RESUMEN
The United States Food and Drug Administration (FDA) ensures that patients in the United States have access to safe and effective medical devices. The division of neurological and physical medicine devices reviews medical technologies that interface with the nervous system, including many neuromodulation devices. This article focuses on neuromodulation devices and addresses how to navigate the FDA's regulatory landscape to successfully bring devices to patients.
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Aprobación de Recursos/legislación & jurisprudencia , Aprobación de Recursos/normas , Neuroestimuladores Implantables/normas , Estimulación Eléctrica Transcutánea del Nervio/normas , Humanos , Estimulación Eléctrica Transcutánea del Nervio/instrumentación , Estados UnidosRESUMEN
The United States Food and Drug Administration (FDA) ensures that patients in the U.S. have access to safe and effective medical devices. The Division of Neurological and Physical Medicine Devices reviews medical technologies that interface with the nervous system. This article addresses how to navigate the FDA's regulatory landscape to successfully bring medical devices to patients.
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Aprobación de Recursos/legislación & jurisprudencia , Equipos y Suministros , Accesibilidad a los Servicios de Salud , United States Food and Drug Administration/legislación & jurisprudencia , Disfonía , Humanos , Medicina Física y Rehabilitación , Estados UnidosRESUMEN
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.
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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.
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Adhesión Celular/efectos de los fármacos , Nanofibras/toxicidad , Nanotubos de Carbono/toxicidad , Neuritas/efectos de los fármacos , Animales , Línea Celular , Nanofibras/química , Nanomedicina , Nanotubos de Carbono/química , Neuritas/fisiología , RatasRESUMEN
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.
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Potenciales de Acción/fisiología , Corteza Cerebral/citología , Red Nerviosa/fisiología , Neuronas/fisiología , Análisis de Varianza , Animales , Células Cultivadas , Embrión de Mamíferos , Fluoresceínas/metabolismo , Microelectrodos , RatasRESUMEN
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.
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Axones/fisiología , Espacio Extracelular/fisiología , Potenciales de Acción/fisiología , Animales , Técnicas de Cultivo de Célula , Dendritas/fisiología , Impedancia Eléctrica , Diseño de Equipo , Microelectrodos , Ratas , Relación Señal-RuidoRESUMEN
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.