Multiplex Networks of Cortical and Hippocampal Neurons Revealed at Different Timescales

Recent studies have emphasized the importance of multiplex networks – interdependent networks with shared nodes and different types of connections – in systems primarily outside of neuroscience. Though the multiplex properties of networks are frequently not considered, most networks are actually multiplex networks and the multiplex specific features of networks can greatly affect network behavior (e.g. fault tolerance). Thus, the study of networks of neurons could potentially be greatly enhanced using a multiplex perspective. Given the wide range of temporally dependent rhythms and phenomena present in neural systems, we chose to examine multiplex networks of individual neurons with time scale dependent connections. To study these networks, we used transfer entropy – an information theoretic quantity that can be used to measure linear and nonlinear interactions – to systematically measure the connectivity between individual neurons at different time scales in cortical and hippocampal slice cultures. We recorded the spiking activity of almost 12,000 neurons across 60 tissue samples using a 512-electrode array with 60 micrometer inter-electrode spacing and 50 microsecond temporal resolution. To the best of our knowledge, this preparation and recording method represents a superior combination of number of recorded neurons and temporal and spatial recording resolutions to any currently available in vivo system. We found that highly connected neurons (“hubs”) were localized to certain time scales, which, we hypothesize, increases the fault tolerance of the network. Conversely, a large proportion of non-hub neurons were not localized to certain time scales. In addition, we found that long and short time scale connectivity was uncorrelated. Finally, we found that long time scale networks were significantly less modular and more disassortative than short time scale networks in both tissue types. As far as we are aware, this analysis represents the first systematic study of temporally dependent multiplex networks among individual neurons.     

Continuous-flow ATP amplification system for increasing the sensitivity of quantitative bioluminescence assay

We constructed a novel ATP amplification reactor using a continuous-flow system, and this allowed us to increase the sensitivity of a quantitative bioluminescence assay by controlling the number of ATP amplification cycles. We previously developed a bioluminescence assay coupled with ATP amplification using a batch system. However, it was difficult to control the number of amplification cycles. In this study, ATP amplification was performed using a continuous-flow system, and significant linear correlations between amplified luminescence and initial ATP concentration were observed. When performing four cycles of continuous-flow ATP amplification, the gradient of amplification was 1.87^N. Whereas the lower quantifiable level was 500 pM without amplification, values as low as 50 pM ATP could be measured after amplification. The sensitivity thus increased 10-fold, with further improvements expected with additional amplification cycles. The continuous-flow system thus effectively increased the sensitivity of the quantitative bioluminescence assay.