Marginalium

Metaphors shape minds:

Scientific analogies can crackle too. Consider one of the puzzles of the visual system: saccades, those rapid, darting eye movements we make a few times per second. These are one of the fastest movements our body can produce – the eye takes only about 20 milliseconds to traverse our field of vision, before settling on the next object of attention. But these rapid eye movements are notoriously sluggish to get going. There’s a whopping gap of around 200 milliseconds from when a visual target appears before a saccade even gets started. The vision neuroscientist Roger Carpenter asked us to imagine it like this:

A fire station receives an urgent summons by telephone. But for nearly an hour absolutely nothing appears to happen; then all of a sudden the firemen leap into action: the doors are flung open and the fire-engines rush off at break-neck speed with their bells ringing, arriving at the fire in less than five minutes.

He offered this analogy to drive home just how odd this situation is, giving us pause to ponder: what on earth is going on while the eye waits to make its move?
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When analogy lands, it adds another dimension to our thinking, so the light hits it in a different way. It can help us understand something more deeply because we have another inroad to it.
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Is there danger, then, in these analogies that can delight and inspire? One risk is that they close down possibilities. They can shut down our thinking, coercing it to fit the shape of someone else’s comparison rather than our own. In feeding you an analogy, I’m not just telling you about a thing – I’m telling you how you should think about that thing and, in doing so, robbing all opportunity for your thoughts to take their own meandering leap into unmapped territories

Then uses lots of example to illustrate, but obviously I liked the brain one:

Our brain isn’t a passive input-output machine. It’s embedded in our body, which is embedded in a world that we need to actively respond to and control. While some ideas from computers have been useful guiding principles for brain research (and vice versa), the story is a much more complicated one: a brain that evolved, over a long sequence of opportunistic and sometimes clumsy adaptations; a brain with billions of diverse neurons and other cells, their connections, and their nonlinear properties. It’s a story we are still only touching the surface of in neuroscience.

It’s a much quicker version of my own article on this.