Latent effects of hypoxia on the gastropod Crepidula onyx

2013 ◽  
Vol 480 ◽  
pp. 145-154 ◽  
Author(s):  
A Li ◽  
JMY Chiu
Keyword(s):  
Latent Effects ◽  
Crepidula Onyx

Modelling of non-proportional hardening by dislocation based latent effects for SA333 Grade-6 C-Mn Steel

2019 ◽  
Vol 6 (8) ◽  
pp. 086562
Author(s):  
S Bhattacharjee ◽  
S Dhar ◽  
S K Acharyya ◽  
S K Gupta
Keyword(s):  
Latent Effects ◽  
Mn Steel

scholarly journals The dynamic neural code of the retina for natural scenes

2018 ◽  
Author(s):  
Niru Maheswaranathan ◽  
Lane T. McIntosh ◽  
Hidenori Tanaka ◽  
Satchel Grant ◽  
David B. Kastner ◽  
...  
Keyword(s):  
Visual Processing ◽  
Ganglion Cells ◽  
Predictive Coding ◽  
Neural Code ◽  
Natural Scenes ◽  
Large Set ◽  
Fundamental Limits ◽  
Fundamental Goal ◽  
Latent Effects ◽  
Highly Correlated

AbstractUnderstanding how the visual system encodes natural scenes is a fundamental goal of sensory neuroscience. We show here that a three-layer network model predicts the retinal response to natural scenes with an accuracy nearing the fundamental limits of predictability. The model’s internal structure is interpretable, in that model units are highly correlated with interneurons recorded separately and not used to fit the model. We further show the ethological relevance to natural visual processing of a diverse set of phenomena of complex motion encoding, adaptation and predictive coding. Our analysis uncovers a fast timescale of visual processing that is inaccessible directly from experimental data, showing unexpectedly that ganglion cells signal in distinct modes by rapidly (< 0.1 s) switching their selectivity for direction of motion, orientation, location and the sign of intensity. A new approach that decomposes ganglion cell responses into the contribution of interneurons reveals how the latent effects of parallel retinal circuits generate the response to any possible stimulus. These results reveal extremely flexible and rapid dynamics of the retinal code for natural visual stimuli, explaining the need for a large set of interneuron pathways to generate the dynamic neural code for natural scenes.

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