Healthcare Innovations to Address the Challenges of the COVID-19 Pandemic.

We have been faced with an unprecedented challenge in combating the COVID-19/SARS-CoV2 outbreak that is threatening the fabric of our civilization, causing catastrophic human losses and a tremendous economic burden globally. During this difficult time, there has been an urgent need for biomedical engineers, clinicians, and healthcare industry leaders to work together to develop novel diagnostics and treatments to fight the pandemic including the development of portable, rapidly deployable, and affordable diagnostic testing kits, personal protective equipment, mechanical ventilators, vaccines, and data analysis and modeling tools. In this position paper, we address the urgent need to bring these inventions into clinical practices. This paper highlights and summarizes the discussions and new technologies in COVID-19 healthcare, screening, tracing, and treatment-related presentations made at the IEEE EMBS Public Forum on COVID-19. The paper also provides recent studies, statistics and data and new perspectives on ongoing and future challenges pertaining to the COVID-19 pandemic.

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.

Pattern separation and completion of distinct axonal inputs transmitted via micro-tunnels between co-cultured hippocampal dentate, CA3, CA1 and entorhinal cortex networks.

OBJECTIVE: Functions ascribed to the hippocampal sub-regions for encoding episodic memories include the separation of activity patterns propagated from the entorhinal cortex (EC) into the dentate gyrus (DG) and pattern completion in CA3 region. Since a direct assessment of these functions is lacking at the level of specific axonal inputs, our goal is to directly measure the separation and completion of distinct axonal inputs in engineered pairs of hippocampal sub-regional circuits. APPROACH: We co-cultured EC-DG, DG-CA3, CA3-CA1 or CA1-EC neurons in a two-chamber PDMS device over a micro-electrode array (MEA60), inter-connected via distinct axons that grow through the micro-tunnels between the compartments. Taking advantage of the axonal accessibility, we quantified pattern separation and completion of the evoked activity transmitted through the tunnels from source into target well. Since pattern separation can be inferred when inputs are more correlated than outputs, we first compared the correlations among axonal inputs with those of target somata outputs. We then compared, in an analog approach, the distributions of correlation distances between rate patterns of the axonal inputs inside the tunnels with those of the somata outputs evoked in the target well. Finally, in a digital approach, we measured the spatial population distances between binary patterns of the same axonal inputs and somata outputs. MAIN RESULTS: We found the strongest separation of the propagated axonal inputs when EC was axonally connected to DG, with a decline in separation to CA3 and to CA1 for both rate and digital approaches. Furthermore, the digital approach showed stronger pattern completion in CA3, then CA1 and EC. SIGNIFICANCE: To the best of our knowledge, these are the first direct measures of pattern separation and completion for axonal transmission to the somata target outputs at the rate and digital population levels in each of four stages of the EC-DG-CA3-CA1 circuit.

Specific CA3 neurons decode neural information of dentate granule cells evoked by paired-pulse stimulation in co-cultured networks.

CA3 and dentate gyrus (DG) neurons are cultured in two-chamber devices on multi-electrode arrays (MEAs) and connected via micro-tunnels. In order to evoke time-locked activity, paired-pulse stimulation is applied to 22 different sites and repeated 25 times in each well in 5 MEA co-cultures and results compared to CA3-CA3 and DG-DG networks homologous controls. In these hippocampal sub-regions, we focus on the mechanisms underpinning a network's ability to decode the identity of site specific stimulation from analysis of evoked network responses using a support vector machine classifier. Our results indicate that a pool of CA3 neurons is able to reliably decode the identity of DG stimulation site information.

Narrow microtunnel technology for the isolation and precise identification of axonal communication among distinct hippocampal subregion networks.

Communication between different sub regions of the hippocampus is fundamental to learning and memory. However accurate knowledge about information transfer between sub regions from access to the activity in individual axons is lacking. MEMS devices with microtunnels connecting two sub networks have begun to approach this problem but the commonly used 10 µm wide tunnels frequently measure signals from multiple axons. To reduce this complexity, we compared polydimethylsiloxane (PDMS) microtunnel devices each with a separate tunnel width of 2.5, 5 or 10 µm bridging two wells aligned over a multi electrode array (MEA). Primary rat neurons were grown in the chambers with neurons from the dentate gyrus on one side and hippocampal CA3 on the other. After 2-3 weeks of culture, spontaneous activity in the axons inside the tunnels was recorded. We report electrophysiological, exploratory data analysis for feature clustering and visual evidence to support the expectation that 2.5 µm wide tunnels have fewer axons per tunnel and therefore more clearly delineated signals than 10 or 5 µm wide tunnels. Several measures indicated that fewer axons per electrode enabled more accurate detection of spikes. A clustering analysis comparing the variations of spike height and width for different tunnel widths revealed tighter clusters representing unique spikes with less height and width variation when measured in narrow tunnels. Wider tunnels tended toward more diffuse clusters from a continuum of spike heights and widths. Standard deviations for multiple cluster measures, such as Average Dissimilarity, Silhouette Value (S) and Separation Factor (average dissimilarity/S value), support a conclusion that 2.5 µm wide tunnels containing fewer axons enable more precise determination of individual action potential peaks, their propagation direction, timing, and information transfer between sub networks.

Sparse and Specific Coding during Information Transmission between Co-cultured Dentate Gyrus and CA3 Hippocampal Networks.

To better understand encoding and decoding of stimulus information in two specific hippocampal sub-regions, we isolated and co-cultured rat primary dentate gyrus (DG) and CA3 neurons within a two-chamber device with axonal connectivity via micro-tunnels. We tested the hypothesis that, in these engineered networks, decoding performance of stimulus site information would be more accurate when stimuli and information flow occur in anatomically correct feed-forward DG to CA3 vs. CA3 back to DG. In particular, we characterized the neural code of these sub-regions by measuring sparseness and uniqueness of the responses evoked by specific paired-pulse stimuli. We used the evoked responses in CA3 to decode the stimulation sites in DG (and vice-versa) by means of learning algorithms for classification (support vector machine, SVM). The device was placed over an 8 × 8 grid of extracellular electrodes (micro-electrode array, MEA) in order to provide a platform for monitoring development, self-organization, and improved access to stimulation and recording at multiple sites. The micro-tunnels were designed with dimensions 3 × 10 × 400 µm allowing axonal growth but not migration of cell bodies and long enough to exclude traversal by dendrites. Paired-pulse stimulation (inter-pulse interval 50 ms) was applied at 22 different sites and repeated 25 times in each chamber for each sub-region to evoke time-locked activity. DG-DG and CA3-CA3 networks were used as controls. Stimulation in DG drove signals through the axons in the tunnels to activate a relatively small set of specific electrodes in CA3 (sparse code). CA3-CA3 and DG-DG controls were less sparse in coding than CA3 in DG-CA3 networks. Using all target electrodes with the three highest spike rates (14%), the evoked responses in CA3 specified each stimulation site in DG with optimum uniqueness of 64%. Finally, by SVM learning, these evoked responses in CA3 correctly decoded the stimulation sites in DG for 43% of the trials, significantly higher than the reverse, i.e., how well-recording in DG could predict the stimulation site in CA3. In conclusion, our co-cultured model for the in vivo DG-CA3 hippocampal network showed sparse and specific responses in CA3, selectively evoked by each stimulation site in DG.

Repeating Spatial-Temporal Motifs of CA3 Activity Dependent on Engineered Inputs from Dentate Gyrus Neurons in Live Hippocampal Networks.

Anatomical and behavioral studies, and in vivo and slice electrophysiology of the hippocampus suggest specific functions of the dentate gyrus (DG) and the CA3 subregions, but the underlying activity dynamics and repeatability of information processing remains poorly understood. To approach this problem, we engineered separate living networks of the DG and CA3 neurons that develop connections through 51 tunnels for axonal communication. Growing these networks on top of an electrode array enabled us to determine whether the subregion dynamics were separable and repeatable. We found spontaneous development of polarized propagation of 80% of the activity in the native direction from DG to CA3 and different spike and burst dynamics for these subregions. Spatial-temporal differences emerged when the relationships of target CA3 activity were categorized with to the number and timing of inputs from the apposing network. Compared to times of CA3 activity when there was no recorded tunnel input, DG input led to CA3 activity bursts that were 7× more frequent, increased in amplitude and extended in temporal envelope. Logistic regression indicated that a high number of tunnel inputs predict CA3 activity with 90% sensitivity and 70% specificity. Compared to no tunnel input, patterns of >80% tunnel inputs from DG specified different patterns of first-to-fire neurons in the CA3 target well. Clustering dendrograms revealed repeating motifs of three or more patterns at up to 17 sites in CA3 that were importantly associated with specific spatial-temporal patterns of tunnel activity. The number of these motifs recorded in 3 min was significantly higher than shuffled spike activity and not seen above chance in control networks in which CA3 was apposed to CA3 or DG to DG. Together, these results demonstrate spontaneous input-dependent repeatable coding of distributed activity in CA3 networks driven by engineered inputs from DG networks. These functional configurations at measured times of activation (motifs) emerge from anatomically accurate feed-forward connections from DG through tunnels to CA3.

Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks.

Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura's and van Rossum's spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous synchronized network burst events that propagated between layers and highlight the potential applications of these MEMs devices as a tool for further investigation of structure and functional dynamics among neural populations.

Structure, Function, and Propagation of Information across Living Two, Four, and Eight Node Degree Topologies.

In this study, we created four network topologies composed of living cortical neurons and compared resultant structural-functional dynamics including the nature and quality of information transmission. Each living network was composed of living cortical neurons and were created using microstamping of adhesion promoting molecules and each was "designed" with different levels of convergence embedded within each structure. Networks were cultured over a grid of electrodes that permitted detailed measurements of neural activity at each node in the network. Of the topologies we tested, the "Random" networks in which neurons connect based on their own intrinsic properties transmitted information embedded within their spike trains with higher fidelity relative to any other topology we tested. Within our patterned topologies in which we explicitly manipulated structure, the effect of convergence on fidelity was dependent on both topology and time-scale (rate vs. temporal coding). A more detailed examination using tools from network analysis revealed that these changes in fidelity were also associated with a number of other structural properties including a node's degree, degree-degree correlations, path length, and clustering coefficients. Whereas information transmission was apparent among nodes with few connections, the greatest transmission fidelity was achieved among the few nodes possessing the highest number of connections (high degree nodes or putative hubs). These results provide a unique view into the relationship between structure and its affect on transmission fidelity, at least within these small neural populations with defined network topology. They also highlight the potential role of tools such as microstamp printing and microelectrode array recordings to construct and record from arbitrary network topologies to provide a new direction in which to advance the study of structure-function relationships.

Scale of Carbon Nanomaterials Affects Neural Outgrowth and Adhesion.

Carbon nanomaterials have become increasingly popular microelectrode materials for neuroscience applications. Here we study how the scale of carbon nanotubes and carbon nanofibers affect neural viability, outgrowth, and adhesion. Carbon nanotubes were deposited on glass coverslips via a layer-by-layer method with polyethylenimine (PEI). Carbonized nanofibers were fabricated by electrospinning SU-8 and pyrolyzing the nanofiber depositions. Additional substrates tested were carbonized and SU-8 thin films and SU-8 nanofibers. Surfaces were O2-plasma treated, coated with varying concentrations of PEI, seeded with E18 rat cortical cells, and examined at 3, 4, and 7 days in vitro (DIV). Neural adhesion was examined at 4 DIV utilizing a parallel plate flow chamber. At 3 DIV, neural viability was lower on the nanofiber and thin film depositions treated with higher PEI concentrations which corresponded with significantly higher zeta potentials (surface charge); this significance was drastically higher on the nanofibers suggesting that the nanostructure may collect more PEI molecules, causing increased toxicity. At 7 DIV, significantly higher neurite outgrowth was observed on SU-8 nanofiber substrates with nanofibers a significant fraction of a neuron's size. No differences were detected for carbonized nanofibers or carbon nanotubes. Both carbonized and SU-8 nanofibers had significantly higher cellular adhesion post-flow in comparison to controls whereas the carbon nanotubes were statistically similar to control substrates. These data suggest a neural cell preference for larger-scale nanomaterials with specific surface treatments. These characteristics could be taken advantage of in the future design and fabrication of neural microelectrodes.

An in vitro method to manipulate the direction and functional strength between neural populations.

We report the design and application of a Micro Electro Mechanical Systems (MEMs) device that permits investigators to create arbitrary network topologies. With this device investigators can manipulate the degree of functional connectivity among distinct neural populations by systematically altering their geometric connectivity in vitro. Each polydimethylsilxane (PDMS) device was cast from molds and consisted of two wells each containing a small neural population of dissociated rat cortical neurons. Wells were separated by a series of parallel micrometer scale tunnels that permitted passage of axonal processes but not somata; with the device placed over an 8 × 8 microelectrode array, action potentials from somata in wells and axons in microtunnels can be recorded and stimulated. In our earlier report we showed that a one week delay in plating of neurons from one well to the other led to a filling and blocking of the microtunnels by axons from the older well resulting in strong directionality (older to younger) of both axon action potentials in tunnels and longer duration and more slowly propagating bursts of action potentials between wells. Here we show that changing the number of tunnels, and hence the number of axons, connecting the two wells leads to changes in connectivity and propagation of bursting activity. More specifically, the greater the number of tunnels the stronger the connectivity, the greater the probability of bursting propagating between wells, and shorter peak-to-peak delays between bursts and time to first spike measured in the opposing well. We estimate that a minimum of 100 axons are needed to reliably initiate a burst in the opposing well. This device provides a tool for researchers interested in understanding network dynamics who will profit from having the ability to design both the degree and directionality connectivity among multiple small neural populations.

Large extracellular spikes recordable from axons in microtunnels.

When extracellular action potentials (spikes) from cultured neurons are recorded using microelectrode arrays in open wells, their amplitudes are usually quite small (often below the noise level) despite the extracellular currents originating from the relatively large surface area of neural cell somata. In this paper rat cortical neurons were seeded into one well of a two well system separated by 3 × 10 µm microtunnels and then seven days later into the second well forming a feed-forward network between two small neuronal assemblies. In contrast to measurements in the open well spikes recorded from axons within the restricted volumes imposed by the microtunnels are often several orders of magnitude larger than in the open well, with high signal to noise ratio, despite the currents originating in the much smaller surface area of the axon. Average signal amplitudes exceeding 250 µV are typical, with some signals as large as 4.5 mV (signal-to-noise ratio up to 450), 20 times greater than the maximum recorded from electrodes in adjacent but open wells. We confirm the dependence of signal amplitude on the impedance of the microtunnel and discuss possible reasons for the phenomenon.

Toward a self-wired active reconstruction of the hippocampal trisynaptic loop: DG-CA3.

The mammalian hippocampus functions to encode and retrieve memories by transiently changing synaptic strengths, yet encoding in individual subregions for transmission between regions remains poorly understood. Toward the goal of better understanding the coding in the trisynaptic pathway from the dentate gyrus (DG) to the CA3 and CA1, we report a novel microfabricated device that divides a micro-electrode array into two compartments of separate hippocampal network subregions connected by axons that grow through 3 × 10 × 400 µm tunnels. Gene expression by qPCR demonstrated selective enrichment of separate DG, CA3, and CA1 subregions. Reconnection of DG to CA3 altered burst dynamics associated with marked enrichment of GAD67 in DG and GFAP in CA3. Surprisingly, DG axon spike propagation was preferentially unidirectional to the CA3 region at 0.5 m/s with little reverse transmission. Therefore, select hippocampal subregions intrinsically self-wire in anatomically appropriate patterns and maintain their distinct subregion phenotype without external inputs.

Chronic stimulation of cultured neuronal networks boosts low-frequency oscillatory activity at theta and gamma with spikes phase-locked to gamma frequencies.

Slow wave oscillations in the brain are essential for coordinated network activity but have not been shown to self-organize in vitro. Here, the development of dissociated hippocampal neurons into an active network with oscillations on multi-electrode arrays was evaluated in the absence and presence of chronic external stimulation. Significant changes in signal power were observed in the range of 1-400 Hz with an increase in amplitude during bursts. Stimulation increased oscillatory activity primarily in the theta (4-11 Hz) and slow gamma (30-55 Hz) bands. Spikes were most prominently phase-locked to the slow gamma waves. Notably, the dissociated network self-organized to exhibit sustained delta, theta, beta and gamma oscillations without input from cortex, thalamus or organized pyramidal cell layers.

Hippocampal networks on reliable patterned substrates.

Toward the goal of reproducible live neuronal networks, we investigated the influence of substrate patterns on neuron compliance and network activity. We optimized process parameters of micro-contact printing for reproducible geometric patterns of 10 µm wide lines of polylysine with 4, 6, or 8 connections at a constant square array of nodes overlying the recording electrodes of a multielectrode array (MEA). We hypothesized that an increase in node connections would give the network more inputs resulting in higher neuronal outputs as network spike rates. We also chronically stimulated these networks during development and added astroglia to enhance network activity. Our results show that despite frequent localization of neuron somata over the electrodes, the number of spontaneously active electrodes was reduced 3-fold compared to random networks, independent of pattern complexity. Of the electrodes active, the overall spike rate was independent of pattern complexity, consistent with homeostasis of activity. Lower mean burst rates were seen with higher levels of pattern complexity; however, burst durations increased 1.6-fold with pattern complexity (n=6027 bursts, p<0.001). Inter-burst interval and percentage of active electrodes displaying bursts also increased with pattern complexity. The extra-burst (non-burst or isolated) spike rate increased 4-fold with pattern complexity, but this relationship was reversed with either chronic stimulation or astroglia addition. These studies suggest for the first time that patterns which limit the distribution of branches and inputs are deleterious to activity in a hippocampal network, but that higher levels of pattern complexity promote non-burst activity and favor longer lasting, but fewer bursts.

Propagation of action potential activity in a predefined microtunnel neural network.

A polydimethylsiloxane microtunnel device with two wells is aligned and attached on top of a multi-electrode array. Neurons are grown first in one well and allow the propagation of axons through the tunnels into a second well. After 10 days, cells are plated in the second well, with much lower likelihood of extending axons back to the first well, with the intent of creating unidirectional connectivity between populations of neurons in the two wells. Here we report electrophysiological evidence that supports the hypothesis that the dominant information flow is in the desired direction. This was done by measuring the propagation speed and direction of individual action potentials, with the result that 84% of the spikes propagated in the desired direction. Further, we recorded globally synchronized burst activity on each of the electrodes, identified the timing of the first spike on each electrode, recorded locally synchronized burst activity which is found only in the second well and does not propagate back to the first well and concluded that this measure of burst propagation supports the hypothesis of a unidirectionally connected network. Two hypotheses are discussed for the mechanism underlying the activity pattern of the particular neural networks.

In vitro microelectrode array technology and neural recordings.

In vitro microelectrode array (MEA) technology has evolved into a widely used and effective methodology to study cultured neural networks. An MEA forms a unique electrical interface with the cultured neurons in that neurons are directly grown on top of the electrode (neuron-on-electrode configuration). Theoretical models and experimental results suggest that physical configuration and biological environments of the cell-electrode interface play a key role in the outcome of neural recordings, such as yield of recordings, signal shape, and signal-to-noise ratio. Recent interdisciplinary approaches have shown that MEA performance can be enhanced through novel nanomaterials, structures, surface chemistry, and biotechnology. In vitro and in vivo neural interfaces share some common factors, and in vitro neural interface issues can be extended to solve in vivo neural interface problems of brain-machine interface or neuromodulation techniques.

Designing Neural Networks in Culture: Experiments are described for controlled growth, of nerve cells taken from rats, in predesigned geometrical patterns on laboratory culture dishes.

Technology has advanced to where it is possible to design and grow-with predefined geometry and surprisingly good fidelity-living networks of neurons in culture dishes. Here we overview the elements of design, emphasizing the lithographic techniques that alter the cell culture surface which in turn influences the attachment and growth of the neural networks. Advanced capability in this area makes it possible to design networks of desired complexity. Other issues addressed include the influence of glial cells and media on activity and the potential for extending the designs into three dimensions. Investigators are advancing the art and science of analyzing and controlling through stimulation the function of the neural networks, including the ability to take advantage of their geometric form in order to influence functional properties.