Neural modelling to explore how information is processed in the auditory centres of the brain
Dr Sean Byrnes
Principal Investigator
Dr David Grayden
Special Research
Fellow
The University of Melbourne
Prof Tony Burkitt
Special Research
Fellow
The University of Melbourne
We are using computer models to better understand how the brain learns and recognises patterns of sensory input that change over time. We explore how patterns that change slowly compared with the pace of neural activity, such as sequences of syllables in speech, can be learnt and stored by a network of neurons.
Based on experimental data from the hippocampus, a part of the brain critical to the formation of memories, we have developed a neural network model that shows how sequences of sensory events can be learnt through the adaptation of neural connections as a result of experience. We hope our model will lead to a better understanding of how the brain recognizes and learns distinct sequences of sensory events, and that we can apply the insights gained to improve speech recognition and cochlear implant processing.
The model is made up of pools of neurons each responding to a particular sensory event. A schematic of a single pool showing its inputs (both external and from other pools) and outputs (to other pools) is shown here.
Through adaptation of the connections to other pools, individual neurons learn to detect specific sequences.