Fiber-based Probes for Electrophysiology, Photometry, Optical and Electrical Stimulation, Drug Delivery, and Fast-Scan Cyclic Voltammetry In Vivo.

Recording and modulation of neuronal activity enables the study of brain function in health and disease. While translational neuroscience relies on electrical recording and modulation techniques, mechanistic studies in rodent models leverage genetic precision of optical methods, such as optogenetics and imaging of fluorescent indicators. In addition to electrical signal transduction, neurons produce and receive diverse chemical signals which motivate tools to probe and modulate neurochemistry. Although the past decade has delivered a wealth of technologies for electrophysiology, optogenetics, chemical sensing, and optical recording, combining these modalities within a single platform remains challenging. This work leverages materials selection and convergence fiber drawing to permit neural recording, electrical stimulation, optogenetics, fiber photometry, drug and gene delivery, and voltammetric recording of neurotransmitters within individual fibers. Composed of polymers and non-magnetic carbon-based conductors, these fibers are compatible with magnetic resonance imaging, enabling concurrent stimulation and whole-brain monitoring. Their utility is demonstrated in studies of the mesolimbic reward pathway by simultaneously interfacing with the ventral tegmental area and nucleus accumbens in mice and characterizing the neurophysiological effects of a stimulant drug. This study highlights the potential of these fibers to probe electrical, optical, and chemical signaling across multiple brain regions in both mechanistic and translational studies.

Multifunctional fibers enable modulation of cortical and deep brain activity during cognitive behavior in macaques.

Recording and modulating neural activity in vivo enables investigations of the neurophysiology underlying behavior and disease. However, there is a dearth of translational tools for simultaneous recording and localized receptor-specific modulation. We address this limitation by translating multifunctional fiber neurotechnology previously only available for rodent studies to enable cortical and subcortical neural recording and modulation in macaques. We record single-neuron and broader oscillatory activity during intracranial GABA infusions in the premotor cortex and putamen. By applying state-space models to characterize changes in electrophysiology, we uncover that neural activity evoked by a working memory task is reshaped by even a modest local inhibition. The recordings provide detailed insight into the electrophysiological effect of neurotransmitter receptor modulation in both cortical and subcortical structures in an awake macaque. Our results demonstrate a first-time application of multifunctional fibers for causal studies of neuronal activity in behaving nonhuman primates and pave the way for clinical translation of fiber-based neurotechnology.

Multifunctional microelectronic fibers enable wireless modulation of gut and brain neural circuits.

Progress in understanding brain-viscera interoceptive signaling is hindered by a dearth of implantable devices suitable for probing both brain and peripheral organ neurophysiology during behavior. Here we describe multifunctional neural interfaces that combine the scalability and mechanical versatility of thermally drawn polymer-based fibers with the sophistication of microelectronic chips for organs as diverse as the brain and the gut. Our approach uses meters-long continuous fibers that can integrate light sources, electrodes, thermal sensors and microfluidic channels in a miniature footprint. Paired with custom-fabricated control modules, the fibers wirelessly deliver light for optogenetics and transfer data for physiological recording. We validate this technology by modulating the mesolimbic reward pathway in the mouse brain. We then apply the fibers in the anatomically challenging intestinal lumen and demonstrate wireless control of sensory epithelial cells that guide feeding behaviors. Finally, we show that optogenetic stimulation of vagal afferents from the intestinal lumen is sufficient to evoke a reward phenotype in untethered mice.

Magnetically Actuated Fiber-Based Soft Robots.

Broad adoption of magnetic soft robotics is hampered by the sophisticated field paradigms for their manipulation and the complexities in controlling multiple devices. Furthermore, high-throughput fabrication of such devices across spatial scales remains challenging. Here, advances in fiber-based actuators and magnetic elastomer composites are leveraged to create 3D magnetic soft robots controlled by unidirectional fields. Thermally drawn elastomeric fibers are instrumented with a magnetic composite synthesized to withstand strains exceeding 600%. A combination of strain and magnetization engineering in these fibers enables programming of 3D robots capable of crawling or walking in magnetic fields orthogonal to the plane of motion. Magnetic robots act as cargo carriers, and multiple robots can be controlled simultaneously and in opposing directions using a single stationary electromagnet. The scalable approach to fabrication and control of magnetic soft robots invites their future applications in constrained environments where complex fields cannot be readily deployed.

A Local Graph-Based Structure for Processing Gigantic Aggregated 3D Point Clouds.

We present an original workflow for structuring a point cloud generated from several scans. Our representation is based on a set of local graphs. Each graph is constructed from the depth map provided by each scan. The graphs are then connected together via the overlapping areas, and careful consideration of the redundant points in these regions leads to a piecewise and globally consistent structure for the underlying surface sampled by the point cloud. The proposed workflow allows structuring aggregated point clouds, scan after scan, whatever the number of acquisitions and the number of points per acquisition, even on computers with very limited memory capacities. To show that our structure can be highly relevant for the community, where the gigantic amount of data represents a real scientific challenge per se, we present an algorithm based on this structure capable of resampling billions of points on standard computers. This application is particularly attractive for simplifying and visualizing gigantic point clouds representing very large-scale scenes (buildings, urban scenes, historical sites...), which often require a prohibitive number of points to describe them accurately.

Customizing MRI-Compatible Multifunctional Neural Interfaces through Fiber Drawing.

Fiber drawing enables scalable fabrication of multifunctional flexible fibers that integrate electrical, optical and microfluidic modalities to record and modulate neural activity. Constraints on thermomechanical properties of materials, however, have prevented integrated drawing of metal electrodes with low-loss polymer waveguides for concurrent electrical recording and optical neuromodulation. Here we introduce two fabrication approaches: (1) an iterative thermal drawing with a soft, low melting temperature (Tm) metal indium, and (2) a metal convergence drawing with traditionally non-drawable high Tm metal tungsten. Both approaches deliver multifunctional flexible neural interfaces with low-impedance metallic electrodes and low-loss waveguides, capable of recording optically-evoked and spontaneous neural activity in mice over several weeks. We couple these fibers with a light-weight mechanical microdrive (1g) that enables depth-specific interrogation of neural circuits in mice following chronic implantation. Finally, we demonstrate the compatibility of these fibers with magnetic resonance imaging (MRI) and apply them to visualize the delivery of chemical payloads through the integrated channels in real time. Together, these advances expand the domains of application of the fiber-based neural probes in neuroscience and neuroengineering.

Modular Integration of Hydrogel Neural Interfaces.

Thermal drawing has been recently leveraged to yield multifunctional, fiber-based neural probes at near kilometer length scales. Despite its promise, the widespread adoption of this approach has been impeded by (1) material compatibility requirements and (2) labor-intensive interfacing of functional features to external hardware. Furthermore, in multifunctional fibers, significant volume is occupied by passive polymer cladding that so far has only served structural or electrical insulation purposes. In this article, we report a rapid, robust, and modular approach to creating multifunctional fiber-based neural interfaces using a solvent evaporation or entrapment-driven (SEED) integration process. This process brings together electrical, optical, and microfluidic modalities all encased within a copolymer comprised of water-soluble poly(ethylene glycol) tethered to water-insoluble poly(urethane) (PU-PEG). We employ these devices for simultaneous optogenetics and electrophysiology and demonstrate that multifunctional neural probes can be used to deliver cellular cargo with high viability. Upon exposure to water, PU-PEG cladding spontaneously forms a hydrogel, which in addition to enabling integration of modalities, can harbor small molecules and nanomaterials that can be released into local tissue following implantation. We also synthesized a custom nanodroplet forming block polymer and demonstrated that embedding such materials within the hydrogel cladding of our probes enables delivery of hydrophobic small molecules in vitro and in vivo. Our approach widens the chemical toolbox and expands the capabilities of multifunctional neural interfaces.

Influence of Magnetic Fields on Electrochemical Reactions of Redox Cofactor Solutions.

Redox cofactors mediate many enzymatic processes and are increasingly employed in biomedical and energy applications. Exploring the influence of external magnetic fields on redox cofactor chemistry can enhance our understanding of magnetic-field-sensitive biological processes and allow the application of magnetic fields to modulate redox reactions involving cofactors. Through a combination of experiments and modeling, we investigate the influence of magnetic fields on electrochemical reactions in redox cofactor solutions. By employing flavin mononucleotide (FMN) cofactor as a model system, we characterize magnetically induced changes in Faradaic currents. We find that radical pair intermediates have negligible influence on current increases in FMN solution upon application of a magnetic field. The dominant mechanism underlying the observed current increases is the magneto-hydrodynamic effect. We extend our analyses to other diffusion-limited electrochemical reactions of redox cofactor solutions and arrive at similar conclusions, highlighting the opportunity to use this framework in redox cofactor chemistry.

A Crisis-Responsive Framework for Medical Device Development Applied to the COVID-19 Pandemic.

The disruption of conventional manufacturing, supply, and distribution channels during the COVID-19 pandemic caused widespread shortages in personal protective equipment (PPE) and other medical supplies. These shortages catalyzed local efforts to use nontraditional, rapid manufacturing to meet urgent healthcare needs. Here we present a crisis-responsive design framework designed to assist with product development under pandemic conditions. The framework emphasizes stakeholder engagement, comprehensive but efficient needs assessment, rapid manufacturing, and modified product testing to enable accelerated development of healthcare products. We contrast this framework with traditional medical device manufacturing that proceeds at a more deliberate pace, discuss strengths and weakness of pandemic-responsive fabrication, and consider relevant regulatory policies. We highlight the use of the crisis-responsive framework in a case study of face shield design and production for a large US academic hospital. Finally, we make recommendations aimed at improving future resilience to pandemics and healthcare emergencies. These include continued development of open source designs suitable for rapid manufacturing, education of maker communities and hospital administrators about rapidly-manufactured medical devices, and changes in regulatory policy that help strike a balance between quality and innovation.

Dynamic Image Quantization Using Leaky Integrate-and-Fire Neurons.

This paper introduces a novel coding/decoding mechanism that mimics one of the most important properties of the human visual system: its ability to enhance the visual perception quality in time. In other words, the brain takes advantage of time to process and clarify the details of the visual scene. This characteristic is yet to be considered by the state-of-the-art quantization mechanisms that process the visual information regardless the duration of time it appears in the visual scene. We propose a compression architecture built of neuroscience models; it first uses the leaky integrate-and-fire (LIF) model to transform the visual stimulus into a spike train and then it combines two different kinds of spike interpretation mechanisms (SIM), the time-SIM and the rate-SIM for the encoding of the spike train. The time-SIM allows a high quality interpretation of the neural code and the rate-SIM allows a simple decoding mechanism by counting the spikes. For that reason, the proposed mechanisms is called Dual-SIM quantizer (Dual-SIMQ). We show that (i) the time-dependency of Dual-SIMQ automatically controls the reconstruction accuracy of the visual stimulus, (ii) the numerical comparison of Dual-SIMQ to the state-of-the-art shows that the performance of the proposed algorithm is similar to the uniform quantization schema while it approximates the optimal behavior of the non-uniform quantization schema and (iii) from the perceptual point of view the reconstruction quality using the Dual-SIMQ is higher than the state-of-the-art.

In Vivo Photopharmacology Enabled by Multifunctional Fibers.

Photoswitchable ligands can add an optical switch to a target receptor or signaling cascade and enable reversible control of neural circuits. The application of this approach, termed photopharmacology, to behavioral experiments has been impeded by a lack of integrated hardware capable of delivering both light and compounds to deep brain regions in moving subjects. Here, we devise a hybrid photochemical genetic approach to target neurons using a photoswitchable agonist of the capsaicin receptor TRPV1, red-AzCA-4. Using multifunctional fibers with optical and microfluidic capabilities, we delivered a transgene coding for TRPV1 into the ventral tegmental area (VTA). This sensitized excitatory VTA neurons to red-AzCA-4, allowing us to optically control conditioned place preference in mice, thus extending applications of photopharmacology to behavioral experiments. Applied to endogenous receptors, our approach may accelerate future studies of molecular mechanisms underlying animal behavior.

Regulatory and Safety Considerations in Deploying a Locally Fabricated, Reusable Face Shield in a Hospital Responding to the COVID-19 Pandemic.

BACKGROUND: Due to supply chain disruption, the COVID-19 pandemic has caused severe shortages in personal protective equipment for health care professionals. Local fabrication based on 3D printing is one way to address this challenge, particularly in the case of products such as protective face shields. No clear path exists, however, for introducing a locally fabricated product into a clinical setting. METHODS: We describe a research protocol under Institutional Review Board supervision that allowed clinicians to participate in an iterative design process followed by real-world testing in an emergency department. All designs, materials used, testing protocols, and survey results are reported in full to facilitate similar efforts in other clinical settings. FINDINGS: Clinical testing allowed the incident command team at a major academic medical center to introduce the locally fabricated face shield into general use in a rapid but well-controlled manner. Unlike standard hospital face shields, the locally fabricated design was intended to be reusable. We discuss the design and testing process and provide an overview of regulatory considerations associated with fabrication and testing of personal protective equipment, such as face shields. CONCLUSIONS: Our work serves as a case study for robust, local responses to pandemic-related disruption of medical supply chains with implications for health care professionals, hospital administrators, regulatory agencies, and concerned citizens in the COVID-19 and future health care emergencies. FUNDING: : This work was supported by the Harvard MIT Center for Regulatory Sciences, NIH/NCI grants U54-CA225088 and T32-GM007753, and the Harvard Ludwig Center. M.-J.A. is a Friends of McGovern Graduate Fellow.

Next-generation interfaces for studying neural function.

Monitoring and modulating the diversity of signals used by neurons and glia in a closed-loop fashion is necessary to establish causative links between biochemical processes within the nervous system and observed behaviors. As developments in neural-interface hardware strive to keep pace with rapid progress in genetically encoded and synthetic reporters and modulators of neural activity, the integration of multiple functional features becomes a key requirement and a pressing challenge in the field of neural engineering. Electrical, optical and chemical approaches have been used to manipulate and record neuronal activity in vivo, with a recent focus on technologies that both integrate multiple modes of interaction with neurons into a single device and enable bidirectional communication with neural circuits with enhanced spatiotemporal precision. These technologies not only are facilitating a greater understanding of the brain, spinal cord and peripheral circuits in the context of health and disease, but also are informing the development of future closed-loop therapies for neurological, neuro-immune and neuroendocrine conditions.

Retina-Inspired Filter.

This paper introduces a novel filter, which is inspired by the human retina. The human retina consists of three different layers: the Outer Plexiform Layer (OPL), the inner plexiform layer, and the ganglionic layer. Our inspiration is the linear transform which takes place in the OPL and has been mathematically described by the neuroscientific model "virtual retina." This model is the cornerstone to derive the non-separable spatio-temporal OPL retina-inspired filter, briefly renamed retina-inspired filter, studied in this paper. This filter is connected to the dynamic behavior of the retina, which enables the retina to increase the sharpness of the visual stimulus during filtering before its transmission to the brain. We establish that this retina-inspired transform forms a group of spatio-temporal Weighted Difference of Gaussian (WDoG) filters when it is applied to a still image visible for a given time. We analyze the spatial frequency bandwidth of the retina-inspired filter with respect to time. It is shown that the WDoG spectrum varies from a lowpass filter to a bandpass filter. Therefore, while time increases, the retina-inspired filter enables to extract different kinds of information from the input image. Finally, we discuss the benefits of using the retina-inspired filter in image processing applications such as edge detection and compression.

Frames for exact inversion of the rank order coder.

Our goal is to revisit rank order coding by proposing an original exact decoding procedure for it. Rank order coding was proposed by Thorpe et al. who stated that the order in which the retina cells are activated encodes for the visual stimulus. Based on this idea, the authors proposed in [1] a rank order coder/decoder associated to a retinal model. Though, it appeared that the decoding procedure employed yields reconstruction errors that limit the model bit-cost/quality performances when used as an image codec. The attempts made in the literature to overcome this issue are time consuming and alter the coding procedure, or are lacking mathematical support and feasibility for standard size images. Here we solve this problem in an original fashion by using the frames theory, where a frame of a vector space designates an extension for the notion of basis. Our contribution is twofold. First, we prove that the analyzing filter bank considered is a frame, and then we define the corresponding dual frame that is necessary for the exact image reconstruction. Second, to deal with the problem of memory overhead, we design a recursive out-of-core blockwise algorithm for the computation of this dual frame. Our work provides a mathematical formalism for the retinal model under study and defines a simple and exact reverse transform for it with over than 265 dB of increase in the peak signal-to-noise ratio quality compared to [1]. Furthermore, the framework presented here can be extended to several models of the visual cortical areas using redundant representations.

Mean square error approximation for wavelet-based semiregular mesh compression.

The objective of this paper is to propose an efficient model-based bit allocation process optimizing the performances of a wavelet coder for semiregular meshes. More precisely, this process should compute the best quantizers for the wavelet coefficient subbands that minimize the reconstructed mean square error for one specific target bitrate. In order to design a fast and low complex allocation process, we propose an approximation of the reconstructed mean square error relative to the coding of semiregular mesh geometry. This error is expressed directly from the quantization errors of each coefficient subband. For that purpose, we have to take into account the influence of the wavelet filters on the quantized coefficients. Furthermore, we propose a specific approximation for wavelet transforms based on lifting schemes. Experimentally, we show that, in comparison with a "naive" approximation (depending on the subband levels), using the proposed approximation as distortion criterion during the model-based allocation process improves the performances of a wavelet-based coder for any model, any bitrate, and any lifting scheme.

Design of signal-adapted multidimensional lifting scheme for lossy coding.

This paper proposes a new method for the design of lifting filters to compute a multidimensional nonseparable wavelet transform. Our approach is stated in the general case, and is illustrated for the 2-D separable and for the quincunx images. Results are shown for the JPEG2000 database and for satellite images acquired on a quincunx sampling grid. The design of efficient quincunx filters is a difficult challenge which has already been addressed for specific cases. Our approach enables the design of less expensive filters adapted to the signal statistics to enhance the compression efficiency in a more general case. It is based on a two-step lifting scheme and joins the lifting theory with Wiener's optimization. The prediction step is designed in order to minimize the variance of the signal, and the update step is designed in order to minimize a reconstruction error. Application for lossy compression shows the performances of the method.