Solving the paradox of the equipotential and modular brain: A neurocomputational model of stroke vs. slow-growing glioma

In acute brain damage (e.g., stroke), patients can be left with specific deficits while other domains are unaffected, consistent with the classical 'modular' view of cortical organization. On this view, relearning of impaired function is limited because the remaining brain regions, tuned to other domains, have minimal capacity to assimilate an alternative activity. A clear paradox arises in low-grade glioma where an even greater amount of cortex may be affected and resected without impairment. Using a neurocomputational model we account for the modular nature of normal function as well as the contrasting types of brain insult through the interaction of three computational principles: patterns of connectivity; experience-dependent plasticity; and the time course of damage. This work provides support for a neo-Lashleyan view of cortical organization.