Connectivity and Dynamics Underlying Synaptic Control of the Subthalamic Nucleus.

Adaptive motor control critically depends on the interconnected nuclei of the basal ganglia in the CNS. A pivotal element of the basal ganglia is the subthalamic nucleus (STN), which serves as a therapeutic target for deep brain stimulation (DBS) in movement disorders, such as Parkinson's disease. The functional connectivity of the STN at the microcircuit level, however, still requires rigorous investigation. Here we combine multiple simultaneous whole-cell recordings with extracellular stimulation and neuroanatomical analysis to investigate intrinsic and afferent connectivity and synaptic properties of the STN in acute brain slices obtained from rats of both sexes. Our data reveal an absence of intrinsic connectivity and an afferent innervation with low divergence, suggesting that STN neurons operate as independent processing elements driven by upstream structures. Hence, synchrony in the STN, a hallmark of motor processing, exclusively depends on the interactions and dynamics of GABAergic and glutamatergic afferents. Importantly, these inputs are subject to differential short-term depression when stimulated at high, DBS-like frequencies, shifting the balance of excitation and inhibition toward inhibition. Thus, we present a mechanism for fast yet transient decoupling of the STN from synchronizing afferent control. Together, our study provides new insights into the microcircuit organization of the STN by identifying its neurons as parallel processing units and thus sets new constraints for future computational models of the basal ganglia. The observed differential short-term plasticity of afferent inputs further offers a basis to better understand and optimize DBS algorithms. The subthalamic nucleus (STN) is a pivotal element of the basal ganglia and serves as target for deep brain stimulation, but information on the functional connectivity of its neurons is limited. To investigate the STN microcircuitry, we combined multiple simultaneous patch-clamp recordings and neuroanatomical analysis. Our results provide new insights into the synaptic organization of the STN identifying its neurons as parallel processing units and thus set new constraints for future computational models of the basal ganglia. We further find that synaptic dynamics of afferent inputs result in a rapid yet transient decoupling of the STN when stimulated at high frequencies. These results offer a better understanding of deep brain stimulation mechanisms, promoting the development of optimized algorithms.