Biomodeling System - Interaction Between Living Neuronal Networks and the Outer World

Kudoh, Suguru N.; Hosokawa, Chie; Kiyohara, Ai; Taguchi, Takahisa; Hayashi, Isao

doi:10.20965/jrm.2007.p0592

Cited by 26 publications

(15 citation statements)

References 14 publications

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“…Dissociated neuron was plated with a nominal density of 2500 cells/mm 2 onto a poly(ethylenimine)-coated multi-electrode dish (MED) probe (Alpha MED Scientific, Osaka, Japan). The probe consisted of 64 planar microelectrodes and 4 reference electrodes [Kudoh et al, 2007;Hosokawa et al, 2008;Ito et al, 2010]. Each electrode was 50×50 m 2 and the electrode spacing was 150 m.…”

Section: Experimental Procedures Cell Culture On Measmentioning

confidence: 99%

Xenon-induced inhibition of synchronized bursts in a rat cortical neuronal network

et al. 2012

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List of abbreviations:Xe, xenon; DIV, day in vitro; DMEM, Dulbecco's Modified Eagle Medium; MEA, multi-electrode array; MED, multi-electrode dish; GABAA, -aminobutyric acid type-A; NMDA, N-methyl-D-aspartate; SR, spike rate; SBR, synchronized-burst rate; SA, spike amplitude; SW, spike width; BD, burst duration; IBI, inter-burst interval, SIB, number of spikes in a burst 2 Abstract:Xenon (Xe) and other inert gases produce anesthesia via an inhibitory mechanism in neuronal networks. To better understand this mechanism, we measured the electrical signals from cultured rat cortical neuronal networks in a multi-electrode array (MEA) under an applied Xe pressure. We used the MEA to measure the firing of the neuronal network with and without Xe gas pressurized to 0.3 MPa. The MEA system monitored neuronal spikes on 16 electrodes (each 50×50 m 2 ) at a sampling rate of 20 kHz. The embryo rat cortical cells were first cultured on MEAs without Xe for approximately three weeks, at which time they produced synchronized bursts that indicate maturity. Then, with an applied Xe pressure, the synchronized bursts quickly ceased, whereas single spikes continued. The Xe-induced inhibition-recovery of neuronal network firing was reversible: after purging the Xe from the system, the synchronized bursts gradually resumed. Thus, Xe did not inhibit single neuron firing, yet reversibly inhibited the synaptic transmission. This finding agrees with the channel-blocker and a modified-hydrate hypothesis of anesthesia, but not the lipid-solubility hypothesis. (174 words)

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Section: Experimental Procedures Cell Culture On Measmentioning

confidence: 99%

Xenon-induced inhibition of synchronized bursts in a rat cortical neuronal network

et al. 2012

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“…At the present time we examine this issue using a neuro-robotic system consisting of a single dissociated culture system and a small mobile robot. So far, we achieved a collision avoidance behavior [28]. We also obtained preliminary results suggesting that the ensemble learning was established in the neural system.…”

Section: Designing Aca Based On the Bio-robotics Synthesismentioning

confidence: 71%

Discussion about “synthetic intelligence” in dissociated culture system

Kudoh

Kiyohara

Taguchi

2011

Elect Comm in Japan

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SUMMARYThe fundamental frameworks for possessing qualia are "embodiment" and the network structures of the relationships between internal modules. We proposed "Anaplastic cognitive agent" (ACA) composed by interactions between submodules with hierarchical history functions and network structures. A dissociated culture system can discriminate several distinct spatiotemporal patterns of action potentials evoked by current inputs, and possesses kinds of history function; history properties of network dynamics, synaptic plasticity, and so on. Key words: qualia; history function; dissociated culture system; synthetic intelligence. The Brain and "Information Processing Models"We think that studies of so-called artificial intelligence are motivated not only by potential practical applications but, even more important, by the desire to understand human intellectual faculties. By creating devices performing the same functions as human intelligent information processing, we are trying to constructively understand the intellect and to find explanations of our mental functions and feelings. However, since models derived from artificial intelligence represent certain engineering values, a large number of intelligence models with accent on the engineering aspects have been proposed based on functional characteristics of the brain. It is extremely difficult to realize such biological features as creativity and adaptability to unfamiliar environments. However, since under certain conditions or within a known environment frame devices for intelligent information processing sometimes can find limited practical applications as tools, in many cases modeling of these specific features of living creatures is not necessary. In this context, many intelligence models detached from the brain have been developed. Considering that computational models influence interpretation of the data of biological and psychological experiments, applied models designed by "intentionally" detaching the brain have a practical value, but it is necessary to keep in mind that consciousness is lost. A typical example of such conditions can be found in the "dual storage model" of information processing in the field of cognitive psychology proposed by Atkinson and Shiffrin (Fig. 1) [1, 2]. According to the paradigm of this model, input from the environment is stored as the temporary working memory in short-term storage. There, the information after coding, storage, retrieval, decision making, and interacting with the contents of long-term memory, is stored again in the long-term storage to be retrieved as the response to the information received from the outside world. The short-term memory, which is the central idea of this model, later was expanded as the "working memory" by addition of such subsystems as "a central executive system." The working memory by itself is independent and evokes the idea of a "little man in the brain." Background of such representation of the thought process as an information processing model can be tracked to development of computer...

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“…In this paper, we introduce a fuzzy bio-interface between a culture dish of rat hippocampal neurons and the khepera robot [4]- [8]. We propose a model to analyze logic of signals and connectivity of electrodes in a culture dish, and show the bio-robot hybrid we developed [9], [10].…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, they have not yet achieved a certain task that experimenter desired. We show a robot system that controlled by a living neuronal network through the fuzzy bio-interface in order to achieve such a task [4]- [8]. This fuzzy bio-interface consists of two sets of fuzzy IF-THEN rules: (1) to translate sensor signals of robot into stimuli for the living neuronal network, and (2) to control (i.e.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy bio-interface: Indicating logicality from living neuronal network and learning control of bio-robot

Hayashi

Kiyotoki

Kiyohara

et al. 2011

The 2011 International Joint Conference on Neural Networks

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Recently, many attractive brain-computer interface and brain-machine interface have been proposed. The outer computer and machine are controlled by brain action potentials detected through a device such as near-infrared spectroscopy (NIRS) and electroencephalograph (EEG), and some discriminant model determines a control process. In this paper, we introduce a fuzzy bio-interface between a culture dish of rat hippocampal neurons and the khepera robot. We propose a model to analyze logic of signals and connectivity of electrodes in a culture dish, and show the bio-robot hybrid we developed. We believe that the framework of fuzzy system is essential for BCI and BMI, thus name this technology "fuzzy bio-interface". We show the usefulness of a fuzzy bio-interface through some examples.

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Biomodeling System - Interaction Between Living Neuronal Networks and the Outer World

Cited by 26 publications

References 14 publications

Xenon-induced inhibition of synchronized bursts in a rat cortical neuronal network

Xenon-induced inhibition of synchronized bursts in a rat cortical neuronal network

Discussion about “synthetic intelligence” in dissociated culture system

Fuzzy bio-interface: Indicating logicality from living neuronal network and learning control of bio-robot

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