The following original articles are individual published works concerning similar topics:

Evolutionary Neuropathology: Understanding Neuropathological Disease in Terms
of Adaptation to Environment

Article I
Evolutionary Neuropathology & Congenital Mental Retardation
Do Environmental Cues Predictive of Maternal Deprivation Influence the Fetus to Minimize
Cerebral Metabolism in Order to Express Bioenergetic Thrift?
see below

Article II
Evolutionary Neuropathology & Down Syndrome
An Analysis of the Etiological and Phenotypical Characteristics of Down Syndrome Suggests
that it May Represent an Adaptive Response to Maternal Deprivation
click here

Article III
Schizophrenia & Phenotypic Plasticity:
Schizophrenia may represent a predictive, adaptive response to severe environmental adversity
that allows both bioenergetic thrift and a defensive behavioral strategy.
click here

Article IV
Stress Cascade: The Effects of Glucocorticoids on the Hippocampus.
Could Stress Signify the Presence of an Environment that is Inhospitable to Advanced
Cognition?  
click here

Article V
Evolutionary Neuropathology and Alzheimer’s Disease:
Preclinical Alzheimer’s Disease is an Adaptive, Metabolically Thrifty Compensation for
Diminished Foraging Capacity in Old Age
click here

Article VI
Discussion
click here

Article VII
Conceptualizing the autism spectrum in terms of natural selection & natural history: The solitary
forager theory
click here


Copyright  Jared Reser 06/05/04


Please send all inquiries to: jared@jaredreser.com

These articles are available at: www.evolutionaryneuropathology.net




Article I:


Evolutionary Neuropathology: Congenital Mental Retardation
Do Environmental Cues Predictive of Maternal Deprivation Influence the Fetus to Minimize
Cerebral Metabolism in Order to Express Bioenergetic Thrift?


Medical Hypotheses, Volume 67, Issue 3, 2006, Pages 529-544



Abstract

This article will propose that humans have an adaptive vulnerability to certain forms of mental
retardation, specifically, neuropathological disorders that cause decreased energy expenditure
in the hippocampus and the cerebral cortex.  This hypothesis will be analyzed in terms of 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.  For example, a malnourished mother has an increased propensity to give birth to
offspring that feature a “thrifty phenotype” which permits highly efficient calorie utilization,
increased fat deposition and a sedentary nature.  This article interprets several prenatal
occurrences, including maternal malnourishment, low birth weight, multiparity, short birth interval,
advanced maternal age and maternal stress- which are currently identified by the
epidemiological literature as risk factors for neuropathology- to be environmental cues that
communicate to the fetus that, because it will be neglected of maternal investment, developing a
metabolically conservative brain will be the most effective ecological strategy.  

Success in hunting and foraging in mammals, primates and especially humans is known to be
dependent on prolonged maternal investment.  Low levels of maternal care are known to result in
low survivorship of offspring, largely 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 article will suggest 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 article do not cause damage to vital
homeostatic systems; most simply decrease the size and energy expenditure of the cerebral
cortex and the hippocampus, the two structures known to show plasticity during changes in
ecological rigor in vertebrates.  Also, many disorders that present comorbidly with
neuropathology, such as tendency toward obesity, decrement in 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.

Determining the relative impact of evolutionary causation on neuropathological disease should
prove informative for medical and gene therapeutic treatment modalities.  Furthermore, use of
the maternal deprivation paradigm presented here may help researchers more precisely identify
the risk factors that determine cognitive trajectory.  

Introduction

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].  The thrifty phenotype
hypothesis [3,4] has been used widely to interpret studies showing that maternal malnutrition is a
strong 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 increased risk of negative 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 article will focus on several risk factors for human neuropathology 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 both nourishment and important survival information (memes) 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 mental retardation excluding
Down syndrome [9], and mental retardation of unknown cause [10] in offspring.  It is clear that an
older mother is probabilistically more likely to die before she is able to 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 memetic transference.  It may be instructive to interpret the epidemiological
data to be suggesting that older mothers engage in fetal programming- they switch on genes in
the fetus that will elicit neuropathology- decreasing their child’s reliance on them by lowering their
caloric requirements and the inhibitory pressures on their instincts and natural reflexes.  

Anthropologists contend that the human brain was able to evolve to such large proportions,
despite the accompanying metabolic costs, because humans greatly benefited from the ability to
store crucial lessons about 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 that are deprived of maternal
instruction, and thus deprived of many valuable lessons, might have had difficulty procuring 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 in order to assume a resting metabolic rate better suited for meme deprivation- the
environment encountered after birth.  

Apes and monkeys provide far less parental investment than humans; they have far smaller
brains and they inhabit a less mentally demanding place on the food chain.  It is likely that the
niche filled by maternally deprived, mentally retarded humans would have closely resembled the
less cognitively rigorous niche of our smaller brained, primate cousins.  We will also concentrate
on other parallels between mentally retarded individuals and apes 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.


Background

Mental Retardation and Evolutionary Medicine
Today, the costs of mental retardation (MR) are well documented but the defensive
manifestations may be hidden because of discrepancies between our modern and ancestral
environments.  Many traits that are known to have been defensive in the ancestral environment
are now seen as maladaptive in the present (“environmental mismatch”) and the science of
evolutionary medicine attempts to identify and characterize these traits.  Williams and Nesse [16]
suggest that in order to show that a trait may be a form of evolutionary medicine, it is important to
provide evidence that the trait is relatively prevalent, that it is heritable and that susceptibility
varies within populations.  It is also necessary to show how the benefits associated with the trait
may have outweighed the costs [16].  Researchers have identified many such “pathological”
conditions such as anxiety, cystic fibrosis, diabetes mellitus, diarrhea, fever, inflammation,
obesity, pain, sneezing, sickle cell anemia and vomiting and have helped to show that they
actually represent evolved defenses [17-19].  

Introduction:
In this section we will focus on several risk factors for mental retardation that may be associated
with either maternal mortality, burden on maternal resources or fetal malnourishment.  These risk
factors include low birth weight, multiparity, short birth intervals, advanced maternal age, obstetric
complications and maternal stress.  We will assume that such risk factors may be associated
with maternal deprivation or the impairment of a mother’s ability to transfer both nourishment and
important survival information (memes) 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) (Claycomb et al., 2004), Down’s Syndrome (Hook, 1981), severe
mental retardation excluding Down syndrome (McQueen et al. 1987), and mental retardation of
unknown cause (Croen et al., 2001) in offspring.  It is clear that an older mother is
probabilistically more likely to die before she is able to provide the two decades of 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
memetic transference.  This is why I interpret the epidemiological data to be suggesting that
older mothers engage in fetal programming- they turn on genes in the fetus that will elicit mental
retardation- decreasing their children’s reliance on them by lowering their child’s caloric
requirements and by lowering the inhibitory pressures on their child’s instincts and natural
reflexes.  

Anthropologists contend that the human brain was able to evolve to such large proportions,
despite the accompanying metabolic costs, because humans greatly benefited from the ability to
store crucial lessons about food extraction and hunting (Kaplan et al. 2000, Milton 1999, Stanford
1999, 2001).  The human ecological niche is well known to be cognitively rigorous and skill
intensive (Tooby& DeVore 1987) and so large brains were valuable because they facilitated the
acquisition, storage and implementation of these lessons (Kaplan et al. 2000).  Knowing this, it
seems logical to assume that an individual that is deprived of parental instruction, and thus
deprived of many valuable lessons, might have had difficulty procuring food to meet its metabolic
needs.  Therefore, those individuals who will be deprived of parental investment should benefit
from inhibiting the growth of metabolically excessive nerve tissue in order to assume a resting
metabolic rate better suited for meme deprivation- the environment encountered after birth.  

Ape and monkey parents provide less parental investment than do human parents and so it is
likely that the niche filled by parentally deprived, mentally retarded humans would have closely
resembled the less cognitively rigorous  niche of our smaller brained, primate ancestors.  We will
also concentrate on other parallels between mentally retarded individuals and apes including
cerebrocortical and hippocampal size, thyroid activity, and regulation of the HPA axis and we will
conclude that these similarities imply that both groups would have shared a similar foraging
strategy in ancestral times.


Background

Mental Retardation and Evolutionary Medicine
Today, the costs of mental retardation (MR) are well documented but the defensive
manifestations may be hidden because of discrepancies between our modern and ancestral
environments.  Many traits that are known to have been defensive in the ancestral environment
are now seen as maladaptive in the present (“environmental mismatch”) and the science of
evolutionary medicine attempts to identify and characterize these traits.  Williams and Nesse [16]
suggest that in order to show that a trait may be a form of evolutionary medicine, it is important to
provide evidence that the trait is relatively prevalent, that it is heritable and that susceptibility
varies within populations.  It is also necessary to show how the benefits associated with the trait
may have outweighed the costs [16].  Researchers have identified many such “pathological”
conditions such as anxiety, cystic fibrosis, diabetes mellitus, diarrhea, fever, inflammation,
obesity, pain, sneezing, sickle cell anemia and vomiting and have helped to show that they
actually represent evolved defenses [17-19].  

Many articles in the last decade have analyzed various forms of psychopathology (anxiety,
bipolar disorder, depression, obsessive compulsive disorder, etc.) in terms of evolutionary
theory and evolutionary medicine [19,20], and this area of research is often referred to as
“evolutionary psychopathology.”  Mental retardation and the underlying neuropathology though,
have not been analyzed in terms of evolutionary medicine and have not received a great deal of
theoretical attention.  Unlike the present article, evolutionary analyses of mental retardation are
typically population-based and fail to offer an explanation for why the disease arises in affected
individuals [21].  

It can surely be argued that the rather diverse assortment of relatively prevalent forms of mental
retardation are unrelated, purely pathological, and have no evolutionary significance.  However,
this article will explore the assertion that some forms are related and do represent a type of
contingency based, ecological strategy.  It is not expected that this paradigm will apply to every
form of organic, congenital neuropathology but several diseases will be identified as candidates.
It is hoped that this article influences researchers to use the present paradigm to identify other
candidates.  Through an analysis of epidemiological, etiological, neuroantomical and
physiological similarities between attention deficit hyperactivity disorder, Down syndrome,
microcephaly, schizophrenia, syndromic mental retardation and mental retardation of unknown
cause, I hope to characterize their evolutionary significance.


The Metabolic Costs Associated with Brain Cells
It is clear that 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].  In fact, 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 very expensive 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 acts
to minimize 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].  It is widely believed that this mechanism may be
related to an ecological strategy where terminating extraneous neurons increases metabolic
efficiency [32-35].

Research has shown that even within populations of a single species, a large degree of variation
in absolute number of neurons exists between individuals.  Intraspecific diversity in 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 article 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 factors.


Phenotypic Plasticity Affects Hippocampal Size in Mammals and Birds
Neuron number has been known to fluctuate in individual animals and these fluctuations often
seem to 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 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 spatial tasks also increase hippocampal size in food caching
birds [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 size 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 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 to be an ecological strategy [45,51].

Individual humans that are destined to be deprived of maternal investment and meme
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
article, all of which feature decreased hippocampal volume, may be analogous to the phenotypes
of other enrichment deprived mammals that are forced to employ less complicated foraging
strategies.


Neuropathology May Influence Animals to Adopt a Less Cognitively Rigorous Niche
One of the most consistent and conspicuous findings in ADHD, Alzheimers,  Down’s syndrome,
the stress cascade effect and schizophrenia is disproportionately small size or hypometabolism
of the hippocampus (see figure below).  The neocortex is also relatively diminished in each.    


Mental Retardation May Influence Animals to Adopt a Less 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.  

Disease                        Hippocampal Diminishment and/or Hypometabolism
ADHD                                 Yes (Ernst et al., 2003)
Alzheimer’s                        Yes (Brun et al., 1981; Pearson et al 1985)
Down Syndrome                Yes (Kesslak et al., 1994; Aylward et al., 1999)
Schizophrenia                    Yes (Bilder et al., 1995; Tamminga et al. 1992)
Stress Cascade                 Yes (Sapolsky 1986; 1996)

The cerebral cortex and hippocampus, are thought to be very important in sophisticated hunting
and food extraction techniques.  Clutton-Brock and Harvery [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 as well as 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 made marked comments 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 and the evolution of
these types of adaptations is the domain of optimal foraging theory (OFT)[26]. OFT is often used
to explain subtle variations in metabolic processes and is applied to anthropological,
primatological and zoological phenomena.  It makes sense, in terms of OFT, that if the most
prevalent forms of mental retardation 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 and utilization of ecologically relevant information, the cerebral
cortex and the 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, and this article is
attempting to show that fetuses down-regulate the same activity when preparing for maternal
deprivation.


Results / Pertinent Data

The Epidemiological Risk Factors that Link Neuropathology to Maternal Deprivation
This section will identify specific epidemiological risk factors for neuropathology, which might be
related to deficits in maternal investment.

As mentioned previously, advanced maternal age at birth is one of the most powerful predictors
of ADHD [7], Down syndrome [8], severe mental retardation excluding Down syndrome [9], and
mental retardation of unknown cause [10] in offspring.  A human mother that is older is more
likely to die before she is able to provide the nearly two decades of maternal investment and
memetic transference that is required to enable her offspring to become self-sufficient within the
notoriously 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.  It should be instructive to identify the proximate
factors that cause the brain of the human fetus to be vulnerable to physiological indicators of
maternal age.

Short birth interval, a risk factor for Down syndrome [69], schizophrenia [70] and other
neurodegenerative disorders [71], is also associated with increased burden on maternal
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 is
more likely that it will survive to reproductive age.  

The same reasoning applies to multiple birth, which is also a significant risk factor for certain
forms of human mental retardation including Down syndrome [72,73], general mental retardation
[74], mental retardation 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
neuropathology in an ecological strategy by associating it with the r-strategy.  For this reason, it
is also interesting to note that mental retardation is strongly associated with precocious puberty
[77], another characteristic of the r-strategy.

Advanced paternal age is also a risk factor for schizophrenia and some 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 is a strong relationship between maternal stress during pregnancy and
neurodevelopmental disorders in offspring [80-83].  A mother that has been 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.  In fact, many studies
have shown that high levels of maternal stress in humans are associated with impoverished
childcare [84-86].

Very low birth weight is a very strong perinatal 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], mental retardation
of unknown cause [10], microcephaly [89] and schizophrenia [75,90]. These relationships must
be explored in more detail, but this preliminary evidence supports the hypothesis that
neuropathology may be a predictive, adaptive response to nutritional deprivation and
environmental adversity, and another nosological facet of the thrifty phenotype phenomenon.




Associated Disorders                                References

Advanced Maternal Age
Down Syndrome                                                  Hook, 1981
ADHD                                                                  Claycomb et al., 2004
Mental Retardation Excluding Down Syndrome   McQueen et al. 1987
Mental Retardation of Unknown Cause               Croen et al., 2001

Advanced Paternal Age
Schizophrenia                                                     Johansen, 1958; Raschka, 1998;
                                                Malaspina et al, 2001; Dalman et al., 2002; Zammit,2003

Advanced Grandmaternal Age
Down Syndrome                                                 Aagesen et al., 1984

Obstetric Complications
Schizophrenia                                                    Verdoux et al., 1993
ADHD                                                                 Milberger et al., 1997
Severe Psychopathology                                   Eaton et al., 2001
Neurodevelopmental Disability                           Taylor et al., 1985        

Maternal Infection
Schizophrenia                                                     Mednick et al., 1988

Short Birth Interval
Down Syndrome                                                  Brender 1986
Other Neurodegenerative Disorders                   Jongbloet 2002
Schizophrenia                                                     Smits, 2004

Multiple Births
Down’s syndrome                                                 Doria-Rose et al., 2003; Clementi et al. 1999
Mental Retardation                                               Louhiala, 1995
Mental Retardation of Unknown Cause                Croen et al., 2001
Schizophrenia                                                      Hultman et al., 1999;       
                  

Maternal Stress
Schizophrenia                                                      van Os et al., 1998; Brixey et al., 1993; Selten, 1997
ADHD                                                                   McIntosh et al., 1995


Very Low Birth Weight
ADHD                                                                   Breslau et al., 1996; Mick et al., 2002        
Mental Retardation of Unknown Cause                Croen et al., 2001
Microcephaly                                                        Gross et al., 1978
Schizophrenia                                                      Wahlbeck et al., 2001; Hultman et al., 1999

 
Analogous / Homologous Neuropathological Responses to Maternal Deprivation in Rats
It has been established that many other animals share similar plastic responses to environmental
cues and this requires us to concede that our own 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.  In fact, a well investigated mouse model for the association between maternal
deprivation and hippocampal neuropathology [92,93] provides a wealth of relevant information.  
The offspring of 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 also results in the disruption of
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].  The maternal deprivation model
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 physical presence or
absence of a mother, but instead, 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, it would seem that 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].  It is clear that this fetal response to stress in rats
and monkeys is very similar to the neuropathological responses to stress that 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 and adequate meme
transference.  

Healthy, normal 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.


Other Ecologically Significant Traits that Present With Neuropathology

Animals Respond Plastically to Starvation in Order to Minimize Energy Expenditure
Many animals are well known to demonstrate consistent plastic responses to starvation that help
to minimize energy expenditure.  Starvation evokes several physiological changes, the most
dramatic of which include suppression of metabolic rate, reduction of thyroid hormone levels and
growth hormone levels, a reduction in fertility (through the suppression of gonadal function) and
an increased activation of the hypothalamic-pituitary-adrenal axis [107,108].  Many forms of
neuropathology feature these same physiological alterations and I will argue that this is because
maternally deprived humans in the environment of evolutionary adaptedness (EEA) would have
benefited from the same physiological alterations as starving animals.
 

Lower Metabolic Rates in Individuals with Mental Retardation
Individuals deprived of maternal investment would probably be forced to survive in a less
cognitively demanding place on the food chain, for instance they might have to settle for less
calorie rich foods and smaller meals.  Correspondingly, many forms of mental retardation 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 in the retarded
population, and points out that eating style does not seem to be the cause [109].  Obesity and
musculo-skeletal impairment have been found to be significant health problems associated with
both intellectual disability [110] and mental retardation [111].  Another analysis points out that the
majority of studies that evaluated the cardiovascular fitness level of adults with mental retardation
have reported levels representative of a highly sedentary population [112].  

It is also important to note that many forms of syndromic mental retardation 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 that predispose mentally retarded individuals to obesity, probably only represent a
liability in our modern environment.  These genes were most probably an asset to survival in the
Plio-Pleistocene because they would have caused the mentally retarded to conserve calories.  
The deprived conditions faced by the mentally retarded were probably analogous, in some ways,
to those encountered by the ancestors of modern groups with high incidence of obesity such as
the Pima Indians (who have been studied by Valencia et al. [115]).  This propensity, seen in MR
individuals, may also be analogous to the increased risk of obesity and the metabolic syndrome
seen in low birth weight babies which is widely thought to be a predictive, adaptive response
[116-118].  

Many forms of mental retardation that feature low muscle tone and low metabolic rates also
feature very low metabolic rates in infancy.  This infantile hypotonia would have allowed these
infants a low metabolism thereby ensuring that 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 MR 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.

Mental Retardation and Diabetes
A currently popular theory, James Neel’s thrifty gene hypothesis, contends that the genes for
diabetes provide an adaptive advantage that makes their bearers less susceptible to starvation
(Neel 1962, 1982, 1999).  One should expect that individuals that were deprived of parental
investment might be more susceptible to starvation.  It is recognized that several
neurodegenerative disorders including Alzheimers disease, Bardet-Biedl syndrome, Down
syndrome, Prader-Willi syndrome, Schizophrenia (Dixon et al., 2000; Felker et al., 1996), Turner
syndrome, Werner syndrome and many others are associated with increased incidence of
diabetes mellitus (Ristow, 2004).  

It is very important to mention that the risk for childhood (Bingley et al., 2000) and gestational
(Jolly et al., 2000) diabetes increases rapidly with maternal age.  This shared susceptibility to
advanced maternal age creates a parallel between neuropathology and diabetes and further
suggests that both neuropathology and advanced maternal age may be associated with a thrifty
phenotype.

Mental Retardation and Cardiovascular Disease
Heart disease and cardiovascular disease have been associated with Down syndrome [129-
131], schizophrenia [132,133] general mental retardation [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 and 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 in order to mitigate
the risk of starvation.  

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 serious strain on their
“thrifty” heart and makes them susceptible to heart disease [137].  For these reasons the heart
disease that is characteristic of the Down syndrome, schizophrenic, and other MR phenotypes
may represent yet another method of energy conservancy.


Mental Retardation and Hypothyroidism
One of the first major endocrinological differences found between humans and apes is a marked
increase in thyroid output in humans [138,139].  Not just apes, but almost all other mammals have
a larger adrenal glands 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 constant energy supply that
their hunting niche demanded.  I argue that the MR niche would have closely resembled the less
strenuous foraging niche seen in apes and monkeys and so it makes sense that an MR
phenotype 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:

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.  


Mental Retardation and Stress
A largely disproportionate number of people with mental retardation have an up-regulation of the
hypothalamic-pituitary-adrenal axis and they are particularly susceptible to stress and stress
diseases [146].  They react to only mildly threatening stimuli with an exaggerated adrenal/stress
response.  Maternally deprived rats, with poorly developed hippocampi, show the same
exaggerated adrenal/stress response [93].  Zhang et al, emphasize that this fundamental
reliance on stress is part of an ecological strategy that allows deprived rats rapid access to
energy stores in order to react 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
threat than to continually mobilize energy stores as thyroid hormones are well known to do [139].  
It is possible that individuals with neuropathology and hypothyroidism, like their animal
analogues, would have benefited from the ability to conserve energy that would have been
exhausted had they had a proportionately larger thyroid.  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.  

Individuals deprived of parental guidance probably had much more difficulty in assessing
dangerous situations 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.  Similar adaptive benefits have been proposed to explain the link
between maternal deprivation and the fetal programming of the stress response strategy in rats
[93].


Associated Thrifty Disorder                Reference
Cardiovascular Disease
Down syndrome                                     Marino, 1993; Tubman et al., 1991; Spicer, 1984 [129-131]
Mental Retardation                                Cooper, 1997 [134]
Schizophrenia                                         Kendrick 1996; Davidson 2002 [132,133]

Diabetes
Down syndrome                                     Anwar et al., 1998 [147]
Other Neurodegenerative Dis.             Ristow, 2004 [125]
Schizophrenia                                         Dixon et al., 2000; Felker et al., 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 et al., 1992; Prasher 1995; Luke et al., 1996 [147-149]
Other Neurodegenerative Dis.              O’Rahilly et al., 2003 [114]
Other Forms of Syndromic MR            Gunay-Aygun et al., 1997 [113]
Schizophrenia                                         Allison et al., 1999; Ryan et al., 2002; Lambert 2002[151-152]

Exaggerated Stress Response
Mental retardation                                  Sandman et al., 1985 [146]
Fragile X                                                   Hessl et al., 2004, Wisbeck et. al. 2000 [153-154]
Profound Mental Retardation               Chaney, 1996 [155]
Schizophrenia                                         Walker et al., 1996; 1997 [156,157]


Fitting this Theory into an Anthropological Context
It is thought that highly productive yet very-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 EEA selected individuals most actively on the basis of 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 relatively large amounts of meat [158-160] made
up a large part of the hunter/gatherer diet in the EEA.  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 it absolutely requires parental and social
guidance [11].  In foraging groups babies that were deprived of maternal interaction and
investment were at an extreme disadvantage because they would probably not properly learn the
language, would probably not 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 strategies associated with human hunting
and gathering are extremely sophisticated [12,163].  In fact, chimpanzees are known to become
fully capable foragers within their first decade [11] whereas most human hunter-gathers are not at
their peak rate of productivity until mid adulthood [163].  These points considered, it would seem
that an individual that was 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 must have been strong in the EEA.

A hominid, or early human, that was mentally retarded 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 MR diet would have likely consisted of small
game, easily accessible vegetation, insects and other invertebrates, dried fruit, and other
relatively low quality foods that are easy to extract.  The MR propensity for a lower metabolism
would have allowed such a moderate diet to sustain their simple foraging activities.  It is
conceivable that the MR diet would have been supplemented by the efforts of close kin and
community members; however, it is likely that it would have closely resembled that of monkeys
and apes.  

It is a common observation that carnivores, unlike herbivores, raised in captivity do not thrive
when released into the wild [11].  To be successful in their specialized niche carnivores must
receive early training, and must 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 MR individual
may be analogous to the herbivore’s because both enjoy relative independence of parental
investment.  

The fossil record shows that, for an extended period of time, many human-like hominids had very
small brains.  The huge variability in brain size in hominids found in the fossil record is proof that
the near 1400cc 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 “deficiencies”
seen in MR individuals may have analogues in extinct hominids.  



The Psychological Benefits Neuropathology May Confer on Deprived Individuals

Cognitive Noise
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 intimately related to a
concept that I will term “cognitive noise.”  Cognitive noise consists of any thoughts,
conceptualizations or cognitions that will direct, motivate or in any way effect the future behavior
of an animal without producing a survival advantage for it.  I suggest that if it were possible to
increase the intelligence of an r-selected animal, without changing its ecological setting or
increasing the amount of parental instruction it receives, that the animal’s fitness would only be
hindered, due to an increased proclivity for making irrelevant or fallacious conceptualizations.  

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 hunter or 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 improperly employ its
ability for mental analysis and create conceptualizations and mental systematizations that do not
facilitate threat avoidance, feeding or reproduction.  Such an animal may also frequently engage
in extraneous thinking, which could interfere with its ability to remain vigilant.  I argue that the
metabolically expensive, neurological organ that allows complex analysis in K-selected animals
(the brain) 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, and yet we do not
see this.

“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 (fish, 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.  Because the brain of a
maternally deprived animal will naturally expend more energy than it allows the animal to seek out
and obtain, the best strategy to dis-inhibit instinct is the one characterized by “neuropathology.”  
Thus, neuropathology in effect, minimizes the organism’s reliance on nurture (memes) and
maximizes their reliance on nature (genetic instincts).

1) Cognitive noise is directly proportional to encephalization.

2) Cognitive noise is inversely proportional to parental investment.

3) Cognitive noise, by definition, is inversely proportional to reproductive success.






























Examples of the Cognitive-Ecological Continuum in the Animal Kingdom
Sea squirts in Japanese seas metabolize their own brains once they have permanently attached
themselves to a rock [164].  This is evidence of adaptive “neuropathology” at work in the animal
world.  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 own
cognitive capabilities in order to decrease unnecessary energy expenditure.  In other words, a
change in its ecological niche obviates the need for encephalization and elicits
“neuropathological” alteration.

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
allows this) to ensure copulatory efficiency.  Dawkins (possibly informed by the research of Ken
Roeder) explains that by removing the male’s head the female insures 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.



Discussion and the Introduction of an Important Concept: Meme Utility

I offer the concept of “meme utility” to generalize some of the claims made in this paper.  I define
meme utility as the measure of the survival advantage that the utilization of memes provides for
an individual animal- where memes are units of behavioral information that can be transferred
from one animal to another [165].  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
important 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 a “decephalization” strategy.  Observations like these suggest that clinical neuroscientific
phenomena may be explicable in terms of ethology, bioanthropology, bioenergetics and
memetics.  

A similar relationship may be applied to explain the stress cascade phenomenon. When meme
utilization is effective a mature animal will often experience neuroendocrinological 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 metabolic function, a “pathophysiological” phenomenon known as the
stress cascade response [59,60].  The stress cascade may represent an ecological strategy to
minimize reliance on ineffective memes, and reemphasize instinct, by decreasing hippocampal
energy expenditure.  

The concept of meme utility can also be applied to Alzheimer’s and senile dementia. Natural
aging and senescence are known to hinder human physical capabilities and it is physical health
and strength that are necessary to utilize the memes previously stored for human hunting and
foraging.  Therefore, it would make sense that someone who was no longer physically able to
utilize the information, should experience low meme utility and should thus benefit from
metabolizing less energy in the areas responsible for storing the information.  This cognitive
impairment is seen in the early and middle stages of Alzheimer’s disease and, just like the other
disorders, the metabolic deficit is most readily apparent in the hippocampus [166,167].



Conclusion

It seems that maternal deprivation may be a powerful and informative indicator of environmental
quality that has profound predictive affects on the developing fetus. This hypothesis cannot be
fully substantiated; however, because of the scarcity of related research.  It is evident that much
more work is needed to define the parameters of the influence of maternal deprivation on
congenital neuropathology.  

Unfortunately, most forms of mental retardation cannot yet be effectively treated and providing
care for the large number of retarded individuals puts a large strain on present day economies.  
However, providing a comprehensive, evolutionary explanation for susceptibility to retardation
may explain the large prevalence in human populations and may also help to inform psycho-
social, bio-medical and gene therapeutic treatment strategies.

I hope that 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, then parents can be instructed how best
to minimize inadvertent exposure of the fetus, and child, to neuropathology inducing
environmental cues.  


This article has been an introduction to the concepts and relationships that I will refer to in
subsequent sections.  Please read on for more evidence.



To continue to section II please click here.




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; 44:125 32

[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 defecits
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 HOPA12bp 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: 7th 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.




To continue to artilce II please click here.