In part one, visiting scientist Jeremy Forest gives a brief overview of the plasticity mechanisms in the brain. He goes over how neurons interact and change over time with different plasticity events in dendritic spines, and covers topics such as molecular mechanisms, synaptic activations, and structural plasticity.
Throughout the presentation, Jeremy points out the biological mechanisms, such as time-scale interactions, that could potentially be modeled in AI systems and bring many benefits, such as continual learning and efficiency.
In part two, Jeremy continues his overview of the plasticity mechanisms in the brain and focuses on activity levels in neurons rather than dendritic spines.
He talks about how memory ensembles are dynamic and how neurons encode signals. He then explores different behavioral expressions of memory and context impacts plasticity mechanisms in neurons. He makes the case that all those mechanisms interact on widely different timescales and timescale should be considered when developing deep learning networks.