We compared psychophysical and functional magnetic resonance imaging (fMRI) responses within areas V1-V3 and MT+ during both a speed and a contrast discrimination task. We found that fMRI responses did not depend significantly on task in any of these areas. Moreover, responses in V1-V3 were larger than those in MT+ for both the speed and the contrast discrimination tasks across a wide range of contrasts. This pattern of results demonstrates that localizing function based on finding those regions of cortex that show greater activity to a given task-stimulus combination than to other tasks and stimuli may, under certain conditions, be misleading. However, a simple ideal observer model assuming that perceptual thresholds are dependent on neuronal population responses does successfully show that V1 has neuronal properties consistent with our subjects' contrast discrimination performance, and that MT+ has neuronal properties consistent with subjects' performance on a speed discrimination task.
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http://dx.doi.org/10.1523/JNEUROSCI.4476-04.2005 | DOI Listing |
BMC Ophthalmol
January 2025
Department of Optometry, School of Rehabilitation, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: The psychometric properties of the Convergence Insufficiency Symptom Survey (CISS) have been previously determined across the younger adult population. This study investigated the psychometric properties of the CISS in presbyopic adults via classical and Rasch analysis.
Methods: A total of 100 presbyopic individuals (40-60 years) were selected with far and near acuity of 20/20 with their habitual spectacles; 50 had convergence insufficiency and 50 had normal binocular vision.
Background: This study aimed to explore the clinical and pathological features of patients with diabetic kidney disease (DKD), with and without non-diabetic kidney disease (NDKD), through a retrospective analysis. The objective was to provide clinical insights for accurate identification.
Methods: A retrospective analysis of 235 patients admitted to the Department of Nephrology at Hangzhou Hospital of Traditional Chinese Medicine was conducted between July 2014 and December 2022.
Transl Pediatr
December 2024
Central Laboratory, Jiangxi Provincial Children's Hospital, The Affiliated Children's Hospital of Nanchang Medical College, Nanchang, China.
Background: Oral microbiome homeostasis is important for children's health, and microbial community is affected by anesthetics. The application of anesthetics in children's oral therapy has become a relatively mature method. This study aims to investigate the effect of different anesthesia techniques on children's oral microbiota.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Radiation Oncology, Cancer Center, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, People's Republic of China.
This study aims to compare the survival discrimination of the Tumor-Node-Metastasis (TNM) eighth and ninth editions for patients with localized and locally advanced (LLA) anal squamous cell carcinoma (ASCC) treated non-surgically and to evaluate the prognostic impact of T classification and lymph node (LN) status with data from the Surveillance, Epidemiology, and End Results database. We retrospectively included 6,876 patients in the comparison. We observed the inversion of survival outcomes for stages IIB and IIIA diseases in the TNM eighth edition [median overall survival (OS): 112 months for stage IIB vs.
View Article and Find Full Text PDFPhysiol Meas
January 2025
Harbin Institute of Technology, Harbin Institute of Technology, Harbin, 150001, CHINA.
Objective: The demand for ECG datasets, particularly those containing rare classes, poses a significant challenge as deep learning becomes increasingly prevalent in ECG signal research. While Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) are widely adopted, they encounter difficulties in effectively generating samples for classes with limited instances.
Approach: To address this issue, we propose a novel Feature Disentanglement Auto-Encoder (FDAE) designed to dissect various generative factors under a contrastive learning framework within ECG data to facilitate the generation of new ECG samples.
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