Connectome cost conservation model of skill learning

Inter-subject variability in learning and hence plasticity is fundamental in behavioral research. Neuroplasticity is studied either by exploring biological aspects of the synapse or regional brain activity. Lacking from these is a network, holistic and integrated view of the brain as an inter-connected organ.

The connectome, the wiring diagram of the brain, is one of the greatest promises of neuroscience.

The only methodology that allows the exploration of the human brain connectome in-vivo, is MRI via diffusion or resting state fMRI.

This project will explore and model the connectomes of subjects before and after skill learning compared to skilled-controls. I hypothesize that the brain connectome alters its details in response to skill learning.

I anticipate that the baseline individual connectome will predict the ability of the brain to change in relation to specific task.

I suggest that balancing mechanisms of the connectome underlie network rewiring in response to learning and may predict the behavioral outcome. We have recently revealed a connectome efficiency conservation law across mammals driving the premises of this project. The outcome of this project is to bridge the gap between neuropsychology and neurobiology views of neuroplasticity.

The indication that the connectome is a key feature in plasticity will lead to a paradigm shift in the field and provide cognitive neuroscientists new empirical tools to explore the relations between brain and behavior.

Finally, as I anticipate that the connectome predisposes the capacity to rewire, the suggested predictive modelling framework could be the bases to simulate individual ability to learns, rehabilitates or develop degenerative processes. Learning, memory, decision-making and other cognitive process happen at the whole organ level.

We have invested a lot of effort to explore brain plasticity in a segregated manner it is high time for a more global, network view of the neuroplasticity.