We investigate neural activity of the neural network including delayed couplings by using attractor reconstruction images. The paper presents the effects on neural activity when the value and distribution of delayed coupling is changed. In particular, we focus on the complexity of attractor images and evaluate the relationship between delayed coupling and complexity.

Living organisms must actively maintain themselves in order to continue existing. Autopoiesis is a key concept in the study of living organisms, where the boundaries of the organism are not static but dynamically regulated by the system itself. To study the autonomous regulation of a self-boundary, we focus on neural homeodynamic responses to environmental changes using both biological and artificial neural networks. Previous studies showed that embodied cultured neural networks and spiking neural networks with spike-timing dependent plasticity (STDP) learn an action as they avoid stimulation from outside. In this article, as a result of our experiments using embodied cultured neurons, we find that there is also a second property allowing the network to avoid stimulation: If the agent cannot learn an action to avoid the external stimuli, it tends to decrease the stimulus-evoked spikes, as if to ignore the uncontrollable input. We also show such a behavior is reproduced by spiking neural networks with asymmetric STDP. We consider that these properties are to be regarded as autonomous regulation of self and nonself for the network, in which a controllable neuron is regarded as self, and an uncontrollable neuron is regarded as nonself. Finally, we introduce neural autopoiesis by proposing the principle of stimulus avoidance.

Microelectrode arrays (MEAs) enable fast and high-throughput readout of cell's electrical signals. MEAs are currently used for phenotype characterization and drug toxicity/efficacy testing with iPSC-derived neurons and cardiomyocytes. A key advantage of MEAs is the capability to record and stimulate individual neurons at multiple sites simultaneously. We will present ongoing advancements of MEA technology, with a focus on achieving higher quality recordings by means of monolithic co-integration of circuitry on chip by using CMOS technology [1]. Such high-density MEAs with more than 3000 electrodes per mm2 are a suitable tool for capturing neuronal activity across various scales, including axons, somas, dendrites, entire neurons, and networks.

An inverter is employed as an analog amplifier for realizing a front-end amplifier for neural spike detection. The amplifier operates in two phases, a biasing and an amplification phase. A high-pass filter is realized by repetitively resetting the neural amplifier and the high-pass cutoff frequency can be adjusted by the resetting frequency. The neural amplifier is designed in a 0.18μm 1P5M CMOS process and post-layout periodic small-signal and periodic noise simulations using SpectreRF were carried out. The neural amplifier achieves an input-referred noise of 3.29μVRMSfrom 6Hz to 10kHz, a power consumption of 3.2μW from a 0.8V power supply, and the efficiency factors of noise and power are 2.53 and 5.12 at a reset switching frequency of 10Hz, respectively.

Complementary semiconductor-metal-oxide (CMOS) technology is a very powerful technology that can be more or less directly interfaced to electrogenic cells, like heart or brain cells in vitro. To this end, the cells are cultured directly atop the CMOS chips, which usually undergo dedicated postprocessing to obtain a reliable bidirectional interface via noble-metal microelectrodes or high-k dielectrics. The big advantages of using CMOS integrated circuits (ICs) include connectivity, the possibility to address a large number of microelectrodes on a tiny chip, and signal quality, the possibility to condition small signals right at the spot of their generation. CMOS will be demonstrated to constitute an enabling technology that opens a route to high-spatio-temporal-resolution and low-noise electrophysiological recordings from a variety of biological preparations, such as brain slices, or cultured cardiac and brain cells. The recording technique is extracellular and noninvasive, and the CMOS chips do not leak out any toxic compounds, so that the cells remain viable for extended times. In turn, the CMOS chips have been demonstrated to survive several months of culturing while being fully immersed in saline solution and being exposed to cellular metabolic products. The latter requires dedicated passivation and packaging techniques as will be shown. Fully integrated, monolithic microelectrode systems, which feature large numbers of tightly spaced microelectrodes and the associated circuitry units for bidirectional interaction (stimulation and recording), will be in the focus of this review. The respective dense microelectrode arrays (MEAs) with small pixels enable subcellular-resolution investigation of regions of interest in, e.g., neurobiological preparations, and, at the same time, the large number of electrodes allows for studying the activity of entire neuronal networks . Application areas include neuroscience, as the devices enable fundamental neurophysiological insights at the cellular and circuit level, as well as medical diagnostics and pharmacology.