It is widely appreciated that well-balanced excitation and inhibition are necessary for proper function in neural networks. However, in principle, such balance could be achieved by many possible configurations of excitatory and inhibitory strengths, and relative numbers of excitatory and inhibitory neurons. For instance, a given level of excitation could be balanced by either numerous inhibitory neurons with weak synapses, or few inhibitory neurons with strong synapses. Among the continuum of different but balanced configurations, why should any particular configuration be favored? Here we address this question in the context of the entropy of network dynamics by studying an analytically tractable network of binary neurons. We find that entropy is highest at the boundary between excitation-dominant and inhibition-dominant regimes. Entropy also varies along this boundary with a trade-off between high and robust entropy: weak synapse strengths yield high network entropy which is fragile to parameter variations, while strong synapse strengths yield a lower, but more robust, network entropy. In the case where inhibitory and excitatory synapses are constrained to have similar strength, we find that a small, but non-zero fraction of inhibitory neurons, like that seen in mammalian cortex, results in robust and relatively high entropy.

Lysenin is a pore-forming toxin, which self-inserts open channels into sphingomyelin containing membranes and is known to be voltage regulated. The mechanistic details of its voltage gating mechanism, however, remains elusive despite much recent efforts. Here, we have employed a novel combination of experimental and computational techniques to examine a model for voltage gating, that is based on the existence of an “effective electric dipole” inspired by recent reported structures of lysenin. We support this mechanism by the observations that (i) the charge-reversal and neutralization substitutions in lysenin result in changing its electrical gating properties by modifying the strength of the dipole, and (ii) an increase in the viscosity of the solvent increases the drag force and slows down the gating. In addition, our molecular dynamics (MD) simulations of membrane-embedded lysenin provide a mechanistic picture for lysenin conformational changes, which reveals, for the first time, the existence of a lipid-dependent bulge region in the pore-forming module of lysenin, which may explain the gating mechanism of lysenin at a molecular level.

No abstract