Action potential propagation recorded from single axonal arbors using multielectrode arrays

Beyond a Transmission Cable-New Technologies to Reveal the Richness in Axonal Electrophysiology

The axon is a neuronal structure capable of processing, encoding, and transmitting information. This assessment contrasts with a limiting, but deeply rooted, perspective where the axon functions solely as a transmission cable of somatodendritic activity, sending signals in the form of stereotypical action potentials. This perspective arose, at least partially, because of the technical difficulties in probing axons: their extreme length-to-diameter ratio and intricate growth paths preclude the study of their dynamics through traditional techniques. Recent findings are challenging this view and revealing a much larger repertoire of axonal computations. Axons display complex signaling processes and structure-function relationships, which can be modulated via diverse activity-dependent mechanisms. Additionally, axons can exhibit patterns of activity that are dramatically different from those of their corresponding soma. Not surprisingly, many of these recent discoveries have been driven by novel technology developments, which allow for in vitro axon electrophysiology with unprecedented spatiotemporal resolution and signal-to-noise ratio. In this review, we outline the state-of-the-art in vitro toolset for axonal electrophysiology and summarize the recent discoveries in axon function it has enabled. We also review the increasing repertoire of microtechnologies for controlling axon guidance which, in combination with the available cutting-edge electrophysiology and imaging approaches, have the potential for more controlled and high-throughput in vitro studies. We anticipate that a larger adoption of these new technologies by the neuroscience community will drive a new era of experimental opportunities in the study of axon physiology and consequently, neuronal function.

Interactions between cathodic- and anodic-pulses during high-frequency stimulations with the monophasic-pulses alternating in polarity at axons-experiment and simulation studies

Background. Electrical neuromodulation therapies commonly utilize high-frequency stimulations (HFS) of biphasic-pulses to treat neurological disorders. The biphasic pulse consists of a leading cathodic-phase to activate neurons and a lagging anodic-phase to balance electrical charges. Because both monophasic cathodic- and anodic-pulses can depolarize neuronal membranes, splitting biphasic-pulses into alternate cathodic- and anodic-pulses could be a feasible strategy to improve stimulation efficiency.Objective. We speculated that neurons in the volume initially activated by both polarity pulses could change to be activated only by anodic-pulses during sustained HFS of alternate monophasic-pulses. To verify the hypothesis, we investigated the interactions of the monophasic pulses during HFS and revealed possible underlying mechanisms.Approach. Different types of pulse stimulations were applied at the alvear fibers (i.e. the axons of CA1 pyramidal neurons) to antidromically activate the neuronal cell bodies in the hippocampal CA1 region of anesthetized ratsin-vivo. Sequences of antidromic HFS (A-HFS) were applied with alternate monophasic-pulses or biphasic-pulses. The pulse frequency in the A-HFS sequences was 50 or 100 Hz. The A-HFS duration was 120 s. The amplitude of antidromically-evoked population spike was measured to evaluate the neuronal firing induced by each pulse. A computational model of axon was used to explore the possible mechanisms of neuronal modulations. The changes of model variables during sustained A-HFS were analyzed.Main results. In rat experiments, with a same pulse intensity, the activation volume of a cathodic-pulse was greater than that of an anodic-pulse. In paired-pulse tests, a preceding cathodic-pulse was able to prevent a following anodic-pulse from activating neurons due to refractory period. This indicated that the activation volume of a cathodic-pulse covered that of an anodic-pulse. However, during sustained A-HFS of alternate monophasic-pulses, the anodic-pulses were able to prevail over the cathodic-pulses in activating neurons in the overlapped activation volume. Model simulation results show the mechanisms of the activation failures of cathodic-pulses. They include the excessive membrane depolarization caused by an accumulation of potassium ions, the obstacle of hyperpolarization in the conduction pathway and the interactions from anodic-pulses.Significance. The study firstly showed the domination of anodic-pulses over cathodic-pulses in their competitions to activate neurons during sustained HFS. The finding provides new clues for designing HFS paradigms to improve the efficiency of neuromodulation therapies.

Positive and biphasic extracellular waveforms correspond to return currents and axonal spikes

Multiple biophysical mechanisms may generate non-negative extracellular waveforms during action potentials, but the origin and prevalence of positive spikes and biphasic spikes in the intact brain are unknown. Using extracellular recordings from densely-connected cortical networks in freely-moving mice, we find that a tenth of the waveforms are non-negative. Positive phases of non-negative spikes occur in synchrony or just before wider same-unit negative spikes. Narrow positive spikes occur in isolation in the white matter. Isolated biphasic spikes are narrower than negative spikes, occurring right after spikes of verified inhibitory units. In CA1, units with dominant non-negative spikes exhibit place fields, phase precession, and phase-locking to ripples. Thus, near-somatic narrow positive extracellular potentials correspond to return currents, and isolated non-negative spikes correspond to axonal potentials. Identifying non-negative extracellular waveforms that correspond to non-somatic compartments during spikes can enhance the understanding of physiological and pathological neural mechanisms in intact animals.

Functional neuronal circuitry and oscillatory dynamics in human brain organoids

Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiology of neuronal circuits within organoids remains under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we captured spontaneous extracellular activity from brain organoids derived from human induced pluripotent stem cells. We inferred functional connectivity from spike timing, revealing a large number of weak connections within a skeleton of significantly fewer strong connections. A benzodiazepine increased the uniformity of firing patterns and decreased the relative fraction of weakly connected edges. Our analysis of the local field potential demonstrate that brain organoids contain neuronal assemblies of sufficient size and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug action, and the effects of external stimuli upon neuronal networks.

From End to End: Gaining, Sorting, and Employing High-Density Neural Single Unit Recordings

The meaning behind neural single unit activity has constantly been a challenge, so it will persist in the foreseeable future. As one of the most sourced strategies, detecting neural activity in high-resolution neural sensor recordings and then attributing them to their corresponding source neurons correctly, namely the process of spike sorting, has been prevailing so far. Support from ever-improving recording techniques and sophisticated algorithms for extracting worthwhile information and abundance in clustering procedures turned spike sorting into an indispensable tool in electrophysiological analysis. This review attempts to illustrate that in all stages of spike sorting algorithms, the past 5 years innovations' brought about concepts, results, and questions worth sharing with even the non-expert user community. By thoroughly inspecting latest innovations in the field of neural sensors, recording procedures, and various spike sorting strategies, a skeletonization of relevant knowledge lays here, with an initiative to get one step closer to the original objective: deciphering and building in the sense of neural transcript.

Reactive Sputtered Silicon Nitride as an Alternative Passivation Layer for Microelectrode Arrays in Sensitive Bioimpedimetric Cell Monitoring

Microelectrode arrays (MEAs) are widely used to study the behavior of cells noninvasively and in real time. While the design of MEAs focuses mainly on the electrode material or its application-dependent modification, the passivation layer, which is crucial to define the electrode area and to insulate the conducting paths, remains largely unnoticed. Because often most cells are in direct contact with the passivation layer rather than the electrode material, biocompatible photoresists such as SU-8 are almost exclusively used. However, SU-8 is not without limitations in terms of optical transmission, optimal cell support, or compatibility within polymer-based microfluidic lab on chip systems. Here, we established a silicon nitride (SiN) passivation by physical vapor deposition (PVD), which was optimized and evaluated for impedance spectroscopy-based monitoring of cells. Surface characteristics, biocompatibility, and electrical insulation capability were investigated and compared to SU8 in detail. To investigate the influence of the SiN passivation on the impedimetric analysis of cells, HEK-293 A and MCF-7 were chosen as adherent cell models and measured on microelectrodes of 50-200 μm in diameter. The results clearly revealed an overall suitability of SiN as alternative passivation. While for the smallest electrode size a cell line dependent comparable or slightly decreased cell signal could be observed in comparison with SU-8, a significant higher cell signal was observed for microelectrodes larger than 50 μm in diameter. Furthermore, a high suitability for the bonding of PEGDA and PDMS microfluidic structures on the SiN passivation layer without any leakage could be demonstrated.

The Flow of Axonal Information Among Hippocampal Subregions: 1. Feed-Forward and Feedback Network Spatial Dynamics Underpinning Emergent Information Processing

The tri-synaptic pathway in the mammalian hippocampus enables cognitive learning and memory. Despite decades of reports on anatomy and physiology, the functional architecture of the hippocampal network remains poorly understood in terms of the dynamics of axonal information transfer between subregions. Information inputs largely flow from the entorhinal cortex (EC) to the dentate gyrus (DG), and then are processed further in the CA3 and CA1 before returning to the EC. Here, we reconstructed elements of the rat hippocampus in a novel device over an electrode array that allowed for monitoring the directionality of individual axons between the subregions. The direction of spike propagation was determined by the transmission delay of the axons recorded between two electrodes in microfluidic tunnels. The majority of axons from the EC to the DG operated in the feed-forward direction, with other regions developing unexpectedly large proportions of feedback axons to balance excitation. Spike timing in axons between each region followed single exponential log-log distributions over two orders of magnitude from 0.01 to 1 s, indicating that conventional descriptors of mean firing rates are misleading assumptions. Most of the spiking occurred in bursts that required two exponentials to fit the distribution of inter-burst intervals. This suggested the presence of up-states and down-states in every region, with the least up-states in the DG to CA3 feed-forward axons and the CA3 subregion. The peaks of the log-normal distributions of intra-burst spike rates were similar in axons between regions with modes around 95 Hz distributed over an order of magnitude. Burst durations were also log-normally distributed around a peak of 88 ms over two orders of magnitude. Despite the diversity of these spike distributions, spike rates from individual axons were often linearly correlated to subregions. These linear relationships enabled the generation of structural connectivity graphs, not possible previously without the directional flow of axonal information. The rich axonal spike dynamics between subregions of the hippocampus reveal both constraints and broad emergent dynamics of hippocampal architecture. Knowledge of this network architecture may enable more efficient computational artificial intelligence (AI) networks, neuromorphic hardware, and stimulation and decoding from cognitive implants.

Extracellular detection of neuronal coupling

We developed a method to non-invasively detect synaptic relationships among neurons from in vitro networks. Our method uses microelectrode arrays on which neurons are cultured and from which propagation of extracellular action potentials (eAPs) in single axons are recorded at multiple electrodes. Detecting eAP propagation bypasses ambiguity introduced by spike sorting. Our methods identify short latency spiking relationships between neurons with properties expected of synaptically coupled neurons, namely they were recapitulated by direct stimulation and were sensitive to changing the number of active synaptic sites. Our methods enabled us to assemble a functional subset of neuronal connectivity in our cultures.

3D high-density microelectrode array with optical stimulation and drug delivery for investigating neural circuit dynamics

Investigation of neural circuit dynamics is crucial for deciphering the functional connections among regions of the brain and understanding the mechanism of brain dysfunction. Despite the advancements of neural circuit models in vitro, technologies for both precisely monitoring and modulating neural activities within three-dimensional (3D) neural circuit models have yet to be developed. Specifically, no existing 3D microelectrode arrays (MEAs) have integrated capabilities to stimulate surrounding neurons and to monitor the temporal evolution of the formation of a neural network in real time. Herein, we present a 3D high-density multifunctional MEA with optical stimulation and drug delivery for investigating neural circuit dynamics within engineered 3D neural tissues. We demonstrate precise measurements of synaptic latencies in 3D neural networks. We expect our 3D multifunctional MEA to open up opportunities for studies of neural circuits through precise, in vitro investigations of neural circuit dynamics with 3D brain models.

Microelectrode Array based Functional Testing of Pancreatic Islet Cells

Electrophysiological techniques to characterize the functionality of islets of Langerhans have been limited to short-term, one-time recordings such as a patch clamp recording. We describe the use of microelectrode arrays (MEAs) to better understand the electrophysiology of dissociated islet cells in response to glucose in a real-time, non-invasive method over prolonged culture periods. Human islets were dissociated into singular cells and seeded onto MEA, which were cultured for up to 7 days. Immunofluorescent imaging revealed that several cellular subtypes of islets; β, δ, and γ cells were present after dissociation. At days 1, 3, 5, and 7 of culture, MEA recordings captured higher electrical activities of islet cells under 16.7 mM glucose (high glucose) than 1.1 mM glucose (low glucose) conditions. The fraction of the plateau phase (FOPP), which is the fraction of time with spiking activity recorded using the MEA, consistently showed distinguishably greater percentages of spiking activity with high glucose compared to the low glucose for all culture days. In parallel, glucose stimulated insulin secretion was measured revealing a diminished insulin response after day 3 of culture. Additionally, MEA spiking profiles were similar to the time course of insulin response when glucose concentration is switched from 1.1 to 16.7 mM. Our analyses suggest that extracellular recordings of dissociated islet cells using MEA is an effective approach to rapidly assess islet functionality, and could supplement standard assays such as glucose stimulate insulin response.