Out of the single‐neuron straitjacket: Neurons within assemblies change selectivity and their reconfiguration underlies dynamic coding

Abstract: We investigated cell assemblies in the frontal cortex of macaques during two discrimination tasks. Focusing on the period of goal-action transformation, we extracted spikes fired during assembly activation from the full neural activity and showed that the contribution of a neuron to assembly coding, when it co-ordinates with other assembly neurons, differs from its coding in isolation. Neurons, with their flexible participation to multiple assemblies, contributed to the encoding of new information not encoded by the neurons alone. Even non-discriminative neurons acquired selectivity as part of the collective activity of the assemblies. Thus, neurons in their assemblies process distinct information for various purposes as a chess simul master, playing on multiple chessboards. The reconfiguration of the participation of the neurons into different assemblies in the goal-action transformation process translated into a dynamic form of coding, whereas minimal reconfiguration was associated with the static goal coding of the memory period. (Figure presented.). Key points: Traditionally, the coding properties of a neuron are studied using all its activity (full-spikes), irrespective of its co-ordination with different groups of neurons. With an assembly centered approach, we can determine the neuron's coding properties not in absolute terms, but relative to the assembly of neurons with which it co-ordinates. When neurons are studied in different assemblies—focusing only on the spikes fired during assembly coordination (assembly-spikes)—they can contribute to the coding of different variables. The coding flexibility of the same neuron in multiple assemblies increases the amount of information it can contribute to encoding compared to isolated neurons. Dynamic coding, as opposed to static coding, as observed during the goal-action transformation process, can be explained by an increase in the reconfiguration of active assemblies, with neurons contributing to the coding of different variables in different epochs, depending on which assembly is active.