An Extreme Value Theory Model of Cross-Modal Sensory Information Integration in Modulation of Vertebrate Visual System Functions

Banerjee, Sreya; Scheirer, Walter J.; Li, Lei

doi:10.1101/423038

Cited by 2 publications

(3 citation statements)

References 52 publications

(52 reference statements)

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“…This analysis will produce scaling relations that also permit to compute the probability that all cascades in a certain time interval have intensity less than a given threshold. This kind of extreme value laws for the size of neuronal cascades has not been investigated before, to the best of our knowledge-see however [24] for a discussion of the relevance of extreme value theory to sensorial perception.…”

Section: Neuronal Avalanchesmentioning

confidence: 96%

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Extreme value theory of evolving phenomena in complex dynamical systems: Firing cascades in a model of a neural network

Caby

Mantica

2020

Chaos: An Interdisciplinary Journal of Nonlinear Science

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We extend the scope of the dynamical theory of extreme values to cover phenomena that do not happen instantaneously, but evolve over a finite, albeit unknown at the onset, time interval. We consider complex dynamical systems, composed of many individual subsystems linked by a network of interactions. As a specific example of the general theory, a model of neural network, introduced to describe the electrical activity of the cerebral cortex, is analyzed in detail: on the basis of this analysis we propose a novel definition of neuronal cascade, a physiological phenomenon of primary importance. We derive extreme value laws for the statistics of these cascades, both from the point of view of exceedances (that satisfy critical scaling theory) and of block maxima.

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Section: Neuronal Avalanchesmentioning

confidence: 96%

“…Numerical experiment will confirm the formal theory. In the considered example, this offers a new statistical characterization of neuronal cascades, which might perhaps be of physiological relevance [24].…”

Section: Contents Of the Papermentioning

confidence: 99%

Extreme value theory of evolving phenomena in complex dynamical systems: Firing cascades in a model of a neural network

Caby

Mantica

2020

Chaos: An Interdisciplinary Journal of Nonlinear Science

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“…They considered single-unit retinal ganglion cells for those experiments. Banerjee et al [4] modeled this phenomenon by assuming the importance of extreme cellular responses in the modulation of sensory systems and applying the statistical extreme value theory.…”

Section: Introductionmentioning

confidence: 99%

An Assistive Computer Vision Tool to Automatically Detect Changes in Fish Behavior In Response to Ambient Odor

Banerjee

Alvey

Brown

et al. 2020

Preprint

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The analysis of fish behavior in response to odor stimulation is a crucial component of the general study of cross-modal sensory integration in vertebrates. In zebrafish, the centrifugal pathway runs between the olfactory bulb and the neural retina, originating at the terminalis neuron in the olfactory bulb. Any changes in the ambient odor of a fish’s environment warrants a change in visual sensitivity and can trigger mating-like behavior in males due to increased GnRH signaling in the terminalis neuron. Behavioral experiments to study this phenomenon are commonly conducted in a controlled environment where a video of the fish is recorded over time before and after the application of chemicals to the water. Given the subtleties of behavioral change, trained biologists are currently required to annotate such videos as part of a study. This process of manually analyzing the videos is time-consuming, requires multiple experts to avoid human error/bias and cannot be easily crowdsourced on the Internet. Machine learning algorithms from computer vision, on the other hand, have proven to be effective for video annotation tasks because they are fast, accurate, and, if designed properly, can be less biased than humans. In this work, we propose to automate the entire process of analyzing videos of behavior changes in zebrafish by using tools from computer vision, relying on minimal expert supervision. The overall objective of this work is to create a generalized tool to predict animal behaviors from videos using state-of-the-art deep learning models, with the dual goal of advancing understanding in biology and engineering a more robust and powerful artificial information processing system for biologists.

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An Extreme Value Theory Model of Cross-Modal Sensory Information Integration in Modulation of Vertebrate Visual System Functions

Cited by 2 publications

References 52 publications

Extreme value theory of evolving phenomena in complex dynamical systems: Firing cascades in a model of a neural network

Extreme value theory of evolving phenomena in complex dynamical systems: Firing cascades in a model of a neural network

An Assistive Computer Vision Tool to Automatically Detect Changes in Fish Behavior In Response to Ambient Odor

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