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Principles of neuroplasticity and behavior
Bryan Kolb and Robbin Gibb
Behavioral neuroscience spent much of the twentieth
century seeking the fundamental rules of cerebral
organisation. One underlying assumption of much
of that work was that there is constancy in cerebral
organisation and function, both between and within
mammalian species (e.g., Kaas, 2006). One unex-
pected principle to emerge, however, was that
although there is much constancy in cerebral func-
tioning, there is remarkable variability as well. This
variability reflects the brain’s capacity to alter its
structure and function in reaction to environmental
diversity, thus reflecting a capacity that is often
referred to as brain plasticity. Although this term is
now commonly used in psychology and neuro-
science, it is not easily defined and is used to refer to
changes at many levels in the nervous system ranging
from molecular events, such as changes in gene
expression, to behavior (e.g., Shaw & McEachern,
2001). The relationship between molecular or cellular
changes and behavior is by no means clear and is
plagued by the problems inherent in inferring causa-
tion from correlation. Nonetheless, we believe that it
is possible to identify some general principles of brain
plasticity and behavior. As we do so we will attempt to
link these principles to potential clinical implications.
Assumptions underlying brain plasticity
As we consider the principles of brain plasticity, we
need to consider five underlying assumptions that
will color our perspective.
Brain plasticity takes advantage of a basic,
but flexible, blueprint for cerebral organisation
that is formed during development
The process of brain development is a remarkable
feat of nature. Billions of neurons and glia must be
generated, they must migrate to their correct loca-
tions, and they must form neuronal networks that
can underlie functions that range from as simple as
postural reflexes to complex thought. Although a
complete genetic blueprint for neuronal organisa-
tion might be possible for a simple creature like the
nematode Caenorhabditis elegans, which has a total
of 302 neurons, it is not remotely possible for the
mammalian brain to have a specific blueprint (Katz,
2007). The best that nature can be expected to do is
to produce a rough blueprint of cerebral organisa-
tion that must be shaped by experience in order for
animals to exploit specific ecologies, including cul-
tures. The disadvantage of such flexibility is that it is
possible to make errors, but this problem is certainly
outweighed by the advantage of having a brain that
can learn complex motor or perceptual skills that
could scarcely have been anticipated by evolution
thousands or even millions of years before.
Cerebral functions are both localised
One of the great issues in the history of brain
research relates to whether functions are discretely
localised in the brain (for a review, see Kolb &
Whishaw, 2001). The resolution to this debate was
important because the degree of localisation of
Cognitive Neurorehabilitation, Second Edition: Evidence and Application, ed. Donald T. Stuss, Gordon Winocur and
Ian H. Robertson. Published by Cambridge University Press. © Cambridge University Press 2008.
[6–21] 15.3.2008 1:02PM
function places constraints on the potential extent
of functional plasticity. The more distributed a
function, the greater the likelihood that the neural
networks underlying the function will be flexible
after a brain injury. As we enter the twenty-first
century it is clear that functions are at once localised
and distributed. Consider language. Although there
are discrete language zones in the cortex, language
is much more distributed across the cortex than
would have been expected from the classical neu-
rologists (e.g., Geschwind, 1972). But there are limits
to distributed functions, especially in the sensory
systems. For example, information coming to the
occipital lobe travels from the eye to subcortical
areas, then to Visual area 1 (V1) where it is pro-
cessed, and then is sent on to other visual regions
such as V2 and on to V3 etc. If V1 is only partially
damaged, V2 will still receive some input and can
function, albeit not normally. Further, after partial
damage, neural networks in V1 and V2 could reor-
ganise and possibly facilitate some type of func-
tional improvement. But if V1 is completely (or
substantially) damaged, downstream visual areas,
such as V2, will not be provided with appropriate
inputs and no amount of reorganisation in V2 could
instantiate functional recovery. The partial localisa-
tion of functions thus places significant constraints
upon plasticity and recovery of function.
Changes in the brain can be shown at many
levels of analysis
Although it is ultimately the activity of neuronal
networks that controls behavior, and thus changes
in neuronal network activity that are responsible for
behavioral change, there are many ways to examine
changes in the activity of networks. Changes may be
inferred from global measures of brain activity, such
as in the various forms of in vivo imaging, but such
changes are far removed from the molecular pro-
cesses that drive them. Changes in the activity of
networks likely reflect changes at the synapse but
changes in synaptic activity must result from more
molecular changes such as modifications in chan-
nels, gene expression, and so on. The problem in
studying brain plasticity is to choose a surrogate
marker that best suits the question being asked.
Changes in potassium channels may be perfect for
studying presynaptic changes at specific synapses
that might be related to simple learning in inverte-
brates (e.g., Kandel, 1979; Lukowiak et al., 2003;
Roberts & Glanzman, 2003) but are impractical for
understanding sex differences in language process-
ing. The latter might best be studied by in vivo
imaging or postmortem analysis of cell morphology
(e.g., Jacobs et al., 1993). Neither level of analysis is
“correct.” The appropriate level must be suited for
the research question at hand.
One convenient surrogate for synaptic change in
laboratory studies of brain and behavior is dendritic
morphology. In this type of study entire neurons are
stained with a heavy metal (gold, silver or mercury)
and the dendritic space is calculated (Figure 1.1). It
is assumed that by knowing the space available for
Figure 1.1. Example of a Golgi-Cox stained pyramidal cell
from layer III of the parietal cortex of th e rat. A. Higher
power magnification showing spines on an apical branch.
B. Higher power magnification showing spines on a basilar
branch. (Photograph courtesy of Grazyna Gorny.)
Principles of neuroplasticity and behavior 7
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synapses it is possible to infer associations between
synaptic organisation and behavior – notwithstanding
the problems inherent in correlational studies dis-
cussed below. The studies of Jacobs and Scheibel
(Jacobs et al., 1993; Jacobs & Scheibel, 1993) provide
a good example. These researchers examined the
dendritic morphology of pyramidal neurons in post-
mortem brains of people whose educational and
employment history was known. Comparison of
synapse numbers in the posterior speech zone of
people with university education, high-school edu-
cation, or less than high-school education showed
that there were progressively more synapses on the
neurons from brains with more education. The
study cannot tell us why this correlation is present
but it tells us that there is some relationship
between experience and synaptic organisation.
To be functionally meaningful, changes
reflecting brain plasticity must persist for at
least a few days
Changes in neuronal activity related to brain plasti-
city may be of limited duration, perhaps in the order
of seconds or milliseconds. While such changes are
interesting in their own right, we are focusing our
attention on longer-lasting changes that persist for
at least a few days. This is a practical assumption as
we think about how experiences might be related to
chronic behavioral changes seen after brain injury
or with addiction.
Correlation is not a four-letter word
By its very nature, behavioral neuroscience searches
for neuronal correlates of behavior. Some of these
changes are directly associated with behavior but
others are more ambiguous. Consider an example.
If an individual is given a psychoactive drug we may
see an obvious acute behavioral change such as
increased motor activity. If the drug is taken repeat-
edly, we may see that there is an escalating increase
in the drug-dependent hyperactivity, a phenom-
enon referred to as drug-induced behavioral sensiti-
sation. If we were to look for changes in the brain
that were related to the observed sensitisation we
might find a change in synapse number in some
discrete brain region such as the nucleus accum-
bens (NAcc). Both the behavioral change and the
synaptic change are correlates of the drug adminis-
tration. But what is the relationship between the
behavioral and synaptic change? We can conclude
that the drug caused the behavioral change but it is
less clear that the drug directly caused the neuronal
change. Perhaps the behavioral change caused the
neuronal change or maybe both were related to
some other change in the brain. Thus, a common
criticism of studies trying to link neuronal changes
to behavior is that “they are only correlates.” This is
true but it is hardly a reason to dismiss such studies.
The task is to try to break the correlation by showing
that one change can occur without the other. The
presence of such evidence would disconfirm cau-
sality but, unfortunat ely, the failure to break the
correlation is not proof of causation. Ultimately
the proof would be in showing how the synaptic
changes arose, which would presumably involve
molecular analysis such as a change in gene tran-
scription. For many studies this would be an
extremely difficult challenge and often impractical.
It is our view that once we understand the “rules”
that govern neuronal and behavioral change, we will
be better able to look for molecular changes.
Furthermore, we argue that a certain level of ambi-
guity in the degree of causation is perfectly justifi-
able at this stage of our knowledge. Understanding
the precise mechanism whereby the synaptic
changes might occur is not necessary to proceed
with further studies aimed at improving functional
Principles of brain plasticity
Although it is presumptuous to try to identify basic
principles of brain plasticity when so much is still
unknown, we believe that the progress over the past
decade allows us to begin to identify some of the
rules underlying brain plasticity. These principles
should be seen as a work in progress that will
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[6–21] 15.3.2008 1:02PM
undoubtedly be expanded and further demonstra-
ted over the next decade.
When the brain changes, this is reflected in
The primary function of the brain is to produce
behavior but behavior is not constant. We learn
and remember, we create new thoughts or images,
and we change throughout our lifetime. All of these
processes require changes in neural networks. It
follows that whenever neural networks change,
behavior, including mental behavior, will also
change. A corollary of this principle is that in order
to change behavior we must change the brain. This
latter idea is especially important as we search for
treatments for brain injuries or diseases.
Plasticity is found in all nervous systems and
the principles are conserved
Even the simplest animals, such as the nematode
C. elegans, can show simple learning that is corre-
lated with neuronal plasticity (e.g., Rose & Rankin,
2001). Similarly, there is now an extensive literature
showing neuronal and other changes in invertebrates
such assea snailAplysia during simplelearning, inclu-
ding associative learning. Furthermore, it now has
become clear that both simple and complex nervous
systems show both pre- and postsynaptic changes
and that the changes are remarkably similar (e.g.,
Rose & Rankin, 2001). There is reason to believe,
for example, that there are NMDA-like changes in
learning in both mammals and invertebrates (e.g.,
Roberts & Glanzman, 2003). The details of the postsy-
naptic second messengers may differ in simple and
complex systems but the general principles appear to
be conserved across both simple and complex animals.
The brain is altered by a wide range
Virtually every experience has the potential to alter
the brain, at least briefly. It now has been shown
that a wide variety of experiences can also produce
enduring changes, ranging from general sensory-
motor experience to psychoactive drugs to electrical
brain stimulation (see Table 1.1). The bulk of these
studies have used morphological techniques such
as electron microscopy or Golgi-like stains and have
shown that experience-dependent changes can be
seen in every species of animals tested, ranging
from fruit flies and bees to rats, cats and monkeys
(for a review see Kolb & Whishaw, 1998). Consider a
When animals are placed in complex environ-
ments rather than simple laboratory cages, within
30 days there is about a 5% increase in brain weight
and cortical thickness, an increase in cortical ace-
tylcholine and neurotrophic factors (e.g., nerve
growth factor (NGF), brain-derived neurotrophic
factor (BDNF), fibroblast growth factor-2 (FGF-2)),
as well as changes in physiological properties of
neurons such as those measured in studies of
Table 1.1. Factors affecting the synaptic organisation
of the normal brain
Sensory and motor experience
Greenough & Chang,
Task learning Greenough & Chang,
Gonadal hormones and stress
Stewart & Kolb, 1988
Psychoactive drugs (e.g.,
Robinson & Kolb,
Neurotrophic factors (e.g., NGF,
Kolb et al., 1997
Natural rewards (e.g., social
Fiorino & Kolb, 2003
Ageing Kramer et al., 2004
Stress McEwen, 2005
Anti-inflammatories (e.g., COX-2
Silasi & Kolb, 2007
Diet (e.g., choline) Meck & Williams,
Electrical stimulation: kindling Teskey et al., 2001
LTP Ivanco et al., 2000
Direct cortical stimulation Teskey et al., 2004
Principles of neuroplasticity and behavior 9
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long-term potentiation (LTP) (for a review see Kolb
& Whishaw, 1998). Although most studies have
focused on neocortical changes, similar changes
can also be seen in hippocampus and striatum
(e.g., Comery et al., 1996; Juraska, 1990). The ana-
tomical and physiological changes are associated
with improved performance on tests of both motor
and cognitive behaviors and although the data are
correlational, it is generally assumed that the mor-
phological changes are responsible for the facilita-
tion in behavior.
Experience-dependent changes in the brain do
not require procedures as intense as complex hous-
ing, however. Increased social experience selec-
tively increases synapses in the orbital frontal
cortex (Fiorino & Kolb, 2003; Hamilton et al., 2003).
We have also seen that tactile stimulation either in
infancy or adulthood alters cells in sensorimotor
cortex (e.g., Gibb & Kolb, submitted a,b). This latter
treatment has also been used in animals with cort-
ical injuries to stimulate dendritic growth and facil-
itate functional recovery. Although there is little
evidence that exercise can enhance plasticity in
the normal brain, there is growing evidence that it
can facilitate plastic changes in the injured lab ani-
mal and human brain (e.g., Gibb et al., 2005; Kramer
et al., 2006).
A final example can be seen in the effects of psy-
choactive drugs. Robinson & Kolb (1999a) showed
that repeated doses of amphetamine or cocaine
given to rats produced a persisting increase in den-
dritic length and spine density localised to the
medial prefrontal cortex (mPFC) and NAcc but not
to adjacent sensorimotor cortical regions. It now
appears that repeated doses of all psychoactive
drugs, including prescription drugs, change neuro-
nal morphology. The details of drug-induced mor-
phological changes vary with the drug but the
general principle is that psychoactive drugs alter
neuronal morphology in the cerebrum and this
can be seen both in dendritic measures as well as
in a variety of more molecular measures (for a
review, see Hyman et al., 2006). Once again, the
relationship between the behavioral changes, such
as drug-induced behavioral sensitisation, and the
altered neuronal networks has yet to be proven but
there is little doubt that the chronic effects of drug
use are not neutral to cerebral functioning. The
ability of drugs to alter neuronal morphology may
be important for rehabilitation because drugs can
be combined with behavioral treatments such as
rehabilitation therapy, including cognitive therapy
(e.g., Gonzalez et al., 2006).
Taken together the examples described above
illustrate the power of experience in modulating
cerebral networks and in facilitating remodeling
stimulated by behavioral therapies. Although expe-
rience is likely more effective in remodeling neural
networks as they are repairing after injury, improve-
ment still can occur late after injury (e.g., Hodics
et al., 2006). Psychomotor stimulants may provide a
powerful way of reinstigating cerebral plasticity late
after injury to facilitate the effectiveness of behav-
Plastic changes are age-specific
When weanling, adult, or senescent rats were placed
in a complex environment, we had anticipated that
we would find larger changes in the younger ani-
mals but to our surprise, we found a qualitative
difference in the neuronal response to the same
experience. Thus, whereas rats at all ages showed
an increase in dendritic length and branching in
neocortical pyramidal cells after complex housing,
rats placed in the environments as infants showed a
decrease in spine density whereas young adult or
senescent rats showed an increase in spine density
(Kolb et al., 2003a). A similar drop in spine density
was found in later studies in which newborn rats
were given tactile stimulation with a soft brush for
15 min, three times daily over the first 10 days of life
(Kolb & Gibb, submitted).
The obvious question is whether the behavioral
effects to the complex housing are the same
depending upon the age at experience. Our early
results suggest that there is an advantage in both
cognitive and motor tasks and that it does not mat-
ter when the experience occurred. There are clearly
different ways to organise neuronal networks to
10 Bryan Kolb and Robbin Gibb
[6–21] 15.3.2008 1:02PM
enhance both motor and cognitive behaviors. This
point is important as we consider treatments for
brain dysfunction – there may be many ways to
Early events, including prenatal events, can
influence the brain throughout life
Our finding that early postnatal experiences could
alter neuronal organisation led us to ask if prenatal
experiences might also alter cerebral organisation.
In one study pregnant dams were placed in complex
environments for 8 hours a day prior to their preg-
nancy and then throughout the 3 week gestation. (In
different studies the dams were in the environments
during the day or night but it made no difference.)
Analysis of the adult brains of their infants showed a
decrease in dendritic length and an increase in spine
density in adulthood (Gibb et al., submitted). We
were surprised both that there was a large effect of
prenatal experience and that it was qualitatively
different than experience either in the juvenile
period or in adulthood. More recently we have
shown that a variety of prenatal experiences alter
brain organisation in adulthood including prenatal
tactile stimulation (i.e., stimulation of the pregnant
dam), exercise during pregnancy, prenatal stress
and psychoactive drugs. All of these experiences
also chronically alter motor and cognitive functions,
with the precise effect varying with the different
experiences (for a review see Kolb et al., in press).
Although we do not know how these prenatal
changes might influence the effect of postnatal
experiences, it is clear that prenatal experiences
produce chronic effects on brain organisation and
behavior. One is reminded here of the idea of cog-
nitive (or neural) reserve as being key factors in the
onset of dementias (e.g., Stern, 2006). Might early
life events influence cognitive reserve in adulthood
Plastic changes are area dependent
Although we are tempted to expect plastic changes in
neuronal networks to be fairly general, it is becoming
clear that many experience-dependent changes are
highly specific. The clearest examples can be seen in
neuropsychological studies in which animals are
trained on cognitive or motor tasks. For example,
rats trained on a visuospatial task show specific
changes in visual cortex whereas rats trained on
motor tasks show specific changes in motor cortex
(e.g., Greenough & Chang, 1989; Kolb & Cioe, sub-
mitted; Withers & Greenough, 1989). Such task-
dependent specific changes are reasonable in view
of the relative localisation of functions in the cortex.
But not all area-dependent changes are so easily
predicted. Consider two examples.
We noted above that the effect of psychoactive
drugs appeared to be selective to regions that
receive dopaminergic innervation. We therefore
were surprised to find that the orbitofrontal cortex
(OFC), another region that receives dopaminergic
innervation, showed drug-induced changes that are
opposite to those in mPFC and NAcc (Robinson &
Kolb, 2004). Thus, whereas psychomotor stimulants
increased dendritic length and spine density in the
mPFC, they decreased the same measures in
the OFC. The contrasting effects of these drugs on
the two prefrontal regions are puzzling given the
similarity in thalamic and other connections of the
two regions (e.g., Uylings et al., 2003). Curiously,
there also are differential effects of gonadal hor-
mones on the two prefrontal regions as well: mPFC
neurons have more synaptic space in males whereas
OFC neurons have more space in females (Kolb &
Stewart, 1991). Although we do not yet know what
such differences mean behaviorally, there can be
little doubt that the differential response of two
such similar cortical regions to drugs and hormones
must be important in understanding their functions.
Plastic changes are time-dependent
There is growing evidence that plastic changes are
not constant and can change over time. The clearest
example comes from drug studies. For example,
although there are large increases in spine density
and dendritic length 2 weeks after cessation of cocaine
administration, these changes slowly disappear over a
Principles of neuroplasticity and behavior 11
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4-month period (Kolb et al., 2003b). In contrast,
when rats are given morphine and the brains are
examined immediately after drug cessation, there
is an increase in dendritic arborisation in NAcc
ez et al., 2006) but a month later
the changes are just the opposite (Robinson & Kolb,
1999b). One reason for the time-dependent effects
of the drug exposure may be that behavior is chang-
ing as the animals are first in withdrawal and then
adapt to the drug’s absence.
Time-dependent plasticity also can be seen in
response to repeated electrical brain stimulation.
Repeated low intensity stimulation can slowly lead
to the development of spontaneous seizures, a phe-
nomenon known as kindling (Teskey, 2001). The
development of seizures is correlated with changes
in dendritic length and spine density that normalise a
month after cessation of electrical stimulation
(Teskey et al., 2001). Curiously, the stimulation also
produces physiological changes that do not change.
In this case it appears that the experience (i.e., the
electrical stimulation) produces both dendritic and
physiological change but the two are not related.
The possibility that there are different chronic
and transient experience-dependent changes in
cerebral neurons is consistent with genetic studies
showing that there are different genes expressed
acutely and chronically in response to complex
environments (Rampon et al., 2000). The difference
in how transient and persistent changes in neuronal
networks relate to behavior is unknown.
Brain injury produces plastic changes
that vary with etiology
Although we may be able to point to a specific prox-
imal cause of a brain injury, such as a stroke, the end
result of brain injury is not the result of a single
causative event. Rather, there is an initial event fol-
lowed by a cascade of cellular events that can seri-
ously compromise the injured brain as well as brain
regions that were not directly injured. Such post-
injury changes may be rapid, such as changes in pH
or ionic balance that can occur within seconds or
minutes after an injury, or they may be slower such
as the production of glia that migrate to the injured
tissue. Of more interest, however, are the longer-
term changes in neuronal networks that underlie
the emerging post-injury functions. The nature of
these changes varies with the cause of the injury.
The adult brain can be injured in numerous ways,
including especially stroke, head trauma, and neu-
rosurgical excision for disease. The literature on
functional recovery and rehabilitation quite reason-
ably has assumed that after the initial post-injury
period, patients with different types of brain injuries
are likely to benefit similarly from treatments.
However, this presumption rests on the assumption
that the reparative processes that spontaneously
begin after injury are similar for different types of
injuries. A study by Gonzalez & Kolb (2003) leads us
to question this assumption.
These authors gave rats equivalent lesions of the
sensorimotor cortex but produced the damage
either by arterial occlusion, vascular stripping, or
surgical suction. The behavioral outcomes were
similar in three groups, with severe chronic motor
symptoms in the contralateral limbs. Similarly, the
infarct volumes were essentially identical across the
groups. What was surprising, however, was when
the authors examined the morphology of neurons
in the striatum and perilesional area they found that
each group was different (see also Szele et al., 1995).
For instance, the brains with suction lesions showed
atrophy of dendritic fields, whereas the brains of
animals with vascular stripping lesions showed
reconfigured fields with increased dendritic arbor-
isation. We hasten to note, however, that the behav-
ioral recovery within the different groups was
comparable, at least with the behavioral measures
that the authors employed. This finding is reminis-
cent of the evidence showing that perinatal experi-
ences can have different effects on brain organisation
but similar effects on behavior.
One message from the Gonzalez and Kolb study is
that capacity for treatment-induced recovery is
likely not equivalent after injuries with differing
etiologies because the brain is changing differently
with different etiologies. This conclusion has obvious
implications for rehabilitation of human patients
12 Bryan Kolb and Robbin Gibb
[6–21] 15.3.2008 1:02PM
although we unaware of any direct studies on
Neuronal plasticity following brain injury
varies with age
It has been known since the time of Broca that
children seem to have a better outcome after early
injury than adults, but we are just beginning to
understand why this might be so. The first system-
atic studies on the comparative effects of early brain
injury were done by Margaret Kennard, who studied
the effects of motor cortex lesions in infant mon-
keys. Her seminal observation was that the animals
with early lesions showed better recovery of motor
functions than those with injuries in adulthood
(e.g., Kennard, 1942). Although there was later sup-
port for the Kennard findings that “earlier is better”
(e.g., Akert et al., 1960), other studies in monkeys
were less supportive (Goldman, 1974). It was not
until age was systematically varied in studies in
rats and cats that the relationship between age at
injury and functional outcome became clearer.
We have examined the behavior of adult rats that
had focal injuries to the mPFC, motor, temporal,
posterior parietal, or posterior cingulate cortex at
postnatal days 1, 4, 7, 10, or 90 (i.e., adult). The
overall result was that regardless of the location of
injury, the functional outcome was always best after
injury during the second week of life, which in the
rat is a time of intense cerebral synaptogenesis and
glial formation. A similar pattern of results can be
seen in parallel studies of the effects of cortical
lesions in kittens by Villablanca and his colleagues
(e.g., Schmanke & Villablanca, 2001; Villablanca
et al., 1993), although because the rat and cat
develop at different rates the precise ages are differ-
ent in the two species. The key point here is that
birth date is irrelevant – it is the stage of neural
development that is important.
But what brain changes account for the age effects?
In principle, there are three ways that an injured
brain could compensate for lost tissue: (1) reorgan-
isation of existing neuronal networks; (2) develop-
ment of novel networks; and (3) regeneration of the
lost tissue. All three occur after early brain injury.
We consider each briefly.
The first studies on anatomical compensations
after early brain injury focused on connectivity
after unilateral damage to the motor system (e.g.,
Castro, 1990; D’Amato & Hicks, 1980; Villablanca &
Gomez-Pinilla, 1987; Whishaw & Kolb, 1988). The
general finding was that if there is perinatal damage
to the cortex that normally gives rise to the cortico-
bulbar and corticospinal pathways, the intact path-
way on the opposite side sprouts new connections
both to subcortical motor regions of the damaged
hemisphere as well as through an enlarged ipsilat-
eral corticospinal pathway. These new pathways are
believed to underlie the better motor outcomes of
the early injuries. Parallel findings are seen in the
sensory systems as novel pathways develop after
damage to primary visual cortex (see a review by
Payne & Lomber, 2001). Curiously, however, novel
pathways are not always beneficial. We have found
that damage to the mPFC in the first week of life
results in many anomalous networks but this is
correlated with poor outcome on various measures
of cognitive function (Kolb et al., 1994). In general,
however, the development of novel networks pro-
vides one explanation for the Kennard effect.
Another way to make inferences about neuronal
network remodeling is to examine dendritic morphol-
ogy after early injuries. The overall result of these
studies is that when functional outcome is good,
there is an increase in dendritic arborisation and
spine density in pyramidal neurons in the remaining
cortical mantle (e.g., Kolb et al., 1992, 1994; Kolb &
Whishaw, 1989). In contrast, when functional out-
come i s poor, there is an atrophy of dendritic arbor
and spine density. The emergence of the beneficial
compensatory changes in dendritic organisation takes
several weeks and is correlated with an emergence of
the improved cognitive function (Kolb & Gibb, 1993).
The idea that the generation of new tissue might be
possible after cerebral injury in postnatal mammals
was slow to develop and faced considerable skepti-
cism (e.g., Altman, 1962). There now is compelling
evidence that new neurons can be formed after
injury (see Chapter 22 by Stickland, Weiss, & Kolb,
Principles of neuroplasticity and behavior 13
[6–21] 15.3.2008 1:02PM
this volume) and especially after neonatal injury
(Kolb et al., 1998). For example, rats with mPFC
lesions around postnatal day 10 show a spontane-
ous regeneration of much of the lost tissue. Removal
of the tissue removes the functional recovery and
blockade of the tissue regrowth prevents the recov-
ery (e.g., Dallison & Kolb, 2003; Kolb et al., 1998).
Although the spontaneous regeneration can occur
after mPFC lesions such regeneration is uncom-
mon, but it can be induced by infusion of FGF-2
after cortical injury on day 10 (e.g., Monfils et al.,
2006). Again in these studies the removal of the new
tissue leads to a return of the functional deficits and
prevention of the regrowth prevents the functional
The effect of age on post-injury plasticity is likely
not only relevant during development. Teuber
(1975) reported that brain-injured soldiers also
showed a benefit of being younger: 18-year-olds
fared better than 25-year-olds who fared better
than older soldiers. It is generally assumed that
plastic changes are less likely to occur as the brain
ages but this has not been well studied and there is
little doubt that even senescent animals can show
considerable cortical plasticity (e.g., Kolb et al.,
2003a; Kramer et al., 2004). There still needs to be
systematic studies of cerebral plasticity and behav-
ior throughout the lifespan in both normal and
Experience-dependent changes interact
As animals travel through life they have an almost
infinite number of experiences that could alter brain
organisation. There are virtually no experimental
studies attempting to determine how a lifetime’s
experiences might interact. We attempted to
address this question in a series of studies in which
animals received psychoactive drugs before place-
ment in complex environments (Hamilton & Kolb,
2005; Kolb et al., 2003b; Li et al., 2005). We hypoth-
esised that because the mPFC and NAcc were so
profoundly altered by the drugs, they might show
less (or no) change in response to the housing expe-
rience. To our surprise, not only did the mPFC and
NAcc show no response to the experience, but nei-
ther did any other cortical regions. For example,
pyramidal neurons in the parietal cortex, which
normally show large experience-dependent change
but little drug-dependent change, showed no
response to the complex housing after prior experi-
ence with amphetamine, cocaine, or nicotine. An
obvious question was whether prior experience
with complex housing would interfere with drug-
dependent changes. It does. Animals given complex
housing experience prior to repeated doses of nic-
otine show a much attenuated response to the drug.
Another example of interactions in experience-
dependent changes can be seen in the sexually
dimorphic response of cortical and hippocampal
neurons to complex housing. Juraska (1990) has
shown that whereas occipital cortex neurons show
increased dendritic arbor in response to complex
housing in males, there are no such changes in
females. In contrast, females show increased den-
dritic arbor in hippocampus whereas males do not.
One of the most common experiences of everyday
life is stress. In view of the significant effects of stress
on dendritic morphology and neurogenesis (see
Chapter 4 by Hunter & McEwen, this volume) it
seems likely that stress will interact with other
experience-dependent changes. We have found,
for example, that prenatal stress will block the nor-
mal recovery from cortical injury in the second week
of life (Gibb & Kolb, unpublished).
Finally, we note that prenatal exposure to experi-
ences described above interact with later postnatal
brain injury to produce differential changes in neuro-
nal networks and correlated functional recovery. For
instance, rats given prenatal experience via their
mother’s exposure to tactile stimulation or complex
housing show an attenuated effect of the later expe-
rience to perinatal brain injury and in some instances
show almost complete recovery that is correlated
with enhanced dendritic changes (Gibb et al., sub-
mitted). In contrast, rats exposed to stress or fluoxe-
tine prenatally show an exaggerated behavioral effect
of the same perinatal brain injuries and the poor
outcome is correlated with an apparent blockade of
post-injury compensatory changes (Day et al., 2003).
14 Bryan Kolb and Robbin Gibb
[6–21] 15.3.2008 1:02PM
Experience differentially affects the normal
and injured brain
We initially assumed that a given experience would
produce similar changes in the normal and injured
brain although there might be quantitative differen-
ces in the two conditions. It is now becoming clear
that the same experience can sometimes have the
opposite effect in the normal and injured brain.
One example is tactile stimulation during infancy:
there is a decrease in spine density in otherwise
normal animals but an increase in cortically injured
animals (Kolb & Gibb, submitted). Preliminary stud-
ies show similar paradoxically different effects of
other treatments such as complex housing and psy-
choactive drugs. This type of finding has important
implications for the development of rehabilitative
treatments so we need to understand why the effects
are different in the normal and injured brain.
Understanding normal plasticity gives us a key
to fixing the abnormal brain
It is our working hypothesis that as we learn more
about how the normal brain can be changed by
experience we will be able to apply this knowledge
to the injured brain. This strategy is proving to be
successful and Tables 1.2 and 1.3 summarise exam-
ples of developing treatments for damage to adult
and infant brains, respectively. The general conclu-
sion from this literature is that many, but not all,
factors that produce dendritic reorganisation and
functional benefit in the normal brain can provide
benefit after brain injury in both adults and infants.
The greatest benefit to lab animals with injury at
any age is clearly complex housing. As noted earlier,
complex housing leads to increases in various
growth factors, and includes social stimulation, sen-
sory stimulation, and increased motor activity. It is
likely the combination of all of these factors that
provides the large benefit. A key feature too is that
there is 24 hours of stimulation 7 days a week, rather
than an hour or so twice a week as might be more
likely with typical therapy given to human brain-
injured patients. Although it would be ideal to
provide human patients with some type of equiva-
lent therapy this would likely be impractical for
most health-care systems to provide. Furthermore,
placing animals or human patients with severe
motor deficits in complex environments is likely to
be quite stressful so we need to look at alternate
treatments. To date, the most promising treatments
include the use of psychomotor stimulants such as
amphetamine (Sutton et al., 1989) or nicotine
(Gonzalez et al., 2006). Clinical trials with amphet-
amine have given uneven results, likely because of
differences in lesion size. Laboratory studies suggest
that whereas rats with small lesions show a signifi-
cant benefit of amphetamine, those with large
Table 1.2. Factors enhancing recovery of the injured
Biernaskie & Corbett, 2001
Olfactory stimulation Gonzalez & Kolb, 2006
Psychoactive drugs (e.g.,
Sutton et al., 1989
Neurotrophic factors (e.g.,
nerve growth factor)
Kolb et al., 1997
Silasi & Kolb, 2007
Electrical stimulation Teskey et al., 2004
Inosine Chen et al., 2002
Antibodies to No-Go Papadopoulos et al., 2006
Table 1.3. Factors enhancing recovery from early injury
Postinjury complex housing
Kolb & Elliott, 1987
Postinjury tactile stimulation Gibb & Kolb, submitted b
Prenatal complex housing Gibb et al., submitted
Prenatal tactile stimulation Gibb & Kolb, submitted a
Gonadal hormones Kolb & Stewart, 1995
Neurotrophic factors (e.g.,
fibroblast growth factor-2)
Comeau et al., 2007
Diet (e.g., choline; vitamins/
Halliwell et al., submitted
Olfactory stimulation Gonzalez & Kolb, 2006
Principles of neuroplasticity and behavior 15
[6–21] 15.3.2008 1:02PM
lesions do not (Goldstein & Davis, 1990). Nicotine
may prove to be more effective as it has wider-
spread changes in neuronal morphology in the nor-
mal brain and preliminary laboratory studies do
show that nicotine is much more effective than
amphetamine in treating animals with large cortical
strokes (Moroz & Kolb, 2005).
One additional treatment that is proving to be
effective in treating both laboratory animals and
stroke patients is direct cortical electrical stimula-
tion (Kleim et al., 2003; Teskey et al., 2003). An
obvious extension of the electrical stimulation stud-
ies is the combination of the stimulation with other
factors such as sensory or motor therapies or psy-
chomotor stimulation, although to our knowledge
this has not yet been tried. We note too that pre-
injury experiences may interact with post-injury
treatments. Recall the complex interactions of experi-
ence and dr ugs discussed above. In one preliminary
study we did show that prior exposure to nicotine
blocked the effectiveness of post-injury nicotine treat-
ment, a result reminiscent of the drug/environment
studies (Gonzalez & Kolb, unpublished observations).
In sum, we believe that there is considerable
potential in treating brain injury with factors that
are known to enhance brain plasticity in the normal
animal. It is likely that combinations of treatments
will prove the most effective. We do note too, how-
ever, that it is quite likely that injuries of different
etiologies will respond differently to specific factors.
The relative strength (and duration)
of plasticity is related to relevance of the
event to the animal and the intensity or
frequency of the events
Although most experiences must be repeated for us
to learn, some experiences need only be encountered
once and there is long-term change in behavior.
One example is food aversions that are related to a
single incidence of illness, a phenomenon referred
to as taste aversion conditioning. If animals are pre-
sented with a novel taste that is paired with illness,
there is an immediate and permanent aversion to
the taste. This learning requires only a single trial.
The key point is that food-related illness is highly
relevant to the animal and the brain is clearly pre-
pared to make certain associations (Yamamoto
et al., 1994). A parallel example can be seen in
imprinting in fowl (e.g., Lorenz, 1970), which is a
process where an organism learns, during a sensi-
tive period, to restrict its social preferences to a class
of objects. Horn and his colleagues have shown that
there are immediate changes in a part of the chick’s
hyperstriatum after visual imprinting. A variety of
rapidly occurring changes have been demonstrated
including an increase in dendritic length but a
decrease in spine density, increased glutamatergic
excitatory transmission, increased NMDA receptor
density, increased immediate early gene expression,
and other postsynaptic molecular changes (e.g.,
Horn 1998; Horn et al., 2001; Solomonia et al.,
2005). An important feature of the Horn experi-
ments is that although the most effective stimuli
for the changes are fowl, in the absence of fowl
there are still changes, thus suggesting flexibility in
the innate imprinting system.
The intensity of stimuli can be manipulated in
other models by varying drug doses, time in com-
plex housing, duration of electrical stimulation, etc.
For example, drug studies show that low doses of
psychomotor stimulants produce more restricted
changes in dendritic arborisation than higher
doses (e.g., Diaz-Heijtz et al., 2003) whereas addi-
tional doses of psychomotor stimulants produce
escalating increases in spine density (Kolb et al.,
2003b). Similarly, although animals may show
increased dendritic material in cortical pyramidal
cells after only a few days of complex housing, the
increases are much larger after longer durations
(e.g., Greenough & Chang, 1989).
One interesting aspect of electrical stimulation is
that whereas high frequency (25–200 Hz) stimulation
will produce enhanced postsynaptic potentiation
(i.e., long-term potentiation), low frequency stimula-
tion (3 Hz) will produce reduced potentiation (e.g.,
Cain, 2001; Teyler, 2001). The different forms of
stimulation lead to the activation of different post-
synaptic signaling pathways and a host of different
plastic changes (e.g., Teyler, 2001).
16 Bryan Kolb and Robbin Gibb
[6–21] 15.3.2008 1:02PM
Finally, a recent meta-analysis of physiotherapy
after stroke has concluded that the duration and
intensity of post-stroke therapy has a direct effect
on recovery on tests of daily living (Kwakkel et al.,
2004). These studies had no measure of brain
changes but the behavioral benefits of the therapy
provide a fairly strong suggestion that the treatment
did alter cerebral organisation.
Brain plasticity is not always a good thing
To this point we mostly have emphasised the plastic
changes in the brain that can support improved
motor and cognitive function. But plastic changes
can also interfere with behavior. For example, it is
reasonable to propose that some of the maladaptive
behavior of drug addicts could result from drug-
related changes in prefrontal neuronal morphology
(Robinson & Kolb, 2004). Another example can be
seen in schizophrenia.
Schizophrenia is a developmental disorder in
which the brain begins to show abnormalities in
morphology and behavior in late adolescence. The
abnormalities include reduced volumes of the fron-
tal and temporal lobes as well as increased ventric-
ular volume. Morphological analysis of neurons in
the prefrontal cortex of postmortem brains of schiz-
ophrenic patients shows a reduction in dendritic
arborization and spine density (Black et al., 2004).
The cause of these changes is poorly understood but
one hypothesis is that the changes are in response to
some developmental abnormality in the hippo-
campus (Lipska & Weinberger, 2002). Analysis of
hippocampal neurons in postmortem tissue from
schizophrenics shows disorganised organisation of
pyramidal cells that could result from some sort of
brain perturbation or genetic abnormality (Conrad
et al., 1991). The precise cause is difficult to study
in human postmortem tissue but it is possible to
manipulate the hippocampus in developing labora-
tory animals. Behavioral studies of laboratory ani-
mals with small ventral hippocampal lesions (or
hippocampal inactivation) in infancy show adult
functional disorders that are reminiscent of animals
with adult prefrontal injury (Lipska & Weinberger,
2002). Anatomical studies of similar animals show
reduced dendritic arborisation and spine density
similar to what has been seen in human schizo-
phrenic patients (Flores et al., 2005). Such changes
are not seen in rats with similar injuries in adult-
hood. It thus appears that both the behavioral and
morphological effects of the small ventral hippo-
campal injury only occur after a perturbation in
infancy. This perturbation is proposed to lead to
plastic changes in the developing prefrontal cortex
that lead to behavioral abnormalities in adulthood.
One prediction of this model is that the structural
abnormalities in the frontal lobe should not pro-
gress in adulthood but likely would remain static.
This appears to be the case (Pantelis et al., 2005).
There are many other examples of pathological
plasticity including pathological pain (Baranauskas,
2001), pathological response to sickness (Raison
et al., 2006), epilepsy (Teskey, 2001), and dementia
(Mattson et al., 2001). One goal is to find ways to
block or reverse pathological plasticity, although
this is likely to prove difficult.
We have tried to identify a set of principles that
describe the “rules” that define experience-dependent
changes in brain and behavior. Our choice of liter-
ature used to define the principles is obviously
biased and somewhat arbitrary but we believe that
we have provided a framework that others may find
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