ArticlePDF AvailableLiterature Review

Abstract and Figures

Over the past three decades, developmental neurobiologists have made tremendous progress in defining basic principles of brain development. This work has changed the way we think about how brains develop. Thirty years ago, the dominant model was strongly deterministic. The relationship between brain and behavioral development was viewed as unidirectional; that is, brain maturation enables behavioral development. The advent of modern neurobiological methods has provided overwhelming evidence that it is the interaction of genetic factors and the experience of the individual that guides and supports brain development. Brains do not develop normally in the absence of critical genetic signaling, and they do not develop normally in the absence of essential environmental input. The fundamental facts about brain development should be of critical importance to neuropsychologists trying to understand the relationship between brain and behavioral development. However, the underlying assumptions of most contemporary psychological models reflect largely outdated ideas about how the biological system develops and what it means for something to be innate. Thus, contemporary models of brain development challenge the foundational constructs of the nature versus nurture formulation in psychology. The key to understanding the origins and emergence of both the brain and behavior lies in understanding how inherited and environmental factors are engaged in the dynamic and interactive processes that define and guide development of the neurobehavioral system.
The major events of gastulation occur between E13 and E20. (a) The onset of gastrulation is marked by the formation of the primitive streak and the primitive node. The primitive streak provides an opening to deeper embryonic layers. The primitive node is a critical molecular signaling center. On E13, cells from the epiblast layer begin to migrate toward the primitive node and streak (arrows). The dotted line indicates the cross-sectional view shown in panel b. (b) The migrating cells first move to the primitive streak and then change direction and move down and under the upper layer (arrows). As the cells pass the node they receive molecular signals that induce gene expression in the migrating cells. By the end of gastrulation, the hypoblast layer is replaced by the newly formed endodermal layer and the epiblast layer by the ectodermal layer. Between these layers the mesodermal layer forms. (c) Once under the upper layer, the cells change direction and begin migrating rostrally under the upper layer (arrows). The first cells to migrate form the most rostral regions of the newly forming endodermal and mesodermal layers. Later migrating cells form progressively more caudal regions of the layers. (d) Cells that migrate along the axial midline send molecular signals that induce cells in the overlying epiblast layer to differentiate into neuroectodermal cells (gray rectangular band) which are the neural progenitor cells. Migrating cells also receiving a second set of signals from the node that induce anterior or posterior fate in different subpopulations of the neurectodermal cells. Early migrating cells signal anterior fate in the progenitor cells, while late migrating cells signal posterior fate.
… 
Content may be subject to copyright.
CHAPTER 1
Brain development and the nature versus nurture
debate
Joan Stiles*
Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
Abstract: Over the past three decades, developmental neurobiologists have made tremendous progress
in defining basic principles of brain development. This work has changed the way we think about how
brains develop. Thirty years ago, the dominant model was strongly deterministic. The relationship
between brain and behavioral development was viewed as unidirectional; that is, brain maturation
enables behavioral development. The advent of modern neurobiological methods has provided
overwhelming evidence that it is the interaction of genetic factors and the experience of the individual
that guides and supports brain development. Brains do not develop normally in the absence of critical
genetic signaling, and they do not develop normally in the absence of essential environmental input.
The fundamental facts about brain development should be of critical importance to neuropsychologists
trying to understand the relationship between brain and behavioral development. However, the
underlying assumptions of most contemporary psychological models reflect largely outdated ideas
about how the biological system develops and what it means for something to be innate. Thus,
contemporary models of brain development challenge the foundational constructs of the nature versus
nurture formulation in psychology. The key to understanding the origins and emergence of both the
brain and behavior lies in understanding how inherited and environmental factors are engaged in the
dynamic and interactive processes that define and guide development of the neurobehavioral system.
Keywords: brain development; behavioral development; nature v nurture; plasticity; embryo; gastrula-
tion; gene expression; genetic signaling; cortical area; cortical reorganization; genetic constraints;
environmental constraints; temporal constraints.
Over the past three decades, developmental
neurobiologists have made tremendous progress
in defining basic principles of mammalian brain
development (Stiles, 2008). These advances extend
to all levels of the developing system, from
understanding the role of gene expression to the
organization of neocortex. With those advances
have come fundamental changes in the underlying
*Corresponding author.
Tel.: þ1-858-534-2567; Fax: +1-858-822-1602
E-mail: stiles@ucsd.edu
O. Braddick, J. Atkinson and G. Innocenti (Eds.)
Progress in Brain Research, Vol. 189
ISSN: 0079-6123
Copyright Ó2011 Elsevier B.V. All rights reserved.
3DOI: 10.1016/B978-0-444-53884-0.00015-4
models of how this complex biological system
emerges. Thirty years ago, the dominant model
was strongly deterministic. The relationship
between brain and behavioral development was
viewed as unidirectional; brain maturation was
thought to enable behavioral development. In con-
trast to older maturational models, the emerging
picture of brain development is of a dynamic and
adaptive system that is constrained by both
inherited factors and the experience of the organ-
ism (Gottlieb, 2007; Keller, 2000a; Lehrman,
2001; Morange, 2001; Moss, 2003; Stiles, 2008).
Normal brain development requires the expression
of very specific genes, but just as important are the
specific kinds of input the organism receives.
While this progress in understanding the
biological bases of brain development is perhaps
inherently interesting, it is legitimate to ask
whether these developments in neurobiology
have implications for other fields. Specifically, is
it important for investigators studying other
aspects of human development to know about
brain development? I will argue in this chapter
that it is, but the question is why?
Knowledge of contemporary models of brain
development is important because, in fact, most tra-
ditional models of behavioral development rely on
assumptions about biological development. But
the models most behavioral scientists evoke are
not current, and thus their underlying assumptions
about critical issues concerning theorigins of behav-
ior are out of date. Alignment of our models of brain
and behavioral development is essential for prog-
ress in understanding of how humans develop, bio-
logically, cognitively, or socially. The purpose of
this chapter is to provide an overview of some very
basic principles of brain development drawn from
contemporary developmental neurobiology that
may be of use to investigators from a wide range of
disciplines, and in particular to developmental
psychologists whose specific focus is the origin of
knowledge and its biological underpinnings.
Psychological models of inheritance
The central questions in developmental psychol-
ogy are: How do children come to know about
the world, and what are the origins of knowledge?
Major developmental theories differentially stress
either the level and content of knowledge avail-
able to the newborn, or the factors and processes
that underlie development, and specifically
learning. These issues define Nature versus.
Nurture debate in psychology.
The Nature versus Nurture debate is best
described as a continuum of thought, but one that
can be well characterized by specifying the two
ends of that continuum. On one end of the contin-
uum is the nativist perspective, the goal of which
is to define innate conceptual constraints and
structures. Innate concepts are defined as infor-
mation that is available without experience
(Spelke, 2003; Spelke and Kinzler, 2009).
Examples of in innate concepts include, knowl-
edge of the physical world, rudimentary mathe-
matics, fundamental linguistic structures (Carey
and Markman, 1999; Gelman, 2000; Kinzler and
Spelke, 2007). Proponents of traditional nurture-
based views (represented, e.g., by Piagetian,
neoconstructivist, and information processing
perspectives) argue that complex concepts can
emerge from more primitive, but innate, sensory,
motor, and learning abilities (Cohen et al., 2002;
Elman et al., 1996; Newcombe, 2002; Sirois
et al., 2008). It is notable that both sides in the
ongoing psychological debate compartmentalize
developmental influences by their proposed
origins. They both assume that innate factors
originate from within the organism and are pre-
sumably part of the biological endowment, while
learned behaviors originate from outside the
organism and result from experience in the world.
Thus, at issue in the traditional psychological
naturenurture debate is not whether there are
innately specified behaviors, but rather whether
4
there exists a privileged set of core concepts
(Gelman, 2000) that should be included among
class of innate behaviors, and whose origin does
not need to be explained.
Implicit in both accounts are assumptions
about the relationship between the biological
system and experience, but what is missing is
an account of the biological feasibility of the
assumptions about innateness. Specifically, how
does a biological system support an innate idea?
What is an innate learning mechanism? Neither
side has adequately addressed the question of
biological feasibility, and yet each side makes
assumptions about biology that are under-speci-
fied yet central to their theory of development.
Biological perspective on inheritance
Biological accounts of inheritance have framed
the key questions about innateness very differ-
ently (Stiles, 2008). The central issues from a
biological perspective concern both what is
inherited and how these inherited factors can
account for both intergenerational constancy and
individual variability. Biological models of inheri-
tance identify two primary inherited factors. The
first is the genetic material, specifically the
nucleotide sequences of DNA. This is the mate-
rial, particulate matter that is passed inter-
generationally from parent to offspring. Gene
products are essential for all aspects of develop-
ment. However, the genes themselves, do only
one thing, they provide a template for coding pro-
tein. It is the proteins that are the active agents in
biological development. Thus, while genes con-
tain information that is essential for the develop-
ment and functioning of the biological organism,
the genes themselves are basically inert
molecules. They cannot participate directly in
biological processes. Rather, the relationship
between the information in a gene and a develop-
mental outcome is indirect. The information in
the gene sequences must be extracted, recoded,
and translated; and that requires the other aspect
of biological inheritance, which is the cell. The
cell is the first environment in the sense that it is
a structure that contains the biological machinery
necessary for gene expression, specifically the
ribosomes, and the nuclear and cytoplasmic
elements needed to generate proteins. Genes
have never been transmitted intergenerationally
in the absence of a cell. Thus, what is inherited
at the moment of conception are both the essen-
tial code and the biological means for generating
the active agents of biological development
and function (Jablonka, 2002; Keller, 2000a,b;
Sarkar, 2000).
Within the biological model, therefore, it is
development rather than inheritance that is the
central construct (Lewontin, 1983; Oyama, 2000;
Oyama et al., 2001; Stiles, 2008). Biological inher-
itance provides essential tools, but neither the
genes nor environment factors prescribe out-
comes. The biological state of the organism at
any moment is the product of developmental pro-
cesses that involve an intricate interplay among
complex cascades of gene expression interacting
with influences from an ever-expanding range of
environmental factors. Thus, it would be a mis-
take to construe intrinsic factors as in some way
deterministic and extrinsic factors as modulatory.
While the products of gene transcription play
essential roles in influencing development and
function, single genes do not determine complex
structural or behavioral outcomes. At all stages,
the focus should be on the developmental
process, and that requires both intrinsic and
extrinsic signaling.
The brain as a model of biological development
Recent models of brain development support this
dynamic view of biological inheritance and devel-
opment. While it is not possible in a few pages to
provide an overview of the incredibly complex
and intricate processes that underlie mammalian
brain development, a few carefully selected
examples drawn from diverse stages of
5
embryonic, fetal, and postnatal development can
illustrate the multifaceted and interactive nature
of development.
Brain development is an complex event that
begins during the third week of gestation and con-
tinues, well, certainly through adolescence, and
quite arguably through the lifespan. In humans,
brain development requires the generation of an
estimated 100 billion neurons, and most of the
neurons that make up the neocortex are produced
in the first half of the period of gestation
(Pakkenberg and Gundersen, 1997). To achieve
those numbers, it is estimated that at the peak
of neuron production, 200,000 neurons are pro-
duced every minute. Further, every neuron makes
connections with as many as a thousand other
neurons. Thus, there are at least 60 trillion
connections or synapses in the human brain.
However, the numbers alone do not capture the
complexity of the emerging structural and func-
tional organization in the developing human
brain. That story emerges in the intricate and
dynamic interactions among this large and diverse
array of neural elements.
The sections that follow will briefly summarize
the events surrounding five important milestones
in brain development. Each contributes to the
complex set of processes that underlie the gradual
emergence and elaboration of the mammalian neo-
cortex. The examples are sampled from five succes-
sive developmental periods and each describes a
step in the development of areal organization of
the neocortex. With each step in development,
the organization of the neocortex becomes more
highly specified, but at each step, the system is
dynamic and susceptible to multiple influences.
Emerging organization depends on the interaction
of both intrinsic and extrinsic signaling cues. How-
ever, before introducing these milestones, it is
important to define more precisely the topic of dis-
cussion, which is the gradual parcellation of the
neocortex into discrete neocortical areas.
The mature human brain has characteristic
folds and ridges, but the surface subdivisions are
uniform in appearance (see Fig. 1a). The neocor-
tex consists of a thin mantel layer of cells resting
on the surface of the brain (see Fig. 1b) with
extensive underlying white matter pathways and
subcortical nuclei forming networks of
connections both with peripheral structures and
among cortical areas. Although the mature
human neocortex appears to be relatively
uniform from one region to the next, it is actually
partitioned into subregions, or areas, that are
differentiated by the cell types they contain, the
pattern connections they form with other areas,
and their function. Figure 1c illustrates an early,
though still widely used, account of area organiza-
tion in the mature human neocortex (Brodmann,
1909). The question addressed here is what is
known about the development of this essential
pattern of cortical organization.
Five milestones in the development of the areal
organization of neocortex
The remainder of this chapter will focus on five
pre- and postnatal events that contribute to the
emerging areal organization of the mammalian
neocortex. Each reflects the effects of complex
signaling cascades involving multiple interacting
cues. Together they provide a picture of brain
development as a dynamic interactive event that
emerges gradually over a protracted period of
time, constrained by multiple genetic, environ-
mental, and temporal factors. The five events
include two early occurring events that are
dominated by organism intrinsic signaling: (1)
the specification of neural progenitor or stem cells
and initial spatial patterning of the embryonic
nervous system; (2) the initial areal patterning of
the neocortex. The three later events are
dominated by extrinsic signals: (3) the role of
visual input on emerging visual system organiza-
tion; (4) functional respecification of a cortical
sensory area by alteration of input; (5) neural
plasticity and reorganization of adult neocortex.
6
Early intrinsic signaling and the development of
the embryonic central nervous system
The embryonic period of development extends
from conception through gestational week
8 (GW8). At the end of this period, the major
compartments of the central and peripheral
nervous system are well defined, the segmental
organization of the spinal column and hindbrain
has emerged, and primitive midbrain and
diencephalic structures are identifiable. Most
critically, the neocortex has begun to form. This
section considers two important events, one
that marks the onset of brain development, the
differentiation of the neural progenitor cells lines,
and one that establishes the fundamental organi-
zation of the neocortex. Intrinsic molecular
signaling among multiple cell populations plays
an essential role in these critically important early
events.
(a) (b)
(c)
Lateral
surface
Medial
surface
Fig. 1. Views of the mature human brain. (a) Lateral view (rostral end is left, caudal is right) shows an apparently uniform surface
marked by gyri and sulcal folds (right hemisphere of J. Piłsudskis brain, lateral view, image in the public domain). (b) Coronal
cross-section (cut at approximately the level of the dotted line in a) is stained for cell bodies that mark neurons. The neocortex
is the thin mantel layer (dark gray) on the surface of the brain. The white areas are connecting fiber pathways. (Image
reproduced with permission from http://www.brains.rad.msu.edu which is supported by the U.S. National Science Foundation.)
Brodmanns (1909) original mapping of cortical areas. Each area has a characteristic structural and functional organization. All
images obtained with permission from Wiki Commons, http://commons.wikimedia.org/wiki.
7
Specifying the neural progenitor cells and initial
spatial patterning of the nervous system
Brain development begins in the third week post-
conception as part of a larger set of processes
referred to collectively as gastrulation. During
gastrulation, the primary stem cell lines differenti-
ate. These include stem cell lines for all of the
major body systems. Among these newly
differentiating stem cell lines are the neural stem
cells, which are typically referred to as the neural
progenitor cells. The neural progenitor cells
will give rise to most of the cells of the brain and
central nervous system, including all of the neurons
and most of the support cells. The brain and central
nervous system. The differentiation of the neural
progenitor cells thus marks the beginning of brain
development (Gilbert, 2006; Sadler, 2006).
Gastrulation occurs between embryonic day 13
and 20 (E13E20, this notation indicates the num-
ber of days since the conception of the embryo).
At the beginning of gastrulation (E13) the
embryo consists of a two-layered, disk-shaped
structure (see Fig. 2a). By the end of gastrulation
(a) (b) Cross-section: placenta and embryo
Amniotic
Sac Dorsal surface
of embryo
Embryo
Yolk Sac
Rostral
end of
embryo
Rostral (head)
Caudal (tail) Rotate 90° right Rotate 90° in depth
Dorsal view of an E13 embryo rotated to position in
placenta (in B):
(c) (d) Comparable spatial
axes for a crawling
infant
Dorsal
L
R
Caudal
Rostral
Ventral
Dorsal view (E13)
Rostral (head)
Caudal (tail)
Fig. 2. The major spatial dimensions of the E13 embryo. (a) The dorsal surface view of the embryo on E13 is shown in the first panel.
The wall of the amniotic sac has been cut away to reveal the dorsal surface (epiblast layer) of the embryo. The rostral (head) end of
the embryo is on the top of this figure, and the caudal (tail) end is at the bottom. (b) A lateral cross-section of the embryo and placenta
at E13. On E13, the two-layered embryo is located centrally between two major placental sacs. The amniotic sac (which later in
development will surround the embryo) is located above the embryo, and the yolk sac is located below. The rostral end of the
embryo is to the right in this figure. (c) To place the embryo shown in the first panel of a within the context of the lateral view of the
embryo and placenta shown in b, it is necessary to first rotate the embryo so that the rostral end faces right (second panel of c), and
then rotate the embryo in depth so that the dorsal surface faces up (last panel of c). (d). The comparable rostral-caudal and dorsal-
ventral spatial axes of an infant. The spatial axes of a crawling infant are comparable to the position of the embryo in b.
8
(E20), the embryo will retain its disk-shaped
structure, but will have become a three-layered
structure. Each of the three layers contains differ-
ent types of stem cells that will give rise to the
cells that form different body systems. The neural
progenitor cells will differentiate from a subset of
cells in the uppermost, or dorsal, layer of the
three-layered embryo. By the end of gastrulation
at the end of the third week of gestation, the neu-
ral progenitor cells will be located along the axial
midline of the dorsal (or uppermost) layer of the
embryo (indicated by the red rectangle in Fig. 3c).
Before considering the processes that lead to
the differentiation of the neural stem cells it is
helpful to provide some orientation to structure
and spatial dimensions of the embryo on E13. A
dorsal view of the E13 embryo is shown in Fig. 2a.
In this view, rostral or head end of the embryo is
at the top, and the caudal or tail end is at the bot-
tom. To clarify the shape and orientation of the
embryo, consider its appearance within the
context of the placenta. A mid-saggital cross sec-
tion of the placenta and embryo at E13 are shown
in Fig. 2b. The two-layered embryo is indicated
by the dark and light bands extending horizon-
tally in the center between the placental sacs.
The dorsal surface of the embryo is on top, the
ventral surface on bottom. The amniotic sac is
located above the embryo, yolk sac is located
below and the connecting stalk that attaches the
embryo to the uterine wall is to the far left. To
place the dorsal view of the embryo shown in
Fig. 2a into the orientation shown in the placental
cross section shown in Fig. 2b, it is necessary to
first cut away the amniotic sac (indicated by the
dotted line in Fig. 2b) so that the dorsal surface
of the embryo is exposed, and then rotate the
embryo. The embryo is first rotated so that the
rostral end is on the right, and then it is rotated
in depth so that the dorsal surface faces upward
(see Fig. 2c). In this position, the connecting stalk
is on the left and the cut edge of the embryo is on
(a) (b)
Primitive
node
Primitive node
Epiblast
Mesodermal cells Hypoblast
Primitive
streak
Primitive
streak
(c) (d)
Fig. 3. The major events of gastulation occur between E13 and E20. (a) The onset of gastrulation is marked by the formation of the
primitive streak and the primitive node. The primitive streak provides an opening to deeper embryonic layers. The primitive node is
a critical molecular signaling center. On E13, cells from the epiblast layer begin to migrate toward the primitive node and streak
(arrows). The dotted line indicates the cross-sectional view shown in panel b. (b) The migrating cells first move to the primitive
streak and then change direction and move down and under the upper layer (arrows). As the cells pass the node they receive
molecular signals that induce gene expression in the migrating cells. By the end of gastrulation, the hypoblast layer is replaced
by the newly formed endodermal layer and the epiblast layer by the ectodermal layer. Between these layers the mesodermal
layer forms. (c) Once under the upper layer, the cells change direction and begin migrating rostrally under the upper layer
(arrows). The first cells to migrate form the most rostral regions of the newly forming endodermal and mesodermal layers. Later
migrating cells form progressively more caudal regions of the layers. (d) Cells that migrate along the axial midline send
molecular signals that induce cells in the overlying epiblast layer to differentiate into neuroectodermal cells (gray rectangular
band) which are the neural progenitor cells. Migrating cells also receiving a second set of signals from the node that induce
anterior or posterior fate in different subpopulations of the neurectodermal cells. Early migrating cells signal anterior fate in the
progenitor cells, while late migrating cells signal posterior fate.
9
the top. In this orientation, the spatial dimensions
of the embryo correspond to the major spatial
axes of a crawling infant shown in Fig. 2d.
The signals that trigger the differentiation of
neural progenitor cells arise from complex molec-
ular signaling from multiple cell populations. Just
prior to the onset of gastrulation, a grooved open-
ing called the primitive streak forms in the dorsal
cell layer (see Fig. 3a). The primitive streak
begins to form in the most caudal region of the
dorsal layer of the embryo and courses rostrally,
ending at a newly formed signaling center called
the primitive node.The primitive streak is actu-
ally an opening in the dorsal layer of the embryo
that provides access to the lower layers. The
primitive node, that forms at the most rostral
end of the primitive streak, is a critical molecular
signaling center. At the onset of gastrulation, a
subset of cells from the dorsal cell layer begin to
migrate toward the primitive streak and primitive
node. When the cells reach the opening, they
change course and begin to migrate down and
under the upper layer of the embryo as shown
in the cross-sectional coronal view of the embryo
in Fig. 3b. These cells will form the new interme-
diate, third layer of the embryo. As indicated in
Fig. 3c, once under the dorsal layer the cells
change direction and begin migrating rostrally
underneath the dorsal layer, thus forming the
new intermediate layer called the mesodermal
layer. Early migrating cells move to the most ros-
tral region of the new middle layer, while later
migrating cells form progressively more caudal
parts of the middle layer.
Importantly, as the cells that migrate along the
axial midline of the embryo pass the nodethey
receive a signal that triggers a signaling cascade
(gene expression) within the migrating cells. The
signals that emanate from the migrating cells, in
turn send signals to the cells that remain in the mid-
line region of the upper (dorsal) layer of the
embryo. It is this signal that promotes the differen-
tiation of the midline dorsal layer cells into neural
progenitor cells (location indicated by the rectan-
gle in Fig. 3d). Thus, at the end of gastrulation on
E20, the neural progenitor cells are positioned in
a band that runs along the axial midline of the
upper layer of the embryo. That entire upper layer
is now called the ectodermal layer.The subre-
gion located along the axial midline of the ectoder-
mal layer is referred to as the neurectoderm, and it
forms a structured referred to as the neural plate.
The signaling cascades provided by the migrat-
ing cells also serve to establish the basic spatial
organization of the developing nervous system.
This is accomplished by systematic changes in
the particular sets of signals sent to the migrating
cells at different points during gastrulation. Recall
that the earliest migrating cells move to the most
rostral regions of the embryo. These cells receive
signals from the node that induces them to pro-
duce signals that induce neural progenitor fate
in the overlying cells, but the node also signals
those cells to become the neural progenitors that
will create the neurons of the forebrain. Later
migrating cells move to more caudal regions.
These cells receive signals from the node that
induce them to produce signals for neural progen-
itor fate, but also signals the neural progenitors to
create the neurons of the midbrain, hindbrain,
and spinal cord. Thus, the sets of cues transmitted
from the nodal cells to the migrating cells change
over time. Those changes induce different
patterns of gene expression in the migrating cells
which leads to regional differences in the signals
that are sent to the newly differentiating neural
progenitor cells in the overlying layer. This com-
plex temporal variation in signaling involving
multiple cell populations serves to establish the
basic rostralcaudal organization of the brain
and central nervous system.
Establishing the initial areal organization of the
neocortex
The events of gastrulation set the stage for the
next step in the development of the areal organi-
zation of cortex. By the end of the gastrulation,
the neural progenitor population has been
10
established and there is very primitive differentia-
tion of cells along the major spatial axes of the
embryonic nervous system. The initial differentia-
tion of anteriorneural progenitor cells prepares
the primitive nervous system the next step in
cortical development which involves increasing
specification of the cortical regions. These events
occur during the second month of gestation in
humans and involve further differentiation of
the neural progenitor cell population.
Between gastrulation and the events of the sec-
ond month, major changes occur in the morphol-
ogy of the embryo, the most important of which
involve the formation of the neural tube. Neural
tube formation begins at the end of GW3 with
the appearance of two ridges that bracket the lon-
gitudinal sides of the neural plate (Fig. 4a).
Between the ridges are the neural progenitor
cells. Over the course of several days, the ridges
rise, fold inward and fuse to form a hollow tube
Mesencephalon
Diencephalon
Telencephalic vesicle
Pontine flexure
Metencephalon
Myelencephalon
Spinal Cord
Cervical flexure
Cephalic flexure
(f)
Mesencephalon
Rhombencephalon
Spinal Cord
Cervical flexure
Cephalic flexure
Optic vesicle
Prosencephalon
(e)
(a) (b)
Primitive streak
E19 E20
Primitive node
Neural groove
Neural fold
Posterior neuropore
Anterior neuropore
(d)
E23
(c)
E22
Neural fold
Fig. 4. Changes in the morphology of the embryo in the embryonic period. The formation of the neural tube occurs between E19 and
E29. (a) The emergence of the neural ridges is observed on E19. (b) The ridges fold over to begin the process of neural tube formation
on E20. (c) Closure of the neural tube begins on E22 in central regions of the newly forming neural tube. (d) Closure continues in rostral
and caudal direction. The anterior neuropore closes on E25, and the posterior on E27. (e) Following the closure ofthe neural tube, the
embryo begins to expand particularly in anterior regions. The primary vesicles are evident by E28. These include the Prosencephalon,
Mesencephalon, and Rhombencephalon. (f) By E49 the secondary vesicles emerge. The Prosencephalon differentiates into the
Telencephalon and Diencephalon, and the Rhombencephalon into the Metencephalon and Myelencephalon.
11
(Copp et al., 2003). Fusion begins in the center of
the emerging neural tube and then proceeds in
both anterior and posterior directions (Fig. 4b).
The ends of the tube, the anterior and posterior
neuropores, are the last segments to close, on
E25 and E27, respectively. When the neural tube
is complete, the neural progenitor cells form a sin-
gle cell layer that lines the center of the neural tube
in a region called the ventricular zone(VZ). The
neural progenitor cells in the most anterior region
of the neural tube will give rise to the brain, while
more caudally positioned cells will give rise to the
hindbrain and spinal column.
In the month following neural tube closure, the
embryo undergoes dramatic and rapid change in
its morphology. The anterior end of the tube
expands to form the three primary brain
vesicles,or pouches (Fig. 4e). The most anterior
of these embryonic brain vesicles is called the
prosencephalonwhich is the embryonic precur-
sor of the forebrain. The middle vesicle is the
mesencephalonwhich is the precursor of mid-
brain structures, and the most posterior is the
rhombencephalonwhich will become the hind-
brain. These three segments further subdivide
and by the end of embryonic period the five sec-
ondary brain vesicles are present (Fig. 4f). The
prosencephalon divides into the telencephalon
and the diencephalon,and the rhombencepha-
lon divides into the metencephalonand mye-
lencephalon.The mesencephalon does not
further divide. These five subdivisions are aligned
along the anteriorposterior axis of the embryo
and establish the primary organization of the
CNS (Stiles, 2008).
The changes associated with the emergence of
the secondary brain vesicles are accompanied at
the cellular level with changes in the neural pro-
genitor population. Just prior to the production
of the first neurons on E42, another set of com-
plex signaling cascades direct the further regional
differentiation of neural progenitors cell popula-
tion. This time the signaling will establish the first
and most primitive patterning of sensorimotor
areal organization of the neocortex. Rudimentary
cortical areas are the product of interactive signal-
ing cascades involving multiple genes, expressed
in different concentrations in different brain
regions.
Cells in different regions of the neural prolifer-
ative zone express different genes. This introduces
regional differences in the types of proteins that are
present, and thus the types of signals that are pro-
duced. Further, in many cases, proteins are pro-
duced in different concentrations, creating
gradients of gene expression. This pattern of
graded gene expression provides an important
basic mechanism for establishing cortical areas.
Combinations of proteins in varying con-
centrations signal the further regional differentia-
tion of the neural progenitor cells, and that in
turn results in the subsequent production region-
ally varying neuronal populations. In this example,
this graded pattern of gene expression in anterior
regions of the VZ serves to specify the basic senso-
rimotor organization of the developing neocortex.
In this example, two genes are involved which
code for the transcription factor proteins Emx2
and Pax6 (Bishop et al., 2000, 2002). In the
normal animal (the mouse in this example), two
complementary expression gradients are
observed within the neural proliferative zone
(see Fig. 5a): (1) Emx2 is expressed in high con-
centrations in caudalmedial areas; (2) Pax6 is
expressed in high concentration in rostrallateral
areas. Combinations of different concentrations
of gene expression result in the emergence of dif-
ferent rudimentary somatosensory cortical areas.
The combination of high levels of Pax6 and low
levels of Emx2 induces motor cortices (M1), while
the opposite combination of concentrations
induces visual cortex (V1). Intermediate levels of
both proteins induces somatosensory cortex (S1).
To show that it is the interaction of the two
proteins that induces the different cortical areas
gene knockout studies were conducted. Two
different strains of mice were developed. In the
Emx2 mutation, levels of Emx2 were suppressed.
When that happens, the concentration gradient
of Pax6 extends further back (see Fig. 5b).
12
This produces a change in the distribution and
position of cortical areas such that visual areas
shrink (V1), and motor areas expand (M1).
The opposite effect is found when Pax6 expression
is suppressed (see Fig. 5c). Emx2 extends forward,
and visual areas expand (V1) and motor areas
shrink (M1). These data show that it is the interac-
tion of these two proteins at specific concentration
levels establishes the very early, rudimentary plan
of these key cortical areas. It is the right amount
of each protein in the right locations and
interacting with the right amount of the other
protein that contributes to the emergence of the
typical pattern of cortical organization.
While these data provide a good description of
the basic processes that underlie the early specifi-
cation of cortical area, recent evidence indicates
other molecular players also contribute to these
early patterns of cortical specification (OLeary
et al., 2007a,b). Since the original reports of the
contributions of Pax6 and Emx2 to cortical orga-
nization, it has become clear that the interactions
(a)
Normal
(wild type):
Pax6
Emx2
Emx2
Pax6
Emx2 Pax6
R
L
C
M
M1
S1
V1
Emx2
Mutation:
R
L
C
M1
S1
V1
M
(b)
R
L
C
M1
S1
V1
M
Pax6
Mutation:
(c)
L
A
PANR, CoP (Fgf8, Fgf17)
Cortical Hem (Wnts, Bmps)
Shh
Anti-hem (Tgfa, Fgf7, Sfrp2)
M
(d)
Fig. 5. The effects of different concentrations of Emx2 and Pax6 on the development of sensorimotor cortical areas. It is the
combination of specific concentrations of each molecule that determines the identity of the cortical region. Mutations that affect
the quantities of either molecule, alter cortical patterning. (a) Normal graded expression patterns for Emx2 and Pax 6 and the
cortical areas they produce on the far right. (b) Effects of a mutation of Emx2. Note motor areas expand and visual areas shrink.
(c) Effects of a mutation of Pax6. Note visual areas expand and motor areas shrink. (d) A number of patterning centers have
been identified. The express secreted proteins that modulate the expression of the major transcription factors that define area
specification. (ac). Adapted with permission from Bishop et al. (2000). (d) Adapted with permission from OLeary and Sahara,
2008.R¼rostral, C¼caudal, M¼medial, L¼lateral, A¼anterior, P¼posterior.
13
are more complex. At least two additional tran-
scription factors have been identified, Coup-TF1
and SP8. Each has a characteristic pattern of
graded expression and knockout studies reveal
that altering the expression of these genes system-
atically alters the organization of somatosensory
and motor areas within the emerging neocortex.
Finally, the expression of all of these transcrip-
tion factors is controlled by signaling from a num-
ber of signaling centers, specifically, anterior
neural ridge, cortical hem, antihem (see Fig. 5d;
OLeary and Sahara, 2008). Each of these signal-
ing centers expresses secreted molecules that
diffuse in a gradient and in turn induce the graded
expression of the transcription factors that play
critical role in establishing rudimentary sensori-
motor area organization in the developing
neocortex. Thus, as was the case in the initial
specification of the neural progenitor cell lines,
the emergence of primitive areal organization in
the neocortex is the product of complex signaling
cascades involving multiple cell populations.
Extrinsic signaling and the organization of
neocortical areas
The two developmental events discussed thus far
described the series of early occurring molecular
events that lead to the establishment of the rudi-
mentary cortical area organization. However,
those early patterns of areal organization are far
from complete. Later in development intrinsic sig-
naling continues to play a critical role in neocorti-
cal development, but extrinsic signaling is also
necessary for the emergence of typical patterns
of neocortical organization and function. Three
examples illustrate this point.
The role of visual input on emerging visual
system organization
The seminal work of Hubel and Wiesel (Hubel
and Wiesel, 1963; Hubel et al., 1977; Wiesel,
1982; Wiesel and Hubel, 1963a, 1965) examined
the effects of specific experience on the internal
organization of a crucial cortical area, primary
visual cortex (PVC). In particular, the studies
looked at the effects of monocular deprivation
on the organization of ocular dominance columns
of young rhesus macaque monkeys. Input layer of
PVC, cortical layer 4, receives most of the visual
sensory input from the primary visual pathway.
Inputs from each eye remain segregated along the
length of the primary visual pathway from the ret-
ina, along the optic nerve, through the optic chi-
asm, to the thalamus, and finally to primary visual
cortex. As the fibers enter PVC, they organize into
bands of eye-specific inputs called ocular domi-
nance columns (ODC). The ODC can be visualized
by injecting a radioactive, retrograde tracer into
one eye. The tracer moves away from the eye in a
retrograde fashion along the length of the visual
pathway, and is taken up into the cell bodies of
layer 4 cortical neurons that receive input from
the tracer injected eye, thus marking the ODC
(see Fig. 6a). The light bands indicate neurons
receiving input from the tracer injected eye, the
dark bands the neurons from the other eye. The
origins of these bands in the late postnatal period
are thought to rely on intrinsic signaling, possibly
in concert with extrinsic input. However, as
demonstrated by Hubel and Wiesels studies of
early monocular deprivation, patterned visual
input during the early postnatal period is necessary
to maintain this basic pattern of organization.
In the monocular deprivation studies, one eye
was sutured closed during a critical period of
early development that extends from the third
postnatal week to about 1 year of age. After a
period of deprivation the eye was unsutured,
and a retrograde tracer injected into the non-
deprived eye. As indicated in Fig. 6b, the narrow
dark bands represent the inputs from the
deprived eye, and the light bands inputs from
the active eye. These data clearly show that
changes in the input can alter patterns of connec-
tivity within a cortical area. Cortical inputs from
the deprived eye retract, whereas inputs from
the active eye expand into the territory formerly
14
occupied by those of the deprived eye. This kind
of dramatic shift in patterns of connectivity within
PVC is thought to reflect competitive processes
that are typical during early brain development. It
is well documented that neurons compete for
resources such as nerve growth factor which is
produced by target neurons and available in
limited quantities at synaptic sites (Chao, 2003;
Huang and Reichardt, 2001; Levi-Montalcini,
1964, 1987). Among the cell populations that
project to a target region, active cells have a com-
petitive advantage in obtaining these resources
and thereby in establishing stable cortical
connections. The reduction in activity of cells in
the deprived eye places them at a competitive
disadvantage that results in loss of connectivity
and reduction in their access to cortical territory.
Functional respecification of a cortical sensory
area by alteration of input
As dramatic as the studies of ocular dominance col-
umn plasticity are, other work has shown that capac-
ity of the developing brain to respond and adapt to
alternative patterns of input can involve entirely
different classes of input. During the early postnatal
period of development, input from a different
sensory modality can fundamentally redefine the
organization and function of a cortical area.
In a series of studies conducted by Sur and col-
leagues (Pallas et al., 1990; Sur and Leamey, 2001;
Sur and Rubenstein, 2005; Sur et al., 1999), the
visual and auditory input pathways of neonatal
ferrets were dramatically altered. The primary
visual cortex (PVC) was surgically removed and
the major input pathway from the cochlea to pri-
mary auditory cortex (PAC) was severed (Pallas
et al., 1990; Sur et al., 1988). These rewiring
procedures induced dramatic alterations in the
structural and functional organization of primary
auditory cortex. The primary visual pathway
established functional connections with PAC,
and the PAC neurons responded to visual input
(von Melchner et al., 2000). In addition, the orga-
nization within both the thalamus (the major sub-
cortical sensory relay nucleus) and auditory
cortex reflected the 2-D, retinotopicorganiza-
tion typical of PVC, rather than the 1-D tonotopic
organization typical of PAC (Horng and Sur,
2006; Sur and Leamey, 2001). Thus, the surgical
interventions resulted in a dramatic alteration in
the patterns of brain connectivity, and in a funda-
mental reassignment of the function of PAC
from auditory to visual.
(a) (b)
Fig. 6. Autoradiographs of the ocular dominance columns (ODC) in two young monkeys. A radioactive transneuronal dye was
injected into one eye and taken up by neurons in the input layer of primary visual cortex (PVC). (a) The normal patterning of
the ODC in a 6-week-old monkey. ODCs from each eye are equal and adultlike. (b) ODC patterning from an animal that was
monocularly deprived at 2 weeks of age. The nondeprived eye was injected with the tracer at 18 months of age. ODC for the
nondeprived eye (light bands) expand and while those of the deprived eye (dark bands) shrink showing clear dominance of
the nondeprived eye in PVC. Adapted with permission from LeVay et al. (1980), figures 5 and 6.
15
The capacity to experimentally induce this kind
of dramatic change in the neural architecture of
young animals is thought to rely on the massive
overproduction of neural connections that is typi-
cal during early brain development (Bourgeois
and Rakic, 1993; Bourgeois et al., 1994;
Huttenlocher and Dabholkar, 1997; Innocenti and
Price, 2005; Zecevic et al., 1989). In the normal
course of development connectivity in the brain is
exuberant with most regions making transient
connections with multiple brain regions that are
not observed in the mature brain. It is assumed that
competitive forces act to shape the final patterns of
connectivity, such that optimally efficient networks
are retained and less optimal patterns of connectiv-
ity are pruned back. When normal auditory input
was eliminated in the young ferrets, competition
for resources in PAC was reduced and the typically
transient visual inputs to PAC stabilized, providing
visual input to what would normally have become
an auditory area. Thus, the experimental manipu-
lation had the effect of reassigning the function of
this region of the sensory cortex from auditory to
visual. Later studies showed that the functional
reassignment of PAC as a visual area can happen
even when PVC is preserved, creating an animal
with two primary visual areas.
Neural plasticity and reorganization of adult
neocortex
Finally, there now a large body of work showing
that the capacity for neocortical reorganization is
not confined to early development. (Gilbert et al.,
2009; Kaas, 1991; Merzenich and Jenkins, 1993;
Merzenich et al., 1996; Winship and Murphy,
2009; Yamahachi et al., 2009). Variations in input
or alterations of the sensory systems can induce
quite dramatic changes in the organization of a
cortical area even in adult animals. This section
will present just one example to illustrate these
points. The example involves reorganization in
the primary auditory cortex of a Rhesus macaque
monkey following experimental elimination of
high frequency tone receptors in the cochlea.
Primary auditory cortex (PAC) in the macaque
brain is located in on the dorsal surface of the
temporal lobe on the lower bank of the lateral
sulcus, and is typically hidden from view by the
overlying frontoparietal cortex (Hackett et al.,
2001). Figure 7a shows the location of macaque
PAC (indicated by the circle) with the frontal
and parietal cortices removed. Functionally,
PAC is characterized by its one-dimensional
tonotopic organization in which neurons in caudal
regions respond to high frequencies and those in
rostral regions to low frequencies (see Fig. 7b),
reflecting the one-dimensional functional organi-
zation and pattern of input from the cochlea.
In a study conducted by Schwaber et al. (1993),
the typical low-rostral to high-caudal tonotopic
organization of PAC was first documented in a
sample of Rhesus macaque monkeys by recording
the responsivity of PAC neurons to tones of dif-
ferent frequencies (see Fig. 7b). They then used
ototoxic chemicals to selectively destroy cochlear
fibers responsive to high frequencies (above
10 kHz), thus eliminating normal input to the
most caudal regions of primary auditory cortex.
Two to three months after the ototoxic surgery,
microelectrical recordings taken in primary audi-
tory cortex showed reorganization (see Fig. 7c).
Neurons that were formerly responsive to high
frequencies now responded to midrange tones.
Further, the reorganized cortex retained the basic
pattern of tonotopy, but range now extended
from low to midrange tones across the full extent
of cortex reflecting changes in input introduced
by the experimental alteration of the cochlea.
Thus, this study documents ongoing plasticity in
the mature brain. Even in adult animals, experi-
ence can alter functional brain organization.
The dynamics of brain development: Exuberance
and constraints
This series of studies was intended to convey the
dynamic nature of brain development. From
the very earliest steps, brain development is
influenced by both intrinsic factors, the molecular
16
cues derived from gene expression, and extrinsic
factors, input from sources outside the organism.
Neither set of factors acts in isolation to determine
developmental outcome. Rather, they work in
concert as part of a complex and dynamic system
that serves to support and guide the development
of the brain. This is a model of neural develop-
ment that is anchored in the process of develop-
ment itself, with each step influenced by myriad
cues arising from multiple levels of the emerging
system. Indeed, one might legitimately ask
whether such a model is too dynamic. There are
many degrees of freedom in these complex, inter-
active signaling cascades, but if there is no specific
mechanism for determining a particular outcome,
then how it is that development proceeds with
such uniformity to produce species typical
organisms? The answer to this question lies in
the fact that while development is dynamic it is
also occurs within the context of very powerful
constraints that originate from three principle
sources: genetics, environment, and time.
Genetic constraints
Genes are the first factor that imposes constraints
on the developmental process. Each species, each
individual, has a specific set of genes that have
been acquired across the course of evolution.
The availability of specific gene products at
particular points in development is essential for
(a)
(b)
Low Low
Medium Medium
High
(c)
Fig. 7. The effects of altered input on adult brain organization. (a) Lateral view of an adult macaque brain with the frontal and
parietal cortices removed to reveal primary auditory cortex (A1). (b) The high-caudallow-rostral tonotopic map of primary
auditory cortex was first mapped electrophysiologically. (c) After ototoxic destruction of the high frequency receptors in the
cochlea, a shift in the functional organization is observed. The tonotopic continuum is observed, but it has shifted across the full
extent of A1, indicating plasticity in the mature macaque brain. Adapted with permission from Schwaber et al. (1993).
17
normal outcomes. Further the particular quantity
of a particular gene product is an essential factor
in developmental outcomes. As illustrated by the
work of OLeary and colleagues, modulation of
the level of transcription factor expression can
fundamentally alter the emerging organization of
somatosensory and motor areas cortex. Thus,
genes provide powerful constraints on develop-
mental processes and play a large and essential
role in brain development.
Environmental constraints
The second source of constraint comes from the
environment. Like genes, the environment
imposes rigorous constraints on how an organism
can develop. From an evolutionary perspective,
development is an adaptation to the contingencies
of the environment. Ontological development
relies on what Bill Greenough (Black and
Greenough, 1986; Greenough et al., 1987) has
called experience expectant change. Normal
development requires normal input from the
world to modulate and shape the emerging func-
tional organization of neural systems. Neural sys-
tems do not development normally in the absence
of typical environmental input. Studies of depri-
vation such as those illustrated in the work of
Hubel and Wiesel provide powerful examples of
the importance of normal, expected, input on
developing systems.
Temporal constraints
The third constraint is time. Specifically, develop-
ment is a complex, multilevel process that unfolds
over time. Biological systems start out simple and
become more complex over time. Across the
entire period of brain development the neural
system depends on the availability of the right
neural elements appearing at the appropriate
moment in developmental time. Often the emer-
gence of a new element depends critically on the
developmental events that immediately precede
it. As such, the developing organism often creates
as it goes the tool necessary for each successive
step in development. Thus, time constrains what
changes can occur and what factors can influence
development. In that sense, development is a
temporally constrained, self-organizing process.
Critically, the temporal component of develop-
ment involves three factors: progressive differen-
tiation, progressive commitment, and changing
sensitivity to local cues.
Progressive differentiation
Progressive differentiation refers to the ongoing
increases in the complexity of the organism. The
examples presented earlier illustrated this phe-
nomenon. The embryo goes from a two-layered
to a three-layered structure as new cell lines dif-
ferentiate and become organized and integrated.
Migrating cells that will by the end of gastrulation
form the mesodermal germ layer of the embryo,
also establish signaling pathways that promote
the differentiation of the neural progenitor cell
population in the ectodermal layer. This progres-
sive differentiation of neural progenitors also has
a spatial component that is critical for establishing
the basic functional organization of the embryo.
Concurrent with the signaling that promotes the
differentiation of the neural progenitor cell lines,
more specific signaling establishes subpopulations
of neural progenitors along the emerging neuraxis
of the embryo. Cells in rostral regions differenti-
ate to become forebrain progenitors, while more
caudally positioned cells differentiate to become
spinal and hindbrain progenitors. A few weeks
later, the graded expression of multiple transcrip-
tion factor proteins in the rostral progenitor cell
population will promote further differentiation
within cell populations destined to form the major
sensory and motor areas of the emerging neocor-
tex. Progressive differentiation brings increasing
complexity at all levels of the neural system from
cells lines to neural systems.
18
Progressive commitment
Progressive commitment refers to the stabiliza-
tion of systems. Developing systems exhibit con-
siderable plasticity and capacity to adapt to
varying signals and contingencies. But this plastic-
ity is constrained and declines with development
as different neural populations become progres-
sively committed to particular systems. Initially
the cells of the embryo are totipotentwhich
means that they are capable of differentiating into
any cell type in the body. But with development
there is progressive restriction in that potential
and as a consequence there are emerging con-
straints on plasticity. This kind of waning plastic-
ity is also observed much later in development.
For example, basic sensory areas in the neonatal
brain retain the capacity to receive input that
can fundamentally change their normally targeted
function. Surs neonatal rewiring studies demon-
strated that when normal patterns of input are
disrupted, primary auditory cortex retains the
capacity to adapt to quite different modes of sen-
sory input. Early synaptic exuberance, which is
found throughout the developing brain, is thought
to underlie this capacity for plastic adaptation. In
the absence of competition from auditory regions,
normally transient visual inputs can stabilize,
effectively changing PAC into a visual area.
Changing sensitivity to developmental signals
The final aspect of temporal constraint involves
changing sensitivity to developmental signals.
The level of development of the organism con-
strains what kinds of signals it can respond to.
At any point in time, the developing organism
has both a state and a history that constrains its
developmental potential. The history is the sum
of all of the events that contributed to the current
state of the organism. The state represents both
the current structure and functional capacity of
the organism, as well as its potential for further
change. Sensitivity to a specific intrinsic or
extrinsic influence depends on the current devel-
opmental state of the organism. For example,
auditory input has no effect on the events of gas-
trulation, but is critical for the development of
features such tonotopy in primary auditory cor-
tex. Thus, the increasing variety of structural
elements (some permanent, some transient)
creates diversity in the kinds of interactions that
can be engaged in the complex signaling cascades
that structure the developing brain.
Nature v Nurture or Nature X Nurture
This view of development and inheritance pre-
sents a very different perspective on the Nature
versus Nurture debate than that typically raised
in the classical psychological debates. By this
view, everything that develops has an innate
aspect. It must, because all developmental pro-
cesses rely, fundamentally, on the information
encoded in the genes and on the cellular
mechanisms that provide access to that informa-
tion. But genes themselves do not participate in
developmental processes. Rather it is the
products of gene expression, the proteins, that
are the active agents in development. But gene
products do not, by themselves, create neural
structures or functions. Rather, they participate
in complex signaling cascades that over time serve
to direct the fate of cells, the organization of sys-
tems, and the establishment of signaling pat-
hways. Indeed, the same gene product can have
markedly different effects depending on the
developmental context in which it is expressed.
Thus, at no point in brain development can the
effects of inherited and experiential factors be
separated. Rather, throughout development
intrinsic and extrinsic factors interact continu-
ously creating the dynamic processes and events
that guide the development of the brain.
This means that boundaries between what is
internal to the organism and what is external are
fluid. There is no point in development when
the organism is self-containedand separate
19
from the external world. Thus, at least for the devel-
opment of the brain, attempts to categorize
neurodevelopmental events as the product of
nature or nurture cannot succeed because the fun-
damental processes of brain development at every
level require the interaction of nature and nurture.
It is the process of development which begins with
the initial inheritance of genes and the first environ-
ment (the cell) and extends at least through child-
hood and more likely through the lifespan, that is
the key to understanding the origins and emer-
gence of complex biological structures like the
brain. Given the essential interdependence of brain
and behavioral development, it is likely that devel-
opmental processes are the key to understanding
the emergence of complex behavior as well. Ulti-
mately a unified account of human development
will require the alignment of the neurobiological
and behavioral models and that will require
integrated definitions of inheritance as well as con-
sensus on the role of both genes and environmental
factors on neurobehavioral development.
Acknowledgments
This work was supported by the National Institute
of Child Health and Human Development Grants
R01-HD25077 and 1 R01 HD060595. The author
would also like to acknowledge the support of the
UCSD Center for Human Development and the
UCSD Kavli Institute for Brain and Mind.
References
Black, J. E., & Greenough, W. T. (1986). Induction of pattern
in neural structure by experience: Implications for cognitive
development. In M. E. Lamb, A. L. Brown & B. Rogoff
(Eds.), Advances in developmental psychology, (Vol. 4,
pp. 150). Hillsdale, NJ: Erlbaum.
Bishop, K. M., Goudreau, G., et al. (2000). Regulation of area
identity in the mammalian neocortex by Emx2 and Pax6.
Science, 288(5464), 344349.
Bishop, K. M., Rubenstein, J. L., et al. (2002). Distinct actions of
Emx1, Emx2, and Pax6 in regulating the specification of areas
in the developing neocortex. Journal of Neuroscience, 22(17),
76277638.
Bourgeois, J. P., Goldman-Rakic, P. S., & Rakic, P. (1994).
Synaptogenesis in the prefrontal cortex of rhesus monkeys.
Cerebral Cortex,4(1), 7896.
Bourgeois, J. P., & Rakic, P. (1993). Changes of synaptic
density in the primary visual cortex of the macaque monkey
from fetal to adult stage. The Journal of Neuroscience,13(7),
28012820.
Brodmann, K. (1909). Vergleichende Lokalisationslehre der
Grosshirnrinde in ihren Prinzipien Dargestellt auf Grund
des Zellenbaues. Leipzig, Germany: J.A. Barth.
Carey, S., & Markman, E. M. (1999). Cognitive development.
In B. M. Bly & D. E. Rumelhart (Eds.), Cognitive science.
Handbook of perception and cognition (pp. 201254). (2nd
ed.). San Diego, CA: Academic Press, Inc.
Chao, M. V. (2003). Neurotrophins and their receptors: A con-
vergence point for many signalling pathways. Nature
Reviews. Neuroscience,4(4), 299309.
Cohen, L. B., Chaput, H. H., & Cashon, C. H. (2002). A con-
structivist model of infant cognition. Cognitive Development.
Special Issue: Constructivism Today,17(34), 13231343.
Copp, A. J., Greene, N. D., & Murdoch, J. N. (2003). The
genetic basis of mammalian neurulation. Nature Reviews.
Genetics,4(10), 784793.
Elman, J. L., Bates, E. A., Johnson, M. H., Karmiloff-Smith, A.,
et al. (1996). Rethinking innateness: A connectionist perspec-
tive on development. Cambridge, MA: The MIT Press.
Gelman, R. (2000). Domain specificity and variability in
cognitive development. Child Development,71(4), 854856,
discussion 860851.
Gilbert, S. F. (2006). Developmental biology (8th ed.).
Sunderland, MA: Sinauer Associates Inc.
Gilbert, C. D., Li, W., & Piech, V. (2009). Perceptual learning
and adult cortical plasticity. Journal of Physiology,587(Pt
12), 27432751.
Gottlieb, G. (2007). Probabilistic epigenesis. Developmental
Science,10(1), 111.
Greenough, W. T., Black, J. E., & Wallace, C. S. (1987). Expe-
rience and brain development. Child Development,58(3),
539559.
Hackett, T. A., Preuss, T. M., & Kaas, J. H. (2001). Architec-
tonic identification of the core region in auditory cortex of
macaques, chimpanzees, and humans. The Journal of
Comparative Neurology,441(3), 197222.
Horng, S. H., & Sur, M. (2006). Visual activity and cortical
rewiring: Activity-dependent plasticity of cortical networks.
Progress in Brain Research,157,311.
Huang, E. J., & Reichardt, L. F. (2001). Neurotrophins: Roles
in neuronal development and function. Annual Review of
Neuroscience,24, 677736.
Hubel, D. H. & Wiesel T. N. (1963). Receptive fields of cells in
striate cortex of very young, visually inexperienced kittens.
Journal of Neurophysiology, 26, 9941002.
20
Hubel, D. H., Wiesel, T. N., et al. (1977). Plasticity of ocular
dominance columns in monkey striate cortex. Philosophical
Transactions of the Royal Society of London. Series B:
Biological Sciences, 278(961), 377409.
Huttenlocher, P. R., & Dabholkar, A. S. (1997). Regional
differences in synaptogenesis in human cerebral cortex.
The Journal of Comparative Neurology,387(2), 167178.
Innocenti, G. M., & Price, D. J. (2005). Exuberance in the
development of cortical networks. Nature Reviews.
Neuroscience,6(12), 955965.
Jablonka, E. (2002). Information: Its interpretation, its inheri-
tance, and its sharing. Philosophy of Science,69, 578605.
Kaas, J. H. (1991). Plasticity of sensory and motor maps in adult
mammals. Annual Review of Neuroscience,14, 137167.
Keller, E. F. (2000a). The century of the gene. Cambridge, MA:
Harvard University Press.
Keller, E. F. (2000b). Decoding the genetic program: Or, some
circular logic in the logic of circularity. In P. J. Beurton, R.
Falk & H.-J. Rheinberger (Eds.), The concept of the gene
in development and evolution: Historical and epistemological
perspectives (pp. 159177). Cambridge: Cambridge Univer-
sity Press.
Kinzler, K. D., & Spelke, E. S. (2007). Core systems in human
cognition. Progress in Brain Research,164, 257264.
Lehrman, D. S. (2001). A critique of Konrad Lorenzs theory
of instinctive behavior. Cambridge, MA: The MIT Press.
LeVay, S., Wiesel, T. N., et al. (1980). The development of
ocular dominance columns in normal and visually deprived
monkeys. Journal of Comparative Neurology, 191(1), 151.
Levi-Montalcini, R. (1964). The nerve growth factor. Annals
of the New York Academy of Sciences,118, 149170.
Levi-Montalcini, R. (1987). The nerve growth factor 35 years
later. Science,237(4819), 11541162.
Lewontin, R. C. (1983). Genes, organism and environment.
Cambridge Cambridgeshire, In D. S. Bendall (Ed.), Evolu-
tion: From molecules to men (pp. 273285). New York:
Cambridge University Press.
Merzenich, M. M., & Jenkins, W. M. (1993). Reorganization of
cortical representations of the hand following alterations of
skin inputs induced by nerve injury, skin island transfers,
and experience. Journal of Hand Therapy,6(2), 89104.
Merzenich, M., Wright, B., Jenkins, W., Xerri, C., Byl, N.,
Miller, S., et al. (1996). Cortical plasticity underlying percep-
tual, motor, and cognitive skill development: Implications
for neurorehabilitation. Cold Spring Harbor Symposia on
Quantitative Biology,61,18.
Morange, M. (2001). M. Cobb, Trans.The misunderstood gene.
Cambridge, MA: Harvard University Press.
Moss, L. (2003). What genes cant do. Cambridge: The MIT
Press.
Newcombe, N. S. (2002). The nativist-empiricist controversy in
the context of recent research on spatial and quantitative
development. Psychological Science,13(5), 395401.
OLeary, D. D., Chou, S. J., et al. (2007a). Regulation of lami-
nar and area patterning of mammalian neocortex and
behavioural implications. Novartis Found Symp 288,
141159; discussion 159164, 276181.
OLeary, D. D., Chou, S. J., & Sahara, S. (2007b). Area pat-
terning of the mammalian cortex. Neuron,56(2), 252269.
OLeary, D. D., & Sahara, S. (2008). Genetic regulation of
arealization of the neocortex. [Research Support, N.I.H.,
Extramural Review]. Current opinion in neurobiology,18
(1), 90100.
Oyama, S. (2000). The ontogeny of information: Developmen-
tal systems and evolution (2nd ed.). Durham, NC: Duke Uni-
versity Press.
Oyama, S., Griffiths, P. E., & Gray, R. D. (2001). Introduction:
What is developmental systems theory? In S. Oyama, P. E.
Griffiths & R. D. Gray (Eds.), Cycles of contingency: Devel-
opmental systems and evolution (pp. 111). Cambridge, MA:
The MIT Press.
Pakkenberg, B., & Gundersen, H. J. (1997). Neocortical neu-
ron number in humans: Effect of sex and age. The Journal
of Comparative Neurology,384(2), 312320.
Pallas, S. L., Roe, A. W., & Sur, M. (1990). Visual projections
induced into the auditory pathway of ferrets. I. Novel inputs
to primary auditory cortex (AI) from the LP/pulvinar
complex and the topography of the MGN-AI projection.
The Journal of Comparative Neurology,298(1), 5068.
Sadler, T. W. (2006). Langmans medical embryology
(10th ed.). Philadelphia: Lippincott Williams and Wilkins.
Sarkar, S. (2000). Information in genetics and developmental
biology: Comments on Maynard Smith. Philosophy of Sci-
ence,67, 208213.
Schwaber, M. K., Garraghty, P. E., & Kaas, J. H. (1993).
Neuroplasticity of the adult primate auditory cortex follow-
ing cochlear hearing loss. The American Journal of Otology,
14(3), 252258.
Sirois, S., Spratling, M., Thomas, M. S., Westermann, G.,
Mareschal, D., & Johnson, M. H. (2008). Precis of
neuroconstructivism: How the brain constructs cognition.
The Behavioral and Brain Sciences,31(3), 321331, discus-
sion 331356.
Spelke, E. (2003). Core knowledge. In N. Kanwisher & J.
Duncan (Eds.), Attention and performance: Functional neu-
roimaging of visual cognition, (Vol. XX, pp. 2955). Oxford:
Oxford University Press.
Spelke, E., & Kinzler, K. D. (2009). Innateness, learning, and
rationality. Child Development Perspectives,3(2).
Stiles, J. (2008). The fundamentals of brain development:
Integrating nature and nurture. Cambridge, MA: Harvard
University Press.
Sur, M., Angelucci, A., & Sharma, J. (1999). Rewiring cortex:
The role of patterned activity in development and plasticity
of neocortical circuits. Journal of Neurobiology,41(1),
3343.
21
Sur, M., Garraghty, P. E., & Roe, A. W. (1988). Experimen-
tally induced visual projections into auditory thalamus and
cortex. Science,242(4884), 14371441.
Sur, M., & Leamey, C. A. (2001). Development and plasticity
of cortical areas and networks. Nature Reviews. Neurosci-
ence,2(4), 251262.
Sur, M., & Rubenstein, J. L. (2005). Patterning and plasticity
of the cerebral cortex. Science,310(5749), 805810.
von Melchner, L., Pallas, S. L., & Sur, M. (2000). Visual
behaviour mediated by retinal projections directed to the
auditory pathway. Nature,404(6780), 871876.
Wiesel, T. N. (1982). Postnatal development of the visual
cortex and the influence of environment. Nature, 299
(5884), 583591.
Wiesel, T. N., & Hubel, D. H. (1963a). Single-cell responses in
striate cortex of kittens deprived of vision in one eye. Jour-
nal of Neurophysiology, 26, 10031017.
Wiesel, T. N., & Hubel, D. H. (1965). Comparison of the
effects of unilateral and bilateral eye closure on cortical unit
responses in kittens. Journal of Neurophysiology, 28(6),
10291040.
Winship, I. R., & Murphy, T. H. (2009). Remapping the
somatosensory cortex after stroke: Insight from imaging
the synapse to network. The Neuroscientist,15(5), 507524.
Yamahachi, H., Marik, S. A., McManus, J. N., Denk, W., &
Gilbert, C. D. (2009). Rapid axonal sprouting and pruning
accompany functional reorganization in primary visual cor-
tex. Neuron,64(5), 719729.
Zecevic, N., Bourgeois, J. P., & Rakic, P. (1989). Changes in
synaptic density in motor cortex of rhesus monkey during
fetal and postnatal life. Brain Research. Developmental
Brain Research,50(1), 1132.
22
... Neurodevelopment is the biological process resulting in the development and maturation of the nervous system. In humans, the process starts at the third week of embryonic growth with the formation of the neural tube [1][2][3][4][5]. From the ninth week onward, the brain orderly maturates and acquires its typical structure, under a tightly orchestrated chain of events that includes abundant cell proliferation, migration, and differentiation [1,4,5]. ...
... In humans, the process starts at the third week of embryonic growth with the formation of the neural tube [1][2][3][4][5]. From the ninth week onward, the brain orderly maturates and acquires its typical structure, under a tightly orchestrated chain of events that includes abundant cell proliferation, migration, and differentiation [1,4,5]. Any disruption to such orderly and complex chain of events may lead to dysfunctional brain development, and consequently to a neurodevelopmental phenotype. ...
Article
Full-text available
Neurodevelopmental disorders (NDDs) represent a growing medical challenge in modern societies. Ever-increasing sophisticated diagnostic tools have been continuously revealing a remarkably complex architecture that embraces genetic mutations of distinct types (chromosomal rearrangements, copy number variants, small indels, and nucleotide substitutions) with distinct frequencies in the population (common, rare, de novo). Such a network of interacting players creates difficulties in establishing rigorous genotype-phenotype correlations. Furthermore, individual lifestyles may also contribute to the severity of the symptoms fueling a large spectrum of gene-environment interactions that have a key role on the relationships between genotypes and phenotypes. Herein, a review of the genetic discoveries related to NDDs is presented with the aim to provide useful general information for the medical community.
... Gelişim boyunca, kalıtımsal ve çevresel faktörler sürekli olarak etkileşime girerek, beynin gelişimine rehberlik eden dinamik süreçleri ve olayları yaratmaktadır. 17 Erken çocukluk döneminde beyin son derece esnektir (plastisite). Bu gelişmiş plastisite durumu beyni aynı zamanda her tür deneyime ve kırılganlığa da açık hale getirmektedir. ...
Article
ÖZET Dünya Sağlık Örgütü, beş yaşın altı 200 milyondan fazla çocuğun, yoksulluk, yetersiz beslenme ve güvenli olmayan ev ortamları da dahil olmak üzere çoklu risk faktörlerine maruz kaldığını, bu nedenle gelişim potansiyellerini gerçekletiremediğini bildirmektedir. Çocuğun gelişimi sırasında kalıtımsal ve çevresel faktörler sürekli olarak etkileşime girerek, gelişime rehberlik eden dinamik süreçleri yaratmaktadır. Epidemiyolojik, klinik ve gelişimsel araştırma çalışmaları, çevrenin yaşam boyunca bireyin fiziksel, bilişsel, sosyal ve duygusal gelişimi ile ruhsal sağlığı üzerine güçlü bir etkisi olduğunu göstermiştir. Anne-babalık, bebeklikten yetişkinliğe kadar olan dönemde duygusal, entelektüel, fiziksel ve sosyal gelişimi teşvik ederek bir çocuğu yetiştirme görevi olarak tanımlanmakta olup çocuk-çevre etkileşimine aracılık ederek çocuk sağlığının kalitesini belirlemektedir. Genlerin ve çevresel faktörlerin nasıl etkileşime girdiğini anlamaya yönelik araştırmalarda, kalıtımsal farklılıkların, çevresel etkilere maruz kalmanın ve bu etkilere maruz kalınan gelişimsel zamanın da önemli olduğu ve bu nedenle her çocukta etkileşimlerin aynı şekilde sonuçlanmadığı düşünülmektedir. Duyarlılık, sorumluluk, özen ve iletişimi içeren olumlu ebeveynlik, çocuklarda olumlu gelişimsel sonuçlar ile ilişkilendirilmektedir. Annebabalar çocuğun potansiyeline uygun büyüme ve gelişimini sağlayacak destekleyici ve geliştiren bakım çerçevesini oluşturacak ve genişletecek olan kişilerdir. Anahtar Kelimeler: Ebeveynlik; çocuk sağlığı; gelişim; çevre; kalıtım; gelişim ABSTRACT The World Health Organization reports that more than 200 million children under the age of five are not fulfilling their developmental potential due to exposure to multiple risk factors, including poverty, malnutrition and unsafe home environments. During the child's development, genetic and environmental factors constantly interact, creating dynamic processes that guide the child's development. Epidemiological, clinical and developmental research studies have shown that the environment has a strong influence on the physical, cognitive, social and emotional development and mental health of individuals throughout their lives. Different levels of co-existence of genetic and environmental factors have been used to explain variability in child health and development. It is thought that genotypes are also effective on children's behavior and development, and not all effects are purely genetic, the environment also shapes children's behavior and development. Healthy development is the result of interactions between key protective and risk factors during critical or sensitive developmental stages. Parenting is defined as the task of raising a child by promoting emotional, intellectual, physical and social development from infancy to adulthood, and determines the quality of child health by mediating the child-environment interaction. Positive parenting, which includes sensitivity, responsibility, care and communication, is associated with positive developmental outcomes in children. Parents are the people who will create and expand the supportive and nurturing care framework that will ensure the growth and development of the child in accordance with their potential. Keywords: Parenting; child health; development; nurture; nature
... Human brain development begins in the 3rd week of gestation and continuing until adulthood [1], with dynamic changes in the brain happening through childhood and adolescence. The complex process that is postnatal brain maturation involves the formation and maturation of tracts, combined with regressive processes including apoptosis of brain cells [2,3]. ...
Article
Full-text available
Brain development occurs until adulthood, with time-sensitive processes happening during embryo development, childhood, and puberty. During early life and childhood, dynamic changes in the brain are critical for physiological brain maturation, and these changes are tightly regulated by the expression of specific regulatory genetic elements. Early life insults, such as hypoxia, can alter the course of brain maturation, resulting in lifelong neurodevelopmental conditions. MicroRNAs are small non-coding RNAs, which regulate and coordinate gene expression. It is estimated that one single microRNA can regulate the expression of hundreds of protein-coding genes.. Uncovering the miRNome and microRNA-regulated transcriptomes may help to understand the patterns of genes regulating brain maturation, and their contribution to neurodevelopmental pathologies following hypoxia at Postnatal day 7. Here, using a PCR-based platform, we analyzed the microRNA profile postnatally in the hippocampus of control mice at postnatal day 8, 14, and 42 and after hypoxia at postnatal day 7, to elucidate the set of microRNAs which may be key for postnatal hippocampus maturation. We observed that microRNAs can be divided in four groups based on their temporal expression. Further after an early life insult, hypoxia at P7, 15 microRNAs showed a misregulation over time, including Let7a. We speculated that the transcriptional regulator c-myc is a contributor to this process. In conclusion, here, we observed that microRNAs are regulated postnatally in the hippocampus and alteration of their expression after hypoxia at birth may be regulated by the transcriptional regulator c-myc.
... 293−296 These steps of neuronal network organization can overlap or progress at a di erent pace in di erent brain areas and at di erent developmental stages. 293,294,297 In the human fetus, neuronal circuit formation starts with the proliferation of neuronal progenitor cells and radial glial cells, and the generation of immature neurons in the subgranular and subventicular zones of the dentate gyrus around gestational week 5. 293,298 Next, immature neurons undergo radial migration along radial glial cells and generate six cortical layers in an inside-out manner, 293,294,297,299 a process beginning around gestational week 7. 294,300,301 The innermost cortical layer is formed by the earliest-born neurons, while the outermost layer is formed by the latest born neurons and is completed around gestational week 18. 284,285,293,294,300,302,303 Around midgestation, neurites start to grow from immature neurons. This process is then followed by axonal elongation, dendritic arborization, and finally synaptogenesis. ...
Article
Full-text available
The widespread adoption of microfluidic devices among the neuroscience and neurobiology communities has enabled addressing a broad range of questions at the molecular, cellular, circuit, and system levels. Here, we review biomedical engineering approaches that harness the power of microfluidics for bottom-up generation of neuronal cell types and for the assembly and analysis of neural circuits. Microfluidics-based approaches are instrumental to generate the knowledge necessary for the derivation of diverse neuronal cell types from human pluripotent stem cells, as they enable the isolation and subsequent examination of individual neurons of interest. Moreover, microfluidic devices allow to engineer neural circuits with specific orientations and directionality by providing control over neuronal cell polarity and permitting the isolation of axons in individual microchannels. Similarly, the use of microfluidic chips enables the construction not only of 2D but also of 3D brain, retinal, and peripheral nervous system model circuits. Such brain-on-a-chip and organoid-on-a-chip technologies are promising platforms for studying these organs as they closely recapitulate some aspects of in vivo biological processes. Microfluidic 3D neuronal models, together with 2D in vitro systems, are widely used in many applications ranging from drug development and toxicology studies to neurological disease modeling and personalized medicine. Altogether, microfluidics provide researchers with powerful systems that complement and partially replace animal models.
... Beyond the first 1000 days, neurocognitive development is a result of early childhood and mid-childhood exposures: disease prevention, nutrition, security and safety, caregiving practices, and early learning possibilities. 4 16 38 39 One limitation of our study is the method used for assessing cognitive development. At 5 years of age, we used the Griffith's Mental Developmental Scales, which provides a score for five different developmental domains. ...
Article
Full-text available
Objective To assess whether intermittent preventive treatment of pregnant women (IPTp) with sulfadoxine-pyrimethamine (SP) and azithromycin (AZI) in a malaria-endemic area leads to sustained gains in linear growth and development in their offspring. Design Follow-up study of a randomised trial. Setting Mangochi District in rural southern Malawi. Participants 1320 pregnant women and their offspring. Interventions IPTp monthly with SP and twice with AZI (AZI-SP group), monthly with SP but no AZI (monthly SP), or twice with SP (control). No intervention was given to children. Main outcome measures Cognitive performance using Raven’s Coloured Progressive Matrices (CPM) at 13 years of age; mean height and height-for-age Z-score (HAZ), cumulative incidence and prevalence of stunting (HAZ <−2); weight, body mass index, mid-upper-arm circumference and head circumference. Results At approximately 13 years of age, the mean CPM score was 14.3 (SD 3.8, range 6–29, maximum 36), with no differences between groups. Children in the AZI-SP group were on average 0.4 cm (95% CI −0.9 to 1.7, p=0.6) taller than those in the control group. For cumulative incidence of stunting, the HR in the AZI-SP group was 0.72 (95% CI 0.61 to 0.84, p<0.001) compared with the control and 0.76 (95% CI 0.65 to 0.90, p<0.001) compared with the monthly SP groups. There was no intergroup difference in stunting prevalence or anthropometric measurements. Conclusions In rural Malawi, maternal intensified infection control during pregnancy reduces offspring’s cumulative incidence of ever being stunted by 13 years of age. In this study, there was no evidence of a positive impact on cognitive performance. Trial registration number NCT00131235 .
... In the study of Stiles (2011), the fundamental facts about brain development should be of critical importance to neuropsychologists trying to understand the relationship between brain and behavioral development. Nonetheless, the underlying presuppositions of most contemporary psychological models indicate mostly outdated notions regarding how the biological system occurs and what it intends to be innate. ...
Article
This article iterates and synthesizes findings from literature reviews that intended to describe and present the development of musical abilities. In this matter, the ability of music could be both influenced by society and/or by blood, in terms of genes; both science and experience contribute to this development. This study employed a descriptive method to gather information about present existing conditions through a library method and literature review. The data were analyzed using explanatory synthesis. Based on the literature review, the researcher identified two comparative views on the development of musical abilities: nature and nurture. The researcher used four criteria in synthesizing reviews such as cognitive development, intelligence, the relationship between nature and nurture, and musicality is nature, musical ability is nurtured. In conclusion, when it comes to musical ability, nature works in tandem with nurture; musical talent takes nature and nurture. The result of the perception in the origins and appearance of both the intelligence and action dwells in the discernment of how hereditary and social factors are involved in the active and interactional processes that specify and direct its development. The source and power of music could be some determined by association and/or by ancestry, in terms of genes; both scientific discipline and natural event impart to the development of musical abilities.
... Neurodevelopment is a complex set of biological processes that result in the orderly development and maturation of the nervous system 1 . Any disruption in this tightly orchestrated chain of events may lead to altered brain development and to an abnormal neurodevelopmental phenotype [2][3][4] . Factors that can disrupt neurodevelopment are not fully delineated, but a significant proportion of neurodevelopmental risk is attributed to copy number variants (CNVs) 5,6 . ...
Article
Full-text available
The 15q11.2 BP1-BP2 (Burnside-Butler) deletion is a rare copy number variant impacting four genes (NIPA1, NIPA2, CYFIP1, and TUBGCP5), and carries increased risks for developmental delay, intellectual disability, and neuropsychiatric disorders (attention-deficit/hyperactivity disorder, autism, and psychosis). In this case report (supported by extensive developmental information and medication history), we present the complex clinical portrait of a 44-year-old woman with 15q11.2 BP1-BP2 deletion syndrome and chronic, treatment-resistant psychotic symptoms who has resided nearly her entire adult life in a long-term state psychiatric institution. Diagnostic and treatment implications are discussed.
Chapter
There is continuing debate on the relative importance of genetic and environmental factors in determining our intellectual and learning abilities. Recent advances in neuroimaging and neuroscience research support the importance of both. While studies on gross and microscopic brain architecture allowed relating cognitive, motor and emotional functions to specific brain areas, newer imaging techniques provide data on signal transduction pathways across the living brain, further enhancing our understanding of the adult learning process. The NIH Human Connectome Project allowed the mapping of such pathways and clarifying how epigenetic factors and neuroplasticity help brain development in response to environmental influences such as cultural, nutritional and hormonal factors and physical exercise. Lessons from reverse-engineering the brain enabled the development of AI, virtual and augmented reality systems, neural networks and deep learning algorithms. The ongoing research on simulation neuroscience and reverse-engineering is expected to lead to the creation of biologically detailed digital reconstruction and simulation of the brain.
Article
Full-text available
This magnetoencephalography study aimed at characterizing age-related changes in resting-state functional brain organization from mid-childhood to late adulthood. We investigated neuromagnetic brain activity at rest in 105 participants divided into three age groups: children (6–9 years), young adults (18–34 years) and healthy elders (53–78 years). The effects of age on static resting-state functional brain integration were assessed using band-limited power envelope correlation, whereas those on transient functional brain dynamics were disclosed using hidden Markov modeling of power envelope activity. Brain development from childhood to adulthood came with (1) a strengthening of functional integration within and between resting-state networks and (2) an increased temporal stability of transient (100–300 ms lifetime) and recurrent states of network activation or deactivation mainly encompassing lateral or medial associative neocortical areas. Healthy aging was characterized by decreased static resting-state functional integration and dynamic stability within the primary visual network. These results based on electrophysiological measurements free of neurovascular biases suggest that functional brain integration mainly evolves during brain development, with limited changes in healthy aging. These novel electrophysiological insights into human brain functional architecture across the lifespan pave the way for future clinical studies investigating how brain disorders affect brain development or healthy aging.
Preprint
Full-text available
This magnetoencephalography study aimed at characterizing age-related changes in resting-state functional brain organization from mid-childhood to late adulthood. We investigated neuromagnetic brain activity at rest in 105 participants divided into three age groups: children (6-9 years), young adults (18-34 years) and healthy elders (53-78 years). The effects of age on static resting-state functional integration were assessed using band-limited power envelope correlation, whereas those on transient functional dynamics were disclosed using hidden Markov modeling of power envelope activity. Brain development from childhood to adulthood came with (i) a strengthening of functional integration within and between resting-state networks and (ii) an increased temporal stability of transient (100-300 ms lifetime) and recurrent states of network activation or deactivation mainly encompassing lateral or medial associative neocortical areas. Healthy aging was characterized by decreased static resting-state functional integration and dynamical stability within the visual network. These results based on electrophysiological measurements free of neurovascular biases suggest that functional brain integration mainly evolves during brain development, with limited changes in healthy aging. These novel electrophysiological insights into human brain functional architecture across the lifespan pave the way for future clinical studies investigating how brain disorders affect brain development or healthy aging.
Book
Full-text available
Article
Full-text available
Evelyn Fox Keller has been observing and reflecting on genetics for decades, first as a molecular biologist, later as a historian, best known for her biography of the corn geneticist and Nobel Prizewinner Barbara McClintock, and as a philosopher of science interested in gender and language. In The Century of the Gene, Keller offers a new interpretation of the past of genetics and a manifesto for its future. As she sees it, the transformation of genetics into genomics is a fundamental transformation, but it will remain incomplete unless, together with new data and new techniques, there are new concepts and new words as well.
Book
Full-text available
Article
Full-text available
The semantic concept of information is one of the most important, and one of the most problematical concepts in biology. I suggest a broad definition of biological information: a source becomes an informational input when an interpreting receiver can react to the form of the source (and variations in this form) in a functional manner. The definition accommodates information stemming from environmental cues as well as from evolved signals, and calls for a comparison between information-transmission in different types of inheritance systems-the genetic, the epigenetic, the behavioral, and the cultural-symbolic. This comparative perspective highlights the different ways in which information is acquired and transmitted, and the role that such information plays in heredity and evolution. Focusing on the special properties of the transfer of information, which are very different from those associated with the transfer of materials or energy, also helps to uncover interesting evolutionary effects and suggests better explanations for some aspects of the evolution of communication.
Article
Modern stereological methods provide precise and reliable estimates of the number of neurons in specific regions of the brain. We decided to estimate the total number of neocortical neurons in the normal human brain and to analyze it with respect to the major macro- and microscopical structural components, to study the internal relationships of these components, and to quantitate the influence of important physiological variables on brain structure. The 94 brains reported represent a consecutive collection of brains from the general Danish population. The average numbers of neocortical neurons were 19 billion in female brains and 23 billion in male brains, a 16% difference. In our study, which covered the age range from 20 years to 90 years, approximately 10% of all neocortical neurons are lost over the life span in both sexes. Sex and age were the main determinants of the total number of neurons in the human neocortex, whereas body size, per se, had no influence on neuron number. Some of the data presented have been analyzed by using new mathematical designs. An equation predicting the total neocortical neuron number in any individual in which sex and age are known is provided.
Article
Langman's Medical Embryology covers embryology for medical, nursing, and health professions students with a strong clinical emphasis. The text is highly valued as a teaching and learning resource for its clinical correlation boxes, summaries, problems to solve, illustrations and clinical images, and clear, concise writing style all of which make the subject matter accessible to students and relevant to instructors. Online material includes Simbryo an animation program showing processes, organs, and systems developing in human embryos as well as review questions and full text online. A separate Faculty Image Bank and PowerPoint presentations are also available."