Introduction: Retinal input processing in the human visual system involves a phasic and tonic neural response. We investigated the role of the magno- and parvocellular systems by comparing the influence of the active neural population size and its discharge activity on the amplitude and latency of four VEP components.
Method: We recorded the scalp electric potential of 20 human volunteers viewing a series of dartboard images presented as a pattern reversing and pattern on-/offset stimulus. These patterns were designed to vary both neural population size coding the temporal- and spatial luminance contrast property and the discharge activity of the population involved in a systematic manner.
Results: When the VEP amplitude reflected the size of the neural population coding the temporal luminance contrast property of the image, the influence of luminance contrast followed the contrast response function of the parvocellular system. When the VEP amplitude reflected the size of the neural population responding to the spatial luminance contrast property the image, the influence of luminance contrast followed the contrast response function of the magnocellular system. The latencies of the VEP components examined exhibited the same behavior across our stimulus series.
Conclusions: This investigation demonstrates the complex interplay of the magno- and parvocellular systems on the neural response as captured by the VEP. It also demonstrates a linear relationship between stimulus property, neural response, and the VEP and reveals the importance of feedback projections in modulating the ongoing neural response. In doing so, it corroborates the conclusions of our previous study.
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http://dx.doi.org/10.1002/brb3.860 | DOI Listing |
J Comp Physiol A Neuroethol Sens Neural Behav Physiol
January 2025
Department of Zoology, University of British Columbia, Vancouver, BC, Canada.
Terrestrial molluscs living in temperate and polar environments must contend with cold winter temperatures. However, the physiological mechanisms underlying the survival of terrestrial molluscs in cold environments and the strategies employed by them are poorly understood. Here we investigated the cold tolerance of Ambigolimax valentianus, an invasive, terrestrial slug that has established populations in Japan, Canada, and Europe.
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Hospital Virgen de la Arrixaca, 30120 Murcia, Spain.
Accurate segmentation of the left ventricular myocardium in cardiac MRI is essential for developing reliable deep learning models to diagnose left ventricular non-compaction cardiomyopathy (LVNC). This work focuses on improving the segmentation database used to train these models, enhancing the quality of myocardial segmentation for more precise model training. We present a semi-automatic framework that refines segmentations through three fundamental approaches: (1) combining neural network outputs with expert-driven corrections, (2) implementing a blob-selection method to correct segmentation errors and neural network hallucinations, and (3) employing a cross-validation process using the baseline U-Net model.
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Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China.
Bird species detection is critical for applications such as the analysis of bird population dynamics and species diversity. However, this task remains challenging due to local structural similarities and class imbalances among bird species. Currently, most deep learning algorithms focus on designing local feature extraction modules while ignoring the importance of global information.
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December 2024
2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, 12462 Athens, Greece.
The widespread propagation of wireless communication devices, from smartphones and tablets to Internet of Things (IoT) systems, has become an integral part of modern life. However, the expansion of wireless technology has also raised public concern about the potential health risks associated with prolonged exposure to electromagnetic fields. Our objective is to determine the optimal machine learning model for constructing electric field strength maps across urban areas, enhancing the field of environmental monitoring with the aid of sensor-based data collection.
View Article and Find Full Text PDFNutrients
January 2025
Center for the Study of Metabolism, Body Composition and Lifestyle, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy.
Background/objectives: Disordered eating (DE) is a wide-spectrum condition, represented by altered eating patterns, behaviors, and attitudes aimed at controlling food intake, body weight, and shape, which does not necessarily satisfy the diagnostic criteria for an eating disorder of clinical severity. DE is frequently reported among athletes, but its prevalence and associated factors have not been fully elucidated. In this study, we intended to assess the prevalence of DE among adult athletes from different sports disciplines in Italy and Lebanon and to identify the factors associated with DE.
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