A low-noise, modular, and versatile analog front-end intended for processing in vitro neuronal signals detected by microelectrode arrays

Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments

Objective.Neural activity represents a functional readout of neurons that is increasingly important to monitor in a wide range of experiments. Extracellular recordings have emerged as a powerful technique for measuring neural activity because these methods do not lead to the destruction or degradation of the cells being measured. Current approaches to electrophysiology have a low throughput of experiments due to manual supervision and expensive equipment. This bottleneck limits broader inferences that can be achieved with numerous long-term recorded samples.Approach.We developed Piphys, an inexpensive open source neurophysiological recording platform that consists of both hardware and software. It is easily accessed and controlled via a standard web interface through Internet of Things (IoT) protocols.Main results.We used a Raspberry Pi as the primary processing device along with an Intan bioamplifier. We designed a hardware expansion circuit board and software to enable voltage sampling and user interaction. This standalone system was validated with primary human neurons, showing reliability in collecting neural activity in near real-time.Significance.The hardware modules and cloud software allow for remote control of neural recording experiments as well as horizontal scalability, enabling long-term observations of development, organization, and neural activity at scale.

Superior galvanostatic electrochemical deposition of platinum nanograss provides high performance planar microelectrodes forin vitroneural recording

Objective.Platinum nanograss (Ptng) has been demonstrated as an excellent coating to increase the electrode roughness and reduce the impedance of microelectrodes for neural recording. However, the optimisation of the original potentiostatic electrochemical deposition (PSED) method has been performed by the original group only and noin vitrovalidation of functionality was reported.Approach.This study firstly reinvestigates the use of the PSED method for Ptng coating at different charge densities which highlights non-uniformities in the edges of the microelectrodes for increasing deposition charge densities, leading to a decreased impedance which is in fact an artefact. We then introduce a novel Ptng fabrication method of galvanostatic electrochemical deposition (GSED).Main results.We demonstrate that the GSED deposition method also significantly reduces the electrode impedance, raises the charge storage capacity and provides a significantly more planar electrode surface in comparison to the PSED method with negligible edge effects. In addition, we demonstrate how high-quality neural recordings were performed, for the first time, using the Ptng GSED deposition microelectrodes from human hNT neurons and how spiking and bursting were observed.Significance.Thus, the GSED Ptng deposition method presented here provides an alternative method of microelectrode fabrication for neural applications with excellent impedance and planarity of surface.

A biomimetic soft robotic pinna for emulating dynamic reception behavior of horseshoe bats

Encoding of sensory information is fundamental to closing the performance gap between man-made and biological sensing. It has been hypothesized that the coupling of sensing and actuation, a phenomenon observed in bats among other species, is critical to accomplishing this. Using horseshoe bats as a model, we have developed a biomimetic pinna model with a soft actuation system along with a prototype strain sensor for enabling motor feedback. The actuation system used three individually controlled pneumatic actuators per pinna which actuated different portions of the baffle. This prototype produced eight different possible motions that were shown to have significant effects on incoming sound and could hence function as a substrate for adaptive sensing. The range of possible motions could be expanded by adjusting the fill and release parameters of the actuation system. Additionally, the strain sensor was able to represent the deformation of the pinna as measurements from this sensor were highly correlated with deformation estimates based on stereo vision. However, the relationship between displacements of points on the pinna and the sensor output was nonlinear. The improvements embodied in the system discussed here could lead to enhancements in the ability of autonomous systems to encode relevant information about the real world.