Cell diversity and network dynamics in photosensitive human brain organoids.

In vitro models of the developing brain such as three-dimensional brain organoids offer an unprecedented opportunity to study aspects of human brain development and disease. However, the cells generated within organoids and the extent to which they recapitulate the regional complexity, cellular diversity and circuit functionality of the brain remain undefined. Here we analyse gene expression in over 80,000 individual cells isolated from 31 human brain organoids. We find that organoids can generate a broad diversity of cells, which are related to endogenous classes, including cells from the cerebral cortex and the retina. Organoids could be developed over extended periods (more than 9 months), allowing for the establishment of relatively mature features, including the formation of dendritic spines and spontaneously active neuronal networks. Finally, neuronal activity within organoids could be controlled using light stimulation of photosensitive cells, which may offer a way to probe the functionality of human neuronal circuits using physiological sensory stimuli.

Automated in vivo patch-clamp evaluation of extracellular multielectrode array spike recording capability.

Much innovation is currently aimed at improving the number, density, and geometry of electrodes on extracellular multielectrode arrays for in vivo recording of neural activity in the mammalian brain. To choose a multielectrode array configuration for a given neuroscience purpose, or to reveal design principles of future multielectrode arrays, it would be useful to have a systematic way of evaluating the spike recording capability of such arrays. We describe an automated system that performs robotic patch-clamp recording of a neuron being simultaneously recorded via an extracellular multielectrode array. By recording a patch-clamp data set from a neuron while acquiring extracellular recordings from the same neuron, we can evaluate how well the extracellular multielectrode array captures the spiking information from that neuron. To demonstrate the utility of our system, we show that it can provide data from the mammalian cortex to evaluate how the spike sorting performance of a close-packed extracellular multielectrode array is affected by bursting, which alters the shape and amplitude of spikes in a train. We also introduce an algorithmic framework to help evaluate how the number of electrodes in a multielectrode array affects spike sorting, examining how adding more electrodes yields data that can be spike sorted more easily. Our automated methodology may thus help with the evaluation of new electrode designs and configurations, providing empirical guidance on the kinds of electrodes that will be optimal for different brain regions, cell types, and species, for improving the accuracy of spike sorting. NEW & NOTEWORTHY We present an automated strategy for evaluating the spike recording performance of an extracellular multielectrode array, by enabling simultaneous recording of a neuron with both such an array and with patch clamp. We use our robot and accompanying algorithms to evaluate the performance of multielectrode arrays on supporting spike sorting.

Three-dimensional multiwaveguide probe array for light delivery to distributed brain circuits.

To deliver light to the brain for neuroscientific and neuroengineering applications like optogenetics, in which light is used to activate or silence neurons expressing specific photosensitive proteins, optical fibers are commonly used. However, an optical fiber is limited to delivering light to a single target within the 3D structure of the brain. Here, we describe the design and fabrication of an array of thin microwaveguides, which terminates at a three-dimensionally distributed set of points, appropriate for delivering light to targets distributed in a 3D pattern throughout the brain.

Scalable, Modular Three-Dimensional Silicon Microelectrode Assembly via Electroless Plating.

We devised a scalable, modular strategy for microfabricated 3-D neural probe synthesis. We constructed a 3-D probe out of individual 2-D components (arrays of shanks bearing close-packed electrodes) using mechanical self-locking and self-aligning techniques, followed by electroless nickel plating to establish electrical contact between the individual parts. We detail the fabrication and assembly process and demonstrate different 3-D probe designs bearing thousands of electrode sites. We find typical self-alignment accuracy between shanks of <0.2° and demonstrate orthogonal electrical connections of 40 µm pitch, with thousands of connections formed electrochemically in parallel. The fabrication methods introduced allow the design of scalable, modular electrodes for high-density 3-D neural recording. The combination of scalable 3-D design and close-packed recording sites may support a variety of large-scale neural recording strategies for the mammalian brain.

Multiplexed neural recording along a single optical fiber via optical reflectometry.

We introduce the design and theoretical analysis of a fiber-optic architecture for neural recording without contrast agents, which transduces neural electrical signals into a multiplexed optical readout. Our sensor design is inspired by electro-optic modulators, which modulate the refractive index of a waveguide by applying a voltage across an electro-optic core material. We estimate that this design would allow recording of the activities of individual neurons located at points along a 10-cm length of optical fiber with 40-µm axial resolution and sensitivity down to 100 µV using commercially available optical reflectometers as readout devices. Neural recording sites detect a potential difference against a reference and apply this potential to a capacitor. The waveguide serves as one of the plates of the capacitor, so charge accumulation across the capacitor results in an optical effect. A key concept of the design is that the sensitivity can be improved by increasing the capacitance. To maximize the capacitance, we utilize a microscopic layer of material with high relative permittivity. If suitable materials can be found­possessing high capacitance per unit area as well as favorable properties with respect to toxicity, optical attenuation, ohmic junctions, and surface capacitance­then such sensing fibers could, in principle, be scaled down to few-micron cross-sections for minimally invasive neural interfacing. We study these material requirements and propose potential material choices. Custom-designed multimaterial optical fibers, probed using a reflectometric readout, may, therefore, provide a powerful platform for neural sensing.

Close-Packed Silicon Microelectrodes for Scalable Spatially Oversampled Neural Recording.

OBJECTIVE: Neural recording electrodes are important tools for understanding neural codes and brain dynamics. Neural electrodes that are closely packed, such as in tetrodes, enable spatial oversampling of neural activity, which facilitates data analysis. Here we present the design and implementation of close-packed silicon microelectrodes to enable spatially oversampled recording of neural activity in a scalable fashion. METHODS: Our probes are fabricated in a hybrid lithography process, resulting in a dense array of recording sites connected to submicron dimension wiring. RESULTS: We demonstrate an implementation of a probe comprising 1000 electrode pads, each 9 × 9 µm, at a pitch of 11 µm. We introduce design automation and packaging methods that allow us to readily create a large variety of different designs. SIGNIFICANCE: We perform neural recordings with such probes in the live mammalian brain that illustrate the spatial oversampling potential of closely packed electrode sites.

Heterogeneous neural amplifier integration for scalable extracellular microelectrodes.

We here demonstrate multi-chip heterogeneous integration of microfabricated extracellular recording electrodes with neural amplifiers, highlighting a path to scaling electrode channel counts without the need for more complex monolithic integration. We characterize the noise and impedance performance of the heterogeneously integrated neural recording electrodes, and analyze the design parameters that enable the low-voltage neural input signals to co-exist with the high-frequency and high-voltage digital outputs on the same silicon substrate. This heterogeneous integration approach can enable future scaling efforts for microfabricated neural probes, and provides a design path for modular, fast, and independent scaling innovations in recording electrodes and neural amplifiers.

A direct-to-drive neural data acquisition system.

Driven by the increasing channel count of neural probes, there is much effort being directed to creating increasingly scalable electrophysiology data acquisition (DAQ) systems. However, all such systems still rely on personal computers for data storage, and thus are limited by the bandwidth and cost of the computers, especially as the scale of recording increases. Here we present a novel architecture in which a digital processor receives data from an analog-to-digital converter, and writes that data directly to hard drives, without the need for a personal computer to serve as an intermediary in the DAQ process. This minimalist architecture may support exceptionally high data throughput, without incurring costs to support unnecessary hardware and overhead associated with personal computers, thus facilitating scaling of electrophysiological recording in the future.