Before I talk about the study I want to provide some background on autism research and twin studies. The question that most behavioral geneticists ask is NOT whether autism is genetic or environmental. There is enough data to show that autism is NOT purely genetic and that autism is NOT purely environmental. The consensus is that autism is a very heterogenous condition that is likely due to multiple genetic and environmental factors.  So real question is what are the relative contributions of the environment, our genes, and other bio-social processes to the development of autism. To this end, behavioral geneticists examine the similarity between monozygotic (MZ) vs. dizygotic (DZ) twins to determine the relative genetic vs. environmental contributions of a specific condition. Specifically, if the correlation within MZ twins in regards to the rate of a disorder is greater than the correlation within DZ twins, then you would assume a significant genetic contribution. Why? MZ twins are genetically identical while DZ are not.  If a disorder has a large genetic contribution, then you would expect those twins that are identical to be more likely to both have the disorder than twins that are not identical. In contrast, in a disorder with little genetic contribution, DZ and MZ twins would be equally likely to share the disorder since the difference in how genetically identical they are would make little difference.

So in this study, the authors examined data from two large twin cohorts from Sweden (N=11,122) and the UK (N= 13,524) who were assessed at age 9 with two different autism scales/interviews. In Sweden the children were assessed with the Autism-Tics, AD/HD, and other Co-morbidities (A-TAC). In the UK, the children were assessed with the Childhood Autism Spectrum Test.

The results:

The graphic below shows the percentage changes in the probability of having a diagnosed ASD by having a father in different age groups.

As you can see, compared to 24-34 year old dads, there was a large increase in the odds of having a child with ASD (almost 100%) for younger dads, a similar increase for dads 35-44, and a very large increase (over 200%) for dads older than 51. However, only the change in fathers >51 in Sweden was statistically significant. The other changes only approached significance, likely because of the low rates of ASD among these cohorts.

As comparison, below you can see the changes in ASD traits for children of fathers in different age groups.

This time, the increase in autism traits for children of young fathers (<25) and older (>50) fathers is statistically significantly when compared to kids whose fathers were 25-34. So this study is consistent with previous research showing an increased risk of ASD among older fathers. However, the study also shows an potential increased risk of ASD for younger fathers as well. There was no effect of maternal age on the risk of ASD.

What about the role of parental age in the relative genetic/environmental contribution to ASD diagnoses?

Below is a graph that presents the correlation within MZ or DZ twins for different paternal age groups.

You will notice that the correlation between the MZ twins is always higher than the correlation between the DZ twins, suggesting some genetic contribution to the disorder. That is, MZ are more likely to BOTH have ASD than DZ twins. However, notice how the difference between the DZ and MZ twins is reduced for the older parents, in both Sweden and the UK. What does this mean? It means that the relative genetic contributions to ASD appear to decrease for older fathers. Now see below the raw correlations for all age groups:

What it is interesting about these data is that the correlation within the MZ increases with the fathers age. For example,  MZ twins of fathers over 40 have an almost 1-to-1 correspondence of the disorder. That is, if one twin had the condition, the other twin almost always had it too. Does this means genetic? Well, at the surface you would think this means genetic, after all both twins are genetically identical and both twins have the disorder. However, remember that MZ were conceived from the same sperm, and in this case, from the same sperm that may be ‘damaged’. So the increase concordance among MZ twins for older dads is not necessarily reflective of a genetic anomaly. In fact, the authors indicated how this effect may be due to the prolonged exposure to environmental toxins among the older fathers leading to sperm mutations. If that hypothesis is correct, it could be the environment, and not the genes, what is responsible for the increase risk in ASD among children of older dads.

The reference:
Lundström, S., Haworth, C., Carlström, E., Gillberg, C., Mill, J., Råstam, M., Hultman, C., Ronald, A., Anckarsäter, H., Plomin, R., Lichtenstein, P., & Reichenberg, A. (2010). Trajectories leading to autism spectrum disorders are affected by paternal age: findings from two nationally representative twin studies Journal of Child Psychology and Psychiatry DOI: 10.1111/j.1469-7610.2010.02223.x

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To this end, the authors examined MRI results of 14 children (age 6-14) with a ICD-10-based diagnosis of autism obtained via ADI-R but without any additional co-morbid condition. These children were compared to 14 matched typically developing kids. Specifically, the authors were interested in examining relations between ‘fractional anisotrophy’ and severity of symptoms. Fractional anisotrophy is a relatively new indicator of white matter integrity (instead of simply white matter volume).

The Results:

1. When compared to typically developing peers, children with autism displayed significantly lower fractional anisotrophy in the prefrontal lobes, right ventral temporal lobe, left middle temporal lobe, and left cerebellar hemisphere. In addition, children with autism displayed higher fractional anisotrophy in the superior longitudinal fasciculus and the left occipital lobe.
2. ADI-A scores (anomalies in social interactions) were associated with lower fractional anisotrophy in the fronto-striatal-temporal regions and the posterior corpus callosum,
3. ADI-B scores (anomalies n communication) were associated with lower fractional anisotrophy in the fronto-striatal area and the posterior corpus callosum
4. ADI-D scores (repetitive or stereotyped behaviors) were associated with lower fractional anisotrophy in the basal ganglia, temporo-parietal lobe, splenium of the corpus callosum and cerebellum.

In summary, the group-differences approach suggested that children with autism had anomalies in regions that had been previously identified as atypical in autism (prefrontal and ventral temporal lobes). However, when the authors examined correlates of fractional anisotrophy and specific symptoms, they found a much more complex picture of brain functioning in autism. Specifically, key symptoms of autism were associated with anomalies in areas of the brain involved in understanding the mental state of others, facial recognition, eye gaze, and understanding emotional states and gestures.

You may have noted however, that children with autism had greater fractional anisotrophy in two areas (superior fasciculus and left occipital lobe). The authors argued that this finding may be due to increase use of brain regions involved in working memory and visual processing. Therefore, these findings may reflect brain correlates of advanced non-verbal strategies used by individuals with autism to process verbal information.

Finally, some of you are familiar with the studies showing increased white matter volume in individuals with autism. Pure white matter studies suggest that children with autism have larger white matter volume, which has been interpreted as the result of impaired cell pruning during development. However, the current study confirms that the examination of pure white matter volume may not be sensitive enough to identify specific anomalies associated with autism symptoms.

On a unrelated programming note: Tonight we will start a technical transition of our blogging software, which we hope to complete by Sunday. During this time we will be unable to write additional reviews and the website may be down for a few hours this Saturday and Sunday. We hope to continue our posts on Monday May 11th. Thank you for your patience!

Cheung, C., Chua, S., Cheung, V., Khong, P., Tai, K., Wong, T., Ho, T., & McAlonan, G. (2009). White matter fractional anisotrophy differences and correlates of diagnostic symptoms in autism Journal of Child Psychology and Psychiatry DOI: 10.1111/j.1469-7610.2009.02086.x

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One way to test this hypothesis would be to also assess for ‘global processing’ skills. If individuals with ASD show superior performance on tasks requiring to break whole pictures in to parts, but show impaired performance on tasks requiring to process whole complex pictures, then the hypothesis would be supported (albeit not confirmed). In an article to be published in the Journal of Autism and Developmental Disorders, researcher Emma Grinter and her colleagues at the University of Western Australia attempted to examine this issue. Specifically, the authors were interested in examining whether typically developing individuals who have autistic traits show the same pattern of performance as those with diagnoses of autism. Thus, the authors examined 595 undergraduate students who completed a measure of autism-like symptoms. Based on the responses to this measure, 26 students were identified as having very high autism symptoms and 29 with very low levels of symptoms. The students then completed a series of visual perceptual tests.

The results:

1. On a test requiring participants to identify embedded figures within a complex larger picture, those with high autism symptoms were significantly faster and committed fewer errors than those with low autism symptoms. These results were independent of the gender of the participants, even though males outperformed females on these tasks.

2. On two tasks of global processing, the participants with high autism symptoms had significantly “higher thresholds”. Higher thresholds on these tasks indicate difficulty in the processing and identification of whole motion and static patterns. Thus, this suggests that these tasks were easier for those with low levels of autism symptoms than for the group with high levels of symptoms.

The results of this study support the possibility that the superior performance on tasks requiring the identification of embedded figures in autism, may be at least partly due to difficulties in whole picture processing. Furthermore, the study suggests that this pattern is noticeable even among typically developing individuals who show sub-clinical symptoms of autism, suggesting that such neurocognitive pattern may be closely related to the underlying cognitive processing in the general autism syndrome.
Grinter, E., Maybery, M., Beek, P., Pellicano, E., Badcock, J., & Badcock, D. (2009). Global Visual Processing and Self-Rated Autistic-like Traits Journal of Autism and Developmental Disorders DOI: 10.1007/s10803-009-0740-5

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This week a group of researchers from Yale University published a study on Nature that adds another piece to this puzzle. The authors presented a Pat-a-cake animation in which a character is clapping his hands. However, the video was presented using motion-capture, a technique that uses light dots to represent the joints of the body. The video was presented upside down in one side of the screen and upside up in the other side. Then the authors tracked the eye movements of children with autism, children with developmental delays, and typically developing children.

Here is a sample of one of the videos used:

[youtube=http://www.youtube.com/watch?v=dy-PvokLhiM]

Surprisingly, the children with autism concentrated on the motion-sound sync. That is, they focused on the hands clapping instead of other social aspects of the video. On the other hand, children with developmental delays, as well as typically developing children, seemed to focus on biological motion and socially relevant stimuli. Also, consistent with the previous study about eyes aversion I discussed, the kids with autism didn’t show a preference for the upright image – their eyes moved back and forth from the two sides of the screen. Instead, the typically developing kids preferred to look at the upright image. However, this pattern was observed only during videos that did not present the motion-sound.

In sum, this study show that children with autism seem to prefer motion-sound synchronicity, and this may explain why kids with autism prefer to look at the mouth area of the face instead of the eyes.

The article: Klin, A., Lin, D., Gorrindo, P., Ramsay, G., & Jones, W. (2009). Two-year-olds with autism orient to non-social contingencies rather than biological motion Nature DOI: 10.1038/nature07868

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A brief review of: INGE-MARIE EIGSTI, LOISA BENNETTO (2009). Grammaticality judgments in autism: Deviance or delay Journal of Child Language DOI: 10.1017/s0305000909009362

In this study the authors compared 21 children with ASDs (19 males, 10 to 16 years) and 22 typically developing kids (20 males, 9 to 17 years) on a series of cognitive and language tests, including IQ, vocabulary, and a grammaticality judgment tasks. In this last task, the children are presented 140 sentences with and without grammatical errors. When errors were present, these could occur at the beginning, the middle, or the end of each sentence. The sentences also varied in length from 5 to 11 words. The sentences were presented orally and the participants had to identify which sentences had errors.

The ASD performed worse than the typically developing group across the entire grammaticality judgment task. However, the authors noted that the groups did NOT differ when the sentences were short or medium length. That is, the apparent relative weaker performance among the ASD group was mostly during long sentences. In addition, these group differences were more pronounced when the error was located at the end of long sentences. This indicates that the group differences may be due to difficulty in working memory and attention among the autism group.

However, it is unlikely that these findings are only attributable to working memory problems. Specifically, the ASD groups showed impaired performance only to some type grammatical errors but not others. That is, the ASD group had difficulty identifying omissions and substitution errors, but did not show difficulty identifying order or insertion errors. This suggests that attention and working memory difficulties interact with some unique deficits in grammaticality judgment.

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A review of: Maiko Satomoto, Yasushi Satoh, Katsuo Terui, Hideki Miyao, Kunio Takishima, Masataka Ito, Junko Imaki (2009). Neonatal Exposure to Sevoflurane Induces Abnormal Social Behaviors and Deficits in Fear Conditioning in Mice Anesthesiology, 110 (3), 628-637 DOI: 10.1097/ALN.0b013e3181974fa2

NOTE: THIS IS A PRE-CLINICAL (ANIMAL) STUDY.

I will keep my reviews of animal studies short and I want to emphasize that these type of studies are intended only to inform future research with animals and humans, and no extrapolations of these findings to humans should be made. This is of great importance because most findings obtained with animals are eventually not replicated with humans. That is, our field is littered with interesting, controversial, and often shocking animal findings that simply eventually didn’t apply to humans. In addition, animal models of specific conditions are by definition limited, in that animal dysregulation of behavior does not necessarily parallel human processes. For example, lack of social interactivity in the mice does not necessarily reflect “mice autism,” just like limited social interactivity in humans does not by itself reflect autism. Animal work is of utmost importance but we must use caution when reaching conclusions from such findings.

A number of studies have examined the effects of neonatal exposure to anesthesia on brain development, yet little is known about the possible effects of pediatric anesthesia on social functioning. In this study the authors examined the effects of sevoflurane on the social development of mice. The researchers reported that neonatal exposure to sevoflurane resulted in neurodegeneration in the caudate/putamen, retrosplenial cortex, dorsal hippocampal commisuure, and neocortex. Neonatal exposure also resulted in normative responses to novel environment (normal fear behaviors) but significantly less social behaviors. For example, when given the option, typical mice spend more time interacting with other mice than with objects. However, under the same environment, mice exposed to sevoflurane during the neonatal period spend more time interacting with objects than other mice. Furthermore, mice exposed to sevoflurane displayed impaired social memory when compared to non-exposed mice.

As previously stated, this study presents very preliminary animal evidence that a common pediatric anesthetic produces brain neurodegeneration and social impairment in mice. The authors correctly called for the need for additional animal and human research that could examine whether the risk of neonatal exposure to sevoflurane in regards to social functioning is also found in humans. Currently, there is no evidence that such association exists.

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A review of: Natalia M. Kleinhans, Todd Richards, Kurt E. Weaver, Olivia Liang, Geraldine Dawson, Elizabeth Aylward (2009). Brief Report: Biochemical Correlates of Clinical Impairment in High Functioning Autism and Asperger’s Disorder Journal of Autism and Developmental Disorders DOI: 10.1007/s10803-009-0707-6

This brief yet powerful article is an example of research moving beyond making simple comparisons between typically developing children and children with autism – a move that has implications for how we conduct and evaluate etiological and mechanistic research.

In sum, the authors were interested in examining amygdala functioning in autism. The amygala serves a critical function in emotion recognition and processing, and thus it has been implicated in the neurophysiology of autism. For example, individuals with autism have been found to display atypical amygdala growth processes from childhood into adolescence (see for example Nacewiz et al., 2006. Archives of General Psychiatry, 63,12).

In this study the authors wanted to examine the biochemical integrity of the amygdala among individuals with high functioning autism and typical developing peers. In addition, the authors wanted to examine whether biochemical alterations in the amygdala would be associated with specific clinical symptoms of autism. The participants included 20 adults with high functioning autism (18 males, average age 23.57) and 19 typically developing peers (17 males, average age 23.32). Autism diagnosis was confirmed via ADOS and ADI. The Amygdale’s bilateral biochemical functioning was obtained via magnetic resonance spectroscopy. Four metabolites were measured: N-acetyl aspartate (NAA), creatine/Phosphocreatine (Cre), choline (Cho), and myoinositol (ml).

The authors did not find any differences in the concentrations of any of the metabolites when comparing the HFA and the control groups. Both groups had equal levels of all the metabolites measured. However, among the individuals with HFA, NAA was significantly associated with communication impairments, as measured by the ADI. In addition, Cre and NAA were associated with restrictive interests, and Cre alone was associated with social difficulties. The results therefore, indicate that those with the lowest concentrations of these metabolites tended to have more severe clinical symptoms as reported by the ADI.

The results of this study provide support for the need to conduct examinations that go beyond simple group comparisons. In this case, the authors found no differences in any of the metabolites between the two groups, which could easily lead one to conclude that such metabolites may not play a role in autism. Yet, the results were strong in indicating that key metabolites, while observed at normative levels, play a key role in the clinical presentation of the disorder. Although this is not necessarily new, it is consistent with a paradigm shift in how etiological or mechanistic research is conducted, in that the presence of normative functioning in a particular domain or brain process (when compared to typical peers) does not necessarily indicate that such domain is not implicated in the phenomenology of the condition.

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Although dysregulation of serotonin has been associated with several psychiatric disorders, there is evidence suggesting that disruption in serotonin systems may be implicated in autism. Specifically, serotonin is a critical component of the regulation of the growth and maturation of key areas of the Brain. This is relevant to autism research as numerous studies suggest that autism is associated with impaired cell pruning during development. But not all individuals with autism show dysregulation of serotonin systems. For example, only about 30% of individuals with autism show hyperserotonemia, or elevated blood serotonin levels (see for example Hranilovic et al., 2007 DOI: 10.1007/s10803-006-0324-6).

In this study the authors wanted to examine 3 proteins associated with serotonin functioning (5HTT,MAOB, and 5HT2Ar) in 3 groups of people: 15 individuals with autism and elevated serotonin blood levels (10 male, between 19 and 36 years, mean age 29.6), 17 individuals with autism but normal serotonin levels (12 male, between 21 and 42 years, mean age 30.3), and 15 non-autistic individuals (12 male, between 22 and 54 years, mean age 41.7).

The most surprising finding is that the authors observed altered kinetics of one protein (MAOB) in both groups of individuals with autism. That is, even those with non-elevated blood serotonin levels displayed dysregulation of MAOB when compared with non-autistic individuals. Although it is possible that this difference is due to medications being taken by the participants with autism, the authors indicate that there is no evidence that the type of medications reported by the participants would affect MAOB functioning. Therefore, the examination of simple blood serotonin levels may not fully reflect differences between individuals with autism and non-autistics in their serotonin functioning.

Original Abstract:

Disturbances in serotonin (5HT) neurotransmission have been indicated as biological substrates in several neuropsychiatric disorders including autism. Blood 5HT concentrations, elevated in about one-third of autistic subjects, are regulated through the action of peripheral 5HT-associated proteins. We have measured the activity of two platelet 5HT-associated proteins: 5HT transporter (5HTT) and monoamine oxidase B (MAOB), and indirectly studied the activity of 5HT2A receptor (5HT2Ar) in 15 hyper-serotonemic (HS) and 17 normoserotonemic (NS) autistic subjects, and 15 healthy controls (C).While mean velocities of 5HTT kinetics did not significantly differ among the groups, significant elevation in the mean velocity of MAOB kinetics was observed in NS subjects and was even more pronounced in HS subjects in comparison to controls. Also, a decrease in adenosine 50 -diphosphate-induced platelet aggregation of borderline significance was observed in NS subjects, compared to C subjects. The results suggest a possibility of upregulation of monoaminergic synthesis/ degradation and, probably consequential, downregulation of 5HT2Ar in autistic subjects.

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Just last week I had the opportunity to hear Dr. Richard Davidson, one of the fathers of the field of affective neuroscience, give a lecture in which he discussed brain volume differences in children with autism. The last pre-publication article of Journal of Autism and Developmental Disorders was very timely, as it also examines brain volume differences in austim, specifically in the Corpus Callosum. The CC is a structure that serves as a connection bridge between the two brain hemispheres. Since it contains a vast number of connecting pathways, anomalies within the Corpus Callosum have been associated with disorders that are hypothesized to be related to impaired connectivity between key brain areas. While a number of studies have shown that people with autism tend to have reduced CC volume, the authors of the current study wanted to expand this research by examining whether such reduced volume is also associated with the type of cognitive difficulties found in autism.

The authors examined 32 individuals with autism (29 males, 2 females, mean age 19.8 with a range of 8 to 45 years) who had been diagnosed via ADOS/ADI, and 32 typically developing individuals who were matched for gender, age, IQ, and socio economic status. None of the participants had history of infections genetic or metabolic disorders, birth asphyxia, head injuries, or seizures. The participants completed a series of neurocognitive tests as well as a MRI scan of their brain.

The results indicate that, when compared to typically developing individuals, participants with autism had smaller Corpus Callosum. This reduction in volume was limited to specific areas including the Rostrum, Genu, Anterior Body. Furthermore, as expected based on previous findings, the individual with autism had much lower scores on executive functioning (cognitive) tests when compared to typically developing participants.

The major finding however is that among typically developing participants within group variation in Corpus Callosum volume was not associated with variation in performance on the neurocognitive tests. That is, the size of the Corpus Callosum did not predict how well these participants would perform on the cognitive tests. However, among individual with autism, the size of the Corpus Callosum was associated with performance on this test, in that those with smaller Corpus Callosum tended to have more impaired performance than those with larger CC volumes.

This study provides additional evidence of Corpus Callosum atrophy in individuals with autism and the possible role of such anomaly in neurocognitive functioning, especially executive functioning tasks.

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In my last post I summarized a portion of a recent article examining the evidence for autism “recovery.” That first post was mostly focused on the definition of recovery, the evidence showing rates of recovery among children initially diagnosed with ASDs, and the factors that predicted increased rates of recovery. In this post I want to finish summarizing the original article by discussing the proposed mechanisms by which recovery may take place.

In sum, the authors state that recovery may occur as a function of one or several of the following mechanisms:

1. Normalizing input through attention
The general concept here is that some of the deficits in autism are due to limitations in attention or distraction that limits the child’s exposure to key stimuli (language, eyes, faces) that are critical for normal development. By redirecting the child’s attention to key stimuli via specific treatment interventions (e.g., ABA), it may be possible to help the child return to a more typical developmental trajectory.

2. Promoting the reinforcement value of social stimuli
This mechanism assumes that we are social because we are rewarded for being social. It is possible that children with autism lack the ability to experience internal rewards from social interactions, thus limiting the occurrence of such behaviors. By promoting such reinforcement (providing external rewards) we may be able to increase social behaviors by fostering the natural reinforcing properties of such behaviors

3. Early intervention provides enriched environments
Whether as the result of attention/distraction difficulties, or problems with the mechanisms that control the feelings of reward we experience during social interactions, one theory of autism suggests that limited environmental input contributes to the development of autistic symptoms. For example, children exposed to severe sensory deprivation (such as children in Eastern European orphanages), are at an increased risk for developing autism symptoms. Animal models have also shown that environmental deprivation leads to disruption in typical development, especially in the social realm. Therefore, early interventions may increase environmental sensory exposure (“enriched environmental opportunities”) facilitating a return to typical developmental trajectories among some children.

4. Early intervention provides mass practice and trials
This mechanism is based on the concept of neuro-cognitive rehabilitation. That is, that intensive repetition facilitates recovery of brain function, likely by facilitating the creation of new neural pathways. Therefore, this mechanism assumes that autism is at least partially due to problems during neural development that leads to an atypical neural organization. The mass repetition provided by intensive intervention would facilitate the development of new neural connections that normalize neural functioning, leading to a decrease in symptoms and neuro-cognitive deficits.

5. Compensatory processes
Similarly to #4, this mechanism suggests that even when brain organization can not be changed (as in irreversible brain damage), early intervention can lead to the development of compensatory behaviors or mechanisms that help the child “bypass” the original deficits. A simple example in physical rehabilitation is the case of right-handed person that suffers a stroke and loses functioning of his right hand. This person may, via intensive training, learn how to write well with his left hand, therefore compensating for the original deficit. In the case of autism, an example would be the case of implicit vs. explicit recognition of emotional facial expressions. Typically developing kids implicitly recognize facial expressions without necessarily needing to “break down” the components of such facial expression (e.g., shape of mouth, tears, etc). However, children with autism may have a deficit in this implicit system, but may learn to compensate for this deficit by developing explicit strategies (e.g., tears most often means sad) that would result in the same outcome: recognition of facial expressions.

6. Suppression of interfering behaviors
This is conceptually related to #1. Early interventions lead to suppression of behaviors that interfere with attentional focus to key environmental stimuli. For example, repetitive behaviors limit environmental input to usually one key non-social stimulus. Treatment interventions that reduce repetitive behaviors also result in an increase in behaviors that facilitate typical brain development, such as social interactions.

7. Limiting stress and arousal
Also conceptually related to #1 and #6, this mechanism indicates that early interventions reduces emotional arousal facilitating attentional focus to key environmental stimuli and also preventing the damaging effects of exposure to chronic stress.

8. Boosting recovery via biological treatments
Finally, biological interventions may facilitate recovery by enhancing the effects of the previously described mechanisms. For example, anti-anxiety medications may lead to a reduction of stress and arousal, thus facilitating the effectiveness of other behavioral interventions in promoting attentional focus, compensatory mechanisms, etc.

A final comment, please note that the mechanisms described above are simply the authors’ interpretation of what could be the underlying mechanisms for recovery. Although there is evidence to support these processes, these are entirely theoretical mechanisms, and the research on their validity is ongoing.

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