Neurons encode information using two main schemes: rate coding (frequency of firing) and temporal coding (timing or pattern of firing). By the term "firing", we refer to the generation of an action potential, also called a "spike", which corresponds to a peak of electric voltage and to an associated electric current. These propagate along one neuron and from one neuron to the other.
As mentioned in Wikipedia, "binary symbols can be used to mark the spikes: 1 for a spike, 0 for no spike". Also, "temporal coding allows the sequence 000111000111 to mean something different from 001100110011". Citing the same Wikipedia article, candidates for temporal codes include [26]:
1) time-to-first-spike after the stimulus onset,
2) phase-of-firing with respect to background oscillations,
3) characteristics based on the second and higher statistical moments of the ISI (Inter-Symbol Interference) probability distribution,
4) spike randomness,
5) precisely timed groups of spikes (temporal patterns)
A selected excerpt from the mentioned above Wikipedia article is provided:
"Information is carried either in terms of the relative timing of spikes in a population of neurons (temporal patterns) or with respect to an ongoing brain oscillation (phase of firing)[3][6]. Spikes occurring at specific phases of an oscillatory cycle are more effective in depolarizing the post-synaptic neuron [27]." Therefore, timing is a main factor affecting outcomes.
The video entitled "HBP Neurorobotics platform EU Review release" available at URL https://youtu.be/ee0iZaiQjLU, which is related to neurorobotics presents neuronal "spiking" patterns and their use in neurorobotics.
Neurons may follow specific firing sequences, which may represent "key sequences" for specific functions.
We can "translate" them digitally, by using "1" for the time points when the neuron fires or is activated, and "0" for the time points when it remains inactive or does not fire.
In this way, we obtain binary sequences which represent streams of bits which are either 0 or 1.
We may refer to these as key sequences as key bitstreams.
The study https://pmc.ncbi.nlm.nih.gov/articles/PMC3505670/ provides in Figure 4 an example where a "bad" neuronal firing sequence is identified (blue rectangle).
Then, the outcome is corrected by application of a "good" or "correct" neuronal firing sequence (red rectangle).
A digital translation could refer to the bad sequence as "100010001" and to the good sequence as "100010000". The difference could be an extra firing at the end.
Image of recorded action potentials during a stimulus: https://mrgreene09.github.io/computational-neuroscience-textbook/Ch5.html (section 6.3)
Please refer to this reference.
More details:
Mathieu Beraneck, and Hans Straka. “Vestibular Signal Processing by Separate Sets of Neuronal Filters.” Journal of Vestibular Research, vol. 21, no. 1, 15 Mar. 2011, pp. 5–19, https://doi.org/10.3233/ves-2011-0396 (PDF)