Abstract

Local field potentials (LFPs) are widely interpreted as readouts of population synaptic activity, an assumption derived almost entirely from cortical recordings. Whether these principles extend to subcortical structures remains unclear. We address this question in the subthalamic nucleus (STN), where LFPs are routinely recorded and used to guide adaptive deep brain stimulation for Parkinson's disease, using a biophysically detailed population model benchmarked against patient microelectrode recordings. As in the cortex, STN extracellular potentials were dominated by synaptic currents. Differently from the cortex, however, LFPs could not be reliably predicted from these currents or other average population quantities. This dissociation arises from the STN's symmetric neuronal morphology and lack of recurrent connectivity, which promote destructive interference among single-neuron contributions, decoupling the LFP from population-level dynamics. This decoupling was not absolute: pathological beta synchrony restored a robust synapse-LFP relationship by consistent underlying dynamics, while the aperiodic slope of the power spectral density tracked STN neuronal morphology, firing rate, and excitatory-inhibitory balance. Together, these findings challenge the prevailing view of LFPs as universal readouts of population activity. Our results show that the interpretability of extracellular signals depends critically on neuronal morphology and synchronization state, and provide a mechanistic framework for the use of STN LFPs as biomarkers in adaptive deep brain stimulation for Parkinson's disease.