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I have been reading with fascination about the several molecular- and cellular-scale mechanisms and structural changes that underlie what we refer to as long-term plasticity. For instance, [1], [2], [3].

In particular, there seem to be at least: synaptic scaling, synaptic pruning, synaptogenesis, spinogenesis, neurogenesis.

My questions:

  1. How do each of the above mechanisms/ events affect the classical extracellular single/ multi-unit spikes, postsynaptic potentials (LFPs), and local electric fields? Does a mechanistic forward model exist, which specifies the biophysical transformation from synapse-level changes to spikes and LFPs? Are there spike simulators out there that model these properties?

  2. Using such a forward model, can we solve a statistical inverse problem to infer anything at all about these LTP/LTD-induced small-scale structural and functional changes?

  3. For instance, one metric of analysis could be: post-spike-time filters (self-terms and cross-terms) inferred using statistical point-process models. Another could be the shape of the action potential itself, which is typically used only for spike sorting, and then discarded.

  4. Has something along these lines been done? Or is it infeasible? If so, why?

  5. Finally, If anyone could give a brief overview of the gamut of synapse-scale physiological/ imaging techniques used to characterize these mechanisms, I would be very grateful!

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this is a pretty broad question. I can answer parts of it, but it would be insufficient overall. If you can break the question down to smaller chunks, you may get better responses. –  Memming Feb 14 '13 at 16:25
    
Thanks Memming. I need to do some more reading and thinking to break down the question. Will do. Feel free to share some thoughts in the mean time. –  Pavan Ramkumar Feb 15 '13 at 5:56

2 Answers 2

Just adding a little bit here. Estimating changes in connectivity based on STDP is hard http://klab.smpp.northwestern.edu/wiki/images/2/2b/Stevenson_Inferring_Plasticity_2011.pdf

but yes - these questions are enough to keep a big field busy for a long time.

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Thanks!

I was thinking along the following lines.

(1) Write down the cable equations for neurons within a network, given: anatomical layout of the network, spatial distribution of dendrites, spines, synapses, and synaptic strengths (forward model).

(2) Acquire joint microscopy + electrophysiology dataset.

(3) Invert the forward model with synaptic strengths as free parameters.

(4) Track these inferred parameters over time or compare them between conditions.

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Yes, that could be a strategy. I like your idea. But, you'll need to record from pairs of connected cells intracellularly which is not impossible, but limits long stable recordings. I guess imaging techniques may be able to get over this limit. –  Memming Feb 22 '13 at 14:17

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