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Bade, M. L.

Publications and source records attributed to Bade, M. L..

2 recordsLinked to original sources

Model of naturally occurring refractive error (NORE) in mice

PurposeAnimal models of myopia typically induce monocular refractive shifts via form deprivation (FD) or lens-induced myopia (LIM), modeling susceptibility to myopia, but with potentially limited applicability to childhood myopia. Here we describe a novel, genetically diverse mouse model of naturally occurring refractive error (NORE) with three distinct refractive phenotypes: hyperopic, myopic, and intermediate. MethodsC57BL/6J mice were mated to 129S2/SvPasCrl mice to create F1 or F2 offspring. Refractive errors in male and female F1 (N=21) and F2 (N=101) mice were assessed on postnatal days (P) 28 and 42 using photorefractometry. In a subset of mice (N=30-40), corneal radius of curvature, axial ocular dimensions, retinal and visual function were assessed. ResultsF2 mice were classified as NORE with either hyperopic (RE[&ge;]0 diopters (D) at P28 and P42), myopic (RE<0D at P28 and P42) or intermediate (RE<0D at P28 and RE[&ge;]0D at P42) refractions based on individual trajectories. All ocular parameters changed with age, with significantly slower growth in axial length and vitreous chamber depth in the intermediate versus myopic mice (p<0.05). Lens thickness was smaller in the myopic group at P28. Differences in refraction were not attributed to variances in retinal function or dopamine signaling. ConclusionsNORE mice represent a novel, genetically diverse wild-type mouse model that, unlike traditional models, does not require interventions such as FD or LIM to induce myopia. NORE mice provide a valuable tool for future investigations of genetic and environmental mechanisms and targeted therapeutic strategies for refractive errors.

genetics↗

Mice preferentially use increases in cerebral cortex spike rates to detect changes in visual stimuli

Whenever the retinal image changes some neurons in visual cortex increase their rate of firing, while others decrease their rate of firing. Linking specific sets of neuronal responses with perception and behavior is essential for understanding mechanisms of neural circuit computation. We trained mice to perform visual detection tasks and used optogenetic perturbations to increase or decrease neuronal spiking primary visual cortex (V1). Perceptual reports were always enhanced by increments in V1 spike counts and impaired by decrements, even when increments and decrements were delivered to the same neuronal populations. Moreover, detecting changes in cortical activity depended on spike count integration rather than instantaneous changes in spiking. Recurrent neural networks trained in the task similarly relied on increments in neuronal activity when activity was costly. This work clarifies neuronal decoding strategies employed by cerebral cortex to translate cortical spiking into percepts that can be used to guide behavior.

neuroscience↗