A computational neural model that incorporates both intrinsic dynamics and sensory feedback in the Aplysia feeding network.

Studying the nervous system underlying animal motor control can shed light on how animals can adapt flexibly to a changing environment. We focus on the neural basis of feeding control in Aplysia californica. Using the Synthetic Nervous System framework, we developed a model of Aplysia feeding neural circuitry that balances neurophysiological plausibility and computational complexity. The circuitry includes neurons, synapses, and feedback pathways identified in existing literature. We organized the neurons into three layers and five subnetworks according to their functional roles. Simulation results demonstrate that the circuitry model can capture the intrinsic dynamics at neuronal and network levels. When combined with a simplified peripheral biomechanical model, it is sufficient to mediate three animal-like feeding behaviors (biting, swallowing, and rejection). The kinematic, dynamic, and neural responses of the model also share similar features with animal data. These results emphasize the functional roles of sensory feedback during feeding.

Semi-Automated Quantitative Evaluation of Neuron Developmental Morphology In Vitro Using the Change-Point Test.

Neuron morphology gives rise to distinct axons and dendrites and plays an essential role in neuronal functionality and circuit dynamics. In rat hippocampal neurons, morphological development occurs over roughly one week in vitro. This development has been qualitatively described as occurring in 5 stages. Still, there is a need to quantify cell growth to monitor cell culture health, understand cell responses to sensory cues, and compare experimental results and computational growth model predictions. To address this need, embryonic rat hippocampal neurons were observed in vitro over six days, and their processes were quantified using both standard morphometrics (degree, number of neurites, total length, and tortuosity) and new metrics (distance between change points, relative turning angle, and the number of change points) based on the Change-Point Test to track changes in path trajectories. Of the standard morphometrics, the total length of neurites per cell and the number of endpoints were significantly different between 0.5, 1.5, and 4 days in vitro, which are typically associated with Stages 2-4. Using the Change-Point Test, the number of change points and the average distance between change points per cell were also significantly different between those key time points. This work highlights key quantitative characteristics, both among common and novel morphometrics, that can describe neuron development in vitro and provides a foundation for analyzing directional changes in neurite growth for future studies.

Biohybrid robots: recent progress, challenges, and perspectives.

The past ten years have seen the rapid expansion of the field of biohybrid robotics. By combining engineered, synthetic components with living biological materials, new robotics solutions have been developed that harness the adaptability of living muscles, the sensitivity of living sensory cells, and even the computational abilities of living neurons. Biohybrid robotics has taken the popular and scientific media by storm with advances in the field, moving biohybrid robotics out of science fiction and into real science and engineering. So how did we get here, and where should the field of biohybrid robotics go next? In this perspective, we first provide the historical context of crucial subareas of biohybrid robotics by reviewing the past 10+ years of advances in microorganism-bots and sperm-bots, cyborgs, and tissue-based robots. We then present critical challenges facing the field and provide our perspectives on the vital future steps toward creating autonomous living machines.

Long-Fiber Embedded Hydrogel 3D Printing for Structural Reinforcement.

Hydrogels are candidate building blocks in a wide range of biomaterial applications including soft and biohybrid robotics, microfluidics, and tissue engineering. Recent advances in embedded 3D printing have broadened the design space accessible with hydrogel additive manufacturing. Specifically, the Freeform Reversible Embedding of Suspended Hydrogels (FRESH) technique has enabled the fabrication of complex 3D structures using extremely soft hydrogels, e.g., alginate and collagen, by assembling hydrogels within a fugitive support bath. However, the low structural rigidity of FRESH printed hydrogels limits their applications, especially those that require operation in nonaqueous environments. In this study, we demonstrated long-fiber embedded hydrogel 3D printing using a multihead printing platform consisting of a custom-built fiber extruder and an open-source FRESH bioprinter with high embedding fidelity. Using this process, fibers were embedded in 3D printed hydrogel components to achieve significant structural reinforcement (e.g., tensile modulus improved from 56.78 ± 8.76 to 382.55 ± 25.29 kPa and tensile strength improved from 9.44 ± 2.28 to 45.05 ± 5.53 kPa). In addition, we demonstrated the versatility of this technique by using fibers of a wide range of sizes and material types and implementing different 2D and 3D embedding patterns, such as embedding a conical helix using electrochemically aligned collagen fiber via nonplanar printing. Moreover, the technique was implemented using low-cost material and is compatible with open-source software and hardware, which facilitates its adoption and modification for new research applications.

Volumetric MicroCT Intensity Histograms of Fatty Infiltration Correlate with the Mechanical Strength of Rotator Cuff Repairs: An Ex Vivo Rabbit Model.

BACKGROUND: Fatty infiltration of the rotator cuff occurs after injury to the tendon and results in a buildup of adipose in the muscle. Fatty infiltration may be a biomarker for predicting future injuries and mechanical properties after tendon repair. As such, quantifying fatty infiltration accurately could be a relevant metric for determining the success of tendon repairs. Currently, fatty infiltration is quantified by an experienced observer using the Goutallier or Fuchs staging system, but because such score-based quantification systems rely on subjective assessments, newer techniques using semiautomated analyses in CT and MRI were developed and have met with varying degrees of success. However, semiautomated analyses of CT and MRI results remain limited in cases where only a few two-dimensional slices of tissue are examined and applied to the three-dimensional (3-D) tissue structure. We propose that it is feasible to assess fatty infiltration within the 3-D volume of muscle and tendon in a semiautomated fashion by selecting anatomic features and examining descriptive metrics of intensity histograms collected from a cylinder placed within the central volume of the muscle and tendon of interest. QUESTIONS/PURPOSES: (1) Do descriptive metrics (mean and SD) of intensity histograms from microCT images correlate with the percentage of fat present in muscle after rotator cuff repair? (2) Do descriptive metrics of intensity histograms correlate with the maximum load during mechanical testing of rotator cuff repairs? METHODS: We developed a custom semiautomated program to generate intensity histograms based on user-selected anatomic features. MicroCT images were obtained from 12 adult female New Zealand White rabbits (age 8 to 12 months, weight 3.7 kg ± 5 kg) that were randomized to surgical repair or sham repair of an induced infraspinatus defect. Intensity histograms were generated from images of the operative and contralateral intact shoulder in these rabbits which were presented to the user in a random order without identifying information to minimize sources of bias. The mean and SD of the intensity histograms were calculated and compared with the total percentage of the volume threshold as fat. Patterns of fat identified were qualitatively compared with histologic samples to confirm that thresholding was detecting fat. We conducted monotonic tensile strength-to-failure tests of the humeral-infraspinatus bone-tendon-muscle complex, and evaluated associations between histogram mean and SDs and maximum load. RESULTS: The total percentage of fat was negatively correlated with the intensity histogram mean (Pearson correlation coefficient -0.92; p < 0.001) and positively with intensity histogram SD (Pearson correlation coefficient 0.88; p < 0.001), suggesting that the increase in fat leads to a reduction and wider variability in volumetric tissue density. The percentage of fat content was also negatively correlated with the maximum load during mechanical testing (Pearson correlation coefficient -78; p = 0.001), indicating that as the percentage of fat in the volume increases, the mechanical strength of the repair decreases. Furthermore, the intensity histogram mean was positively correlated with maximum load (Pearson correlation coefficient 0.77; p = 0.001) and histogram SD was negatively correlated with maximum load (Pearson correlation coefficient -0.72; p = 0.004). These correlations were strengthened by normalizing maximum load to account for animal size (Pearson correlation coefficient 0.86 and -0.9, respectively), indicating that as histogram mean decreases, the maximum load of the repair decreases and as histogram spread increases, the maximum load decreases. CONCLUSION: In this ex vivo rabbit model, a semiautomated approach to quantifying fat on microCT images was a noninvasive way of quantifying fatty infiltration associated with the strength of tendon healing. CLINICAL RELEVANCE: Histogram-derived variables may be useful as surrogate measures of repair strength after rotator cuff repair. The preclinical results presented here provide a foundation for future studies to translate this technique to patient studies and additional imaging modalities. This semiautomated method provides an accessible approach to quantification of fatty infiltration by users of varying experience and can be easily adapted to any intensity-based imaging approach. To translate this approach to clinical practice, this technique should be calibrated for MRI or conventional CT imaging and applied to patient scans. Further investigations are needed to assess the correlation of volumetric intensity histogram descriptive metrics to clinical mechanical outcomes.

Control for multifunctionality: bioinspired control based on feeding in Aplysia californica.

Animals exhibit remarkable feats of behavioral flexibility and multifunctional control that remain challenging for robotic systems. The neural and morphological basis of multifunctionality in animals can provide a source of bioinspiration for robotic controllers. However, many existing approaches to modeling biological neural networks rely on computationally expensive models and tend to focus solely on the nervous system, often neglecting the biomechanics of the periphery. As a consequence, while these models are excellent tools for neuroscience, they fail to predict functional behavior in real time, which is a critical capability for robotic control. To meet the need for real-time multifunctional control, we have developed a hybrid Boolean model framework capable of modeling neural bursting activity and simple biomechanics at speeds faster than real time. Using this approach, we present a multifunctional model of Aplysia californica feeding that qualitatively reproduces three key feeding behaviors (biting, swallowing, and rejection), demonstrates behavioral switching in response to external sensory cues, and incorporates both known neural connectivity and a simple bioinspired mechanical model of the feeding apparatus. We demonstrate that the model can be used for formulating testable hypotheses and discuss the implications of this approach for robotic control and neuroscience.

Kinesin and Dynein Mechanics: Measurement Methods and Research Applications.

Motor proteins play critical roles in the normal function of cells and proper development of organisms. Among motor proteins, failings in the normal function of two types of proteins, kinesin and dynein, have been shown to lead many pathologies, including neurodegenerative diseases and cancers. As such, it is critical to researchers to understand the underlying mechanics and behaviors of these proteins, not only to shed light on how failures may lead to disease, but also to guide research toward novel treatment and nano-engineering solutions. To this end, many experimental techniques have been developed to measure the force and motility capabilities of these proteins. This review will (a) discuss such techniques, specifically microscopy, atomic force microscopy (AFM), optical trapping, and magnetic tweezers, and (b) the resulting nanomechanical properties of motor protein functions such as stalling force, velocity, and dependence on adenosine triphosophate (ATP) concentrations will be comparatively discussed. Additionally, this review will highlight the clinical importance of these proteins. Furthermore, as the understanding of the structure and function of motor proteins improves, novel applications are emerging in the field. Specifically, researchers have begun to modify the structure of existing proteins, thereby engineering novel elements to alter and improve native motor protein function, or even allow the motor proteins to perform entirely new tasks as parts of nanomachines. Kinesin and dynein are vital elements for the proper function of cells. While many exciting experiments have shed light on their function, mechanics, and applications, additional research is needed to completely understand their behavior.

Organismal Engineering: Towards a Robotic Taxonomic Key for Devices Using Organic Materials.

Can we create robots with the behavioral flexibility and robustness of animals? Engineers often use bio-inspiration to mimic animals. Recent advances in tissue engineering now allow the use of components from animals. By integrating organic and synthetic components, researchers are moving towards the development of engineered organisms whose structural framework, actuation, sensing, and control are partially or completely organic. This review discusses recent exciting work demonstrating how organic components can be used for all facets of robot development. Based on this analysis, we propose a Robotic Taxonomic Key to guide the field towards a unified lexicon for device description.