Flexible neural interfaces capable of monitoring subcortical neuronal activity facilitate the study of deep brain neural circuits and their interactions with the cortex. However, there exists a paucity of translational tools for interfacing subcortical nuclei surfaces within the intraventricular cerebrospinal fluid. Here, we developed a flexible and conformal intraventricular interface (IVI) featuring a deformable microelectrode array paired with a silk scaffold. The IVI can be minimally invasively implanted into the lateral ventricles with the assistance of commonly used clinical catheters, self-unfolding in the cerebrospinal fluid environment to conformally attach to the surfaces of periventricular neural structures, and capturing high-quality signals by virtue of the microelectrode’s in-plane shielding. In parkinsonian ewes, the IVI detects deep brain abnormalities and achieves stable, biocompatible in vivo recordings for four weeks. This platform enables chronic monitoring and circuit analysis of healthy and diseased deep brain regions, facilitating studies of neural circuits between periventricular surface neurons and distant brain areas.

pdf/silk-enabled-conformal-intraventricular-interfaces-for-ral3qyl64d1n.pdf

Silk-enabled conformal intraventricular interfaces for minimally invasive neural recordings

Silk-Based Self-Unfolding Electrode Array for Minimally-invasive Large-Scale Deep Brain Activity Monitoring

We report a real-time functional brain mapping technique based on high-channel-count, ultra-conformal electrocorticographic (ECoG) electrodes. The MEMSbased 64-channel ECoG electrodes can well conform to the curvilinear surface of the cortex, thus showing good neural signal recording quality. This neural interface was applied to Labrador dogs for delineating cortical areas related to eyelid, nose, and limb motor function. The result was in strong congruence to that derived by electrical cortical stimulation (ECS) mapping, which is the gold standard in mapping the eloquent cortex. Our method can provide an instant functional map, which promises a great potential of this technique in the realtime passive functional mapping of the eloquent cortex.

Real-Time Functional Brain Mapping Based on High-Channel-Count, Ultra-Conformal Neural Interface

We report a microelectrode array (MEA) system that enables stimulation and in situ electrophysiological recording by integrating a 32-channel microelectrode array with highly transparency fabricated on a glass substrate. The specially designed double shielding rings allow to reduce electromagnetic shielding and reduced the noise of the MEA to only about 3 µV, which is much lower than that of commercial electrodes with around 10µV [1]. As a proof of concept, simultaneous electrical stimulation and electrophysiological recordings with signal to noise ratios up to 30 were achieved in cellular models. In contrast to existing technologies, our MEA will allow to specifically modulate the activity of neurons.

A Low Noise Microelectrode Array for Specific Cell Activity Modulation from Cell to Tissue

This paper reports a flexible, foldable and conformal neural interface with in-plane shielding fabricated by MEMS process. Based on the tailored planar pattern derived from hemisphere, it can conformally attach to curved surfaces with featured radiuses of typical intracranial space-occupying tumors or brain nuclei. Introducing the controlled degradable silk fibroin as the temporary immobilization material, it can be temporarily fixed into ball shape to minimize implantation trauma during surgery, and conformally cover the curved surface after silk dissolved by tissue fluids, which makes it suitable for electrophysiological monitoring of deep brain regions. Additionally, coplanar metal shielding layer design reduces the interference of mechanical artifacts and power frequency noises, which significantly improves the quality of recorded signals.

Silk-Enabled Foldable and Conformal Neural Interface with In-Plane Shielding for High-Quality Electrophysiological Recordings

A Silk-Based Multifunctional and Bidirectional Neural Interface

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