GABAergic-like dopamine synapses in the brain.

Dopamine synapses play a crucial role in volitional movement and reward-related behaviors, while dysfunction of dopamine synapses causes various psychiatric and neurological disorders. Despite this significance, the true biological nature of dopamine synapses remains poorly understood. Here, we show that dopamine transmission is strongly correlated with GABA co-transmission across the brain and dopamine synapses are structured and function like GABAergic synapses with marked regional heterogeneity. In addition, GABAergic-like dopamine synapses are clustered on the dendrites, and GABA transmission at dopamine synapses has distinct physiological properties. Interestingly, the knockdown of neuroligin-2, a key postsynaptic protein at GABAergic synapses, unexpectedly does not weaken GABA co-transmission but instead facilitates it at dopamine synapses in the striatal neurons. More importantly, the attenuation of GABA co-transmission precedes deficits in dopaminergic transmission in animal models of Parkinson's disease. Our findings reveal the spatial and functional nature of GABAergic-like dopamine synapses in health and disease.

Fast diffraction-limited image recovery through turbulence via subsampled bispectrum analysis.

Imaging through temporally changing aberrations is a common challenge that can be found in many different fields such as astronomy, long-range surveillance, and deep tissue bioimaging. Based on the notions originally developed in speckle interferometry, time-varying aberrations can be used to our advantage to obtain diffraction-limited resolution images through turbulence via bispectrum analysis. However, due to the heavy computational load brought on by the triple correlation and the phase extraction process, widespread use has been limited. Here, we demonstrate a Fourier domain subsampling scheme that can accelerate the speed of bispectrum analysis by more than 2 orders of magnitude. In contrast to other approaches for parallelization such as those based on Radon transform or image segmentation, our proposed method enables diffraction-limited imaging without suffering from resolution loss or image artifacts.