Understanding how the brain works is arguably one of the greatest scientific challenges of our time. Although there have been piecemeal efforts to explain how different brain regions operate, no general theory of brain function is universally accepted. A fundamental underlying limitation is our ignorance of the brain's microcircuitry, the synaptic connections contained within any given brain area, which Cajal referred to as “impenetrable jungles where many investigators have lost themselves” (Ramón y Cajal, 1923). To explore these jungles, neuroscientists have traditionally relied on electrodes that sample brain activity only very sparsely—from one to a few neurons within a given region. However, neural circuits can involve millions of neurons, so it is probable that neuronal ensembles operate at a multineuronal level of organization, one that will be invisible from single neuron recordings, just as it would be pointless to view an HDTV program by looking just at one or a few pixels on a screen.
Neural circuit function is therefore likely to be emergent—that is, it could arise from complex interactions among constituents. This hypothesis is supported by the well-documented recurrent and distributed architecture of connections in the CNS. Indeed, individual neurons generally form synaptic contacts with thousands of other neurons. In distributed circuits, the larger the connectivity matrix, the greater the redundancy within the network and the less important each neuron is. Despite these anatomical facts, neurophysiological studies have gravitated toward detailed descriptions of the stable feature selectivity of individual neurons, a natural consequence of single-electrode recordings. However, given their distributed connections and their plasticity, neurons are likely to be subject to continuous, dynamic rearrangements, participating at different times in different active ensembles. Because of this, measuring emergent functional states, such as dynamical attractors, could be more useful for characterizing the functional properties of a circuit than recording receptive field responses from individual cells. Indeed, in some instances where large-scale population monitoring of neuronal ensembles has been possible, emergent circuit states have not been predictable from responses from individual cells.