Postsynaptic currents

There are several experiments you can do that utilize PSCs; synapse number, silent synapses, excitatory/inhibitory ratio, synaptic multiplicity, and changes in synaptic release regulated by other non-ionic receptors. One important thing to note is that PSCs and PSPs are not the same. PSPs are dependent on the cells capacitance and change with membrane voltage.

Miniature postsynaptic currents (mPSCs)¶

Recording and analyzing mininaturen postsynaptic currents (mPSCs) is one of the most common experiments in patch clamp electrophysiology. Less common but still useful are mininature postsynaptic potentials. Miniature postsynaptic currents or potentials (mini’s) are quantal events that are ionic postsynaptic currents/potentials evoked from the release of a single synaptic vesicle in a probablistic manner. Quantal events were discovered in the neuromuscular junction where the experimenters found that even if you continuous changed the stimulus you would only get discrete changes the postsynaptic potentials Del Castillo & Katz, 1954. These discrete events happen because a low stimulus only a single synaptic vesicle is released then you keep increasing the stimulus until you get two synaptic vesicle are released and so on. We typically use TTX to isolate minis rather than electrical stimulus since most of us do not record at the neuromuscular junction. TTX was first discovered to “isolate” quantal events in the neuromuscular junction about 10 years later Elmqvist & Feldman, 1965. It looks almost 25 years until someone showed that quantal transmission occured in the mammalian CNS Brown et al., 1979.

Frequency of mPSCs is used as a proxy for the number of functional synapses (synapses that have presynaptic input) that contain the receptor of interest (but not necessarily the number of synapses). The interpretation of mPSC data depends on what receptor you are recording from. If you are recording mEPSCs from AMPARs then you are likely getting the number of “active” or “non-silent” synapses (i.e. the number of presynaptic elements that have a postsynaptic elements with the receptor you are interested in). If you are recording NMDARs you will get the number of synapses with NMDAR receptors some of which may be silent. If you are recording mIPSCs then you are getting the number of inhibitory synapses. With mIPSCs you could be getting GABAAR or GlyR unlees you block one or the other. One important caveat of mPSCs is that you are not getting where the presynaptic input is coming from. If you want projection specific synaptic input you need to run a different type of experiment than we will be covering in a later chapter.

Interpreting mPSCs¶

There are several important features of mPSCs that you will want to analyze: frequency, amplitude and rise rate and the decay rate.

Frequency¶

PSC frequency is used as a proxy for the number of synapses that contain the receptor whose currents you are recording. The more mPSCs, the more synapses. However, if there are changes in release probability you could also get a change in frequency without a change in synapse number. To determine whether there are changes in release probability you will need to run some pair-pulse (PPR) experiments which are described in a later chapter. One caveat with PPR is that it is calcium dependent release, where spontaneous release in several excitatory, but not inhibitory, synapses is calcium-independent Williams & Smith, 2018. You may get reviewers who push back against mEPSC data without a subsequent PPR experiment but we may not even be testing the same synaptic release mechanism.

Amplitude¶

Another feature is PSC amplitude. A larger amplitude could mean two things. Larger mPSCs could mean there are more receptors at the postsynaptic element (thus a larger current). Alternatively, larger mPSC amplitude could mean that you get less distal synapses due to decreased dendritic length or more synapses close to the cell body with no change in dendritic length. More distal mPSCs should have a slower rise rate due to dendritic lowpass filtering. Lastly, you can look at the tau or decay rate of the mPSC. Changes in tau are usually due to changes in receptor subunit composition. Tau is especially useful when you need to identify specific cells types. Interneurons, like parvalbumin interneurons, have a very short mPESC tau compared to pyramidal neurons. Tau can also be affected by dendritic filtering.

Distribution of the data.¶

Lastly, most of the raw, cell level data you get from mPSCs will be lognormal, exponential or gamma distributed. Rarely will you get normally distributed data. This has big implication for downstream analysis. For example the mean of a lognormal distribution is just the geometric mean: 10**np.mean(np.log10(data)). If your data is gamma distributed then log transforming with just skew the data in opposite direction which makes it much harder to get good measure of central tendency, however a square root transform also works well. If you want to learn more about distributions check out the distributions chapter.

Why do postsynaptic currents look they way they do?¶

Postsynaptic currents have a very specific shape. This shape can modeled by multiplying two exponentials of opposite direction together (subtract one exponential from 1). This shape allows PSCs to act as coincidence detectors. The sharp rise allows PSCs to be temporally precise. The long decay allows PSCs to overlap in time and summate to drive an action potential. The shorter the decay the shorter the time window PSCs have to summate. Different cells and different PSC types have different rise rates and decay rates. PV interneurons have very “fast” excitatory currents which means they need very tightly synchronized synaptic input. Pyramidal cell have “slower” excitatory currents which means they can summate input over a longer period of time. Inhibitory currents (at least on pyramidal cells) tend to be very slow.

Reversal potential¶

Synpatic currents have a reversal potentiall that is important for how they function in-vivo. The reversal potential is the membrane voltage at which the ionic potential is equation due do equal distribution of the ion of interest. For Na+, the reversal potential is close to 0 mV. The reversal potential effects the ability of a neuron to change the membrane voltage. The closer the reversal potential the less effect the ionic current will have on the membrane voltage since.

Where to learn more¶

The best book I have read on this subject is by Biophysics of Computation(Koch (1998)) if you want an in-depth mathematic explanation of synaptic function.