Intrinsic Plasticity

under Neurophysiology of Learning and Memory

Intrinsic plasticity, also known as non-synaptic plasticity, is a form of neuronal plasticity which differs from classic synaptic plasticity such as long-term potentiation (LTP) through the fact that it is widespread and affects the entire neuron's excitatory properties. As its name suggests, it occurs on a wide scale, affecting the ability of the entire neuron to evoke EPSPs and consequently an action potential (AP), typically through modulation of ion channel currents, and other as of yet unidentified mechanisms. While these two forms of plasticity are distinct from one another, scientists have shown that intrinsic and synaptic plasticity interact with one another When first identified in 1973 by Bliss and Lomo, not much was known about the mechanisms of intrinsic plasticity, and for many years scientists focused more on identifying the molecular correlates of synaptic plasticity instead. Since then the field has grown immensely, with many new studies being performed annually in various animal models such as rabbits, rats, Lymnaea stagnalis and Aplysia californica. As intrinsic plasticity has been implicated in the regulation of memory formation and forms of synaptic plasticity, it may be relevant to other plastic processes such as pain perception, and activity-dependent processes such as synaptogenesis.


1 Electrophysiological markers of intrinsic plasticity
. 1.1 Changes in spike threshold
. 1.2 Modulation of input resistance
. 1.3 Increased cell excitability
. 1.4 Reduced afterhyperpolarization
2 Animal models of intrinsic plasticity
. 2.1 Classical conditioning paradigms
. 2.2 Operant conditioning paradigms
. 2.3 Electrophysiological recording from tissue slices
3 Molecular substrates of intrinsic plasticity
. 3.3 Modulation of persistent ion currents
4 References

Electrophysiological markers of intrinsic plasticity

There are several key features of intrinsic plasticity which have been identified. One such electrophysiological alteration is a decrease in the spike threshold of the neuron, i.e. the minimum current required to elicit an EPSP, or sometimes an action potential in response to a stimulus. Another classic marker of intrinsic plasticity is an increase in the excitability of a cell following induction of synaptic plasticity in the neuron. This was originally observed by Bliss and Lomo in the granule cells of the dentate gyrus of rabbits. Cells undergoing non-synaptic plasticity also show a marked reduction in the afterhyperpolarization period following successive action potentials, rendering the neurons more excitable and capable of firing successive action potentials with a smaller temporal delay. Finally, the input resistance of the neuron also changes with respect to the mechanisms of intrinsic plasticity (Breton & Stuart, 2009).

Changes in spike threshold

Reduction in AP threshold demonstrating intrinsic plasticity following classical conditioning in rat CA1 hippcampus

Spike threshold as defined with respect to intrinsic plasticity refers to the minimal current required to elicit a population spike, or EPSP, in a given region in response to a stimulus. It may also be used to denote the minimal depolarization required for the generation of an action potential at the axon hillock of the neuron. Following induction of synaptic plasticity, it has been shown that spike threshold tends to decrease, making a neuron more likely to elicit an EPSP, thus leading to greater spatial and temporal summation and a higher propensity to generate an action potential following stimulation.
In rat hippocampal CA1 pyramidal neurons, induction of LTP was followed by a change in the intrinsic excitability of the neuron, mediated primarily through a decrease in AP threshold, afterhyperpolarization, and spike onset time. This was shown to occur primarily through downregulation of biphasic somatic A-type potassium channels, which led to an increase in the excitability of the cell by depolarization of the neuronal membrane (Breton & Stuart, 2009).

Another study looking at changes in intrinsic excitability of Purkinje cells in the rabbit cerebellum demonstrated that following classical conditioning, the level of parallel fiber stimulation required to evoke an EPSP in the Purkinje cell dendrites was reduced (Schreurs et al., 1997). This further suggests that intrinsic plasticity proceeds in part through a decrease in spike threshold, and provides evidence from a completely different brain region, using a completely different conditioning paradigm.

Modulation of input resistance

The input resistance of a neuron is defined as the change in voltage associated with the injection of a current, divided by the input current. As such an increase in the input resistance of a neuron means that there will be a greater change in the surface voltage of the membrane in response to a current, thus rendering the neuron more excitable as less current is required to elicit the same depolarization. As such it is no surprise that input resistance is typically increased in neurons which undergo processes of intrinsic plasticity. One such experiment was conducted using an in-vitro model of operant conditioning in Aplysia californica. Through operant conditioning of the feeding circuit of Aplysia, a key "decision-making" neuron known as B51 demonstrated increased cell excitability through both a decrease in spike threshold and an increase in the input resistance of the neuron (Mozzachiodi et al., 2008). This has also been shown to be the case in sensory and motor areas of the cat cortex following classical conditioning of the eye-blink reflex (Woody & Black-Cleworth, 1973), demonstrating that these effects occur independent of the type of conditioning paradigm employed.

Increased cell excitability

Reduction in AP onset time and afterhyperpolarization following LTP induction in rat CA1 pyramidal neurons.
This is the most general characteristic of intrinsic plasticity, and is typically mediated through changing electrophysiological properties such as the reduced spike threshold and reduced post-burst afterhyperpolarization. This has been examined in rabbits using the trace eye-blink conditioning paradigm. This is a classical conditioning experiment involved in pairing an unconditioned stimulus (typically a tone) with a mild air puff to the eye. The animal then learns the association between this stimulus and the air puff, and blinks the eye in response to the unconditioned stimulus alone. By recording from CA1 neurons in slices of rabbit hippocampus at various stages of conditioning, it has been shown that these cells increased their excitability in a learning-specific manner (Moyer et al., 1996).

Experiments in Lymnaea stagnalis have also demonstrated that non-synaptic plasticity occurs by means of increased cell excitability (Jones et al., 2003; Kemenes et al., 2006). In fact, this occurs several hours after conditioning, meaning it coincides with the supposed time frame for consolidation of long-term memories. This suggests an interaction between this intrinsic plasticity and mechanisms of memory consolidation, perhaps serving to facilitate the passage of memories from within the circuit to external storage in long-term memory.

Reduced afterhyperpolarization

Following an action potential, there is an afterhyperpolarization resulting from the rapid influx of potassium into the cell following the opening of voltage-gated potassium channels. This results in a rapid decrease in membrane potential, which typically exceeds the resting membrane potential of the cell. This lasts until potassium channels finally close, and the membrane potential slowly increases back to normal over a phase known as the refractory period. A reduction in this afterhyperpolarization, as is commonly seen when non-synaptic plasticity occurs, renders the neuron more able to fire action potentials in rapid succession. This has been demonstrated to occur in the CA1 region of the hippocampus both in rats (Jung & Hoffman, 2009) and rabbits (Moyer et al., 1996), the latter undergoing trace eye-blink conditioning. This is yet another characteristic of intrinsic plasticity on a neuronal level.

Animal models of intrinsic plasticity

There are numerous experimental models for studying the mechanisms of intrinsic plasticity in animals. Model organisms include rats, rabbits, and the snail Lymnaea stagnalis. In mammalian models, intrinsic plasticity is typically examined in brain regions which are known to undergo synaptic plasticity, as intrinsic plasticity typically occurs in conjunction with LTP or LTD. As such, it is typically studied in the CA1 region of the hippocampus, where synaptic plasticity has been previously shown to occur, or in the cerebellum, where trace eye-blink conditioning induces learning via long-term depression. While the majority of conditioning experiments use the classical conditioning paradigm, there are some newer studies which attempt to examine intrinsic plasticity in response to operant conditioning paradigms.

Classical conditioning paradigms

Classical conditioning involves learning an association between two simultaneously presented stimuli to elicit a response in the presence of a normally neutral stimulus alone. A widely used experimental paradigm is that of eye-blink conditioning, involving the pairing of a tone with a puff to the eye. After repeated training, the animal learns to associate the tone with the air puff, and will blink in response to the tone alone. This behavioural conditioning can thus be used to train animals and induce learning via long-term potentiation and other mechanisms of synaptic plasticity. As a consequence, some non-synaptic plasticity is typically observed, and this forms the basis for studies on the neurophysiological and molecular properties of this form of learning. Multiple studies of intrinsic plasticity have used this methodology in cats (Woody & Black-Cleworth, 1973) and rabbits (Moyer et al., 1996; Schreurs et al., 1997).

Other experiments use food-reward classical conditioning in Lymnaea stagnalis to examine changes in the non-synaptic properties of neurons involved in the snail feeding circuit (Kemenes et al., 2006; Jones et al., 2003). They use a single-trial appetitive conditioning model which they have developed to train the snails to associate a neutral stimulus (amyl acetate) with a stimulus associated with feeding (sucrose) to induce feeding behaviour (Kemenes et al., 2002).

Operant conditioning paradigms

In contrast to classical conditioning paradigms, examples of the use of operant conditioning paradigms to study intrinsic plasticity are far fewer in number. One reason for this may be that it is difficult to induce operant conditioning in some model organisms, such as Aplysia. In order to circumvent this, Mozzachiodi et al. developed a technique to mimic operant conditioning of feeding behaviour in Aplysia californica, allowing them to study how intrinsic plasticity affects long-term associative learning. They used in-vitro analogs of operant conditioning to observe an increase in the excitability of B51, an important critical for feeding behaviour in Aplysia. These techniques were developed recently, and are extensively described by Björn Brembs in Lymnaea stagnalis, Drosophila melanogaster, and the classic Aplysia californica.

Electrophysiological recording from tissue slices

While conditioning of an animal, both classical and operant, typically occurs in-vivo, there are methods to generate the same synaptic plasticity in-vitro using organotypic tissue slices. This has been performed in rats to examine the electrochemical properties neurons undergoing long-term potentiation, in order to possibly determine the molecular mechanisms by which intrinsic plasticity is mediated (Breton & Stuart, 2009). This has the advantage of permitting rapid recording, with a signal that is purely due to stimulation evoked by the experimenter in a highly controlled manner. The disadvantage is that tissue tends to die after only a few hours in-vitro, and as such it is impossible to obtain recordings after a certain period of time following conditioning. This technique also permits for patch-clamp recordings of individual membrane channels, which as it turns out may be responsible for mediating intrinsic plasticity in rats.

Molecular substrates for intrinsic plasticity

In order to examine the molecular substrates of intrinsic plasticity, it is necessary to do a very detailed analysis of the ion channels which modulate the excitability of the neuronal membrane, as well as potentially examine any proteins involved in regulating the activity of such channels. Recent studies have shown that intrinsic plasticity may be achieved through the modulation of persistent ion currents.

Modulation of persistent ion currents

Since mechanisms of intrinsic plasticity proceed through modulation of the electrochemical properties of neurons, it follows that this change is in turn modulated through activity-dependent alterations in the properties of ion channels in the neuronal membrane. This has been demonstrated to be the case with the A-type potassium channel following artificial LTP induction in rat hippocampal slices in-vitro (Breton & Stuart, 2009). Using patch-clamp recording, it was found that LTP-induced intrinsic plasticity was concomitant with a biphasic change in the current of A-type potassium channels. In the first phase, there was a rapid decrease in potassium current through the channel through a shifting of the inactivation curve, meaning that these channels were inactivated faster, rendering the neuron more excitable. This change only persisted for about 20 minutes, however, and rapidly returned to resting levels following this period. By then blocking clathrin-mediated endocytosis of these potassium channels using DYN, a potent inhibitor of endocytosis, it was shown that measures of intrinsic plasticity were inhibited in the neuron, suggesting that intrinsic plasticity beyond the 20 minute mark occurs via endocytosis of the A-type potassium channels. This mechanism is in some ways similar to AMPA receptor endocytosis in LTD, a post-synaptic mechanism of synaptic plasticity.


Bliss, T.V.P., & Lomo, T. (1973). Long-lasting potentiation of synaptic transmission in the dentate area anesthetized rabbit following stimulation of the perforant path. J. Physiol., 232, 331-56.

Brembs, B. (2003). Operant conditioning in invertebrates. Curr Opin Neurobiol., 13(6), 710-7.

Breton, J.D., & Stuart, G.J. (2009). Loss of sensory input increases the intrinsic excitability of layer 5 pyramidal neurons in rat barrel cortex. J. Physiol., 587(21), 5107-19.

Jones, N.G., Kemenes, I., Kemenes, G., & Benjamin, P.R. (2003). A persistent cellular change in a single modulatory neuron contributes to associative long-term memory. Curr Biol., 13(12), 1064-9.

Jung, S.C., & Hoffman, D.A. (2009). Biphasic somatic A-type K channel downregulation mediates intrinsic plasticity in hippocampal CA1 pyramidal neurons. Plos. One, 4(8), e6549.

Kemenes, I., Straub, V.A., Nikitin, E.S., Staras, K., O'Shea, M., Kemenes, G., & Benjamin, P.R. (2006). Role of delayed non-synaptic neuronal plasticity in long-term associative memory. Curr Biol., 16(13), 1269-79.

Kemenes, I., Kemenes, G., Andrew, R.J., Benjamin, P.R., & O'Shea, M. (2002). Critical time-window for NO-cGMP-dependent long-term memory formation after one-trial appetitive conditioning. J. Neurosci, 22(4), 1414-25.

Moyer, J.R., Thompson, L.T., & Disterhoft, J.F. (1996). Trace eyeblink conditioning increases CA1 excitability in a transient and learning-specific manner. J. Neurosci., 16(17), 5536-46.

Mozzachiodi, R., Lorenzetti, F.D., Baxter, D.A, & Byrne, J.H. (2008). Changes in neuronal excitability serve as a mechanism of long-term memory for operant conditioning. Nat Neurosci.,11(10), 1146-8.

Schreurs, B.G., Tomsic, D., Gusev, P.A., & Alkon, D.L. (1997). Dendritic excitability microzones and occluded long-term depression after classical conditioning of the rabbit's nictitating membrane response. J. Neurophysiol., 77(1), 86-92.

Woody, C.D., Black-Cleworth, P. (1973). Differences in excitability of cortical neurons as a function of motor projection in conditioned cats. J Neurophysiol., 36(6), 1104-16.