We attempt to evaluate the residual visual capacities of nine patients (seven males and two females; age range 4 to 35 years, mean 13.8 +/- 9.98) with cerebral visual impairment coupled with severe motor and intellectual disabilities by their contrast sensitivities to sine-wave gratings. Two methods were used for detecting the occurrence of ocular responses to stimuli: (1) detection of optokinetic nystagmus to drifting sinusoidal gratings by naked-eye observation and electronystagmography and (2) detection of ocular pursuit for a drifting Gabor patch by naked-eye observation. We succeeded in measuring the sensitivities of eight cases. For the remaining one case, only the Gabor method could be applied. Most cases showed low contrast sensitivity in both higher (2 and 4 cycles/degree) and lower (0.125 and 0.25 cycles/degree) spatial frequencies and relatively high contrast sensitivity in the middle (0.5 and 1 cycle/degree) range of spatial frequencies. We conclude that the residual visual capacities of patients with severe motor and intellectual disabilities and cerebral visual impairment can be measured fairly accurately by these behavioral methods.

Download full-text PDF

Source
http://dx.doi.org/10.1177/08830738020170101201DOI Listing

Publication Analysis

Top Keywords

contrast sensitivity
12
severe motor
12
motor intellectual
12
intellectual disabilities
12
cerebral visual
12
visual impairment
12
patients severe
8
disabilities cerebral
8
residual visual
8
visual capacities
8

Similar Publications

End-to-End Deep Learning Prediction of Neoadjuvant Chemotherapy Response in Osteosarcoma Patients Using Routine MRI.

J Imaging Inform Med

January 2025

Department of Radiology, Peking University People's Hospital, 11 Xizhimen Nandajie, Xicheng District, Beijing, 100044, P. R. China.

This study aims to develop an end-to-end deep learning (DL) model to predict neoadjuvant chemotherapy (NACT) response in osteosarcoma (OS) patients using routine magnetic resonance imaging (MRI). We retrospectively analyzed data from 112 patients with histologically confirmed OS who underwent NACT prior to surgery. Multi-sequence MRI data (including T2-weighted and contrast-enhanced T1-weighted images) and physician annotations were utilized to construct an end-to-end DL model.

View Article and Find Full Text PDF

"Multimodal Sleep Signal Tensor Decomposition and Hidden Markov Modeling for Temazepam-Induced Anomalies Across Age Groups".

J Neurosci Methods

January 2025

School of Electrical and Computer Engineering, Gallogly College of Engineering, University of Oklahoma, Norman, OK 73019, USA.

Background: Recent advances in multimodal signal analysis enable the identification of subtle drug-induced anomalies in sleep that traditional methods often miss.

New Method: We develop and introduce the Dynamic Representation of Multimodal Activity and Markov States (DREAMS) framework, which embeds explainable artificial intelligence (XAI) techniques to model hidden state transitions during sleep using tensorized EEG, EMG, and EOG signals from 22 subjects across three age groups (18-29, 30-49, and 50-66 years). By combining Tucker decomposition with probabilistic Hidden Markov Modeling, we quantified age-specific, temazepam-induced hidden states and significant differences in transition probabilities.

View Article and Find Full Text PDF

The Southern California Bight is an ecologically important region for many local and migratory fauna. We combine bulk and compound-specific amino acid stable isotope measurements in the skeletons of proteinaceous octocorals with new regional ocean modeling system model output to explore biogeochemical changes at two locations within the Bight - Santa Cruz Basin and Santa Barbara Channel. Separated by the Channel Islands, these sites display distinct oceanographic regimes.

View Article and Find Full Text PDF

Towards contrast-agnostic soft segmentation of the spinal cord.

Med Image Anal

January 2025

NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Québec, Canada; Mila - Québec Artificial Intelligence Institute, Montréal, Québec, Canada; Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Québec, Canada; Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montréal, Québec, Canada. Electronic address:

Spinal cord segmentation is clinically relevant and is notably used to compute spinal cord cross-sectional area (CSA) for the diagnosis and monitoring of cord compression or neurodegenerative diseases such as multiple sclerosis. While several semi and automatic methods exist, one key limitation remains: the segmentation depends on the MRI contrast, resulting in different CSA across contrasts. This is partly due to the varying appearance of the boundary between the spinal cord and the cerebrospinal fluid that depends on the sequence and acquisition parameters.

View Article and Find Full Text PDF

Intraindividual Comparison of Image Quality Between Low-Dose and Ultra-Low-Dose Abdominal CT With Deep Learning Reconstruction and Standard-Dose Abdominal CT Using Dual-Split Scan.

Invest Radiol

January 2025

From the Department of Radiology, Ulsan University Hospital, Ulsan, Republic of Korea (T.Y.L.); Department of Radiology, University of Ulsan College of Medicine, Seoul, Republic of Korea (T.Y.L.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (J.H.Y., H.K., J.M.L.); Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea (J.H.Y., S.H.P., J.M.L.); Department of Radiology, Inje University Busan Paik Hospital, Busan, Republic of Korea (J.Y.P.); Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea (S.H.P.); Department of Radiology, Hanyang University College of Medicine, Seoul, Republic of Korea (C.L.); Division of Biostatistics, Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea (Y.C.); and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea (J.M.L.).

Objective: The aim of this study was to intraindividually compare the conspicuity of focal liver lesions (FLLs) between low- and ultra-low-dose computed tomography (CT) with deep learning reconstruction (DLR) and standard-dose CT with model-based iterative reconstruction (MBIR) from a single CT using dual-split scan in patients with suspected liver metastasis via a noninferiority design.

Materials And Methods: This prospective study enrolled participants who met the eligibility criteria at 2 tertiary hospitals in South Korea from June 2022 to January 2023. The criteria included (a) being aged between 20 and 85 years and (b) having suspected or known liver metastases.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!