Our best guess is that an average neuron in the human brain transmits a spike about 0.1-2 times per second.


Bias from neurons with sparse activity

When researchers measure neural activity, they can fail to see neurons which rarely fire during the experiment (those with ‘sparse’ activity).1Preferentially recording more active neurons means overestimating average rates of firing. The size of the bias seems to be around a factor of ten: it appears that around 90% of neurons are ‘silent’, so unlikely to be detected in these kinds of experiments. This suggests that many estimates should be scaled down by around a factor of around ten.

Assorted estimates

Informal estimates

Informal websites and articles commonly report neurons as firing between <1 and 200 times per second.2 These sources lack references and are not very consistent, so we do not put much stock in them.

Estimates of rate of firing in human neocortex

Based on the energy budget of the brain, it appears that the average cortical neuron fires around 0.16 times per second. It seems unlikely that the average cortical neuron spikes much more than once per second.

The neocortex is a large part of the brain. It accounts for around 80% of the brain’s volume3, and uses 44% of its energy4. It appears to hold at least a third of the brain’s synapses if not many more5. Thus we might use rates of firing of cortical neurons as a reasonable proxy for normal rates of neuron firing in the brain. We can also do a finer calculation.

We might roughly expect energy used by the brain to scale in proportion both to the spiking rate of neurons and to volume. This is because the energy required for every neuron to experience a spike scales up in proportion to the surface area of the neurons involved6, which we expect to be roughly proportional to volume.

So we can calculate:

energy(cortex) = volume(cortex) * spike_rate(cortex) * c

energy(brain) = volume(brain) * spike_rate(brain) * c

For c a constant.


energy(cortex)/energy(brain) = volume(cortex) * spike_rate(cortex)/volume(brain) * spike_rate(brain)

From figures given above then, we can estimate:

0.44 = 0.8 * 0.16/spike_rate(brain)

spike_rate(brain) = 0.8 * 0.16 /0.44 = 0.29

Or for a high estimate:

0.44 = 0.8 * 1/spike_rate(brain)

spike_rate(brain) = 0.8 * 1 /0.44 = 1.82

So based on this rough extrapolation from neocortical firing rates, we expect average firing rates across the brain to be around 0.29 per second, and probably less than 1.82 per second. This has been a very rough calculation however, and we do not have great confidence in these numbers.

Estimates of rate of firing in non-human visual cortex

A study of macaque and cat visual cortex found rates of neural firing averaging 3-4 spikes per second for cats in different conditions, and 14-18 spikes per second for macaques. A past study found 9 spikes per second for cats.7 It is hard to know how these estimates depend on the region being imaged and on the animal being studied, which significantly complicates extracting conclusions from these results. Furthermore, these studies appear to be subject to the bias discussed above, from only sampling visually responsive cells. Thus they probably overestimate overall neural activity by something like a factor of ten. This suggests figures in the 0.3-1.8 range, consistent with estimates from the neocortex. Note that the visual cortex is part of the neocortex, so this increases our confidence in our estimates for that, without reducing our uncertainty about the rest of the brain.

Maximum neural firing rates

The ‘refractory period’ for a neuron is the time after it fires during which it either can’t fire again (‘absolute refractory period’) or needs an especially large stimulus to fire again (‘relative refractory period’). According to physiologyweb.com, absolute refractory periods tend to be 1-2ms and relative refractory periods tend to be 3-4ms.8 This implies than neurons are generally not capable of firing at more than 250-1000 Hz. This is suggestive, however the site does not say anything about the distribution of maximum firing rates for different types of neurons, so the mean firing rate could in principle be much higher.