Structural plasticity for neuromorphic networks with electropolymerized dendritic PEDOT connections.

Neural networks are powerful tools for solving complex problems, but finding the right network topology for a given task remains an open question. Biology uses neurogenesis and structural plasticity to solve this problem. Advanced neural network algorithms are mostly relying on synaptic plasticity and learning. The main limitation in reconciling these two approaches is the lack of a viable hardware solution that could reproduce the bottom-up development of biological neural networks. Here, we show how the dendritic growth of PEDOT:PSS-based fibers through AC electropolymerization can implement structural plasticity during network development. We find that this strategy follows Hebbian principles and is able to define topologies that leverage better computing performances with sparse synaptic connectivity for solving non-trivial tasks. This approach is validated in software simulation, and offers up to 61% better network sparsity on classification and 50% in signal reconstruction tasks.

Electropolymerization processing of side-chain engineered EDOT for high performance microelectrode arrays.

Microelectrode Arrays (MEAs) are popular tools for in vitro extracellular recording. They are often optimized by surface engineering to improve affinity with neurons and guarantee higher recording quality and stability. Recently, PEDOT:PSS has been used to coat microelectrodes due to its good biocompatibility and low impedance, which enhances neural coupling. Herein, we investigate on electro-co-polymerization of EDOT with its triglymated derivative to control valence between monomer units and hydrophilic functions on a conducting polymer. Molecular packing, cation complexation, dopant stoichiometry are governed by the glycolation degree of the electro-active coating of the microelectrodes. Optimal monomer ratio allows fine-tuning the material hydrophilicity and biocompatibility without compromising the electrochemical impedance of microelectrodes nor their stability while interfaced with a neural cell culture. After incubation, sensing readout on the modified electrodes shows higher performances with respect to unmodified electropolymerized PEDOT, with higher signal-to-noise ratio (SNR) and higher spike counts on the same neural culture. Reported SNR values are superior to that of state-of-the-art PEDOT microelectrodes and close to that of state-of-the-art 3D microelectrodes, with a reduced fabrication complexity. Thanks to this versatile technique and its impact on the surface chemistry of the microelectrode, we show that electro-co-polymerization trades with many-compound properties to easily gather them into single macromolecular structures. Applied on sensor arrays, it holds great potential for the customization of neurosensors to adapt to environmental boundaries and to optimize extracted sensing features.

Precision of neuronal localization in 2D cell cultures by using high-performance electropolymerized microelectrode arrays correlated with optical imaging.

Recently, the development of electronic devices to extracellularly record the simultaneous electrical activities of numerous neurons has been blooming, opening new possibilities to interface and decode neuronal activity. In this work, we tested how the use of EDOT electropolymerization to tune post-fabrication materials could optimize the cell/electrode interface of such devices. Our results showed an improved signal-to-noise ratio, better biocompatibility, and a higher number of neurons detected in comparison with gold electrodes. Then, using such enhanced recordings with 2D neuronal cultures combined with fluorescent optical imaging, we checked the extent to which the positions of the recorded neurons could be estimated solely via their extracellular signatures. Our results showed that assuming neurons behave as monopoles, positions could be estimated with a precision of approximately tens of micrometers.