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The visual system can compute summary statistics of several visual elements at a glance. Numerous studies have shown that an ensemble of different visual features can be perceived over 50-200 ms; however, the time point at which the visual system forms an accurate ensemble representation associated with an individual's perception remains unclear. This is mainly because most previous studies have not fully addressed time-resolved neural representations that occur during ensemble perception, particularly lacking quantification of the representational strength of ensembles and their correlation with behavior. Here, we conducted orientation ensemble discrimination tasks and electroencephalogram (EEG) recordings to decode orientation representations over time while human observers discriminated an average of multiple orientations. We modeled EEG signals as a linear sum of hypothetical orientation channel responses and inverted this model to quantify the representational strength of orientation ensemble. Our analysis using this inverted encoding model revealed stronger representations of the average orientation over 400-700 ms. We also correlated the orientation representation estimated from EEG signals with the perceived average orientation reported in the ensemble discrimination task with adjustment methods. We found that the estimated orientation at approximately 600-700 ms significantly correlated with the individual differences in perceived average orientation. These results suggest that although ensembles can be quickly and roughly computed, the visual system may gradually compute an orientation ensemble over several hundred milliseconds to achieve a more accurate ensemble representation.
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http://dx.doi.org/10.3389/fnins.2024.1387393 | DOI Listing |
J Chem Inf Model
September 2025
Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, U.K.
We present the protolysis-targeting chimera (PROTAC) Conformer Generator, a fast and knowledge-based tool for generating robust conformational ensembles of PROTACs and other chimeric degraders. The modeling protocol integrates conformer generation, rigid-body ternary complex (TC) assembly, and conformational sampling strategies that address the inherent flexibility and complexity of these molecules. Each modeled TC is evaluated using a clash-score and a surface-score, designed to prioritize sterically and geometrically plausible models with favorable protein surface interactions.
View Article and Find Full Text PDFChem Biomed Imaging
August 2025
Department of Chemistry, Colorado State University, 200 West Lake Street, Fort Collins, Colorado 80523-1872, United States.
Defect-mediated energy transfer (EnT) is a radiative process that occurs between donor defect states in the forbidden bandgap of semiconductor nanocrystals (NCs) and dye molecules bound to their surfaces. The EnT efficiency depends on the number of dye molecules attached to each NC, the donor-acceptor distance, and the dipole orientation factor between the donor and acceptor, all of which vary across individual NCs in a sample. While ensemble-level fluorescence spectroscopy measurements have provided values for donor-acceptor distances, dye-to-NC ratios, and EnT rate constants, questions remain about the impact of donor/acceptor heterogeneity on observed EnT efficiencies.
View Article and Find Full Text PDFJ Biol Chem
August 2025
Department of Pharmaceutical Sciences, College of Pharmacy, University of New Mexico, Albuquerque, NM, 87131; Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, NM, 87131. Electronic address:
Mammalian nitric oxide synthases (NOSs) are flavo-hemoproteins that rely on dynamic interdomain interactions for activity. Calmodulin (CaM) facilitates specific, interdomain FMN-heme interactions that enable inter-subunit FMN-heme electron transfer essential for nitric oxide biosynthesis. Our quantitative cross-linking mass spectrometry (qXL MS) results demonstrate that the abundance of inter-subunit cross-links correlates with CaM-induced formation of the docked FMN/heme complex in neuronal NOS [Jiang et al.
View Article and Find Full Text PDFSensors (Basel)
August 2025
College of Electronics and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
To address the challenging problem of multi-scale inshore-offshore ship detection in synthetic aperture radar (SAR) remote sensing images, we propose a novel deep learning-based automatic ship detection method within the framework of compositional learning. The proposed method is supported by three pillars: context-guided region proposal, prototype-based model-pretraining, and multi-model ensemble learning. To reduce the false alarms induced by the discrete ground clutters, the prior knowledge of the harbour's layout is exploited to generate land masks for terrain delimitation.
View Article and Find Full Text PDFUltrason Imaging
August 2025
School of Computing, University of Buckingham, Buckingham, UK.
Breast ultrasound images play a pivotal role in assessing the nature of suspicious breast lesions, particularly in patients with dense tissue. Computerized analysis of breast ultrasound images has the potential to assist the physician in the clinical decision-making and improve subjective interpretation. We assess the performance of conventional features, deep learning features and ensemble schemes for discriminating benign versus malignant breast lesions on ultrasound images.
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