Grant-in-Aid for Transformative Research Areas（Ａ）
Bioengineering Group (A02)
A02-1 In vitro reconstitution of bioplausible models and their wetware applications
PIHideaki YamamotoAssociate Professor, Tohoku UniversityResearchmap
Co-IShigeo SatoProfessor, Tohoku UniversityLab.HP
Co-ISatoshi MoriyaSpecially Appointed Assistant Professor, Tohoku UniversityResearchmap
Goal
Build a closed-loop feedback system for artificial neuronal networks, and constructively analyze the physical basis of biological information processing.
Research plans
This research will construct a closed-loop feedback system for artificial neuronal networks (i.e., cultured neuronal networks with predefined structures) and constructively verify the biological plausibility of the reservoir-based predictive coding model. Through this, we aim to understand the functional significance of spontaneous activity in the nervous system. In the latter half of the project, research will be advanced to verify the biological plausibility of reward-based learning and to develop basic technology for the realization of chemically-powered "wetware."
A02-2 Interface control of multicellular neuronal networks
Goal
We build a new interface that combines the artificial neuronal network and cultured skeletal muscle tissue by generating stimulus input signals to the neurons from various environmental information in real time and transferring the output spike signals to the skeletal muscle tissue to control the bioactuator's motion.
Research plans
We support all the area members including those conducting publicly offered researches by constructing a new platform for consluting data acquisition and data structuring in Waseda university backed by supports from the MEXT ARIM project such as machine sharing and device prototyping.
A02-3 Development of biomedical wetware based of artificial neuronal networks
PIAyumi Hirano-IwataProfessor, Tohoku UniversityLab.HP
Co-IKaoru HiramotoAssistant Professor, Tohoku UniversityResearchmap
Co-IMaki KomiyaAssistant Professor, Tohoku UniversityResearchmap
Co-IDaisuke TadakiAssistant Professor, Tohoku UniversityResearchmap
Goal
We develop a new biomedical wetware device by constructing artificial neural cell circuits and analyzing the brain's damage tolerance, repair characteristics, and pharmacological effects.
Research plans
Damage tolerance and self-repairing are essential brain characteristics as an information-processing system. In this project, we will construct an optical system that uses focused pulsed UV lasers to sever the connections of artificial neural circuits. We will analyze the multicellular data obtained through calcium imaging and compare them with data from animal experiments to study the damage tolerance and self-repairing properties of neural circuits. We aim to model chemically modulated diseases by evaluating the pharmacological effects on artificial neuronal circuits from a bottom-up perspective. We will systematically analyze the damage tolerance and self-repairing characteristics of neuronal networks in terms of circuit structure and drug sensitivity. In the second half of the research period, we will demonstrate the potential of artificial neuronal circuits as multicellular wetware in the field of medical engineering, particularly in disease modeling and new drug evaluation systems.
A02-4a TBA
PIYoshiho IkeuchiProfessor, The University of TokyoResearchmap
Goal
TBA
Research plans
TBA
A02-4b TBA
PIHiroaki NorimotoProfessor, Nagoya UniversityResearchmap
Goal
To elucidate the neural mechanisms by which visual experiences are encoded as memory in brain circuits.
Research plans
We will use an ex vivo eye-brain preparation from reptiles to record visual responses in the cortex and hippocampus. We will examine whether visually responsive neuronal ensembles undergo spontaneous replay after stimulation. Furthermore, we will monitor plastic changes among these neurons in real time during replay.
A02-4c Adaptive information processing in cultured neuronal network based on light-techniques
PIShin-ya KawaguchiProfessor, Kyoto UniversityResearchmap
Goal
Here, aiming for in vitro reconstitution of animals’ learning ability in dissociated neuronal culture, we develop a system to real-time communicate with the network based on cutting-edge fluorescent techniques.
Research plans
Taking advantages of cutting-edge fluorescent imaging and tour-de-force electrophysiological recordings of neuronal membrane potential, we obtain neuronal activity non-invasively in a real-time manner. Based on the computation of obtained activity of multiple neurons, we next develop a system to give real-time feedback pathways using electrical and/or light stimulation. Finally, we also manipulate neuronal and/or synaptic plasticity with light-stimulation, and obtain insights into essential mechanisms for adaptive in vitro information processing.
A02-4d TBA
PIKoji SakaiResearch Scientist, Nippon Telegraph and Telephone CorporationResearchmap
Goal
TBA
Research plans
TBA
A02-4e TBA
PIShotaro YoshidaAssistant Professor, Chuo UniversityResearchmap
Goal
TBA
Research plans
TBA
A02-4f Critical computing in the brain with spontaneous activity
PIHirokazu TakahashiProfessor, The University of TokyoResearchmap
Goal
We propose and address the working hypothesis that spontaneous activity in the brain maintains the critical state and optimizes its information processing capacity.
Research plans
Based on the critical brain hypothesis and the theory of reservoir computing, we will study spiking neural networks (SNN) (in silico), dissociated neuronal cultures (in vitro), and rodent sensory cortex (in vivo). This work aims to (1) establish a method for quantifying the information processing capacity (IPC) of the spontaneously active brain, (2) verify the functional significance of spontaneous activity, and (3) improve the information processing of neural networks and the brain by regulating spontaneous activity.
