Thesis Project Form
Title (tentative): A digital implementation of Spiking Neural Network to reproduce brain connectivity| Thesis advisor(s): Chiappalone Michela, Takashi Kohno (University of Tokyo) | E-mail: |
| Address: Via Opera Pia 13, 16145 Genova | Phone: |
Description
Motivation and application domain
Spiking neuron models simulate neuronal activities and allow us to analyze and reproduce the information processing of the nervous system. The Piecewise Quadratic Neuron (PQN) model is based on a qualitative modeling approach that aims to reproduce only the key dynamics behind neuronal activities. It consumes much fewer circuit resources than the ionic-conductance models although it accurately reproduces theirs responses. This model intends to serve as a tool for building a large-scale closer-to-biology spiking neural network.
General objectives and main activities
The thesis research will be aimed at performing a hardware implementation (on FPGA) of a neural network composed by different types of biologically inspired neurons. This circuit could be potentially exploited within a biological experiment for the delivery of brain-like stimulation patterns. Accordingly, the main tasks will be the following ones:
• Studying the basis of Digital Design, FPGA and VHDL
• VHDL programming, for hardware design of the FPGA
• Python programming, for stimulating the FPGA
• Computational modelling of brain network
• Studying the basis of Digital Design, FPGA and VHDL
• VHDL programming, for hardware design of the FPGA
• Python programming, for stimulating the FPGA
• Computational modelling of brain network
Training Objectives (technical/analytical tools, experimental methodologies)
The thesis will allow training in computational neuroscience, modelling, neuromorphic engineering, hardware implementation, signal processing.
Place(s) where the thesis work will be carried out: Institute of Industrial Science, University of Tokyo, Tokyo, Japan
Additional information
Pre-requisite abilities/skills: Coding expertise is mandatory, as well as interest in digital hardware implementation.
Maximum number of students: 1
Financial support/scholarship: YES