Engineered Biological Neural Networks on High Density CMOS Microelectrode Arrays

Abstract

In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.

Microfluidic cell engineering on high-density microelectrode arrays for assessing structure-function relationships in living neuronal networks

“…Multiple methods, including laser lithography ( Schürmann et al, 2018 ), microcontact printing ( James et al, 2000 ; Nam et al, 2006 ), agarose-gel patterning ( Suzuki et al, 2005 ; Hong and Nam, 2020 ), and microfluidic devices ( Pan et al, 2015 ; Forró et al, 2018 ), have been used to pattern dissociated neurons on MEAs. Patterning dissociated neurons on HD-MEA has been demonstrated using microfluidic devices, firstly by Lewandowska et al (2015) and later by Kim et al (2020) and Duru et al (2022) . The major challenge in patterning neurons on HD-MEA devices lies in the surface topography of the device, which originates in the passivation layer and the underlying electronics, which inhibit stable sealing of the microfluidic device, as was shown in Figure 1C .…”

“…The studies have revealed several non-random properties such as the modular architecture as a structure that is evolutionarily conserved in the nervous system ( van den Heuvel et al, 2016 ) and provided mechanistic insights into how network structure defines system functions in both normal and pathological brains ( Lynn and Bassett, 2019 ; van den Heuvel and Sporns, 2019 ; Suárez et al, 2021 ). While many studies have deciphered the structure-function relationships in the nervous system in vivo ( Meunier et al, 2010 ; Lee et al, 2016 ), recent advances in cell engineering technology using micropatterned proteins and microfluidic devices have enabled the use of cultured cells to study these relationships in a well-defined in vitro system ( Feinerman et al, 2008 ; Lewandowska et al, 2015 ; Pan et al, 2015 ; Albers and Offenhäusser, 2016 ; Yamamoto et al, 2016b , 2018 ; Forró et al, 2018 ; Hong and Nam, 2020 , 2022 ; Takemuro et al, 2020 ; Duru et al, 2022 ; Ihle et al, 2022 ).…”

“…Recently, high-density MEA (HD-MEA) technology has been developed to mitigate the trade-off problem between spatial and temporal resolutions ( Berdondini et al, 2009 ; Frey et al, 2010 ; Hierlemann et al, 2011 ; Bertotti et al, 2014 ; Obien et al, 2015 ; Yuan et al, 2020 ; Steinmetz et al, 2021 ). More precisely, recent HD-MEA devices offer spatial resolutions of over 3,000 electrodes mm –2 with the electrode pitch below 20 μm and a temporal resolution below 100 μs ( Bertotti et al, 2014 ; Lewandowska et al, 2015 ; Kim et al, 2020 ; Yuan et al, 2020 ; Steinmetz et al, 2021 ; Duru et al, 2022 ; Shimba et al, 2022 ). The electrode pitch is comparable to the size of a neuronal cell body, and the temporal resolution is higher than a typical delay of synaptic transmission (∼0.6 ms) ( Lisman et al, 2007 ).…”

“…Here, we fabricated neuronal networks possessing a modular architecture on HD-MEA using a polydimethylsiloxane (PDMS) microfluidic film and recorded their spontaneous activity at a resolution of 50 μs. Engineering neuronal networks of HD-MEA has been challenging due to the surface topography originating in the passivation layer and the underlying electronics of the device ( Frey et al, 2010 ; Hierlemann et al, 2011 ), which inhibits stable sealing of microfluidic devices ( Duru et al, 2022 ). We resolved this issue by coating the HD-MEA surface with a cell-permissive hydrogel which smoothened the surface topography of the HD-MEA, enabling a gap-less adhesion of the PDMS microfluidic film to the HD-MEA.…”

Topologically controlled circuits of human iPSC-derived neurons for electrophysiology recordings

“…Second, the current layout of the PDMS circuit is constrained by the need to interface it with a 60-electrode MEA layout and only allows recording and stimulating from specific positions in the system. By using a high-density CMOS MEA, which was recently shown to be compatible with PDMS microstructures, 73 such design constraints could be eliminated and any part of the circuits could be recorded from and stimulated. This would however complicate imaging assays, as high-density CMOS MEAs are not transparent.…”