P.212 Providing support for the null hypothesis in functional magnetic resonance imaging: testing group-level Bayesian inference

Masharipov, Ruslan; Kireev, Maxim; Korotkov, Alexander; Медведев, С. В.

doi:10.1016/j.euroneuro.2020.09.159

Cited by 1 publication

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A practically significant effect is identified using the effect size threshold γ. If an effect falls within the range [-γ; γ] (region of practical equivalence (ROPE)) with a probability higher than 95%, the null hypothesis that the effect is absent is accepted [9,22], suggesting practical equivalence of local neuronal activity for the samples compared. In other words, this makes it possible to consider the null hypothesis of mean equality to be significant.…”

Section: Methodsmentioning

confidence: 99%

“…New approaches have recently been developed to overcome this limitation. When testing a new approach that is based on Bayesian statistics and makes it possible to accept the null hypothesis of the absence of practical difference between group variables in analyzing the fMRI data, preliminary findings have indicated that brain regions that are candidate hidden nodes are possible to select [9]. This opens new experimental opportunities in studying the functional role of hidden nodes.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Functional Role of Hidden Nodes of Brain Systems Responsible for Visual Identification and Categorization

et al. 2021

View full text Add to dashboard Cite

Inconsistent data on local activity and distant interactions of individual elements in brain systems is still an unsolved problem in studying systemic activity of the human brain. A phenomenon of hidden nodes has recently been discovered in the field; i.e., several brain structures can be involved in their function exclusively via changes in distant functional connections, but without a detectable change in energy consumption. A study of hidden nodes was continued using the fMRI data obtained in conditions of image identification and categorization. A means to localize the hidden nodes was proposed, and methods of the graph theory were used to verify the critical role of hidden nodes in systemic activity of the brain. It was found additionally that different types of hidden nodes may exist to perform different functions in the configuration of brain systemic activity.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%