Plasticity and Adaptation in Neuromorphic Biohybrid Systems

Neuromorphic systems take inspiration from the principles of biological information processing to form hardware platforms that enable the large-scale implementation of neural networks. The recent years have seen both advances in the theoretical aspects of spiking neural networks for their use in classification and control tasks and a progress in electrophysiological methods that is pushing the frontiers of intelligent neural interfacing and signal processing technologies. At the forefront of these new technologies, artificial and biological neural networks are tightly coupled, offering a novel \u201cbiohybrid\u201d experimental framework for engineers and neurophysiologists. Indeed, biohybrid systems can constitute a new class of neuroprostheses opening important perspectives in the treatment of neurological disorders. Moreover, the use of biologically plausible learning rules allows forming an overall fault-tolerant system of co-developing subsystems. To identify opportunities and challenges in neuromorphic biohybrid systems, we discuss the field from the perspectives of neurobiology, computational neuroscience, and neuromorphic engineering. \ua9 2020 The Author(s

Developing an In Vitro Assay for Detection and Characterization of Functional Connectivity within Transplantation Candidate Embryonic Stem Cell-Derived V2a Interneuron Networks

Facilitating plasticity after spinal cord injury tends to be the focus of most modern interventions for this condition. In particular, stem cell therapies attempt to both modulate and mimic some of the native plasticity after injury through multiple mechanisms. One such mechanism, the creation of new exogenous relay circuits bridging the injury, has been explored extensively, revealing serious impediments to its optimization and adoption for clinical settings. Our collaborator, the Sakiyama-Elbert group, has spent years addressing the first limitation, the variability of cellular graft composition, by perfecting protocols to generate embryonic stem cell (ESC)-derived populations of neurons with pre-determined genetic identity. Recently, they developed a protocol to develop highly-enriched populations of Chx10-expressing V2a interneurons (INs), a ventral interneuron population that has garnered recent interest due to its role in central pattern generating function and favorable phenotypic properties. This predominantly glutamatergic and long, ipsilaterally projecting population appears to be a prime candidate for transplantation therapies for SCI, especially for the creation of relay circuits that can potentially circumnavigate injuries. The research documented in this thesis attempts to begin to address the second limitation of stem cell transplantation therapy, our minimal understanding of intra-graft network connectivity after transplantation. Due to the limitations of current techniques for evaluating the connectivity of populations like ESC-derived V2a INs, the relationship between functional recovery and the functional properties of the novel circuits formed within the graft still eludes researchers. This thesis focuses on the development of an assay capable of rapidly detecting connectivity within ESC-derived candidate populations. By extending previous work in the stem cell field, we combine in vitro multi-electrode arrays (MEAs) with an extensively studied metric of functional connectivity, cross-correlation, to detect and characterize individual functional connections between ESC-derived neurons. We first validated this assay by culturing ESC-derived populations differentiated for increased expression of Chx10 on MEAs. We found that both dissociated and aggregated cultures formed functional busting networks with significant functional connectivity detected with the use of Between-Sample Analysis of Connectivity, a methodology originally developed for in vitro circadian networks. Aggregated networks, however, had much more consistent electrode coverage and individual neuron detection that dissociated networks. After this validation study, we characterized the functional connectivity within highly-enriched populations of ESC-V2a INs, comparing their connectivity to populations of ESC-MN/glia and mixed populations of ESC-V2a/MN/glia. We found that ESC-MN/glia aggregates formed active networks with a variety of activity and functional connectivity that was dependent on the transmission of glutamate. ESC-V2a INs could only survive out to the 4-week time point if they were grown in media conditioned with glial factors, but these cultures still lacked spontaneous extracellular activity. Mixed ESC-V2a/MN/glia populations formed the most active networks and had thousands of detectable connections which were also dependent on glutamate transmission. Application of glycine antagonist modulated network activity but the underlying cause is fairly inconclusive due to possible secondary effects. High growth factor concentrations in the growth media actually decreased network activity and detectable functional connections in the mixed populations. All of these findings in this proof of concept study collectively suggest that a mixture of ESC-V2a INs and ESC-MN/glia may be the most viable candidate for transplantation and sets the stage for future investigations into the manipulability of their connectivity with electrical stimulation, as well as scaled versions of this assay performed in combination with animal studies

Information processing in dissociated neuronal cultures of rat hippocampal neurons

One of the major aims of Systems Neuroscience is to understand how the nervous system transforms sensory inputs into appropriate motor reactions. In very simple cases sensory neurons are immediately coupled to motoneurons and the entire transformation becomes a simple reflex, in which a noxious signal is immediately transformed into an escape reaction. However, in the most complex behaviours, the nervous system seems to analyse in detail the sensory inputs and is performing some kind of information processing (IP). IP takes place at many different levels of the nervous system: from the peripheral nervous system, where sensory stimuli are detected and converted into electrical pulses, to the central nervous system, where features of sensory stimuli are extracted, perception takes place and actions and motions are coordinated. Moreover, understanding the basic computational properties of the nervous system, besides being at the core of Neuroscience, also arouses great interest even in the field of Neuroengineering and in the field of Computer Science. In fact, being able to decode the neural activity can lead to the development of a new generation of neuroprosthetic devices aimed, for example, at restoring motor functions in severely paralysed patients (Chapin, 2004). On the other side, the development of Artificial Neural Networks (ANNs) (Marr, 1982; Rumelhart & McClelland, 1988; Herz et al., 1981; Hopfield, 1982; Minsky & Papert, 1988) has already proved that the study of biological neural networks may lead to the development and to the design of new computing algorithms and devices. All nervous systems are based on the same elements, the neurons, which are computing devices which, compared to silicon components, are much slower and much less reliable. How are nervous systems of all living species able to survive being based on slow and poorly reliable components? This obvious and na\uefve question is equivalent to characterizing IP in a more quantitative way. In order to study IP and to capture the basic computational properties of the nervous system, two major questions seem to arise. Firstly, which is the fundamental unit of information processing: 2 single neurons or neuronal ensembles? Secondly, how is information encoded in the neuronal firing? These questions - in my view - summarize the problem of the neural code. The subject of my PhD research was to study information processing in dissociated neuronal cultures of rat hippocampal neurons. These cultures, with random connections, provide a more general view of neuronal networks and assemblies, not depending on the circuitry of a neuronal network in vivo, and allow a more detailed and careful experimental investigation. In order to record the activity of a large ensemble of neurons, these neurons were cultured on multielectrode arrays (MEAs) and multi-site stimulation was used to activate different neurons and pathways of the network. In this way, it was possible to vary the properties of the stimulus applied under a controlled extracellular environment. Given this experimental system, my investigation had two major approaches. On one side, I focused my studies on the problem of the neural code, where I studied in particular information processing at the single neuron level and at an ensemble level, investigating also putative neural coding mechanisms. On the other side, I tried to explore the possibility of using biological neurons as computing elements in a task commonly solved by conventional silicon devices: image processing and pattern recognition. The results reported in the first two chapters of my thesis have been published in two separate articles. The third chapter of my thesis represents an article in preparation

Creation of Defined Single Cell Resolution Neuronal Circuits on Microelectrode Arrays

The way cell-cell organization of neuronal networks influences activity and facilitates function is not well understood. Microelectrode arrays (MEAs) and advancing cell patterning technologies have enabled access to and control of in vitro neuronal networks spawning much new research in neuroscience and neuroengineering. We propose that small, simple networks of neurons with defined circuitry may serve as valuable research models where every connection can be analyzed, controlled and manipulated. Towards the goal of creating such neuronal networks we have applied microfabricated elastomeric membranes, surface modification and our unique laser cell patterning system to create defined neuronal circuits with single-cell precision on MEAs. Definition of synaptic connectivity was imposed by the 3D physical constraints of polydimethylsiloxane elastomeric membranes. The membranes had 20μm clear-through holes and 2-3μm deep channels which when applied to the surface of the MEA formed microwells to confine neurons to electrodes connected via shallow tunnels to direct neurite outgrowth. Tapering and turning of channels was used to influence neurite polarity. Biocompatibility of the membranes was increased by vacuum baking, oligomer extraction, and autoclaving. Membranes were bound to the MEA by oxygen plasma treatment and heated pressure. The MEA/membrane surface was treated with oxygen plasma, poly-D-lysine and laminin to improve neuron attachment, survival and neurite outgrowth. Prior to cell patterning the outer edge of culture area was seeded with 5x105 cells per cm and incubated for 2 days. Single embryonic day 7 chick forebrain neurons were then patterned into the microwells and onto the electrodes using our laser cell patterning system. Patterned neurons successfully attached to and were confined to the electrodes. Neurites extended through the interconnecting channels and connected with adjacent neurons. These results demonstrate that neuronal circuits can be created with clearly defined circuitry and a one-to-one neuron-electrode ratio. The techniques and processes described here may be used in future research to create defined neuronal circuits to model in vivo circuits and study neuronal network processing

Multi-electrode array recording and data analysis methods for molluscan central nervous systems

In this work the use of the central nervous system (CNS) of the aquatic snail Lymnaea stagnalis on planar multi-electrode arrays (MEAs) was developed and analysis methods for the data generated were created. A variety of different combinations of configurations of tissue from the Lymnaea CNS were explored to determine the signal characteristics that could be recorded by sixty channel MEAs. In particular, the suitability of the semi-intact system consisting of the lips, oesophagus, CNS, and associated nerve connectives was developed for use on the planar MEA. The recording target area of the dorsal surface of the buccal ganglia was selected as being the most promising for study and recordings of its component cells during fictive feeding behaviour stimulated by sucrose were made. The data produced by this type of experimentation is very high volume and so its analysis required the development of a custom set of software tools. The goal of this tool set is to find the signal from individual neurons in the data streams of the electrodes of a planar MEA, to estimate their position, and then to predict their causal connectivity. To produce such an analysis techniques for noise filtration, neural spike detection, and group detection of bursts of spikes were created to pre-process electrode data streams. The Kohonen self-organising map (SOM) algorithm was adapted for the purpose of separating detected spikes into data streams representing the spike output of individual cells found in the target system. A significant addition to SOM algorithm was developed by the concurrent use of triangulation methods based on current source density analysis to predict the position of individual cells based on their spike output on more than one electrode. The likely functional connectivity of individual neurons identified by the SOM technique were analysed through the use of a statistical causality method known as Granger causality/causal connectivity. This technique was used to produce a map of the likely connectivity between neural sources

Biomedical Tissue Culture

This book describes many aspects of tissue culture models in an extensive manner. The book includes many topics like, the development of cultural methods to produce massive neuronal syncytial connections and induce their fusion with formation of bi- and multinucleated cells, the applicability in research of cell lines derived from the cultivation of placenta derived cells and cell populations with properties of progenitor/stem cells, the procedures that may be used to regenerate cartilage tissue with appropriate mechanical properties, the improvements made in the use of cell culture for virus isolation, tissue-based models for HCV replication in vitro, cultures to study the pathogenicity of enteropathogenic bacteria, the use of viral DNA and cDNA Array in the diagnosis of respiratory tract infections (RTI) in comparison with routine diagnosis methods

Engineering Hyaluronic Acid Carbon Nanotube Nanofibers: A Peripheral Nerve Interface To Electrically Stimulate Regeneration

Peripheral nerve injuries annually affect hundreds of thousands of people globally. Current treatments like the gold standard autograft and commercially available nerve guide conduits (NGC) are insufficient to repair long gap peripheral nerve injuries. NGCs can aid recovery but lack key microenvironment cues that promote nerve regeneration. We hypothesized that providing topographical, mechanical, and electrical guidance cues through a nanofibrous composite biopolymer would result in improved neuron growth metrics using an in vitro model. We embedded hydrophilic carbon nanotubes (CNT) within hyaluronic acid (HA) nanofibers by electrospinning. The aims of this study were (1) to define the topographical, nanomechanical, and electrochemical material properties of HA-CNT nanofibers and (2) to determine the electrical stimulus parameters required to elicit increased neurite outgrowth on our nanofibrous scaffold. Mechanical properties were evaluated under physiological conditions using nanofiber samples hydrated to equilibrium. Local elastic modulus was measured by fitting atomic force microscopy quantitative nanomechanical mapping data to the Sneddon model. The mean and standard error for Local Young\u27s modulus was 74.93±12.6 kPa for HA nanofibers and 174.85±31.9 kPa for HA-CNT nanofibers. The electrochemical characterization performed was electrical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Conductivity and charge storage capacity of HA-CNT nanofibers were significantly increased. EIS resulted in a decreased resistance to current flow by a factor of 1.7 at 20 Hz and 1.2 at 1kHz. CV revealed a 2.1-fold increase in specific capacitance (mF/cm2) of HA-CNT relative to HA nanofibers. Chick dorsal root ganglia neurons grown on HA or HA-CNT substrates for 24h were either unstimulated or stimulated at 20Hz for 30min or 60min using a charge balanced 150, 200, or 250mV/mm square wave. Neuron outgrowth after 72h was significantly longer on HA-CNT substrates electrically stimulated for 60min at all stimulus amplitudes versus all other groups (p \u3c 0.01). Significant effects of fiber type, time, and stimulus amplitude were also observed when measuring neuron viability. This study demonstrates the potential of combining electrical stimulation with material based repair strategies for neural regeneration. Further, the results contribute to defining the electrical stimulus parameters necessary for regeneration in the peripheral nerve environment. Incorporating well-dispersed hydrophilic CNTs in HA nanofibers significantly enhances neural regeneration following electrical stimulation in vitro. Future work encompasses characterizing glial responses to electrical stimulation including electrophysiological calcium imaging assays to elucidate the governing molecular mechanisms for both neuronal and glial behavior

Focussed MeV-Ion Micro- and Nano-Beams in the Life Sciences: Selected Applications

This work presents the development of a sub-micron nuclear microprobe for applications in the life sciences. It includes quantitative trace element analysis with sub-micron spatial resolution, 2D- and 3D-microscopy of density distributions and the targeted irradiation of living cells with counted single ions. The analytical methods base on particle induced X-ray emission spectrometry (PIXE), Rutherford backscattering spectrometry (RBS), scanning transmission ion microscopy (STIM) and STIM-tomography. The specific development of the existing nuclear microprobe LIPSION led to an improved performance of the capabilities for trace element analysis. For sub-micron analysis the spatial resolution could be improved to 300 nm at a sensitivity of about 1 µg/g for metal ions in biological matrices; for a resolution of 1 µm the sensitivity was improved to 200 ng/g (3 µmol/l). This habilitation thesis comprises a short general introduction including the motivation to utilize focussed high energy ion beams, an overview on the applications and actual research fields. The introduction is followed by the basic principles of the equipments and analytical methods. An estimation of the limits of resolution for element analytical and single ion techniques is given for the Leipzig system. Thereafter, selected studies from different research areas are presented. The first presented application is a study from environmental air pollution research. It is demonstrated that the microscopic elemental analysis of single aerosol particles can be used to assess the contributions from different sources. A further example is the analysis of the distribution of nanoparticles in skin cross-sections for a risk assessment of the applications of nanosized physical UV-filters in cosmetic products. The risk assessment is followed by the micro-analysis of trace elements, especially of bound metal ions, in brain sections on the cellular and sub-cellular level. After this the application of focussed MeV ion beams in low dose radiobiological research is presented. Finally, the analysis of 3D-density distributions by proton micro-tomography is demonstrated. A summary concludes on the applications and gives an outlook to further applications and methodological developments. The appendix comprises the relevant publications of the author.Die vorliegende Arbeit etabliert für Anwendungen in den Lebenswissenschaften den Einsatz hochfokussierter MeV-Ionenstrahlen für nuklear-mikroskopische Methoden der quantitativen Spurenelementanalyse, der 2D- und 3D-Dichtemikroskopie sowie für die gezielte Bestrahlung einzelner lebender Zellen für radiobiologische Experimente. Zur Anwendung kamen die Methoden ortsaufgelöste Protonen induzierte Röntgenfluoreszenzanalyse (particle induced X-ray emission - PIXE), Spektrometrie rückgestreuter Ionen (Rutherford backscattering spectrometry - RBS) und Rastertransmissionsionenmikroskopie (scanning transmission ion microscopy - STIM). Durch eine gezielte Weiterentwicklung des bestehenden Ionenstrahlmikroskops, der Hochenergie Ionennanosonde LIPSION, konnte die Ortsauflösung für Spurenelementanalyse auf unter 300 nm verbessert werden, beziehungsweise die Sensitivität für Metallionen in biologischen Proben auf unter 200 ng/g (3 µmol/l) bei einer Ortsauflösung von 1 µm verbessert werden. Die Habilitationsschrift umfasst eine kurze allgemeine Einleitung einschließlich der Motivation für den Einsatz fokussierter MeV-Ionenstrahlen sowie einen Überblick über die Anwendungsgebiete und aktuellen Forschungsschwerpunkte. Danach werden kurz die Grundlagen der Technik und Methoden vorgestellt, gefolgt von einer Abschätzung der A\u7fuflösungsgrenzen für Elementanalysen und Einzelionentechniken. Danach werden ausgewählte Anwendungen aus verschiedenen Forschungsgebieten vorgestellt. Das erstes Beispiel ist aus der Umweltforschung. Es wird dargestellt, wie mittels ortsaufgelöster Elementspektroskopie eine Abschätzung der Feinstaubbelastung nach Beiträgen einzelner Verursacherquellen erfolgen kann. Dann folgt als Beispiel eine ortsaufgelöste Analyse der Verteilung von Nanopartikeln aus Sonnencremes in Hautquerschnitten zur Risikoabschätzung der Anwendungen von Nanotechnologie in kosmetischen Produkten. Desweiteren werden Studien der Spurenelementverteilung, speziell der von gebundenen Metallionen, in Hirnschnitten auf zellulärer und subzellulärer Ebene erläutert. Das anschließende Beispiel erläutert die Anwendung niedriger Energiedosen in der Radiobiologie anhand des Beschusses einzelner lebender Zellen mit abgezählten einzelnen Ionen. Als letztes Beispiel wird die Anwendung hochfokussierter Ionenstrahlen für die Mikrotomographie gezeigt. Abschließend folgt eine zusammenfassende Bewertung der vorgestellten Anwendungen mit einem Ausblick auf weitere Anwendungen und methodische Entwicklungen. Der Arbeit sind die relevanten Veröffentlichungen mit Beteiligung des Autors als Anhang beigefügt

Construction of carbon-based three-dimensional neural scaffolds and their structural regulation

Motivation The brain is formed by an intricate assembly of cellular networks, where neurons are embedded in an extracellular matrix (ECM) consisting of an intricate three-dimensional (3D) mesh of proteins that provides complex chemical, electrical and mechanical signalling.1 Given this complexity as well as the limitations of in vivo studies,2 it is important to develop in vitro models able to recapitulate the brain connectivity at various levels and ultimately, provide a mimic of the human brain suitable for preclinical applications.3 By reproducing cell to cell and cell to ECM interactions so to mimic the in vivo microenvironment, 3D tissue engineering promotes more physiological responses than conventional 2D cultures.4 Toward this goal, several 3D supporting materials or scaffolds have been developed, tested and applied.5 Among them, emerging carbon-based materials, such as carbon nanotubes (CNTs) 6, graphene oxide 7 and graphene foam (GF) 8 have high mechanical stability, high porosity and dense interconnectivity, providing a 3D microenvironment beneficial for cell growth and interaction.9 My Work In my Ph.D., I aimed to construct 3D neural scaffolds based on carbon materials especially graphene and carbon nanotubes (CNTs) and explore the regulation of these scaffolds for specific application in neural cultures. To achieve these goals, I combined chemical vapor deposition (CVD) and nano-fabrication for the preparation of different kinds of scaffolds and then used these scaffolds for the neural cultures. In the characterization of neural culture part, I mainly used optical imaging methods, particularly immunochemistry and calcium imaging, to investigate the neuronal network morphology and electrical dynamics of reconstructed 3D primary cultures from rats. These are my main results: 1) By using Fe nanoparticles confined to the interlamination of graphite as catalyst, we have obtained a fully 3D interconnected CNT web through the pores of graphene foam (GCNT web) by in situ chemical vapor deposition. This 3D GCNT web has a thickness up to 1.5 mm and a completely geometric, mechanical and electrical interconnectivity. Dissociated cortical cells cultured inside the GCNT web form a functional 3D cortex-like network exhibiting a spontaneous electrical activity that is closer to what is observed in vivo. Moreover, we have explored the application of this functional 3D cortex-like network: 2) By co-culturing and fluorescently labelling glioma and healthy cortical cells with different colours, a new in vitro model is obtained to investigate malignant glioma infiltration. This model allows reconstruction of the 3D trajectories and velocity distribution of individual infiltrating glioma with an unprecedented precision. The model is cost-effective and allows a quantitative and rigorous screening of anti-cancer drugs. 3) We have fabricated a 3D free-standing ordered graphene (3D-OG) network with the pore size of 20 \u3bcm, the skeleton width of 20 \u3bcm and an exact 90\ub0 orientation angle between the building blocks. Extensive interconnectivity of graphene sheets allows 3D-OG scaffolds to be free-standing and to be easily manipulated. When primary cortical cells are cultured on 3D-OG scaffolds, the cells form well-defined 3D connections with a cellular density similar to that observed when cells were cultured on 2D coverslip. In contrast to the 2D coverslips culture, astrocytes cultured on 3D-OG scaffolds did not have a flat morphology but had a more ramified shape similar to that seen in vivo conditions. Moreover, neurons on 3D-OG scaffolds had axons and dendrites aligned along the graphene skeleton allowing the formation of neuronal networks with highly controlled connections. Neuronal networks grown on 3D-OG scaffolds had a higher electrical activity with functional signaling over a long distance. 4) We have constructed a novel scaffold of three-dimensional bacterial cellulose-graphene foam (3D-BC/G) for neural stem cells (NSCs) in vitro, which was prepared via in situ bacterial cellulose interfacial polymerization on the skeleton surface of porous graphene foam. We found that 3D-BC/G can not only support NSCs growth and adhesion, but also keep NSCs stemness and enhanced its proliferative capacity. Further phenotypic analysis indicated that 3D-BC/G can induce NSCs selectively to differentiate into neurons, forming a neural network in short time. It was also meanwhile demonstrated to have good biocompatibility for primary cortical neurons and enhanced neuronal network activities by measuring calcium transient