Sensory neurons display transient changes in their response properties following prolonged exposure to an appropriate stimulus (adaptation). In adult cat primary visual cortex, spatial frequency-selective neurons shift their preferred spatial frequency (SF) after being adapted to a non-preferred SF. In anesthetized cats prepared for electrophysiological recordings in the visual cortex, we applied a non-preferred spatial frequency for two successive periods of adaptation (a recovery and interval of ∼90 min separated both phases of adaptation) in order to determine if a first adaptation retained an influence on a second adaptation. The first application of a non-preferred SF shifted the tuning curve of the cell mainly in the direction of the imposed SF. The results showed that attractive shifts occurred more frequently (68%) than repulsive (12%) changes in cortical cells. The increase of responsivity was band-limited and occurred around the imposed SF, while flanked responses remained unmodified in all conditions. After a recovery period allowing neurons to restore their original SF tuning curves, we carried out a second adaptation which produced four major results: (1) a higher proportion of repulsive shifts (31%) compared to attractive shifts (49%), (2) an increase of the magnitude of the attractive shifts, (3) an additional enhancement of the evoked firing rate for the newly acquired SF, and (4) for the acquired SF the variability coefficient decreased following the second adaptation. The supplementary response changes suggest that neurons in area 17 keep a "memory" trace of the previous stimulus properties. It also highlights the dynamic nature of basic neuronal properties in adult cortex since repeated adaptations modified both the spatial frequency tuning selectivity and the response strength to the preferred spatial frequency. These enhanced neuronal responses suggest that the range of adaptation-induced plasticity available to the visual system is broader than anticipated.
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http://dx.doi.org/10.1016/j.neuroscience.2010.10.017 | DOI Listing |
Trans R Soc Trop Med Hyg
January 2025
Centre for Snakebite Research and Interventions, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UK.
Background: Snakebite is a priority neglected tropical disease, but incidence data are lacking; current estimates rely upon incomplete health facility reports or ad hoc surveys. Spatial analysis methods harness statistical associations between case incidence and spatially varying factors to improve estimates. This systematic review aimed to identify variables associated with snakebite risk in spatial and temporal analyses for inclusion in geospatial studies to improve risk estimation accuracy.
View Article and Find Full Text PDFJACC Adv
December 2024
Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, New York, USA.
Background: The Hispanic/Latino population is not uniform. Prevalence and clinical outcomes of cardiac arrhythmias in ethnic background subgroups are variable, but the reasons for differences are unclear. Vectorcardiographic Global Electrical Heterogeneity (GEH) has been shown to be associated with adverse cardiovascular outcomes.
View Article and Find Full Text PDFLandsc Ecol
January 2025
Department of Spatial Sciences, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Praha - Suchdol, Czech Republic.
Context: Historical land use is thought to have influenced plant community diversity, composition and function through the local persistence of taxa that reflect ecological conditions of the past.
Objectives: We tested for the effects of historical land use on contemporary plant species richness, composition, and ecological preferences in the grassland vegetation of Central Europe.
Methods: We analyzed 6975 vegetation plots sampled between 1946 and 2021 in dry, mesic, and wet grasslands in the borderland between Austria, the Czech Republic, and Slovakia.
Heliyon
January 2025
BCN MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Deformable image registration is a cornerstone of many medical image analysis applications, particularly in the context of fetal brain magnetic resonance imaging (MRI), where precise registration is essential for studying the rapidly evolving fetal brain during pregnancy and potentially identifying neurodevelopmental abnormalities. While deep learning has become the leading approach for medical image registration, traditional convolutional neural networks (CNNs) often fall short in capturing fine image details due to their bias toward low spatial frequencies. To address this challenge, we introduce a deep learning registration framework comprising multiple cascaded convolutional networks.
View Article and Find Full Text PDFFourier ptychographic microscopy (FPM) can provide high-throughput imaging by computationally combining low-resolution images at different spatial frequencies within the Fourier domain. The core algorithm for FPM reconstruction draws upon phase retrieval techniques, including methods such as the ptychographic iterative engine (PIE), regularized PIE (rPIE), and embedded pupil function FPM (EPRY-FPM). The calibration of the physical setup plays a crucial role in the quality of the reconstructed high space-bandwidth product (SPB) image.
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