An infographic on schizophrenia

In continuation of the theme of May as Mental Health month, passing along an infographic received in email. Hope it helps in raising awareness.
Schizophrenia: The Broken Mind

Neural correlates of conscious access: implications for autism/psychosis

First published Electroencephalogram of a human
Image via Wikipedia

There is a recent article in New Scientist about consciousness and its neural correlates and the article focuses on work of Stanislas Deheane and his colleagues and how they are trying to get evidence and proof for the Global workspace theory of consciousness as proposed by Beranrd Baars.

That led me to this excellent article by Raphaël Gaillard that uses iEEG (intracranial EEG) using electrodes placed in brain, but not doing single-cell recording but still working on aggregates but at a much higher spatial and temporal resolution than normal extra-cranial EEG. They used electrodes placed in epileptic patients undergoing surgery and determined the difference in neural activity during conscious and unconscious access.

For differentiating between the unconscious and conscious access they used the popular visual masking paradigm, whereby a target word is presented and then immediately afterwords (after a few ms only) a mask is presented; if the duration of stimuli presentation is less and it is immediately followed by a mask, then though the stimulus is processed unconsciously, it is not available for verbal report and is not processed consciously. In contrast, in the unmasked condition, the target is not followed by a mask and hence is available for conscious access. In the present experiment, the authors used a forward as well as a backward mask and also had a condition whereby a blank screen was present instead of target ; so that effects of processing target alone could be determined after subtracting the effect of masks. the paper is one access and very lucidly written so go have a look!

A quick detour: Bernard Baars global workspace theory posits that consciousness arises when neural representations of external stimuli, are made available wide spread to global areas of the brain and not restricted to the originating local areas. This has also been characterized as an attentional spotlight and whatever comes under the spotlight in global workspace, is widely visible to the rest of the audience (the other parts of the brain) and also gives rise to consciousness. In the absence of coming to focal awareness(spotlight), the processing/representation happens unconsciously by the many different parallel brain modules. Thus, while unconscious representations may arise in brain locally, to become conscious they need to become widespread and available to the entire (or most of) the brain. To boot:

We adopted a theory-driven approach, trying to test experimentally a set of explicit predictions derived from the global workspace model of conscious access. This model, in part inspired from Bernard Baars’ theory [30], proposes that at any given time, many modular cerebral networks are active in parallel and process information in an unconscious manner [22,23,31,32]. Incoming visual information becomes conscious, however, if and only if the three following conditions are met [23]: Condition 1: information must be explicitly represented by the neuronal firing of perceptual networks located in visual cortical areas coding for the specific features of the conscious percept. Condition 2: this neuronal representation must reach a minimal threshold of duration and intensity necessary for access to a second stage of processing, associated with a distributed cortical network involved in particular parietal and prefrontal cortices. Condition 3: through joint bottom-up propagation and top-down attentional amplification, the ensuing brain-scale neural assembly must “ignite” into a self-sustained reverberant state of coherent activity that involves many neurons distributed throughout the brain.

Based on this theoretical framework, the following hypothesis were developed:

Neurophysiological Predictions Derived from the Global Workspace Model

In the light of our model, the masked–unmasked contrast corresponds to a comparison between a visual representation satisfying only condition 1 and a representation satisfying all three conditions for conscious access listed above. The global workspace model therefore leads to the following four predictions.

Prediction 1: a common early stage of processing.
Both masked and unmasked words should evoke similar neural activity within an early time window, reflecting a fast feedforward sweep propagating from posterior to anterior cortices. In particular, invisible masked words should induce transient event-related responses along the ventral visual pathway, as assessed by iERPs and ERSP.

Prediction 2: a temporal divergence.
Following this initial common stage, only unmasked words should be associated with sustained effects. We thus predict a divergence in cortical activation for unmasked and masked words. Given that we contrasted heavily masked stimuli with unmasked stimuli, we expect a progressive buildup of the divergence between these two conditions. In the light of recent high-resolution scalp electroencephalogram (EEG) studies in visual masking and attentional blink paradigms, this temporal divergence is expected to occur within a 200–500-ms window [1,2].

Prediction 3: an anatomical divergence.
The activation of frontal and parietal areas, which are allegedly dense in global workspace neurons, should be particularly sensitive to consciously perceived words (see [32] and Figure 1 of [22] for explicit simulations of this property). Although masked words may cause a small, transient and local activation within these regions, we predict that unmasked words should elicit a global and long-lasting activation of these regions, corresponding to a broadcasting process.

Prediction 4: phase synchrony and causality.
During this late time window, the long-lasting and long-distance neuronal assembly specific to conscious processing should be associated with an intense increase in bidirectional interelectrode communication. Measures of phase synchrony and Granger causality should be particularly apt at capturing this phenomenon.

And this is exactly what they found. They found that upto 200 ms activity in the unmasked and masked condition did not differ significantly and represented an early stage of processing. In the 200-500 ms window (post stimulus onset), there was temporal divergence with there being long-distance beta synchrony, sustained amplitudes and power in gamma band and Granger causality in the unmasked case, but not in the masked case. Further, there was anatomical divergence, with the unmasked condition showing more occipitotemporal activation, while the unmasked condition showing global (and especially frontal) activation. Lastly while local beta synchrony and reverse feed back causality (accounted perhaps by top-down attentional factors that try to focus more given the masking) was associated with the masked condition, long distance beta synchrony and causal imbalance in the feed-forward direction was only found in the unmasked condition, thereby validating the claim that in the unmasked condition the posterior local representations weer made globally available to anterior regions as well (these are my very brief summaries, you should read the original freely available article for nuances and details).

This is how the authors conclude:

The main motivation of our study was to probe the convergence of multiple neurophysiological measures of brain activity in order to define candidate neural signatures of conscious access. Conscious word processing was associated with the following four markers: (1) sustained iERPs within a late time window (>300 ms after stimulus presentation); (2) sustained and late spectral power changes, combining a high-gamma increase, beta suppression, and alpha blockage; (3) sustained and late increases in long-range phase coherence in the beta range; and (4) sustained and late increases in long-range causal relations.

Our results suggest that in the search for neural correlates of consciousness, time-domain, frequency-domain, and causality-based electrophysiological measures should not be seen as competing possibilities. Rather, all of these measures may provide distinct glimpses into the same distributed state of long-distance reverberation. Indeed, it seems to be the convergence of these measures in a late time window, rather than the mere presence of any single one of them, that best characterizes conscious trials.

That brings me back to the new scientist article:

Dehaene’s group had already shown that distant areas of the brain are connected to each other and, importantly, that these connections are especially dense in the prefrontal, cingulate and parietal regions of the cortex, which are involved in processes like planning and reasoning.

Considering Baars’s theory, the team suggested that these long-distance connections may be the architecture that links the many separate regions together during conscious experience. “So, you may have multiple local processes, but a single global conscious state,” says Dehaene. If so, the areas with especially dense connections would be prime candidates for key regions in the global workspace.

Now it is well known that in autism there are more local connections and more local processing; while psychosis/ schizophrenia spectrum is marked by more long-distance connections/ activity. If so , it is not unreasonable to conclude that psychotics may have higher p-conscious experiences while autistics may be stuck at more lower A-conscious experiences. I proposed something like that in my post titled ‘what it is like to be a zombie‘ and you are strongly encouraged to go read it now.

Further we also know that default mode network is highly activated in psychosis and very less in activity in autistics and that is again converging proof. From the new scientist article:

Certain regions of the brain’s global workspace, dubbed the default mode network (DMN), are active even when we are resting and not concentrating on any particular task. If the global workspace really is essential for conscious perception, Laureys’s team predicted that the activity of the DMN should be greatest in healthy volunteers and in people with locked-in-syndrome, who are conscious but can only move their eyes, and much less active in minimally conscious patients. Those in a vegetative state or in a coma should have even less activity in the DMN.

The researchers found just that when they scanned the brains of 14 people with brain damage and 14 healthy volunteers using fMRI. In a paper published in December 2009, they showed that the activity of the DMN dropped exponentially starting with healthy volunteers right down to those in a vegetative state (Brain, vol 133, p 161). “The difference between minimally conscious and vegetative state is not easy to make on the bedside and four times out of 10 we may get it wrong,” he says. “So this could be of diagnostic value.”

While the DMN may be important marker for brain damaged patients, it also has the potential to become a marker for different feels of consciousness sin brain intact but differently wired brains like those of autistics and psychotics.

I believe one way of conceptualizing autism is as a diminishing of consciousness/ subjective experience; while that of psychosis as overabundance of consciousness/ subjective feeling. Maybe that is why shamans of all ages have been closely identified with the psychotic spectrum.

If autistics have more local processing, then perhaps they should be better at tasks involving unconscious stimuli: perhaps that’s why despite their savantic abilities , much of what happens in the autistic mind is not only non-verbal , but also non-conscious and hence not juts not available for verbal report, but not accessible to consciousness.

I strongly feel that adding the consciousness dimension to autism/schizophrenia spectrum may be a good thing and lead to more clarity and new directions in research.

Gaillard, R., Dehaene, S., Adam, C., Clémenceau, S., Hasboun, D., Baulac, M., Cohen, L., & Naccache, L. (2009). Converging Intracranial Markers of Conscious Access PLoS Biology, 7 (3) DOI: 10.1371/journal.pbio.1000061

Reblog this post [with Zemanta]

Autism and Schizophrenia: proof from comparative genomics

An overview of the structure of DNA.
Image via Wikipedia

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

Reblog this post [with Zemanta]

Self relevance and the reality-fictional blur

There is a new study in PLOS One that argues that we make reality-fictional distinction on the basis of how personally relevant the event in question is. To be fair, the study focuses on fictional, famous or familiar (friends and family) entities like Cinderella, Obama or our mother and based on the fact that these are arranged in increasing order of personal relevance, as well as represent fictional and real characters, tries to show that one of the means by which we try to distinguish fictional from real characters is by the degree of personal relevance these characters are able to invoke in us.

The authors build upon their previous work that showed that amPFC(anterior medial prefrontal cortex) and PCC (Posterior Cingulate cortex), which are part of the default brain network, are differentially recruited when people are exposed to contexts involving real as opposed to fictional entities. From this neural correlate of the regions involved in distinguishing fiction from reality, and from the known functions of these brain regions in self-referential thinking and autobiographical memory retrieval, the authors hypothesized that the reality-fictional distinction may be mediated by the relevance to self and this difference in self-relevance leads to differential engagement of these brain areas. I quote form the paper:

In the first attempt to tackle this issue using functional magnetic resonance imaging (fMRI), we aimed to uncover which brain regions were preferentially engaged when processing either real or fictional scenarios . The findings demonstrated that processing contexts containing real people (e.g., George Bush) compared to contexts containing fictional characters (e.g., Cinderella) led to activations in the anterior medial prefrontal cortex (amPFC) and the posterior cingulate cortex (PCC).

These findings were intriguing for two reasons. First, the identified brain areas have been previously implicated in self-referential thinking and autobiographical memory retrieval. This suggested that information about real people, in contrast to fictional characters, may be coded in a manner that leads to the triggering of automatic self-referential and autobiographical processing. This led to the hypothesis that information about real people may be coded in more personally relevant terms than that of fictional characters. We do, after all, occupy a common social world and have a wider range of associations in relation to famous people. These may be spontaneously triggered and processed further when reading about them. A logical extension of this premise would be that explicitly self-relevant information should therefore elicit such processing to an even greater extent.

To study the above hypothesis they used an experimental study that used behavioral measures like reaction time, correctness and perceived difficulty of judging propositions involving fictional, famous and close entities. Meanwhile they also measured , using fMRI, the differential recruitment of brain areas as the subjects performed under the different entity conditions. The experimental design is best summarized by having a look at the below figure.

What they found was that for the control condition and the fictional condition the reaction time , correctness and perceived difficulty associated with the proposition was signifciantkly different (lower RT, lower correctness and more perceived difficulty) than for the famous and friend entities condition. Thus, from the behavioral data is was apparent that real characters were judged faster , accurately and more easily than fictional characters. The FMRI data showed that , as hypothesiszed, amPFC and PCC were recruited significantly more in personal relevance contexts and showed a gradient in the expected direction. The below figure should summariz the findings:

In particular, in line with our predictions, regions in and near the amPFC (including the ventral mPFC) and PCC (including the retrosplenial cortex) were modulated by the degree of personal relevance associated with the presented entities. These regions were most strongly engaged when processing high personal relevance contexts (friend-real), secondarily for medium relevance contexts (famous-real) and least of all in the low personal relevance contexts (fiction) (high relevance>medium relevance>low relevance).

The amPFC and PCC regions are known to be commonly engaged during autobiographical and episodic memory retrieval as well as during self-referential processing. Regarding their specific roles, there is evidence indicating that amPFC is comparatively more selective for self-referential processing whereas the PCC/RSC is more selective for episodic memory retrieval . The results of the present study contribute to the understanding of processes implemented in these regions by showing that the demands on autobiographical retrieval processes and self-referential mentation are affected by the degree of personal relevance associated with a processed scenario. It should additionally be noted that the extension of the activations in anterior and ventral PFC regions into subgenual cingulate areas indicates that the degree of personal relevance also modulated responsiveness in affective or emotional regions of the brain .

Here is what the authors have to say about the wider ramifications:

That core regions of the brain’s default network are spontaneously modulated by the degree of stimulus-associated personal relevance is a consequential finding for two reasons. Firstly, the findings suggest that one of the factors that guide our implicit knowledge of what is real and unreal is the degree of coded personal relevance associated with a particular entity/character representation.


What this might translate to at a phenomenological level is that a real person feels more “real” to us than a fictional character because we automatically have access to far more comprehensive and multi-flavored conceptual knowledge in relation to the real people than fictional characters. This would also explain why a real person we know personally (a friend) feels more real to us than a real person who we do not know personally (George Bush).

I would say that there are other broader implications. First it is important to note that phenomenologically, Schizophrenia/psychosis is charachterized by an inability to distinguish reality from fiction. What is fictious also starts seeming real. A putative mechanism of why even fictional things start assuming ‘real’ dimensions may be the attribution of personal relevance or significance to those fictional entities. If something, even though fictional in nature, become highly personally relevant, then it would be easier to treat it as real. What ties things together is the fact that the default brain network is indeed overactive in the schizophrenics. If the PCC and amPFC are hyperactive, no wonder even fictional entities would be attributed personal relevance and incorporated into reality. I had earlier too discussed the delusions of reference with respect to default network hyperactivity in shizophrenics and this can be easily extended to now account for the loss of contact with reality , with the relevance and reality linkage in place. when everything is self relevant everything is real.

As always I am excited and would like some experiments done with schizophrnics/scizotypals using the same experimental paradigm and finding whether there is significant differences in the behavioral measures between controls and subjects and whether that is mediated by differential engagement of the default brain network. In autistics of course I hypothesize the opposite effects.

Needless to say I am grateful to Neuronarrative for reporting on this and helping me make one more puzzle piece fit in place.

Abraham, A., & von Cramon, D. (2009). Reality?=?Relevance? Insights from Spontaneous Modulations of the Brain’s Default Network when Telling Apart Reality from Fiction PLoS ONE, 4 (3) DOI: 10.1371/journal.pone.0004741

The factor structure of Religiosity and its neural substrates

A new article in PNAS by Grafman et al, argues that Religiosity can be broken down into three factors and the underlying machinery that these factors use are basic Theory Of Mind (ToM) circuitry, thus substantiating the claim that religion occurred as a byproduct of basic ToM related adaptations, although not ruling out that once established Religion may have provided adaptive advantage.

First a detour. I am more interested in this study as I had once claimed that Schizophrenics were more religious than Autistics and I have been maintaining that Religion is just one aspect of an underlying hyper-mentalizing to hyper-physicalism continuum on which these two spectrum disorders lie on opposite ends. The case for less ToM abilities in ASD seems to be fairly settled; its also becoming apparent that in Schizophrenia spectrum disorders you have excess of ToM abilities; This study by showing the ToM to Religion linkage, fills in the gaps and another puzzle piece falls in place.

On to the study. The authors first show that Religious Belief can be split into three factors. they use a novel (to me) technique of Multi Dimensional Scaling (MDS) to tease out the factors associated with religious belief. I have not checked how MDS works, but I assume it is similar to Factor analysis and can give us reliable factor structure underlying the data. They build on previous research and discovered the following three factors:

  1. God’s perceived level of involvement,
  2. God’s perceived emotion, and
  3. religious knowledge source. 

The first factor refers to endowing intentionality to superantural agents like God; the second factor refers to endowing emotions to God an dthe thierd factor refers to the source of the religious beliefs- whether it is doctrinal or derived from experience. Thus the trinity of intention, emotion and belief – alos the trinity involved in ToM tasks. The authors do a good job of describing the factors, so I’ll let them do it.

Dimension 1 (D1) correlated negatively with God’s perceived level of involvement (–0.994), Dimension 2 (D2) correlated negatively with God’s perceived anger (–0.953) and positively with God’s perceived love (0.953), and Dimension 3 (D3) correlated positively with doctrinal (0.993) and negatively with experiential (–0.993) religious content. D1 represents a quantitative gradient of a single concept and we will be referring to it as ‘‘God’s perceived level of involvement.’’ D2 and D3 represent gradients of contrasting concepts; we will be referring to them as ‘‘God’s perceived emotion’’ (D2) and ‘‘religious knowledge source’’ (D3).

God’s perceived level of involvement (D1) organizes statements so that ‘‘God is removed from the world’’ or ‘‘Life has no higher purpose’’ have high positive coordinate values, while ‘‘God’s will guides my acts,’’ ‘‘God protects one’s life,’’ or ‘‘God is punishing’’ have high negative values. Generally speaking, on the positive end of the gradient lie statements implying the existence of uninvolved supernatural agents, and on the negative end lie statements implying involved supernatural agents.

God’s perceived emotion (D2) ranges from love to anger and organizes statements so that ‘‘God is forgiving’’ and ‘‘God protects all people’’ have high positive-coordinate values, while ‘‘God is wrathful’’ and ‘‘The afterlife will be punishing’’ have high negative values. Generally speaking, on the positive end of the gradient lie statements implying the existence of a loving (and potentially rewarding) supernatural agent, and on the negative end lie statements suggestive of wrathful (and potentially punishing) supernatural agent.

Religious knowledge (D3) ranges from doctrinal to experiential and organizes statements so that ‘‘God is ever-present’’ and ‘‘A source of creation exists’’ have high positive-coordinate values, while ‘‘Religion is directly involved in worldly affairs’’ and ‘‘Religion provides moral guiding’’ have high negative values. Generally speaking, on the positive end of the gradient lies theological content referring to abstract religious concepts, and on the negative end lies theological content with moral, social, or practical implications.

This breakup of religiosity into three factors is itself commendable, but then they go on to show, using fMRI data that these factors activate areas of brain associated with ToM abilities. I don’t really understand all their fMRI data, but the results seem interesting. Here is what they conclude:

The MDS results confirmed the validity of the proposed psychological structure of religious belief. The 2 psychological processes previously implicated in religious belief, assessment of God’s level of involvement and God’s level of anger (11), as well as the hypothesized doctrinal to experiential continuum for religious nowledge, were identifiable dimensions in our MDS analysis. In addition, the neural correlates of these psychological dimensions were revealed to be well-known brain networks, mediating evolutionary adaptive cognitive functions.

This study defines a psychological and neuroanatomical framework for the (predominately explicit) processing of religious belief. Within this framework, religious belief engages well-known brain networks performing abstract semantic processing, imagery, and intent-related and emotional ToM, processes known to occur at both implicit and explicit levels (36, 39, 50). Moreover, the process of adopting religious beliefs depends on cognitive-emotional interactions within the anterior insulae, particularly among religious subjects. The findings support the view that religiosity is integrated in cognitive processes and brain networks used in social cognition, rather than being sui generis (2–4). The evolution of these networks was likely driven by their primary roles in social cognition, language, and logical reasoning (1, 3, 4, 51). Religious cognition likely emerged as a unique combination of these several evolutionarily important cognitive processes (52). Measurable individual differences in these core competencies (ToM, imagination, and so forth) may predict specific patterns of brain activation in response to religious stimuli.

As always I am excited and would like to see some field work being carried out to determine religiosity in ASD and Schizophrenia spectrum groups and see if we get the same results (less religiosity in autism and more religiosity in schizophrenics) as predicted, based on their baseline ToM abilities.

PS: I was not able to use the DOI lookup fetaure of Research Blogging, but the DOI of article is
* Dimitrios Kapogiannis,, * Aron K. Barbey,, * Michael Su,, * Giovanna Zamboni,, * Frank Krueger,, * and Jordan Grafman (2009). Cognitive and neural foundations of religious belief PNAS

Go to Top