Yuichiro Yada

State-Dependent Propagation of Neuronal Sub-Population in Spontaneous Synchronized Bursts

Repeating stable spatiotemporal patterns emerge in synchronized spontaneous activity in neuronal networks. The repertoire of such patterns can serve as memory, or a reservoir of information, in a neuronal network; moreover, the variety of patterns may represent the network memory capacity. However, a neuronal substrate for producing a repertoire of patterns in synchronization remains elusive. We herein hypothesize that state-dependent propagation of a neuronal sub-population is the key mechanism. By combining high-resolution measurement with a 4096-channel complementary metal-oxide semiconductor (CMOS) microelectrode array (MEA) and dimensionality reduction with non-negative matrix factorization (NMF), we investigated synchronized bursts of dissociated rat cortical neurons at approximately 3 weeks in vitro. We found that bursts had a repertoire of repeating spatiotemporal patterns, and different patterns shared a partially similar sequence of sub-population, supporting the idea of sequential structure of neuronal sub-populations during synchronized activity. We additionally found that similar spatiotemporal patterns tended to appear successively and periodically, suggesting a state-dependent fluctuation of propagation, which has been overlooked in existing literature. Thus, such a state-dependent property within the sequential sub-population structure is a plausible neural substrate for performing a repertoire of stable patterns during synchronized activity.

Development of neural population activity toward self-organized criticality

Self-organized criticality (SoC), a spontaneous dynamic state established and maintained in networks of moderate complexity, is a universal characteristic of neural systems. Such systems produce cascades of spontaneous activity that are typically characterized by power-law distributions and rich, stable spatiotemporal patterns (i.e., neuronal avalanches). Since the dynamics of the critical state confer advantages in information processing within neuronal networks, it is of great interest to determine how criticality emerges during development. One possible mechanism is developmental, and includes axonal elongation during synaptogenesis and subsequent synaptic pruning in combination with the maturation of GABAergic inhibition (i.e., the integration then fragmentation process). Because experimental evidence for this mechanism remains inconclusive, we studied the developmental variation of neuronal avalanches in dissociated cortical neurons using high-density complementary metal-oxide semiconductor (CMOS) microelectrode arrays (MEAs). The spontaneous activities of nine cultures were monitored using CMOS MEAs from 4 to 30days in vitro (DIV) at single-cell spatial resolution. While cells were immature, cultures demonstrated random-like patterns of activity and an exponential avalanche size distribution; this distribution was followed by a bimodal distribution, and finally a power-law-like distribution. The bimodal distribution was associated with a large-scale avalanche with a homogeneous spatiotemporal pattern, while the subsequent power-law distribution was associated with diverse patterns. These results suggest that the SoC emerges through a two-step process: the integration process accompanying the characteristic large-scale avalanche and the fragmentation process associated with diverse middle-size avalanches.

Identification of diverse synchrony patterns in dissociated cortical culture using Bayesian non-negative matrix factorization

Synchrony in a neuronal network is not just a spontaneous event but rather a representation of inner information. In this point of view, the variety of synchrony patterns is considered to be related to inner capacity of the network. However, evaluating and comparing the variety of synchrony patterns, especially between different samples or different times, is difficult. In this paper, we proposed to identify the variety of synchrony based on Bayesian model selection. Hypothesizing that globally synchronized activity consists of partial synchrony, we attempted to identify reproducible-spatial pattern bases in spontaneous bursting activities of dissociated cortical cultures using Bayesian non-negative matrix factorization. Neuronal activity was recorded with high-density CMOS electrode arrays. Bayesian treatment provides evidence for selection of the number of bases based on marginal likelihood. We compared model evidence of the activity in juvenile and matured cultures. Our results suggested that the variety of synchrony patterns diversify through maturation.

Use of retroreflector and multi-zeros optical beam for remote monitoring of lateral deformation

In previous paper, we described a principle of free-space optical measurement system for monitoring full-axis (three translational and three rotational) deformation of large and long structures such as bridges, roads, and highways. Accurate full-axis deformation sensing enables progressive displacement measurement for chain of nodes. In this paper, we specialize proposed system in two node lateral displacement detection using retroreflector at remote node. In this system, a remote node consists of only passive element without any power supply or moving parts, so that a remote node can be implemented into a small size and breakdown free stable system. Therefore, it is especially appropriate for severe environment such as nuclear reactor or blast furnace.