Mean Squared Displacement
Finding the MSD (not a trivial task) of the simulation was done using a Matlab toolbox. The target extrasynaptic MSD was 0.1 µm²⁄s (from Choquet FIG: {{#info: 
{{{2}}} CLICK AWAY FROM IMAGE TO CLOSE }}). Given this target MSD, scaling the model to real-world values is then a 2-step process. First, the randomly generated step-size was scaled to produce an MSD of 0.1 Units²⁄step. Second, the dimentions of the model was scaled to make 0.1 Units²⁄step ≈ 0.1 µm²⁄s. It was found that an XY random step-size of µ=0.5 (σ=.2) units produced an MSE ≈ 0.1 Units²⁄step. Then, the 0.5 arbitrary units was given meaning (converted to 0.5 µm) by scaling the model according to real-world values: the PSD areas were set to a 3-unit (.3 µm) diameter, 20 units (2 µm) apart, within a rectangular field 20 units (2 µm) wide and 60 units (6 µm) long. Thus, a particle with an XY step-size of µ=0.5 moving in a straight line, could theoretically go from PSD1 to PSD2 in ≈ 4 steps.
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MEAN SQUARED DISPLACEMENT
- Brownian Motion Mean Squared Displacement
- The goal of this calculation is to relate the simulated particle diffusion to real world values, namely velocity.
- Particle velocity will be a function of MSD x units ²⁄s which scales on space (units) and time (s) parameters.
- Space and time in the model are defined arbitrarily as Step_Size and Step where each Step a particle moves a distance randomly chosen from a normal distribution (µ=1,σ=.2)
- a step size of 1 unit/step will produce a brownian motion MSD of ~0.52 ±0.2 units ²/s
- empirical observations show that reasonable values for MSD are:
- PSD 0.01 µm ²/s
- synaptic 0.05 µm ²/s
- extrasynaptic 0.1 µm ²/s
- given an MSD of 0.52 ±0.2 units ²/s at the current parameters: 1 step = 1 unit (at µ=1,σ=.2), the model will need to be scaled such that particles move at an extrasynaptic rate of 0.1 µm ²/s.
- spines are on average 1 to 10 µm apart, if the model is comparing two spines 1 µm apart, they should be separated by 5 units of model space. This is because the current particle diffusion rate of the model is .5 µm ²/s and the empirical MSD is .1 µm ²/s
Michalet • 2010 • Phys Rev E Stat Nonlin Soft Matter Phys - PDF
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We examine the capability of mean square displacement analysis to extract reliable values of the diffusion coefficient D of single particle undergoing Brownian motion in an isotropic medium in the presence of localization uncertainty. The theoretical results, supported by simulations, show that a simple unweighted least square fit of the MSD curve can provide the best estimate of D provided an optimal number of MSD points is used for the fit. We discuss the practical implications of these results for data analysis in single-particle tracking experiments.