What are the rules of brain learning?

Add to your list(s) Download to your calendar using vCal

• Cian O'Donnell, University of Bristol
• Wednesday 06 February 2019, 12:00-13:00
• Centre for Computational Biology (Y2 Haworth Building).

If you have a question about this talk, please contact Dr Christopher Yau.

Brains learn by changing the strength of their synaptic connections, in a process called synaptic plasticity. To understand how brain learning works, we’d like to model the rules of this process mathematically, then study its properties in neural circuit simulations. Traditional plasticity models are either 1) phenomenological, abstracting away the molecular machinery of synapses, or 2) highly detailed biochemical models. The former type are likely too simple to capture key properties of synapses, but the latter type are too complicated to analyse mathematically or even to simulate in neural circuit models. We instead aimed to build a new model at an intermediate level of detail, based on our collaborators’ physiological data from rodent hippocampal synapses. In this talk I will discuss this new model and what it can tell us about brain learning.

Our main finding was that the intrinsic noise from low-copy number synaptic proteins introduces large variability in synaptic plasticity outcomes. We quantitatively compared the model’s pattern of variability across stimulation protocols to that found experimentally, and found a good match. This gives evidence that the rules of brain learning are stochastic.

Joint work with Romain Veltz, Yuri Rodrigues, and Hélène Marie.

This talk is part of the Centre for Computational Biology Seminar Series series.

This talk is included in these lists:

• Centre for Computational Biology (Y2 Haworth Building)
• Centre for Computational Biology Seminar Series

Note that ex-directory lists are not shown.