OK, what? Look at this:

A pyramidal cell — squashed into two dimensions. The black blob in the middle is the neuron’s body; the rest of the wires are its dendrites. Credit: Alain Dexteshe / http://cns.iaf.cnrs-gif.fr/alain_geometries.html

This is a picture of a pyramidal cell, the neuron that makes up most of your cortex. The blob in the centre is the neuron’s body; the wires stretching and branching above and below are the dendrites, the twisting cables that gather the inputs from other neurons near and far. Those inputs fall all across the dendrites, some right up close to the body, some far out on the tips. Where they fall matters.

But you wouldn’t think it. When talking about how neurons work, we usually end up with the sum-up-inputs-and-spit-out-spike idea. In this idea, the dendrites are just a device to collect inputs. Activating each input alone makes a small change to the neuron’s voltage. Sum up enough of these small changes, from all across the dendrites, and the neuron will spit out a spike from its body, down its axon, to go be an input to other neurons.

The sum-up-and-spit-out-spike model of a neuron. If enough inputs arrive at the same time — enough to cross a threshold (grey circle) — the neuron spits out a spike.

It’s a handy mental model for thinking about neurons. It forms the basis for all artificial neural networks. It’s wrong.

Those dendrites are not just bits of wire: they also have their own apparatus for making spikes. If enough inputs are activated in the same small bit of dendrite then the sum of those simultaneous inputs will be bigger than the sum of each input acting alone:

The two coloured blobs are two inputs to a single bit of dendrite. When they are activated on their own, they each create the responses shown, where the grey arrow indicates the activation of that input (response here means “change in voltage”). When activated together, the response is larger (solid line) than the sum of their individual responses (dotted line).

The relationship between the number of active inputs and the size of the response in a little bit of dendrite looks like this:

Size of the response in a single branch of a dendrite to increasing numbers of active inputs. The local “spike” is the jump from almost no response to a large response.

There’s the local spike: the sudden jump from almost no response to a few inputs, to a big response with just one more input. A bit of dendrite is “supralinear”: within a dendrite, 2+2=6.

We’ve known about these local spikes in bits of dendrite for many years. We’ve seen these local spikes in neurons within slices of brain. We’ve seen them in the brains of anaesthetised animals having their paws tickled (yes, unconscious brains still feel stuff; they just don’t bother to tell anyone). We’ve very recently seen them in the dendrites of neurons in animals that were moving about (yeah, Moore and friends recorded the activity in something a few micrometres across from the brain of a mouse that was moving about; crazy, huh?). A pyramidal neuron’s dendrites can make “spikes”.