Connectome cost conservation model of skill learning

Introduction

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 interconnected organ.

The Connectome

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.

Project Goals

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.

Predictions

I anticipate that:

1. The baseline individual connectome will predict the ability of the brain to change in relation to specific tasks.
2. 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.

Expected Outcomes

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 with new empirical tools to explore the relations between brain and behavior.

Implications

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

Conclusion

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 neuroplasticity.