The postsynaptic adhesion protein neuroligin-2 (NL2) is selectively localized at inhibitory synapses. Here, we studied network activity in the dentate gyrus of NL2-deficient mice following perforant path (PP) stimulation in vivo. We found a strong increase in granule cell (GC) excitability. Furthermore, paired-pulse inhibition (PPI) of the population spike, a measure for γ-aminobutyric acid (GABA)ergic network inhibition, was severely impaired and associated with reduced GABA_A receptor (GABA_AR)–mediated miniature inhibitory postsynaptic currents recorded from NL2-deficient GCs. In agreement with these functional data, the number of gephyrin and GABA_AR clusters was significantly reduced in the absence of NL2, indicating a loss of synaptic GABA_ARs from the somata of GCs. Computer simulations of the dentate network showed that impairment of perisomatic inhibition is able to explain the electrophysiological changes observed in the dentate circuitry of NL2 knockout animals. Collectively, our data demonstrate for the first time that deletion of NL2 increases excitability of cortical neurons in the hippocampus of intact animals, most likely through impaired GABA_AR clustering.

The nervous system is a nonlinear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of nonlinear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system’s behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in nonneuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a nontrivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics.