J. K. F. Zoellner began writing on "experimental proofs" of a fourth spatial dimension, and of the existence of spirits, in 1878. His arguments caused strong controversy, with rebuttal essays by Wilhelm Wundt and others. The author argues that Zoellner's case that these matters are experimental questions rested on arguments which Hermann von Helmholtz, inveighing against rationalist views of space and space perception, had recently published. Zoellner's use of Helmholtz's arguments to advance and defend his spiritist views occasioned strong criticism of Helmholtz, affected careers and reputations of scholars in Berlin and Leipzig, and caused enduring controversy over the credibility of Helmholtz's empiricist theory of space perception.
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http://dx.doi.org/10.1002/1520-6696(198910)25:4<371::aid-jhbs2300250406>3.0.co;2-b | DOI Listing |
Respir Res
January 2025
Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Department of Biomedical Engineering, Air Force Medical University, Xi'an, 710032, China.
Background: Acute pulmonary embolism represents the third most prevalent cardiovascular pathology, following coronary heart disease and hypertension. Its untreated mortality rate is as high as 20-30%, which represents a significant threat to patient survival. In view of the current lack of real-time monitoring techniques for acute pulmonary embolism, this study primarily investigates the potential of the pulsatility electrical impedance tomography (EIT) technique for the detection and real-time monitoring of acute pulmonary embolism through the collection and imaging of the pulsatile signal of pulmonary blood flow.
View Article and Find Full Text PDFFront Hum Neurosci
December 2024
Department of Aerospace Medical Equipment, School of Aerospace Medicine, Air Force Medical University, Xi'an, Shaanxi, China.
Backgrounds: Functional near-infrared spectroscopy (fNIRS) is widely used for the evaluation of mental workload (MWL), but it is not yet clear whether it is affected by physical factors during cognitive tasks. Therefore, the combined effects of physical and cognitive loads on hemodynamic features in the prefrontal cortex were evaluated.
Methods: Thirty-three eligible healthy male subjects were asked to perform three types of cognitive tasks (1-back, 2-back and 3-back).
J Vis
January 2025
McGill Vision Research, Department of Ophthalmology & Visual Sciences, McGill University, Montreal, QC, Canada.
Here, we investigate the shift in eye balance in response to monocular cueing in adults with amblyopia. In normally sighted adults, biasing attention toward one eye, by presenting a monocular visual stimulus to it, can shift eye balance toward the stimulated eye, as measured by binocular rivalry. We investigated whether we can modulate eye balance by directing monocular stimulation/attention in adults with clinical binocular deficits associated with amblyopia and larger eye imbalances.
View Article and Find Full Text PDFInvest Ophthalmol Vis Sci
January 2025
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Sun Yat-Sen University, Guangzhou, China.
Purpose: The purpose of this study was to investigate the relationship between fixation stability deficits in anisometropic amblyopia and various visual functions, as well as the underlying retinal structure.
Methods: All 164 patients with anisometropic amblyopia were recruited in this cross-sectional study. The contrast sensitivity function (CSF) was measured using the qCSF method, whereas the MP-3 microperimeter was used to assess fixation stability and locate the preferred retinal locus.
Sci Rep
January 2025
Department of Computer Science, Kebri Dehar University, Kebri Dehar, Ethiopia.
Artificial Intelligence techniques are being used to analyse vast amounts of medical data and assist in the accurate and early diagnosis of diseases. The common brain related diseases are faced by most of the people which affects the structure and function of the brain. Artificial neural networks have been extensively used for disease prediction and diagnosis due to their ability to learn complex patterns and relationships from large datasets.
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