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Technological advances have dramatically expanded our ability to probemulti-neuronal dynamics and connectivity in the brain. However, our ability toextract a simple conceptual understanding from complex data is increasinglyhampered by the lack of theoretically principled data analytic procedures, aswell as theoretical frameworks for how circuit connectivity and dynamics canconspire to generate emergent behavioral and cognitive functions. We review andoutline potential avenues for progress, including new theories of highdimensional data analysis, the need to analyze complex artificial networks, andmethods for analyzing entire spaces of circuit models, rather than one model ata time. Such interplay between experiments, data analysis and theory will beindispensable in catalyzing conceptual advances in the age of large-scaleneuroscience.

On Simplicity and Complexity in the Brave New World of Large-Scale Neuroscience