software
Neural information systems laboratory
Theoretically understand the brain
We have a brain and perform highly intelligent activities. What kind of activity of the brain makes intelligence possible? And is it possible to give machines the same intelligence as the brain? We are conducting research on the theoretical neuroscience and machine learning in order to elucidate the information basis of intelligence from both biological and machine perspectives.
College of Systems Engineering and Science Department of Electronic Information Systems
/ Graduate School of Engineering and Science（Master's Program） Systems Engineering and Science
/ Graduate School of Engineering and Science（Doctor's Program） Functional Control Systems Course
- Faculty Name
- HOSAKA, Ryosuke
- Keyword
- Computational neuroscience,Reservoir Computing,Stochastic differential equation,Simulations,Causality analysis,Mathematical enginerring,Spike Statistics,Brain waves
This lab is for this SDG activity:
STUDY FIELDS
- Neuroscience
- Information theory
- Probability and statistics
- Differential equations
- Artificial intelligence
- Electrophysiology
FOR SOCIETY
Brains are dynamic systems whose networks change and they are also subject to noises. How does such an unstable and non-stationary system achieve stable information representation? We will apply our results to engineering fields to propose stable information processing machines.
RESEARCH THEMES
- Excitatory-inhibitory equilibrium and information processing function guided by synaptic learning
- Causal Analysis of Cultured Neural Networks
- Derivation of meta-grammatical rules by computational cognitive and neuroscientific methodologies
- Application of Autonomous Excitation-Reduction Equilibrium to Reservoir Computing
