Fig 4. Inhibitory plasticity self-organises a multiplexed burst code.

(A) Example illustrating a multiplexed burst code in PCs in which somatic and dendritic inputs are represented in the event rate and the burst fraction, respectively [17]. Events are either a burst or single spike, while the burst fraction (BF) is the fraction of events that are bursts. (B) Alternating and opposite pulse inputs (dashed lines) are delivered to the somatic and dendritic compartment ($I_i^{\text{s},\text{high}}=800\text{pA}$, $I_i^{\text{s},\text{low}}=500\text{pA}$, $I_i^{\text{d},\text{high}}=105\text{pA}$, $I_i^{\text{d},\text{low}}=-480\text{pA}$, ${\sigma }_i^{\text{s}}={\sigma }_i^{\text{d}}=450\text{pA}$). The pulse inputs can be decoded from the event rate (solid black) and BF (solid red) respectively (see Methods). (C) Stimulation paradigm with an increase in background excitation (300, 600 and 900 pA; red triangle = dendrite, black triangle = soma) on which pulse inputs are superimposed. (D) Comparison of somatic input/event rate (left) and dendritic input/burst probability (right). Event rate and BF were rescaled using a linear decoder. Dashed lines represent the true inputs. The multiplexed code deteriorates when dendritic and somatic background currents are increased relative to Fig 4B. The values on the y-axis are external input strengths in pA. (E) Quality of the multiplexed burst code for increased background excitation, measured by the Pearson correlation coefficient between the two input currents and event rate (black) and burst fraction (red), respectively (see Methods). (F) Inhibitory plasticity restores the multiplexed burst code in a biological microcircuit without the need for fine-tuning the background input or noise levels. The microcircuit is similar to Fig 3, with constant external inputs, recurrent connections and plasticity on all inhibitory connections. Background excitation to both somatic and dendritic compartments was increased with 900 pA, where event rate (BF) is not informative of somatic (dendritic) input pulses. (G) The learning process increases the standard deviation of the net dendritic (red) and somatic (black) input currents. (H) Decoded inputs from the event rate (black) and BF (red) before and after learning, as in D. (I) Pearson correlation between actual and decoded inputs to quantify the quality of the multiplexed burst code over the course of learning (see Methods).