Although much is known about the properties of single neuronal units, the rules by which neurons coordinate their activity to represent information about the visual stimuli remain elusive. To understand why, one must consider that the responses of single units are both noisy and ambiguous: responses to the same stimulus vary considerably, and responses to multiple different stimuli can be the same. To achieve optimal real-time performance, these ambiguities must be resolved at the level of neuronal populations via coordinated firing of distinct neuronal ensembles. It is not clear how these ensembles emerge and sustain their coordinated activity. High resolution optical imaging methods have recently revealed the dynamic patterns of neural activity across the layers of area V1, making it possible to apply network analysis methods to address this important question. Neuronal groups that fire in synchrony may be more efficient at relaying shared information to downstream targets1 and are more likely to belong to networks of neurons subserving the same function. Here we will use metrics of synchrony to identify such functional connectivity and study their architecture. Note that being “functionally connected” does not necessarily mean that neurons are anatomically connected to each other. 

A century of remarkable anatomical studies demonstrated that the cortex is largely modular in structure repeating approximately the same anatomical connectivity theme with certain variations from area to area. The vertical arrangement of the basic anatomical module gave rise the concept of the cortical micro-column. The structural similarity between micro-columns across cortical areas suggests that they fulfill an important computational role, albeit in different computational contexts from area to area. The principles by which cortical neurons coordinate their activity along micro-columns to communicate information to higher and lower areas are not known.