Explain how the brain changes its structure and function through experience, describe the mechanisms and the environmental factors that drive it, and evaluate the evidence, including the London taxi driver studies.
Each is in the Psychology glossary, with every other term in the subject.
A rehabilitation treatment after stroke in which the unaffected arm is restrained so that the patient must practise intensively with the weakened arm, encouraging functional reorganisation.
The growth of new branches on a neuron’s dendrites in response to experience, which allows the neuron to form more synapses with other neurons.
An environment that offers more sensory, physical, social and cognitive stimulation than a standard one; in animal research it is compared with an impoverished environment to study plasticity.
Brain change that depends on experiences specific to an individual, such as learning a language, a skill or a route, and that can happen at any age.
Brain change that depends on experiences almost every member of a species meets at a predictable age, such as patterned light or speech, which the brain needs to wire its basic systems.
A form of neuroplasticity in which undamaged brain areas take over functions that were carried out by a damaged area, as in recovery after a stroke.
A long-lasting strengthening of a synapse that follows repeated stimulation, so that the receiving neuron responds more strongly; it is a leading cellular explanation of learning and memory.
Describe neuroplasticity and explain how it differs from the older view of a fixed adult brain.
Explain the main mechanisms of neuroplasticity: long-term potentiation, dendritic branching, synapse formation and pruning, and functional reorganisation.
Explain the difference between experience-expectant and experience-dependent plasticity.
Explain how environmental factors such as enrichment, practice, language learning and sensory loss shape the brain.
Describe the research by Maguire et al. (2000) and Woollett and Maguire (2011) on London taxi drivers and explain why the second study was needed.
Apply neuroplasticity to behaviour in health, development, relationships and learning.
Evaluate research on neuroplasticity with reference to measurement, causality, change and bias.
Neuroplasticity is the brain’s ability to change its structure and function as a result of experience, learning and injury. It explains why practising a skill changes the brain areas that control it, why children who grow up in very different environments develop different brains, and why many people recover lost abilities after a stroke.
Neuroplasticity is a term of the biological approach, but it shows the biological and the environmental working together: experience changes biology, and the changed biology shapes later behaviour. It is central to the concept of change, and studying it raises problems of measurement (brain scans measure volume, not learning itself) and of causality (a bigger brain area might be the cause of a skill rather than its result).
With a free account, Augment remembers where you stopped and what you have practiced.
The formation of new neurons; in adult mammals it occurs in only a few regions, such as part of the hippocampus, and how much it happens in adult humans is debated.
The ability of the brain to change its structure and function in response to experience, learning or injury, throughout life.
Scope: An approach term in the biological approach. Questions can ask about the process of neuroplasticity and the role of environmental factors in brain development, with any example; it is applied in all four contexts, especially human development and learning and cognition.
For much of the 20th century, many scientists believed that the adult brain was largely fixed. On this view the brain grew and organised itself in childhood, and after that it could only lose cells and connections, not gain them. Research since the 1960s, first in animals and then with human brain imaging, has shown that the brain keeps changing throughout life, although the amount and speed of change decline with age.
Plasticity happens at several levels. At the smallest scale, individual synapses become stronger or weaker. At a larger scale, neurons grow new branches and form new connections, and some unused connections are removed. At the largest scale, whole areas of the cerebral cortex change in size or take on new functions. Brain scans in humans usually detect only the largest changes, while the smaller ones are studied mainly in animals.
Type | What changes | Example |
|---|---|---|
Structural plasticity | The physical structure: synapses, dendrites, grey matter volume, white matter | Grey matter in the hippocampus grows as trainee taxi drivers learn London’s streets |
Functional plasticity | Which areas carry out a function, or how strongly they respond | The visual cortex of people blind from early life responds to touch when they read Braille |
Functional reorganisation | Undamaged areas take over the work of damaged ones | Arm movement recovers after a stroke through intensive therapy |
Plasticity is not a single process. Several mechanisms work together, each at a different scale and speed. The diagram shows how repeated experience leads from changes at single synapses to changes in whole brain areas, and how circuits that are rarely used lose connections.
In 1949 the psychologist Donald Hebb proposed that when one neuron repeatedly helps to make another fire, the connection between them grows stronger. This principle is often summed up as “neurons that fire together wire together”. It suggested a physical basis for learning: experience would change the strength of particular connections, and the pattern of strong connections would store what had been learned.
Bliss and Lømo (1973) found the effect Hebb had predicted. They stimulated a pathway into the hippocampus of anaesthetised rabbits with short bursts of high-frequency electrical pulses. Afterwards, a single pulse produced a larger response in the receiving neurons than before, and in 15 of the 18 rabbits this strengthening lasted from 30 minutes to 10 hours. The effect became known as long-term potentiation (LTP).
LTP involves changes on both sides of the synapse: the sending neuron may release more neurotransmitter, and the receiving neuron adds more receptors to its membrane, so the same signal has a bigger effect. Because LTP is strongest in the hippocampus, an area essential for forming new memories, it is widely accepted as one of the mechanisms of learning, although showing that a particular memory depends on particular strengthened synapses remains difficult.
Neurons receive signals through their dendrites, the branching extensions of the cell body. With repeated stimulation, dendrites grow new branches and small spines, which create space for new synapses. This dendritic branching increases the number of connections a neuron can make. New synapses can also form where none existed, a process called synaptogenesis, which is fastest in infancy but continues throughout life.
Much of the evidence for these structural changes comes from animal research, because counting dendrites and synapses requires examining brain tissue under a microscope. In humans, structural MRI can detect only the combined effect of many such changes, which appears as a change in the volume or density of grey matter.
Plasticity also works by subtraction. Connections that are rarely used tend to weaken and may be removed, while those that are used often are kept and strengthened. This synaptic pruning is most intense in childhood and adolescence, when it shapes the developing brain, but weakening of unused connections continues in adults. It is one reason why skills that are not practised fade.
Two further mechanisms are debated or less well understood. Neurogenesis, the birth of new neurons, continues in adult rodents in part of the hippocampus, but researchers disagree about how much it happens in the adult human brain. Changes in white matter are better established: the fatty myelin that insulates nerve fibres can increase with practice, which makes signals between regions faster and better coordinated.
A study by Tang et al. (2010) at Dalian University of Technology in China found that 11 hours of integrative body–mind training, a meditation method based on traditional Chinese medicine, increased a scan measure of white matter integrity in a pathway connecting the anterior cingulate cortex, an area involved in self-regulation, to other brain structures. The study suggests that even a short programme of mental training can change the brain’s connections, although the scan measure is indirect and the long-term effect was not tested.
YouTubePlastic changes differ in what kind of experience triggers them. Some experiences are met by almost every member of a species at a predictable point in development: light and patterned images reaching the eyes, the sounds of speech, a caregiver who responds. The brain has evolved to “expect” these experiences and uses them to finish wiring its basic systems. Other experiences are specific to one person, such as learning Mandarin, the violin or the streets of a city, and they shape the brain in ways that differ from person to person. The first kind of change is called experience-expectant plasticity and the second experience-dependent plasticity.
Experience-expectant plasticity is tied to development. The brain overproduces connections in anticipation of the expected input, and the input then decides which connections survive. If the expected experience is missing at the right time, the system may never develop normally. This is the basis of sensitive periods in development, such as the period in early childhood when the visual system needs clear input from both eyes.
Experience-expectant | Experience-dependent | |
|---|---|---|
Kind of experience | Common to almost all members of the species | Specific to the individual |
Timing | A limited window in development | Throughout life |
What happens if it is missing | Lasting deficits are likely | The person simply does not gain that skill |
Examples | Patterned vision; hearing speech sounds; responsive care in infancy | Juggling, a second language, taxi drivers’ knowledge of London |
Evidence | Early deprivation in Romanian institutions; visual deprivation in kittens | Maguire et al. (2000); Draganski et al. (2004) |
Research on children raised in severely deprived institutions in Romania shows experience-expectant plasticity at work in humans. In the Bucharest Early Intervention Project, young children who were moved from institutions to foster families gained more in cognitive development than those who stayed, and the gains were greatest for those placed youngest. The brain appears to expect the stimulation of family care in the first years of life, and its absence has effects that are hard to reverse later. The timing of these windows, and how far they are critical or only sensitive, is a central question in brain maturation.
The environment influences the brain through the experiences it provides. Research has identified several environmental factors that produce measurable plastic change, from the richness of an animal’s cage to years of practice, a second language and the loss of a sense.
The first strong evidence that experience changes brain structure came from animal studies of enriched environments. Rosenzweig, Bennett and Diamond (1972) reported that rats raised in large cages with other rats and changing toys developed a heavier, thicker cortex than rats kept alone in small, bare cages. Later studies found more dendritic branching and more synapses per neuron in enriched animals.
These findings are strong in rats, but extrapolation to humans needs care. A laboratory cage is far more impoverished than any normal human home, so the “enriched” condition may simply restore what a normal environment provides. The findings support the idea that severe deprivation harms brain development more than they support claims that extra stimulation produces “super-brains” in children.
Learning a new skill changes the brain areas that support it. Draganski et al. (2004) scanned young adults in Germany before and after half of them learned to juggle with three balls over three months. The jugglers showed a temporary increase in grey matter in an area of the temporal lobe that processes visual motion, and the increase partly disappeared after three months without practice. The change appeared with practice and faded with disuse, which is stronger evidence than a one-off comparison of experts and non-experts.
Skilled performance also changes how the cortex is organised. Elbert et al. (1995) used magnetoencephalography to map the somatosensory cortex of violin, cello and guitar players. The cortical area representing the fingers of the left hand, which press the strings, was larger than in non-musicians, and the difference was greatest in players who had started young. No such difference was found for the right hand, which holds the bow. The specific demands of a skill therefore change the specific part of the cortex that serves it.
Changes can also be fast. Pascual-Leone et al. (1995) taught adults a five-finger piano exercise with two hours of practice a day. Within five days, the area of motor cortex controlling the finger muscles of the practising hand had enlarged, as shown by transcranial magnetic stimulation mapping, while control participants who did not practise showed no change.
A second language changes the brain too. Mechelli et al. (2004) used voxel-based morphometry, a method that compares the density of grey matter across the whole brain, with bilingual and monolingual adults. Learning a second language was linked to greater grey matter density in the left inferior parietal cortex, and the density was greater in those who had learned the language earlier and in those who were more proficient. The results show both experience-dependent plasticity and the importance of timing.
Everyday activities can produce measurable change. Kühn et al. (2014) randomly allocated adults in Berlin to play the platform game Super Mario 64 for at least 30 minutes a day for two months or to a control group that did not play. The training group showed grey matter increases in the right hippocampus, the right dorsolateral prefrontal cortex and the cerebellum, areas involved in spatial memory, planning and fine motor control. Hölzel et al. (2011) found that 16 adults who completed an eight-week mindfulness-based stress reduction course showed increased grey matter concentration in the left hippocampus and other areas, compared with 17 people on a waiting list.
When one source of input disappears, the brain areas that processed it can be put to new use. Sadato et al. (1996) used PET to show that the visual cortex of people blinded early in life became active when they read Braille by touch, whereas in sighted people it was not. Merabet et al. (2008) blindfolded sighted adults for five days while they learned Braille: their visual cortex began to respond to touch, but this response disappeared within a day of removing the blindfold. Fast, reversible change of this kind suggests that existing hidden connections are “unmasked” first, and that lasting structural change follows only if the new demand continues.
Environmental factor | Study | Change found | What it shows |
|---|---|---|---|
Enrichment (animals) | Rosenzweig et al. (1972) | Thicker, heavier cortex in rats | Stimulation shapes brain structure |
Motor practice | Draganski et al. (2004) | Grey matter in a motion area rose, then partly fell | Change follows use and fades with disuse |
Musical training | Elbert et al. (1995) | Larger left-hand finger map in string players | Specific demands change specific areas |
Second language | Mechelli et al. (2004) | More grey matter in left inferior parietal cortex | Earlier learning gives larger change |
Video game training | Kühn et al. (2014) | Grey matter rose in hippocampus, prefrontal cortex, cerebellum | Randomised design supports causation |
Meditation | Hölzel et al. (2011); Tang et al. (2010) | Grey matter in hippocampus; white matter integrity | Mental training changes structure |
Sensory loss | Sadato et al. (1996); Merabet et al. (2008) | Visual cortex used for touch | Areas can take on new functions |
When part of the brain is damaged, by a stroke or an injury, the functions it supported are often lost at first. Over the following weeks and months many patients recover some of them. Part of this early recovery happens because swelling goes down and surviving cells start working again. The longer-term recovery depends on functional reorganisation: undamaged areas near the lesion, or in the opposite hemisphere, gradually take over some of the lost functions.
Reorganisation depends on use. After a stroke that weakens one arm, patients naturally rely on the other arm, and the weakened arm is used less and less. The psychologist Edward Taub called this “learned non-use”. If the weak arm is rarely used, the brain areas that could take over its control receive little stimulation, and recovery stalls. This idea led to a therapy built directly on the principles of plasticity.
In constraint-induced movement therapy (CIMT), the patient’s stronger arm is restrained in a mitt for most of the day, usually over two weeks, while they practise everyday tasks for several hours a day with the weaker arm. The forced, repeated use is intended to drive reorganisation in the motor areas around the damage. The EXCITE trial, reported by Wolf et al. (2006), randomly allocated 222 patients who had had a stroke three to nine months earlier to two weeks of CIMT or to usual care.
After 12 months, the CIMT group had improved more on laboratory tests of arm function and in how much and how well they used the arm in daily life. Because patients were randomly allocated, the difference can be attributed to the therapy rather than to differences between the patients. The trial shows that plasticity can be deliberately encouraged by therapy to bring about recovery.
Recovery is usually more complete when damage happens early in life, when the brain is more plastic. A child whose entire left hemisphere is removed before the age of three can develop near-normal language in the right hemisphere, which is rarely possible in adults. Even in children, though, recovery is often incomplete, and some functions are reorganised at the cost of others, an effect sometimes called crowding. Plasticity can also be maladaptive: after the loss of a limb, the cortex that represented it can be taken over by neighbouring areas, which is one explanation of the pain or sensations some amputees feel in a limb that is no longer there.
Because plasticity links experience to the brain, it appears in every context of the course, usually together with cognitive and sociocultural factors.
Context | Example | How neuroplasticity is involved |
|---|---|---|
Health and well-being | Rehabilitation after stroke; mindfulness courses | Therapy drives functional reorganisation; mental training is linked to grey matter change in the hippocampus. |
Human development | Children moved from institutions to foster families | Experience-expectant plasticity: the developing brain needs responsive care, and the timing of placement matters. |
Human relationships | Children growing up with two languages at home | The language environment of the family shapes grey matter in language-related areas. |
Learning and cognition | Trainee taxi drivers learning London’s streets | Experience-dependent plasticity: years of spatial learning increase posterior hippocampal grey matter. |
In each example the brain change is part of a longer chain. A foster family provides care because of social and economic arrangements; bilingual children hear two languages because of migration and culture; taxi drivers learn London because of a job and a qualification system. Neuroplasticity explains how these social and cognitive experiences become part of biology, which is why it is often used to argue against strictly biological determinism.
YouTubeMost human studies measure plasticity with structural MRI, using methods such as voxel-based morphometry to compare the volume or density of grey matter. A larger volume could reflect more synapses, more dendritic branches, more blood vessels, more support cells or, possibly, new neurons. The scans cannot tell these apart, so “grey matter increase” is an indirect measure of an unknown mix of changes. Animal studies, which can count synapses directly, help to interpret human findings but raise problems of extrapolation.
A cross-sectional study that finds a difference between experts and non-experts cannot show which came first. People with larger hippocampi might be drawn to jobs that need spatial memory, just as people with certain brains might be drawn to music. Stronger evidence comes from longitudinal designs, which scan the same people before and after training, and from randomised experiments such as Kühn et al. (2014). Even in that experiment, grey matter growth was linked to participants’ desire to play, so motivation may affect how much the brain changes.
Plasticity research shows that change can be reversed. Draganski’s jugglers lost part of their grey matter gain after they stopped practising, and the blindfolded participants in Merabet et al. (2008) lost their visual-cortex response to touch within a day. This fits the “use it or lose it” principle, and it means that a single scan after training says little about lasting change. Long follow-up periods are needed to show that an intervention has a durable effect.
Many imaging studies of plasticity have small samples, often 12 to 20 participants per group. Small studies are more likely to produce false positive results and to overestimate the size of real effects, and striking results are more likely to be published than null ones, which is publication bias. Most samples are also from Europe and North America, although research such as Tang et al. (2010) in China suggests that similar processes operate elsewhere.
Plasticity research is easily overstated in public. Commercial “brain-training” programmes and some educational products claim that their exercises will rewire the brain and raise intelligence. Evidence that training on such games improves anything beyond the trained task is weak. Researchers have a responsibility to communicate what plasticity studies do and do not show, so that families, schools and older adults do not spend money or hopes on claims that research does not support.
Two studies by Eleanor Maguire’s team at University College London belong together. The first found a brain difference in experienced taxi drivers; the second followed trainees over several years to test whether learning caused it.
Maguire et al. (2000) aimed to find out whether people with extensive experience of spatial memory, licensed London taxi drivers, differ in hippocampal structure from people without such experience. Woollett and Maguire (2011) aimed to test whether learning the layout of London causes structural change in the hippocampus, by scanning trainees before and after their training.
To be licensed, a London taxi driver must pass “the Knowledge”: memorising about 25,000 streets within six miles of Charing Cross station and thousands of landmarks, which takes three to four years. Maguire et al. (2000) used structural MRI with 16 right-handed male licensed drivers, mean age 44, who had driven for 1.5 to 42 years (mean 14.3). Their scans were compared with those of 50 right-handed men of similar age who did not drive taxis, taken from a database of scans. Hippocampal grey matter was measured with voxel-based morphometry and by measuring the area of the hippocampus on each slice of the scan.
Woollett and Maguire (2011) used a longitudinal design. They scanned and tested 79 male trainees at the start of their training and 31 male controls of similar age, education and IQ. Three to four years later, 39 trainees had qualified, 20 had failed or given up but agreed to be tested again, and all 31 controls returned. Memory was tested with tasks on London landmarks and with general tests such as recalling a complex figure after 30 minutes.
Maguire et al. (2000) found that the posterior (back) part of the hippocampus was larger in taxi drivers than in controls, while the anterior (front) part was larger in controls. Total hippocampal volume did not differ. In the drivers, the volume of the right posterior hippocampus correlated positively with years spent driving a taxi (r = 0.6), and the volume of the anterior hippocampus correlated negatively with it.
Woollett and Maguire (2011) found no differences between the groups at the start: those who would later qualify, those who would not, and the controls had similar hippocampal grey matter and memory scores. After training, grey matter in the posterior hippocampus had increased in the trainees who qualified, but not in those who failed or in the controls. The qualified trainees were better at judging the positions of London landmarks than controls, but worse at recalling a complex figure after a delay, the same pattern seen in experienced drivers.
Both groups of trainees spent about three years in training, so time alone did not explain who changed. The trainees who qualified trained for about 35 hours a week, compared with about 17 hours for those who did not. Intensity of practice, and success in learning the map, rather than simply being a trainee, went with the brain change.
Maguire et al. (2000) concluded that the posterior hippocampus stores a spatial representation of the environment and can expand to hold a more detailed one in people who depend heavily on spatial memory. Because the 2000 study was cross-sectional, it could not rule out that people with larger posterior hippocampi become taxi drivers. Woollett and Maguire (2011) concluded that acquiring the Knowledge causes a selective increase in posterior hippocampal grey matter in adults, which is strong evidence of experience-dependent plasticity in the adult human brain.
The 2011 study answers the main weakness of the 2000 study. Because the groups did not differ before training, the later difference is unlikely to reflect a pre-existing brain advantage. Participants were not randomly allocated, though: trainees chose how hard to study, and those who qualified may have differed in motivation or in a predisposition to plasticity, which the authors themselves acknowledged. A later study by Maguire, Woollett and Spiers (2006) compared taxi drivers with London bus drivers, who drive and experience stress as much but follow fixed routes; only the taxi drivers showed the hippocampal pattern, which suggests spatial learning, not driving or stress, is the key factor.
Grey matter volume is an indirect measure: it shows that something in the posterior hippocampus increased, but not whether this was new synapses, dendrites, support cells or new neurons. The memory measures add strength by showing a matching change in behaviour. The trade-off between posterior growth and poorer recall of new visual information suggests that the brain reorganises to suit the demands placed on it, with costs as well as gains.
All participants were men, because very few London taxi drivers are women, and all were learning one unusual skill in one city. The findings may not generalise to women, to other kinds of learning or to people in other cultures. The sample in 2000 was small (16 drivers), and the controls came from a scan database rather than being recruited to match each driver, which is a weakness that the 2011 design corrected.
Sources: Maguire, E. A., Gadian, D. G., Johnsrude, I. S., Good, C. D., Ashburner, J., Frackowiak, R. S. J. and Frith, C. D. (2000). Navigation-related structural change in the hippocampi of taxi drivers. _PNAS, 97(8), 4398–4403; Woollett, K. and Maguire, E. A. (2011). Acquiring “the Knowledge” of London’s layout drives structural brain changes. Current Biology, 21(24), 2109–2114._
Neuroplasticity appears mainly in Paper 1. Section A can ask you to explain neuroplasticity, or how one environmental factor influences it, with an example. Section B can give a scenario from any context, such as rehabilitation, education or child development, and ask you to apply neuroplasticity to it. Plasticity studies are also good evidence in Section C essays on brain development, biological factors in cognitive processes or treatment.
The same answer structure works for “Explain neuroplasticity with reference to one example of human behaviour”: define the term with a mechanism, describe the behaviour, and explain how the behaviour reflects a change in the brain.
Neuroplasticity is the brain’s ability to change its structure and function in response to experience, learning and injury, throughout life.
Mechanisms include long-term potentiation, dendritic branching, new synapses, pruning of unused connections, changes in myelin and functional reorganisation.
Experience-expectant plasticity depends on experiences almost everyone meets at a predictable age; experience-dependent plasticity depends on individual experiences and happens at any age.
Environmental factors that change the brain include enrichment, practice (juggling, music), language learning, video games, meditation and sensory loss.
After brain damage, functional reorganisation can restore lost functions, especially with intensive practice such as constraint-induced movement therapy, but recovery is often incomplete and declines with age.
Maguire et al. (2000) found larger posterior hippocampi in London taxi drivers; Woollett and Maguire (2011) showed with a longitudinal design that learning the Knowledge caused the increase.
Evaluation issues: grey matter is an indirect measure; cross-sectional studies cannot show direction; changes can reverse; samples are small and mostly Western; findings are easily overstated in public.
I can describe neuroplasticity and explain how it differs from the older view of a fixed adult brain.
I can explain long-term potentiation, dendritic branching, pruning and functional reorganisation.
I can explain the difference between experience-expectant and experience-dependent plasticity with an example of each.
I can explain how at least three environmental factors shape the brain, with a study for each.
I can describe the taxi driver studies and explain why the longitudinal study was needed.
I can apply neuroplasticity to a scenario in each of the four contexts.
I can evaluate plasticity research with reference to measurement, causality, change and bias.