Putting thought in the right place, part 2

CAP v2.1.2

In the last blog post, I discussed the Cognitive Action Pathways model, a schematic conceptual representation of the hierarchy of key components that underpin human thought and behaviour.

Small changes in the early processes within the Cognitive-Action Pathway model can snowball to effect every other part of the process. A real life example of this is ASD, or Autism Spectrum Disorder.

ASD has been present since time immemorial. Numerous bloggers speculate that Moses may have had ASD, while a couple of researchers proposed that Samson was on the spectrum (although their evidence was tenuous [1]). Thankfully, autism is no longer considered a form of demon possession or madness, or schizophrenia, or caused by emotionally distant “refrigerator mothers”, nor treated with inhumane experimental chemical and physical “treatments” [2, 3].

The autism spectrum is defined by two main characteristics: deficits in social communication and interaction, and restricted repetitive patterns of behaviour. People on the autism spectrum also tend to have abnormal sensitivity to stimuli, and other co-existing conditions like ADHD. The full diagnostic criteria can be found in DSM5. The new criteria are not without their critics [4-6], but overall, reflect the progress made in understanding the biological basis of autism.

ASD is recognized as a pervasive developmental disorder secondary to structural and functional changes in the brain that occur in the womb, and can be detected as early as a month after birth [7]. In the brain of a foetus that will be born with ASD, excess numbers of dysfunctional nerve cells are unable to form the correct synaptic scaffolding, leaving a brain that is large [8, 9], but out-of-sync. The reduced scaffolding leads to local over-connectivity within regions of the brain, and under-connectivity between the regions of the brain [10]. The majority of the abnormal cells and connections are within the frontal lobe, especially the dorsolateral prefrontal cortex and the medial prefrontal cortex [11], as well as the temporal lobes [12]. The cerebellum is also significantly linked to the autism spectrum [13]. There is also evidence that the amygdala and hippocampus, involved in emotional regulation and memory formation, are significantly effected in ASD [10].

There is also strong evidence for an over-active immune system in an autistic person compared to a neurotypical person, with changes demonstrated in all parts of the immune system, and the immune system in the brain as well as the rest of the body [14]. These immune changes contribute to the reduced ability of the brain to form new branches as well as develop new nerve cells or remove unnecessary cells.

There are a number of environmental and epigenetic associations linked to autism. These include disorders of folate metabolism [15, 16], pollutants [17], fever during pregnancy [18] and medications such as valproate and certain anti-depressants [19, 20] which are linked with an increase in autism[1]. Supplements such as folate [15, 21], omega-6 polyunsaturated fatty acids [22] and the use of paracetamol for fevers in pregnancy [18] have protective effects.

Although these factors are important, genes outweigh their influence by about 4:1. Twin studies suggest that between 70-90% of the risk of autism is genetic [23, 24]. Individual gene studies have only shown that each of the many single genes carry about a one percent chance each for the risk of autism [10]. It’s been proposed that the hundreds of genes linked with autism [10, 25] are not properly expressed (some are expressed too much, some not enough). The resulting proteins from the abnormal gene expression contribute to a different function of the cell’s machinery, altering the ability of a nerve cell to fully develop, and the ability of nerve cells to form connections with other nerve cells [26]. The effects are individually small, but collectively influential [24]. Autism is considered a complex genetic disorder involving rare mutations, complex gene × gene interactions, and copy number variants (CNVs) including deletions and duplications [27].

According to the Cognitive-Action Pathways model, the triad of the environment, epigenetics, and genes influence a number of processes that feed into our actions, thoughts, perceptions, personality and physiology. In ASD, the starting place is language processing.

New born babies from as young as two days old prefer listening to their own native language [28], which suggests that we are born already pre-wired for language. Auditory stimuli (sounds) are processed in the temporal lobes, including language processing. In neurotypical people, language processing is done predominantly on the left side, with some effect from the right side. But in people with autism, because of the abnormal wiring, there is only significant activity of the right temporal lobe [12]. Even more, from data so recent that it’s pending publication, loss of the processing of information of the left temporal lobe reversed the brains orientation to social and non-social sounds, like the sound of the babies name [7].

The change in the wiring of the left and right temporal lobes then alters the processing of language, specifically the social significance of language and other sounds. So already from a young age, people with autism will respond differently to environmental stimuli compared to a neurotypical person.

In the same way, the fusiform gyrus is part of the brain that processes faces. It’s quite specific to this task in a neurotypical person. However, the altered wiring of the brain in someone with autism causes a change, with different parts of the brain having to take up the load of facial processing [29].

Each time that one part of the brain can’t perform it’s normal function, the other parts take up the load. However that reduces the capacity for those parts of the brain to perform their own normal functions. In the case of the temporal lobes and the fusiform areas, this results in a reduced ability to discern subtleties especially those related to recognizing social cues. A neurotypical person and an autistic person could be standing in front of the same person, listening to the same words, and seeing the same facial expressions, but because of the way each persons brain processes the information, the perception of those words and cues can be completely different. This demonstrates how genetic changes can lead to changes in the perception of normal sensory input, resulting in differences in the physiological response, emotions, feelings, thoughts and actions, despite identical sensory input.

Physiology

The same changes that effect the cerebral cortex of the brain also have an influence on the deeper structures such as the hippocampus and the amygdala. The hippocampus is largely responsible for transforming working memory into longer term declarative memory. Studies comparing the size of the hippocampus in ASD children have shown an increase in size compared with typical developing children [30]. Combined with the deficits in the nerve cell structure of the cerebellum [13], autistic children and adults have a poor procedural memory (action learning, regulated by the cerebellum) and an overdeveloped declarative memory (for facts, regulated by the hippocampus). This has been termed the “Mnesic Imbalance Theory” [31].

The amygdala is also functionally and anatomically altered because of the changes to the nerve cells and their connections. The amygdala is larger in young children with ASD compared to typically developing children. As a result, young ASD children have higher levels of background anxiety than do neurotypical children [32]. It’s proposed that not only do ASD children have higher levels of background anxiety, they also have more difficulty in regulating their stress system, resulting in higher levels of stress compared to a neurotypical child exposed to the same stimulus [33].

Personality

On a chemical level, autism involves genes that encode for proteins involved in the transport of key neurotransmitters, serotonin and dopamine. Early evidence confirms the deficits of the serotonin and dopamine transporter systems in autism [34]. These neurotransmitters are integral to processing the signals of mood, stress and rewards within the brain, and as discussed in the last chapter, are significantly involved in the genesis of personality.

The abnormal neurotransmitter systems and the resulting deficiencies in processing stress and rewards signals contribute to a higher correlation of neuroticism and introverted personality styles in children with autism symptoms [35, 36].

So people with autism genes are going to process stress and rewards in a different way to the neurotypical population. As a result, their feelings, their thoughts and their resulting actions are tinged by the differences in personality through which all of the incoming signals are processed.

Actions

The underlying genes and neurobiology involved in autism also effect the final behavioural step, not only because genes and sensory input influence the personality and physiology undergirding our feelings and thoughts, but also because they cause physical changes to the cerebellum, the part of the brain involved in fine motor control and the integration of a number of higher level brain functions including working memory, behaviour and motivation [13, 37].

When Hans Asperger first described his cohort of ASD children, he noted that they all had a tendency to be clumsy and have poor handwriting [38]. This is a good example of how the underlying biology of ASD can effect the action stage independently of personality and physiology. The cerebellum in a person with ASD has reduced numbers of a particular cell called the Purkinje cells, effecting the output of the cerebellum and the refined co-ordination of the small muscles of the hands (amongst other things). Reduced co-ordination of the fine motor movements of the hands means that handwriting is less precise and therefore less neat.

A running joke when I talk to people is the notoriously illegible doctors handwriting. One of the doctors I used to work with had handwriting that seriously looked like someone had dipped a chicken’s toes in ink and let it scratch around for a while. My handwriting is messy – a crazy cursive-print hybrid – but at least it’s legible. I tell people that our handwriting is terrible because we spent six years at medical school having to take notes at 200 words a minute. But it might also be that the qualities that make for a good doctor tend to be found in Asperger’s Syndrome, so the medical school selection process is going to bias the sample towards ASD and the associated poor handwriting (Thankfully, those that go on to neurosurgery tend to have good hand-eye coordination).

But if your educational experience was anything like mine, handwriting was seen as one of the key performance indicators of school life. If your handwriting was poor, you were considered lazy or stupid. Even excluding the halo effect from the equation, poor handwriting means a student has to slow down to write neater but takes longer to complete the same task, or writes faster to complete the task in the allotted time but sacrificing legibility in doing so.

Either way, the neurobiology of ASD results in reduced ability to effectively communicate, leading to judgement from others and internal personal frustration, both of which feedback to the level of personality, molding future feelings, thoughts and actions.

Thought in ASD

By the time all the signals have gone through the various layers of perception, personality and physiology, they reach the conscious awareness level of our stream of thought. I hope by now that you will agree with me that thought is irrevocably dependent on all of the various levels below it in the Cognitive-Action Pathways Model. While thoughts are as unique as the individual that thinks them, the common genetic expression of ASD and the resulting patterns in personality, physiology and perception lead to some predictable patterns of thought in those sharing the same genes.

As a consequence of the differences in the signal processing, the memories that make their way to long-term storage are also going to be different. Memories and memory function are also different in ASD for other neurobiological reasons, as described earlier in the blog with the Mnesic Imbalance Theory.

Summary

The Cognitive-Action Pathways model is a way of describing the context of thoughts to other neurological processes, and how they all interact. It shows that conscious thoughts are one link of a longer chain of neurological functions between stimulus and action – simply one cog in the machine. The autistic spectrum provides a good example of how changes in genes and their expression can dramatically influence every aspect of a person’s life – how they experience the world, how they feel about those experiences, and how they think about them.

I used autism as an example because autism is a condition that’s pervasive, touching every aspect of a person’s life, and provides a good example of the extensive consequences from small genetic changes. But the same principles of the Cognitive-Action Pathways Model apply to all aspects of life, including conditions that are considered pathological, but also to our normal variations and idiosyncrasies. Small variations in the genes that code for our smell sensors or the processing of smells can change our preferences for certain foods just as much as cultural exposure. Our appreciation for music is often changed subtly between individuals because of changes in the structure of our ears or the nerves that we use to process the sounds. The genetic structure of the melanin pigment in our skin changes our interaction with our environment because of the amount of exposure to the sun we can handle.

So in summary, this blog was to set out the place that our thoughts have in the grand scheme of life. Thought is not the guiding or controlling force, it is simply a product of a number of underlying functions and variables.

References

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  4. Buxbaum, J.D. and Baron-Cohen, S., DSM-5: the debate continues. Mol Autism, 2013. 4(1): 11 doi: 10.1186/2040-2392-4-11
  5. Volkmar, F.R. and Reichow, B., Autism in DSM-5: progress and challenges. Mol Autism, 2013. 4(1): 13 doi: 10.1186/2040-2392-4-13
  6. Grzadzinski, R., et al., DSM-5 and autism spectrum disorders (ASDs): an opportunity for identifying ASD subtypes. Mol Autism, 2013. 4(1): 12 doi: 10.1186/2040-2392-4-12
  7. Pierce, K. Exploring the Causes of Autism – The Role of Genetics and The Environment (Keynote Symposium 11). in Asia Pacific Autism Conference. 2013. Adelaide, Australia: APAC 2013.
  8. Courchesne, E., et al., Evidence of brain overgrowth in the first year of life in autism. JAMA, 2003. 290(3): 337-44 doi: 10.1001/jama.290.3.337
  9. Shen, M.D., et al., Early brain enlargement and elevated extra-axial fluid in infants who develop autism spectrum disorder. Brain, 2013. 136(Pt 9): 2825-35 doi: 10.1093/brain/awt166
  10. Won, H., et al., Autism spectrum disorder causes, mechanisms, and treatments: focus on neuronal synapses. Front Mol Neurosci, 2013. 6: 19 doi: 10.3389/fnmol.2013.00019
  11. Courchesne, E., et al., Neuron number and size in prefrontal cortex of children with autism. JAMA, 2011. 306(18): 2001-10 doi: 10.1001/jama.2011.1638
  12. Eyler, L.T., et al., A failure of left temporal cortex to specialize for language is an early emerging and fundamental property of autism. Brain, 2012. 135(Pt 3): 949-60 doi: 10.1093/brain/awr364
  13. Fatemi, S.H., et al., Consensus paper: pathological role of the cerebellum in autism. Cerebellum, 2012. 11(3): 777-807 doi: 10.1007/s12311-012-0355-9
  14. Onore, C., et al., The role of immune dysfunction in the pathophysiology of autism. Brain Behav Immun, 2012. 26(3): 383-92 doi: 10.1016/j.bbi.2011.08.007
  15. Schmidt, R.J., et al., Maternal periconceptional folic acid intake and risk of autism spectrum disorders and developmental delay in the CHARGE (CHildhood Autism Risks from Genetics and Environment) case-control study. Am J Clin Nutr, 2012. 96(1): 80-9 doi: 10.3945/ajcn.110.004416
  16. Mbadiwe, T. and Millis, R.M., Epigenetics and Autism. Autism Res Treat, 2013. 2013: 826156 doi: 10.1155/2013/826156
  17. Volk, H.E., et al., Residential proximity to freeways and autism in the CHARGE study. Environ Health Perspect, 2011. 119(6): 873-7 doi: 10.1289/ehp.1002835
  18. Zerbo, O., et al., Is maternal influenza or fever during pregnancy associated with autism or developmental delays? Results from the CHARGE (CHildhood Autism Risks from Genetics and Environment) study. J Autism Dev Disord, 2013. 43(1): 25-33 doi: 10.1007/s10803-012-1540-x
  19. Rai, D., et al., Parental depression, maternal antidepressant use during pregnancy, and risk of autism spectrum disorders: population based case-control study. BMJ, 2013. 346: f2059 doi: 10.1136/bmj.f2059
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  21. Suren, P., et al., Association between maternal use of folic acid supplements and risk of autism spectrum disorders in children. JAMA, 2013. 309(6): 570-7 doi: 10.1001/jama.2012.155925
  22. Lyall, K., et al., Maternal dietary fat intake in association with autism spectrum disorders. Am J Epidemiol, 2013. 178(2): 209-20 doi: 10.1093/aje/kws433
  23. Abrahams, B.S. and Geschwind, D.H., Advances in autism genetics: on the threshold of a new neurobiology. Nature Reviews Genetics, 2008. 9(5): 341-55
  24. Geschwind, D.H., Genetics of autism spectrum disorders. Trends Cogn Sci, 2011. 15(9): 409-16 doi: 10.1016/j.tics.2011.07.003
  25. Chow, M.L., et al., Age-dependent brain gene expression and copy number anomalies in autism suggest distinct pathological processes at young versus mature ages. PLoS Genet, 2012. 8(3): e1002592 doi: 10.1371/journal.pgen.1002592
  26. O’Roak, B.J., et al., Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. Nature, 2012. 485(7397): 246-50 doi: 10.1038/nature10989
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  28. Moon, C., et al., Two-day-olds prefer their native language. Infant behavior and development, 1993. 16(4): 495-500
  29. Pierce, K., et al., Face processing occurs outside the fusiform `face area’ in autism: evidence from functional MRI. Brain, 2001. 124(10): 2059-73 doi: 10.1093/brain/124.10.2059
  30. Schumann, C.M., et al., The amygdala is enlarged in children but not adolescents with autism; the hippocampus is enlarged at all ages. J Neurosci, 2004. 24(28): 6392-401 doi: 10.1523/JNEUROSCI.1297-04.2004
  31. Romero-Munguía, M.A.n., Mnesic Imbalance and the Neuroanatomy of Autism Spectrum Disorders, in Autism – A Neurodevelopmental Journey from Genes to Behaviour, Eapen, V., (Ed). 2011 Edition 1st, InTech. p. 425-44.
  32. Bal, E., et al., Emotion recognition in children with autism spectrum disorders: relations to eye gaze and autonomic state. J Autism Dev Disord, 2010. 40(3): 358-70 doi: 10.1007/s10803-009-0884-3
  33. Harms, M.B., et al., Facial emotion recognition in autism spectrum disorders: a review of behavioral and neuroimaging studies. Neuropsychol Rev, 2010. 20(3): 290-322 doi: 10.1007/s11065-010-9138-6
  34. Nakamura, K., et al., Brain serotonin and dopamine transporter bindings in adults with high-functioning autism. Arch Gen Psychiatry, 2010. 67(1): 59-68 doi: 10.1001/archgenpsychiatry.2009.137
  35. Austin, E.J., Personality correlates of the broader autism phenotype as assessed by the Autism Spectrum Quotient (AQ). Personality and Individual Differences, 2005. 38(2): 451-60
  36. Wakabayashi, A., et al., Are autistic traits an independent personality dimension? A study of the Autism-Spectrum Quotient (AQ) and the NEO-PI-R. Personality and Individual Differences, 2006. 41: 873-83
  37. De Sousa, A., Towards an integrative theory of consciousness: part 1 (neurobiological and cognitive models). Mens Sana Monogr, 2013. 11(1): 100-50 doi: 10.4103/0973-1229.109335
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[1] A word of caution: While there’s good evidence that valproate increases the risk of autism, and a possible link between some anti-depressants and autism, that risk has to be balanced with the risk to the baby of having a mother with uncontrolled epilepsy or depression, which may very well be higher. If you’re taking these medications and you are pregnant, or want to become pregnant, consult your doctor BEFORE you stop or change your medications. Work out what’s right for you (and your baby) in your unique situation.

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Bad choices cause brain damage?

“To err is human; to forgive, divine.”  Alexander Pope.

I’m not perfect.  At least, not the last time I checked.  And we’re all the same, aren’t we.  We all know through experience that we all stuff things up on a fairly regular basis.  We make bad choices.  We’re human!

Dr Caroline Leaf, Communication Pathologist and self-titled Cognitive Neuroscientist, believes that these bad choices literally cause brain damage.  Her fundamental assumption is that our thoughts control our brain [1: p33].  These thoughts can be healthy or they can be toxic.  Toxic thoughts “are thoughts that trigger negative and anxious emotions, which produce biochemicals that cause the body stress.” [2: p19]

Dr Leaf’s assumption is that thoughts and bad choices cause our brain cells to shrivel or die. “Once your body is truly in stress mode and the cortisol is flowing, dendrites start shrinking and even ‘falling off’” [2: p32].  She also says that, “We have two choices, we can let our thoughts become toxic and poisonous or we can detox our negative thoughts which will improve our emotional wholeness and even recover our physical health.” [2: p21]

It sounds a little extreme.  We all make bad choices, and we all experience stress.  When we’re stressed, do our memories really go missing, or the dendrites of nerve cells shake and fall like tree branches in a storm?  If we make a bad choice, do we really get brain damage?  Lets see what the scientific literature has to say.

Imagine walking along a path in a forest and you see a snake, only inches in front of you on the path.  What do you do? When faced with a high level of acute stress, the brain switches into a binary mode – fight/flight or freeze. Self-preservation has to kick in.  The only decision you have to make then and there is whether to run, to try and kill the snake before it kills you, or stop dead still and hope that the snake ignores you and slithers away.

At that point, most memory is redundant, as is a high-level analysis of snake species, or any other cognitive pursuit.  The brain doesn’t need them at that precise moment.  If they did engage, they would just get in the way.  Switching the thinking parts of your brain off focuses your attention on the immediate danger.  It’s an adaptive survival response.  Meantime, your memories and your theoretical knowledge about snakes don’t disappear.  They are still there, unchanged.  It is false to suggest that the memories “shrink”.

We’ve all experienced “mental block”.  Sometimes when we get into a situation, like an exam or a business meeting, our stress levels are high, and binary mode kicks in again, although this time it can be a hindrance.  This phenomenon of mental block under high stress was first proposed in 1908 and is currently known as the Yerkes-Dodson Law, a fundamental principle of the behavioural sciences [3].  Similar to the stress-productivity curve, Yerkes and Dodson proposed a U-shaped curve to represent the relationship between arousal (which could be either level of consciousness or stress) and behavioural performance.  At low arousal, there is poor performance.  At the mid-point of arousal, there is peak performance, and at high arousal, performance diminishes.

But again, our memories don’t shrink, and our nerve cell branches don’t fall off.  Once we reduce our level of arousal, we move away from the fight/flight/freeze mode, and everything is still there (and we perform better, according to Yerkes-Dodson).

Dr Leaf has a favourite analogy of “neurons as trees”.  And if neurons are trees, then the branches can “fall off”.  But neurons are not trees and dendrites are not tree branches.  The dendrites do not ‘fall off’ the neuron.  The neurons in the brain have mechanisms for ongoing brain plasticity – the ability of the brain to adapt to the challenges and changes in its internal and external environment that are constantly occurring.  If the brain needs to build a new circuit to encode a new piece of information, then it grows new dendrites and creates new synapses.  But the brain is limited by the amount of energy it can consume, and therefore the number of synapses it can maintain.  So the brain trims unnecessary dendrites, a process called “synaptic pruning”.

Synaptic pruning is a normal process. Chechik and Meilijson confirm that, “Human and animal studies show that mammalian brains undergoes massive synaptic pruning during childhood, removing about half of the synapses until puberty.” [4]

Synaptic pruning is not deleterious, but beneficial.  Chechik and Meilijson also note that, “synaptic overgrowth followed by judicial pruning along development improves the performance of an associative memory network with limited synaptic resources.” [4] So synaptic pruning is a normal physiological process, and occurs in all of us for many reasons, predominantly to improve the efficiency of our neural networks.  Perhaps synaptic pruning associated with the stress response is also an adaptive process?

Synaptic pruning also occurs in other physiological states that have nothing to do with stress or thought, such as the effects of oestrogen during the menstrual cycle and at menopause [5, 6].

A link between stress and dendrite loss has been discovered, but it is not consistent.  Some authors like Kopp and Rethelyi suggest that “severe stress for a prolonged period causes damage in hippocampal pyramidal neurons, especially in the CA3 and CA4 region and reductions in the length and arborization of their dendrites.” [7] However, Chen et al writes, “Whereas hippocampus-mediated memory deficits commonly were associated with—and perhaps result from—loss of synapse-bearing dendrites and dendritic spines, this association has not been universal so that the structure–function relationship underlying the effects of stress on hippocampal neurons has not been resolved.” [8]

It’s more accurate to think that chronic stress causes dendritic remodeling in animals [9], in which some nerve cells prune their synapses, which others grow them, and energy is diverted away from new nerve cell formation to the new synapses that are needed to cope with the stress.

A number of scientists have pointed out that patients with depression or anxiety, who normally have high levels of stress, have a smaller hippocampus and larger amygdala, so stress and depression must cause the smaller brain regions [9].  There may be some reduction in the number of synapses within the hippocampus and the frontal lobes of the brain, which may account for the change in size observed by a number of researchers.  But the modern thinking on these changes is that they are associated with depression, not caused by depression [10] (Correlation does not equal causation).

So, stress is associated with depression, but this is because genetic defects in one or multiple genes reduce the ability for the brain cells to produce synaptic branches.  It’s this decrease in the number of synapses that contributes to the typical changes in the brain seen at autopsy of patients who suffered from depression or anxiety [11].  The reduced ability of the nerve cells to grow synapses means that new branches can’t grow fast enough to process the stress signals properly [11, 12].  The poor signal transmission leads to a predisposition towards mood disorders like anxiety and depression [10, 11, 13-15], and less synaptic branches means both a smaller volume of the hippocampus, and an inability to process stress signals leads to a larger, overactive amygdala.

In summary, synaptic pruning is not due to toxic thinking or bad choices, unless every one of us engages in nothing but toxic thinking from early childhood to puberty, and menopause causes bad choices and toxic thoughts.  Stress doesn’t cause dendrites to fall off, but causes a reorganization of the dendrites to adapt to the new signals. The reduced capacity to form new dendrites makes those prone to mood disorders more vulnerable to stress, and depression or anxiety is the end result.

We are all bound to make bad choices and to have stress.  They don’t cause brain damage.  Which if you’re not perfect like me, is good news.

References

1.         Leaf, C.M., Switch On Your Brain : The Key to Peak Happiness, Thinking, and Health. 2013, Baker Books, Grand Rapids, Michigan

2.         Leaf, C., Who Switched Off My Brain? Controlling toxic thoughts and emotions. 2nd ed. 2009, Inprov, Ltd, Southlake, TX, USA:

3.         Cohen, R.A., Yerkes–Dodson Law, in Encyclopedia of Clinical Neuropsychology, Kreutzer, J.S., et al., Editors. 2011, Springer Science+Business Media LLC: New York ; London. p. 2737-8.

4.         Chechik, G., et al., Neuronal regulation: A mechanism for synaptic pruning during brain maturation. Neural Comput, 1999. 11(8): 2061-80  http://www.ncbi.nlm.nih.gov/pubmed/10578044

5.         Chen, J.R., et al., Gonadal hormones modulate the dendritic spine densities of primary cortical pyramidal neurons in adult female rat. Cereb Cortex, 2009. 19(11): 2719-27 doi: 10.1093/cercor/bhp048

6.         Dumitriu, D., et al., Estrogen and the aging brain: an elixir for the weary cortical network. Ann N Y Acad Sci, 2010. 1204: 104-12 doi: 10.1111/j.1749-6632.2010.05529.x

7.         Kopp, M.S. and Rethelyi, J., Where psychology meets physiology: chronic stress and premature mortality–the Central-Eastern European health paradox. Brain Res Bull, 2004. 62(5): 351-67 doi: 10.1016/j.brainresbull.2003.12.001

8.         Chen, Y., et al., Correlated memory defects and hippocampal dendritic spine loss after acute stress involve corticotropin-releasing hormone signaling. Proc Natl Acad Sci U S A, 2010. 107(29): 13123-8 doi: 10.1073/pnas.1003825107

9.         Karatsoreos, I.N. and McEwen, B.S., Psychobiological allostasis: resistance, resilience and vulnerability. Trends Cogn Sci, 2011. 15(12): 576-84 doi: 10.1016/j.tics.2011.10.005

10.       Palazidou, E., The neurobiology of depression. Br Med Bull, 2012. 101: 127-45 doi: 10.1093/bmb/lds004

11.       Karatsoreos, I.N. and McEwen, B.S., Resilience and vulnerability: a neurobiological perspective. F1000Prime Rep, 2013. 5: 13 doi: 10.12703/P5-13

12.       Russo, S.J., et al., Neurobiology of resilience. Nature neuroscience, 2012. 15(11): 1475-84

13.       Felten, A., et al., Genetically determined dopamine availability predicts disposition for depression. Brain Behav, 2011. 1(2): 109-18 doi: 10.1002/brb3.20

14.       Bradley, R.G., et al., Influence of child abuse on adult depression: moderation by the corticotropin-releasing hormone receptor gene. Arch Gen Psychiatry, 2008. 65(2): 190-200 doi: 10.1001/archgenpsychiatry.2007.26

15.       Hauger, R.L., et al., Role of CRF receptor signaling in stress vulnerability, anxiety, and depression. Ann N Y Acad Sci, 2009. 1179: 120-43 doi: 10.1111/j.1749-6632.2009.05011.x