Cytocompatible and water-stable ultrafine collagen fibers were electrospun by dissolving collagen in a low corrosive ethanol-water solvent and crosslinked by citric acid (CA) with glycerol as the crosslinking extender. Conventional solvents used for electrospinning of collagen either cause denaturation or contain more than 50% salt potentially leading to poor mechanical properties and water stability of the scaffolds. Collagen scaffolds have to be modified by techniques, such as, crosslinking to overcome the limitations in strength and stability. However, the existing crosslinking methods are either cytotoxic or ineffective. In this research, a benign ethanol-water solvent system and an extender-aided CA crosslinking method were developed. The native collagen conformation was retained after electrospinning, and the dry/wet strengths and water stability of fibers were substantially enhanced after crosslinking. The crosslinked electrospun scaffolds could maintain their fibrous structure for up to 30 days in phosphate-buffered saline at 37°C. Cells exhibited better attachment and growth on the CA crosslinked collagen fibers than on the glutaraldehyde crosslinked scaffolds.

Objective Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main Results The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (≤9.2%) and ROA (≤1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n=3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of <1% between approaches. Significance The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts.

Objective A computational model that accounts for heterogeneous tissue properties was used to compare multiple independent current control (MICC), multi‐stim set (MSS), and concurrent activation (co‐activation) current steering technologies utilized in deep brain stimulation (DBS) on volume of tissue activated (VTA) and power consumption. Methods A computational model was implemented in Sim4Life v4.0 with the multimodal image‐based detailed anatomical (MIDA) model, which accounts for heterogeneous tissue properties. A segmented DBS lead placed in the subthalamic nucleus (STN). Three milliamperes of current (with a 90 μs pseudo‐biphasic waveform) was distributed between two electrodes with various current splits. The laterality, directional accuracy, volume, and shape of the VTAs using MICC, MSS and co‐activation, and their power consumption were computed and compared. Results MICC, MSS, and coactivation resulted in less laterality of steering than single‐segment activation. Both MICC and MSS show directional inaccuracy (more pronounced with MSS) during radial current steering. Co‐activation showed greater directional accuracy than MICC and MSS at centerline between the two activated electrodes. MSS VTA volume was smaller and more compact with less current spread outside the active electrode plane than MICC VTA. There was no consistent pattern of power drain between MSS and MICC, but electrode co‐activation always used less power than either fractionating paradigm. Conclusion While current fractionalization technologies can achieve current steering between two segmented electrodes, this study shows that there are important limitations in accuracy and focus of tissue activation when tissue heterogeneity is accounted for.

These results suggest that pathway targeting with patient-specific model-based optimization algorithms can efficiently identify non-trivial electrode configurations for enhancing activation of clinically relevant pathways. However, the results also indicate that inter-pathway correlations can limit selectivity for certain pathways even with directional DBS leads.

Traditional mechanical testing often results in the destruction of the sample, and in the case of long term tissue engineered construct studies, the use of destructive assessment is not acceptable. A proposed alternative is the use of an imaging process called magnetic resonance elastography. Elastography is a nondestructive method for determining the engineered outcome by measuring local mechanical property values (i.e., complex shear modulus), which are essential markers for identifying the structure and functionality of a tissue. As a noninvasive means for evaluation, the monitoring of engineered constructs with imaging modalities such as magnetic resonance imaging (MRI) has seen increasing interest in the past decade 1 . For example, the magnetic resonance (MR) techniques of diffusion and relaxometry have been able to characterize the changes in chemical and physical properties during engineered tissue development 2 . The method proposed in the following protocol uses microscopic magnetic resonance elastography (μMRE) as a noninvasive MR based technique for measuring the mechanical properties of small soft tissues 3 . MRE is achieved by coupling a sonic mechanical actuator with the tissue of interest and recording the shear wave propagation with an MR scanner 4 . Recently, μMRE has been applied in tissue engineering to acquire essential growth information that is traditionally measured using destructive mechanical macroscopic techniques 5 . In the following procedure, elastography is achieved through the imaging of engineered constructs with a modified Hahn spin-echo sequence coupled with a mechanical actuator. As shown in Figure 1, the modified sequence synchronizes image acquisition with the transmission of external shear waves; subsequently, the motion is sensitized through the use of oscillating bipolar pairs. Following collection of images with positive and negative motion sensitization, complex division of the data produce a shear wave image. Then, the image is assessed using an inversion algorithm to generate a shear stiffness map 6 . The resulting measurements at each voxel have been shown to strongly correlate (R 2 >0.9914) with data collected using dynamic mechanical analysis 7 . In this study, elastography is integrated into the tissue development process for monitoring human mesenchymal stem cell (hMSC) differentiation into adipogenic and osteogenic constructs as shown in Figure 2. Video LinkThe video component of this article can be found at http://www.jove.com/video/3618/ Protocol Tissue Construct PreparationThe tissue construct preparation process consists of three main stages: expansion of cell population, seeding of cells onto a biomaterial scaffold, and differentiation through the use of chemical signaling molecules. The procedure for construct preparation is based on methods conducted by Dennis et al., Hong et al., and Marion and Mao 8,9,10 . Actuator CharacterizationCharacterization of the actuator is a vital step for the MRE experiment. MRE relies on the propagation of mechanical...

Deep brain stimulation (DBS) therapy is a potent tool for treating a range of brain disorders. High frequency stimulation (HFS) patterns used in DBS therapy are known to modulate neuronal spike rates and patterns in the stimulated nucleus; however, the spatial distribution of these modulated responses are not well understood. Computational models suggest that HFS modulates a volume of tissue spatially concentrated around the active electrode. Here, we tested this theory by investigating modulation of spike rates and patterns in non-human primate motor thalamus while stimulating the cerebellar-receiving area of motor thalamus, the primary DBS target for treating Essential Tremor. HFS inhibited spike activity in the majority of recorded cells, but increasing stimulation amplitude also shifted the response to a greater degree of spike pattern modulation. Modulated responses in both categories exhibited a sparse and long-range spatial distribution within motor thalamus, suggesting that stimulation preferentially affects afferent and efferent axonal processes traversing near the active electrode and that the resulting modulated volume strongly depends on the local connectome of these axonal processes. Such findings have important implications for current clinical efforts building predictive computational models of DBS therapy, developing directional DBS lead technology, and formulating closed-loop DBS strategies.

Objective: To study the effect of directional deep brain stimulation (DBS) electrode configuration and vertical electrode spacing on the volume of tissue activated (VTA) in the globus pallidus, pars interna (GPi). Background: Directional DBS leads may allow clinicians to precisely direct current fields to different functional networks within traditionally targeted brain areas. Modeling the shape and size of the VTA for various monopolar or bipolar configurations can inform clinical programming strategies for GPi DBS. However, many computational models of VTA are limited by assuming tissue homogeneity. Methods: We generated a multimodal image-based detailed anatomical (MIDA) computational model with a directional DBS lead (1.5 mm or 0.5 mm vertical electrode spacing) placed with segmented contact 2 at the ventral posterolateral "sensorimotor" region of the GPi. The effect of tissue heterogeneity was examined by replacing the MIDA tissues with a homogeneous tissue of conductance 0.3 S/m. DBS pulses (amplitude: 1 mA, pulse width: 60 µs, frequency: 130 Hz) were used to produce VTAs. The following DBS contact configurations were tested: single-segment monopole (2B-/Case+), two-segment monopole (2A-/2B-/Case+ and 2B-/3B-/Case+), ring monopole (2A-/2B-/2C-/Case+), one-cathode three-anode bipole (2B-/3A+/3B+/3C+), three-cathode three-anode bipole (2A-/2B-/2C-/3A+/3B+/3C+). Additionally, certain vertical configurations were repeated with 2 mA current amplitude. Results: Using a heterogeneous tissue model affected both the size and shape of the VTA in GPi. Electrodes with both 0.5 mm and 1.5 mm vertical spacing (1 mA) modeling showed that the single segment monopolar VTA was entirely contained within the GPi when the active electrode is placed at the posterolateral "sensorimotor" GPi. Two segments in a same ring and ring settings, however, produced VTAs outside of the GPi Zhang et al. Heterogeneous VTA Modeling in GPi border that spread into adjacent white matter pathways, e.g., optic tract and internal capsule. Both stacked monopolar settings and vertical bipolar settings allowed activation of structures dorsal to the GPi in addition to the GPi. Modeling of the stacked monopolar settings with the DBS lead with 0.5 mm vertical electrode spacing further restricted VTAs within the GPi, but the VTA volumes were smaller compared to the equivalent settings of 1.5 mm spacing.

Development of future closed-loop DBS therapies that rely on LFP feedback will benefit from implanting DBS arrays with electrode sizes and spacings that are more consistent with the dimensions of oscillatory sinks and sources within the brain.