Data mining opens the door to predictive neuroscience
From the post:
Ecole Polytechnique Fédérale de Lausanne (EPFL) researchers have discovered rules that relate the genes that a neuron switches on and off to the shape of that neuron, its electrical properties, and its location in the brain.
The discovery, using state-of-the-art computational tools, increases the likelihood that it will be possible to predict much of the fundamental structure and function of the brain without having to measure every aspect of it.
That in turn makes modeling the brain in silico — the goal of the proposed Human Brain Project — a more realistic, less Herculean, prospect.
The fulcrum of predictive analytics is finding the “basis” for prediction and within what measurement of error.
Curious how that would work in an employment situation?
Rather than Google’s intellectual hazing rituals, project a thirty-minute questionnaire on Google hires against their evaluations at six-month intervals. Give prospective hires the same questionnaire and then “up” or “down” decisions on hiring. Likely to be as accurate as the current rituals.
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