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1. Serotonergic neurons in 3D-hydrogels: Tunable environments to study axon dynamics

   Haiman, Justin H.; Hingorani, Melissa; Dunn, Geneva; Janusonis, S. (November 2022, Abstracts Society for Neuroscience)

   Serotonergic axons (fibers) have a ubiquitous distribution in vertebrate brains, where they form meshworks with well-defined, regionally-specific densities. In humans, perturbations of these densities have been associated with abnormal neural processes, including neuropsychiatric conditions. The self-organization of serotonergic meshworks depends on the cumulative behavior of many serotonergic axons, each one of which has a virtually unpredictable trajectory. In order to bridge the high stochasticity at the microscopic level and the regional stability at the mesoscopic level, we are developing tunable hydrogel systems that can support causal modeling of these processes. These same systems can support future restorative efforts in neural tissue because serotonergic axons are nearly unique in their ability to robustly regenerate in the adult brain. In the study, we extended our research in 2D-primary brainstem cultures (Hingorani et al., 2022) to 3D-hydrogels. Tunable hydrogel scaffolds can closely mimic the mechanical and biochemical properties of actual neural tissue in all three dimensions and are therefore qualitatively different from 2D-environments. However, the integration of these scaffolds with highly sensitive neurons poses unique challenges. As the first step in building a hydrogel-based platform for the bioengineering of serotonergic axons, we studied primary brainstem neurons in several commercially available hydrogel platforms. The viability and dynamics of serotonergic somata and neurites were analyzed at different days in vitro with immunocytochemistry and high-resolution confocal microscopy. In addition, live imaging of neuron growth cones was performed, and the observed dynamics was compared to our extensive database of holotomographic (refractive index-based) recordings in 2D-cultures. The progress and key problems will be discussed. This research was funded by NSF CRCNS (#1822517 and #2112862), NIMH (#MH117488), and the California NanoSystems Institute. 

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2. Fully parallel 512-ch dual-mode electrophysiology and neurochemical amplifiers

   https://doi.org/10.1109/MWSCAS54063.2022.9859534  

   Mulberry, Geoffrey; White, Kevin A.; Kim, Brian N. (August 2022, Fully parallel 512-ch dual-mode electrophysiology and neurochemical amplifiers)

   The electrical potential recordings using a large microelectrode array from neuronal cultures has been widely used to monitor neural spike activities and cellular activities. However, this approach does not monitor neurochemical release, and therefore only contains indirect information regarding synaptic neurotransmission. At the synapses, these action potentials instigate the secretion of neurotransmitters. Neurochemical recordings, based on electrochemical methods, enable the direct monitoring of synaptic transmissions with single-vesicle resolution as well as the excellent temporal resolution in the microsecond scale. The neural spike activities and the neurotransmitter secretions are related; however, one cannot be used to predict the other because of the complex vesicle trafficking and exocytosis processes. Here, we present a dual-mode amplifier array which integrates 256-ch transconductance amplifiers and 256-ch transimpedance amplifiers. The dual-mode amplifier array enables the simultaneous recordings of electrophysiology and neurochemical activities. Capturing both neurochemical and neural spike (action potential and local field potential) activities would provide comprehensive spatiotemporal images of the brain activities. 

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3. Spatially expandable fiber-based probes as a multifunctional deep brain interface

   https://doi.org/10.1038/s41467-020-19946-9  

   Jiang, Shan; Patel, Dipan C.; Kim, Jongwoon; Yang, Shuo; Mills, III, William A.; Zhang, Yujing; Wang, Kaiwen; Feng, Ziang; Vijayan, Sujith; Cai, Wenjun; et al (November 2020, Nature Communications)

   Abstract Understanding the cytoarchitecture and wiring of the brain requires improved methods to record and stimulate large groups of neurons with cellular specificity. This requires miniaturized neural interfaces that integrate into brain tissue without altering its properties. Existing neural interface technologies have been shown to provide high-resolution electrophysiological recording with high signal-to-noise ratio. However, with single implantation, the physical properties of these devices limit their access to one, small brain region. To overcome this limitation, we developed a platform that provides three-dimensional coverage of brain tissue through multisite multifunctional fiber-based neural probes guided in a helical scaffold. Chronic recordings from the spatially expandable fiber probes demonstrate the ability of these fiber probes capturing brain activities with a single-unit resolution for long observation times. Furthermore, usingThy1-ChR2-YFPmice we demonstrate the application of our probes in simultaneous recording and optical/chemical modulation of brain activities across distant regions. Similarly, varying electrographic brain activities from different brain regions were detected by our customizable probes in a mouse model of epilepsy, suggesting the potential of using these probes for the investigation of brain disorders such as epilepsy. Ultimately, this technique enables three-dimensional manipulation and mapping of brain activities across distant regions in the deep brain with minimal tissue damage, which can bring new insights for deciphering complex brain functions and dynamics in the near future. 

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4. Machine learning-assisted stiffness prediction in high-cell-density bioprinting

   https://doi.org/10.1631/bdm.2400454  

   Guan, Jiaao; Sun, Yazhi; Yao, Emmie J; Xiang, Yi; Melarkey, Mary K; Lu, Grace Y; Burns, Amelia H; Zhang, Nancy; Chen, Shaochen (July 2025, Bio-Design and Manufacturing)

   Abstract Bioprinting of cell-laden hydrogels is a rapidly growing field in tissue engineering. The advent of digital light processing (DLP) three-dimensional (3D) bioprinting technique has revolutionized the fabrication of complex 3D structures. By adjusting light exposure, it becomes possible to control the mechanical properties of the structure, a critical factor in modulating cell activities. To better mimic cell densities in real tissues, recent progress has been made in achieving high-cell-density (HCD) printing with high resolution. However, regulating the stiffness in HCD constructs remains challenging. The large volume of cells greatly affects the light-based DLP bioprinting by causing light absorption, reflection, and scattering. Here, we introduce a neural network-based machine learning technique to predict the stiffness of cell-laden hydrogel scaffolds. Using comprehensive mechanical testing data from 3D bioprinted samples, the model was trained to deliver accurate predictions. To address the demand of working with precious and costly cell types, we employed various methods to ensure the generalizability of the model, even with limited datasets. We demonstrated a transfer learning method to achieve good performance for a precious cell type with a reduced amount of data. The chosen method outperformed many other machine learning techniques, offering a reliable and efficient solution for stiffness prediction in cell-laden scaffolds. This breakthrough paves the way for the next generation of precision bioprinting and more customized tissue engineering. 

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5. Neuromodulation of Neural Oscillations in Health and Disease

   https://doi.org/10.3390/biology12030371  

   Weiss, Evan; Kann, Michael; Wang, Qi (March 2023, Biology)

   Using EEG and local field potentials (LFPs) as an index of large-scale neural activities, research has been able to associate neural oscillations in different frequency bands with markers of cognitive functions, goal-directed behavior, and various neurological disorders. While this gives us a glimpse into how neurons communicate throughout the brain, the causality of these synchronized network activities remains poorly understood. Moreover, the effect of the major neuromodulatory systems (e.g., noradrenergic, cholinergic, and dopaminergic) on brain oscillations has drawn much attention. More recent studies have suggested that cross-frequency coupling (CFC) is heavily responsible for mediating network-wide communication across subcortical and cortical brain structures, implicating the importance of neurotransmitters in shaping coordinated actions. By bringing to light the role each neuromodulatory system plays in regulating brain-wide neural oscillations, we hope to paint a clearer picture of the pivotal role neural oscillations play in a variety of cognitive functions and neurological disorders, and how neuromodulation techniques can be optimized as a means of controlling neural network dynamics. The aim of this review is to showcase the important role that neuromodulatory systems play in large-scale neural network dynamics, informing future studies to pay close attention to their involvement in specific features of neural oscillations and associated behaviors. 

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