Highly-integrable analogue reservoir circuits based on a simple cycle architecture.

Physical reservoir computing is a promising solution for accelerating artificial intelligence (AI) computations. Various physical systems that exhibit nonlinear and fading-memory properties have been proposed as physical reservoirs. Highly-integrable physical reservoirs, particularly for edge AI computing, has a strong demand. However, realizing a practical physical reservoir with high performance and integrability remains challenging. Herein, we present an analogue circuit reservoir with a simple cycle architecture suitable for complementary metal-oxide-semiconductor (CMOS) chip integration. In several benchmarks and demonstrations using synthetic and real-world data, our developed hardware prototype and its simulator exhibit a high prediction performance and sufficient memory capacity for practical applications, showing promise for future applications in highly integrated AI accelerators.

Effects of eyestalk ablation and seawater temperature on D-glutamate levels in the reproductive tissues of male kuruma prawn Marsupenaeus japonicus.

D-Glutamate, a novel D-amino acid found in animal tissues, exclusively exists in the male reproductive tissues of kuruma prawn, Marsupenaeus japonicus. Herein, changes in the D-glutamate content were determined in the male reproductive tissues of M. japonicus, during acclimation with breeding seawater temperature of 18°C-22°C and unilateral eyestalk ablation. The D-glutamate content in the testis increased with increasing seawater temperature, and with unilateral eyestalk ablation. This suggests that both stimulations induced D-glutamate synthesis in the testis. Although the D-alanine content in the testis increased after unilateral eyestalk ablation, it did not change with elevated seawater temperature. Furthermore, we determined the D-glutamate distribution in the M. japonicus spermatophore. This indicates that D-glutamate is crucial in prawn fertilization.

Distribution and role of d-glutamate, a novel d-amino acid identified in animals, in the reproductive tissues of male kuruma prawn Marsupenaeus japonicus.

Some aquatic invertebrates contain free d-alanine. We previously showed copious amounts of free d-glutamate, a novel d-amino acid, in the tissue of the male reproductive organs of Marsupenaeus japonicus. Herein, we clarified the distribution and potential role of d-glutamate and d-alanine in male reproductive tissues, namely the testis, vas deferens and seminal receptacle at different growth stages of M. japonicus. The percentage of d-glutamate to total glutamate was over 50% in these tissues. In particular, the content of d-glutamate was the most abundant in the vas deferens, the ratio of d-glutamate to total glutamate was approximately 80%. In contrast, d-alanine content was the lowest in the vas deferens among these tissues. d-Glutamate content was the highest when the prawn weighed 12 g, indicating that d-glutamate is actively synthesized in the younger stage. Our findings suggest that d-glutamate plays an important role in the reproductive functions of M. japonicus.

Dynamical system design for silicon neurons using phase reduction approach.

In the present paper, we apply a computer-aided phase reduction approach to dynamical system design for silicon neurons (SiNs). Firstly, we briefly review the dynamical system design for SiNs. Secondly, we summarize the phase response properties of circuit models of previous SiNs to clarify design criteria in our approach. From a viewpoint of the phase reduction theory, as a case study, we show how to tune circuit parameters of the resonate-and-fire neuron (RFN) circuit as a hybrid type SiN. Finally, we demonstrate delay-induced synchronization in a silicon spiking neural network that consists of the RFN circuits.

Network model of chemical-sensing system inspired by mouse taste buds.

Taste buds endure extreme changes in temperature, pH, osmolarity, so on. Even though taste bud cells are replaced in a short span, they contribute to consistent taste reception. Each taste bud consists of about 50 cells whose networks are assumed to process taste information, at least preliminarily. In this article, we describe a neural network model inspired by the taste bud cells of mice. It consists of two layers. In the first layer, the chemical stimulus is transduced into an irregular spike train. The synchronization of the output impulses is induced by the irregular spike train at the second layer. These results show that the intensity of the chemical stimulus is encoded as the degree of the synchronization of output impulses. The present algorithms for signal processing result in a robust chemical-sensing system.

Analog VLSI implementation of resonate-and-fire neuron.

We propose an analog integrated circuit that implements a resonate-and-fire neuron (RFN) model based on the Lotka-Volterra (LV) system. The RFN model is a spiking neuron model that has second-order membrane dynamics, and thus exhibits fast damped subthreshold oscillation, resulting in the coincidence detection, frequency preference, and post-inhibitory rebound. The RFN circuit has been derived from the LV system to mimic such dynamical behavior of the RFN model. Through circuit simulations, we demonstrate that the RFN circuit can act as a coincidence detector and a band-pass filter at circuit level even in the presence of additive white noise and background random activity. These results show that our circuit is expected to be useful for very large-scale integration (VLSI) implementation of functional spiking neural networks.