Interpreting the Entire Connectivity of Individual Neurons in Micropatterned Neural Culture With an Integrated Connectome Analyzer of a Neuronal Network (iCANN)

Approaches for Memristive Structures Using Scratching Probe Nanolithography: Towards Neuromorphic Applications

This paper proposes two different approaches to studying resistive switching of oxide thin films using scratching probe nanolithography of atomic force microscopy (AFM). These approaches allow us to assess the effects of memristor size and top-contact thickness on resistive switching. For that purpose, we investigated scratching probe nanolithography regimes using the Taguchi method, which is known as a reliable method for improving the reliability of the result. The AFM parameters, including normal load, scratch distance, probe speed, and probe direction, are optimized on the photoresist thin film by the Taguchi method. As a result, the pinholes with diameter ranged from 25.4 ± 2.2 nm to 85.1 ± 6.3 nm, and the groove array with a depth of 40.5 ± 3.7 nm and a roughness at the bottom of less than a few nanometers was formed. Then, based on the Si/TiN/ZnO/photoresist structures, we fabricated and investigated memristors with different spot sizes and TiN top contact thickness. As a result, the HRS/LRS ratio, U_SET, and I_LRS are well controlled for a memristor size from 27 nm to 83 nm and ranged from ~8 to ~128, from 1.4 ± 0.1 V to 1.8 ± 0.2 V, and from (1.7 ± 0.2) × 10^-10 A to (4.2 ± 0.6) × 10^-9 A, respectively. Furthermore, the HRS/LRS ratio and U_SET are well controlled at a TiN top contact thickness from 8.3 ± 1.1 nm to 32.4 ± 4.2 nm and ranged from ~22 to ~188 and from 1.15 ± 0.05 V to 1.62 ± 0.06 V, respectively. The results can be used in the engineering and manufacturing of memristive structures for neuromorphic applications of brain-inspired artificial intelligence systems.

Nanoscale Patterning of In Vitro Neuronal Circuits

Methods for patterning neurons in vitro have gradually improved and are used to investigate questions that are difficult to address in or ex vivo. Though these techniques guide axons between groups of neurons, multiscale control of neuronal connectivity, from circuits to synapses, is yet to be achieved in vitro. As studying neuronal circuits with synaptic resolution in vivo poses significant challenges, we present an in vitro alternative to validate biophysical and computational models. In this work we use a combination of electron beam lithography and photolithography to create polydimethylsiloxane (PDMS) structures with features ranging from 150 nm to a few millimeters. Leveraging the difference between average axon and dendritic spine diameters, we restrict axon growth while allowing spines to pass through nanochannels to guide synapse formation between small groups of neurons (i.e., nodes). We show this technique can be used to generate large numbers of isolated feed-forward circuits where connections between nodes are restricted to regions connected by nanochannels. Using a genetically encoded calcium indicator in combination with fluorescently tagged postsynaptic protein, PSD-95, we demonstrate functional synapses can form in this region.

Single-cell patterning regulation by physically modified silicon nanostructures

Chemically and biologically modified substrates for single-cell patterning have been studied extensively, but physically modified structures for single-cell patterning still need further study. In this paper, physically modified silicon nanostructures were introduced to study their effect on SHSY5Y cells. Double-beam double exposure laser interference lithography combined with metal-assisted etching (MACE) was used to fabricate the physically modified silicon nanostructures. It was found that the cells on the gratings stretched and grew orderly along the grating with a small cell area and almost the same cell length compared with those on the Si wafer (control group). While on the grids, the cells were round with limited spreading, grew independently and had the smallest cell area and cell length. Moreover, the localization ratio of cells adhered onto the areas of nanopillars in the grid structures with different periods has been investigated. The results suggest that the physically modified grid silicon nanostructures can regulate the single-cell localization growth and the rational design of substrate structures can maximize the single-cell localization ratio. The findings provide guidance for the design of physically modified nanostructures and regulating single cell patterning, and a better understanding of single-cell localized growth.

Two-Wavelength Computational Holography for Aberration-Corrected Simultaneous Optogenetic Stimulation and Inhibition of In Vitro Biological Samples

Optogenetics is a versatile toolset for the functional investigation of excitable cells such as neurons and cardiomyocytes in vivo and in vitro. While monochromatic illumination of these cells for either stimulation or inhibition already enables a wide range of studies, the combination of activation and silencing in one setup facilitates new experimental interrogation protocols. In this work, we present a setup for the simultaneous holographic stimulation and inhibition of multiple cells in vitro. The system is based on two fast ferroelectric liquid crystal spatial light modulators with frame rates of up to 1.7 kHz. Thereby, we are able to illuminate up to about 50 single spots with better than cellular resolution and without crosstalk, perfectly suited for refined network analysis schemes. System-inherent aberrations are corrected by applying an iterative optimization scheme based on Zernike polynomials. These are superposed on the same spatial light modulators that display the pattern-generating holograms, hence no further adaptive optical elements are needed for aberration correction. A near-diffraction-limited spatial resolution is achieved over the whole field of view, enabling subcellular optogenetic experiments by just choosing an appropriate microscope objective. The setup can pave the way for a multitude of optogenetic experiments, in particular with cardiomyocytes and neural networks.