UC San Diego

While various theories have been proposed on the methods by which information is encoded, processed, and transmitted within the brain, one view gaining increasing currency capitalizes on the ability of large populations of neurons and their associated synapses to fire simultaneously in accordance to each other. However, current biological experimental techniques are limited in their ability to accurately observe with sufficient precision the activity of such large populations of synapses to the degree necessary to conclusively validate and refine population spike-time based coding theories. By using highly detailed computer modeling studies in conjunction with large amounts of biologically recorded data from the well-studied and physiologically important thalamocortical connections, we are able to bridge the gap between current experimental limitations and proposed theories. We find synchrony to be a highly effective mechanism for information transfer and that biological neurons seem to balance the need to transmit information reliably and precisely with the energetic costs of doing so. Furthermore, we find that modeling synchrony within increasingly realistic environmental and structural contexts not only demonstrates the robustness of synchronous information coding, but a likely adaptiveness to noise and other variations as found in biological systems. Overall, these observations help to provide further eludication and validation of theories of population-based spike time neural coding and neural connectivity