Speaker
Description
Local field potentials (LFPs), the low-frequency component of the extracellular potential, are widely interpreted as readouts of population synaptic activity¹, an assumption derived almost entirely from cortical recordings. Whether these principles extend to subcortical structures remains unclear. Here, 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 disease². We built a biophysically detailed population model of the STN and validated it against patient microelectrode recordings³. As in the cortex, we found that STN extracellular potentials were dominated by synaptic currents. Unlike in the cortex⁴, however, LFPs could not be reliably predicted from these currents or from other average population measures. We showed that this discrepancy arises from the STN's symmetric neuronal morphology and lack of recurrent connectivity, which promote destructive interference among single-neuron contributions, thereby decoupling the LFP from population-level dynamics. However, this decoupling was not absolute: when we introduced pathological beta synchrony and constrained the model using experimental data, a robust synapse–LFP relationship was restored through more consistent underlying dynamics. Furthermore, even in asynchronous settings, we found that 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.
- https://doi.org/10.1038/nrn3599.
- https://doi.org/10.1002/ana.23951.
- https://doi.org/10.1073/pnas.2205881119.
- https://doi.org/10.1371/journal.pcbi.1004584.
| Preferred Presentation | Oral Presentation |
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