With technological advances in neuroanatomy and neurophysiology, neuroscience of multi-regional brain-wide neural circuits is taking off. However, recent studies in this area have renewed the debate on local versus global neural representation and processing. Here, focusing on working memory (a core cognitive function), I will propose a mechanism for functional specificity in a cortex made of repeated canonical local circuits à la Kevan Martin and Rodney Douglas. First, I will introduce large-scale modeling of cortex based on connectomic data for monkeys and mice. Second, I will show that our model naturally gives rise to a hierarchy of timescales, and I will highlight macroscopic gradients of synaptic excitation and inhibition as a general principle of the large-scale cortical organization. Third, I will present our modeling of distributed working memory and simple decision-making. This line of work gives rise to the new concept of “bifurcation in space” to explain the emergence of functional modularity in a cortical system.

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