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Optical approaches to synaptic plasticity: From unitary events to learning rules

Optical approaches to synaptic plasticity: From unitary events to learning rules. Sam Wang Princeton University. Laboratory of Sam Wang. Optical physiology and synaptic plasticity: Shari Gelber Bernd Kuhn Daniel O’Connor Ilker Ozden Dmitry Sarkisov Shy Shoham Megan Sullivan

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Optical approaches to synaptic plasticity: From unitary events to learning rules

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  1. Optical approaches to synaptic plasticity: From unitary events to learning rules Sam Wang Princeton University

  2. Laboratory of Sam Wang Optical physiology and synaptic plasticity: Shari Gelber Bernd Kuhn Daniel O’Connor Ilker Ozden Dmitry Sarkisov Shy Shoham Megan Sullivan Gayle Wittenberg Brain scaling and evolution: Mark Burish Damon Clark Kim Hatch Harrison Aline Johnson Jennifer Shultz Pat Tanapat Matt Wagers Krysta Wyatt

  3. Learning rules: from single synapses to STDP • The hippocampal CA3-CA1 synapse • Multiphoton optical approaches: imaging and uncaging

  4. CA3-CA1 synapse of hippocampus Rich history of extracellular and single-cell recording The cell biology and plasticity literature is vast One synapse per connection Has AMPA, NMDA, mGluR,…

  5. Plasticity is usually measured across many synapses… …what are its properties at single synapses? 30,000 synapses

  6. Delivery of glutamate receptors

  7. Calmodulin-dependent protein kinase II: a molecular switch J. Lisman, H. Schulman, and H. Cline (2002) Nature Rev. Neurosci. 3:175

  8. Plasticity events are single steps occurring at distributed times

  9. Plasticity in single steps

  10. Simulated plasticity events Real plasticity data

  11. Potentiation and depression are symmetrically-sized events

  12. The distribution of unitary events can account for the time course of plasticity

  13. Unitary properties of plasticity at CA3-CA1 synapses All-or-none Single steps up and down Steps are of similar size

  14. Learning Rules Presynaptic Neuron Postsynaptic Neuron A B Spike Times from Neuron A + Spike Times from Neuron B + Learning Rule = Expected Synaptic Plasticity

  15. Different Synapses, Different Learning Rules Abbott and Nelson Nat. Neurosci. 2000

  16. CA3-CA1 synaptic plasticity: a vast literature Any new learning rule measured here should be consistent with this large body of previous work.

  17. Questions at the CA3-CA1 synapse • Can we separate bidirectional learning rules into specific requirements for potentiation and depression? • Can we resolve STDP with previous whole-cell and field recording studies at this synapse? • How might the learning rule map to behavior?

  18. Plasticity at CA3-CA1: a separable process?

  19. LTD and LTP are separable

  20. STDP studies at CA3-CA1 have yielded conflicting results In cultured neurons: Causal pairings lead to LTP Bi and Poo 1999 60 total pairings at 1 Hz In CA3-CA1 brain slice: Causal pairings: Pike et al. 1999 40 total pairings at 5 Hz Christie et al. 1996 900 total pairings at 3 Hz …no change. …LTD.

  21. Causal pairing fails to induce LTP Single EPSPs before single APs 70-200 pairings with Dt=0-10 ms (pre before post) Pairing frequency 0.1-5 Hz

  22. If causal parings lead to LTD, could this explain why low-frequency stimulation induces LTD? • Low frequency stimulation either causes cell to spike or doesn’t • If cell is held at -70 mV, LFS does not result in LTD • If cell doesn’t spike, LFS does not result in LTD (Christie and Johnston 96)

  23. Spike timings during an LTD protocol are causal

  24. STDP rule I:Pairing single pre- and post-synaptic spikes

  25. What are the conditions for LTP?

  26. Field recording studies suggest bursts and theta frequency Patterned presynaptic stimulation studies: LTP Pre APs 0.2 sec 100 Hz No Plasticity Pre APs 2 sec 100 Hz No Plasticity Pre APs 100 Hz Rose and Dunwiddie 1986, Larson and Lynch 1986, 1989

  27. LTP induction requires postsynaptic bursting Pairings of EPSP with postsynaptic bursts of two APs spaced 10 ms apart 100 pairings at 5 Hz EPSP 0-10 ms before first AP

  28. Dt Spike timing dependent LTP is frequency-dependent • Potentiation requires postsynaptic bursts • Pairings are effective at 5 Hz (near theta) • …can LTD be induced by reversing the pairing order?

  29. 10 ms LTD occurs when pairing order is reversed Pairings of EPSP with postsynaptic bursts of two APs spaced 10 ms apart 100 pairings at 5 Hz EPSP 10-20 ms after first AP n=6

  30. STDP rule II:With postsynaptic bursts

  31. Can we find conditions that lead to an LTP-only rule?

  32. LTP requires fewer pairings than LTD Reduce number of pairings to 30. LTP is observed; LTD is not.

  33. 30 vs. 100 pairings 30 pairings (black circles) 100 pairings (gray circles) Causal: EPSP 2-20 ms before 1st AP Anti-Causal: EPSP 2-20 ms after second AP 30 100 30 100 … by decreasing number of pairings we should observe an LTP-only rule.

  34. The Potentiation Rule • Is narrow in time • Requires causal pairings • Requires postsynaptic bursts • Requires high frequency pairings • Few pairings still lead to LTP The Depression Rule • Is broad in its timing dependence • Requires many pairings • Has no strong requirement for • frequency or bursting

  35. Bidirectional plasticity In regions of parameter space that satisfy criteria for both LTP and LTD, a bidirectional rule will be measured. However, this is not a unique rule for the synapse. STDP is just one slice taken through a high-dimensional parameter space.

  36. What do multiple STDP rules mean for the animal? LTP rule appears well matched to in vivo recordings What about LTD? Can LTD be induced with the number of action potentials fired during one pass through a place field? Is the concept of “one-shot learning” specific to LTP? What about other behavioral states like various phases of sleep?

  37. What’s Next? Why not continue to explore parameter space exhaustively? …because it’s exhausting!

  38. Manipulating biochemistry with caged compounds Furuta, Wang et al. (1999) PNAS 96:1193 Pettit, Wang et al. (1997) Neuron 19:465

  39. Uncaging in spatial patterns Resolution: <1 micron 30,000 locations per second Shy Shoham

  40. Simulating presynaptic stimulation with glutamate uncaging • Enables us to further dissect learning • rules into: • Plasticity at individual synapses • To have greater control teasing apart • spatial effects • Can study many synapses at once which • should speed exploration of the many • parameters of learning rules.

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