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3rd Year Neuroscience Essay
Essay about synaptic plasticity and memory
Date : 05/11/2017
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Uploaded by : Gemma
Uploaded on : 05/11/2017
Subject : Neuroscience
Choose a
form of plasticity that occurs at a particular synapse. Describe its
properties. Give arguments for and against this synaptic plasticity
representing the cellular substrate of particular types of learning. How would
you design an experiment to demonstrate the causal link between synaptic
plasticity and learning and memory? Synaptic plasticity describes the activity-dependent
changes in synaptic efficacy that can be observed in multiple brain regions. Long-term
potentiation (LTP) was first described by Bliss and Lomo (1973), and enables synaptic transmission to be
increased. The vast majority of experimental work on LTP has been performed at
excitatory synapses between the Schaffer-collateral and commissural axons and
apical dendrites of pyramidal cells in the CA1 region of hippocampus (Hc),
though the LTP observed at CA1 synapses appears to be identical (or at least
very similar) to LTP observed at glutamatergic synapses throughout the
mammalian brain. Indeed, the observation that LTP can be most reliably
generated in brain regions involved in learning and memory (Neves et al 2008), in conjunction with the fact that LTP
can be rapidly induced, long-lasting and display properties of input
specificity and associativity, has made it a prime candidate as a cellular
correlate of learning and memory. The synaptic plasticity and memory (SPM)
hypothesis, defined by Martin et al (2000) states that activity-dependent synaptic
plasticity is induced at appropriate synapses during memory formation, and is
both necessary and sufficient for the information storage underlying the type
of memory mediated by the brain area in which that plasticity is observed . In this
essay, I will discuss the properties of the LTP observed in Hc CA1 (focussing
on its postsynaptic expression mechanisms), the evidence for and against
its involvement in Hc-dependent types of memory, and what further work must be
done to provide evidence for the causal link between LTP and memory. LPT can be induced by either high-frequency
stimulation (tetanic stimulation) of the presynaptic neuron (resulting in
strong temporal summation of EPSPs in the postsynaptic spine), low-frequency
stimulation of the axon held at a strongly depolarised membrane potential
(typically -10mV, called the pairing protocol), or precisely timed stimulation
of the presynaptic neuron followed by the postsynaptic neuron (within 10ms).
Any of these three protocols results in strong postsynaptic depolarisation,
maximal activation of NMDA receptors (which are blocked by Mg2+ at
resting membrane potential, acting as coincidence detectors (Nowak et al (1984)), and thus maximal NMDAR-dependent influx
of Ca2+. A number of studies have shown that LTP is reliant on this
NMDAR-dependent postsynaptic Ca2+ influx. In studies on rat CA1
slices, Collingridge et al (1983) showed that application of AP5 inhibits
the induction of LTP without altering the performance of the synapse, whilst Malenka et al (1988) used Nitr-5 (a photolabile calcium chelator)
to show that postsynaptic Ca2+ is not only necessary but also
sufficient to induce LTP. Microflourometric measurements in individual CA1
pyramidal cells during LTP induction showed that high-frequency stimulus trains
produce transient components of postsynaptic Ca2+ accumulation that
is blocked by AP5, indicating that LTP-induction protocols induce an
NMDAR-mediated increase in intracellular Ca2+ (Regehr & Tank, 1990). This Ca2+ then interacts with
a number of enzymes to bring about the induction and expression of LTP. In 1989, whilst trying to determine how both LTP
and LTD (long-term depression) could rely on a Ca2+ signal, Lisman
proposed that LTP is a consequence of a shift towards protein kinase activity
that occurs at higher [Ca2+], and there is much evidence in support
of this. Malenka et al (1989) found that intracellular injection of H-7
(a general protein kinase inhibitor) into CA1 pyramidal cells blocks LTP
induction, indicating the necessity of kinase activity (and thus
phosphorylation) for LTP. Further experiments by Malinow et al (1989) showed that postsynaptic CaMKII and PKC
are required for LTP induction, and Lledo et al
(1995) showed that the
injection of a truncated, constitutively active form of CaMKII into CA1
pyramidal cells is sufficient for synaptic strength augmentation. Evidence shows
that CaMKII is able to directly phorphorylate AMPAR GluR1 at Ser831
in situ (Barria et al, 1997), thus increasing the AMPAR single-channel
conductance (Benke et al, 1998 Derkach et al, 1999). In addition, it is thought that CaMKII
may act to bring about the insertion of AMPARs at the synapse. Other protein
kinases have also been implicated in LTP induction. Inhibition of PKC or PKA
blocks LTP induction (Malinow et al, 1989 Frey et al, 1993). High [Ca2+] activates
adenylyl cyclase, increasing intracellular cAMP levels, and resulting in the
activation of PKA, which goes on to inhibit PP1, thus inhibiting the
dephosphorylation pathway implicated in LTD. However, whilst CaMKII and PKC appear necessary for
the induction of LTP, there remains debate about how LTP can be maintained
beyond the Ca2+ signal. Though CaMKII is able to be autophosphorylated
on Thr286 upon activation by Ca2+ (thus rendering its
activity no longer dependent on Ca2+ and enabling its activity to
continue beyond the transient Ca2+ signal), postsynaptic H-7
application after the induction of LTP has no effect on its maintenance,
indicating that CaMKII and PKC are not necessary for LTP s maintenance.
Instead, it has been suggested that PKM, which is
constitutively active, is both necessary and sufficient for LTP maintenance. Ling et al (2002) showed that chelerythrine and ZIP (PKM inhibitor) inhibits the maintenance of
established LTP, whilst the diffusion of PKM into cells enhanced the EPSC amplitudes within
minutes. However, Volk et al (2013) used KO mice to show that mice lacking PKM exhibited normal synaptic transmission and LTP
at schaffer collateral-CA1 synapses. Thus, the debate about the involvement of PKM continues on. As alluded to above, a number of the properties of LTP
make it an ideal candidate as the cellular substrate of learning and memory. In
addition to being rapidly induced and long-lasting, LTP is also highly input
specific, as shown by Andersen et al (1980) in their studies on CA1 regions of guinea
pig Hc sliced maintained in vitro. This property of LTP is accounted for by the
local source of Ca2+ within dendritic spines, and greatly increases
the computational possibilities and storage capacities of each neuron.
Furthermore, the associative induction of LTP described by Barrionuevo and Brown (1983) has been argued to be a cellular analogue
of associative or classical conditioning. However, whilst the LTP generated in
CA1 by the induction protocols outlined above has the appropriate properties
for a memory mechanisms, this LTP only reflects a memory of the brain having
been (artificially) electrically stimulated and does not provide evidence that
learning itself induces LTP in vivo. Learning induced LTP is difficult to demonstrate
for 2 reasons. Firstly, many Hc-dependent learning tasks are iterative and thus
require multiple training trials for the memory to be formed. Differences in
learning rates across animals would obscure time-sensitive markers of LTP.
Secondly, the synaptic changes may be sparse and widely distributed, meaning
that potentiated synapses would be difficult to locate within a vast sea of
synapses. Whitlock et al (2006) were able to overcome this by training adult
rats using the inhibitory avoidance (IA) paradigm, which has been shown to
create a stable memory trace in a single trial, and to cause substantial
changes in gene expression in CA1. They showed that IA results in an immediate
NMDAR-dependent increase in phosphorylation of GluR1 at Ser831, the delivery of GluR1 and GluR2 (but not NR1)
to the synaptoneurosome (SNS) biochemical fraction, and an increase in the
slope of the evoked fEPSP, thus mimicking the effects of HFS. In addition, they
showed that these IA-induced increases in evoked fEPSP partially occluded
subsequent LTP by FHS, providing evidence that LTP and learning induce change
by a common mechanism There is much evidence supporting the importance of
the hippocampus in certain kinds of memory. The famous case of patient HM shows
that damage to/lesioning of Hc results in profound amnesia, whilst
electrophysiolocial recordings and molecular imaging in animals, and MRI in
humans provides correlative evidence that certain types of learning involve Hc
activity. However, the exact role of Hc in memory remains contested. The theory
that is perhaps most influential, put forward by O Keefe and Nadel in 1978,
posits that the primary role of Hc is to encode spatial information and form
spatial memories. This is based on the discovery of place cells in CA1 (O Keefe & Dostrovsky, 1971), and the observation that lesions in Hc
impair spatial memory, particularly the acquisition of associative spatial
reference memories such as during the Morris Watermaze task. Thus, the
hypothesis that LTP-like mechanisms in the CA1-subregion of Hc underlie
Hc-dependent forms of associative spatial learning has emerged. Based on this,
manipulation that prevent Hc LTP should prevent Hc-dependent forms of learning,
and this has been studied using both pharmacological and genetic tools, as is
discussed below. In 2006, Pastalkova et al injected a cell-permeable PKM inhibitor into the rat Hc. Though found that
this both reserved LTP maintenance in vivo and also produced persistent loss of
1-day-old spatial information. Furthermore, they found that the inhibitor could
block LTP and impair Hc-dependent memory even if administered days after
acquisition. Thus, they argued that the mechanism maintaining LTP also sustains
spatial memory. Morris et al (1986) showed the importance of NMDAR-dependent
LTP in spatial memory by applying AP5 to rats by intracerebroventricular
infusion using osmotic minipumps. They trained control and AP5-infused rats on
the morris watermaze task, and found that the AP5 rats stabilized escape
latencies at a higher level (were impaired) and were also impaired in the
transfer test. Furthermore, as the AP5 mice performed as well as controls in a
visual discrimination task, they argued that chronic AP5 infusion led to a
spatial learning impairment that was not caused by secondary sensorimotor or
motivational impairment. However, other studies have reported that chronic AP5
application results in sensorimotor deficits, and even in the above studies,
the AP5 rats were more prone to falling off the platform. Also, in the above
study, AP5 application is not Hc-specific as it diffuses all around the brain, and
thus it is not possible to conclude that the effect seen is due to blocking Hc
NMDAR. Furthermore, Bannerman et al (1995) found that NMDAR-dependent LTP was not
required for spatial navigation or to form associations between a spatial
location and a platform. They pre-trained rats in a watermaze task before
implanting the minipumps and training them in a second task. This pretraining
ameliorated the effects of the AP5, with the rats showing no impairment in a
transfer test. They showed that the Hc was still necessary for spatial learning
even after pretraining, as rats lesioned after pretraining were significantly
impaired. They argued that though NMDAR-dependent LTP was required for some
component of spatial learning, it may not be required for encoding spatial
representations of a specific environment. Thus, we see that no clear
conclusions can be drawn from these pharmacological studies. Other labs have used a genetic approach to study the
involvement of hippocampal LTP in learning and memory. Silva et al (1992) showed that -CaMKII knockout (KO)
mice exhibit mostly normal behaviours and intact postsynaptic mechanisms
(including NMDAR function). However, these mice exhibit specific learning
impairments, indicating the importance of -CaMKII in spatial
learning but not in non-spatial learning. Tsien et al (1996) used the Cre/LoxP method to create a
mouse strain with CA1 pyramidal cell-specific GluN1 KO. LTP could not be
induced at these synapses, and the mice showed significant impairment in
spatial tasks, though not in non-spatial tasks. However, it was later found by
other labs that the KO was not truly Hc-specific, and indeed, other labs
obtained different results when using confirmed Hc-specific GluN1 KO mice. Bannerman et al (2012) showed that whilst LTP could not be
induced in CA1 of these mice, they showed no impairment in the watermaze task
of transfer task. However, in a spatial discrimination watermaze task (using
two visually identical beacons), na ve KO mice were significantly impaired,
making more choice errors than controls, though performing as well as controls
in the transfer task. They observed that the number of choice errors varied
systematically a function of where the trial was started from. Thus, it was
postulated that the KO did not result in a spatial learning deficit, but rather
an inability to use spatial cues to behaviourally inhibit strong conditioned
responses. The group argued that hippocampal LTP was not required to encode
associative spatial memories, but rather were important for when one must
disambiguate between overlapping or competing memories. They did not deny that
synaptic plasticity is important for learning and memory, as has been shown by
other studies, but their evidence suggest that perhaps the role of the Hc must
be reconsidered. Hc could still be important for learning and memory, but may
not be the site at which memories are encoded. Thus, we see that even genetic
studies are not able to offer clear conclusion on the topic. Furthermore, it is important to note that in the above
experiments, it is difficult to conclude that LTP has been completely
abolished. Though we see that experimenter-induced LTP has been abolished, the
Hc is likely to use different protocols to establish LTP (indeed, some LTP
induction protocols are not physiologically plausible). It is possible that
behaving animals may still be able to generate sharp-wave ripples: naturally
occurring high-frequency waveforms generated by synchronous firing of CA3
pyramidal cells that can facilitate LTP induction. Indeed, Hoffman et al (2002) showed that, whilst LTP induced by a
brief burst of 100Hz stimulation was absent in GluN1 KO mice CA1, LTP could
still be induced by theta-burst pairing protocol, which mimics the theta waves
generated in Hc of rodents when they explore an environment. When designing experiments testing the causal link
between memory and synaptic plasticity, it is important to not only consider
synaptic plasticity at single neurons, but also how networks of neurons act
together to encode neurons. The necessity for synaptic plasticity in memory
encoding could be shown in experiments using circuit-specific memory erasure
(that is to say, the silencing of neurons containing synapses that were
modified during the acquisition of memories), though this will require the advent
of more technologies. One approach could be the generation of a transgenic
animal model in which promoters from activity-dependent genes are used to drive
the expression of transgenes specifically in recently potentiated cells. These
transgenes could be used to reversibly inactivate Hc neuronal spiking by
driving the expression of membrane proteins that generate appropriate changes
in excitability, thus enable us to study the effect on the memory when the
neurons associated with it are silenced. Evidence has shown that the expression
of several immediate-early genes (IEGs) such as Arc/Arg3.1 are upregulated by
LTP-inducing protocols in vitro, in vivo, and in behavioural training. The
drosophila melanogaster GPCR for allatostatin (AlstR) has been shown to be able
to couple to mammalian G-protein-activated inwardly rectifying K+
channels, thus hyperpolarising and silencing the neuron upon allatostatin
application. In a transgenic mouse, the activity-dependent Arc/Arg3.1 promoter
could be used to drive AlstR expression, meaning that cells with potentiated
synapses will express the receptor. As the receptors are internalised and
degraded after some time, the application of allatostatin would silence neurons
with recently potentiated synapses, meaning that this method could be used to
erase recent memories whilst sparing more remote memories. This would enable
the study of the causal link between synaptic plasticity and memory storage. In
addition, future studies must aim to also show the sufficiency of plasticity
for memory storage. Such studies may appear impossible, as it would be unclear
which synapses within a sea of synapses in a network should by modified.
Perhaps one way of getting around this would be to use a standard training
procedure to form a Hc-dependent memory, then erase this memory, and finally
attempt to re-install the memory using the knowledge gained about synaptic
changes during the original learning. Thus, we see that the full understanding
of memory and the neural circuity involved may not be achieved until tools have
been developed to study networks at large. In conclusion, we have discussed the properties of the
LTP that can be induced in CA1 region of Hc, and seen that behavioural learning
is able to induce LTP-like changes that mimic and occlude LTP (indicating that
they act by common mechanisms). We have discussed a number of properties of LTP
that make it a promising candidate for a cellular substrate of memory, but
although increasing numbers of experiments provide evidence for a causal link
between LTP and memory, definitive evidence that LTP is necessary for
Hc-dependent learning is lacking. Indeed, a number of experiments provide
opposing evidence, claiming that NMDAR-dependent LTP in Hc is not required for
Hc-dependent forms of associative spatial learning. This being said, it is also
important to consider that though LTP may not be necessary for learning
(perhaps due to another mechanism), LTP may be the brain s default choice for
memory encoding when available, and may be the most physiologically relevant
form of memory encoding. Finally, we have discussed how, in order to fully
understand the link between plasticity and memory, neural networks must be
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