I have blogged extensively about the Autism and Schizophrenia as opposites on a continuum theory. I remember first putting this theory in words in an article 3 yrs back on the mouse trap titled Autism and Schizophrenia: the two cultures. That 2006 article, in turn, was inspired by Daniel Nettle’s 2005 article in Journal of Research in Personality where Nettle had also proposed the dichotomy and that paper helped crystallize my thoughts on the subject, a theory which I had been building on my own and now supported by someone like Nettle who I respect a lot. Important to note that at that time I was blissfully unaware of Badcock or Crespi and their work. It is to the credit of Badcock that he had published in 2006 his own theory of Autism and Schizophrenia as opposites on a continuum based on parental imprinting of genes and proposed a mechanism. Crespi I guess got involved in Badcocks’s efforts later on and gave it more experimental and theoretic grounding. I firts became aware of Badcock and Crespi’s work in early 2008.
The wider world became aware of the Autism/Schizophrenia dichotomy sometime in late 2008 (November 2008) . at that time too, I was a little disappointed because most of the coverage did not mention Daniel Nettle, who I think should be credited for this work and line of reasoning too. As a consolation, some reports did mention Chris Frith who has also been partly supporting the thesis.
I wanted to give a historical perspective, because I am sure the recent Crespi article would be grabbed on by mainstream media and the pioneers Chris Frith/Nettle perhaps overlooked- but to me they too are heroes for having come up with such profound early insights. this is not to discredit teh work of Badcock and Crespi- they are doing a thorough job of convincing the skeptics and delineating the exact mechanism and genetics involved.
While we are on the topic of historical perspective , let me also pat myself on the back. In May 2008, a study came out that de novo Copy Number Variations’s (CNVs) were quite high in schizophrenics and they are in the same region as that for autistics who also have high CNVs in the same region. While some took that result to imply that Schizophrenia and Autism are same and are not different, I persisted and proposed a mechanism, whereby they could still be opposites : To quote:
Now as it happens previous research has also found that CNVs are also found to a higher extent in autistics. Moreover, research has indicated that the same chromosomal regions have CNVs in both Autism and Schizophrenia. To me this is exciting news. Probably the chromosomal region (neurexin related is one such region) commonly involved in both schizophrenia and autism is related to cognitive style, creativity and social thinking. Qualitatively (deletions as opposed to duplications) and quantitatively (more duplications) different type of CNVs may lead to differential eruption of either Schizophrenia or Autism as the same underlying neural circuit gets affected due to CNVs, though in a different qualitative and quantitative way.
Now one and half year later Crespi et al report the results of their study which has found exactly the same- that is, if deletions in some locus lead to autism, duplications lead to schizophrenia and vice versa. That to me is clinching evidence of my thesis. Who says Science does not happen on blogs- I proposed something to flow as a consequence of theory and exactly the same thing is found as per the hypothesis. I feel vindicated and emotional to some extent. Loves labor has not been lost to deaf ears.
Let us then return to the new and latest study that has sort of proven that Autism and Schizophrenia are opposites, genetically. Crespi et al, report in the latest PNAS edition that comparative genomics leads to that conclusion. What Crespi et al did was look at theCNV s and the locus whee CNV in both Autism and Schizophrenia are involved and sure enough they found the pattern I had proposed. I’ll now quote from the abstract and the article extensively:
We used data from studies of copy-number variants (CNVs), singlegene associations, growth-signaling pathways, and intermediate phenotypes associated with brain growth to evaluate four alternative hypotheses for the genomic and developmental relationships between autism and schizophrenia: (i) autism subsumed in schizophrenia, (ii) independence, (iii) diametric, and (iv) partialoverlap. Data from CNVs provides statistical support for the hypothesis that autism and schizophrenia are associated with reciprocal variants, such that at four loci, deletions predispose to one disorder, whereas duplications predispose to the other. Data from single-gene studies are inconsistent with a hypothesis based on independence, in that autism and schizophrenia share associated genes more often than expected by chance. However, differentiation between the partial overlap and diametric hypotheses using these data is precluded by limited overlap in the specific genetic markers analyzed in both autism and schizophrenia. Evidence from the effects of risk variants on growth-signaling pathways shows that autism-spectrum conditions tend to be associated with upregulation of pathways due to loss of function mutations in negative regulators, whereas schizophrenia is associated with reduced pathway activation. Finally, data from studies of head and brain size phenotypes indicate that autism is commonly associated with developmentally-enhanced brain growth, whereas schizophrenia is characterized, on average, by reduced brain growth.These convergent lines of evidence appear most compatible with the hypothesis that autism and schizophrenia represent diametric conditions with regard to their genomic underpinnings, neurodevelopmental bases, and phenotypic manifestations as reflecting under-development versus dysregulated over-development of the human social brain.
Copy Number Data. Rare copy-number variants (CNVs) at seven loci, 1q21.1, 15q13.3, 16p11.2, 16p13.1, 17p12, 22q11.21, and 22q13.3 (Tables S1 and S2), have been independently ascertained and associated with autism and schizophrenia in a sufficient number of microarray-based comparative genomic hybridization (aCGH) and SNP-based studies to allow statistical analysis of the frequencies of deletions versus duplications in these two conditions (Table 1, Tables S3–S9). For five of the loci (1q21.1, 16p11.2, 16p13.1, 22q11.21, and 22q13.3), specific risk variants have been statistically supported for both autism and schizophrenia using case-control comparisons, which allows direct evaluation of the alternative hypotheses in Fig. 1. One locus (16p13.1) supports a model of overlap, and four loci support the reciprocal model, such that deletions are associated with increased risk of autism and duplications with increased risk of schizophrenia (16p11.2, 22q13.3), or deletions are associated with increased risk of schizophrenia and duplications with increased risk of autism (1q21.1, 22q11.21). For 1q21.1 and 22q11.21, contingency table analyses also indicate highly significant differences in the frequencies of deletions compared with duplications for the two disorders, such that schizophrenia is differentially associated with deletions and autism with duplications. By contrast, for 16p11.2 and 22q13.3 such analyses show that autism is differentially associated with deletions and schizophrenia with duplications.
I cannot cut n paste the table, but a look at the table clears all doubts. They also look at gene association data and come to a similar conclusion ruling out model A (autism, subsumed in schizophrenia) or model B (autism and schizophrenia are independent of each other).
Models 1C (diametric) and 1D (overlapping) both predict broad overlap in risk genes between autism and schizophrenia, and do not necessarily predict an absence or paucity of genes affecting one condition but not the other. In theory, these models can be differentiated by using data on specific risk alleles for specific loci (such as single-nucleotide polymorphisms, haplotypes, or genotypes), which should be partially shared under the overlapping model but different under the diametric model. For the genes DAO, DISC1, GRIK2, GSTM1, and MTHFR, the same allele, genotype, or haplotype was associated with both autism and schizophrenia, and for the genes AHI1, APOE, DRD1, FOXP2, HLA-DRB1, and SHANK3, alternative alleles, genotypes, or haplotypes at the same loci appear to mediate risk of these two conditions (SI Text). For the other genes that have been associated with both conditions, heterogeneity in the genetic markers used, heterogeneity among results from multiple studies of the same genes, and the general lack of functional information preclude interpretation in terms of shared or alternative risk factors.
Models of autism as a subset of schizophrenia (Fig. 1A), and autism and schizophrenia as independent or separate (model 1B), can be rejected with some degree of confidence, but models involving diametric etiology (model 1C) or partial overlap (model 1D) cannot be clearly rejected. Taken together, most of the data and analyses described here appear to support the hypothesis of autism and schizophrenia as diametric conditions, based primarily on the findings that reciprocal variants at 1q21.1, 16p11.2, 22q11.21, and 22q13.3 represent statistically-supported, highly-penetrant risk factors for the two conditions (Table 1), and that for a number of genes, alternative alleles or haplotypes appear to mediate risk of autism versus schizophrenia.
Additional lines of evidence supporting the diametric hypothesis, from previous studies of autism and schizophrenia, include:
1. Data showing notable rarity of familial coaggregation of autism with schizophrenia (38), in contrast, for example, to strong patterns of co-occurance within pedigrees of schizophrenia, schizoaffective disorder, and bipolar disorder (39).
2. Psychiatric contrasts of Smith-Magenis syndrome with Potocki-Lupski syndrome (due to the reciprocal duplication at the Smith-Magenis locus), Williams syndrome with cases of Williams-syndrome region duplication, and Klinefelter syndrome with Turner syndrome, each of which tends to involve psychotic-affective spectrum phenotypes in the former syndrome, and autistic spectrum conditions in the latter (5, 40).
3. Effects of autism and schizophrenia risk alleles on common growth-signaling pathways, such that autism has been associated with loss of function in genes, such as FMR1, NF1, PTEN, TSC1, and TSC2 that act as negative regulators of the PI3K, Akt, mTOR, or other growth-signaling pathways (41–45), whereas schizophrenia tends to be associated with reduced function or activity of genes that up-regulate the PI3K, Akt, and other growth-related pathways (46–49).
4. Increased average head size, childhood brain volume, or cortical thickness in individuals with: (i) idiopathic autism (50–53), (ii) the autism-associated duplications at 1q21.1 (17) and 16p13.1 (32) and the autism-associated deletions at 6p11.2 (31), and (iii) autism due to loss of function (or haploinsufficiency) of FMR1 (54), NF1 (55), PTEN (56) and RNF135 (57). By contrast, reduced average values for brain size and cortical thickness, due to some combination of reduced growth and accelerated gray matter loss, have been demonstrated with notable consistency across studies of schizophrenia (58–62), and such reduced head or brain size has also been associated with the schizophrenia-linked CNVs at 1q21.1 and 22q11.21 (17, 63, 64), and with deletions of 16p13.1 (65).
I am more than pleased with these results. Badcock too is. You can read his comments here. What about you? What would it take to convince you? 🙂
Crespi, B., Stead, P., & Elliot, M. (2009). Evolution in Health and Medicine Sackler Colloquium: Comparative genomics of autism and schizophrenia Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.0906080106
Two main underlying deficits have been proposed in autism– one concerning an inactive or non-existent Theory of Mind module and another a tendency towards Weak Central Coherence. ToM defects reflect in the communicative, social and imaginative deficits seen in autistics; while the savant skills as well as restrictive and repetitive behavior (restricted repertoire of interests ;obsessive desire for sameness – islets of ability – idiot savant abilities – excellent rote memory – preoccupation with parts of objects ) are best explained by taking recourse to the Autism-as-a cognitive-style having weak Central Coherence argument. I’ve discussed the crucial aspects of both of these two dimensions in y series of posts on autism and psychosis and shown how they have to be seen on a continuum and more as deviation from the normal range with one end as autism and the other as psychosis. We also know that psychosis itself is two dimensional with one dimension being that of schizophrenic spectrum and the other the bipolar spectrum. Thus what I propose is that we start seeing Autism also as a two dimensional disorder with TOM defect subtype a mirror image of schizophrenia; while the Weak CC subtype a mirror image of bipolar or manic depressive phenotype. Here are autistic and psychotic features on these dimensions (from Autism, Happe, the autistic deficits and assets table):
ordering behavioural pictures (Baron-Cohen et al. 1986) vs ordering mentalistic pictures understanding “see” (Perner et al. 1989)
deception false photographs (Leekam & Perner 1991, Leslie & Thaiss 1992) vs. false beliefs recognising happiness and sadness (Baron-Cohen et al. 1993a)
recognizing surprise object occlusion (Baron-Cohen 1992) vs. information occlusion
literal expression (Happé 1993) vs. metaphorical expression
elicited structured play (Wetherby & Prutting 1984)vs. spontaneous pretend play
instrumental gestures (Attwood et al. 1988) vs. expressive gestures
talking about desires and emotions (Tager-Flusberg 1993) vs. talking about beliefs and ideas
using person as tool (Phillips 1993) vs. using person as receiver of information
showing “active” sociability (Frith et al. 1994) vs. showing “interactive” sociability
It is also pertinent in this regard to revisit the question of co-occurrence of autism and schizophrenia. Happe maintains that psychois can only be relaibly seen in Asperge’s group who might have a late developing ToMm ability. To quote:
The higher incidence of psychiatric disorders in this group (asperger’s group) (Tantam 1991, Szatmari et al. 1989b) is well explained by this hypothesis. Depression will be more common since these people have greater insight into their own difficulties and their own feelings and thoughts. Positive symptoms of psychosis, such as hallucinations and delusions would be found only in Asperger’s syndrome cases by this account, if one takes Frith & Frith’s (1991) view of these symptoms as resulting from an “over-active” theory of mind. Asperger’s syndrome people, who gain theory of mind late and therefore abnormally, may be at high risk for having their theory of mind “go wrong”. On this hypothesis it would be impossible for a Kanner-type autistic person (who has no theory of mind) to show these psychotic or positive symptoms. In this sense (according to Frith & Frith’s theory) Asperger’s syndrome would be something of a midpoint between autism and (positive or florid) schizophrenia; while the former is due to a lack of theory of mind, and the latter due to over-active theory of mind, some people with Asperger’s syndrome may show both the scars of early lack and the florid symptoms of late acquired theory of mind working abnormally hard.
There is some preliminary evidence to support the suggestion that the term “Asperger’s syndrome” could meaningfully be restricted to those subjects with autism who have achieved some ability to think about thoughts. Ozonoff et al. (1991) found that their group labelled (perhaps arguably) as having Asperger’s syndrome did not show impairments relative to controls.
It is interesting to note the ‘over-active’ theory of mind reference to Frith and Frith. I could not locate that paper but came across another paper by Abu-akkel that propose over-active ToM as a mechanism of psychosis. There are also some full textrelated articles available online that may be of interest to the serious reader. As for me, it is heartening to note that others concur with the theory of autism and psychosis as opposites on a continuum.
I serendipitously came cross this article today about how our brains are self-organized criticality or systems living on the edge of chaos. There are many interesting ideas and gold nuggets in that article, and I’ll briefly quote from it.
In reality, your brain operates on the edge of chaos. Though much of the time it runs in an orderly and stable way, every now and again it suddenly and unpredictably lurches into a blizzard of noise.
Neuroscientists have long suspected as much. Only recently, however, have they come up with proof that brains work this way. Now they are trying to work out why. Some believe that near-chaotic states may be crucial to memory, and could explain why some people are smarter than others.
In technical terms, systems on the edge of chaos are said to be in a state of “self-organised criticality”. These systems are right on the boundary between stable, orderly behaviour – such as a swinging pendulum – and the unpredictable world of chaos, as exemplified by turbulence.
The quintessential example of self-organised criticality is a growing sand pile. As grains build up, the pile grows in a predictable way until, suddenly and without warning, it hits a critical point and collapses. These “sand avalanches” occur spontaneously and are almost impossible to predict, so the system is said to be both critical and self-organising. Earthquakes, avalanches and wildfires are also thought to behave like this, with periods of stability followed by catastrophic periods of instability that rearrange the system into a new, temporarily stable state.
Self-organised criticality has another defining feature: even though individual sand avalanches are impossible to predict, their overall distribution is regular. The avalanches are “scale invariant”, which means that avalanches of all possible sizes occur. They also follow a “power law” distribution, which means bigger avalanches happen less often than smaller avalanches, according to a strict mathematical ratio. Earthquakes offer the best real-world example. Quakes of magnitude 5.0 on the Richter scale happen 10 times as often as quakes of magnitude 6.0, and 100 times as often as quakes of magnitude 7.0.
These are purely physical systems, but the brain has much in common with them. Networks of brain cells alternate between periods of calm and periods of instability – “avalanches” of electrical activity that cascade through the neurons. Like real avalanches, exactly how these cascades occur and the resulting state of the brain are unpredictable.
Two of the power laws that are found in human brains relate to the phase shift and phase lock periods of EEG/fMRI or human brain systems etc. As per this PLOS comp biology paper:
Self-organized criticality is an attractive model for human brain dynamics, but there has been little direct evidence for its existence in large-scale systems measured by neuroimaging. In general, critical systems are associated with fractal or power law scaling, long-range correlations in space and time, and rapid reconfiguration in response to external inputs. Here, we consider two measures of phase synchronization: the phase-lock interval, or duration of coupling between a pair of (neurophysiological) processes, and the lability of global synchronization of a (brain functional) network. Using computational simulations of two mechanistically distinct systems displaying complex dynamics, the Ising model and the Kuramoto model, we show that both synchronization metrics have power law probability distributions specifically when these systems are in a critical state. We then demonstrate power law scaling of both pairwise and global synchronization metrics in functional MRI and magnetoencephalographic data recorded from normal volunteers under resting conditions. These results strongly suggest that human brain functional systems exist in an endogenous state of dynamical criticality, characterized by a greater than random probability of both prolonged periods of phase-locking and occurrence of large rapid changes in the state of global synchronization, analogous to the neuronal “avalanches” previously described in cellular systems. Moreover, evidence for critical dynamics was identified consistently in neurophysiological systems operating at frequency intervals ranging from 0.05–0.11 to 62.5–125 Hz, confirming that criticality is a property of human brain functional network organization at all frequency intervals in the brain’s physiological bandwidth.
Further, as per research by Thatcher et al, the EEG phase shift is larger in people with high IQ, while phase lock is smaller in the people with high IQ.
Phase shift duration (40–90 ms) was positively related to intelligence (P < .00001) and the phase lock duration (100–800 ms) was negatively related to intelligence (P < .00001). Phase reset in short interelectrode distances (6 cm) was more highly correlated to I.Q. (P < .0001) than in long distances (> 12 cm).
Further, in this paper , thatcher eta look at autistics and conclude that the people with autism show some deficits in phase shift and phase lock.
Results: In both short (6 cm) and long (21 – 24 cm) inter-electrode distances phase shift duration in ASD subjects was significantly shorter in all frequency bands but especially in the alpha-1 frequency band (8 – 10 Hz) (P < .0001). Phase lock duration was significantly longer in the alpha-2 frequencyband (10 – 12 Hz) in ASD subjects (P < .0001). An anatomical gradient was present with the occipitalparietal regions the most significant. Conclusions: The findings in this study support the hypothesis that neural resource recruitment occurs in the lower frequency bands and especially the alpha-1 frequency band while neural resource allocation occurs in the alpha-2 frequency band. The results are consistent with a general GABA inhibitory neurotransmitter deficiency resulting in reduced number and/or strength of thalamo-cortical connections in autistic subjects
It is interesting that in the original new scientist article , thatcher speculates that the pattern in schizophrenia may be reverse of what is seen in autism (exactly my thoughts, though the confounding of low IQ with autism may explain his autism results to an extent):
He found that the length of time the children’s brains spent in both the stable phase-locked states and the unstable phase-shifting states correlated with their IQ scores. For example, phase shifts typically last 55 milliseconds, but an additional 1 millisecond seemed to add as many as 20 points to the child’s IQ. A shorter time in the stable phase-locked state also corresponded with greater intelligence – with a difference of 1 millisecond adding 4.6 IQ points to a child’s score (NeuroImage, vol 42, p 1639). Thatcher says this is because a longer phase shift allows the brain to recruit many more neurons for the problem at hand. “It’s like casting a net and capturing as many neurons as possible at any one time,” he says. The result is a greater overall processing power that contributes to higher intelligence. Hovering on the edge of chaos provides brains with their amazing capacity to process information and rapidly adapt to our ever-changing environment, but what happens if we stray either side of the boundary? The most obvious assumption would be that all of us are a short step away from mental illness. Meyer-Lindenberg suggests that schizophrenia may be caused by parts of the brain straying away from the critical point. However, for now that is purely speculative. Thatcher, meanwhile, has found that certain regions in the brains of people with autism spend less time than average in the unstable, phase-shifting states. These abnormalities reduce the capacity to process information and, suggestively, are found only in the regions associated with social behaviour. “These regions have shifted from chaos to more stable activity,” he says. The work might also help us understand epilepsy better: in an epileptic fit, the brain has a tendency to suddenly fire synchronously, and deviation from the critical point could explain this. “They say it’s a fine line between genius and madness,” says Liley. “Maybe we’re finally beginning to understand the wisdom of this statement.”
Thus, it seems Autism and Psychosis are just two ways in which self-organized criticality can cease to do what it was designed to do- live on the edge , without falling on either side of order or chaos.
I am sure many of you are already familiar with Nagel’s perennial question ‘what it is like to be a bat?‘ (see this one with some added commentary too). Today I propose to ask a slightly different question ‘what it is like to be a zombie‘? That may seem absurd at the outset, as in many people’s mind Zombies are synonymous with no consciousness. I beg to differ. As I have already indicated in my last post on major conscious and unconscious processes in the brain, there is an easy problem of A-consciousness and there is a hard problem of P-consciousness. I have already tried to breakup A-consciousness in its parts and I similarly think that P-consciousness is much more that qualia (qualia I envisage as more grounded in sensory or perceptive systems). So given the fact that most zombies are behaviorurally indistinguishable from normal humans, and given the fact that most people who argue for zombie models of humans (that ‘there is no one home to watch/direct the picture’) do still endow the zombie and themselves with the A-consciousness aspects – they do not deny that a representation is made and is consciously available for processing (the theater of consciousness) , it is reasonable to speculate that although lacking full P-consciousness, it would still be something like to feel like a zombie. Let me draw an analogy, in some dissociative disorders, one starts seeing the world as unreal (derealization) and the self as unreal (depersonalization) ; yet even though one believes oneself to be unreal there is still something it is like to exist in that ‘unreal’ state.
Similarly, though one may model oneself and others as zombies, still it would be something like it is to be in a state that thinks and believes that one is a zombie and also acts accordingly. I am making a leap here. I am assuming that awareness or modeling of ones A-conscious experiences leads to or affects one’s phenomenal consciousness. Thus, in my view , someone who models oneself and others as a zombie, would have a different sort of P-consciousness or what it feels-to-be-like, than a person who models oneself and others as sentient agents and his P-cosnsciousness would be of a different nature.
Now consider the problem we face when confronted with a world which is deterministic and chaotic at the same time, and which is inhabited by agents which seem to be unpredicatable and constrained at the same time. I have already indicated elsewhere, that people may form tow types of model- one is a statistical/ deterministic model that they may apply to the world; another is a probabilisitic/agentic model that they may apply to the self (as well as other sentient beings). If one keeps these domains of folk-physics and folk-psychology separate, all is hunky dory; all hell breaks lose (pun intended; zombies are correlated with dead apocalypse scenarios in popular culture) when one applies a deterministic model (that fits the world) to the self/others. Similarly all hell breaks loose, when one applies an agentic/indetrminsitc model (that fits the sefl/others) to the world.
For today, we will focus on the problem of modeling self, and leave the problem of modeling world for a later day. A self may act differently in many similar/same situations. If it acts the same on each occasion, given the same situation; we can easily say that the situation causes the action. This poses no problem for the zombie (I will refer to a zombie as a person whose self/other conceptualization is as that of oneself/others as machines), as one has a deterministic rule that defines the self- (given situation A-> action B), and thus one can keep one’s model of self as-a-deterministic-being consistent. On the other hand, if the situation A sometimes leads to action B, but at other times to action C, then one has to explain the variance in the behavioral output. Consider first the problem of explaining the variance between-subjects. Given the same situation A, subject Z acts in way B while the subject Y acts in way C. There is considerable variance. If one assumes all selves as created equal, then all should have behaved similarly. Either one has to grant an extraordinariness and uniqueness to all selves, or if one has a statistical and ordinary nature of human beings, one has to grant that the subject given the same situation, should have behaved identically. But we all see that there is considerable variance. This variance is individualistc and one may try to explain this between-subjects variance using subject’s personal history (prior conditioning: a behavioristic model; or repressed emotional experiences/memories: psychoanalytical theory), one may also look at subject’s common ancestral history and use that to explain behavior (genetic differences: evolutionary biology; cultural differences : anthropology ) or one may even look at his holistic experiences and use that individualistic experiential history as a basis for explaining behavior ( consider two identical twins that because of their different sampling of environment may end up as differently conditioned etc). Phew that covers all the major psychological theories that I could remember.
Now lets focus on the problem of explaining within-subjects variance ; given the fact that the Situation is the same (situation A) and the subject is the same (subject Z), why does the same subject react differently to the same situation (acts in ways B and C). This is a relatively hard problem. One could deny the problem itself and claim that no situation is identical, but hey we are doing armchair philosophy right now, and we have already agreed to the premise of existence of a same situation A when we discussed between-subjects variance above, so it doesn’t hurt to concede that the situation A can be same for subject Z, but he may still react differently in ways B and C. None of the above psychological approaches, if applied in a strict, causal deterministic sense can explain the same subject Z reacting differently to situation A , as the subject Z’s personal history (conditioning, repressed memories) or ancestral history (genes, cultural influences) or even previous experiences and choices remain the same and thus should ideally have led to the same behavior. I am making an assumption here that situation A is repeated twice or more in succession (closely in time) so that one cannot counter and say that conditioning (to take an example) has changed in meanwhile due to situation A itself and thus, as the subject Z (at time t=1) has changed to an extent (by delta effect of situation A on the ‘earlier’ subject Z at time t=0) , so he may react differently at tome t=1 from how he reacted at time t=0. What we are really doing is doing away with a term of the equation; we are saying subject Z is not constant (it keep changing- self as constantly changing- a Buddhist philosophical premise and also favored by many in psychology) , but in the spirit of Camus’s Absurdity argument in Myth of Sisyphus, I am not satisfied with doing away one of the variables of the equation itself, so let us see, where this model of self-as-a-deterministic-being leads us to. Now that subject Z remains the same for two iterations of situation A, how can one explain the variance that results in action B at one time and action C at the other. One can again try to dissolve the equation by claiming that there is no unified self in space (earlier argument was that there is no unified self in time- it is a constantly changing in time self) – that is we are not a single self , but made up of many different selves- some conscious, some unconscious etc. Different selves may compete with each other and whoever wins at the moment, directs the show. Again assuming different selves cohabiting the same person doesn’t really feel what-it-is like to-be-oneself , and apart from some multiple-personality disorder (DID) this has not been frequently reported; but more importantly . Granting multiple selves to subject Z again vanishes one of the terms of the equation, and I am not interested, I want to stay and see where my inquiry takes me to.
If the situation is same, the subject is same and a single one, than what explains the within-subject variance? One has to grant unpredictability to a self that was assumed to be deterministic to begin with. One can now take two routes, either resort to the magical mumbo-jumbo of quantum world and indeterminacy and uncertainty; or stay in the deterministic world but look at complex systems/ chaos theory etc to explain the apparent indeterminacy. I believe a zombie will prefer the second route and model the self as a complex-system/chaotic self. One could say that the self/ others are still completely determined, but due to an initial ‘butterfly flapping wings effect‘ the self seems or appears to be unpredictable and will continue to remain unpredicatble because of that ‘original sin’. The original sin may be how the infant took the first breath, whether he cried or laughed when born; what the time of conception was etc etc. Whatever may be the initial condition that escaped measuring, it leads to an unperdicatble self, a chaotic self that one cannot measure in the present and thus cannot predict in the long term- a self that is as fickle and as perdicatble as the waether.
There are important implications to seeing / modeling the self as a chaotic system. That leads to a diminished sense of agency / responsibility as perhaps there is not much one can do to correct the original sin and thus modify/ change ones long term behavior. This diminished p-consciousness of agency and the consequent differential experiences of sensations/ perceptions should also lead to diminished qualia or what-it-feels-to be-like feeling. Maybe the zombies do feel really like zombies- mechanical and chaotic- going along the life stream in a mechanical , predetermined manner- seeing all and understanding all, even acting and reacting, but feeling impotent and lifeless, perhaps just fulfilling a role which has been scripted by someone else (the initial butterfly flapping its wings or the original sin).
This is a good point to stop, but I would like to thank Melbren, a reader of this blog, who commented on my last post and asked me if I would re-define , give a new name to Autism spectrum disorders. Thta made me think and somehow led to this post. But first his comment:
Very cool post. And I love your blog. I am trying to think about this particular post in terms of your psychotic spectrum–most specifically as it relates to autism. But I am impeded by an overwhelming feeling that if we have a new spectrum–we’ll need new terms. The term “autism” has outgrown its usefulness, don’t you think?
For one thing–if we are to use the framework of a psychosis spectrum–I think there will be a lot of people currently diagnosed with autism who are, in fact, organically more biased toward the opposite end of the spectrum. However, such individuals may still have “stereotypies” that we have come to associate with the term “autism.”
That being said–if you were appointed “word czar of the day,” and, as such, had the authority to scrap all of our conventional terminology and come up with “new and improved” terms that are more in alignment with a psychosis spectrum–what new terms would you choose?
I conceptualize autism as defect whereby people falsely apply a deterministic model (relevant for the world/ non-living things) to the self/others (living things) ; I consider of psychosis as the reverse, whereby one applies an agentic model to the world, thus exhibiting magical thinking etc. Because psychotic spectrum is consptualised in terms of a disability (loss of contact with reality), I would rechristen autism spectrum as the zombie spectrum (loss of contact with agency); of course, If I indeed am the ‘word czar of the day’ I’ll probably rename both as consciousness-orientation (psychotic spectrum) and reality-orientation (autistic spectrum) and highlight the good aspects of both- shaministic Altered states of consciousness and creativity of schizotypals and the scientific and savantic abilities of the Aspergers. Of course, in a lighter vein, perhaps the autistic spectrum people are ‘muggles’ (believers in ordinariness ) who still have to come to terms with the ‘magic’ (believers in extraordinariness) of consciousness.
There is a recent article in Nature Neuroscience by Philpot et al regarding how experience-dependent synaptic plasticity is downregulated in Angelmans’ syndrome and perhaps in Autism too, as the Ube3a gene involved is implicated in both disorders.
First a little history about Angelman– it is a disorder caused by deletion/lack of a maternally imprinted UBE3a gene in chromosomal region 15q11-q13 . It is typically contrasted with Prader-Willi syndrome which is caused by a paternally imprinted gene malfunction in the same chromosomal region. Christopher Badcock has used this to contrast Autism (related to Angelman) and Psychosis (more common in PWS) to argue that Autism and Psychosis are due to a genomic imprinting tug of war between fathers and mothers genes.
I have written about Badcock’s and Crespi’s thesis before and how it fits in with my views on Autism and Psychosis; suffice it to say that I am seeing the new study primarily from this prism of Autism and Psychosis dichotomy.
First , let us see what the study tells us:
It uses mouse model that contains silenced maternal Ube3a genes (Ube3a m-p+ mouse), thus trying to make a mouse model of Angelman.
What it found was:
1) Ube3a expression was markedly reduced in Ube3am-/p+ mice compared with wild-type mice in all three brain regions (visual neocortex, hippocampus,cerebellam). Consistent with previous observations, this attenuation was brain specific, as Ube3a was highly expressed in the liver of both Ube3am+/p- and Ube3am-/p+ mice.
2) To determine the physiological consequences of Ube3a loss on neocortical development, we examined the developmental acquisition of spontaneous excitatory synaptic transmission by recording miniature excitatory postsynaptic currents (mEPSCs) in layer 2/3 pyramidal neurons of visual cortex (see Supplementary Table 1 online for intrinsic membrane properties of recorded neurons). Consistent with previous findings24, 25, mEPSC amplitudes decreased and frequency increased during development in wild-type mice . Just before eye opening (postnatal day 10, P10), mEPSC frequency and amplitude were indistinguishable between wild-type and Ube3am-/p+ mice . Thereafter, mEPSC frequency failed to develop normally in Ube3am-/p+ mice
3)Although dark rearing had no measurable effect on mEPSC amplitude in wild-type mice at P25 , sensory deprivation strongly attenuated the normal developmental increase in mEPSC frequency in wild-type mice . In contrast, dark rearing did not affect mEPSC amplitude or frequency in Ube3am-/p+ mice. Consequently, mEPSC frequency in normally reared Ube3am-/p+ mice was not significantly different from that of dark-reared wild-type mice . These findings demonstrate that, although Ube3a is not necessary for the initial sensory-independent establishment of synaptic connectivity, it is selectively required for experience-dependent maturation of excitatory circuits.
4)We therefore compared the properties of neocortical long-term depression (LTD) and LTP at layer 2/3 synapses in visual cortex of wild-type and Ube3am-/p+ mice at both young (P25) and adult (P100) ages. Because layer 2/3 pyramidal neurons receive major inputs from layer 4 pyramidal neurons, layer 2/3 field potentials were evoked by layer 4 stimulation . We began by measuring LTD in young mice using a standard stimulation protocol (1 Hz for 15 min). Although LTD was reliably induced in young wild-type mice, it was absent in young Ube3am-/p+ mice . We also observed deficits in LTP induction. A relatively weak induction protocol (three 1-s trains of 40-Hz stimulation) elicited LTP in young wild-type mice, but failed to reliably induce LTP in young Ube3am-/p+ mice . To test whether the neocortex of Ube3am-/p+ mice was capable of expressing LTP, we also applied a strong LTP stimulation protocol (two 1-s trains of 100-Hz stimulation). This protocol consistently induced LTP in both Ube3am-/p+ and wild-type mice. Thus, as with LTP deficits in hippocampus8, 9, the LTP induction machinery is impaired in the visual cortex of Ube3am-/p+ mice and this deficit in LTP can be overcome with strong stimulation.
5)To determine whether the plasticity deficits in Angelman syndrome mice persisted into adulthood, we tested LTD and LTP in adults (P100). In adult wild-type mice, LTD induced by 1-Hz stimulation was absent, as expected27, whereas LTP could be induced with strong stimulation. In adult Ube3am-/p+ mice, however, neither of these protocols were effective at modifying synaptic strength. These results indicate that wild-type mice show attenuated neocortical plasticity as they mature and that this attenuation of plasticity is more severe in the absence of Ube3a . Furthermore, these data indicate that plasticity defects in Angelman syndrome mice persist into adulthood.
..and so on (go read the full paper)
In a nutshell, what they found was that in presence of visual stimuli, the plasticity (measured by LTP/LTD ) of visual cortex was adversely affected. As sensory stimulus would normally be available while developing, this would adversely affect the plasticity in adolescence/ critical periods and also continue into adulthood.
Thus, Autism/ Angelman are charechterised by less synaptic plasticity in adulthood and during critical development periods. Paradoxically, this loss of synaptic plasticity is concomitant on their it being experience-dependent or having sensory stimuli. If the organism is sensory deprived, it may still retain the normal synaptic plasticity exhibited by similar sensory deprived normal people.
How does this relate to Psychosis? If my thesis is correct that autism and Psychosis are opposites, then I would predict that in either prader-willi or in Psychosis (scheziphrenia etc) there should be excessive experience-dependent plasticity. I was glad to learn that I am not the first one to make that proposition, but someone back in 1995 has argued for Hippocampal synaptic plasticity as an endophenotyoe for Episodic Psychosis. I now quote heavily form that article.
Here is the abstract:
Structural change in the hippocampal formation has become popular as a proposed neurobiological substrate for schizophrenic disorders. It is postulated that behavioral plasticity in the form of long-term potentiation of hippocampal synaptic transmission is an attractive putative mechanism for the mediation of transient psychosis. Moreover, the disturbed hippocampal neuroarchitecture found in schizophrenic brain may be susceptible to potentiation and dysfunctional to the degree that delusions and hallucinations develop. Partial and selective blockade of the receptors mediating potentiation may prove to be an efficient means of preventing psychotic episodes and avoiding further damage to the involved network. Basic research, utilizing experimental models such as intraventricular kainic acid injection, may help to clarify the anatomical and physiological substrate of psychosis.
The Main thesis of the paper is:
1. Anatomical, physiological, pharmacological, and behavioral findings are most consistent with the view that neuropathological changes within the limbic system, specifically within the hippocampal formation, may represent a biological substrate of schizophrenia.
2. The biological mechanism underlying transient psychosis may be long-term potentiation (LTP) of synaptic transmission within the hippocampal formation.
3. The effects of dopamine manipulation on these behaviors may be mediated by direct actions on the compromised limbic system of the psychotic patient.
Associative plasticity within hippocampus occurs in the form of long-term potentiation (LTP), an experience-dependent increase in synaptic efficacy. Experimentally, LTP is produced by tetanic stimulation of afferent systems (Bliss and Lomo 1973) and has been shown to facilitate simple associative learning (Berger 1984) but disrupt more complex forms of associative plasticity (Robinson et al 1989). Hippocampal LTP has been observed to occur as a consequence of stimulus pairings in classical conditioning (Weisz et al 1984) and appears to be mediated by N-methyl-Daspartate (NMDA) receptors (Harris et al 1984). Pharmacological blockade of NMDA receptors has been shown to disrupt learning and memory in a variety of forms, including simple associations (Stillwell and Robinson 1990), spatial learning (Morris et al 1986; Heale and Harley 1990; Shapiro and Caramanos 1990), conditioned fear (Miserendino et al 1990; Kim et al 1991), olfactory memory (Staubli et al 1989) and gustatory memory (Welzl et al 1990). Some evidence, however, suggests that deficits involve motor impairment as well as disrupted learning (Keith and Rudy 1990)
Hippocampal function is particularly sensitive to neurochemical modulation, and the expression of monoamine receptors in the temporal lobe is altered in schizophrenics (Joyce 1993). Antipsychotics that reduce endogenous dopamine levels (Losonczy et al 1987) exert significant effects on the hippocampus and LTP. Trifluoperazine inhibits induction of LTP in hippocampus (Finn et al 1980), whereas the dopamine antagonist domperidone has been shown to prevent the maintenance of LTP (Frey et al 1990). Long-term effects of antipsychotic drugs include functional supersensitivity of hippocampal pyramidal neurons (Bijak and Smialowski 1989). Thus, individuals with deranged hippocampal neuroarchitecture would be prone to cognitive dysfunction (including, perhaps, perceptual distortion and other schizophrenic symptoms), differentially susceptible to stress, and responsive to amelioration of symptoms via dopamine antagonism. It may be more than coincidence that the time lag between administration of antipsychotic medication (which results in near immediate decrement in dopamine levels) and the attenuation of psychotic symptoms weeks later (Kane 1987) is remarkably consistent with the time parameters of LTP decay (Douglas and Goddard 1975). Also, the selective disruption of “weak” associative responses by antipsychotic drugs (van der Heyden and Bradford 1988) is consistent with interactions between NMDA-receptor blockade and stimulation intensity on induction of LTP (Reed and Robinson 1991).
From the above, at least to me, it is clear that anti-psychotics may work by decreasing LTP/LTD that is enhanced in episodic psychosis. A propensity towards increased experience-dependent enhancement of synaptic palsticty may be at work here and paradoxically the same approach of sensory deprivation, as in Angelman/ Autism may work here too.
Here is the summary:
In summary, potentiation of hippocampal synaptic transmission may be the neurophysiological basis of episodic psychosis. (Post  has proposed a similar process in the amygdala as a useful model in understanding the progression of recurrent affective disorders.) More selective blockade of the NMDA receptor, which mediates LTP, may prove an effective means of attenuating positive symptoms and preventing further accrual of cellular damage in hippocampus.
In my own summation, I am convinced that we would find more synaptic plasticity in Psychotic people and that hyper-plasticity to hypo-plasticity is another dimension on which the autistics and psychotics differ and this again is a result of the genomic imprinting mediated tug-pf-war between the maternal and paternal genomes.
PORT, R., & SEYBOLD, K. (1995). Hippocampal synaptic plasticity as a biological substrate underlying episodic psychosis Biological Psychiatry, 37 (5), 318-324 DOI: 10.1016/0006-3223(94)00128-P Koji Yashiro, Thorfinn T Riday, Kathryn H Condon, Adam C Roberts, Danilo R Bernardo, Rohit Prakash, Richard J Weinberg, Michael D Ehlers & Benjamin D Philpot (2009). Ube3a is required for experience-dependent maturation of the neocortex Nature Neuroscience
I have been maintaining that Autism and Schizophrenia are opposites on a continuum and one dimension on which they differ is Agency , with autistics attributing too less agency to themselves (and others), while schizophrenics attributing too much agency to themselves (and others).
The case for people with ASD is fairly settled. They have deficits in theory Of Mind (ToM) and one mechanism by which this deficit seems to arise is via their attributing less agency to themselves as well as others.
For Schizophrenics too, it was speculated that they have problems with agency , but a clear illustration that they have an enhanced agency attribution device was not firmly established. This study, which dates back to 2003, in my opinion, establishes the fact that their is hyper-agency attribution (or hyper-self-menatlizing) in schizophrenics.
The study in question is one by Haggard et al , and it uses an experimental paradigm to illustrate that schizophrenics indeed have problems with self- agency attribution, and that too in the hypothesized direction.
Here is the abstract:
An abnormal sense of agency is among the most characteristic yet perplexing positive symptoms of schizophrenia. Schizophrenics may either attribute the consequences of their own actions to the intentions of others (delusions of influence), or may perceive themselves as causing events which they do not in fact control (megalomania).Previous reports have often described inaccurate agency judgments in schizophrenia, but have not identified the disordered neural mechanisms or psychological processes underlying these judgments.We report the perceived time of a voluntary action and its consequence in eight schizophrenic patients and matched controls.The patients showed an unusually strong binding effect between actions and consequences. Specifically, the temporal interval between action and consequence appeared shorter for patients than for controls. Patients may overassociate their actions with subsequent events, experiencing their actions as having unusual causal efficacy.Disorders of agency may reflect an underlying abnormality in the experience of voluntary action.
Now, let us pause and recollect that Chris Frith had postulated that the voluntary action mechanism in Scizophrenics is somewhat malformed and specifically there is a disconnect between intention attribution and voluntary action manifestation. He however had not clearly stated that there would be over-attribution of intention to voluntary actions. We all know that dopamine is associated with voluntary action (voluntary movements) and that baseline dopamine is in excess in schizophrenics. This paper ties things in together showing that excess dopamine secretion in basal ganglia and cortical areas may lead to greater biding between intentions and subsequent actions (consequences) and by this mechanism may lead to over-attribution of agency. Of course the paper doe snot establish this mechanism but just speculates on it as one of the possible mechanisms. It is also important to pause and note that schizophrenics have a jumping-to-conclusions bias and thus if an intention and action were more tightly bound (occurred in time in close proximity)_, then they are more likely to judge the two events to be related and the intention to cause the action.
Now let me get to the actual experiment. Haggard et al asked schizophrenics as well as matched controls to note subjective time (using Libets approach) when they decided to voluntarily press a computer key, and also subjective time when they first heard an auditory tone . The tone was presented 250 ms after their voluntary key press. As has been established earlier, and using controls in this experiment, people advance the key press in future (shift it towards future time from the exact time they actually pressed the key) so that subjectively the key press happens after some time form the objective key press and in the direction of the tone presentation. Thus, the effective subjective time between the key press and the tone is reduced. This binding between a voluntary action and its consequence , happens in normal individuals too, but in schizophrenics this happened significantly more in magnitude ans was dependent on two factors. first, like in normals , the voluntary key press was advanced in time towards the tone presentation, but this advance was significantly greater than in the case of controls. Secondly, the subjective auditory tone was sort of anticipated and shifted back in time towards the voluntary key press in schizophrenics. Thus, in schizophrenics, it seemed to them that the auditory tone had occurred prior to when it was actually presented. This lead to overall very significant reduction in subjective time experienced between the voluntary key press and the tone hearing, thus binding the two events strongly and leading to stronger agency inferred. to quantize the things a bit, in normal controls the voluntary key press was on the average occurring 26 ms from the actual key press, the auditory tone was heard 5 ms from the actual presentation and thus the subjective difference between the key press (intention) and tone (consequence) was 250-(26+5)= 239 ms. In schizophrenics, the key press was deemed to occur 60 ms after the actual key press, however most importantly the tone was not heard subjectively after its presentation, but was heard anticipatory 139 ms before its actual presentation, thus the actual perceived subjective time between the key press (intention) and the tone (consequence) was 250-60-139 = 51 ms only. Now , one can easily see, that if perceived subjective time between tow events is shortened in schizophrenia, then wont they end up falsely clubbing many coincidental things too together, because they seem to follow each other in close temporal proximity.
To appreciate the results, one needs to put these results in the broader context of what we know about agency in schizophrenics:
Previous laboratory studies have investigated agency using action attribution tasks. In these tasks, the patient is asked to perform an action, and is shown a visual image corresponding to that action, for example, a line drawn with a pen , a video of a hand making a manual posture , or a computerised image of a joystick moving. By introducing a mismatch between the performed action and the visual feedback, experimenters investigate the accuracy of attribution judgments. The subject has to attribute the viewed image either to an action he has just been instructed to make or to some other source. Interestingly, all these studies have found schizophrenics abnormally willing to attribute to themselves actions which in fact differ from the ones they performed. Thus, they are less sensitive than control subjects to spatial, temporal or kinematic mismatches between actions and visual feedback. The direction of these results points towards an excessive, rather than a reduced, sense of agency. Such results have been interpreted in the context of an internal forward model. Schizophrenic patients’ errors involve mostly over-attribution, implying a forward model with an unusually tolerant comparator.
Impaired judgement of agency can also be linked to the brain abnormalities underlying the disease. Agency involves forming a conscious mental association between one’s own intentional actions, and their consequences in the outside world. Thus, agency may be a conscious aspect of a more general system for instrumental or operant learning about environmental contingencies and rewards. Animal learning studies show that dopaminergic circuits, including the basal ganglia and medial forebrain are essential for associating actions with their effects, and for motivating behaviours. Brain imaging studies in man show that these same areas are active when a voluntary action produces a reward or other salient consequence . Moreover, these dopaminergic circuits are overactive in schizophrenia . Excessive dopaminergic activity might therefore explain abnormalities of conscious agency in schizophrenia, such as over-association between intentions and external events.
This is how they interpret their results:
More importantly, our schizophrenic patients seem to show an exaggerated version of the normal binding effect, or hyperbinding. These results could account for the findings of some action attribution experiments. Franck et al. asked patients and controls to move a joystick and then to observe their movements on a computer screen after a delay. The experimenters systematically varied the delay to investigate at what point the two groups ceased to accept the observed action as their own. Control subjects detected the temporal discrepancy between their action and the image with delays of around 100–150 ms. Schizophrenic subjects were much more tolerant, and accepted the viewed action as their own even for delays of 300 ms. Overall, the detection threshold for the relevant action was increased by about 150–200 ms for the patients compared to the controls. This value can be compared to the 180 ms difference between our patients and controls in the implied perceptual duration of the interval between action and tone.
The direction of the attribution effect is important: schizophrenics over-attributed events to their own agency. Our data suggests that schizophrenic patients have unusually strong associations between conscious representations of action and consequence. Thus, they might bind action and viewed image across the substantial delay periods imposed in the Franck et al. experiment, and be unaware of the artificially-induced lag between these events. There may be a critical period in which to perceive the consequence of an action. Actions and events falling in this period may be perceptually bound. A deficit in setting the duration of this critical period in schizophrenics could contribute to the shifts we found in their subjective temporal experience. This view would interpret abnormal conscious experience in schizophrenia as a problem in predicting the consequences of one’s own actions. Further work could investigate whether temporal analysis in schizophrenic patients is defective only when concerning their own actions, or also when observing actions made by others.
I am thrilled as usual and predict that if the same experimental paradigm is used with Autistic, then they will show very little or no forward movement of subjective time between their actual voluntary key-press and the subjective feel of when they decided to press the key. Also, there would be no anticipatory backwards movement of subjective time for when the tone was heard. Thus, Autistic would perceive the time gap as 250 ms only, or may even perceive the time to be more than 250 ms depending ion whether they move the voluntary key press subjective time back in time. No matter what they should show lesser binding between the intention (if they can form one) and consequence. Haggard P, Martin F, Taylor-Clarke M, Jeannerod M, Franck N. (2003). Awareness of action in schizophrenia Neuroreport, 14 (7), 1081-1085
This blog post has been triggered by a recent news article that found that the default network in schizophrenics was both hyperactive and hyperconnected during rest, and it remained so as they performed demanding cognitive tasks. To quote:
The researchers were especially interested in the default system, a network of brain regions whose activity is suppressed when people perform demanding mental tasks. This network includes the medial prefrontal cortex and the posterior cingulate cortex, regions that are associated with self-reflection and autobiographical memories and which become connected into a synchronously active network when the mind is allowed to wander.
Whitfield-Gabrieli found that in the schizophrenia patients, the default system was both hyperactive and hyperconnected during rest, and it remained so as they performed the memory tasks. In other words, the patients were less able than healthy control subjects to suppress the activity of this network during the task. Interestingly, the less the suppression and the greater the connectivity, the worse they performed on the hard memory task, and the more severe their clinical symptoms.
“We think this may reflect an inability of people with schizophrenia to direct mental resources away from internal thoughts and feelings and toward the external world in order to perform difficult tasks,” Whitfield-Gabrieli explained.
The hyperactive default system could also help to explain hallucinations and paranoia by making neutral external stimuli seem inappropriately self-relevant. For instance, if brain regions whose activity normally signifies self-focus are active while listening to a voice on television, the person may perceive that the voice is speaking directly to them.
The default system is also overactive, though to a lesser extent, in first-degree relatives of schizophrenia patients who did not themselves have the disease. This suggests that overactivation of the default system may be linked to the genetic cause of the disease rather than its consequences.
The study on which this report is based , is supposedly published in advanced online PNAS edition of 19 jan, but I am unable to locate it. However, my readers know my obsession with Autism and Schizophrenia as diametrically opposed disorders theory and so I was seen reading all the other relevant studies related to default Network and especially how it may be differentially and oppositely activated in Autism and Schizophrenia.
First I would like to refer you to an extremely good overview of Default Network by Buckner, Schacter et al which is freely available. I’ll now present some quotes from the paper that are relevant to my thesis. I start with the abstract:
Thirty years of brain imaging research has converged to define the brain’s default network—a novel and only recently appreciated brain system that participates in internal modes of cognition. Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment. Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system. Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others. Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems. The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation. The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations. These two subsystems converge on important nodes of integration including the posterior cingulate cortex. The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world. We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer’s disease.
Some snippets from the introduction:
A common observation in brain imaging research is that a specific set of brain regions—referred to as the default network—is engaged when individuals are left to think to themselves undisturbed . Probing this phenomenon further reveals that other kinds of situations, beyond freethinking, engage the default network. For example, remembering the past, envisioning future events, and considering the thoughts and perspectives of other people all activate multiple regions within the default network . These observations prompt one to ask such questions as: What do these tasks and spontaneous cognition share in common? and what is the significance of this network to adaptive function? The default network is also disrupted in autism, schizophrenia, and Alzheimer’s disease, further encouraging one to consider how the functions of the default network might be important to understanding diseases of the mind. (emphasis mine)
Then they review some history including how default brain activity was recognized when it was found that metabolic demands and blood glucose consumption of brain as a whole remained the same even when the brain was at ‘rest’ viv-a-vis involved in an active task. They also review how when baseline PET/fMRI rest activity was compared to many disparate tasks related fMRI/ PET activity , then while some task-relevant areas showed activations related to baseline, many correlated areas of brain, the default network, showed deactivation in the task-related conditions as compared to baseline. The modern interpretation is that the default network is active at rest and places metabolic demands on the brain. They then reference the seminal work of Rachile et al and how that made the default network as a study area in itself.
They further elaborate on how the default network may be identified as an interconnected and functional brain system and list various approaches like spontaneous correlations at rest, seeding from a RoI and determining the areas correlated to activity in seed region etc, to determine the components of the default network. While dMPFC and PCC are implicated in all analysis, the case for vMPFC, IPL, HF+ and LTC is also strong.
I’ll skip most of this stuff , including comparative analysis. Suffice it to note here that the default brain regions are up to 30% more metabolically demanding then the rest of the brain and are recently evolved/ selected for. this becomes significant in view of recent studies showing that schizophrenia may be a result of selection for metabolism related genes.
The interesting part begins when trying to determine the behavioral/cognitive correlates of this default brain activity. The consensus seems to be that it is used for daydreaming, reconstructing the past, simulating the future, taking other peoples perspective, self-referential processes and in general stimulus independent thought.
A shared human experience is our active internal mental life. Left without an immediate task that demands full attention, our minds wander jumping from one passing thought to next—what William James (1890) called the “stream of consciousness.” We muse about past happenings, envision possible future events, and lapse into ideations about worlds that are far from our immediate surroundings. In lay terms, these are the mental processes that make up fantasy, imagination, daydreams, and thought. A central issue for our present purposes is to understand to what degree, if any, the default network mediates these forms of spontaneous cognition. The observation that the default network is most active during passive cognitive states, when thought is directed toward internal channels, encourages serious consideration of the possibility that the default network is the core brain system associated with spontaneous cognition, and further that people have a strong tendency to engage the default network during moments when they are not otherwise occupied by external tasks.
Support for the same is then provided. The next task the authors undertake is that of determining the function, usefulness and evolutionary rationale for this default brain activity. Two ,in my opinion not mutually exclusive, theories are offered. One is simulation of something that is not tied to current reality (whether it be past memories, future expectations and scenarios or other peoples intentions, beliefs, perspectives). The other theory is that the default mode is a diffused attentional/ exploration state and is suppressed by foveal attention/task focus. The over activity of default network in Schizophrenia can be related to both theories equally well.
In this section, we explore two possible functions of the network, while recognizing that it is too soon to rule out various alternatives. One possibility is that the default network directly supports internal mentation that is largely detached from the external world. Within this possibility, the default network plays a role in constructing dynamic mental simulations based on personal past experiences such as used during remembering, thinking about the future, and generally when imagining alternative perspectives and scenarios to the present. This possibility is consistent with a growing number of studies that activate components of the default network during diverse forms of self-relevant mentalizing as well as with the anatomic observation that the default network is coupled to memory systems and not sensory systems. Another possibility is that the default network functions to support exploratory monitoring of the external environment when focused attention is relaxed. This alternative possibility is consistent with more traditional ideas of posterior parietal function but does not explain other aspects of the data such as the default network’s association with memory structures. It is important to recognize that the correlational nature of available data makes it difficult to differentiate between possibilities, especially because focus on internal channels of thought is almost always correlated with a change in external attention . We also explore in this section an intriguing functional property of the default network: the default network operates in opposition to other brain systems that are used for focused external attention and sensory processing. When the default network is most active, the external attention system is attenuated and vice versa.
To me both the Sentinel and the Internal Mentation hypothesis appear to be somewhat valid and relevant to Schizophrenia. One can attribute Psychosis to both increased ‘watchfulness’ and and increased internal mentation or mentalizing and I have written about the second hypothesis in detail previously.
The most relevant part of the paper is their discussion of Autism, Schizophrenia and Alzheimer’s. I reproduce the entire autism and Schizophrenia section , highlighting a few points:
Autism Spectrum Disorders
The autism spectrum disorders (ASD) are developmental disorders characterized by impaired social interactions and communication. Symptoms emerge by early childhood and include stereotyped (repetitive) behaviors. Baron-Cohen and colleagues (1985) proposed that a core deficit in many children with ASD is the failure to represent the mental states of others, as needed to solve theory-of-mind tasks. Based on an extensive review of the functional anatomy that supports theory-of-mind and social interaction skills, Mundy (2003) proposed that the MPFC may be central for understanding the disturbances in ASD. Given the convergent evidence presented here that suggests the default network contributes to such functions, it is natural to explore whether the default network is disrupted in ASD.
Developmental disruption of the default network, in particular disruption linked to the MPFC, might result in a mind that is environmentally focused and absent a conception of other people’s thoughts. The inability to interact with others in social contexts would be an expected behavioral consequence. It is important to also note that such disruptions, if identified, may not be linked to the originating developmental events that cause ASD but rather reflect a developmental endpoint. That is, dysfunction of the default network and associated symptoms may emerge as an indirect consequence of early developmental events that begin outside the network.
Many studies have explored whether ASD is associated with morphological differences in brain structure. The general conclusion from this literature is that the brain changes are complex, reflecting differences in growth rates and attenuation of growth (see Brambilla et al. 2003 for review). At certain developmental stages these differences are manifest as overgrowth and at later stages as undergrowth. Early observations have implicated the cerebellum. A further consistent observation has been that the amygdala is increased in volume in children with ASD (e.g., Abell et al. 1999, Schumann et al. 2004), perhaps as a reflection of abnormal regulation of brain growth (Courchesne et al. 2001). While not discussed earlier because of our focus on cortical regions, the amygdala is known to contribute to social cognition (Brothers 1990, Adolphs 2001, Phelps 2006) and interacts with regions within the default network. The amygdala has extensive projections to orbital frontal cortex (OFC) and vMPFC (Carmichael & Price 1995).
Of perhaps more direct relevance to the default network, dMPFC has shown volume reduction in several studies of ASD that used survey methods to explore regional differences in brain volume (Abell et al. 1999, McAlonan et al. 2005). The effects are subtle and will require further exploration, but it is noteworthy that, of those studies that have looked, several have noted dMPFC volume reductions in ASD. Of interest, a study using voxel-based morphometry to investigate grey matter differences in male adolescents with ASD noted that several regions within the default network exhibited a relative increase in grey matter volume compared to the control population (Waiter et al. 2004). Because this observation has generally not been replicated in adult ASD groups, future studies should investigate whether complex patterns of overgrowth and undergrowth of the regions within the default network exist in ASD and, if so, whether they track behavioral improvement on tests of social function (see also Carper & Courchesne 2005).
Kennedy and colleagues (2006) recently used fMRI to directly explore the functional integrity of the default network in ASD. In their study, young adults with ASD and age-matched individuals without ASD were imaged during passive tasks and demanding active tasks that elicit strong activity differences in the default network. While the control participants showed the typical pattern of activity in the default network during the passive tasks, such activity was absent in the individuals with ASD. Direct comparison between the groups revealed differences in vMPFC and PCC. Moreover, in an exploratory analysis of individual differences within the ASD group, those individuals with the greatest social impairment (measured using a standardized diagnostic inventory) were those with the most atypical vMPFC activity levels (Fig. 16). An intriguing possibility suggested by the authors of the study and extended by Iacoboni (2006) is that the failure to modulate the default network in ASD is driven by differential cognitive mentation during rest, specifically a lack of self-referential processing.
Another recent study using analysis of intrinsic functional correlations showed that the default network correlations were weaker in ASD (Cherkassky et al. 2006).Of note, the individuals with ASD showed differences in a fronto-parietal network that has been recently hypothesized to control interactions between the default network and brain systems linked to external attention (Vincent et al. 2007b). These data in ASD suggest an interesting possibility: the default network may be largely intact in ASD but under utilized perhaps because of a dysfunction in control systems that regulate its use.
Schizophrenia is a mental illness characterized by altered perceptions of reality. Auditory hallucinations, paranoid and bizarre delusions, and disorganized speech are common positive clinical symptoms (Liddle 1987). Cognitive tests also reveal negative symptoms, including impaired memory and attention (Kuperberg & Heckers 2000). These symptoms lead to questions about their relationship to the default network for a few reasons. The first reason surrounds the association of the default network with internal mentation. Many symptoms of schizophrenia stem from misattributions of thought and therefore raise the question of an association with the default network because of its functional connection with mental simulation. A second related reason has to do with the broader context of control of the default network. While still poorly understood, there appears to be dynamic competition between the default network and brain systems supporting focused external attention (Fransson 2005, Fox et al. 2005, Golland et al. 2007, Tian et al. 2007, see also Williamson 2007). Frontal-parietal systems are candidates for controlling these interactions (Vincent et al. 2007b). The complex symptoms of schizophrenia could arise from a disruption in this control system resulting in an overactive (or inappropriately active) default network. The normally strongly defined boundary between perceptions arising from imagined scenarios and those from the external world might become blurry, including the boundary between self and other (similar to that proposed by Frith 1996).
Three studies have provided preliminary data supporting the possibility that the default network is functionally overactive. Garrity and colleagues (2007) recently reported an analysis of correlations among default network regions in patients with schizophrenia. Studying a sizable data sample (21 patients and 22 controls), they explored task-associated activity modulations within the default network and identified largely similar correlations among default network regions in patients and controls. Differences were noted in specific subregions, as were differences in the dynamics of activity as measured from the timecourses of the fMRI signal. Of particular interest, they noted that within the patient group, the positive symptoms of the disease (e.g., hallucinations, delusions, and thought confusions) were correlated with increased default network activity during the passive epochs, including MPFC and PCC/Rsp. In a related analysis, Harrison et al. (2007) noted accentuated default network activity during passive task epochs in patients with schizophrenia as contrasted to controls, again suggesting an overactive default network. Moreover, within the patient group, poor performance was again correlated with MPFC activation during the passive as compared to the active tasks. Finally, Zhou and colleagues (2007) found that regions constituting the default network were functionally correlated with each other to a significantly higher degree in patients than in control participants. Thus, while the data are limited, these studies converge to suggest that patients with schizophrenia have an overactive default network, as would be expected if the boundary between imagination and reality were disrupted. Overactivity within the network correlates with task performance (Harrison et al. 2007) and clinical symptoms (Garrity et al. 2007).
Several regions of the brain (including medial prefrontal cortex, rostral anterior cingulate, posterior cingulate, and precuneus) are known to have high metabolic activity during rest, which is suppressed during cognitively demanding tasks. With functional magnetic resonance imaging (fMRI), this suppression of activity is observed as “deactivations,” which are thought to be indicative of an interruption of the mental activity that persists during rest. Thus, measuring deactivation provides a means by which rest-associated functional activity can be quantitatively examined. Applying this approach to autism, we found that the autism group failed to demonstrate this deactivation effect. Furthermore, there was a strong correlation between a clinical measure of social impairment and functional activity within the ventral medial prefrontal cortex. We speculate that the lack of deactivation in the autism group is indicative of abnormal internally directed processes at rest, which may be an important contribution to the social and emotional deficits of autism.
In their discussion they make explicit the fact that in Autism, the default Netwrok may be under active.
There are two possible reasons why the ASD group failed to show the typical deactivation effect. One possibility is that midline resting network activity during both rest and task performance is high, and, thus, a subtraction between these conditions would reveal no difference in activity levels. We believe, however, that it is unlikely that high midline network activity was maintained during the cognitively demanding number task in autism for several reasons. First, as mentioned previously, behavioral performance was similar between control and ASD groups. This result, however, would be unexpected if the ASD group were carrying out additional mental processing that control subjects inhibit during cognitively demanding conditions. Second, positron-emission tomography studies of autism, which provide an absolute measure of brain metabolism, have found reduced, as opposed to increased, glucose metabolism in rACC and PCC (36) during task performance, as compared with controls. Furthermore, one positron-emission tomography study found that lower blood flow in MPFC and rACC at rest was correlated with more severe social and communicative impairments in subjects with autism (37), a finding similar to our correlational results. Third, reduced anatomical volumes and neurochemical deficiencies have consistently been observed in MPFC?rACC in adults with autism (reviewed in ref. 26), likely indicative of a reduced functioning of these regions. Therefore, an alternative explanation, the one to which we attribute the lack of deactivation, is that midline activity is low during rest. We suggest, then, that the absence of deactivation in this network indicates that the mental processes that normally occur at rest are absent or abnormal in autism.
What are these mental processes that dominate during rest? Evidence in the literature to date seems to suggest that tasks that induce certain types of internal processing activate this resting network. Examples of such tasks are self- and other-person judgments (4, 6, 7, 19–22, 38–45), person familiarity judgments (24, 25), emotion processing (15–17, 46), perspective-taking (22, 47), passive observation of social interactions vs. nonsocial interactions (18), relaxation based on interoceptive biofeedback (48, 49), conceptual judgments (based on internal knowledge stores) vs. perceptual judgments (50), and episodic memory tasks (51), among others [moral decision making (52), joint attention experience (23), and pleasantness judgments (53)]. Therefore, the activity in these regions at rest might simply reflect the extent to which these types of internally directed thoughts are engaged at rest. In fact, a particularly intriguing behavioral study found that individuals with ASD report very different internal thoughts than control subjects (54, 55), lending support to our interpretation that an absence of this resting activity in autism may be directly related to abnormal internal thought. Admittedly, this is a speculative hypothesis but one that can be explicitly tested.
Recent studies of autism have identified functional abnormalities of the default network during a passive resting state. Since the default network is also typically engaged during social, emotional and introspective processing, dysfunction of this network may underlie some of the difficulties individuals with autism exhibit in these broad domains. In the present experiment, we attempted to further delineate the nature of default network abnormality in autism using experimentally constrained social and introspective tasks. Thirteen autism and 12 control participants were scanned while making true/false judgments for various statements about themselves (SELF condition) or a close other person (OTHER), and pertaining to either psychological personality traits (INTERNAL) or observable characteristics and behaviors (EXTERNAL). In the ventral medial prefrontal cortex/ventral anterior cingulate cortex, activity was reduced in the autism group across all judgment conditions and also during a resting condition, suggestive of task-independent dysfunction of this region. In other default network regions, overall levels of activity were not different between groups. Furthermore, in several of these regions, we found group by condition interactions only for INTERNAL/EXTERNAL judgments, and not SELF/OTHER judgments, suggestive of task-specific dysfunction. Overall, these results provide a more detailed view of default network functionality and abnormality in autism.
If you want to read more about Schizophrenia – default network linkage , read here. If you want to read about Default Network in general , read here ( a very good blog I have recently discovered).
I think the case is settled that at least in the case of Default Network activations, Schizophrenia and Autism are on opposite poles. One has too much default brain activity, the other too little. Also, the function of default network suggests that it is primarily the focus on self and the ability to imagine that is disrupted in autism and heightend to dramatic effects in Schizophrenics.
R. L. BUCKNER, J. R. ANDREWS-HANNA, D. L. SCHACTER (2008). The Brain’s Default Network: Anatomy, Function, and Relevance to Disease Annals of the New York Academy of Sciences, 1124 (1), 1-38 DOI: 10.1196/annals.1440.011 D. P. Kennedy, E. Courchesne (2008). Functional abnormalities of the default network during self- and other-reflection in autism Social Cognitive and Affective Neuroscience, 3 (2), 177-190 DOI: 10.1093/scan/nsn011 D. P. Kennedy (2006). Failing to deactivate: Resting functional abnormalities in autism Proceedings of the National Academy of Sciences, 103 (21), 8275-8280 DOI: 10.1073/pnas.0600674103
Edouard Machery at the Experiments in Philosophy blog writes about a study he conducted with Zalla that found that people with Aspergers syndrome were deficient when it came to identifying purely instrumental desires and the actions resulting from them as intentional actions. but to understand all that we have to understand the concept of purely instrumental desire. This is best done with the free-cup and extra-dollar cases that Machery has constructed to illustrate this phenomenon:
The Free-Cup Case
Joe was feeling quite dehydrated, so he stopped by the local smoothie shop to buy the largest sized drink available. Before ordering, the cashier told him that if he bought a Mega-Sized Smoothie he would get it in a special commemorative cup. Joe replied, ‘I don’t care about a commemorative cup, I just want the biggest smoothie you have.’ Sure enough, Joe received the Mega-Sized Smoothie in a commemorative cup. Did Joe intentionally obtain the commemorative cup?
The Extra-Dollar Case
Joe was feeling quite dehydrated, so he stopped by the local smoothie shop to buy the largest sized drink available. Before ordering, the cashier told him that the Mega-Sized Smoothies were now one dollar more than they used to be. Joe replied, ‘I don’t care if I have to pay one dollar more, I just want the biggest smoothie you have.’ Sure enough, Joe received the Mega-Sized Smoothie and paid one dollar more for it. Did Joe intentionally pay one dollar more?
You surely think that paying an extra dollar was intentional, while getting the commemorative cup was not. So do most people.
Machery likes to analyze the different actions involved in getting a smoothie in terms of their causal structure as well as their valence for the subject (positive valence means actively desired; while negatively or neutrally valanced meaning that one would not like that action to take place normally, but might indulge in if it is instrumental and an intermediate step towards archiving of an ultimate desire.
Thus, in the extra dollar case quenching thirst is the ultimate desire, buying a smoothie an instrumental desire, while shelling an extra dollar though negatively valued is still a purely instrumental desire as it is requisite for fulfilling the ultimate desire. Thus, normal people would consider paying the extra-dollar as intentional as it was due to an action due to a (purely) instrumental desire.
In the free-cup case, again the ultimate desire is to quench the thirst, the instrumental desire is to buy a smoothie, and the free cup that one gets is neither desired ultimately or as (purely) instrumentally as a menas towards an end. In simple words it is not desired at all and I would like to name it as co-incidental desire as opposed to instrumental desire (because having a special edition cup may still have some valence for joe, though he doesn’t actively desire it. Normal as well as Aspergers people deemed getting the free cup as non-intentional.
Where the Aspergics differed was in the extra dollar case. They still thought that paying the extra dollar was non-intentional and Eduoard theorizes that this may be due to inability of those with ASD to consider acts which are merely means towards an end as having an intentional quality.
I might not agree with the specific theorizing of Machery, but I agree that people with ASD have deficits in intentionality and I have been shouting this from rooftops for quite some time now. I also assert that Schizophrenics have too much concept of intentionality. I would not be surprised if a schizotypal, schizophrenic population was given these above two scenarios and it was found that a co-incidental desire like getting a free-cup was also deemed to be an intentional actions. One could come up with strange rationalizations and explanations and believe that though he just wanted to quench his thirst he went to this vendor only because he also wanted a free cup. This would be an extreme case of Magical Thinking, but I wont be surprised to see schizophrenics attributing more intentionality than is done by normal people. I hope someone does the experiment and lets me know! Edouard are you listening?
EDOUARD MACHERY (2008). The Folk Concept of Intentional Action: Philosophical and Experimental Issues Mind & Language, 23 (2), 165-189 DOI: 10.1111/j.1468-0017.2007.00336.x
This edition of Edge features an article by Christopher Badcock, about the imprinted gene theory of Autism Spectrum disorders and the psychotic spectrum disorders that he has been developing with Crespi. It is a must read and has been very nicely done.
He goes on to list the differences between autism and psychosis in a tabular form and then extends this to list the differences between mentalistic and mechansitic cognitions.
delusions of being watched/spied on
apparent deafness/insensitivity to voices
hallucination of and hyper-sensitivity to voices
deficits in interpreting others’ intentions
erotomania/delusions of persecution
deficits in appreciating shared-attention/groups
delusions of conspiracy
theory of mind deficits
magical ideation/delusions of reference
deficit in sense of personal agency/episodic memory
megalomania/delusions of grandeur
literalness/inability to deceive
psychological interaction with self and others
physical interaction with nature and objects
uses social, psychological, and political skills
uses mechanical, spatial, and engineering skills
deficits in autism, augmented in women
accentuated in autism, augmented in men
voluntaristic, subjective, particularistic
deterministic, objective, universal
abstract, general, ambivalent
concrete, specific, single-minded
verbal, metaphoric, conformist
visual, literal, eccentric
top-down, holistic, centrally-coherent
bottom-up, reductionistic, field-independent
epitomized in literature, politics, and religion
epitomized in science, engineering, and technology
‘pseudo-science’: astrology, alchemy, creationism
‘hard science’: astronomy, chemistry, Darwinism
nurtured: culturally- and personally-determined
natural: factually- and genetically-determined
belief-based therapies: placebos, faith-healing, psychotherapy etc.
physical effect-based therapies: drugs, surgery, physiotherapy, etc.
He lists down some of the other arguments that I have made viz the fact that Valproic acid exposure in childhood/ pregnancy causes Autism, while valproic acid is used for treating psychosis. Overall it is a very interesting read and a must read.
He also tries to address the mCDD (or simultaneous occurence of Autism and Schizophrenia) in his article, though I find that part the least convincing. Here is what he has to say:
The model appears to rule out anyone suffering from an ASD and a PSD simultaneously, and such co-morbidity does appear to be rare—but is not unknown. However, I know of cases of individuals diagnosed with bipolar disorder who also show unmistakable signs of ASD during their non-manic phases. Indeed, I have research on one individual who suffers from severe gaze-aversion, autistic deficits in a sense of self and social anxiety most of the time, but who becomes comfortable with other people during manic episodes when his sense of self hypertrophies into megalomania with the feeling that he is the returned Jesus Christ! Furthermore, there is evidence of both ASD and PSD in Newton and Beethoven, and incontrovertibly so in the Nobel-prize winning mathematician John Nash. Here the theory predicts that the ASD must come first (typically in childhood) and leave a permanent savant-like basis later built on by hyper-mentalistic tendencies to produce an unusually broadened and dynamically-balanced cognitive configuration: that of true genius.
I find this fascinating and agree with Badcock that the theory leads to many predictions and all these are testable; so we are witnessing a new paradigmatic shift in our understanding of these neurodevelopmental disorders and further experiments would definitely lend more credence to this theory in my view.
Socrates has raised an important point in one of the recent comments that if Autism and Schizophrenia are opposite poles , how do you explain their (rare) simultaneous co-occurrence? This same question has been raised by other commentators (like Julia) before and though I have responded in the comments, I’ll like to highlight the earlier response here for the benefit of all readers. Here is one of my earlier responses to the prevalance of mCDD and I hope to stimulate some discussion on this:
One way to look at this (mCDD) would be to treat this as similar to mixed episodes in bipolar disorder. Here both symptoms of Mania and depression are present in the same individual though traditionally Mania and depression are thought of as opposite poles on a continuum. In effect though Autism and Schizophrenia/psychosis are opposite extremes, in some individuals both may be present. However, also note the differences form mixed episodes in bipolar; there the mixed state as well as mania and depression happen in the same individual over time; here the disorders itself are simultaneously present in the individual.
Another example I can think of is of recessive alleles for both disorder at the same gene locus. (lets for example consider that eye color is due to recessive alleles at the eye-color locus). Now suppose that recessive allele S confers risk of schizophrenia and N is the normal variant. so SS is schizophrenic; SN is on the continuum toward schizophrenia and normality, perhaps a schizotypal individual. Suppose also that recessive allele A at the same locus makes one susceptible to Autism (they are opposite poles so evidently should work on same locus / loci). Thus AA is autistic and AN is asperper’s; now consider the rare scenario where one gets AS genotype ; in this case one might be asperger’s and schizotypal; in rare scenario this may develop into full-blown child-onset schizophrenia and classified as PDD_NOS or McDD.
To test my theory one can see the frequencies of Autistic and Schizophrenics and also the McDD iondividuals. If there was no interaction, Autism and schizophrenia should be independently inherited and P(mcDD) = P(Autism) * p(schizophrenia) where P is probability of an individual in a population belonging to that disorder. As my theory predicts there should be some interaction (the gene locus is same), so P(mcDD) should be different from that calculated from above (though I lack the requisite math knowledge to come up with a good formula!)
I believe I owe a bigger response to the questions raised, but I am hoping this to turn out as more of a conversation, then a one -sided defense of my pet theory, and would encourage more and more readers to get involved and propose new and radical solutions to this conundrum that has been highlighted! Also any statistics on the co-occurrence and individual occurrence and prevalence of Autism and schizophrenia would be more than welcome