Unlike most visual tasks, contrast discrimination has been reported to be unchanged by practice (Dorais & Sagi, 1997; Adini, Sagi, & Tsodyks, 2002), unless practice is undertaken in the presence of flankers (context-enabled learning, Adini et al., 2002). Here we show that under experimental conditions nearly identical to those in the no-flanker practice experiment of Adini et al. (2002), practice significantly improved contrast discrimination. Moreover, in a separate experiment, we found that practice without flankers can improve contrast discrimination to a level only reached with flankers in Adini et al. (2002), but further practice with flankers produces no further improvement of contrast discrimination. These results call into question whether the "context-enabled learning" proposed by Adini et al. (2002) is different from regular contrast learning without flankers. In separate experiments, we found that contrast learning is tuned to spatial frequency, orientation, retinal location, and, unexpectedly, contrast. We also replicated Sagi, Adini, Tsodyks, and Wilkonsky's (2003) more recent finding that no regular contrast learning occurs if reference contrasts are randomly interleaved (contrast roving), and further demonstrated that flankers have no effect on contrast learning under contrast roving, another piece of evidence equating "context-enabled learning" to regular contrast learning. The contrast specificity of learning and the lack of learning under contrast roving provide new evidence in favor of a multiple contrast-selective channels model of contrast discrimination, and against saturating transducer models and multiplicative noise models.
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http://dx.doi.org/10.1167/4.3.4 | DOI Listing |
Acta Biomater
January 2025
Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, United Kingdom.
The quantitative characterization of the structure of biomineral surfaces is needed for guiding regenerative strategies. Current techniques are compromised by a requirement for extensive sample preparation, limited length-scales, or the inability to repeatedly measure the same surface over time and monitor structural changes. We aim to address these deficiencies by developing Calcium (Ca) K-edge Polarisation Induced Contrast X-ray Fluorescence (PIC-XRF) to quantify hydroxyapatite (HAp) crystallite structural arrangements in high and low textured surfaces.
View Article and Find Full Text PDFEur J Pharm Sci
January 2025
Preclinical Sciences & Translational Safety, Janssen R&D, Turnhoutseweg 30, 2340, Beerse, Belgium. Electronic address:
The purpose of this study was to evaluate EpiColon, a novel human organotypic 3D colon microtissue prototype, developed to assess colonic drug disposition, with a particular focus on permeability ranking, and compare its performance to Caco-2 monolayers. EpiColon was characterized for barrier function using transepithelial electrical resistance (TEER), morphology via histology and immunohistochemistry, and functionality through drug transport studies measuring apparent permeability (P). Cutoff thresholds for the permeability of FITC-dextran 4 kDa (FD4), FITC-dextran 10 kDa (FD10S), and [C]mannitol were established to monitor microtissue integrity.
View Article and Find Full Text PDFThe primary concern among adults with regard to their hearing is the difficulty in comprehending speech, particularly in noisy environments. The constant need to listen attentively leads to heightened frustration, fatigue and decreased concentration. According to research, high-frequency hearing loss could have negative implications on speech perception and make it even harder to communicate.
View Article and Find Full Text PDFNeural Netw
January 2025
School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430070, Hubei, China.
In the Imbalanced Multivariate Time Series Classification (ImMTSC) task, minority-class instances typically correspond to critical events, such as system faults in power grids or abnormal health occurrences in medical monitoring. Despite being rare and random, these events are highly significant. The dynamic spatial-temporal relationships between minority-class instances and other instances make them more prone to interference from neighboring instances during classification.
View Article and Find Full Text PDFSensors (Basel)
January 2025
College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China.
Domain-generalizable re-identification (DG Re-ID) aims to train a model on one or more source domains and evaluate its performance on unseen target domains, a task that has attracted growing attention due to its practical relevance. While numerous methods have been proposed, most rely on discriminative or contrastive learning frameworks to learn generalizable feature representations. However, these approaches often fail to mitigate shortcut learning, leading to suboptimal performance.
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