MIND, BRAIN, AND EDUCATION

The Learning Hippocampus:

Education and
Experience-Dependent
Plasticity
Elisabeth Wenger1 and Martin Lövdén2

ABSTRACT— The hippocampal formation of the brain education, review evidence on how experience may shape
plays a crucial role in declarative learning and memory while this brain region and its functions, discuss age differences
at the same time being particularly susceptible to environ- in such experience-dependent plasticity, and consider the
mental influences. Education requires a well-functioning implications of our current understanding of brain plasticity
hippocampus, but may also influence the development of for the educational setting.
this brain structure. Understanding these bidirectional influ-
ences may have important implications for the educational
setting. Here, we provide an overview of the functions of THE HIPPOCAMPUS AND ITS FUNCTIONAL
the hippocampus, review evidence on how experience may RELEVANCE FOR EDUCATION
shape this brain region and its functions, discuss age differ-
ences in such experience-dependent plasticity, and outline The hippocampal formation is a compound structure in the
the implications of our current theoretical understanding of medial temporal lobe. Opinions differ about which brain
plasticity for the educational setting. regions are encompassed by the term, but most agree on
defining it as the dentate gyrus, the hippocampus proper
with its Cornu Ammonis (CA) fields, and the subiculum
The brain has evolved to educate and be educated, often (Birbaumer & Schmidt, 2010). Together with perirhinal,
instinctively and effortlessly, and is therefore at the core of entorhinal, and parahippocampal cortices, the hippocampal
educational interest (Blakemore & Frith, 2005). The hip- formation forms the medial temporal lobe—a system already
long assumed to be involved in memory processes (Squire,
pocampus is a structure of the brain playing a crucial role in
Stark, & Clark, 2004; see Figure 1). The hippocampus is
learning and memory while also being particularly suscepti-
involved in information processing fundamental to memory
ble to environmental influences. This region is thus impor-
formation and retrieval, such as the ability to discriminate
tant for the understanding of bidirectional influences and
similar stimuli from one another (pattern separation) (J. K.
interactions between ability (e.g., memory) and environment
Leutgeb, Leutgeb, Moser, & Moser, 2007), complete stim-
(e.g., education) that form the development of cognitive abil-
uli that are incomplete (pattern completion) (S. Leutgeb &
ities and skills. In this review, we provide an overview of the
Leutgeb, 2007; Yassa & Stark, 2011), and associate informa-
functional relevance of the hippocampus in the context of
tion (Henke, Weber, Kneifel, Wieser, & Buck, 1999) in time
and space (Moscovitch, Nadel, Winocur, Gilboa, & Rosen-
baum, 2006; Staresina & Davachi, 2009). It is thought to
1 Center for Lifespan Psychology, Max Planck Institute for Human act as a linking node that processes new memories, stores
Development
2 Aging Research Center, Karolinska Institutet and Stockholm associations to its representations, and retrieves old mem-
University ories from a network of different associative areas in the
neocortex (Willshaw, Dayan, & Morris, 2015). There is evi-
Address correspondence to Elisabeth Wenger, Center for Lifespan Psy-
chology, Max Planck Institute for Human Development, Lentzeallee 94, dence for a dissociation of dorsal and ventral regions of the
14195 Berlin, Germany; e-mail: wenger@mpib-berlin.mpg.de hippocampus: while the dorsal pole (which corresponds to

© 2016 International Mind, Brain, and Education Society and Wiley Periodicals, Inc. 1
 The Learning Hippocampus

Fig. 1. The hippocampus within the medial temporal lobe and its associated functions. Adapted from Kahana (2012).

the posterior hippocampus in humans) appears to regulate become knowledge, while episodic memories remain hip-
cognitive-related behaviors, the ventral (anterior) pole may pocampally dependent during their entire lifespan and will
be involved in mood-related responses (Fanselow & Dong, never be fully consolidated into the neocortex (Moscovitch
2010; Moser & Moser, 1998; Wu & Hen, 2014). The hip- et al., 2006; Winocur, Moscovitch, & Bontempi, 2010). The
pocampus thus seems to operate as an integrated unit, con- finding that H.M. was still able to learn motor skills led to
sisting of isolated parts responsible for succinct functions. the hypothesis that only conscious memories, that is, declar-
Not least since the famous case of H.M.—probably ative, explicit memories, are dependent on the hippocampus
the best known single patient in the history of (Squire & Alvarez, 1995) and that procedural memory (i.e.,
neuroscience—the role of the hippocampus in memory has memory for skills) must rely on different brain systems. It
been corroborated and elaborated (Squire, 2009). H.M. had has also been proposed that the hippocampus and neocor-
undergone an experimental neurosurgery lesion including tex could be considered complementary memory systems,
the hippocampus, amygdala, and the adjacent parahip- therefore giving rise to complementary learning theory, with
pocampal gyrus to control seizures and, consequently, the hippocampus being used for fast, unstructured storage
suffered from severe impairments in forming new memories of information arriving from many areas of the neocortex,
and recalling recently encoded memories (Scoville & Milner, while the neocortex would gradually build and adjust its
1957). The investigation of H.M. and his memory impair- semantic representation on the basis of accumulating infor-
ments gave rise to the systems consolidation theory, accord- mation (Kesner & Rolls, 2015; McClelland, McNaughton,
ing to which connections between associative areas in the & O’Reilly, 1995; O’Reilly, Bhattacharyya, Howard, &
neocortex that represent different parts of a memory trace Ketz, 2014).
are strengthened over time, while hippocampal connections The hippocampus or, more generally, the medial temporal
are weakened. This would ultimately lead to hippocampally lobe (MTL) is thus believed to be crucially involved in mem-
independent memory traces that can be retrieved without ory encoding, memory consolidation, and memory retrieval.
relying on the hippocampus (Frankland & Bontempi, 2005; When new declarative information enters the brain, it is pre-
Squire & Bayley, 2007). The multiple trace theory of memory sumed to be encoded by processes in MTL and then pre-
argues that only retention and retrieval of detailed, vivid served in different associative parts in the brain (Paller &
autobiographical memories (episodic memories) depend on Wagner, 2002). MTL is seen as a novelty detector, predict-
the hippocampal system, while knowledge (i.e., semantic ing and identifying interesting novel information that should
memory)—to the extent that it does not incorporate be stored (Kumaran & Maguire, 2009; Nyberg, 2005; Tulv-
episodic details (e.g., information on time and space)—can ing & Kroll, 1995). Already familiar information is thought
be retrieved independently of the hippocampus, at least to be less well encoded as there seems to be no need to
after some time (Moscovitch et al., 2005). Consequently, store information again that is already available (Tulving
this theory states that memories become hippocampally & Kroll, 1995). It is hypothesized that the brain constantly
independent through consolidation and, in this process, predicts future input. The amount of deviation from the

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 Elisabeth Wenger and Martin Lövdén

prediction (prediction error) is thought to be the driving PLASTICITY OF THE HIPPOCAMPUS

factor for encoding of novel information (Henson & Gag-
nepain, 2010; Lisman, Grace, & Düzel, 2011). The consoli- In our view, plasticity denotes the capacity for change in
dation of memory traces is a process typically taking place brain structure induced by a mismatch between the demands
after learning periods when the brain is not consciously of the environment and the current capacity of the brain
encoding or retrieving a certain memory. This process acts (Lövdén, Bäckman, Lindenberger, Schaefer, & Schmiedek,
as a slow integrative that fixates memory traces (Dudai, 2010). This capacity for change can lead to the acquisition
2004; McGaugh, 2000). Memory retrieval is assumed to of new knowledge or the improvement of processing effi-
ciency. Learning is the process of acquiring knowledge, and
be equivalent and complementary to encoding processes
the capacity for learning is one primary function served
in terms of activated brain regions (Nyberg, Habib, McIn-
by the hippocampus. Clearly, there is no doubt that the
tosh, & Tulving, 2000; Wheeler, Petersen, & Buckner, 2004).
demands of education can induce plastic changes, in the
Except for those memories that have become hippocam-
sense that knowledge is acquired. There is also no doubt
pally independent during consolidation, memory retrieval
that more knowledge may expand an individual’s flexibility
is generally found to be dependent on the MTL (Buckner
and improve learning of information that maps onto previ-
& Wheeler, 2001). Retrieval can differ quite substantially in ous knowledge. The crucial question is whether education,
nature, from a vague familiarity with a cued stimulus to full including learning activities, can also enhance processing
recollection of an entire episode—processes that are dis- efficiency, such as the capacity for learning itself.
cussed to be functionally distinct and possibly rely on dif- There is ample evidence indicating that the hippocam-
ferent regions within the MTL (Eichenbaum, Yonelinas, & pus is a plastic brain region. Walhovd and colleagues (2016)
Ranganath, 2007). Retrieval processes are not simply an end argued that the MTL, including the hippocampus, is perhaps
station of a memory trace but are additionally thought to the most plastic brain region as it stands out from others with
involve re-encoding and reconsolidation processes, allowing low evolutionary expansion, low heritability, greater vari-
the memory trace to become labile for a certain period of ability of change through the lifespan, and greater interindi-
time so that it can be modified according to novel informa- vidual differences in intracortical myelin content. Alongside
tion (Dudai, 2004; Takashima et al., 2009; Wiltgen, Brown, other common microstructural mechanisms of plastic brain
Talton, & Silva, 2004). changes, such as changes in synapses, glia cells, or vascula-
Notably, much attention in the literature on cognitive pro- ture (Zatorre, Fields, & Johansen-Berg, 2012), the hippocam-
cessing requirements of education has focused on aspects of pus is considered to be one of the very few brain regions that
cognition, such as reasoning, problem solving, abstraction, preserve their potential for neurogenesis into adulthood and
flexible thinking, and creativity (Baker et al., 2015; Ceci, aging (Altman, 1962; Christie & Cameron, 2006).
1991). These are all cognitive executive functions that have In 1962, Altman was the first to report new neurons and
been most strongly linked with the neocortical frontopari- neuroblasts in adult rats (Altman, 1962). Fifteen years later,
etal brain network (Basten, Hilger, & Fiebach, 2015; Duncan, Kaplan corroborated these results and also found evidence
2013). Importantly, frontal-mediated executive control pro- that complex environments could stimulate neurogenesis
cesses are also known to modulate hippocampal-dependent in the adult visual cortex (Kaplan & Hinds, 1977). The
vast majority of the neuroscience community, however,
learning, and a collaboration between the MTL and pre-
needed another decade to overcome the long-standing
frontal cortex is needed for successful memory formation
paradigm of neurogenesis being restricted to prenatal and
(Simons & Spiers, 2003). It is clear that education requires
early postnatal development. Finally, with the important
acquisition of vast amounts of declarative knowledge,
work by Gould and colleagues, who demonstrated adult
which—as described above—critically involves the hip-
hippocampal neurogenesis also in mammals more related
pocampus. This ability is also one that educational policy to humans (Gould, Reeves, et al., 1999), adult mammalian
makers hope to improve with education. For example, the neurogenesis is now firmly established and has been shown
U.S. Department of Education hopes to foster “lifelong to be involved in learning (Gould, Beylin, Tanapat, Reeves,
learners who can adapt to the constant changes in the & Shors, 1999).
diverse and technology-driven workplaces of the global In rodents, environmental enrichment and voluntary
economy” (U.S. Department of Education, 2013). In other exercise have been shown to enhance neurogenesis (Kem-
words, individuals with better functioning and integrity of permann, Kuhn, & Gage, 1997; van Praag, Kempermann,
the hippocampus are likely to achieve better in school, but & Gage, 1999). Learning may mainly affect cell survival
education also aims to improve this very same functioning. and not cell proliferation, while running may increase cell
Below, we review the evidence on whether the hippocampus division and net neuronal survival (van Praag et al., 1999).
and its functions display such plastic changes. Physical activity has been shown to be a very powerful tool

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 The Learning Hippocampus

Percent signal change

(a) and 90% confidence (b) Hippocampi
interval averaged in
2.0 cluster 120
Interpreters
Controls
1.5

percent signal change

0.00001 75

 volume (mm3)
1.0

p-value
coronal
0.0001 30
0.5
0.001 -15
0.0

-0.5 -60
L axial R 1 2 3 Right HC Left HC
Scan

Fig. 2. Examples of hippocampal plasticity. Longitudinal studies of structural change in hippocampal volume with learning. Figures
adapted from cited publications. (a) Three months of intense studying for a medical exam resulted in volume increases in the left and
right hippocampus, which even continued to increase towards a third measurement 3 months after the exam and termination of studying
(Draganski et al., 2006). (b) Three months of intense language studies were accompanied by changes in left and right hippocampal volume
(Mårtensson et al., 2012).

to affect neurogenesis and therefore learning (Kempermann could be an important part of what makes individuals tal-
et al., 2010) (see also Hassevoort, Khan, Hillman, & Cohen, ented for acquiring a foreign language, perhaps particu-
this issue, for more details on the effects of physical activity larly for the acquisition of foreign vocabulary, which was a
on brain structure and function in children). major part of this particular studying regime. Notably, in a
Plasticity within the hippocampal formation has also been follow-up study of younger adults learning Italian vocabulary
shown in humans, not only in childhood but also in younger at a more normal pace, Bellander and colleagues reported
adulthood (see Lövdén, Wenger, Mårtensson, Lindenberger, that memory performance was associated with the growth
& Bäckman, 2013; May, 2011 for reviews). In their semi- of hippocampal volume during vocabulary acquisition, inde-
nal studies, Maguire and colleagues showed that London pendent of time devoted to the studies and amount of
taxi drivers have a larger posterior hippocampus region acquired vocabulary (Bellander et al., 2016). Hippocampal
compared to controls and that successful spatial knowl- volume has also been shown to be predictive of arithmetic
edge acquisition is related to hippocampal growth (Maguire, skill acquisition in 8–9-year-old children (Supekar et al.,
Woollett, & Spiers, 2006; Maguire et al., 2000; Woollett & 2013). In this study, children with larger right hippocam-
Maguire, 2011). Other types of learning can trigger changes
pus volumes showed greater improvement in arithmetic
in hippocampal volume as well, for example, learning how
problem-solving skills after an 8-week one-to-one math
to juggle over a period of 3 months (Boyke, Driemeyer,
tutoring program. These results suggest that hippocampal
Gaser, Büchel, & May, 2008), spatial navigation training
volume per se may be predictive of learning success. Individ-
(Lövdén et al., 2012), studying for a final medical exam (Dra-
ual differences in hippocampal-volume responses to learn-
ganski et al., 2006), or intense studying of a foreign lan-
ing may index the ability to acquire declarative knowledge
guage (Mårtensson et al., 2012). The two last examples are
particularly interesting in the context of education. The but could also still simply reflect the amount of previously
study by Draganski and colleagues (2006) clearly shows learned information. The extent to which learning and its
that the acquisition of vast medical knowledge is associ- effect on hippocampal structure may also further improve
ated with increases in hippocampal volume (Figure 2). The processing efficiency, such as the ability for new learning as
study by Mårtensson and colleagues (2012) is important such, remains to be further investigated.
because the setting of language studies was school-related, Several studies over the past ten years do, however, indi-
although learning occurred at an extreme pace as the stu- cate that schooling may affect cognitive ability. For example,
dents were training to become highly skilled military inter- the massive increases in intelligence across generations
preters. Additionally of interest, Mårtensson and colleagues of individuals during the 20th century (Flynn, 1984) have
reported that individual differences in volume change were been linked to rising levels of education (Baker et al., 2015;
associated with the acquisition of language independent of Rönnlund & Nilsson, 2009). Several quasi-experimental
the effort put into studying. This finding may indicate that studies, using, for example, variations in exposure to school
plasticity of the hippocampus (i.e., its potential for change) reforms, have also pointed to causal effects of education

4
 Elisabeth Wenger and Martin Lövdén

on cognitive performance in both childhood and adoles- axis activity and modified brain development (Seckl, 2007).
cence (Brinch & Galloway, 2012; Ceci, 1991; Cliffordson Possibly the most direct link between glucocorticoids and
& Gustafsson, 2008). Many of these effects appear to be hippocampal volume was found in rhesus monkeys: pre-
located at the level of broad cognitive abilities rather than at natal treatment with a synthetic glucocorticoid receptor
the level of general intelligence (Cliffordson & Gustafsson, agonist, thereby decreasing the inhibition of HPA axis activ-
2008; Tommasi et al., 2015). To our knowledge, specific ity, resulted in reduced hippocampal volume at 20 months
effects on hippocampus-dependent tasks, such as episodic of age (Uno et al., 1990). Exposure to prenatal stress has
memory ability, have not been reported yet. Experimental also been reported to have effects on adult behavior, namely
studies also—at least to some extent—support the mal- enhanced sensitivity to drug abuse and increases in anxiety-
leability of cognitive ability in childhood and adulthood. and depression-related behaviors, and, importantly, learning
Intervention studies in childhood, such as early head start and memory impairments because of its effects on hip-
programs with various forms of early education, have been pocampal function (Lupien et al., 2009).
shown to raise intelligence, although these effects fade out Contrary to the effects of chronic or severe stress on brain
within a few years (Protzko, 2015). Some cognitive training and behavior early in life, which seem to be long-lasting
studies on younger and older adults also suggest that effects and detrimental across the board, effects of stress dur-
of practicing cognitive tasks may transfer to untrained ing adulthood seem to be less univocal. The impact of
tasks measuring broad abilities, such as episodic memory acute stressors depends on the level of glucocorticoid
(Schmiedek, Lövdén, & Lindenberger, 2010, 2014), indicat- elevations, with small increases resulting in enhanced
ing that cognitive activity may indeed improve processing hippocampus-mediated learning and memory, and larger,
efficiency (Lövdén et al., 2010). However, the reliability and prolonged elevations impairing hippocampal function (Dia-
size of effects of cognitive training remain debated (Au mond, Bennett, Fleshner, & Rose, 1992; Lupien & McEwen,
et al., 2015; Dougherty, Hamovitz, & Tidwell, 2016; Lövdén, 1997). This inverted-U-shaped modulation may constitute a
Bäckman, & Lindenberger, 2015; Melby-Lervåg & Hulme, very useful adaptation by increasing vigilance, memory, and
2016) and so does the presence of causal effects of education learning under stress. Importantly, stress in adulthood, even
on cognitive performance (Deary & Johnson, 2010; Richards chronic stress, may not have the same long-lasting effects
& Sacker, 2011). as stress earlier in life exerts, and its behavioral and neural
In summary, the hippocampus is a highly plastic brain consequences may even be reversible after a few weeks of
structure—a capacity that is important for educational nonstress (Luine, Villegas, Martinez, & McEwen, 1994).
achievement and development of cognitive ability and skill. It appears likely, then, that decreased hippocampal vol-
This malleability of brain structure, however, also seems ume and function found in depression and post-traumatic
to have a negative side to it, that is, the hippocampus may stress disorder (PTSD) (Campbell, Marriott, Nahmias, &
also be particularly vulnerable to risk factors such as stress, MacQueen, 2004; Kühn & Gallinat, 2013) is rather a pre-
vascular conditions, and metabolic syndrome (Kühn & disposition and risk factor for developing such a disorder
Lindenberger, 2016; Raz, 2007). Sapolsky and colleagues than a result of the disorder in adulthood itself (Gilbertson
were among the first to note that stress exposure might lead et al., 2002; Heim, Newport, Mletzko, Miller, & Nemeroff,
to a damaged brain not only in rodents but also in primates 2008). Childhood trauma and the associated neural changes
(Uno, Tarara, Else, Suleman, & Sapolsky, 1989). Stress trig- in the hippocampus are therefore a powerful risk factor for
gers the activation of the hypothalamus-pituitary-adrenal developing depression in adulthood, especially in connec-
(HPA) axis, culminating in the production of glucocor- tion with additional stress (Heim et al., 2008), reiterating
ticoids by the adrenals. Receptors for these steroids are the importance and value of minimizing early life stress and
expressed throughout the brain but are especially numerous stressors to provide for the most optimal starting conditions.
in the hippocampus, thus making it a target region of stress In this context, mindfulness training has been discussed as
hormones and therefore highly susceptible to chronic stress a potential tool to reduce anxiety and stress and has been
(McEwen, 1999). found to represent a moderately effective treatment (Khoury
The effects of stress can already be observed prenatally, et al., 2013). First attempts have been made to implement
when the hippocampus seems to be most vulnerable to mindfulness training in schools, and the effects on stress,
adversity (Lupien, McEwen, Gunnar, & Heim, 2009). In ani- attention, and emotional self-regulation in comparison to
mal studies, it has been shown that a single or repeated expo- control groups have looked promising (Meiklejohn et al.,
sure of a pregnant female to stress (Cadet, Pradier, Dalle, 2012; van de Weijer-Bergsma, Langenberg, Brandsma,
& Delost, 1986) or to glucocorticoids (Dean & Matthews, Oort, & Bögels, 2014). One study even found improved
1999) leads to an increase in maternal glucocorticoid secre- working memory capacity and better performance in a
tion. A portion of these additional maternal glucocorticoids standardized graduate admissions test (GRE), mediated
can then reach the fetus, leading to an increased fetal HPA by reduced mind wandering (Mrazek, Franklin, Phillips,

5
 The Learning Hippocampus

Baird, & Schooler, 2013). However, further studies with

meticulously designed control groups are needed to assess
true unique improvements through mindfulness training
above other stress-reduction paradigms (Jensen, Vangkilde,
Frokjaer, & Hasselbalch, 2012). Flexibility

Amount
AGE DIFFERENCES IN PLASTICITY

Research has now shown that the long-lasting view of an

adult brain incapable of change is too pessimistic: the brain Plasticity
is flexible throughout the lifespan, and it can adjust to
new experiences and challenges, albeit to varying degrees
(Churchill et al., 2002; Hensch, 2005; Kempermann, 2006;
Lövdén et al., 2013). As reviewed above, the hippocampus Childhood Adulthood Old Age
seems to be an especially malleable region in this regard. Lifespan
Although it has been found that lifelong plasticity is pos-
sible, the influence experience can exert to shape the brain Fig. 3. Age differences in plasticity. Flexibility, as the capacity to
changes immensely across the lifespan (Takesian & Hensch, optimize performance within the limits of the current functional
2013; see Figure 3). As much as it is intriguing to argue for supply, is assumed to increase from childhood to adulthood. Plas-
ticity, as the capacity for changes in the brain’s chemistry and struc-
learning and even restructuring of the brain throughout the
ture, is thought to decrease over the lifespan. Figure reprinted from
lifespan, there is no sense in denying that learning (e.g., lan-
Kühn and Lindenberger (2016).
guages) when you are young is so much easier than when you
begin to get older (Kliegl, Smith, & Baltes, 1989).
The notions of “sensitive” or “critical” periods—an inter- extraordinary biological resources that may not be available
val during development when the neural circuits responsible to spare (Kuzawa et al., 2014). Hence, the impression that
for a process are more open for being sculpted and radi- learning comes easier during early phases of life compared to
cally changed by experience—are clearly important in the later ones has its biological foundation in the efficiency of the
context of age differences in plasticity. It has been known brain’s architecture and its reluctance to change its circuits
for nearly 50 years that an animal requires certain kinds of that have been built in accordance to early life experiences.
environmental stimulation at specific times during its devel- This reluctance to change can thus be viewed as an adap-
opment for the brain’s sensory and motor systems to develop tive process, and one may argue that it is partly an active
normally. It was discovered that depriving an organism of developmental process or a “brake” on plasticity during
certain experiences at an early age (e.g., depriving an eye adulthood (Takesian & Hensch, 2013). Hensch and col-
of visual input during a critical period) seriously compro- leagues distinguish between two types of neural “brakes”
mises brain function later on (Wiesel & Hubel, 1963). The on plasticity—structural and functional ones. One structural
effects of deprivation can be much less profound or even not brake could, for example, be the perineuronal net, a com-
detectable if deprivation does not fall within a critical period plex of macromolecules that attach to parvalbumin (PV)
(e.g., the animal had visual input before the time of depriva- interneurons around the time a critical period comes to an
tion) (Wiesel & Hubel, 1963). end and that seem to restrict the extent to which a neural
This research has provided a very striking example of circuit can be modified (Berardi, Pizzorusso, & Maffei, 2004).
plasticity during defined critical periods in brain devel- Chemical breakdown of the perineuronal nets in adult rats
opment: certain sensory experiences ought to occur by a makes their brains prone to being rewired (Pizzorusso,
certain age for the corresponding neural sensory areas to 2002). Functional brakes are chemical compounds such as
develop optimally—thus, called experience-expectant plas- Lynx1—a molecule that shifts the balance of excitation and
ticity in contrast to experience-dependent plasticity (Gree- inhibition in the cortex by dampening the effect of the
nough, Black, & Wallace, 1987). The system is expecting neurotransmitter acetylcholine (Morishita, Miwa, Heintz, &
certain experiences and is setting up its circuits accord- Hensch, 2010). The amount of Lynx1 in the brain seems to
ing to given input. If the appropriate sensory experiences increase at the end of a critical period, and its removal from
do not occur within this specific time window, the neural adult brains, just like the degradation of perineuronal nets,
circuitries are set up in a way best adjusting to this spe- seems to restore neural plasticity (Morishita et al., 2010).
cific, deprived environment. After that, they remain reluc- In sum, always adapting to new environmental demands
tant to change, because rewiring would entail the devotion of with plasticity would be metabolically costly for the brain

6
 Elisabeth Wenger and Martin Lövdén

(Kuzawa et al., 2014). Therefore, favoring stability over con- in age-standardized settings) (Gledhill, Ford, & Goodman,
stant change seems to be a good strategy in adulthood, 2002). This suggests that teachers might not take chrono-
when a human being has acquired a rich model of the world logical age sufficiently into account when assessing pupils’
already, enabling him or her to respond flexibly with a rich ability within one classroom. This can lead to negative con-
behavioral repertoire to most given situations (Kühn & Lin- sequences for the pupils’ self-esteem and also academic
denberger, 2016). At the same time, this emphasis on stability achievements in the long run (Gledhill et al., 2002). It may
obviously inherits the disadvantage of more difficult learning therefore even be more beneficial for a child born close to
and less plastic brains in adulthood. the cut-off date of an academic year to potentially spend
an extra year in kindergarten than starting school as one of
the youngest in this classroom cohort. Although there is an
A FRAMEWORK FOR PLASTICITY AND ITS ongoing debate on whether delayed school entry is benefi-
RELEVANCE FOR EDUCATION cial for children or not (e.g., Jäkel, Strauss, Johnson, Gilmore,
& Wolke, 2015), it seems plausible to believe that children
In summary, the hippocampus plays an important role with appropriately matured brain structure will be able to
in declarative learning and memory of declarative infor- profit most from their schooling environment—much as the
mation while also being formed by such experiences. finding of more hippocampal gray matter volume correlat-
Experience-dependent plasticity is heightened in childhood. ing with greater success in the math tutoring program sug-
This should not be taken to necessarily mean that what is not gests (Supekar et al., 2013). Also, although early head-start
learned in early years will not be possible to compensate for programs with various forms of preschool education raise
later; the hippocampus retains a degree of plasticity in later intelligence, it is important to note that these effects fade
childhood and well into adulthood. There have been some out within a few years (Protzko, 2015). This fading out of
educational debates in which the importance of the first the effects is mainly a result of slower development for the
three years has been overly emphasized, leading to concepts intervention groups after termination of the intervention
like “hothousing”—teaching infants academic skills such as and not a result of the control groups catching up.
reading, logic, and mathematics. It is true that in infancy, These results on early education interventions suggest
there is a dramatic increase in the number of connections that the push for plastic changes is largest when the envi-
between cells and that enrichment leads to more connec- ronmental demands are within the reach of an individuals’
tions in the brain than impoverished environments. Lower capacity. It also suggests that children whose abilities
socioeconomic status has been shown to be correlated increase from educational interventions lose these gains
with lower hippocampal volume (Noble, Houston, Kan, & once returning to their previous environment, indicating
Sowell, 2012), which is still detectable 50 years later, well that cognitive ability adapts to the demand of the environ-
into adulthood (Staff et al., 2012). This relationship could ment, increasing when demands increase and decreasing
be because of differences in cognitive stimulation, linguistic when demands shrink. These findings suggest that ability,
environment, and exposure to stress (Hackman, Farah, such as declarative memory performance, may have lit-
& Meaney, 2010). However, it is important to remember tle effect on determining effects of education on further
the cross-sectional nature of these results in connection development of these abilities. That is, young children may
with socioeconomic status and therewith the possibility generally have little room for actively creating and seeking
of third-factor influences. Negative outcomes in cognitive out environments that put optimal demands on ability
and noncognitive areas after lack of stimulation have been (Protzko, 2015). Such reciprocal effects may, however, play
observed in its extreme because of institutionalization in out stronger in adolescence and early adulthood, when the
Rumanian orphanages (Chugani et al., 2001; Mehta et al., possibility for individual choices of education is larger, and
2009; Wilson, 2003). Importantly, however, these are cases individual capacity determines access to further education
in which deprivation has led to negative outcomes. These to a larger degree.
examples cannot be used to dismiss “normal” environments These reflections on plasticity in childhood fit well with
and promote starting education as early as possible or the supply–demand mismatch model of plasticity, which has
to simply cram infants’ senses with the most numerous been developed in the context of adult plasticity (Lövdén
impressions possible. et al., 2010). In this model, plasticity denotes the inher-
Research has shown that within the same classroom, ent ability of the brain to adapt with structural changes in
the youngest children have lower academic achievement response to altered environmental demands (Lövdén et al.,
than the oldest children in class (Robertson, 2011; Ver- 2010). Plasticity is distinguished from flexibility. Plasticity is
achtert, De Fraine, Onghena, & Ghesquière, 2010) and are a continuous aspiration for equilibrium between the current
being evaluated more often to having special educational experienced environmental demands and the supply pro-
needs (although there were no differences in IQ values vided by the system’s current functional capacity. Flexibility

7
 The Learning Hippocampus

High
Dynamic Prolonged Dynamic
Equilibrium Mismatch Equilibrium
Maximum function
Manifestation

Functional Supply
of plasticity

Negative Mismatch Flexibility: functional

Demand > Supply: supply supports a
Positive Mismatch:
range of functioning
Demand < Supply
but is optimized (black
line) to a level of demand
that is integrated over
Demand on (use of)
functional supply
some unknown time
Low period
Time

Fig. 4. Supply–demand mismatch model of plasticity. Plasticity here is the ability of the brain structure to adapt with macroscale
changes in response to altered environmental demands. It is thus an adaptive process that is triggered by a prolonged mismatch between
the functional supply the brain structure can momentarily provide and the experienced demands the environment poses. If there is
a prolonged negative mismatch between these two, that is, if the environmental demands are consistently higher than the provided
functional supply, the brain structure will adapt in order to again best fit its specific environment. Figure adapted from Lövdén et al.
(2010).

optimizes the brain’s performance within a given state of to help the system adapt to new circumstances only if an
resources and functional supply. The brain constantly tries environmental demand is within this range.
to meet requirements posed by its unique environment. In This supply–demand model of plasticity implies that edu-
the majority of cases, this can be accomplished through cation should challenge individuals optimally at their current
neuronal and behavioral flexibility within a given equilib- level of functioning. As there are large interindividual differ-
rium. However, if these processes do not suffice in fulfilling ences, even within small age ranges within say one classroom
environmental demands, either because of dramatic changes cohort, person-adapted learning environments are of criti-
in requirements or because of damaged functionality of the cal importance. This implication bears some resemblance to
brain following brain injury, then change is demanded and some cognitive theories of instruction, such as cognitive load
can manifest in the form of plastic changes (see Figure 4). theory (Sweller, van Merrienboer, & Paas, 1998) and cog-
In other words, the major driving force of plastic changes nitive theory of multimedia learning (Mayer, 2005). These
is a mismatch between functional supply (e.g., ability) and theories are also concerned with how learning outcomes can
demands (e.g., of education). This mismatch model of plas- be optimized by tailoring instructional designs and learn-
ticity implies that the appearance of neuroplasticity is depen- ing scenarios to the individual learners with their individual
dent on the current level of functioning and flexibility on memory capacities and other individual prerequisites (Ger-
which a mismatch between environmental circumstances jets, Scheiter, & Cierniak, 2009). Besides tailoring instruc-
and brain supply is experienced (Lövdén et al., 2010). If the tional designs to the different pupils, the supply–demand
system is capable of responding to changed requirements model of plasticity would even advise to adjust task difficulty
through already existing flexibility alone, then no mismatch to individual needs and to constantly upgrade difficulty and
is experienced, and no plasticity is necessary. On the other not assume that reached ability levels simply remain with-
hand, if the mismatch is too large, that is, if the new require- out further challenge. A student less talented or less far in
ments are far too high relative to the momentary state of his or her development might profit more from easy tasks
functional level, then the system will not be able to assimi- than his or her further-developed classmate, who might live
late to it in any way, and no plasticity will evolve. Such sit- up more to his or her potentials if challenged more. The pro-
uations could be associated with high levels of stress and posed aptitude–treatment interaction perspective (Cron-
the negative effects on the brain that we reviewed above. In bach & Snow, 1977), where optimal learning occurs when an
other words, this model emphasizes that the system needs instructional design is matched to learners’ particular pre-
to experience the mismatch, which means that the changed requisites, has been advocated with respect to different age
environmental requirements need to lie between certain groups, but probably needs to be applied to individuals even
boundaries of too easy and too difficult tasks in order to show within one age group (i.e., within class rooms with pupils of
experience-dependent plasticity. Neuroplasticity can occur approximately the same age).

8
 Elisabeth Wenger and Martin Lövdén

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