Firing Rate Homeostasis for Dynamic Neural Field Formation

Gläser, Claudius; Joublin, Frank

doi:10.1109/tamd.2011.2138705

Cited by 8 publications

(4 citation statements)

References 52 publications

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“…In comparison to other topological algorithms [67]–[71], the synaptic weights of each neuron inform about the vicinity to other neurons based on their rank order: that is, neurons with similar rank codes are spatially near. First, we study how the sensory inputs shape the sensory mapping and how multimodal integration occurs between the two maps within an intermediate layer that learns information from both.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Minimal Newborn's Intersubjective Mind: The Visuotopic-Somatotopic Alignment Hypothesis in the Superior Colliculus

et al. 2013

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The question whether newborns possess inborn social skills is a long debate in developmental psychology. Fetal behavioral and anatomical observations show evidences for the control of eye movements and facial behaviors during the third trimester of pregnancy whereas specific sub-cortical areas, like the superior colliculus (SC) and the striatum appear to be functionally mature to support these behaviors. These observations suggest that the newborn is potentially mature for developing minimal social skills. In this manuscript, we propose that the mechanism of sensory alignment observed in SC is particularly important for enabling the social skills observed at birth such as facial preference and facial mimicry. In a computational simulation of the maturing superior colliculus connected to a simulated facial tissue of a fetus, we model how the incoming tactile information is used to direct visual attention toward faces. We suggest that the unisensory superficial visual layer (eye-centered) and the deep somatopic layer (face-centered) in SC are combined into an intermediate layer for visuo-tactile integration and that multimodal alignment in this third layer allows newborns to have a sensitivity to configuration of eyes and mouth. We show that the visual and tactile maps align through a Hebbian learning stage and and strengthen their synaptic links from each other into the intermediate layer. It results that the global network produces some emergent properties such as sensitivity toward the spatial configuration of face-like patterns and the detection of eyes and mouth movement.

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Section: Introductionmentioning

confidence: 99%

Modeling the Minimal Newborn's Intersubjective Mind: The Visuotopic-Somatotopic Alignment Hypothesis in the Superior Colliculus

et al. 2013

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“…We tested two models against our behavioral data: one biologically inspired model (in line with with the BDNF principles discussed by Glaser and Joublin, 2011) capturing cellular homeostatic principles, and the same model but with the cellular homeostatic term removed. Each was simulated in Matlab using the exact order and content of trials and color values seen by each of the 30 participants in turn.…”

Section: Modelmentioning

confidence: 99%

“…The cellular mechanism would need to toggle the adaptation of a neural unit between "labile" and "stable" dispositions toward changing connection strengths (Bienenstock, Cooper, & Munro, 1982). One suggested candidate for this process is brain-derived neurotrophic factor (BDNF) (Glaser & Joublin, 2011). Using Calcium levels as a proxy for the instantaneous levels of change at a synapse, neural units coding for changes in the level of BDNF can dynamically alter the underlying synaptic excitation/inhibition levels of cells.…”

Section: Introductionmentioning

confidence: 99%

A modeling link between cognitive and biological homeostasis

Tupper,

Barnes,

Blair

2023

Preprint

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The problem of stability has long been a limiting factor in developing neural networks that can grow in size and complexity. Outside of particular, narrow parameter ranges, changes in activity can easily result in total loss of control. Human cognition must have reliable means of acting to stay within the stable ranges of sensitivity and activation. Learning is one such mechanism, and population dynamics are another. Here, we focus on another, often overlooked stability mechanism: cellular homeostasis through metabolism dynamics. We ran a visual change detection experiment designed to strain networkstability while minimizing any learnable patterns. We fit thedata using models with and without cellular energy levels as a factor, finding that the model influenced by its past history of energy use was a closer fit to the human data.

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“…It is a common method for researchers to analyze and study brain function qualitatively and quantitatively by using mathematical statistical model to model neuron impulse signals of organisms. Characterizing the characteristics of neuronal impulse signals through the mathematical characteristics of the model and verifying the reasonable assumptions made by these characteristics can help researchers deepen their cognition of the functional connections between different types of neurons in the brain and reveal the functional connections among neurons [2,3,4].Exploring the hidden information inside the neuronal pulse signals [5,6,7,8] can also build the corresponding neural prosthesis according to the pulse signal issuing characteristics of specific brain regions [9], which can be used to make up for the functional loss or abnormality of specific brain regions caused by brain damage and other reasons. With the continuous development of microelectrode array technology and the continuous improvement in the spatial and temporal accuracy of the original data of neuron impulse signals collected by related instruments, it has become very common to use data to drive the construction of statistical models, so as to assist researchers to complete the exploration of functional connections between neurons in different brain regions.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Analysis of Spike-Train Based on Poisson-GML

Yang

Fan

2022

J. Phys.: Conf. Ser.

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Mathematical modeling is of great significance to the study of brain function. In this paper, an analysis method based on Poisson’s general linear model is adopted to model the brain impulse sequence. First, the ideas of Hodegkin-Hulex model, STA and Poisson’s general linear model are introduced. Secondly, the implementation of the general linear model is introduced. Finally, Poisson GLM Fit Spike-train is simulated and compared with Linear Gaussian-GLM. The AIC tradeoff estimation model fits well. The superiority of Poisson GLM Fit Spike-Train is demonstrated

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Firing Rate Homeostasis for Dynamic Neural Field Formation

Cited by 8 publications

References 52 publications

Modeling the Minimal Newborn's Intersubjective Mind: The Visuotopic-Somatotopic Alignment Hypothesis in the Superior Colliculus

Modeling the Minimal Newborn's Intersubjective Mind: The Visuotopic-Somatotopic Alignment Hypothesis in the Superior Colliculus

A modeling link between cognitive and biological homeostasis

Modeling and Analysis of Spike-Train Based on Poisson-GML

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