Concussions are high incidence injuries with potentially devastating consequences. Youths are at risk because of a higher threat of repeated injury, and cumulative effects of concussions exist, making accurate diagnosis and follow-up essential. This study examines a navigational memory functional magnetic resonance imaging (fMRI) task to determine whether activation differences exist between children with concussion and uninjured controls. Fifty adolescents were recruited-35 controls and 15 with concussion. All subjects underwent structural and fMRI testing using our navigational memory task, and a battery of neuropsychological testing. The activation patterns of the 15 subjects with concussion were compared with those of 15 age and sex-matched controls. Subtraction and regression analyses were performed using the matched controls along with scatter-plots using means and 95% quantiles of the 35 controls. While no differences were seen with neuropsychological testing or task performance, subjects with concussion had significantly diminished activation in the retrosplenial, thalamic, and parahippocampal areas bilaterally, along with the right dorsolateral prefrontal cortex and left precuneus. Interestingly, they had increased activation in the left hippocampus and right middle temporal gyrus. Regression analysis demonstrated negative correlations between activation and post-concussive symptoms in the left premotor cortex, superior and inferior parietal lobules, and parahippocampal gyrus. Subjects with concussion show both diminished and increased activation in specific cerebral regions, differentiating them from controls. This is one of the first studies to look at such a task using fMRI and its applicability in testing for concussion in children. These findings support navigational memory fMRI as a potential objective test for concussions.
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http://dx.doi.org/10.1089/neu.2014.3470 | DOI Listing |
Sci Rep
December 2024
New Technology Research Institute, BYD Auto Industry Co., Ltd., Shenzhen, 518118, China.
Effective road terrain recognition is crucial for enhancing the driving safety, passability, and comfort of autonomous vehicles. This study addresses the challenges of accurately identifying diverse road surfaces using deep learning in complex environments. We introduce a novel end-to-end Tire Noise Recognition Residual Network (TNResNet) integrated with a time-frequency attention module, designed to capture and leverage time-frequency information from tire noise signals for road terrain classification.
View Article and Find Full Text PDFNeuroSci
December 2024
Department of Physiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, 45110 Ioannina, Greece.
Although spatial memory has been widely studied in rodents, developmental studies involving humans are limited in number and sample size. We designed and studied the validity of two simple experimental setups for the evaluation of spatial memory and navigation development. The dataset of this study was composed of 496 schoolchildren, from 4 to 15 years old.
View Article and Find Full Text PDFBiomimetics (Basel)
December 2024
Sussex AI, School of Engineering and Informatics, University of Sussex, Brighton BN1 9QJ, UK.
Visual navigation is a key capability for robots and animals. Inspired by the navigational prowess of social insects, a family of insect-inspired route navigation algorithms-familiarity-based algorithms-have been developed that use stored panoramic images collected during a training route to subsequently derive directional information during route recapitulation. However, unlike the ants that inspire them, these algorithms ignore the sequence in which the training images are acquired so that all temporal information/correlation is lost.
View Article and Find Full Text PDFBiol Rev Camb Philos Soc
December 2024
Wyoming Cooperative Fish and Wildlife Research Unit, Department of Zoology and Physiology, University of Wyoming, 1000 E University Ave, Laramie, Wyoming, 82071, USA.
Although decades of research have deepened our understanding of the proximate triggers and ultimate drivers of migrations for a range of taxa, how populations establish migrations remains a mystery. However, recent studies have begun to illuminate the interplay between genetically inherited and learned migrations, opening the door to the evaluation of how migration may be learned, established, and maintained. Nevertheless, for migratory species where the role of learning is evident, we lack a comprehensive framework for understanding how populations learn specific routes and refine migratory movements over time (i.
View Article and Find Full Text PDFPNAS Nexus
January 2025
Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL 60208, USA.
The COVID-19 pandemic forced a societal shift from in-person to virtual activities, including scientific conferences. As society navigates a "new normal," the question arises as to the advantages and disadvantages of these alternative modalities. We introduce two new comprehensive datasets enabling direct comparison between virtual and in-person conferences: the first, from a series of nine small conferences, encompasses over 12,000 pairs of potential scientific collaborators across five virtual and four in-person meetings on a range of scientific topics; the expressed goal of these conferences is to create novel collaborations.
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