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1. Thalamo-Prefrontal Connectivity Correlates With Early Command-Following After Severe Traumatic Brain Injury

   https://doi.org/10.3389/fneur.2022.826266  

   Cosgrove, Megan E.; Saadon, Jordan R.; Mikell, Charles B.; Stefancin, Patricia L.; Alkadaa, Leor; Wang, Zhe; Saluja, Sabir; Servider, John; Razzaq, Bayan; Huang, Chuan; et al (February 2022, Frontiers in Neurology)

   Recovery of consciousness after traumatic brain injury (TBI) is heterogeneous and difficult to predict. Structures such as the thalamus and prefrontal cortex are thought to be important in facilitating consciousness. We sought to investigate whether the integrity of thalamo-prefrontal circuits, assessed via diffusion tensor imaging (DTI), was associated with the return of goal-directed behavior after severe TBI. We classified a cohort of severe TBI patients ( N = 25, 20 males) into Early and Late/Never outcome groups based on their ability to follow commands within 30 days post-injury. We assessed connectivity between whole thalamus, and mediodorsal thalamus (MD), to prefrontal cortex (PFC) subregions including dorsolateral PFC (dlPFC), medial PFC (mPFC), anterior cingulate (ACC), and orbitofrontal (OFC) cortices. We found that the integrity of thalamic projections to PFC subregions (L OFC, L and R ACC, and R mPFC) was significantly associated with Early command-following. This association persisted when the analysis was restricted to prefrontal-mediodorsal (MD) thalamus connectivity. In contrast, dlPFC connectivity to thalamus was not significantly associated with command-following. Using the integrity of thalamo-prefrontal connections, we created a linear regression model that demonstrated 72% accuracy in predicting command-following after a leave-one-out analysis. Together, these data support a role for thalamo-prefrontal connectivity in the return of goal-directed behavior following TBI. 

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2. Reduced Reelin Expression in the Hippocampus after Traumatic Brain Injury

   https://doi.org/10.3390/biom10070975  

   Dal Pozzo, Valentina; Crowell, Beth; Briski, Nicholas; Crockett, David P.; D’Arcangelo, Gabriella (July 2020, Biomolecules)

   null (Ed.)

   Traumatic brain injury (TBI) is a relatively common occurrence following accidents or violence, and often results in long-term cognitive or motor disability. Despite the high health cost associated with this type of injury, presently there are no effective treatments for many neurological symptoms resulting from TBI. This is due in part to our limited understanding of the mechanisms underlying brain dysfunction after injury. In this study, we used the mouse controlled cortical impact (CCI) model to investigate the effects of TBI, and focused on Reelin, an extracellular protein that critically regulates brain development and modulates synaptic activity in the adult brain. We found that Reelin expression decreases in forebrain regions after TBI, and that the number of Reelin-expressing cells decrease specifically in the hippocampus, an area of the brain that plays an important role in learning and memory. We also conducted in vitro experiments using mouse neuronal cultures and discovered that Reelin protects hippocampal neuronal cells from glutamate-induced neurotoxicity, a well-known secondary effect of TBI. Together our findings suggest that the loss of Reelin expression may contribute to neuronal death in the hippocampus after TBI, and raise the possibility that increasing Reelin levels or signaling activity may promote functional recovery. 

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3. Imaging the large‐scale and cellular response to focal traumatic brain injury in mouse neocortex

   https://doi.org/10.1113/EP092219  

   Bibineyshvili, Yelena; Vajtay, Thomas J; Salsabilian, Shiva; Fliss, Nicholas; Suvarnakar, Aastha; Fang, Jennifer; Teng, Shavonne; Alder, Janet; Najafizadeh, Laleh; Margolis, David J (February 2025, Experimental Physiology)

   Abstract Traumatic brain injury (TBI) affects neural function at the local injury site and also at distant, connected brain areas. However, the real‐time neural dynamics in response to injury and subsequent effects on sensory processing and behaviour are not fully resolved, especially across a range of spatial scales. We used in vivo calcium imaging in awake, head‐restrained male and female mice to measure large‐scale and cellular resolution neuronal activation, respectively, in response to a mild/moderate TBI induced by focal controlled cortical impact (CCI) injury of the motor cortex (M1). Widefield imaging revealed an immediate CCI‐induced activation at the injury site, followed by a massive slow wave of calcium signal activation that travelled across the majority of the dorsal cortex within approximately 30 s. Correspondingly, two‐photon calcium imaging in the primary somatosensory cortex (S1) found strong activation of neuropil and neuronal populations during the CCI‐induced travelling wave. A depression of calcium signals followed the wave, during which we observed the atypical activity of a sparse population of S1 neurons. Longitudinal imaging in the hours and days after CCI revealed increases in the area of whisker‐evoked sensory maps at early time points, in parallel to decreases in cortical functional connectivity and behavioural measures. Neural and behavioural changes mostly recovered over hours to days in our M1‐TBI model, with a more lasting decrease in the number of active S1 neurons. Our results in unanaesthetized mice describe novel spatial and temporal neural adaptations that occur at cortical sites remote to a focal brain injury. 

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4. Acoustofluidic separation enables early diagnosis of traumatic brain injury based on circulating exosomes

   https://doi.org/10.1038/s41378-021-00244-3  

   Wang, Zeyu; Wang, Haichen; Becker, Ryan; Rufo, Joseph; Yang, Shujie; Mace, Brian E.; Wu, Mengxi; Zou, Jun; Laskowitz, Daniel T.; Huang, Tony Jun (December 2021, Microsystems & Nanoengineering)

   Abstract Traumatic brain injury (TBI) is a global cause of morbidity and mortality. Initial management and risk stratification of patients with TBI is made difficult by the relative insensitivity of screening radiographic studies as well as by the absence of a widely available, noninvasive diagnostic biomarker. In particular, a blood-based biomarker assay could provide a quick and minimally invasive process to stratify risk and guide early management strategies in patients with mild TBI (mTBI). Analysis of circulating exosomes allows the potential for rapid and specific identification of tissue injury. By applying acoustofluidic exosome separation—which uses a combination of microfluidics and acoustics to separate bioparticles based on differences in size and acoustic properties—we successfully isolated exosomes from plasma samples obtained from mice after TBI. Acoustofluidic isolation eliminated interference from other blood components, making it possible to detect exosomal biomarkers for TBI via flow cytometry. Flow cytometry analysis indicated that exosomal biomarkers for TBI increase in the first 24 h following head trauma, indicating the potential of using circulating exosomes for the rapid diagnosis of TBI. Elevated levels of TBI biomarkers were only detected in the samples separated via acoustofluidics; no changes were observed in the analysis of the raw plasma sample. This finding demonstrated the necessity of sample purification prior to exosomal biomarker analysis. Since acoustofluidic exosome separation can easily be integrated with downstream analysis methods, it shows great potential for improving early diagnosis and treatment decisions associated with TBI. 

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5. Noninvasive and reliable automated detection of spreading depolarization in severe traumatic brain injury using scalp EEG

   https://doi.org/10.1038/s43856-023-00344-3  

   Chamanzar, Alireza; Elmer, Jonathan; Shutter, Lori; Hartings, Jed; Grover, Pulkit (December 2023, Communications Medicine)

   Abstract BackgroundSpreading depolarizations (SDs) are a biomarker and a potentially treatable mechanism of worsening brain injury after traumatic brain injury (TBI). Noninvasive detection of SDs could transform critical care for brain injury patients but has remained elusive. Current methods to detect SDs are based on invasive intracranial recordings with limited spatial coverage. In this study, we establish the feasibility of automated SD detection through noninvasive scalp electroencephalography (EEG) for patients with severe TBI. MethodsBuilding on our recent WAVEFRONT algorithm, we designed an automated SD detection method. This algorithm, with learnable parameters and improved velocity estimation, extracts and tracks propagating power depressions using low-density EEG. The dataset for testing our algorithm contains 700 total SDs in 12 severe TBI patients who underwent decompressive hemicraniectomy (DHC), labeled using ground-truth intracranial EEG recordings. We utilize simultaneously recorded, continuous, low-density (19 electrodes) scalp EEG signals, to quantify the detection accuracy of WAVEFRONT in terms of true positive rate (TPR), false positive rate (FPR), as well as the accuracy of estimating SD frequency. ResultsWAVEFRONT achieves the best average validation accuracy using Delta band EEG: 74% TPR with less than 1.5% FPR. Further, preliminary evidence suggests WAVEFRONT can estimate how frequently SDs may occur. ConclusionsWe establish the feasibility, and quantify the performance, of noninvasive SD detection after severe TBI using an automated algorithm. The algorithm, WAVEFRONT, can also potentially be used for diagnosis, monitoring, and tailoring treatments for worsening brain injury. Extension of these results to patients with intact skulls requires further study. 

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