Contrast adaptation is spatial frequency specific in mouse primary visual cortex

King, Jillian L.; Lowe, Matthew; Crowder, Nathan A.

doi:10.1016/j.neuroscience.2015.09.037

Cited by 9 publications

(3 citation statements)

References 50 publications

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“…We focus specifically on orientation adaptation effects in V1. Other factors such as spatial and temporal frequency are also known to influence adaptation (e.g., King, Lowe, & Crowder, 2015 ; Ledue, King, Stover, & Crowder, 2013 ; Saul & Cynader, 1989 ) but are beyond the scope of our current modeling effort, which is based on a population of oriented RFs. We also focus on effects confined to the classical RF of V1 neurons.…”

Section: Introductionmentioning

confidence: 99%

Specificity and timescales of cortical adaptation as inferences about natural movie statistics

2016

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Adaptation is a phenomenological umbrella term under which a variety of temporal contextual effects are grouped. Previous models have shown that some aspects of visual adaptation reflect optimal processing of dynamic visual inputs, suggesting that adaptation should be tuned to the properties of natural visual inputs. However, the link between natural dynamic inputs and adaptation is poorly understood. Here, we extend a previously developed Bayesian modeling framework for spatial contextual effects to the temporal domain. The model learns temporal statistical regularities of natural movies and links these statistics to adaptation in primary visual cortex via divisive normalization, a ubiquitous neural computation. In particular, the model divisively normalizes the present visual input by the past visual inputs only to the degree that these are inferred to be statistically dependent. We show that this flexible form of normalization reproduces classical findings on how brief adaptation affects neuronal selectivity. Furthermore, prior knowledge acquired by the Bayesian model from natural movies can be modified by prolonged exposure to novel visual stimuli. We show that this updating can explain classical results on contrast adaptation. We also simulate the recent finding that adaptation maintains population homeostasis, namely, a balanced level of activity across a population of neurons with different orientation preferences. Consistent with previous disparate observations, our work further clarifies the influence of stimulus-specific and neuronal-specific normalization signals in adaptation.

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Section: Introductionmentioning

confidence: 99%

Specificity and timescales of cortical adaptation as inferences about natural movie statistics

2016

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“…However, both phenomena could also be the signature of spatially-specific sensory adaptation. It is well known that the visual system adapts to visual input, typically leading to reduced neural responses for repeated or prolonged stimulus presentations [36][37][38][39][40][41][42][43][44][45] , and inducing repulsive biases in behavior [46][47][48][49][50] . Neural adaptation to high contrast is believed to reduce perceptual sensitivity to subsequently presented low contrast stimuli 51,52 .…”

Section: Reduction In Previous Choice Weight Is Not Due To Sensory Ad...mentioning

confidence: 99%

Temporal regularities shape perceptual decisions and striatal dopamine signals

Fritsche,

Majumdar,

Strickland

et al. 2023

Preprint

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Perceptual decisions should depend on sensory evidence. However, such decisions are also influenced by past choices and outcomes. These choice history biases may reflect advantageous strategies to exploit temporal regularities of natural environments. However, it is unclear whether and how observers can adapt their choice history biases to different temporal regularities, to exploit the multitude of temporal correlations that exist in nature. Here, we show that mice adapt their perceptual choice history biases to different temporal regularities. This adaptation is well captured by a normative reinforcement learning algorithm with multi-trial belief states, comprising both current trial sensory and previous trial memory states. We demonstrate that striatal dopamine tracks predictions of the model and behavior, pointing towards the involvement of dopamine in forming adaptive history biases. Our results reveal the adaptive nature of perceptual choice history biases, and shed light on their underlying computational principles and neural implementation.

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“…It is a generalized version of Fourier transform. The generalization that is being made is comprised of two additional features including spatial frequency [104][105] and the location of the objects in the images. The basic application of curvelet method is in the domain when the objects within the images contain the minutest scale length.…”

Section: Curvelet Transformmentioning

confidence: 99%

Image Fusion Methods: A Survey

Masood¹,

Sharif²,

Yasmin³

et al. 2017

JESTR

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Image fusion is an approach which is used to amalgamate the corresponding features in a sequence of input images to a single composite image that preserves all the significant features of the input images. Image fusion is also known as pansharpening. It is a method which is used to integrate and add the geometric detail of a high-resolution panchromatic (Pan) image and the information of color of a low-resolution multispectral (MS) image for the production of a high-resolution MS image. This methodology is mainly most important and significant for any large-scale applications. Image fusion classification based on its systems (models and algorithms) are considered and overviewed in this survey. The basic two algorithms categories are analyzed and compared to each other, in the analysis and discussion section the major points to be considered while performing image fusion are highlighted.

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Contrast adaptation is spatial frequency specific in mouse primary visual cortex

Cited by 9 publications

References 50 publications

Specificity and timescales of cortical adaptation as inferences about natural movie statistics

Specificity and timescales of cortical adaptation as inferences about natural movie statistics

Temporal regularities shape perceptual decisions and striatal dopamine signals

Image Fusion Methods: A Survey

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