Exploring The Gabor Methods - amazonia.fiocruz.br

The mammalian visual system has been the focus of countless experimental and theoretical studies designed to elucidate principles of neural computation and sensory coding. Most theoretical work has focused on networks intended to reflect developing or mature neural circuitry, in Exploring The Gabor Methods health and disease. Few computational studies have attempted to model changes that occur in neural circuitry as an organism ages non-pathologically. In this work we contribute to closing this gap, studying how physiological changes correlated with advanced age impact the computational performance of a spiking network model of primary visual cortex V1.

Our results demonstrate that deterioration of homeostatic regulation of excitatory firing, coupled with long-term synaptic plasticity, is a sufficient mechanism to reproduce features of Exploring The Gabor Methods physiological and https://amazonia.fiocruz.br/scdp/essay/perception-checking-examples/co-operative-society.php changes in neural activity data, specifically declines in inhibition and in selectivity to oriented stimuli. This suggests a potential causality between dysregulation of neuron firing Expporing age-induced Methos in brain physiology and functional performance.

While this does not rule out deeper underlying causes or other mechanisms that could give rise to these changes, our approach opens new avenues for exploring these underlying mechanisms in greater depth and making predictions for future experiments. In this work we propose a computational model of an aging-like process in primary visual cortex that reproduces several experimentally-observed changes in senescent cats.

In particular, our model predicts that an age-induced increase in excitatory neural activity amid ongoing synaptic plasticity and homeostatic regulation leads to decreased strengths of synaptic connections and deterioration of neural receptive fields, which in turn lead to decreased network sensitivity to oriented features in visual stimuli.

These results suggest a potential causality between dysregulation of neuron firing and age-induced changes in brain physiology and functional performance, pointing Exploring The Gabor Methods way toward new directions for investigating the dynamics of aging in depth and making predictions for future experiments.

Citation: Talyansky S, Brinkman BAW Dysregulation of excitatory neural firing replicates physiological and functional changes in aging visual cortex. PLoS Comput Biol 17 1 : e This is an open access article distributed under the terms of the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The funders had no role in study design, data collection and analysis, decision to publish, or Exploring The Gabor Methods of the manuscript. Competing interests: The authors have declared that no competing interests exist.

While healthy aging, and in particular its impact on neurological performance, has been the focus of numerous experimental studies [ 1 — 8 ], there are comparatively few theoretical Tye computational studies that focus on normal aging.

1. Introduction

Only recently has theoretical and computational work on aging in non-pathological networks begun to emerge [ 3132 ]. This would help dissociate disease-related changes from those caused during normal aging, and thereby allow researchers to focus their attention on treating potential causes of the disease progression not directly related to normal aging. On the other hand, understanding how the healthy brain ages may enable us to treat declines in performance caused solely by aging, in both healthy subjects and those with neurological disorders or diseases.

In this work we seek to advance our understanding of potential mechanisms and consequences Exploring The Gabor Methods age-induced changes in physiology and functional performance in visual cortex. We do so by using a V1-like network model to qualitatively replicate experimentally-observed differences in the physiology and function of neurons in the visual cortex of young https://amazonia.fiocruz.br/scdp/essay/calculus-on-manifolds-amazon/comparing-the-united-nations-and-the-north.php old cats. In particular, we are motivated by experimental work that finds that senescent brain tissue in cat V1 shows increased spontaneous firing [ 34 ], decreased GABAergic inhibition [ 3536 ], and decreased selectivity to the orientation of grating stimuli [ 34 ].

Then, we can test the sensitivity of neurons to oriented grating stimuli at each Revolution of Hospitality Industry of our network to observe how neural selectivity changes as the networks become increasingly senescent—the strength of the orientation selectivity of the neurons will serve as our assessment of Exploring The Gabor Methods functional performance of the network in this model.

In order to model the experimental results we use E-I Net, a previously-developed spiking network model of mammalian V1 [ 37 ], as the basis for our study.

The network structure of E-I Net is learned by training the model on pixel images of natural scenes, mimicking the early developmental processes [ 38 ] in which neurons develop Gabor-like receptive fields measured experimentally in the visual cortex of mammals [ 39 ]. Similarly, the recurrent connections develop such that neurons with similar receptive fields effectively inhibit one another through intermediary inhibitory neurons. The standard E-I Net model thus Exploring The Gabor Methods the important V1-like features we seek in a network model, and we use it to represent the Ths, mature network.

Importantly, we show that the only modification we need to make to obtain a process that results in aged network phenotypes is a change to the training procedure that will promote increased firing activity within the network with age—the other physiological and functional performance changes emerge from this single change.

Although there may be other mechanisms that can replicate these experimental findings, our model makes several just click for source for other yet-to-be-observed changes in physiology and functional performance that can potentially be used to further test our model and the interpretation of our results.

This paper proceeds as follows: in Results we first give a brief overview of E-I Net and the modifications we made to the model to implement an aging-like phase of the training dynamics. We then present our findings on the physiological changes that occurred in our Mefhods during this aging phase—i. To gain a deeper understanding of how each set of our network parameters contributes to functional performance Metods during the aging process, we perform a number of numerical experiments.

In particular, i we study how orientation selectivity evolves when one or more parameters sets are frozen to their young values and ii we disambiguate Tne receptive field structure or receptive field magnitude contributes more to the declines in orientation selectivity. We begin by briefly reviewing E-I Net [ 37 ], the spiking network model of visual cortex we use in this work, and outlining how we modify this model to implement the aging-like process we use to replicate the experimental findings of [ 34Exploring The Gabor Methods ]. E-I Net comprises a population of recurrently-connected excitatory and inhibitory spiking neurons that receive external inputs Exploring The Gabor Methods by visual stimuli.

As shown schematically in Fig 1each of the N neurons receives visual input in the form of pixel images X from natural scenes; in this work, these scenes are taken from frames of movies in the CatCam database [ 4041 ].]