Numerical Simulation: Fluctuation in Background Synaptic Activity Regulates Synaptic Plasticity.

Synaptic plasticity is vital for learning and memory in the brain. It consists of long-term potentiation (LTP) and long-term depression (LTD). Spike frequency is one of the major components of synaptic plasticity in the brain, a noisy environment. Recently, we mathematically analyzed the frequency-dependent synaptic plasticity (FDP) in vivo and found that LTP is more likely to occur with an increase in the frequency of background synaptic activity. Meanwhile, previous studies suggest statistical fluctuation in the amplitude of background synaptic activity. Little is understood, however, about its contribution to synaptic plasticity. To address this issue, we performed numerical simulations of a calcium-based synapse model. Then, we found attenuation of the tendency to become LTD due to an increase in the fluctuation of background synaptic activity, leading to an enhancement of synaptic weight. Our result suggests that the fluctuation affects synaptic plasticity in the brain.

Sinking of Four Species of Living Diatom Cells Directly Observed by a "Tumbled" Optical Microscope.

The study of the sinking phenomenon of diatom cells, which have a slightly larger specific gravity (~1.3) compared to that of water, is an important research topic for understanding photosynthetic efficiency. In this study, we successfully demonstrated the observation of the sinking behaviors of four different species of diatom using a homemade "tumbled" optical microscope. A homemade 1 mm3 microchamber was employed to decrease the effects of convection currents. In the microchamber, diatom cells were basically settled in a linear manner without floating, although some of the cells were rotated during their sinking. Sinking speeds of the four species of diatom cells, Nitzschia sp., Pheodactylum tricornutum, Navicula sp., and Odontella aurita, were 0.81 ± 5.56, 3.03 ± 10.17, 3.29 ± 7.39, and 11.22 ± 21.42 µm/s, respectively, based on the automatic tracking analysis of the centroids of each cell. Manual analysis of a vector between two longitudinal ends of the cells (two-point analysis) was effective for quantitatively characterizing the rotation phenomenon; therefore, angles and angular velocities of rotating cells were well determined as a function of time. The effects of the cell shapes on sinking velocity could be explained by simulation analysis using the modified Stokes' law proposed by Miklasz et al.