Studies of visual function in behaving subjects require that stimuli be positioned reliably on the retina in the presence of eye movements. Fixational eye movements scatter stimuli about the retina, inflating estimates of receptive field dimensions, reducing estimates of peak responses, and blurring maps of receptive field subregions. Scleral search coils are frequently used to measure eye position, but their utility for correcting the effects of fixational eye movements on receptive field maps has been questioned. Using eye coils sutured to the sclera and preamplifiers configured to minimize cable artifacts, we reexamined this issue in two rhesus monkeys. During repeated fixation trials, the eye position signal was used to adjust the stimulus position, compensating for eye movements and correcting the stimulus position to place it at the desired location on the retina. Estimates of response magnitudes and receptive field characteristics in V1 and in LGN were obtained in both compensated and uncompensated conditions. Receptive fields were narrower, with steeper borders, and response amplitudes were higher when eye movement compensation was used. In sum, compensating for eye movements facilitated more precise definition of the receptive field. We also monitored horizontal vergence over long sequences of fixation trials and found the variability to be low, as expected for this precise behavior. Our results imply that eye coil signals can be highly accurate and useful for optimizing visual physiology when rigorous precautions are observed.

Download full-text PDF

Source
http://dx.doi.org/10.1152/jn.00881.2006DOI Listing

Publication Analysis

Top Keywords

receptive field
24
eye movements
20
eye position
12
eye
11
estimates response
8
fixational eye
8
fixation trials
8
stimulus position
8
compensating eye
8
receptive
7

Similar Publications

Nexus: A versatile console for advanced low-field MRI.

Magn Reson Med

January 2025

Department 8.1 - Biomedical Magnetic Resonance, Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.

Purpose: To develop a low-cost, high-performance, versatile, open-source console for low-field MRI applications that can integrate a multitude of different auxiliary sensors.

Methods: A new MR console was realized with four transmission and eight reception channels. The interface cards for signal transmission and reception are installed in PCI Express slots, allowing console integration in a commercial PC rack.

View Article and Find Full Text PDF

Reading, face recognition, and navigation are supported by visuospatial computations in category-selective regions across ventral, lateral, and dorsal visual streams. However, the nature of visuospatial computations across streams and their development in adolescence remain unknown. Using fMRI and population receptive field (pRF) modeling in adolescents and adults, we estimate pRFs in high-level visual cortex and determine their development.

View Article and Find Full Text PDF

Brief monocular deprivation during a developmental critical period, but not thereafter, alters the receptive field properties (tuning) of neurons in visual cortex, but the characteristics of neural circuitry that permit this experience-dependent plasticity are largely unknown. We performed repeated calcium imaging at neuronal resolution to track the tuning properties of populations of excitatory layer 2/3 neurons in mouse visual cortex during or after the critical period, as well as in mutant mice that sustain critical-period plasticity as adults. The instability of tuning for populations of neurons was greater in juvenile mice and adult mutant mice.

View Article and Find Full Text PDF

Chip defect detection is a crucial aspect of the semiconductor production industry, given its significant impact on chip performance. This paper proposes a lightweight neural network with dual decoding paths for LED chip segmentation, named LDDP-Net. Within the LDDP-Net framework, the receptive field of the MobileNetv3 backbone is modified to mitigate information loss.

View Article and Find Full Text PDF

A Parallel Image Denoising Network Based on Nonparametric Attention and Multiscale Feature Fusion.

Sensors (Basel)

January 2025

School of Electronic and Information Engineering, Ankang University, Ankang 725000, China.

Convolutional neural networks have achieved excellent results in image denoising; however, there are still some problems: (1) The majority of single-branch models cannot fully exploit the image features and often suffer from the loss of information. (2) Most of the deep CNNs have inadequate edge feature extraction and saturated performance problems. To solve these problems, this paper proposes a two-branch convolutional image denoising network based on nonparametric attention and multiscale feature fusion, aiming to improve the denoising performance while better recovering the image edge and texture information.

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!