To Table of Contents array consists of 100 hair-thin silicon needles , each of which picks up the electrical activity of one or two neurons . Those signals are then transmitted through a wire to a computer that we can use to convert the brain activity into instructions to control a machine , or even the person ’ s own arm . We are assuming that the relevant variable here — the language we should try to interpret — is the rate at which neurons discharge , or “ fire .”
Let me explain this using the example of moving a cursor on the screen .
We first generate a movie of a cursor moving : say , left and right . We show this to the person and ask them to imagine they are moving a mouse that controls that cursor , and we record the activity of the neurons in their motor cortex while they do so . For example , it might be that every time you think “ left ,” a certain neuron will fire five times — pop pop pop pop pop — and that if you think “ right ,” it will fire ten times . We can use such information to map activity to intention , telling the computer to move the cursor left when the neuron fires five times , and right when it fires ten times .
Of course , there are other decisions to be made : What if a neuron fires just three times ? So you need a computer model to decide which numbers are close enough to five . And since neuronal activity is naturally noisy , the more neurons we can measure , the better our prediction will be — with the array we implant , we usually get measurements from 50 to 200 .
For the arm prosthesis , we similarly ask people to imagine making the same movement with their own arm . There were people who thought you would have to build separate models for “ flex and extend your elbow ,” “ move your wrist up and down ,” and so on . But it turns out this isn ’ t necessary . The brain doesn ’ t think in terms of muscles or joint angles — the translation of intentions into movement happens later .
How do you find the exact spot in the motor cortex at which to implant the array ?
In fact , I don ’ t think the exact location matters that much . There is also no need for us to know exactly what each individual neuron is trying to do , as long as we can dependably predict the intended action from their combined activity . That goes against the standard old theory that there is a separate location for controlling each finger , for example . If that were the case , it would mean that if you put the array in a particular place you ’ d get great thumb control , but nothing else . I ’ ve spent my entire scientific career saying it
Neuroscientist John Donoghue CREDIT : JAMES PROVOST ( CC BY-ND )
is not true that doing something only engages a small and specific part of the brain . All our neurons form parts of large , interconnected networks .
Do people get better with experience in using the device ?
Not really . The neurons often change their activity , which can corrupt the map , so we have to recalibrate the model at the beginning of every session . This means people have to work with a different model every day , so they don ’ t get better at it .
And if , as sometimes happens , something goes wrong and we give them control that isn ’ t very good , they don ’ t get over it on that day , which can be very frustrating for them . It appears the brain isn ’ t plastic enough to change the activity of specific neurons quickly enough to overcome such problems the same day .