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**Dynamics of NT release Synaptic Plasticity**

Historical overview: Hebb's rule of association. Marr's theories of associative memory. The discovery of LTP. Cooperative effects and the verification of Hebb's postulate. Presynaptic, non-associative changes in synaptic strength: Short-term 'facilitation', 'augmentation', 'potentiation' and 'depression' of transmitter release. The effects of differences in resting values of 'p' on synaptic dynamics. Associative Long-term potentiation (LTP) and depression (LTD) and the BCM theory for synaptic strengthening & weakening. Induction and expression mechanisms. Multiple forms ('early' vs. 'late'). Spike timing dependent plasticity. Metaplasticity. Synaptic tagging. Other forms of synaptic plasticity: changes in vesicular filling, transmitter reuptake, postsynaptic excitability, ion gradients. Lack of LTP/LTD in interneurons. Evidence for a role in learning.

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**Hebb's principle of associative learning (1949):**

"Whenever an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency as one of the cells firing B is increased" 'Neurons that fire together wire together'

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Between 1968 and 1971, David Marr published the first series of theoretical papers that attempted to interpret the anatomical connections and known physiology of specific brain structures (cerebellum, hippocampus, neocortex) in terms of associative memory systems using Hebb's rule. He made numerous specific predictions about the physiological properties of these nets that have since been verified

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In 1973, Bliss, Lomo & Gardner- Medwin published two papers in which they reported that a "long-lasting potentiation" of hippocampal synapses could be induced by "tetanic" (i.e., high frequency) stimulation. These may be the most highly cited papers in neuroscience. The original observation was made in about 1969 by Lomo, who published a brief abstract in 1971. In their conclusion, the authors suggested several possible mechanisms for the enhanced EPSP, including increased transmitter release, an increase in post-synaptic sensitivity and a decrease in the stem resistance of dendritic spines. The debate about this continued for the next 25 years. Surprisingly, there was no mention of Hebb or his neurophysiological postulate for associative memory

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If we define synaptic efficacy as the effectiveness of a synapse in generating an output from the postsynaptic cell, how might synaptic efficacy be modified, and what are the computational consequences of the proposed mechanisms? Some possibilities: * Formation (or elimination) of synaptic contacts * Changes in transmitter release parameters (n, p) * Changes in the amount of transmitter in a vesicle * Changes in transmitter reuptake or inactivation mechanisms * Changes in receptor number, distribution, type or sensitivity * Changes in local postsynaptic active channels (e.g., gCaV) * Changes in dendritic spine size and/or shape * Changes in the global excitability of the postsynaptic cell * Changes in ionic gradients (equilibrium potentials) * Changes in the propagation of action potentials into terminals * Changes in the burst characteristics of the presynaptic neuron

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**Presynaptic changes in efficacy**

m = n x p N=number of vesicles p= release prob. Transmitter release fluctuates probabilistically, but the mean number of quanta released is equal to the probability that a given quantum is released (assumed uniform and constant in simple case) and the number of quanta that are available for release (also assumed uniform and constant in simple case). Two different types of synapses can have the same mean release, but different values of n and p. Such differences contribute to the dynamic properties of synapses during repeated activation, because both p and n are dynamic quantities.

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n p m = n x p Transmitter release fluctuates probabilistically, but the mean number of quanta released is equal to the probability that a given quantum is released (assumed uniform and constant in simple case) and the number of quanta that are available for release (also assumed uniform and constant in simple case). Two different types of synapses can have the same mean release, but different values of n and p. Such differences contribute to the dynamic properties of synapses during repeated activation, because both p and n are dynamic quantities. A major variable that determines release probability is Ca entry into the terminal via voltage gated Ca channels that are activated by Na/K action potentials. Ca entry is dependent on external calcium concentration. Release probability is related to the fourth power of the Ca concentration. Also, as shown on the right, this fourth order relationship means that any residual calcium in the terminal that has not yet been removed since the preceeding impulse (s1) can have a profound effect on the next response (s2).

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**n p Presynaptic facilitation and depression**

When an axon at rest is fired twice in succession, the synaptic output on the second response can be either larger or smaller than the first depending on initial conditions. Given that m = n x p, where both n and p are variable, a variety of outcomes are possible. In general, immediately after the first response, the available quanta (n) are reduced by a factor m. The slow recovery of n is the basis for presynaptic depression. Residual calcium on the other, and its multi-compartment buffering, leads to transient elevations in p. The m on the second response depends on these changed values of n and p. n p Relative change in m = n x p Interaction of facilitation and depression: After a single stimuls, p (green) is transiently incremented but returns quickly to its rest value as the Ca transient dissipates. n (blue) recovers slowly. The relative time constants are about 150 msec vs 1500 msec and are quite consistent in most synapses in brain or muscle. The relative change in the size of the second response during paired stimuli is a function of p, n, and the increment in p. Shown in red is the fractional change in mean quantal release. Extrapolation of the slow depression component after the recovery of p to zero provides a good estimate of p0.

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Augmentation Many synapses, including some in the hippocampus exhibit a more prolonged increase in transmitter release probability following a brief episode of high frequency activation. The increase decays as a two component exponential with time constants of about 5 sec and about 90 sec. These two components are referred to as 'augmentation' and 'potentiation'. If paired stimuli (25 msec apart) are given during this time, there is an increase in relative synaptic depression, consistent with the conclusion that augmentation and potentiation involve an increase in p. Other studies indicate the existence of two components is due to the presence of two different pathways for elimination of residual calcium

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Plot of the relative magnitudes of P1 and P2 (f%) as a function of the relative magnitude of P1 (DV) after induction of Augmentation and Potentation by a high frequency stimulus. Consistent with the hypothesis that the slow change is due to an increase in p, the greater the initial size the greater is the relative depression.

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If few inputs are stimulated together at high frequency, only short-term changes (augmentation and potentiation) are observed (see previous slide); however, if many inputs are stimulated together at high frequency (vertical tick mark), then both short-term and long-term (LTP) changes take place. That these processes work through separate mechanisms was shown by giving stimulus pairs (P1, P2) at low rate (every 2 sec) and observing how the relationship between the two responses varies as a function of time after LTP is induced by stimulating many axons at high frequency. After the short-term changes decay out, there is still LTP, but the increased depression is gone. Note that after a few min, the P1-P2 relationship recovers to the pre LTP induction level, but their absolute size has been increased. Thus, LTP is not due to an increase in p at these synapses. (A, P1 vs time; B, P2 vs time; C, the relative difference between P1 and P2 vs time)

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**Summary of factors affecting neurotransmitter release dynamics:**

Transmitter release probability fluctuates according to the 4th power of internal calcium ion concentration near the release site. After a single action potential, the initial surge of transmitter release that gives rise to the synaptic potential is due to a very localized high Ca++ concentration near the release site. It takes about 100 msec for the Ca++ to equilibrate in the terminal. During this time there is a transient increase in release probability due to a residual local increase in Ca++. This process has been called “facilitation”. After many impulses at high frequency, the accumulation of Ca++ within the terminal after the equilibration phase becomes significant and contributes to a slowly (2-5 min) decaying increase in release probability. Because the Ca++ in the terminal is removed by two different mechanisms, with different rate constants, there appear to be two components to the exponential decay of the increase in p. These components have been called “augmentation” (3-5 sec) and “potentation” (2-5 min). After a release event, there is a depletion of n, the number of quanta available for release (“depression”) whose magnitude immediately after the event is exactly proportional to the initial value of p. The magnitude of n recovers exponentially over about 3 sec. CAVEAT: The foregoing statements are a reasonable description for a single synapse with large n and moderate to small p, or for studies on large populations of synapses in which n may small (1 or 2) at individual synapses, but very large in the collection. When single synapses with small n are studied, the recovery process appears all-or-none and the probability that the release site has recovered approaches 1 exponentially over about 3 sec. Averaging the results from such a synapse over many trials would give the same result as a single trial in the many synapse case.

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