Mapping neural connectivity is a major topic of interest and research in neuroscience. A connectivity map, or “connectome,” would be an invaluable tool for neuroscientists by providing a physiological backbone on which new theories and ideas could be based. Moreover, it could serve as the basis for countless technological advancements in the fields of computer science and neuroinformatics. However, this task is considerably more complicated than it may sound. Each of the brain’s 100 billion neurons forms anywhere from 1,000 to 10,000 synapses with other neurons. Mapping this enormous volume of connections is a truly daunting task. In fact, it has been estimated that generating a high resolution connectome could take longer than the average lifetime using the technology that exists today. Therefore, new tactics must be employed to make significant progress in connectivity mapping.
Giorgio Ascoli, founding Director of the Center for Neural Informatics, Structures, & Plasticity at George Mason University’s Krasnow Institute for Advanced Study, has taken an alternative approach in his work on neural connectivity. In “The Coming of Age of the Hippocampome,” Ascoli describes his statistical method of mapping circuits at the neuron level within a specific brain region or structure. Creating such a high-resolution map is still a lofty goal, but limiting the neuron types and applying statistical algorithms significantly simplifies the issue. Ascoli is currently working on the circuitry map of the rodent hippocampus, which he has termed the “hippocampome.”
The possibility of a hippocampome is an exciting development in neural connectivity. Such a map could help to define and further understand neuron function and clarify how general circuitry works in the brain. However, the hippocampus is one of the most widely studied brain structures, and Ascoli’s method may not be applied as successfully to mapping other, less documented areas of the brain.