Chapter 5: Intellectual Disability May Help Deprived Brains Save Energy

“It is not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change.”

-Charles Darwin

Intellectual Disability Defined:

Intellectual disability, formerly known as mental retardation, is a neurodevelopmental condition that develops in or before childhood. It affects the capacity to learn and retain new information, and it also affects everyday behavior such as social skills and hygiene routines. People with this condition experience limitations with mental functioning and developing adaptive abilities like social and life skills. IQ scores lower than 70 indicate an intellectual disability and apply to 2.5% of the population. The severity of the condition can range from mild to profound.   Slowed acquisition of new knowledge and skills Immature behavior for age Limited capacity for self-care Communication difficulties Difficulty with basic academic skills Difficulty with problem-solving or logical thinking

The Place for Intellectual Disability in Nature

The phenotypic characteristics of many organisms ranging from plants to insects to mammals, are known to show plastic responses to environmental events, many of which are thought to represent adaptive, defensive responses or reproductive strategies [1]. This phenotypic plasticity through differential gene expression is often cued by maternal condition and is known to create profound alterations in the phenotypes of developing organisms [2].

As discussed in the previous chapter, the thrifty phenotype hypothesis [3,4] has been used widely to interpret studies showing that maternal malnutrition is a decisive risk factor for the metabolic syndrome [5]. According to this hypothesis, phenotypes that are programmed by prenatal malnutrition to express low metabolic rates enjoy a survival advantage under deprived circumstances; however, if such a thrifty fetus is born into an environment marked by nutritional abundance, it will face an increased risk of adverse health consequences [6]. Conversely, robust phenotypes that express larger size and rapid metabolism are thought to increase reproductive success when resources are more plentiful but are more susceptible to starvation if exposed to nutritional shortage. Specialists now believe that the association between maternal malnourishment and the offspring’s proclivity for a low metabolism is adaptive, specifically because the mother’s deprived condition during pregnancy is often predictive of the environment into which the fetus will be born. 

This chapter will focus on several risk factors for human intellectual disability that are associated with maternal mortality, burden on maternal resources, or fetal malnourishment. These environmental events include low birth weight, multiparity, short birth interval, advanced maternal age, and maternal stress. Such risk factors may be associated with maternal deprivation: the impairment of a mother’s ability to transfer nourishment, care, and essential survival information to her offspring. 

For example, we will analyze the relationship between advanced maternal age and cognitive deficits. Old age of the mother is one of the most powerful predictors of attention deficit hyperactivity disorder (ADHD) [7], Down syndrome [8], severe intellectual disability excluding Down syndrome [9], and intellectual disability of unknown cause [10] in offspring. An older mother is statistically more likely to die before she can provide the parental investment necessary to produce an ecologically self-sufficient individual. Thus, the offspring of older mothers are at a disadvantage because they are less likely to receive adequate nourishment and instruction. This link may suggest that older mothers engage in fetal programming. They modify gene expression in the developing fetus to alter its cognitive strategy. This increases their offspring’s autonomy by lowering their caloric requirements and the inhibitory pressures on their instincts and natural reflexes. 

The human brain evolved to such large proportions, despite the accompanying metabolic costs, because humans greatly benefited from the ability to learn complex lessons about socialization, food extraction, and hunting [11-13]. The human ecological niche is well known to be cognitively rigorous and skill intensive [15]; consequently, large brains were valuable because they facilitated the acquisition, storage, and implementation of these lessons [11]. Knowing this, it seems logical to assume that individuals deprived of maternal instruction, and thus deprived of many valuable lessons, might have had difficulty procuring the food to meet their metabolic needs. Therefore, individuals exposed to prenatal risk factors for maternal deprivation should benefit from inhibiting the growth of metabolically excessive nerve tissue and assume a resting metabolic rate better suited for a deprived upbringing. 

Apes and monkeys provide far less parental investment than humans; they have smaller brains, and they inhabit a less mentally demanding place on the food chain. The niche filled by maternally deprived humans with intellectual disabilities would likely have closely resembled the less cognitively rigorous niche of our smaller, brained, primate cousins. We will also concentrate on other parallels between mentally disabled people and humanity’s closest living relatives, including cerebrocortical and hippocampal size, thyroid activity, and regulation of the HPA axis, and we will conclude that these similarities imply that the two groups would have shared a similar foraging strategy in ancestral times. (move below)

Intellectual Disability and Evolutionary Medicine

Today, the costs of intellectual disability (formerly known as mental retardation) are well documented, but the defensive manifestations may be hidden because of discrepancies between our modern and ancestral environments. Some forms of intellectual disability may be examples of environmental mismatch, discussed in Chapter 1. Intellectual disability and the underlying neuropathology have not been analyzed in terms of evolutionary medicine and have not been understood in terms of evolutionary theory. Generally, evolutionary analyses of intellectual disability are population-based and fail to explain why the disease arises in affected individuals [21]. Please recall that for a trait to be explicable under evolutionary medicine, the trait must be relatively prevalent, heritable, and susceptibility must vary within populations (16-20).

Figure 1. Distinctive facial characteristics of several types of syndromic intellectual disability. To me they don’t appear defective in any way. Rather, they look like a legitimate twist on humanity. Properly interrogated, each may have a their own benefits and a fascinating evolutionary story.

It can indeed be argued that the rather diverse assortment of relatively prevalent forms of mental retardation are purely pathological, and have no evolutionary significance. However, this chapter will explore the assertion that some forms represent a contingency-based ecological strategy. It is not expected that this paradigm will apply to every form of congenital neuropathology but several diseases will be identified as candidates.

Through an analysis of epidemiological, etiological, neuroanatomical, and physiological similarities between attention deficit hyperactivity disorder, Down syndrome, microcephaly, schizophrenia, syndromic intellectual disability, and intellectual disability of unknown cause, I hope to characterize their evolutionary significance.

Smaller Brains Save Tremendous Energy

There are grave costs associated with encephalization- the accumulation of neurons within the animal brain.  One cost identified by researchers is the high energy demand of nervous tissue [22-24].  For instance, the mass-specific metabolic rate of brain tissue is over 22 times the mass-specific metabolic rate of skeletal muscle [23].  Humans utilize 20 to 25% of their resting metabolic rate in their brains alone, whereas most primates utilize between 8 and 9% [25].

This is a costly organ considering that it accounts for only 2% of total human body weight [26].  Many studies have identified a mechanism common in most animals that minimizes unnecessary neural energy expenditure by reducing neuron number through cell death. One function of neuron death is to remove neurons that have not made correct or sufficiently numerous connections [27-31].  Cell death terminates extraneous neurons increasing metabolic efficiency [32-35].

Research has shown that even within populations of a single species, a significant degree of variation in the absolute number of neurons exists between individuals. Intraspecific diversity in the number of neurons has been found in every group that has been comprehensively analyzed [35]. Furthermore, researchers have argued that this diversity is crucial for evolutionary adaptability and the plasticity of the species [36,37].  Surely the large variation in human cognitive ability, in part, stems from the benefits of intraspecific diversity.  However, this chapter will go further and explore the possibility that all humans have a variety of cognitive trajectories available to them before critical developmental stages are reached, and the trajectories are canalized (determined) by environmental cues predictive of deprivation.

Hippocampus Size Shrinks When not Needed in Other Mammals

Neuron number has been known to fluctuate in individual animals, and these fluctuations often correlate with meaningful environmental cues.  For instance, a pattern of loss and replacement of neurons in the hippocampus [38,39] and the hyperstriatal complex [40] (an area known to be involved in the production and recognition of song) of adult canaries corresponds to seasonal variation, with an increased number of individual neurons in the spring (the mating season) and less in the fall and winter.  Ethological research has shown that food-hoarding bird species that must utilize spatial memory to relocate their food caches in the fall also have a seasonal pattern of loss and replacement of neurons in the hippocampus [41]. Furthermore, more subtle environmental effects, such as needing to hide or cache food, also increase hippocampal size in several bird species [42]. 

Research has strongly suggested that a similar functional relationship exists between behavioral activity and the regulation of neurogenesis in the mammalian hippocampus [43-45]. For instance, food-caching rat species have larger relative hippocampal sizes than similar species that do not cache in scattered locations [46]. In fact, neurogenesis in the hippocampi of individual adult mammals is known to increase with maternal investment, environmental stimulation, and enrichment [43,47-49] and decrease along with the diminishment of body size, metabolic rate, and need to forage [50]. This relationship between environmental demands and investment in hippocampal neurons is commonly interpreted as an ecological strategy [45,51].

Individual humans destined to be deprived of meme (units of behavioral information that can be transferred from one animal to another) transference would probably not pass through their developmental stages in an enriched environment. For this reason, these individuals would probably be forced to subsist using simple, low-yield foraging strategies. Therefore, the forms of neuropathology discussed in this chapter, all of which feature decreased hippocampal volume, may be analogous to the phenotypes of other enrichment-deprived mammals forced to employ less complicated foraging strategies.

Intellectual Disability Permits a Less Cognitively Rigorous Niche

One of the most consistent and conspicuous findings in ADHD, idiopathic MR, the stress cascade effect, and schizophrenia is disproportionately small size or hypometabolism of the hippocampus (see figure below). Furthermore, a comprehensive review reports that each of the four major identifiable prenatal causes of MR: Down syndrome, fragile X syndrome, Prader-Willi syndrome, and Angelman syndrome each feature significant hippocampal neuroanatomical abnormalities [52]. The hippocampal diminishment in said neuropathologic groups may be analogous to the adaptive hippocampal plasticity in the aforementioned birds and mammals.

Disorder	Hippocampal Diminishment and / or Hypometabolism
ADHD	Yes	53
Angelman syndrome	Yes	52
Down syndrome	Yes	54, 55
Fragile X	Yes	52, 56
Idiopathic MR	Yes	52
Prader-Willi syndrome	Yes	52
Schizophrenia	Yes	57, 58
Stress Cascade	Yes	59, 60

Table 1:

The cerebral cortex and hippocampus are thought to be very important in sophisticated hunting and food extraction techniques. Clutton-Brock and Harvey [61] posited that animal species with widely dispersed food resources should be selected for increased memory and spatial capacities. Gibson [62] also pointed out that primate and especially human foraging strategies involve widely dispersed resources and complex extractive techniques. This observation caused him to posit the “food extraction hypothesis,” which explains large cerebrocortical size in monkeys and humans in terms of the relative complexity of their foraging strategies.

Researchers have commented on the importance of the hippocampus [63,64] and the cerebral cortex in storing spatial information, creating mental maps, and allowing sophisticated food procurement strategies [65-67]. In the study of behavioral ecology, natural selection is thought to favor adaptations that increase foraging efficiency. The evolution of these types of adaptations is the domain of optimal foraging theory (OFT) [26]. Optimal foraging theory is often used to explain variations in metabolic processes. It makes sense, in terms of optimal foraging theory, that if the most prevalent forms of intellectual disability were adaptive, they would not affect vital neurological systems (and most do not), yet would instead affect those metabolically expensive systems associated with the storage of information superfluous to their ecological niche, the cerebral cortex, and hippocampus. 

Studies with female mammals have shown that brain areas responsible for learning and memory, especially the hippocampus, become hypermetabolic during pregnancy and early motherhood, and this response is thought to be an ecological strategy that helps mothers become better at protecting, caring for, and providing for their young [68]. It is accepted that mothers up-regulate hippocampal and cerebrocortical activity to prepare for motherhood. This chapter attempts to show that fetuses down-regulate the same activity when preparing for maternal deprivation.

Risk Factors Linking Intellectual Disability to Maternal Deprivation

This section will identify specific epidemiological risk factors for neuropathology, which might be related to deficits in maternal investment. These include short birth interval, multiparity, maternal stress, and low birth weight. As mentioned previously, advanced maternal age at birth is one of the most powerful predictors of ADHD [7], Down syndrome [8], severe intellectual disability excluding Down syndrome [9], and intellectual disability of unknown cause [10] in offspring. An older human mother is more likely to die before she can provide the nearly two decades of maternal investment and memetic transference required to enable her offspring to become self-sufficient within the skill-intensive human ecological niche. Furthermore, older mothers are much more likely to die during or after childbirth and during or after infection and thus are more likely than younger mothers to leave orphans behind. Clearly, a child orphaned at birth, or any time before adulthood is at a disadvantage and may benefit from an alternate foraging strategy. Perhaps some forms of intellectual disability represent humans maximized to survive being raised by the group after their mother’s death. Let us continue by identifying the proximate factors that cause the brain of human fetuses to be vulnerable to physiological indicators of maternal age, health, and wellbeing.

Short birth interval is a measure of time between births. A second baby, conceived only months after a previous birth is often subject to scarcity and deprivation in wild animals. Short birth interval is a risk factor for Down syndrome [69], schizophrenia [70], and other neurodegenerative disorders [71], is also associated with an increased burden on maternal time and resources. A mother who spaces her births close together will have increased difficulty partitioning nutrients and memes. If the second child has a proclivity for energy conservancy, it may be more likely to survive to reproductive age. 

The same reasoning applies to multiple births, where a mother gives birth to two or more babies, which is also a significant risk factor for certain forms of human intellectual disability, including Down syndrome [72,73], general intellectual disability [74], intellectual disability of unknown cause [10], and schizophrenia [75]. It is important to point out that both closely spaced births and multiparity are characteristic of r-selected animals. Sociobiological literature predicts that r-selected animals are less intelligent than K-selected animals because they will receive less parental investment [76]. This reasoning further implicates these neurological disorders in an ecological strategy by associating it with the r-strategy. It is also interesting to note that intellectual disability is strongly associated with precocious puberty [77], another characteristic of the r-strategy.

Studies in animals exposed to stress (separation from parents, threat to life, or famine) indicate that altered DNA methylations, histone modifications, or non-coding RNAs in the germ cells are responsible. These effects can be transferred across multiple generations. They result in changes at multiple levels of organization, from hormone production, cardiovascular function, stress-response regulation, immunity, metabolism, reproduction, cognition, behavior, to metabolic and psychiatric disorders. Effected animals are sometimes referred to as having the ”traumatized phenotype.”

Advanced paternal age is also a risk factor for schizophrenia and some other neurodegenerative disorders [78,79], and it is logical to assume that the presence of a father could also be relevant to the transference of nourishment and survival memes. There are several examples of paternal epigenetic programming in the literature. It would be interesting to know if father preprogram their sperm in other ways. Many recent studies in mammals provide evidence that paternal exposure to different environmental stressors, such psychological stress (social defeat stress, early life trauma and chronic variable stress) can result in transgenerational modifications though the sperm epigenome. It is now clear that maternal and paternal environmental information is transmitted to offspring via eggs and sperm.

There is a strong relationship between maternal stress during pregnancy and neurodevelopmental disorders in offspring [80-83]. A mother exposed to a stressful environment will probably be less likely to provide adequate nourishment and memes to her offspring and therefore should program her child for bioenergetic thrift. Many studies have shown that high maternal stress levels in humans are associated with impoverished childcare [84-86].

Very low birth weight is a robust predictor of several metabolic disorders, including obesity, heart disease, and diabetes each of which is characterized, in the thrifty phenotype literature, as a predictive adaptive response to malnutrition [6]. Low birth weight is also a very strong predictor of different forms of neuropathology, including ADHD [87,88], intellectual disability of unknown cause [10], microcephaly [89], and schizophrenia [75,90]. These relationships must be explored in more detail. However, this preliminary evidence supports the hypothesis that neuropathology may be a predictive, adaptive response to nutritional deprivation and environmental adversity and another facet of the thrifty phenotype phenomenon.

Known Risk Factors                                          References

Advanced Maternal Age

ADHD                                                                  Claycomb et al., 2004 [7]

Down syndrome                                                  Hook, 1981 [8]

Intellectual disability Excluding Down S.                   McQueen et al. 1987 [9]

Intellectual disability of Unknown Cause           Croen et al., 2001 [10]

Short Birth Interval

Down Syndrome                                                  Brender 1986 [69]

Other Neurodegenerative Disorders                 Jongbloet 2002 [71]

Schizophrenia                                                      Smits, 2004 [70]

Multiple Births

Down syndrome                                                   Doria-Rose et al., 2003; Clementi et al. 1999 [72,73]

Intellectual disability                                            Louhiala, 1995 [74]

Intellectual disability of Unknown Cause            Croen et al., 2001 [10]

Schizophrenia                                                      Hultman et al., 1999 [75]                          

Maternal Stress

ADHD                                                                  McIntosh et al., 1995 [83]

Schizophrenia                                          van Os, 1998; Brixey et al., 1993;

Selten et al., 1997 [80-82]

Very Low Birth Weight

ADHD                                                                   Breslau, 1996; Mick, 2002 [87,88] 

Intellectual disability of Unknown Cause           Croen et al., 2001 [10]

Microcephaly                                                       Gross et al., 1978 [89]

Schizophrenia                                                      Hultman; Wahlbeck, 2001 [75,90]

It is possible that the relationships identified here are not evidence of fetal programming or an adaptive link between maternal deprivation and neuropathology. For instance, the effects of maternal age might simply be due to increasing germ cell mutations, and the effects of stress and short birth intervals might simply be due to lowered maternal folate. However, the rate of germ cell mutations and the level of folate depletion may be the ultimate epigenetic mechanisms by which phenotypic plasticity instates this adaptive phenotype. A review of the data suggests a larger, more meaningful relationship in which these forms of intellectual disability would have significantly increased reproductive fitness for at-risk individuals in the human ancestral environment.

It important to note that the most common forms of intellectual disability do not affect vital homeostatic systems. One might assume that the random, purely pathological consequences of germ cell mutations and vitamin deficiencies would create indiscriminate pathological symptoms, many of which would be severely debilitating. Yet many forms of intellectual disability simply cause reductions in the overall energy output of the brain focusing their effect on specific, phylogenetically new, neuroanatomical structures such as the hippocampus and the cerebral cortex. For these reasons, the symptoms of many forms of intellectual disability can be interpreted as adaptive and not purely arbitrary or pathological.    

Intellectual Disability as a Response to Maternal Deprivation in Rats

It has been established that many other animals share similar plastic responses to environmental cues. This requires us to concede that our tendency to react plastically may derive from phylogenetically earlier forms because of a shared evolutionary history [91]. Interestingly, the rodent hippocampus and its inputs are known to be highly sensitive to a range of environmental insults. A well-investigated rodent model for the association between maternal deprivation and hippocampal neuropathology [92,93] provides a wealth of relevant information.

The offspring of mouse mothers that show high levels of care in the form of pup licking, grooming, and arched-back nursing show multiple neurological signs of mental health, increased hippocampal innervation, and enhanced spatial and learning memory [94]. This makes sense in terms of the present hypothesis because a rat that receives this physical attention will probably also receive nourishment and the relevant survival memes from its mother as well and thus should be able to afford the metabolically expensive organs necessary for acquiring and utilizing memes and for initiating high-yield foraging strategies. 

Maternal deprivation, removing young rats from the nest or depriving them of pup licking and grooming, is predictive of impaired learning and memory [95] and disrupts attentional processes [96]. Maternal deprivation is known to decrease the expression of brain-derived neurotrophic factor (BDNF) in rat pups [97] and the expression of several growth factors (BDNF, bFGF, and β-NGF) in pup hippocampal samples [98]. Maternal deprivation has also been shown to be associated with overall decreased neuron survival in the hippocampus [99]. Furthermore, evidence suggests that the mechanism that up-regulates the neurotrophic factors responsible for increased spatial learning is not the mother’s physical presence or absence, but the stimulation provided by a licking action, as shown in experiments that feature artificial “licking-like” tactile stimulation [100]. If it were possible to show that pup licking is predictive of meme transference, this “licking-like” stimulation might be the environmental cue that canalizes young rats’ cognitive-ecological strategy.

Prenatal maternal stress is strongly associated with forms of congenital neuropathology in rats [101], monkeys [102], and humans [103].

Prenatal stress in mother rats and monkeys is known to create learning deficits in the offspring that are associated with decreased neurogenesis in the hippocampus and cerebral cortex [102,104]. This fetal response to stress in rats and monkeys is like the neuropathological responses to stress we just identified in humans. It seems logical that an environment that would cause great psychological stress in a pregnant mother would not be conducive to maternal investment. 

Traits of Intellectual Disability that Have Ecological Significance

Starving Animals Minimize Energy Expenditure

A variety of species are well known for demonstrating consistent plastic responses to starvation that help minimize energy expenditure. Starvation evokes several physiological changes, the most dramatic of which include suppression of metabolic rate, reduction of thyroid hormone and growth hormone levels, a reduction in fertility (through the suppression of gonadal function), and increased activation of the hypothalamic-pituitary-adrenal axis [107,108]. Many forms of neuropathology feature these same physiological alterations. This may be because maternally deprived humans in the environment of evolutionary adaptedness (EEA) would have benefited from the same physiological alterations as starving animals. 

Healthy mice are known to respond plastically to starvation by decreasing hippocampal bioelectrical activity. This is achieved through an increase in the number of hyperphosphorylated tau proteins in their hippocampi [105,106]. Hyperphosphorylated tau is one of the primary pathohistological hallmarks of Alzheimer’s disease and is also a histological component of Down syndrome. This reversible, phenotypic change in mice is analogous to the permanent hippocampal hypometabolism seen in forms of human congenital neuropathology because both may protect against starvation.

Low Metabolic Rate and Obesity in Intellectual Disability

Individuals deprived of maternal investment would probably be forced to survive in a less cognitively demanding place in the food chain. For instance, they might have to settle for less calorie-rich foods and smaller meals. Correspondingly, many forms of intellectual disability are associated with calorie hoarding: low metabolic rates, hypotonic musculature, and a sedentary lifestyle.

A review of the literature identifies obesity as a prevalent problem for individuals with mental disabilities and points out that diet and eating style do not seem to be the cause [109]. Obesity and musculoskeletal impairment have been found to be significant health problems associated with both intellectual disability [110] and mental retardation [111]. Another analysis points out that most studies evaluating the cardiovascular fitness level of adults with intellectual disability have reported levels representative of a highly sedentary population [112]. 

It is also important to note that many forms of syndromic intellectual disability are characterized by obesity and a sedentary lifestyle due to lowered overall metabolic rate and muscle hypotonicity [113]. These disorders include Allan Herndon syndrome, Angelman syndrome, Bardet-Biedl syndrome, Borjeson-Forssman-Lehmann syndrome, Cohen syndrome, Cri du Chat, Down syndrome, Fragile X syndrome, Megalocornea syndrome, Mehmo syndrome, and Prader Willi syndrome [113,114].

The genes predisposing mentally disabled individuals to obesity probably only represent a liability in our modern environment. These genes were probably an asset to survival in the Plio-Pleistocene because they would have caused the mentally disabled to conserve calories. The deprived conditions faced by the mentally disabled were probably analogous, in some ways, to those encountered by the ancestors of modern groups with a high incidence of obesity [115]. This propensity, seen in MR individuals, may also be analogous to the increased risk of obesity and metabolic syndrome seen in low birth weight babies, which is widely thought to be a predictive, adaptive response [116-118]. 

People who are highly skeptical of this line of reasoning should suspend their disbelief and acknowledge that all the developmentally disabled people that they have seen or known were raised with modern luxuries. To be fair, instead, we must imagine intellectually disabled people being raised since infancy as a hunter-gatherer. These people would have been concertedly focused on survival. Also, many of the people that you have seen with intellectual disability are obese, or severely obese, and have restricted mobility because of it. However, these people would not have been obese in the wild, and likely would have usually been fit and lean.

Many forms of intellectual disability that feature low muscle tone and metabolic rate also feature especially low metabolic rates in infancy. This infantile hypotonia would have ensured they necessitated less breast milk. A malnourished mother may not be able to provide sustenance to a baby with normal muscle tone but may be able to produce sufficient milk for a hypotonic baby. Also, many infants with intellectual disability have smaller head circumferences that would have been easier for older or less robust women to give birth to. This reasoning frames infantile hypotonia and decreased head circumference as part of a quantitative reproductive strategy.

Intellectual Disability, Insulin Resistance, and Diabetes

James Neel’s thrifty gene hypothesis, contends that the genes for diabetes make their bearers less susceptible to starvation [119-122]. Low birth weight babies are at an increased risk of developing diabetes, and this reaction to malnutrition is thought to be a predictive, adaptive response [116,117]. We should expect that individuals deprived of parental investment might be more susceptible to starvation and, for this reason, also expect to see evidence of deprived groups expressing the genes for diabetes in the epidemiologic record.

It is recognized that several neurodegenerative disorders, including Bardet-Biedl syndrome, Down syndrome, Prader-Willi syndrome, schizophrenia [123,124], and many others, are strongly associated with an increased incidence of diabetes mellitus [125]. However, diabetes mellitus often presents comorbidly with obesity, making it difficult to extricate the relative impact of diabetic propensity on the MR phenotype.

The risk for childhood [126,127] and gestational [128] diabetes increases rapidly with the advanced age of the mother. This shared susceptibility to advanced maternal age creates a parallel between neuropathology and diabetes. Further, it suggests that both neuropathology and advanced maternal age may be associated with the thrifty phenotype phenomenon.

Intellectual Disability and Cardiovascular Disease

Heart disease and cardiovascular disease have been associated with Down syndrome [129-131], schizophrenia [132,133], general intellectual disability [134], and a wide variety of syndromic types of MR. Heart disease due to a weaker and less energy-expensive heart is seen in humans with low body weight at birth. Researchers have previously ascribed the thrifty phenotype hypothesis to this relationship [116,117,135,136]. This popular literature suggests that the high propensity for low birth weight babies to have heart disease is a predictive adaptive response to the maternal condition that allows the offspring to minimize energy expenditure in the heart to help mitigate the risk of starvation. 

It is recognized that, in modern times, people that express this adaptive response no longer enjoy the benefits because the excess of fatty foods consumed by these individuals puts a severe strain on their “thrifty” hearts making them susceptible to heart disease [137]. For these reasons, the heart disease characteristic of intellectual disability phenotypes may represent yet another method of energy conservancy. Captive animals, because they overeat processed food, often have obesity, diabetes, and cardiovascular disease, but wild animals rarely develop these disorders. This likely would have been true of individuals with intellectual disabilities in the ancestral past.

Intellectual Disability and Hypothyroidism

One of the first major endocrinological differences found between humans and apes is a marked increase in human thyroid output [138,139].  Not just apes but almost all mammals have a larger adrenal gland to thyroid gland ratio, whereas humans have the reverse ratio, featuring an enlarged thyroid [139].  A recent publication by Fred Previc [139] favors G. Crile’s [140] interpretation of the adaptive value of a large thyroid to humans:

“Crile interpreted this difference (in thyroid output) as reflecting the need for more sustained exertion in humans as opposed to more transient activation in nonhumans, which is consistent with theories that early humans may have engaged in extended locomotion and sustained exertion during such activities as scavenging and chase hunting.”

In other words, a proportionately large thyroid allowed humans the sustained energy supply that their hunting niche demanded. The niche inhabited by individuals with intellectual disability would have closely resembled the less strenuous foraging niche seen in apes and monkeys, so it makes sense that they should feature a diminished thyroid gland. It is interesting to note that hypothyroidism is associated with ADHD [141], schizophrenia [142], Down syndrome [143], and congenital hypothyroidism (a form of MR). This association further paints these diseases as atavistic, energy-saving, ecological strategies. A quote from Flier et al. [108] highlights the ecological importance of thyroid plasticity during starvation:

“In the well-studied rodent model, starvation rapidly suppresses T4 and T3 (thyroid) levels. The benefit of this suppression is clear: starvation represents a severe threat to survival, and, in rodents, the capacity to survive without nutrition is measured in days. Because thyroid hormones set the basal metabolic rate, a drop in thyroid hormone levels should reduce the obligatory use of energy stores.”

Not only is starvation known to suppress thyroid levels [144], but hypothyroidism is also well-known to cause degeneration of the hippocampus in rats [145], implicating it further in a cross-taxa ecological strategy.

Intellectual Disability and Stress

A disproportionate number of people with intellectual disability have an up-regulation of the hypothalamic-pituitary-adrenal axis and are particularly susceptible to stress and stress diseases [146]. They react to only mildly threatening stimuli with an exaggerated adrenal/stress response. Rats from stressed mother, as well as rats deprived of their mothers also exhibit the same exaggerated adrenal/stress response as well as poorly developed hippocampi [93]. Zhang et al. emphasize that this reliance on stress is part of an ecological strategy that allows deprived rats rapid access to energy stores so they can react quickly to potential threats.

Adrenaline secreted by the adrenal glands during a stress response is known to increase energy catabolism allowing an animal to react to environmental threats with force and speed. Modern theorists believe that, unlike humans, most animals have larger adrenal glands than thyroid because it is more metabolically efficient to mobilize energy stores only in response to severe threats than to continually mobilize energy stores, as thyroid hormones are known to do [139].

It is possible that individuals with intellectual disability could have used this same strategy to conserve energy. Like many other non-human mammals, their disproportionately large adrenal glands and their “exaggerated stress response” should allow them to use energy stores more efficiently and only when necessary, despite their hypothyroid state. 

Individuals deprived of parental guidance probably had much more difficulty assessing which situations are dangerous and properly employing the fight or flight response. It would be better for such an individual to overreact to inconsequential stimuli than to under-react in response to a potentially lethal threat. This argument has been used to explain the link between maternal deprivation and the fetal programming of the stress response strategy in rats [93].

Associated “Thrifty” Disorders            Reference

Cardiovascular Disease

Down syndrome                                       Marino, 1993; Tubman et al., 1991; Spicer, 1984 [129-131]

Intellectual disability                                 Cooper, 1997 [134]

Schizophrenia                                           Kendrick 1996; Davidson 2002 [132,133]

Diabetes

Down syndrome                                       Anwar et al., 1998 [147]

Other Neurodegenerative Disorders      Ristow, 2004 [125]

Schizophrenia                                           Dixon, 2000; Felker, 1996 [123,124]

Hypothyroidism

ADHD                                                       Rovet et al., 2001 [141]

Down syndrome                                       Karlsson et al., 1998 [143]

Schizophrenia                                           Philibert et al., 2001 [142]

Obesity

Down syndrome                                       Bell, 1992; Prasher 1995 [147-149]

Other Neurodegenerative Disorders      O’Rahilly et al., 2003 [114]

Other Forms of Syndromic MR                Gunay-Aygun et al., 1997 [113]

Schizophrenia                                           Allison, 1999; Ryan, 2002 [151-152]

Exaggerated Stress Response

Intellectual disability                                 Sandman et al., 1985 [146]

Fragile X                                                   Hessl, 2004, Wisbeck, 2000 [153-154]

Profound Intellectual disability                 Chaney, 1996 [155]

Schizophrenia                                           Walker et al., 1996; 1997 [156,157]

Other homestatic, thermoregulatory, respiratory, and circulatory anomalies seen in MR syndromes might be evidence of adaptation to a different ecological niche.

The candidates for adaptive neuropathology that I list here may not be adaptive in the most stringent form of the word. In other words, the ecological causation that I invoke in this chapter may simply explain how MR individuals escaped stringent selective pressures and, thus, why they are as prevalent as they are in modern times.

Foraging Patterns Expected in Individuals with Intellectual Disability

It is thought that highly productive yet hard-to-learn foraging skills differentiate humans from other primates [26]. The “difficult-to-acquire-food hypothesis” promulgated by Kaplan [11] contends that the human ancestral environment selected individuals most actively based on their ability to acquire food to feed their metabolically expensive bodies and brains. To quote the researchers:

“Thus, we propose that the long human life span co-evolved with lengthening of the juvenile period, increased brain capacities for information processing and storage and intergenerational resource flows, all as a result of an important dietary shift. Humans are specialists in that they consume only the highest-quality plant and animal resources in their local ecology and rely on creative, skill-intensive techniques to exploit them.”

Difficult-to-acquire, extracted foods, including abundant meat [158-160], made up a large part of the hunter/gatherer diet in the environment of evolutionary adaptedness. Such foods provide many more total calories and macronutrients than more easily acquired foods [161]. The physical anthropological literature suggests that brain expansion enabled early hominids to extract more difficult-to-acquire foods that, not incidentally, were more nutritious and thus could sustain the larger brains [11].

Human foraging is very cognitively demanding and requires parental and social guidance [11]. In foraging groups, babies deprived of maternal interaction and investment were at an extreme disadvantage because they would probably not properly learn the language or learn to hunt or gather effectively, and would therefore be more susceptible to starvation. Much research has shown that it takes human hunter-gatherers many years of learning to become proficient [162] and that human hunting and gathering strategies are extremely sophisticated [12,163]. Chimpanzees are known to become fully capable foragers within their first decade [11], whereas most human hunter-gathers are not at their peak productivity rate until mid-adulthood [163].

Considering these points, an individual deprived of parental investment would not be able to successfully develop the skills to warrant a metabolically expensive cerebral cortex or hippocampus. For this reason, the selective pressure to link maternal deprivation to neuropathology through phenotypic plasticity may have been strong in the ancestral environment.

A hominin or early human that was mentally disabled would probably not be well adapted to the rigorous environmental niche of its peers. It would probably not have been able to catch large or mid-sized game and might have had trouble extracting roots, tubers, and other difficult-to-acquire, high-calorie foodstuffs. The ancestral diet of individuals with intellectual disability would have likely consisted of small game, easily accessible vegetation, insects and other invertebrates, found fruit, and other relatively low-quality foods that are easy to extract and process. Their propensity for a lower metabolism would have allowed such a moderate diet to sustain their simple foraging activities. It is conceivable that their diet would have been supplemented by the efforts of close kin and community members; however, it would likely have closely resembled that of apes.

Hyperphagia is defined as excessive appetite and constant searching for food. It is common to many forms of intellectual disability such as Prader Willi syndrome. Hyperphagia is probably an ecological strategy impelling these people to seek out low-quality, easy to obtain food stuffs. Rather than planning hunts for big game or laboriously processing and cooking fibrous vegetables, these people may have been roving for berries, flower buds, and insects and overturning rocks to uncover snails and worms. Live insects are relatively easy and safe to acquire, and, unlike scavenged meat, are an unlikely source of pathogens.

It is a common observation that carnivores, unlike herbivores raised in captivity, do not thrive when released into the wild [11]. To succeed in their specialized niche, carnivores must receive early training and have dedicated, protective and didactic mothers. Herbivores, on the other hand, can often be deprived of maternal investment and yet can still subsist later in the wild using simple foraging strategies. Therefore, the life history of the ancestral individual with intellectual disability may be analogous to the herbivore’s because both enjoy relative independence of parental investment. 

The fossil record shows that, for an extended period, many human-like hominids had very small brains. The considerable variability in brain size in hominids found in the fossil record proves that the near 1350 cc brain possessed by modern humans is by no means a requirement for food procurement in a bipedal ape. This forces us to recognize that the neurological “issues” seen in individuals with cognitive deficits may have analogs in our extinct ancestors.

The Behavioral and Psychological Benefits of Intellectual Disability

Meme Utility: It is not Always Helpful to Learn from Your Parents

I offer the concept of “meme utility” to generalize some of the claims made in this paper. Meme utility is the measure of the survival advantage that meme use provides for an animal. It is clear that memes are necessary for reproductive success in many intelligent animals, such as altricial (helpless when born), K strategists, but are less critical for precocial, r strategists that are less encephalized and have little need for parental guidance or social learning.

For example, meme utility would be lower for r-selected animals like mollusks and fish compared to K-selected animals like monkeys and humans. I am advocating that maternal deprivation predicts a decrement in meme utility and thus the potential applicability of intellectual subfunctionality. Observations like these suggest that clinical neurological conditions may be explicable in terms of ethology, bioanthropology, bioenergetics, and memetics.  

A similar relationship may be applied to explain the stress cascade phenomenon which, as you know from Chapter 4, occurs later in life. When meme utilization is effective, a mature animal will often experience reward, which helps to reinforce behaviors and consolidate memories. However, if meme utilization is ineffective, an animal will often experience stress which has been shown to produce a marked deficit in hippocampal and prefrontal metabolic function. The stress cascade may represent an ecological strategy to minimize reliance on ineffective memes and reemphasize instinct. 

Cognitive Noise: When High Intellect Creates Confusion

I contend that r-selected animals (which have large numbers of offspring and offer little parental care) rarely have high encephalization quotients because intelligence is ineffective without parental guidance. Furthermore, I believe that the ultimate factor responsible for the absence of both large brains and advanced intelligence in r-selected animals is, a concept that I will term, “cognitive noise.”  Cognitive noise consists of thoughts or cognitions that will direct, motivate, or affect the future behavior of an animal without producing a survival advantage for it. Cognitive noise includes thoughts that are irrelevant to survival or reproduction, misapprehensions, fallacious conceptualizations, and superstitious behavior. If it were possible to increase the intelligence of an r-selected animal without changing its ecological setting, the animal’s fitness would only be hindered due to an increased proclivity for cognitive noise.

It seems clear that an animal that is thoroughly instructed by its parents and thereby well-informed of the motivations and concerns of a successful forager will be less likely to produce fitness-compromising levels of cognitive noise. But if a highly encephalized, highly intelligent animal is deprived of its parents and of parental instruction, it will tend to improperly employ its ability for mental analysis and create mental systematizations that do not facilitate threat avoidance, feeding, or sex.

When an animal frequently engages in extraneous thinking, this may interfere with its ability to remain vigilant.

I argue that the mammalian brain, a metabolically expensive neurological organ that allows complex analysis in K-selected animals, is not equipped to produce adaptive behavior on its own without memes. If it did, we might expect to see large brains in animal species that do not transfer memes, yet we do not see this. Considering these points, an individual deprived of parental investment would not develop the skills to warrant a metabolically expensive cerebral cortex or hippocampus. Cognitive noise clearly affects us, even today, as studies show that even college students demonstrate high levels of magical ideation and superstitious thinking.

“Unless you keep them (people) busy with some definite subject that will bridle and control them, they throw themselves in disorder hither and yon in the vague field of imagination.”

-Montaigne

This phenomenon must be due, in part, to the inhibitory nature of cognition. Encephalized animals have disproportionately large numbers of inhibitory interneurons in their brains. These interneurons allow complex thought but would be debilitating to animals (i.e., fish and insects) that depend on instinct and quick reflexive reaction. Encephalization most probably inhibits an animal’s propensity to use innate and instinctive behaviors to respond to environmental stimuli. Maternally deprived animals should thus benefit from an ability to dis-inhibit their instinctive drives because instincts guide animals in the absence of mothers. Thus, some forms of neuropathology, may minimize the reliance on nurture (memes) and maximize reliance on nature (genetic instincts).

Female praying mantises occasionally bite off the head of their partner during sex. According to Richard Dawkins’ [165] interpretation of this act, the female bites off his head (and the males allow this) to ensure copulatory efficiency. Dawkins (possibly informed by the research of Ken Roeder) explains that by removing the male’s head, the female ensures that the male’s body will continue mating and will not be impeded by any inhibitory associations within the head that might slow or stop the copulation. A male mantis that stops mating before it releases its germ cells is at a definite selective disadvantage. This is an example that shows how maladaptive encephalization is if it inhibits the ability of the organism to reproduce. This suggests that not only are large brains metabolically expensive, but they can also inhibit adaptive, instinctual behavior. I attribute the intact male mantis’ reluctance to follow instinct to “cognitive noise.”  Mantises are in fact, relatively encephalized insect predators, the intelligence necessary for their hunting niche may be the factor that predisposes them to cognitive noise.

Definition of “Cognitive Noise”

Cognitive noise is any thinking that does not increase an animal’s reproductive success. The smarter and bigger-brained an animal is, the more cognitive noise they are capable of producing. Parental guidance reduces cognitive noise, because it set’s the thinking process on the “right tracks.” This is why all intelligent animals engage in large amounts of postnatal parental investment and instruction. must have parents that are didactic role models.

Sea squirts in Japanese seas metabolize their own brains (or nerve cord) once they have permanently attached themselves to a rock [164]. This is evidence of adaptive “neuropathology” at work in the animal world. In its early life stage, the squirt needs its central and peripheral nervous systems to locate and attain food and subsequently find a rock to attach to. After it adheres to the rock, it can then sacrifice its cognitive capabilities to decrease unnecessary energy expenditure. In other words, a change in its ecological niche obviates the need for encephalization and elicits “neurodegenerative” alteration.

Conclusion

Maternal deprivation may be a powerful and informative indicator of environmental quality that has profound predictive effects on the developing fetus. However, this hypothesis cannot be fully substantiated because of the scarcity of related studies. It is evident that much more work is needed to define the parameters of the influence of maternal deprivation on congenital neuropathology. 

All humans in existence, including those with severe mental handicaps, have tens of billions of neurons. The Dogs and cats we respect and treasure don’t even have 1 billion. Humans with severe intellectual disabilities have more powerful computational organs in their heads than any computer on the planet. I can’t say that every intellectual disability is a superpower but each one is unique, and I believe the vast majority of them come equipped with multiple specializations and compensatory advantages. Each has a natural history regardless of whether it was adaptive or not. I didn’t write these chapters in an attempt to empower people with mental disorders. This is a serious scientific investigation that is looking for hard empirical truths. But please don’t be surprised because anything crafted by nature is bound to be useful and beautiful.

Unfortunately, most forms of intellectual disability cannot yet be effectively treated, and providing proper care for the large number of effected individuals strains present-day families, communities, and economies. However, providing a comprehensive, evolutionary explanation for susceptibility to retardation may explain the prevalence in human populations. It may also help to inform psycho-social, bio-medical, and gene treatment strategies.

I hope this discussion will encourage researchers to use the maternal deprivation paradigm to more precisely identify the risk factors and environmental cues that determine cognitive trajectory. If science can clearly define each risk factor, parents can be instructed on how best to minimize inadvertent exposure of the fetus and child to neuropathology inducing environmental cues. 

These people’s thoughts are streamlined and lean. While our brains get swamped with information about complex patterns, the brains of simpler animals are latching onto much simpler, but more pressing inputs, like movement. Fast movement is prioritized above everything else. For instance, a much larger proportion of the cats brain is used to detect and track movement.

Alexander Luria said that the “retardates” were his favorite patients for many reasons. Oliver Sacks felt that their concrete apprehensions are fully intact.

Individuals with intellectual disability are often very sweet, kind, and friendly. It may be possible that their brains were selected to be this way because they would not have been actively vying for competition and dominance with their fellows. In other words, their alternate niche allowed them to escape the violent dominance hierarchy and the negative thoughts and behaviors that come along with it.

Many people with severe mental disabilities have active mental lives, nonetheless. In truth, a single dysfunctional brain module out of hundreds can lead to pronounced social dysfunction.

The adaptiveness of intelligence is kind of like the adaptiveness of longevity. Both vary between species and are related to the animal’s place in nature. Animals were never meant to be omniscient like they were never meant to be immortal. Organisms have to invest in a great deal of embodied capital to increase their life span, fixing wear and tear, neutralizing free radicals, DNA repair, and others. Just as with intelligence, there must be a confirmed payoff for this investment.

Intellectual disability

It is cognitive parsimony. It is a reliance on nature over nurture. When the predicted quality of nurturance is low, an animal should reduce the expensive and unreliable mechanisms intended to internalize memetic nurturing.

At its core, this work is analyzing chemical interactions- Cognitive Parsimony is ultimately catabolic efficiency maximization.  Meme utility vs. catabolism.

A quantitative reproduction strategy? CP theory is consistent with the selfish gene theory or genic selection theory.

When you look back to the early precursors of life, self-replicating RNA strands, it is clear that they were naturally selected for one primary trait, speed and fidelity of replication. Until they became embedded in a cell wall, they probably did little to protect themselves or respond to the environment in meaningful ways.

Two Opposite Strategies: Scenario Vigilance and Scenario Analysis 

Less encephalized animals react to stimuli in inflexible ways that are guided heavily by instincts. These animals are often precocial “r strategists” that provide little parental investment and have little use for behavioral plasticity. They employ a strategy that we will call “scenario vigilance,” where they remain vigilant for a limited number of stimuli and then react in a stereotypical manner. Their behavior is constrained highly by fixed action patterns, rigid neural modules, and evolutionarily stable strategies. These animals rely on the same behaviors that enabled their ancestors to live long enough to pass the genes for the behavior on to them. Maintaining systems conducive to learning, such as the mother-child bond, lengthening of the juvenile period, and the use of communication, is not conducive to reproductive success in scenario vigilance strategists as genes, not memes, inform their behavior. This strategy is quite robust and is employed by most animal species on the earth. 

The second strategy proposed here is “scenario analysis,” where animals respond to patterns of stimuli with complex behaviors that they have developed through environmental feedback or internal cognition. This approach is used by encephalized, altricial “K strategists” that have few offspring at a time and confer large amounts of parental investment. These more intelligent animals still have instincts and reflexes but subdue them to analyze their situation.

Scenario analysis strategists inhabit ecological niches that do not favor purely reflexive or genetically determined behavioral responses but favor more deliberate thought and conceptual systematization. Animals that employ the scenario analysis strategy usually have a cognitively rigorous place on the food chain. In other words, genes alone cannot prepare them to meet the rigors of their niche. These animals internalize information about their world and, in turn, analyze it to produce situation-appropriate behavior. The conceptual systematizations that scenario analysis strategists use are beneficial because they are formed within the context of tried and true social memes passed from parent to child. 

Judging by the duration of maternal investment in individual offspring, humans might be the species most reliant on parental care and, thus, scenario analysis. The delicacy of extreme scenario analysis, as seen in humans, is evidenced by the fact that most animal species have low intelligence. Scenario vigilance is the more robust strategy because it relies on trustworthy behaviors selected over geological time- genetically determined instincts. Scenario vigilance strategists are predominantly motivated by consumption and replication. In contrast, scenario analysis strategists are enabled to develop secondary and tertiary motivations to survive in a niche that requires more behavioral flexibility. These abstract behaviors increase the reproductive fitness of scenario analysis strategists like humans, apes, and mammals yet are less valuable to scenario vigilance strategists like lower vertebrates and invertebrates. 

Another reason natural selection is parsimonious with cognitive ability is that advanced intelligence in most niches increases the proclivity of making irrelevant or fallacious conceptualizations. I am arguing that extraneous conceptualizations are an inherent part of intelligence. Thus, organisms need a calm and reliable environment to provide critical conceptualizations for encephalization (and scenario analysis) to be adaptive. In other words, a safe environment that sends clear, honest signals about how to act allows animals the knowledge base to begin to formulate meaningful theories from general experience and enables them to predict the probability of events themselves with minimized guidance from gene-imposed probability prediction (instincts). Cognitive simplicity (where meme utility is low) allows genes to program and motivate the individual rather than letting an unpredictable environment program it.  

Chapter Summary

• This chapter proposes that humans have an adaptive vulnerability to certain forms of intellectual disability, specifically congenital neuropathological disorders that cause decreased energy expenditure in the cerebral cortex.

• The existence of these disorders is considered relative to the thrifty phenotype paradigm, according to which adverse prenatal events can cause differential gene expression resulting in a phenotype that is better suited, metabolically, for a deprived environment.

• A malnourished mother has an increased propensity to give birth to offspring with a “thrifty phenotype” that permits highly efficient calorie utilization, increased fat deposition, and a sedentary nature.

• This chapter interprets several epidemiological risk factors, including maternal malnourishment, low birth weight, multiparity, short birth interval, advanced maternal age, and maternal stress, as environmental cues that communicate to the fetus that, because it is likely to be neglected of maternal investment, developing a metabolically conservative brain will be its most effective ecological strategy.

• Success in hunting and foraging in mammals, primates, and especially humans is dependent on prolonged maternal investment. Low levels of maternal care are known to result in low survivorship of offspring, mainly because the offspring are forced to subsist using simple, low-yield foraging strategies.

• A predictive, adaptive response, marked by cerebral hypometabolism, may produce a level of metabolic conservancy that mitigates the risks associated with low levels of maternal care.

• This chapter suggested that certain human neuropathological phenotypes would have been well suited for an ecological niche that closely resembled the less skill-intensive niche of our less encephalized primate ancestors. 

• The forms of congenital neuropathology discussed in this chapter do not cause damage to vital homeostatic systems; most simply decrease the size and energy expenditure of the cerebral cortex and hippocampus, the same two structures known to show plasticity during changes in ecological rigor in vertebrates.

• Many disorders that present comorbidly with neuropathology, such as the tendency toward obesity, reduced anabolic hormones, hypotonic musculature, up-regulation of the hypothalamic-pituitary-adrenal axis, and decreased thyroid output, are associated with energy conservancy and the thrifty phenotype, further implicating neuropathology in an ecological strategy.

References

[1] Via S, Lande R. Genotype-Environment Interaction and the Evolution of Phenotypic Plasticity.Evolution 1985; 39(3):505-22.

[2] Fox CW, Mousseau TA. 1998. Maternal effects as adaptations for transgenerational phenotypic plasticity (TPP). In: Mousseau TA, Fox CW, editors. Maternal Effects as Adaptations. Oxford: Oxford University Press; 1998. P. 159-77

[3] Hales CN, Barker DJ. Type 2 (non-insulin-dependent) diabetes mellitus: the thrifty phenotype hypothesis. Diabetologia 1992; 35: 595-601.

[4] Hales CN, Barker DJ. The thrifty phenotype hypothesis. Br Med Bull 2001; 60:5-20.

[5] Wells J. The thrifty phenotype hypothesis: thrifty offspring or thrifty mother? J Theor Biol 2003; 7:221(1):143-61.

[6] Bateson P, Barker D, Clutton-Brock T, Deb D, D’Udine B, Foley R, Gluckman P, Godfrey K, Kirkwood T, Mirazon Lahr M, McNamara J, Metcalfe N, Monaghan P, Spencer H, Sultan S. Developmental Plasticity and Human Health. Nature 2004; 430, 419-21.

[7] Claycomb CD, Ryan JJ, Miller LJ, Schnakenberg-Ott SD. Relationships among attention deficit hyperactivity disorder, induced labor, and selected physiological and demographic variables. J Clin Psychol 2004; 60(6):689-93.

[8] Hook EB. Rates of chromosome abnormalities at different maternal ages. Obstet Gynecol 1981; 58:282-5.

[9] McQueen P C, Spence MW, Garner JB, Pereira LH, Winsor E. Prevalence of major mental retardation and associated disabilities in the Canadian Maritime Provinces. Am J Ment Deficiency 1987; 91:460–66.

[10] Croen LA, Grether JK, Selvin S. The epidemiology of mental retardation of unknown cause. Pediatrics 2001; 107(6):e86

[11] Kaplan H, Hill K, Lancaster J, Hurtado AM. The evolution of intelligence and the human life history. Evol Anthrop 2000; 9:156-84.

[12] Milton K. A hypothesis to explain the role of meat-eating in human evolution. Evol Anthropol 1999; 8:11-21.

[13] Stanford CG. The hunting apes: meat eating and the origins of human behavior. Princeton: Princeton University Press; 1999.

[14] Stanford CB, Bunn HT. Meat-eating and Human Evolution. Oxford: Oxford University Press; 2001

[15] Tooby J, DeVore I. The Reconstruction of Hominid Behavioral Evolution Through Strategic Modeling. In Primate Models of Hominid Behavior.  Kinzey W, editor. New York: SUNY Press; 1987.

[16] Williams G. Nesse R. The Dawn of Darwinian Medicine. Q Rev Biol 1991;66:1-22.

[17] Nesse R, Williams G. Why We Get Sick. New York: Random House; 1995.

[18] Nesse R, Williams G. Evolution and the origins of disease. Sci Am 1998; 279: 58-65.

[19] Nesse, R. What Darwinian medicine offers psychiatry. In: Trevathan W, Smith E, McKenna J, editors. Evolutionary Medicine. Oxford: Oxford University Press; 1999.

[20] Baron-Cohen S. The maladapted mind: Classic readings in evolutionary psychopathology. Hove, East Sussex: Psychology Press; 1997.

[21] Leckman JF, Mayes LC. Understanding developmental psychopathology: How useful are evolutionary accounts? J Am Acad Child Adolesc Psychiatry 1998; 37(10):1011-21.

[22] Kety SS, Schmidt CF. The effects of altered arterial tensions of carbon dioxide and oxygen on cerebral blood flow and cerebral oxygen consumption of normal young men. J Clin Invest 1948; 27:484-92.

[23] Aschoff J, Günther B, Kramer K. Energiehaushalt und Temperaturregulation. Munich: Urban and Schwarzenberg; 1971.

[24] Aiello LC, Wheeler P. The Expensive Tissue Hypothesis: the brain and the digestive system in human and primate evolution. Curr Anthropol 1995; 36:199-221.

[25] Mink JW, Blumenschine RJ, Adams DB: Ratio of central nervous system to body metabolism in vertebrates: Its constancy and functional basis. Am J Physiol 1981; 241:R203-12.

[26] Boyd R, Silk J. How Humans Evolved. New York: W.W. Norton and Company; 2003.

[27] McLoon SC. Alteration in precision of the crossed retinotectal projection during chick development. Science 1982; 215:1418-20.

[28] Jacobs DS, Perry VH, Hawken MJ

. The postnatal reduction of the uncrossed projection from the nasal retina in the cat. J Neurosci 1984; 4:2425-33.

[29] Lanser ME, Fallon JF. Development of the lateral motor column in the limbless mutant chick embryo. J Neurosci 1984; 4:2043-50.

[30] Lanser ME, Fallon JF. Development of the branchial lateral motor column in the wingless mutant chick embryo: Motorneuron survival under varying degrees of peripheral load. J Comp Neuro 1987; 261: 423-34.

[31] O’Leary DDM, Fawcett JW, Cowan WM. Topographic targeting errors in the retinocollicular projection and their elimination by selective ganglion cell death.  J Neurosci 1986; 6:3692-705.

[32] Katz MJ, Lasek RJ. Evolution of the nervous system: Role of ontogenetic mechanisms in the evolution of matching populations. Proc Natl Acad Sci USA 1978; 75:1349-52.

[33] Finlay BL, Slattery M. Local differences in the amount of early cell death in neocortex predict adult local specializations. Science 1983; 219:1349-51.

[34] Finlay BL, Wikler KC, Sengelaub DR. Regressive events in brain development and scenarios for vertebrate brain evolution. Brain Behav Evol 1987; 30:102-17.

[35] Williams RW, Herrup K.  The control of neuron number. The Annu Rev Neurosci 1988;11:423-53.

[36] DeBrul L. Structural evidence in the brain for a theory of the evolution of behavior. Perspect Biol Med 1960; 4:40–57.

[37] Armstrong E. Mosaic evolution in the primate brain: Differences and similarities in the hominoid thalamus. In: Armstrong E, Falk D, editors. Primate Brain Evolution. Methods and Concepts. New York: Plenum Press; 1982. P. 131-62.

[38] Barnea A, Nottebohm F. Seasonal recruitment of hippocampal neurons in adult free-ranging black-capped chickadees. Proc Natl Acad Sci USA 1994; 91:11217-21.

[39] Barnea A, Nottebohm F. Recruitment and replacement of hippocampal neurons in young and adult chickadees: an addition to the theory of hippocampal learning. Proc Natl Acad Sci USA 1996; 93:714-8.

[40] Goldman SA, Nottebohm F. Neuronal production, migration, and differentiation in a vocal control nucleus of the adult canary brain. Proc Natl Acad Sci USA 1983; 80:2390-94.

[41] Garamszegi LZ, Eens M. The evolution of hippocampus volume and brain size in relation to food hoarding in birds. Ecology Letters 2004; 7:1216.

[42] Clayton NS. Hippocampal growth and maintenance depend on food-caching experience in juvenile mountain chickadees (Poecile gambeli). Behav Neurosci 2001; 115:614-25.

 [43] Nilsson M, Perflilieva E, Johansson U, Orwar O, Eriksson P. Enriched environment increases neurogenesis in the adult rat dentate gyrus and improves spatial memory. J Neurobiol 1999; 39:569-78.

[44] Van Praag H, Christie BR, Sejnowki TJ, Gage FH. Running enhances neurogenesis, learning and long-term potentiation in mice. Proc Natl Acad Sci USA 1999; 96:13427-31.

[45] Kempermann G. Why New Neurons? Possible Functions for Adult Hippocampal Neurogenesis. J Neurosci 2002; 22(3):635-8.

[46] Jacobs LF, Spencer WD. Natural space-use patterns and hippocampal size in kangaroo rats. Brain Behav Evol 1994; 44:12532

[47] Gould E, Beylin A, Tanapat P, Reeves A, Shors TJ. Learning enhances adult neurogenesis in the hippocampal formation. Nat Neurosci 1999; 2:260-5.

[48] Kempermann G, Kuhn HG, Gage FH. More hippocampal neurons in adult mice living in an enriched environment. Nature 1997; 386:493-5.

[49] Kempermann G, Brandon EP, Gage FH. Environmental stimulation of 129/SvJ mice results in increased cell proliferation and neurogenesis in the adult dentate gyrus. Curr Biol 1998; 8:939-42.

[50] Jacobs LF. The economy of winter: phenotypic plasticity in behavior and brain structure. Biol Bull 1996; 191(1):92-100.

[51] Dukas R. Evolutionary Biology of Animal Cognition. Annu Rev Ecol Evol Syst 2004; 35:347-74.

[52] Pulsifer M. The neuropsychology of mental retardation.  J Int Neuropsychol Soc 1996; 2(2):159-76.

[53] Ernst M, Kimes A, London E, Matochik J, Eldreth D, Tata S, Contoreggi C, Leff M, Bolla K.  Neural Substrates of Decision Making in Adults With Attention Deficit Hyperactivity Disorder. Am J Psychiatry 2003; 160:1061-70.

[54] Kesslak JP, Nagata SF, Lott I, Nalcioglu O. Magnetic resonance imaging analysis of age-related changes in the brains of individuals with Down’s syndrome. Neurology 1994; 44:1039-45.

[55] Aylward EH, Li Q, Honeycutt NA, Warren AC, Pulsifer MB, Barta PE, Chan MD, Smith PD, Jerram M, Pearlson GD. MRI volumes of the hippocampus and amygdala in adults with Down’s syndrome with and without dementia. Am J Psychiatry 1999; 156:564-8.

[56] Greicius MD, Boyett-Anderson JM, Menon V, Reiss AL.  Reduced basal forebrain and hippocampal activation during memory encoding in girls with fragile x syndrome.  Dev Neurosci 2004; 15(10): 1579-83.

[57] Bilder RM, Bogerts B, Ashtari M, Wu H, Alvir JM, Jody D, Reiter G, Bell L, Lieberman JA. Anterior hippocampal volume reductions predict frontal lobe dysfunction in first episode schizophrenia. Schizophr Res 1995; 17:47-58.

[58] Tamminga CA, Thaker GK, Buchanan R, Kirkpatrick B, Alphs LD, Chase TN, Carpenter WT. Limbic system abnormalities identified in schizophrenia using positron emission tomography with fluorodeoxyglucose and neocortical alterations with deficit syndrome. Arch Gen Psychiatry 1992; 49(7):522-30.

[59] Sapolsky RM, Krey LC, McEwen BS. The neuroendocrinology of stress and aging: The glucocorticoid cascade hypothesis. Endocr Rev 1986; 7:284-301.

[60] Sapolsky RM. Why stress is bad for your brain. Science 1996; 273:749-50.

[61] Clutton-Brock TH, Harvey PH. Primates, brains and ecology. Journal of the Zoological Society of London 1980; 190:309-23.

[62] Gibson KR. Cognition, brain size and the extraction of embedded food resources. In: Else JGF, Lee PC, editors. Primate Ontogeny, Cognition and Social Behavior. Cambridge: Cambridge University Press; 1987.

[63] Sawaguchi T. Relationships between cerebral indices for ‘extra’ cortical parts and ecological categories in anthropoids. Brain Behav Evol 1989; 43:281-93.

[64] Sawaguchi T. The size of the neocortex in relation to ecology and social structure in monkeys and apes. Folia Primatologica 1992; 58:131-45.

[65] Jerison HJ. Evolution of the Brain and Intelligence. New York: Academic Press; 1973.

[66] Passingham RE. The brain and intelligence. Brain Behav Evol 1975; 11:1-15.

[67] Dunbar RIM. Neocortex size as a constraint on group size in primates. J Hum Evol 1992; 20: 469-93.

[68] Kinsey C, Lambert K. The maternal brain: Pregnancy and motherhood change the structure of the female mammal’s brain, making mothers attentive to their young and better at caring for them. Sci Am 2006; 294:72-9.

[69] Brender J. Down syndrome cluster in Pampa, Gray County – 1985. Internal report of the Texas Department of Health 1986; (unpublished).

[70] Smits L, Pedersen C, Mortensen P, van Os J. Association between short birth intervals and schizophrenia in the offspring. Schizophr Res 2004; 70(1):49-56.

[71] Jongbloet P, Zielhuis G, Pasker-de Jong P. Short pregnancy interval and reproductive disorders. Ned Tijdschr Geneeskd 2002; 146(31):1441-43.

[72] Doria-Rose V, Kim H, Augustine E, Edwards K. Parity and the risk of Down’s syndrome. Am J Epidemiol 2003; 158: 503-8.

[73] Clementi M, Bianca S, Benedicenti F, Tenconi R. Down syndrome and parity. Community Genet 1999; 2:18-22.

[74] Louhiala P. Risk indicators of mental retardation: changes between 1967 and 1981. Dev Med Child Neurol 1995; 37(7):631-6.

[75] Hultman C, Sparen P, Takei N, Murray R, Cnattingius S. Prenatal and perinatal risk factors for schizophrenia, affective psychosis, and reactive psychosis of early onset: case-control study. BMJ 1999; 318:421-26.

[76] Wilson E0. Sociobiology: The new synthesis. Cambridge, MA: Harvard Univ. Press; 1975.

[77] Siddiqi SU, Van Dyke DC, Donohoue P, McBrien DM. Premature sexual development in individuals with neurodevelopmental disabilities.  Dev Med Child Neurol 1999; 41(6):392-95.

[78] Johanson E: A study of schizophrenia in the male. Acta Psychiatr Scand Suppl 1958; 125

[79] Raschka LB. Paternal age and schizophrenia in dizygotic twins. The British Journal of Psychiatry 2000; 176:400-401

[80] van Os J, Selten J. Prenatal exposure to maternal stress and subsequent schizophrenia. The May 1940 invasion of the Netherlands. Br J Psychiatry 1998; 172:324-26.

[81] Brixey S, Gallagher B, McFalls J, Parmelee L. Gestational and neonatal factors in the etiology of schizophrenia. J Clin Psychol 1993; 49(3): 447-56.

[82] Selten J, van Duursen R, van der Graaf C, Gispen W, Kahn R. Second-trimester exposure to maternal stress is a possible risk factor for psychotic illness in the child. Schizophr Res 1997; 24: 258.

[83] Mc Intosh D, Mulkins R, Dean R. Utilization of maternal perinatal risk indicators in the differential diagnosis of ADHD and UADD children. Int J Neurosci 1995; 81:35-46.

[84] Fleming AS. Factors influencing maternal responsiveness in humans: usefulness of an animal model. Psychoneuroendocrinology 1988; 13:189-212.

[85] Dix DN. Why women decide not to breastfeed. Birth 1991; 18: 222-5.

[86] Goldstein D, Lenders J, Kaler S, Eisenhofer G. Catecholamine phenotyping: clues to the diagnosis, treatment, and pathophysiology of neurogenetic disorders. J Neurochem 1996; 67:1781-90.

[87] Breslau N, Brown G, DelDotto J, Kumar S, Ezhuthachan S, Andreski P, Hufnagle K. Psychiatric sequelae of low birth weight at 6 years of age.  J Abnorm Child Psychol 1996; 24(3):385-400.

[88] Mick E, Biederman J, Prince J, Fischer M, Faraone S. Impact of low birth weight on attention-deficit hyperactivity Disorder. J Dev Behav Pediatr 2002; 23(1):16-22.

[89] Gross S, Kosmetatos N, Grimes C, Williams M. Newborn head size and neurological status. Predictors of growth and development of low birth weight infants. Am J Dis Child 1978; 132(8):753-6.

[90] Wahlbeck K, Forsen T, Osmond C, Barker D, Eriksson J. Association of schizophrenia with low maternal body mass index, small size at birth, and thinness during childhood. Arch Gen Psychiatry 2001;58:48-52.

[91] Crespi EJ, Denver RJ. Ancient Origins of Human Developmental Plasticity. Am J of Hum Biol 2005; 17:44-54.

[92] Meaney M. Maternal care, gene expression, and the transmission of individual differences in the stress reactivity across generations.  Annu Rev of Neurosci 2001; 24:1161-92.

[93] Zhang T, Parent C, Weaver I, Meaney M. Maternal Programming of Individual Differences in Defensive Responses in the Rat. Ann NY Acad Sci 2004;1032:85-103

[94] Liu D, Diorio J, Day JC, Francis DD, Meaney MJ.  Maternal care, hippocampal synaptogenesis and cognitive development in rats.  Nature Neurosci 2000; 3(8):799-806.

[95] Oitzl M, Workel J, Fluttert M, Frosch F and De Kloet E. Maternal deprivation affects behavior from youth to senescence: amplification of individual differences in spatial learning and memory in senescent Brown Norway rats. Eur J Neurosci 2000; 12:3771-80.

[96] Ellenbroek BA, Cools AR. Maternal separation reduces latent inhibition in the conditioned taste aversion paradigm. Neurosci Res Comm 1995; 17: 27-33.

[97] Zhang L, Xing G, Levine S, et al. Maternal deprivation induces neuronal death. Soc Neurosci Abst 1997;23:1113.

[98] Diorio J, Weaver I, Meaney M. A DNA array study of hippocampal gene expression regulated by maternal behavior in infancy. Soc Neurosci Abst 2000; 26:1366.

[99] Bredy T, Humpartzoomian R, Cain D, Meaney M. The influence of maternal care and environmental enrichment on hippocampal development and function in the rat.  Neuroscience 2003; 118:571-6.

[100] Levy F, Melo A, Galef BG jr, Madden M, Fleming AS. Complete maternal deprivation affects social but not spatial learning in adult rats. Dev Psychobiol 2003; 43:177-91.

[101] Lin KN, Barela AJ, Chang M, Dicus E, Garrett S, Levine M, Oray S, McClure WO. Prenatal stress generates adult rats with behavioral and neuroanatomical similarities to human schizophrenics. Soc for Neuroscience Abs 1998; 24:796

[102] Schneider M, Roughton E, Koehler A, Lubach G. Growth and development following prenatal stress exposure in primates: an examination of ontogenetic vulnerability. Child Dev 1999; 70(2):263-74.

[103] Huttunen RO, Niskanen P. Prenatal loss of father and psychiatric disorders. Arch Gen Psychiatry 1978; 35, 429-31

[104] Lemaire V, Koehl M, Le Moal M, Brous DN. Prenatal stress produces learning ominida associated with an inhibition of neurogenesis in the hippocampus. Proc Natl Acad Sci USA 2000; 97(20): 11032-37.

[105] Yanagisawa M, Planel E, Ishiguro K, Fujita SC. Starvation induces tau hyperphosphorylation in mouse brain: implications for Alzheimer’s disease. FEBS Letters 1999; 461(3):329-33.

[106] Planel E, Yasutake K, Fujita SC, Ishiguro K. Inhibition of protein phosphatase 2a overrides tau protein kinase i/glycogen synthase kinase 3β and cyclin-dependent kinase 5 inhibition and results in tau hyperphosphorylation in the hippocampus of starved mouse. J Biol Chem 2001; 276(36):34298-306.

[107] Schwartz MW, Dallman MF, Woods SC. Hypothalamic response to starvation: implications for the study of wasting disorders. Am J Physiol 1995; 269: R949-57.

[108] Flier JS. Clinical review.94: What’s in a name? In search of leptin’s physiologic role. J Clin Endocrinol Metab 1998; 83:1407-13.

[109] Burkart JE, Fox RA, Rotatori AF. Obesity of mentally retarded individuals: prevalence, characteristics, and intervention. Am J Ment Defic 1985; 90(3):303-12.

[110] van Schrojenstein Lantman-De Valk H, Metsemakers J, Haveman M, Crebolder H. Health problems in people with intellectual disability in general practice: a comparative study. Fam Pract 2000; 17(5):405-07.

[111] Chaiwanichsiri D, Sanguanrungsirikul S, Suwannakul W. Poor physical fitness of adolescents with mental retardation at Rajanukul School, Bangkok. J Med Assoc Thai 2000; 83(11):1387-92.

[112] Pitetti KH, Rimmer JH, Fernhall B. Physical fitness and adults with mental retardation. An overview of current research and future directions. Sports Med 1993;16(1):23-56.

[113] Gunay-Aygun M, Cassidy SB, Nicholls RD. Prader-Willi and other syndromes associated with obesity and mental retardation. Behav Genet 1997; 27(4):307-24.

[114] O’Rahilly S, Farooqi I, Yeo G, Challis B. Minireview: Human Obesity-Lessons from Monogenic Disorders. Endocrinology 2003; 144(9):3757-64.

[115] Valencia M, Bennett P, Ravussin E, Esparza J, Fox C, Schulz L. The Pima Indians in Sonora, Mexico. Nutr Rev 1999; 57(5 Pt 2):S55-57.

[116] Barker D. Mother, Babies and Health in Later Life. Edinburgh: Churchill Livingstone; 1998.

[117] Barker D, Eriksson J, Forsen T, Osmond C. Fetal origins of adult disease: strength of effects and biological basis. Int J Epidemiol 2002; 31:1235-39.

[118] Gluckman P, Hanson M. The developmental origins of the metabolic syndrome. Trends Endocrinol Metab 2004; 15:183-7.

[119] Diamond J. The Double Puzzle of Diabetes. Nature 2003; 423: 599-602.

[120] Neel JV. Diabetes mellitus: a “thrifty” genotype rendered detrimental by “progress”? Am J Hum Genet 1962;14:353–62.

[121] Neel JV The thrifty genotype revisited. In: Kobberling J, Tattersall R, editors. The Genetics of diabetes mellitus. Amsterdam: Academic Press; 1982. P. 137-47.

[122] Neel, JV. The “Thrifty Genotype” in 1998, Nutr Rev 1999; 57(5 pt. 2): S2-9.

[123] Dixon L, Weiden P, Delahanty J, et al. Prevalence and correlates of diabetes in national schizophrenia samples. Schizophr Bull 2000; 26: 903-12.

[124] Felker B, Yazel JJ, Short D. Mortality and medical comorbidity among psychiatric patients: a review. Psychiatr Serv 1996; 47:1356-63.

[125] Ristow M. Neurodegenerative disorders associated with diabetes mellitus. J Mol Med 2004; 82:510-29.

[126] Bingley P, Douek I, Rogers C, Gale E. Influence of maternal age at delivery and birth order on risk of type 1 diabetes in childhood: prospective population based family study. BMJ 2000; 321:420-4.

[128] Jolly M, Sebire N, Harris J, Robinson S, Regan L. The risks associated with pregnancy in women aged 35 years or older. Hum Reprod 2000; 15(11): 2433-37.

[129] Marino B. Congenital heart disease in patients with Down’s syndrome: anatomic and genetic aspects. Biomed Pharmacother 1993; 47(5):197-200.

[130] Tubman T, Shields M, Craig B, Mulholland H, Nevin N. Congenital heart disease in Down’s syndrome: two year prospective early screening study.  BMJ 1991; 302(6790):1425-27.

[131] Spicer R. Cardiovascular disease in Down syndrome. Pediatr Clin North Am 1984; 31(6):1331-43.

[132] Kendrick T. Cardiovascular and respiratory risk factors and symptoms among general practice patients with long-term mental illness. Br J Psychiatry 1996; 169: 733-9.

[133] Davidson M. Risk of cardiovascular disease and sudden death in schizophrenia. J Clin Psychiatry 2002; 63: 5-11.

[134] Cooper SA. Clinical study of the effects of age on the physical health of adults with mental retardation. Am J Ment Retard 1997; 102(6):582-9.

[135] Barker D, Winter P, Osmond C, Margetts B, Simmonds S. Weight in infancy and death from ischemic heart disease. Lancet 1989; 866(3):57780.

[136] Eriksson J, Forsen T, Tuomilehto J, Osmond C, Barker D. Early growth and coronary heart disease in later life: Longitudinal study. Br Med J 2001; 322: 949-53.

[137] Ridley M. Nature Via Nurture: Genes Experience and What Makes Us Human. New York: Harper Collins; 2003.

[138] Gagneux P, Arness B, Diaz S, Moore S, Patel T, Dillmann W, Parkeh R, Varki A. Proteomic comparison of human and great ape blood plasma reveals conserved glycosylation and differences in thyroid hormone metabolism. Am J Phys Anthropol 2001; 115:99-109.

[139] Previc H. Thyroid Hormone Production in Chimpanzees and Humans: Implications for the Origins of Human Intelligence. Am J Phys Anthropol 2002;118:402-03.

[140] Crile G. Diseases peculiar to civilized man. New York: MacMillan; 1934.

[141] Rovet J, Hepworth S. Attention problems in adolescents with congenital hypothyroidism a multicomponential analysis.  J Int Neuropsychol Soc 2001; 7(6):734-44.

[142] Philibert R, Sandhu H, Hutton A, Wang Z, Arndt S, Andreasen N, Crowe R, Wassink T.   Population-Based association analyses of the HOPA^12bp Polymorphism for Schizophrenia and Hypothyroidism. Am J Med Genet 2001; 105: 130-34.

[143] Karlsson B, Gustafsson J, Hedov G, Ivarsson S, Annerén G. Thyroid dysfunction in Down’s syndrome: relation to age and thyroid autoimmunity. Arch Dis Child 1998; 79: 242-5.

[144] Connors JM, DeVito WJ, Hedge GA. Effects of food deprivation on the feedback regulation of the hypothalamic-pituitary-thyroid axis of the rat. Endocrinology 1985; 117(3):900-6.

[145] Gilbert ME. Alteration in synaptic transmission and plasticity in area CA1 of adult hippocampus following developmental hypothyroidism.  Brain Res Dev Brain Res 2004;148(1):11-8.

[146] Sandman CA, Barron JL, Barker L. Disregulation of the hypothalamic-pituitary-adrenal axis in the mentally retarded. Pharmacol Biochem Behav 1985; 23:21-6.

[147] Anwar A, Walker J, Frier B. Type 1 diabetes mellitus and Down’s syndrome: prevalence, management and diabetic complications. Diabet Med 1998; 15(2): 160-3.

[147] Bell A, Bhate M. Prevalence of overweight and obesity in Down’s syndrome and other mentally handicapped adults living in the community.  J Intellect Disabil Res 1992; 36(4): 359-64.

[148] Prasher V. Overweight and obesity amongst Down’s syndrome adults. J Intellect Disabil Res 1995; 39(5):437-41.

[149] Luke A, Sutton M, Schoeller D, Roizen N. Nutrient intake and obesity in prepubescent children with down syndrome. J Am Diet Assoc 1996; 96(12):1262-67.

[150] Allison DB, Fontaine KR, Heo M, et al. The distribution of body mass index among individuals with and without schizophrenia. J Clin Psychiatry 1999; 60: 215-20.

[151] Ryan MC, Thakore JH. Physical consequences of schizophrenia and its treatment: the metabolic syndrome. Life Sci 2002; 71:239-57.

[152] Lambert T. Hares and tortoises: differential neuroleptic-associated weight gain in the community. In: 7^th Biennial Australasian Schizophrenia Conference; 2002; October 24–26; Sydney: NSW.

[153] Hessl D, Rivera SM, Reiss AL. The Neuroanatomy and neuroendocrinology of fragile x syndrome. Mental Retardation and Developmental Disabilities Research Reviews 2004; 10:17-24.

[154] Wisbeck JM, Huffman LC, Freund L, et al. Cortisol and social stressors in children with fragile X: A pilot study. J Dev Behav Pediatr 2000;21:278-82.

[155] Chaney RH. Psychological stress in people with profound mental retardation. J Intellectual Disabil Res 1996; 40(4):305.

[156] Walker EF, Neumann C, Baum KM, Davis D, Diforio D, Bergman A. Developmental pathways to schizophrenia: Moderate effects of stress. Dev Psychopathol 1996; 8:647-55.

[157] Walker EF, Diforio D. Schizophrenia: A neural diathesis-stress model. Psychol Rev 1997; 104:667-85.

[158] Leonard WR, Robertson ML. Nutritional requirements and human evolution: A bioenergetics model. Am J Hum Biol 1992; 4:179-95.

[159] Leonard WR, Robertson ML. Evolutionary perspectives on human nutrition: The influence of brain and body size on diet and metabolism. Am J Hum Biol 1994; 6: 77-88.

[160] Leonard WR, Robertson ML. On diet, energy metabolism, and brain size in human evolution. Curr Anthropol 1996; 37:125-28.

[161] Kaplan H. The evolution of the human life course. In: Wachter KW, Finch CE, editors. Between Zeus and the Salmon – The biodemography of Longevity. Washington DC: National Academy Press; 1997. P. 175-211.

[162] Lancaster JB. The evolutionary history of human parental investment in relation to population growth and social stratification. In: Gowaty PA, editor. Feminism and evolutionary biology. New York: Chapman and Hall; 1997. P 466-89.

[163] Blurton Jones NG, Marlowe FW. The forager Olympics: does it take 20 years to become a competent hunter-gatherer? Salt Lake City: Human Behavior and Evolution Society; 1999.

[164] Dennett DC. Consciousness Explained. Boston: Little, Brown and Company; 1991.

[165] Dawkins R. The Selfish Gene. Oxford: Oxford University Press; 1976

[166] Brun A, Englund E. Regional pattern of degeneration in Alzheimer’s disease: neuronal loss and histopathological grading. Histopathology 1981; 5:549-64.

[167] Pearson RC, Esiri MM, Hiorns RW, Wilcock GK, Powell TP. Anatomical correlates of the distribution of the pathological changes in the neocortex in Alzheimer disease. Proc Natl Acad Sci USA 1985; 82:4531-34.