Electroretinography (ERG) is a foundational method for assessing visual system physiology, but accurate ERG can be time- and labor-intensive, often involving manual adjustment of the wavelength and intensity of light stimuli and real-time comparison of physiological responses to inform those adjustments. Furthermore, current approaches to ERG often require expertise beyond that necessary for the electrophysiological preparation itself. To improve both the efficiency and accessibility of ERG, we designed an automated system for stimulus presentation and data acquisition. Here, we test this novel system's ability to accurately assess spectral sensitivity in the well-characterized visual system of the crayfish Procambarus clarkii using three approaches: the first, based on response magnitude, maximizes efficiency; the second is a well-established method we use to further validate our efficient approach's accuracy. Third, we explore the potential benefits of extensible automation using a method assessing the interplay between temporal acuity and spectral sensitivity. Using our system, we are able to acquire accurate results in ERG experiments quickly (testing the entire visible spectrum in 8 min, 30 s using our response magnitude approach). Moreover, data collected via all three methods yielded results consistent with each other and previous work on P. clarkii.
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http://dx.doi.org/10.1007/s00359-021-01476-4 | DOI Listing |
JMIR Res Protoc
January 2025
National Radiotherapy, Oncology and Nuclear Medicine Centre, Korle-bu Teaching Hospital, Accra, Ghana.
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View Article and Find Full Text PDFJ Neurosurg
January 2025
1Department of Neurosurgery, Inselspital, Bern University Hospital, University Bern, Switzerland.
Objective: The effectiveness and optimal stimulation site of deep brain stimulation (DBS) for central poststroke pain (CPSP) remain elusive. The objective of this retrospective international multicenter study was to assess clinical as well as neuroimaging-based predictors of long-term outcomes after DBS for CPSP.
Methods: The authors analyzed patient-based clinical and neuroimaging data of previously published and unpublished cohorts from 6 international DBS centers.
JMIR Res Protoc
January 2025
Department of Women's and Children's Health, Participatory eHealth and Health Data Research Group, Uppsala University, Uppsala, Sweden.
Background: Digital health interventions have become increasingly popular in recent years, expanding the possibilities for treatment for various patient groups. In clinical research, while the design of the intervention receives close attention, challenges with research participant engagement and retention persist. This may be partially due to the use of digital health platforms, which may lack adequacy for participants.
View Article and Find Full Text PDFJ Neurosurg Spine
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6Presbyterian St. Lukes Medical Center, Denver, Colorado.
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