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Abstract Silicone‐based devices have the potential to achieve an ideal interface with nervous tissue but suffer from scalability, primarily due to the mechanical mismatch between established electronic materials and soft elastomer substrates. This study presents a novel approach using conventional electrode materials through multifunctional nanomesh to achieve reliable elastic microelectrodes directly on polydimethylsiloxane (PDMS) silicone with an unprecedented cellular resolution. This engineered nanomesh features an in‐plane nanoscale mesh pattern, physically embodied by a stack of three thin‐film materials by design, namely Parylene‐C for mechanical buffering, gold (Au) for electrical conduction, and Poly(3,4‐ethylenedioxythiophene)‐poly(styrenesulfonate) (PEDOT:PSS) for improved electrochemical interfacing. Nanomesh elastic neuroelectronics are validated using single‐unit recording from the small and curvilinear epidural surface of mouse dorsal root ganglia (DRG) with device self‐conformed and superior recording quality compared to plastic control devices requiring manual pressing is demonstrated. Electrode scaling studies from in vivo epidural recording further revealed the need for cellular resolution for high‐fidelity recording of single‐unit activities and compound action potentials. In addition to creating a minimally invasive device to effectively interface with DRG sensory afferents at a single‐cell resolution, this study establishes nanomeshing as a practical pathway to leverage traditional electrode materials for a new class of elastic neuroelectronics. 

We developed a neural network model that can account for major elements common to human focal seizures. These include the tonic-clonic transition, slow advance of clinical semiology and corresponding seizure territory expansion, widespread EEG synchronization, and slowing of the ictal rhythm as the seizure approaches termination. These were reproduced by incorporating usage-dependent exhaustion of inhibition in an adaptive neural network that receives global feedback inhibition in addition to local recurrent projections. Our model proposes mechanisms that may underline common EEG seizure onset patterns and status epilepticus, and postulates a role for synaptic plasticity in the emergence of epileptic foci. Complex patterns of seizure activity and bi-stable seizure end-points arise when stochastic noise is included. With the rapid advancement of clinical and experimental tools, we believe that this model can provide a roadmap and potentially an in silico testbed for future explorations of seizure mechanisms and clinical therapies.