Most neuroscientists make their discoveries in a traditional laboratory or clinical setting. Sean Escola, a theoretical neuroscientist at Columbia University in New York, just needs a powerful computer and, judging from his photo, a good whiteboard.
Using data that he and his colleagues have recorded from living brain cells, called neurons, Escola crunches numbers to develop rigorous statistical models that simulate the activity of neuronal circuits within the brain. He hopes his models will help to build a new neuroscience that brings into sharper focus how the brain’s biocircuitry lights up to generate sensations and thoughts—and how it misfires in various neurological disorders, particularly in mental illnesses.
Like many of his fellow neuroscientists, Escola views the brain as a complex computational machine, with the operative word being “complex.” The human brain consists of roughly 86 billion neurons and billions of other types of cells. Further complicating matters, no two neurons are exactly alike because each one reaches out and touches hundreds or thousands of other cells, forming trillions of information-processing connections, or circuits.
Throughout the day, individual circuits click on and off in our brains to process the external factors that greet and sometimes confront us. The same is true for a wide range of internal stimuli, such as a craving for food or a need for sleep. Escola wants to know how neural circuits process this interplay of internal and external signals—an area of investigation that is just becoming possible through technological innovations arising from NIH-funded research, including the pioneering Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative.
The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.