Table 1.

Criticality parameters and metrics with details of their formulation

Notation	Definition	Formulation
α	Calculated exponent for the truncated power law distribution fitted on avalanche duration, D (time).	$f\left(D\right)=\frac{D^{-\alpha }}{{\sum }_{D_{\min }}^{D_{\max }}{D}^{-\alpha }}$, where maximum likelihood estimation was used to fit a truncated power law to the avalanche duration distribution (f(D)).
τ	Calculated exponent for the truncated power law distribution fitted on avalanche size, S (number of spikes).	$f\left(S\right)=\frac{S^{-\tau }}{{\sum }_{S_{\min }}^{S_{\max }}{S}^{-\tau }}$, where maximum likelihood estimation was used to fit a truncated power law to the avalanche size distribution (f(S)).
βpred	The third hidden power law exponent in critical systems which represents the relationship between size and duration exponents.	${\beta }_{\mathrm{pred}}=\frac{\left(\alpha -1\right)}{\left(\tau -1\right)}$.
DCC	Deviation from criticality coefficient.	DCC = ∣βpred − βfit∣, where $⟨S⟩\propto D^{{\beta }_{\mathrm{fit}}}$.
BR	Branching ratio is the ratio of the number of neurons spiking at time step t + 1 to the number of active neurons at time step t.	〈N(t + 1)∣N(t)〉 = BR ⋅ N(t) + h, where N(t) is the number of active neurons at time t and h is the external drive.
SC error	Avalanche profiles of all sizes are copies of each other as they unfold from different scales, and they all collapse to the same universal shape. A collection of scaling functions (F(. )) are extracted for various D durations. The error for this process is described as: $\frac{\mathrm{var}\left(F\right)}{{\left(\max \left(F\right)-\min \left(F\right)\right)}^2}$.	$s\left(t,D\right)\propto D^{\gamma }F\left(\frac{t}{D}\right)$, where $⟨S⟩\left(D\right)={\int }_0^{D}s\left(t,D\right)dt,F\left(\frac{t}{D}\right)$ is a universal function for all avalanches, γ = β − 1, and SC error is  ∣β −  βpred∣  when $\frac{\mathrm{var}\left(F\right)}{{\left(\max \left(F\right)-\min \left(F\right)\right)}^2}$ is minimised.