Virtual laboratory / Proteins and synapses
Synaptic plasticity in hippocampal slices
Field EPSPs at CA3 to CA1 synapses, the induction of long-term potentiation or depression, and a test of its dependence on NMDA receptors.
Guided experiment: Long-term potentiation in a hippocampal slice.
Synaptic plasticity in hippocampal slices
Field recordings in hippocampal slices measure synaptic transmission from many synapses at once: stimulating the Schaffer collateral axons from CA3 evokes a presynaptic fibre volley and a negative-going field excitatory postsynaptic potential (fEPSP) in stratum radiatum of CA1, whose initial slope reflects synaptic strength. In a classic study in anaesthetised rabbits, brief conditioning trains to the perforant path potentiated the population response of the dentate gyrus for between 30 minutes and 10 hours (Bliss and Lømo, 1973). In rat hippocampal slices, the NMDA-receptor antagonist APV left the Schaffer collateral fEPSP unchanged but prevented the potentiation evoked by high-frequency stimulation (Collingridge et al., 1983), and the same antagonist (AP5 is another name for APV), infused chronically into the cerebral ventricles, suppressed potentiation in vivo and impaired place learning without affecting visual discrimination learning (Morris et al., 1986). Paired pulses probe presynaptic release, whose short-term dynamics can be described by models in which depression depends on release probability (Tsodyks and Markram, 1997).
Design the experiment
Questions to investigate
- Does one train of high-frequency stimulation produce lasting potentiation in control slices, and how much of it decays during the hour?
- Does AP5 prevent the induction of potentiation while leaving baseline transmission and the paired-pulse ratio essentially unchanged?
- Raise or lower the release probability. How does the paired-pulse ratio change, and why does it change with release probability?
- Run low-frequency stimulation, and a time control without conditioning. Which changes exceed slow drift?
- How many animals are needed for a clear answer, and how misleading is it to count slices as independent replicates?
- Change the exclusion criteria. How many slices are lost, and could unequal exclusion bias the comparison?
In a real laboratory
Transverse hippocampal slices, 350–400 µm thick, are cut on a vibratome into ice-cold oxygenated solution and recover for at least an hour in artificial cerebrospinal fluid (ACSF) bubbled with 95% O2 and 5% CO2. In a chamber perfused at 30–32 °C, a stimulating electrode in stratum radiatum activates the Schaffer collaterals, and a glass electrode records the field potential in stratum radiatum of CA1. Each slice is characterised by an input–output curve and paired pulses, the test intensity is set to a fraction of the maximal response, and a stable baseline of at least 20 minutes precedes induction. Exclusion criteria are written down in advance. Drug and control experiments are interleaved in random order, solutions are coded where possible, and both the number of slices and the number of animals are reported, with the animal as the unit of analysis. The work requires approval by an Institutional Animal Ethics Committee (in India, under the CCSEA and the Prevention of Cruelty to Animals Act 1960; elsewhere, the equivalent national body); taking several slices from each animal reduces the number of animals.
How the simulation works
Each sweep is a waveform sampled at 20 kHz: a stimulus artefact, a fibre volley that grows as a sigmoid function of stimulus intensity, and an fEPSP, with filtered recording noise and sweep-to-sweep variability. The slope is measured as in a laboratory, by a straight-line fit between the 10% and 90% points of the initial negative-going phase, and is reported as a positive number in mV/ms. For the time course the window is set on the average of the baseline sweeps and applied to every sweep; single sweeps measured with their own window underestimate small, noisy slopes. At 20 ms the decaying first response slightly reduces the second slope, as in real recordings. Paired-pulse ratios follow an extension of the Tsodyks–Markram model that adds facilitation. Long-term change follows a calcium rule: calcium enters through NMDA receptors, which AP5 blocks by 95%; a weak signal gives no change, an intermediate one depression and a strong one potentiation, which partly decays over tens of minutes. A short post-tetanic potentiation, independent of NMDA receptors, follows high-frequency trains. Slices and animals differ in response size, recruitment, potentiation and drift, and some slices are unhealthy. All values are approximate; the AP5 concentration (50 µM), the ACSF recipe and the stimulation parameters are typical laboratory values, not taken from the cited studies. Population spikes, inhibition, slice temperature, age and the late, protein-synthesis-dependent phase of LTP are not simulated.
- Bliss, T. V., & Lømo, T. (1973). Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. Journal of Physiology, 232(2), 331–356. https://doi.org/10.1113/jphysiol.1973.sp010273
- Collingridge, G. L., Kehl, S. J., & McLennan, H. (1983). Excitatory amino acids in synaptic transmission in the Schaffer collateral-commissural pathway of the rat hippocampus. Journal of Physiology, 334, 33–46. https://doi.org/10.1113/jphysiol.1983.sp014478
- Morris, R. G., Anderson, E., Lynch, G. S., & Baudry, M. (1986). Selective impairment of learning and blockade of long-term potentiation by an N-methyl-D-aspartate receptor antagonist, AP5. Nature, 319(6056), 774–776. https://doi.org/10.1038/319774a0
- Tsodyks, M. V., & Markram, H. (1997). The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability. Proceedings of the National Academy of Sciences of the USA, 94(2), 719–723. https://doi.org/10.1073/pnas.94.2.719
About the simulations
Each simulator is a simplified version of a published model of cells, signals, instruments or behaviour, and runs in the web browser. The simulations show how the techniques work and how design choices change the results; they do not replace training in a laboratory.
All data are simulated and generated afresh on each run, so results vary between runs, as in real experiments. Nothing is stored or sent: designs and results are lost when the page is closed, unless the protocol is copied or the data file is downloaded.
Last updated