This neologism, about to celebrate its centenary, epitomizes an astonishing cycle of reification and change in nosology, a cycle only now coming into clear view as molecular-genetic data confront the traditional, age-old categories of psychiatric classification.
The term autism was, of course, redefined by Leo Kanner (1943) for a childhood psychiatric condition first considered as a subset of schizophrenia, then regarded as quite distinct (Rutter, 1972) or even opposite to it (Rimland, 1964; Crespi and Badcock, 2008), and most recently seen by some researchers as returning to its original Bluelerian incarnation (e.g., Carroll and Owen, 2009). An outstanding new paper by McCarthy et al. (2009), demonstrating that duplications of the CNV locus 16p11.2 are strongly associated with increased risk of schizophrenia, has brought this question to the forefront of psychiatric inquiry, because deletions of this same CNV are one of the most striking recently-characterized risk factors for autism. Additional CNVs, such as those at 1q21.1 and 22q11.21 have also been associated with autism and schizophrenia in one or more studies (e.g., Mefford et al., 2008; Crespi et al., 2009; Glessner et al., 2009), which has led some authors to infer that since an overlapping set of loci mediates risk of both conditions, autism and schizophrenia must be more similar than previously conceived (e.g., Carroll and Owen, 2009; Guilmatre et al., 2009). Similar considerations apply to several genes, such as CNTNAP2 and NRXN1, various disruptions of which have likewise been linked with both conditions (Iossifov et al., 2008; Kirov et al., 2008; Burbach and van der Zwaag, 2009).
So does this plethora of new molecular-genetic data imply that Blueler was indeed correct, if not prescient, that autism and schizophrenia are manifestations of similar disease processes? The answer may appear tantalizingly close, but will likely remain inaccessible without explicit consideration of alternative hypotheses and targeted tests of their differentiating predictions. This approach is simply Platt’s (1964) classic method of strong inference, which has propelled molecular biology so far and fast but left psychiatry largely by the wayside (Cannon, 2009). The alternative hypotheses in this case are clear: with regard to causation from specific genetic and genomic risk factors, autism and schizophrenia are either: 1) independent and discrete, 2) partially yet broadly overlapping, 3) subsumed with autism as a subset of schizophrenia, or 4) diametrically opposite, with normality in the centre. CNVs are especially useful for testing among such alternative hypotheses, because they naturally involve highly-penetrant perturbations in two opposite directions, due to deletions vs duplications of more or less the same genomic regions. Hypotheses 2), 3) and 4) thus predict that autism and schizophrenia should share CNV risk loci, but 2) and 3) predict specific rearrangements (deletions, duplications, or both) shared across both conditions; by contrast, hypothesis (4) predicts that, as highlighted by McCarthy et al. (2009), reciprocal CNVs at the same locus should mediate risk of autism versus schizophrenia. This general approach was pioneered by Craddock et al. (2005, 2009), in their discussion of explicit alternative hypotheses for the relationship between schizophrenia and bipolar disorder, which are now known to share a notable suite of risk alleles.
A key assumption that underlies tests of hypotheses for the relationship between autism and schizophrenia is accuracy of diagnoses. For schizophrenia, this is seldom at issue. However, diagnoses of autism, or autism spectrum disorders such as PDD-NOS, are normally made at an age well before the first manifestations of schizophrenia in adolescence or early adulthood, which generates a risk for false-positive diagnoses of premorbidity to schizophrenia as autism or autism spectrum (e.g., Eliez, 2007). The tendencies for males to exhibit worse premorbidity to schizophrenia than females (Sobin et al., 2001; Tandon et al., 2009), for CNVs to exert severe effects on diverse aspects of early neurodevelopment (Shinawi et al., 2009), and for schizophrenia of earlier onset to exhibit a higher male sex-ratio bias and a stronger tendency to be associated with CNVs rather than other causes (Remschmidt et al., 1994; Rapoport et al., 2009), all suggest a high risk for false-positive diagnoses of autistic spectrum conditions in individuals with these genomic risk factors (Feinstein and Singh, 2007; Reaven et al., 2008; Sugihara et al., 2008; Starling and Dossetor, 2009). Possible evidence of such risk comes from diagnoses of autism spectrum conditions in children with deletions at 15q11.2, 15q13.3, and 22q11.21, and duplications of 16p11.2, CNVs for which schizophrenia risk has been well established from studies of adults (Antshel et al., 2007; Stefansson et al., 2008; Weiss et al., 2008; Ben-Shachar et al., 2009; Doornbos et al., 2009; McCarthy et al., 2009). By contrast, autism-associated CNVs, such as deletions at 16p11.2 (Kumar et al., 2008), or duplications at 22q11.21 (Glessner et al., 2009; Crespi et al., 2009) have seldom also been reported in individuals diagnosed with schizophrenia, which suggests that false-positive diagnoses of schizophrenia as autism are uncommon.
Differentiating between a hypothesis of false-positive diagnoses of premorbidity to schizophrenia as autism, compared to a hypothesis of specific deletions or duplications shared between autism and schizophrenia, requires some combination of longitudinal studies, judicious use of endophenotypes, and adoption of relatively new diagnostic categories such as multiple complex developmental disorder (Sprong et al., 2008). Moreover, to the degree that such false positives are not uncommon, and autism and schizophrenia are underlain by diametric genetically based risk factors, inclusion of children premorbid for schizophrenia in studies on the genetic bases of autism will substantially dilute the probability of detecting significant results.
Ultimately, robust evaluation of alternative hypotheses for the relationship of autism with schizophrenia will require evidence from studies of common and rare SNP variants as well as CNVs, in-depth analyses of the neurodevelopmental and neuronal-function effects of different alterations to genes such as NRXN1, CNTNAP2, and SHANK3, and integrative data from diverse disciplines other than genetics, especially the neurosciences and psychology. Unless such interdisciplinary studies are deployed—in hypothesis-testing frameworks that use strong inference—we should expect to remain, as penned by García Márquez, in “permanent alternation between excitement and disappointment, doubt and revelation, to such an extreme that no one knows for certain where the limits of reality lay”—for yet another 100 years.
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Bleuler E. 1950. Dementia praecox or the group of schizophrenias. (Internat Univ Press, New York). (Translation from 1911 German original).
Burbach JP, van der Zwaag B. Contact in the genetics of autism and schizophrenia. Trends Neurosci. 2009 Feb;32(2):69-72. Abstract
Cannon TD. What is the role of theories in the study of schizophrenia? Schizophr Bull. 2009 May;35(3):563-7. Abstract
Carroll LS, Owen MJ. Genetic overlap between autism, schizophrenia and bipolar disorder. Genome Med. 2009 Oct 30;1(10):102. Abstract
Craddock N, Owen MJ. The beginning of the end for the Kraepelinian dichotomy. Br J Psychiatry. 2005 May;186:364-6. Abstract
Craddock N, O'Donovan MC, Owen MJ. Psychosis genetics: modeling the relationship between schizophrenia, bipolar disorder, and mixed (or "schizoaffective") psychoses. Schizophr Bull. 2009 May;35(3):482-90. Abstract
Crespi B, Badcock C. Psychosis and autism as diametrical disorders of the social brain. Behav Brain Sci. 2008 Jun;31(3):241-61; discussion 261-320.
Crespi B, Stead P, Elliot M. Comparative genomics of autism and schizophrenia. Proc Natl Acad Sci U S A. 2009 (in press).
Doornbos M, Sikkema-Raddatz B, Ruijvenkamp CA, Dijkhuizen T, Bijlsma EK, Gijsbers AC, Hilhorst-Hofstee Y, Hordijk R, Verbruggen KT, Kerstjens-Frederikse WS, van Essen T, Kok K, van Silfhout AT, Breuning M, van Ravenswaaij-Arts CM. Nine patients with a microdeletion 15q11.2 between breakpoints 1 and 2 of the Prader-Willi critical region, possibly associated with behavioural disturbances. Eur J Med Genet. 2009 Mar-Jun;52(2-3):108-15. Abstract
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Related News: Genomic Studies Draw Autism and Schizophrenia Back Toward Each Other
Comment by: Suzanna Russell-Smith, Donna Bayliss, Murray Maybery
Submitted 9 February 2010
Posted 10 February 2010
The Diametric Opposition of Autism and Psychosis: Support From a Study of Cognition
As has been noted previously, Crespi and Badcock’s (2008) theory that autism and schizophrenia are diametrically opposed disorders is certainly a novel and somewhat controversial one. In his recent blog on Psychology Today, Badcock states that the theory stands on two completely different foundations: one in evolution and genetics, and one in psychiatry and cognitive science (Badcock, 2010). While most of the comments posted before ours have addressed the relationship between autism and schizophrenia from a genetic perspective, coming from a psychology background, we note that it is the aspects of Crespi and Badcock’s theory that relate to cognition which have particularly caught our attention. While we can therefore contribute little to the discussion of a relationship between autism and schizophrenia from a genetic standpoint, we present the findings from our recent study (Russell-Smith et al., 2010), which provided the first test of Crespi and Badcock’s claim that autism and psychosis are at opposite ends of the cognitive spectrum.
In placing autism and psychosis at opposite ends of the cognitive spectrum, Crespi and Badcock (2008) propose that autistic and positive schizophrenia traits contrastingly affect preference for local versus global processing, with individuals with autism displaying a preference for local processing and individuals with positive schizophrenia displaying a preference for global processing. That is, these authors claim that while individuals with autism show a tendency to focus on detail or process features in their isolation, individuals with positive schizophrenia show a tendency to look at the bigger picture or process features as an integrated whole. Importantly, since Crespi and Badcock argue for a continuum stretching all the way from autism to psychosis, the same diametric pattern of cognition should be seen in individuals who display only mild variants of autistic and positive schizophrenia traits. This includes typical individuals who score highly on measures such as the Autism Spectrum Quotient (AQ; Baron-Cohen et al., 2001) and the Unusual Experiences subscale of the Oxford-Liverpool Inventory of Experiences (O-LIFE:UE; Mason et al., 2005). These are both reliable and commonly used measures which have been specifically designed to assess the levels of “autistic-like” traits and positive schizotypy traits in typical individuals. Since Crespi and Badcock actually argue their theory is best evaluated with reference to individuals with milder traits of autism and positive schizophrenia, it is with these populations that we investigated their claims.
A task often used to determine whether an individual has a preference for local over global processing is the Embedded Figures Test (EFT; Witkin et al., 1971), which requires individuals to detect hidden shapes within complex figures. As the test requires one to resist experiencing an integrated visual stimulus or gestalt in favor of seeing single elements, it is argued that a local processing style aids successful (i.e., faster) completion of this task (Bolte et al., 2007). Accordingly, from Crespi and Badcock’s (2008) theory, one would expect that relative to individuals with low levels of these traits, individuals with high levels of autistic-like traits should perform better on the EFT, while individuals with positive schizotypy traits should perform worse. To test this claim, our study obtained the AQ and O-LIFE:UE scores for 318 students completing psychology as part of a broader degree (e.g., a BSc or BA). Two pairs of groups (i.e., four groups in total), each consisting of 20 students, were then formed. One of these pairs consisted of High and Low AQ groups, which were selected such that they were separated substantially in their AQ scores but matched as closely as possible on their O-LIFE:UE scores. The other pair of groups, the High and Low O-LIFE:UE groups, were selected such that they were separated in their O-LIFE:UE scores, but matched as closely as possible on their AQ scores. The gender ratio was matched closely across the four groups.
To test the prediction that higher levels of autistic-like traits are associated with more skilled EFT performance, the High and Low AQ groups were compared in terms of their mean response time to accurately locate each of the embedded figures. Individuals in the High AQ group did display more skilled EFT performance than individuals in the Low AQ group, consistent with a greater preference for local over global processing in relation to higher levels of autistic-like traits (see also Almeida et al., 2010; Bolte and Poustka, 2007; Grinter et al., 2009; Grinter et al., 2009). We then compared EFT performance for the O-LIFE:UE groups to test the prediction that higher levels of positive schizotypy traits are associated with less skilled performance on this task. Consistent with a preference for global over local processing in relation to higher levels of positive schizotypy traits, individuals in the High O-LIFE:UE group displayed less skilled EFT performance than individuals in the Low O-LIFE:UE group. Therefore, results from both pairs of groups together provide support for Crespi and Badcock’s (2008) claim that autistic and positive schizophrenia traits are diametrically opposed with regard to their effect on local versus global processing.
However, the support our study offers for Crespi and Badcock’s (2008) theory was tempered slightly by our failure to find the expected contrasting patterns of non-verbal relative to verbal ability for our two pairs of groups. To display the expected patterns, relative to individuals with low levels of these traits, individuals with high levels of autistic-like traits should have displayed higher non-verbal ability relative to verbal ability, whereas individuals with high levels of positive schizotypy traits should have displayed lower non-verbal relative to verbal ability. While visual inspection of mean verbal and non-verbal scores for the O-LIFE:UE groups revealed a trend consistent with what would be expected based on Crespi and Badcock’s theory, none of the group differences was statistically significant. However, as we pointed out in our article, a study which offers a more complete assessment of this aspect of the theory is warranted. In particular, since the use of a student sample in our study no doubt led to a restriction in the range of IQ scores (especially with reference to verbal IQ), a test of community-based samples would be useful.
Therefore, while Crespi and Badcock’s (2008) theory has passed its first major test at the level of cognition, with our results indicating a contrasting effect of autistic-like and positive schizotypy traits with regard to preference for local versus global processing, further investigation of these authors’ theory at both the cognitive and genetic levels is required.
Almeida, R., Dickinson, J., Maybery, M., Badcock, J., Badcock, D. A new step toward understanding Embedded Figures Test performance in the autism spectrum: The radial frequency search task. Neuropsychologia. 2010 Jan;48(2):374-81. Abstract
Badcock, C. (2010). Diametric cognition passes its first lab test. Psychology Today. Retrieved February 8, from http://www.psychologytoday.com/blog/the-imprinted-brain/201002/diametric-cognition-passes-its-first-lab-test.
Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., Clubley, E. (2001). The Autism-Spectrum Quotient (AQ): Evidence from Asperger Syndrome/High-Functioning Autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31, 5-17. Abstract
Bolte, S., Holtmann, M., Poustka, F., Scheurich, A., Schmidt, L. (2007). Gestalt perception and local-global processing in High-Functioning Autism. Journal of Autism and Developmental Disorders, 37, 1493-1504. Abstract
Bolte, S., Poustka, F. (2006). The broader cognitive phenotype of autism in parents: How specific is the tendency for local processing and executive function. Journal of Child Psychology and Psychiatry, 47, 639-645. Abstract
Crespi, B., Badcock, C. (2008). Psychosis and autism as diametrical disorders of the social brain. Behavioral and Brain Sciences, 31, 241-261. Abstract
Grinter, E., Maybery, M., Van Beek, P., Pellicano, E., Badcock, J., Badcock, D. (2009). Global visual processing and self-rated autistic-like traits. Journal of Autism and Developmental Disorders, 39, 1278-1290. Abstract
Grinter, E., Van Beek, P., Maybery, M., Badcock, D. (2009). Brief Report: Visuospatial analysis and self-rated autistic-like traits. Journal of Autism and Developmental Disorders, 39, 670–677. Abstract
Mason, O., Linney, Y., Claridge, G. (2005). Short scales for measuring schizotypy. Schizophrenia Research, 78, 293-296. Abstract
Russell-Smith, S., Maybery, M., Bayliss, D. Are the autism and positive schizotypy spectra diametrically opposed in local versus global processing? Journal of Autism and Developmental Disorders. 2010 Jan 28. Abstract
Witkin, H., Oltman, P., Raskin, E., Karp, S. (1971). A manual for the Embedded Figures Test. Palo Alto, CA: Consulting Psychologists Press.
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Related News: Optogenetics Comes to the Rat Brain
Comment by: Bryan Roth, SRF Advisor
Submitted 16 December 2011
Posted 21 December 2011
I recommend the Primary Papers
This will be a valuable resource for those who use rats for neuropsychopharmacological research. Until now, the use of Cre-recombinase lines for expressing either optogenetic (Boyden et al., 2005) and pharmacogenetic (Armbruster et al., 2007) tools for modulating neuronal activity and signaling was limited to mice. Rats, of course, are superior to mice for many behavioral studies relevant to the pathogenesis and treatment of schizophrenia.
Now, Witten et al. (from the Deisseroth lab) provide rats which will allow for the Cre-mediated expression of a variety of genes. For this study, they utilized adeno-associated viral constructs, which allow for Cre-mediated expression of opsins (AAV-DIO; Tsai et al., 2009), although these rats should be useful for expression of nearly any protein.
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