In this article, we hypothesize that individuals with autism spectrum disorder (ASD) are born with a deficit in invariance detection, which is a learning process whereby people and animals come to attend the relatively stable patterns or structural regularities in the changing stimulus array. This paper synthesizes a substantial body of research which suggests that a deficit in the domain-general perceptual learning process of invariant detection in ASD can lead to a cascade of consequences in different developmental domains. We will outline how this deficit in invariant detection can cause uncertainty, unpredictability, and a lack of control for individuals with ASD and how varying degrees of impairments in this learning process can account for the heterogeneity of the ASD phenotype. We also describe how differences in neural plasticity in ASD underlie the impairments in perceptual learning. The present account offers an alternative to prior theories and contributes to the challenge of understanding the developmental trajectories that result in the variety of autistic behaviors.
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http://dx.doi.org/10.3389/fpsyg.2015.00359 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA 15213.
The auditory system is unique among sensory systems in its ability to phase lock to and precisely follow very fast cycle-by-cycle fluctuations in the phase of sound-driven cochlear vibrations. Yet, the perceptual role of this temporal fine structure (TFS) code is debated. This fundamental gap is attributable to our inability to experimentally manipulate TFS cues without altering other perceptually relevant cues.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Computer Science, National Textile University, Faisalabad, Pakistan.
Accurate diagnosis of pancreatic cancer using CT scan images is critical for early detection and treatment, potentially saving numerous lives globally. Manual identification of pancreatic tumors by radiologists is challenging and time-consuming due to the complex nature of CT scan images and variations in tumor shape, size, and location of the pancreatic tumor also make it challenging to detect and classify different types of tumors. Thus, to address this challenge we proposed a four-stage framework of computer-aided diagnosis systems.
View Article and Find Full Text PDFPLoS One
January 2025
School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China.
Optical Coherence Tomography (OCT) offers high-resolution images of the eye's fundus. This enables thorough analysis of retinal health by doctors, providing a solid basis for diagnosis and treatment. With the development of deep learning, deep learning-based methods are becoming more popular for fundus OCT image segmentation.
View Article and Find Full Text PDFIntroduction: Ethiopia has made notable progress in reducing maternal and perinatal mortality, yet challenges remain in meeting the 2030 Sustainable Development Goals. Persistent issues such as low service utilization, coupled with poor quality, fragmented care, and ineffective referral systems hinder progress. The "Improve Primary Health Care Service Delivery (IPHCSD)" project, implemented by JSI and Amref Health Africa since April 2022, seeks to address these gaps through a Networks of Care (NoCs) approach.
View Article and Find Full Text PDFJ Am Chem Soc
January 2025
Institute of Materials for Electronics and Energy Technology (i-MEET), Department of Materials Science and Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Martensstraße 7, 91058 Erlangen, Germany.
Emerging photovoltaics for outer space applications are one of the many examples where radiation hard molecular semiconductors are essential. However, due to a lack of general design principles, their resilience against extra-terrestrial high-energy radiation can currently not be predicted. In this work, the discovery of radiation hard materials is accelerated by combining the strengths of high-throughput, lab automation and machine learning.
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