scholarly journals Blue-on-Green Flash Induces Maximal Photopic Negative Response and Oscillatory Potential and Serves as a Diagnostic Marker for Glaucoma in Rat Retina

2018 ◽  
Vol 27 (3) ◽  
pp. 210-216
Author(s):  
Su Jin Park ◽  
Sun Sook Paik ◽  
Ji-Yeon Lee ◽  
Su-Ja Oh ◽  
In-Beom Kim
Keyword(s):  
Diagnostic Marker ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Oscillatory Potential ◽  
Rat Retina

The photopic negative response of the flash electroretinogram in retinal vein occlusion

2006 ◽  
Vol 113 (1) ◽  
pp. 53-59 ◽  
Author(s):  
Hongling Chen ◽  
Dezheng Wu ◽  
Shizhou Huang ◽  
Hong Yan
Keyword(s):  
Retinal Vein Occlusion ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Vein Occlusion ◽  
Flash Electroretinogram

Intraocular Pressure Lowering Is Associated with an Increase in the Photopic Negative Response (PhNR) Amplitude in Glaucoma and Ocular Hypertensive Eyes

2013 ◽  
Vol 54 (3) ◽  
pp. 1913 ◽  
Author(s):  
Nuwan Niyadurupola ◽  
Chi D. Luu ◽  
Dan Q. Nguyen ◽  
Kristen Geddes ◽  
Gary X. V. Tan ◽  
...  
Keyword(s):  
Intraocular Pressure ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Pressure Lowering

Photopic Negative Response Reflects Severity of Ocular Circulatory Damage after Central Retinal Artery Occlusion

2009 ◽  
Vol 223 (6) ◽  
pp. 362-369 ◽  
Author(s):  
Celso S. Matsumoto ◽  
Kei Shinoda ◽  
Kisaburo Yamada ◽  
Kazuo Nakatsuka
Keyword(s):  
Central Retinal Artery Occlusion ◽  
Retinal Artery Occlusion ◽  
Artery Occlusion ◽  
Central Retinal Artery ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Retinal Artery

scholarly journals The Photopic Negative Response: An Objective Measure of Retinal Ganglion Cell Function in Patients With Leber's Hereditary Optic Neuropathy

2017 ◽  
Vol 58 (6) ◽  
pp. BIO300 ◽  
Author(s):  
Rustum Karanjia ◽  
Adriana Berezovsky ◽  
Paula Yuri Sacai ◽  
Nivea Nunes Cavascan ◽  
Henry Yuheng Liu ◽  
...  
Keyword(s):  
Ganglion Cell ◽  
Retinal Ganglion Cell ◽  
Optic Neuropathy ◽  
Cell Function ◽  
Objective Measure ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Retinal Ganglion ◽  
Retinal Ganglion Cell Function ◽  
Hereditary Optic Neuropathy

scholarly journals Comparison of Photopic Negative Response of Full-Field and Focal Electroretinograms in Detecting Glaucomatous Eyes

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Shigeki Machida ◽  
Kunifusa Tamada ◽  
Taku Oikawa ◽  
Yasutaka Gotoh ◽  
Tomoharu Nishimura ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Diagnostic Ability ◽  
Full Field ◽  
Receiver Operating Characteristic Curves ◽  
Advanced Glaucoma ◽  
Blue Background ◽  
Higher Sensitivity

Purpose. To compare the photopic negative response (PhNR) of the full-field electroretinogram (ERG) to the PhNR of the focal ERGs in detecting glaucoma.Methods. One hundred and three eyes with glaucoma and 42 normal eyes were studied. Full-field ERGs were elicited by red stimuli on a blue background. The focal ERGs were elicited by a15∘white stimulus spot centered on the macula, the superotemporal or the inferotemporal areas of the macula.Results. In early glaucoma, the areas under the receiver operating characteristic curves (AUCs) were significantly larger for the focal PhNR (0.863–0.924) than those for the full-field PhNR (0.666–0.748) (P<.05). The sensitivity was significantly higher for the focal PhNR than for the full-field PhNR in early (P<.01) and intermediate glaucoma (P<.05). In advanced glaucoma, there was no difference in the AUCs and sensitivities between the focal and full-field PhNRs.Conclusions. The focal ERG has the diagnostic ability with higher sensitivity in detecting early and intermediate glaucoma than the full-field ERG.

scholarly journals Comparison of Machine Learning Approaches to Improve Diagnosis of Optic Neuropathy Using Photopic Negative Response Measured Using a Handheld Device

2021 ◽  
Vol 8 ◽  
Author(s):  
Tina Diao ◽  
Fareshta Kushzad ◽  
Megh D. Patel ◽  
Megha P. Bindiganavale ◽  
Munam Wasi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Optic Neuropathy ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Learning Approaches ◽  
Data Set ◽  
Full Field ◽  
Handheld Device ◽  
Technical Requirements

The photopic negative response of the full-field electroretinogram (ERG) is reduced in optic neuropathies. However, technical requirements for measurement and poor classification performance have limited widespread clinical application. Recent advances in hardware facilitate efficient clinic-based recording of the full-field ERG. Time series classification, a machine learning approach, may improve classification by using the entire ERG waveform as the input. In this study, full-field ERGs were recorded in 217 eyes (109 optic neuropathy and 108 controls) of 155 subjects. User-defined ERG features including photopic negative response were reduced in optic neuropathy eyes (p &lt; 0.0005, generalized estimating equation models accounting for age). However, classification of optic neuropathy based on user-defined features was only fair with receiver operating characteristic area under the curve ranging between 0.62 and 0.68 and F1 score at the optimal cutoff ranging between 0.30 and 0.33. In comparison, machine learning classifiers using a variety of time series analysis approaches had F1 scores of 0.58–0.76 on a test data set. Time series classifications are promising for improving optic neuropathy diagnosis using ERG waveforms. Larger sample sizes will be important to refine the models.

Significant correlations between focal photopic negative response and focal visual sensitivity and ganglion cell complex thickness in glaucomatous eyes

2021 ◽  
Author(s):  
Masahiko Ishizuka ◽  
Shigeki Machida ◽  
Yuji Hara ◽  
Atsushi Tada ◽  
Satoshi Ebihara ◽  
...  
Keyword(s):  
Ganglion Cell ◽  
Cell Complex ◽  
Visual Sensitivity ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Ganglion Cell Complex

Reduction of Oscillatory Potentials and Photopic Negative Response in Patients with Autosomal Dominant Optic Atrophy withOPA1Mutations

2007 ◽  
Vol 48 (2) ◽  
pp. 820 ◽  
Author(s):  
Kentaro Miyata ◽  
Makoto Nakamura ◽  
Mineo Kondo ◽  
Jian Lin ◽  
Shinji Ueno ◽  
...  
Keyword(s):  
Optic Atrophy ◽  
Autosomal Dominant ◽  
Oscillatory Potentials ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Autosomal Dominant Optic Atrophy ◽  
Dominant Optic Atrophy

Time-Frequency Analysis of Photopic Negative Response in CRVO Patients

2020 ◽  
Vol 35 (3) ◽  
pp. 187-193 ◽  
Author(s):  
Soroor Behbahani ◽  
Alireza Ramezani ◽  
Mohammad Karimi Moridani ◽  
Hamideh Sabbaghi
Keyword(s):  
Frequency Analysis ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Time Frequency Analysis ◽  
Time Frequency

Correlation between Photopic Negative Response and Retinal Nerve Fiber Layer Thickness and Optic Disc Topography in Glaucomatous Eyes

2008 ◽  
Vol 49 (5) ◽  
pp. 2201 ◽  
Author(s):  
Shigeki Machida ◽  
Yasutaka Gotoh ◽  
Yoshiharu Toba ◽  
Aki Ohtaki ◽  
Muneyoshi Kaneko ◽  
...  
Keyword(s):  
Nerve Fiber ◽  
Layer Thickness ◽  
Optic Disc ◽  
Retinal Nerve Fiber Layer ◽  
Negative Response ◽  
Photopic Negative Response ◽  
Fiber Layer ◽  
Nerve Fiber Layer ◽  
Nerve Fiber Layer Thickness ◽  
Retinal Nerve Fiber
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