A Biologically New Learning Paradigm Implemented In An Artificial Neural Network

📄 Project Abstract

Shahaf and Marom (2001) have provided evidence that a biological neural network of cultured cortical neurons from baby rats are able to learn. These biological networks have a multitude of connections, stability in connections, and are modifiable by external stimulus. All of this has been shown before however. What Shahaf and Marom have done that is groundbreaking is provide evidence that learning can be achieved in the absence of a separate neural reward mechanism. By stimulating the network until a desired response is achieved and then removing the stimulation, the network is able to locate and stabilise upon selected neurons using the point at which the external stimulation is removed as a guide to which the correct neuron is. This project seeks to reproduce these findings in an artificial environment. A recurrent neural network is chosen that consists of stochastic neurons connected to an appropriate number of neurons. Long-term potentiation and long-term depression are identified ...