Daily quetiapine after severe TBI improves learning and memory.

BACKGROUND: Traumatic brain injury (TBI) induces cognitive deficits driven by neuroinflammation and cerebral edema. The commonly used atypical antipsychotic, quetiapine (QTP), has been recently shown to improve post-TBI outcomes. We hypothesized that QTP would thereby improve animal learning and memory 2 weeks after severe TBI. METHODS: CD1 male mice (n = 35) underwent severe TBI (controlled cortical impact, injury, I) or sham craniotomy (S), followed by BID saline (P, placebo) or QTP (10 or 20 mg/kg, IP) for 2 weeks. Animals underwent Morris Water Maze (MWM) exercises to gauge spatial learning and memory. The distance and time required for swimming animals to reach the platform area (Zone 5, Z5) located in quadrant 1 (Zone 1, Z1) was calculated from digital video recordings analyzed using Ethovision software. Animal bodyweights were recorded daily and on day 14, injured cerebral hemispheres were procured for edema determination (wet-to-dry ratio). Intergroup differences were evaluated with ANOVA/Bonferroni correction (p < 0.05). RESULTS: On day 14, animal weight loss recovery was lowest in I + P compared to I + QTP20 and I + QTP10 (p ≤ 0.01 for either). Cerebral edema was greatest in I + P, and only significantly decreased in I + QTP20 (p < 0.05). Both QTP doses similarly improved spatial learning by significantly reducing latency time and travel distance to target zones (p < 0.05). In probe memory trials, only I + QTP20 and not I + QTP10 significantly favored animal reaching or crossing into target zones (p < 0.05). CONCLUSION: Post-TBI QTP reduces brain edema and improves spatial learning and memory with a potential dose dependence impact benefiting memory up to 14 days. These data suggest an unanticipated QTP benefit following brain injury that should be specifically explored.

Grand Challenges at the Interface of Engineering and Medicine.

Over the past two decades Biomedical Engineering has emerged as a major discipline that bridges societal needs of human health care with the development of novel technologies. Every medical institution is now equipped at varying degrees of sophistication with the ability to monitor human health in both non-invasive and invasive modes. The multiple scales at which human physiology can be interrogated provide a profound perspective on health and disease. We are at the nexus of creating "avatars" (herein defined as an extension of "digital twins") of human patho/physiology to serve as paradigms for interrogation and potential intervention. Motivated by the emergence of these new capabilities, the IEEE Engineering in Medicine and Biology Society, the Departments of Biomedical Engineering at Johns Hopkins University and Bioengineering at University of California at San Diego sponsored an interdisciplinary workshop to define the grand challenges that face biomedical engineering and the mechanisms to address these challenges. The Workshop identified five grand challenges with cross-cutting themes and provided a roadmap for new technologies, identified new training needs, and defined the types of interdisciplinary teams needed for addressing these challenges. The themes presented in this paper include: 1) accumedicine through creation of avatars of cells, tissues, organs and whole human; 2) development of smart and responsive devices for human function augmentation; 3) exocortical technologies to understand brain function and treat neuropathologies; 4) the development of approaches to harness the human immune system for health and wellness; and 5) new strategies to engineer genomes and cells.

Delayed tranexamic acid after traumatic brain injury impedes learning and memory: Early tranexamic acid is favorable but not in sham animals.

BACKGROUND: Early but not late tranexamic acid (TXA) after TBI preserves blood-brain-barrier integrity, but it is unclear if and how dose timing affects cognitive recovery beyond hours postinjury. We hypothesized that early (1 hour post-TBI) but not late (24 hours post-TBI) TXA administration improves cognitive recovery for 14 days. METHODS: CD1 male mice (n = 25) were randomized to severe TBI (injury [I], by controlled cortical impact) or sham craniotomy (S) followed by intravenous saline at 1 hour (placebo [P1]) or 30 mg/kg TXA at 1 hour (TXA1) or 24 hours (TXA24). Daily body weights, Garcia Neurological Test scores, brain/lung water content, and Morris water maze exercises quantifying swimming traffic in the platform quadrant (zone [Z] 1) and platform area (Z5) were recorded for up to 14 days. RESULTS: Among injured groups, I-TXA1 demonstrated fastest weight gain for 14 days and only I-TXA1 showed rapid (day 1) normalization of Garcia Neurological Test ( p = 0.01 vs. I-P1, I-TXA24). In cumulative spatial trials, compared with I-TXA1, I-TXA24 hindered learning (distance to Z5 and % time in Z1, p < 0.05). Compared with I-TXA1, I-TXA24 showed poorer memory with less Z5 time (0.51 vs. 0.16 seconds, p < 0.01) and Z5 crossing frequency. Unexpectedly, TXA in uninjured animals (S-TXA1) displayed faster weight gain but inferior learning and memory. CONCLUSION: Early TXA appears beneficial for cognitive and behavioral outcomes following TBI, although administration 24 hours postinjury consistently impairs cognitive recovery. Tranexamic acid in sham animals may lead to adverse effects on cognition.

Time-dependent homeostatic mechanisms underlie brain-derived neurotrophic factor action on neural circuitry.

Plasticity and homeostatic mechanisms allow neural networks to maintain proper function while responding to physiological challenges. Despite previous work investigating morphological and synaptic effects of brain-derived neurotrophic factor (BDNF), the most prevalent growth factor in the central nervous system, how exposure to BDNF manifests at the network level remains unknown. Here we report that BDNF treatment affects rodent hippocampal network dynamics during development and recovery from glutamate-induced excitotoxicity in culture. Importantly, these effects are not obvious when traditional activity metrics are used, so we delve more deeply into network organization, functional analyses, and in silico simulations. We demonstrate that BDNF partially restores homeostasis by promoting recovery of weak and medium connections after injury. Imaging and computational analyses suggest these effects are caused by changes to inhibitory neurons and connections. From our in silico simulations, we find that BDNF remodels the network by indirectly strengthening weak excitatory synapses after injury. Ultimately, our findings may explain the difficulties encountered in preclinical and clinical trials with BDNF and also offer information for future trials to consider.

Plasticity impairment alters community structure but permits successful pattern separation in a hippocampal network model.

Patients who suffer from traumatic brain injury (TBI) often complain of learning and memory problems. Their symptoms are principally mediated by the hippocampus and the ability to adapt to stimulus, also known as neural plasticity. Therefore, one plausible injury mechanism is plasticity impairment, which currently lacks comprehensive investigation across TBI research. For these studies, we used a computational network model of the hippocampus that includes the dentate gyrus, CA3, and CA1 with neuron-scale resolution. We simulated mild injury through weakened spike-timing-dependent plasticity (STDP), which modulates synaptic weights according to causal spike timing. In preliminary work, we found functional deficits consisting of decreased firing rate and broadband power in areas CA3 and CA1 after STDP impairment. To address structural changes with these studies, we applied modularity analysis to evaluate how STDP impairment modifies community structure in the hippocampal network. We also studied the emergent function of network-based learning and found that impaired networks could acquire conditioned responses after training, but the magnitude of the response was significantly lower. Furthermore, we examined pattern separation, a prerequisite of learning, by entraining two overlapping patterns. Contrary to our initial hypothesis, impaired networks did not exhibit deficits in pattern separation with either population- or rate-based coding. Collectively, these results demonstrate how a mechanism of injury that operates at the synapse regulates circuit function.

Concussion Prone Scenarios: A Multi-Dimensional Exploration in Impact Directions, Brain Morphology, and Network Architectures Using Computational Models.

While individual susceptibility to traumatic brain injury (TBI) has been speculated, past work does not provide an analysis considering how physical features of an individual's brain (e.g., brain size, shape), impact direction, and brain network features can holistically contribute to the risk of suffering a TBI from an impact. This work investigated each of these features simultaneously using computational modeling and analyses of simulated functional connectivity. Unlike the past studies that assess the severity of TBI based on the quantification of brain tissue damage (e.g., principal strain), we approached the brain as a complex network in which neuronal oscillations orchestrate to produce normal brain function (estimated by functional connectivity) and, to this end, both the anatomical damage location and its topological characteristics within the brain network contribute to the severity of brain function disruption and injury. To represent the variations in the population, we analyzed a publicly available database of brain imaging data and selected five distinct network architectures, seven different brain sizes, and three uniaxial head rotational conditions to study the consequences of 74 virtual impact scenarios. Results show impact direction produces the most significant change in connections across brain areas (structural connectome) and the functional coupling of activity across these brain areas (functional connectivity). Axial rotations were more injurious than those with sagittal and coronal rotations when the head kinematics were the same for each condition. When the impact direction was held constant, brain network architecture showed a significantly different vulnerability across axial and sagittal, but not coronal rotations. As expected, brain size significantly affected the expected change in structural and functional connectivity after impact. Together, these results provided groupings of predicted vulnerability to impact-a subgroup of male brain architectures exposed to axial impacts were most vulnerable, while a subgroup of female brain architectures was the most tolerant to the sagittal impacts studied. These findings lay essential groundwork for subject-specific analyses of concussion and provide invaluable guidance for designing personalized protection equipment.

Brain architecture-based vulnerability to traumatic injury.

The white matter tracts forming the intricate wiring of the brain are subject-specific; this heterogeneity can complicate studies of brain function and disease. Here we collapse tractography data from the Human Connectome Project (HCP) into structural connectivity (SC) matrices and identify groups of similarly wired brains from both sexes. To characterize the significance of these architectural groupings, we examined how similarly wired brains led to distinct groupings of neural activity dynamics estimated with Kuramoto oscillator models (KMs). We then lesioned our networks to simulate traumatic brain injury (TBI) and finally we tested whether these distinct architecture groups' dynamics exhibited differing responses to simulated TBI. At each of these levels we found that brain structure, simulated dynamics, and injury susceptibility were all related to brain grouping. We found four primary brain architecture groupings (two male and two female), with similar architectures appearing across both sexes. Among these groupings of brain structure, two architecture types were significantly more vulnerable than the remaining two architecture types to lesions. These groups suggest that mesoscale brain architecture types exist, and these architectural differences may contribute to differential risks to TBI and clinical outcomes across the population.

Traumatic brain injury recapitulates developmental changes of axons.

During development, half of brain white matter axons are maintained for growth, while the remainder undergo developmental axon degeneration. After traumatic brain injury (TBI), injured axons also appear to follow pathways leading to either degeneration or repair. These observations raise the intriguing, but unexamined possibility that TBI recapitulates developmental axonal programs. Here, we examined axonal changes in the developing brain in young rats and after TBI in adult rat. Multiple shared changes in axonal microtubule (MT) through tubulin post-translational modifications and MT associated proteins (MAPs), tau and MAP6, were found in both development and TBI. Specifically, degenerating axons in both development and TBI underwent phosphorylation of tau and excessive tubulin tyrosination, suggesting MT instability and depolyermization. Conversely, nearby axons without degenerating morphologies, had increased MAP6 expression and maintenance of tubulin acetylation, suggesting enhanced MT stabilization, thereby supporting survival or repair. Quantitative proteomics revealed similar signaling pathways of axon degeneration and growth/repair, including protein clusters and networks. This comparison approach demonstrates how focused evaluation of developmental processes may provide insight into pathways initiated by TBI. In particular, the data suggest that TBI may reawaken dormant axonal programs that direct axons towards either degeneration or growth/repair, supporting further study in this area.

A multilayer network model of neuron-astrocyte populations in vitro reveals mGluR5 inhibition is protective following traumatic injury.

Astrocytes communicate bidirectionally with neurons, enhancing synaptic plasticity and promoting the synchronization of neuronal microcircuits. Despite recent advances in understanding neuron-astrocyte signaling, little is known about astrocytic modulation of neuronal activity at the population level, particularly in disease or following injury. We used high-speed calcium imaging of mixed cortical cultures in vitro to determine how population activity changes after disruption of glutamatergic signaling and mechanical injury. We constructed a multilayer network model of neuron-astrocyte connectivity, which captured distinct topology and response behavior from single-cell-type networks. mGluR5 inhibition decreased neuronal activity, but did not on its own disrupt functional connectivity or network topology. In contrast, injury increased the strength, clustering, and efficiency of neuronal but not astrocytic networks, an effect that was not observed in networks pretreated with mGluR5 inhibition. Comparison of spatial and functional connectivity revealed that functional connectivity is largely independent of spatial proximity at the microscale, but mechanical injury increased the spatial-functional correlation. Finally, we found that astrocyte segments of the same cell often belong to separate functional communities based on neuronal connectivity, suggesting that astrocyte segments function as independent entities. Our findings demonstrate the utility of multilayer network models for characterizing the multiscale connectivity of two distinct but functionally dependent cell populations.

Ultrasensitive Single Extracellular Vesicle Detection Using High Throughput Droplet Digital Enzyme-Linked Immunosorbent Assay.

Extracellular vesicles (EVs) have attracted enormous attention for their diagnostic and therapeutic potential. However, it has proven challenging to achieve the sensitivity to detect individual nanoscale EVs, the specificity to distinguish EV subpopulations, and a sufficient throughput to study EVs among an enormous background. To address this fundamental challenge, we developed a droplet-based optofluidic platform to quantify specific individual EV subpopulations at high throughput. The key innovation of our platform is parallelization of droplet generation, processing, and analysis to achieve a throughput (∼20 million droplets/min) more than 100× greater than typical microfluidics. We demonstrate that the improvement in throughput enables EV quantification at a limit of detection = 9EVs/µL, a >100× improvement over gold standard methods. Additionally, we demonstrate the clinical potential of this system by detecting human EVs in complex media. Building on this work, we expect this technology will allow accurate quantification of rare EV subpopulations for broad biomedical applications.

Plasma Neurofilament Light and Glial Fibrillary Acidic Protein Levels over Thirty Days in a Porcine Model of Traumatic Brain Injury.

To establish the clinical relevance of porcine model of traumatic brain injury (TBI) using the plasma biomarkers of injury with diffusion tensor imaging (DTI) over 30 days, we performed a randomized, blinded, pre-clinical trial using Yorkshire pigs weighing 7-10 kg. Twelve pigs were subjected to Sham injury (n = 5) by skin incision or TBI (n = 7) by controlled cortical impact. Blood samples were collected before the injury, then at approximately 5-day intervals until 30 days. Both groups also had DTI at 24 h and at 30 days after injury. Plasma samples were isolated and single molecule array (Simoa) was performed for glial fibrillary acidic protein (GFAP) and neurofilament light (NFL) levels. Afterwards, brain tissue samples were stained for ß-APP. DTI showed fractional anisotropy (FA) decrease in the right corona radiata (ipsilateral to injury), contralateral corona radiata, and anterior corpus callosum at 1 day. At 30 days, ipsilateral corona radiata showed decreased FA. Pigs with TBI also had increase in GFAP and NFL at 1-5 days after injury. Significant difference between Sham and TBI animals continued up to 20 days. Linear regression showed significant negative correlation between ipsilateral corona radiata FA and both NFL and GFAP levels at 1 day. To further validate the degree of axonal injury found in DTI, ß-APP immunohistochemistry was performed on a perilesional tissue as well as corona radiata bilaterally. Variable degree of staining was found in ipsilateral corona radiata. Porcine model of TBI replicates the acute increase in plasma biomarkers seen in clinical TBI. Further, long term white matter injury is confirmed in the areas such as the splenium and corona radiata. However, future study stratifying severe and mild TBI, as well as comparison with other subtypes of TBI such as diffuse axonal injury, may be warranted.

An interdisciplinary computational model for predicting traumatic brain injury: Linking biomechanics and functional neural networks.

The brain is a complex network consisting of neuron cell bodies in the gray matter and their axonal projections, forming the white matter tracts. These neurons are supported by an equally complex vascular network as well as glial cells. Traumatic brain injury (TBI) can lead to the disruption of the structural and functional brain networks due to disruption of both neuronal cell bodies in the gray matter as well as their projections and supporting cells. To explore how an impact can alter the function of brain networks, we integrated a finite element (FE) brain mechanics model with linked models of brain dynamics (Kuramoto oscillator) and vascular perfusion (Balloon-Windkessel) in this study. We used empirical resting-state functional magnetic resonance imaging (MRI) data to optimize the fit of our brain dynamics and perfusion models to clinical data. Results from the FE model were used to mimic injury in these optimized brain dynamics models: injury to the nodes (gray matter) led to a decrease in the nodal oscillation frequency, while damage to the edges (axonal connections/white matter) progressively decreased coupling among connected nodes. A total of 53 cases, including 33 non-injurious and 20 concussive head impacts experienced by professional American football players were simulated using this integrated model. We examined the correlation of injury outcomes with global measures of structural connectivity, neural dynamics, and functional connectivity of the brain networks when using different lesion methods. Results show that injurious head impacts cause significant alterations in global network topology regardless of lesion methods. Changes between the disrupted and healthy functional connectivity (measured by Pearson correlation) consistently correlated well with injury outcomes (AUC≥0.75), although the predictive performance is not significantly different (p>0.05) to that of traditional kinematic measures (angular acceleration). Intriguingly, our lesion model for gray matter damage predicted increases in global efficiency and clustering coefficient with increases in injury risk, while disrupting axonal connections led to lower network efficiency and clustering. When both injury mechanisms were combined into a single injury prediction model, the injury prediction performance depended on the thresholds used to determine neurodegeneration and mechanical tolerance for axonal injury. Together, these results point towards complex effects of mechanical trauma to the brain and provide a new framework for understanding brain injury at a causal mechanistic level and developing more effective diagnostic methods and therapeutic interventions.

Plasticity impairment exposes CA3 vulnerability in a hippocampal network model of mild traumatic brain injury.

Proper function of the hippocampus is critical for executing cognitive tasks such as learning and memory. Traumatic brain injury (TBI) and other neurological disorders are commonly associated with cognitive deficits and hippocampal dysfunction. Although there are many existing models of individual subregions of the hippocampus, few models attempt to integrate the primary areas into one system. In this work, we developed a computational model of the hippocampus, including the dentate gyrus, CA3, and CA1. The subregions are represented as an interconnected neuronal network, incorporating well-characterized ex vivo slice electrophysiology into the functional neuron models and well-documented anatomical connections into the network structure. In addition, since plasticity is foundational to the role of the hippocampus in learning and memory as well as necessary for studying adaptation to injury, we implemented spike-timing-dependent plasticity among the synaptic connections. Our model mimics key features of hippocampal activity, including signal frequencies in the theta and gamma bands and phase-amplitude coupling in area CA1. We also studied the effects of spike-timing-dependent plasticity impairment, a potential consequence of TBI, in our model and found that impairment decreases broadband power in CA3 and CA1 and reduces phase coherence between these two subregions, yet phase-amplitude coupling in CA1 remains intact. Altogether, our work demonstrates characteristic hippocampal activity with a scaled network model of spiking neurons and reveals the sensitive balance of plasticity mechanisms in the circuit through one manifestation of mild traumatic injury.

Flexibility of in vitro cortical circuits influences resilience from microtrauma.

Background: Small clusters comprising hundreds to thousands of neurons are an important level of brain architecture that correlates single neuronal properties to fulfill brain function, but the specific mechanisms through which this scaling occurs are not well understood. In this study, we developed an in vitro experimental platform of small neuronal circuits (islands) to probe the importance of structural properties for their development, physiology, and response to microtrauma. Methods: Primary cortical neurons were plated on a substrate patterned to promote attachment in clusters of hundreds of cells (islands), transduced with GCaMP6f, allowed to mature until 10-13 days in vitro (DIV), and monitored with Ca2+ as a non-invasive proxy for electrical activity. We adjusted two structural factors-island size and cellular density-to evaluate their role in guiding spontaneous activity and network formation in neuronal islands. Results: We found cellular density, but not island size, regulates of circuit activity and network function in this system. Low cellular density islands can achieve many states of activity, while high cellular density biases islands towards a limited regime characterized by low rates of activity and high synchronization, a property we summarized as "flexibility." The injury severity required for an island to lose activity in 50% of its population was significantly higher in low-density, high flexibility islands. Conclusion: Together, these studies demonstrate flexible living cortical circuits are more resilient to microtrauma, providing the first evidence that initial circuit state may be a key factor to consider when evaluating the consequences of trauma to the cortex.

Extracellular vesicles as distinct biomarker reservoirs for mild traumatic brain injury diagnosis.

Mild traumatic brain injury does not currently have a clear molecular diagnostic panel to either confirm the injury or to guide its treatment. Current biomarkers for traumatic brain injury rely mainly on detecting circulating proteins in blood that are associated with degenerating neurons, which are less common in mild traumatic brain injury, or with broad inflammatory cascades which are produced in multiple tissues and are thus not brain specific. To address this issue, we conducted an observational cohort study designed to measure a protein panel in two compartments-plasma and brain-derived extracellular vesicles-with the following hypotheses: (i) each compartment provides independent diagnostic information and (ii) algorithmically combining these compartments accurately classifies clinical mild traumatic brain injury. We evaluated this hypothesis using plasma samples from mild (Glasgow coma scale scores 13-15) traumatic brain injury patients (n = 47) and healthy and orthopaedic control subjects (n = 46) to evaluate biomarkers in brain-derived extracellular vesicles and plasma. We used our Track Etched Magnetic Nanopore technology to isolate brain-derived extracellular vesicles from plasma based on their expression of GluR2, combined with the ultrasensitive digital enzyme-linked immunosorbent assay technique, Single-Molecule Array. We quantified extracellular vesicle-packaged and plasma levels of biomarkers associated with two categories of traumatic brain injury pathology: neurodegeneration and neuronal/glial damage (ubiquitin C-terminal hydrolase L1, glial fibrillary acid protein, neurofilament light and Tau) and inflammation (interleukin-6, interleukin-10 and tumour necrosis factor alpha). We found that GluR2+ extracellular vesicles have distinct biomarker distributions than those present in the plasma. As a proof of concept, we showed that using a panel of biomarkers comprised of both plasma and GluR2+ extracellular vesicles, injured patients could be accurately classified versus non-injured patients.

Regional Neurodegeneration in vitro: The Protective Role of Neural Activity.

Traumatic brain injury is a devastating public health problem, the eighth leading cause of death across the world. To improve our understanding of how injury at the cellular scale affects neural circuit function, we developed a protocol to precisely injure individual neurons within an in vitro neural network. We used high speed calcium imaging to estimate alterations in neural activity and connectivity that occur followed targeted microtrauma. Our studies show that mechanically injured neurons inactivate following microtrauma and eventually re-integrate into the network. Single neuron re-integration is dependent on its activity prior to injury and initial connections in the network: more active and integrated neurons are more resistant to microtrauma and more likely to re-integrate into the network. Micromechanical injury leads to neuronal death 6 h post-injury in a subset of both injured and uninjured neurons. Interestingly, neural activity and network participation after injury were associated with survival in linear discriminate analysis (77.3% correct prediction, Wilks' Lambda = 0.838). Based on this observation, we modulated neuronal activity to rescue neurons after microtrauma. Inhibition of neuronal activity provided much greater survivability than did activation of neurons (ANOVA, p < 0.01 with post-hoc Tukey HSD, p < 0.01). Rescue of neurons by blocking activity in the post-acute period is partially mediated by mitochondrial energetics, as we observed silencing neurons after micromechanical injury led to a significant reduction in mitochondrial calcium accumulation. Overall, the present study provides deeper insight into the propagation of injury within networks, demonstrating that together the initial activity, network structure, and post-injury activity levels contribute to the progressive changes in a neural circuit after mechanical trauma.

Cytosolic PSD-95 interactor alters functional organization of neural circuits and AMPA receptor signaling independent of PSD-95 binding.

Cytosolic PSD-95 interactor (cypin) regulates many aspects of neuronal development and function, ranging from dendritogenesis to synaptic protein localization. While it is known that removal of postsynaptic density protein-95 (PSD-95) from the postsynaptic density decreases synaptic N-methyl-D-aspartate (NMDA) receptors and that cypin overexpression protects neurons from NMDA-induced toxicity, little is known about cypin's role in AMPA receptor clustering and function. Experimental work shows that cypin overexpression decreases PSD-95 levels in synaptosomes and the PSD, decreases PSD-95 clusters/µm2, and increases mEPSC frequency. Analysis of microelectrode array (MEA) data demonstrates that cypin or cypinΔPDZ overexpression increases sensitivity to CNQX (cyanquixaline) and AMPA receptor-mediated decreases in spike waveform properties. Network-level analysis of MEA data reveals that cypinΔPDZ overexpression causes networks to be resilient to CNQX-induced changes in local efficiency. Incorporating these findings into a computational model of a neural circuit demonstrates a role for AMPA receptors in cypin-promoted changes to networks and shows that cypin increases firing rate while changing network functional organization, suggesting cypin overexpression facilitates information relay but modifies how information is encoded among brain regions. Our data show that cypin promotes changes to AMPA receptor signaling independent of PSD-95 binding, shaping neural circuits and output to regions beyond the hippocampus.

NMDA Receptor Alterations After Mild Traumatic Brain Injury Induce Deficits in Memory Acquisition and Recall.

Mild traumatic brain injury (mTBI) presents a significant health concern with potential persisting deficits that can last decades. Although a growing body of literature improves our understanding of the brain network response and corresponding underlying cellular alterations after injury, the effects of cellular disruptions on local circuitry after mTBI are poorly understood. Our group recently reported how mTBI in neuronal networks affects the functional wiring of neural circuits and how neuronal inactivation influences the synchrony of coupled microcircuits. Here, we utilized a computational neural network model to investigate the circuit-level effects of N-methyl D-aspartate receptor dysfunction. The initial increase in activity in injured neurons spreads to downstream neurons, but this increase was partially reduced by restructuring the network with spike-timing-dependent plasticity. As a model of network-based learning, we also investigated how injury alters pattern acquisition, recall, and maintenance of a conditioned response to stimulus. Although pattern acquisition and maintenance were impaired in injured networks, the greatest deficits arose in recall of previously trained patterns. These results demonstrate how one specific mechanism of cellular-level damage in mTBI affects the overall function of a neural network and point to the importance of reversing cellular-level changes to recover important properties of learning and memory in a microcircuit.

Inducing different severities of traumatic brain injury in Drosophila using a piezoelectric actuator.

Drosophila models have been instrumental in providing insights into molecular mechanisms of neurodegeneration, with wide application to human disease. The brain degeneration associated with traumatic brain injury (TBI) has been modeled in Drosophila using devices that inflict trauma on multiple parts of the fly body, including the head. However, the injuries produced by these models are not specific in location and are inconsistent between individual animals. We have recently developed a device that can be used to inflict controlled head injury to flies, resulting in physiological responses that are remarkably similar to those observed in humans with TBI. This protocol describes the construction, calibration and use of the Drosophila TBI (dTBI) device, a platform that employs a piezoelectric actuator to reproducibly deliver a force in order to briefly compress the fly head against a metal surface. The extent of head compression can be controlled through an electrical circuit, allowing the operator to set different levels of injury. The entire device can be assembled and calibrated in under a week. The device components and the necessary electrical tools are readily available and cost ~$800. The dTBI device can be used to harness the power of Drosophila genetics and perform large-scale genetic or pharmacological screens, using a 7-d post-injury survival curve to identify modifiers of injury.