Figure 8. | Nanoconnectomic upper bound on the variability of synaptic plasticity

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Nanoconnectomic upper bound on the variability of synaptic plasticity

Figure 8.

Affiliation details

Howard Hughes Medical Institute, Salk Institute for Biological Studies, United States; Massachusetts Institute of Technology, United States; The University of Texas at Austin, United States; University of California, San Diego, United States
Figure 8.
Download figureOpen in new tabFigure 8. Distinguishable spine sizes.

Over the factor of 60 range in spine head volumes from the data set there are 26 distinguishable intervals of spine sizes with a discrimination probability of 69% for each interval based on signal detection theory (Green and Swets, 1966; Schultz, 2007). The graph illustrates how distinct Gaussian distributions of spine sizes, each with a certain mean size and standard deviation, covers the entire range of spine head sizes on a log scale. The CV of each distribution is a constant value of 0.083 (Figure 5) and the intervals are spaced to achieve a total of 31% overlap with adjacent intervals giving a 69% discrimination threshold (see Materials and Methods). Note that the constant CV observed in the data set (Figure 5) means that the intervals appear uniform in width and spacing on a logarithmic scale. This is a form of non-uniform quantization which efficiently encodes the dynamic range of synaptic strengths at constant precision.