Computational Neuroscience Quotes

A meticulous virtual copy of the human brain would enable basic research on brain cells and circuits or computer-based drug trials.

A fly with a brain the size of a salt grain has the behavioral repertoire nearly as complex as a much larger animal such as a mouse. That's a super-interesting problem from an engineering perspective.

What I'm really interested in is this idea of a 'brain co-processor' - a device that can record from, and deliver information to, so many points in the brain, with a computational infrastructure in between - a computer that can process the information and compute exactly what needs to be restored.

We basically created a computational unit out of two brains.

The brain can be seen as a complex machine, like a gooey computer.

My main interest is in trying to find radically different kinds of neural nets.

The study of thinking machines teaches us more about the brain than we can learn by introspective methods. Western man is externalizing himself in the form of gadgets.

But just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations of intellectual processes in machines should lead to a science, eventually.

I think the definition will change as we learn more, but my working definition of solving the brain is: one, we can model, maybe in a computer, the processes that generate things like thoughts and feelings, and two, we can understand how to cure brain disorders, like Alzheimer's and epilepsy. Those are my two driving goals. One is more human-condition oriented, and one more clinical.

I would argue that if you understand how the cells of the brain are organized into circuits, almost computational circuits if you will, and we see how information flows through those circuits and how it's transformed, we might have a much firmer grasp on why our brains make decisions the way that they do. If we get a handle on that, maybe we can overcome some of our limitations and at the very least we'll understand why we do what we do.