Reconstruction of digit images from human brain fMRI activity through connectivity informed Bayesian networks

2016 ◽  
Vol 257 ◽  
pp. 159-167 ◽  
Author(s):  
Elahe’ Yargholi ◽  
Gholam-Ali Hossein-Zadeh
Keyword(s):  
Human Brain ◽  
Bayesian Networks ◽  
Brain Fmri

A Brief History of Arguments in Resting state Functional Magnetic Resonance Imaging Research

2018 ◽  
pp. 1-4
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Human Brain ◽  
Neural Activity ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Brain Functions ◽  
Imaging Research ◽  
Brain Fmri

All scientific research needs to go through years of arguments and debates to polish itself, including research of functional magnetic resonance imaging (fMRI) in human brain. fMRI is one of the state-of-the-art noninvasive techniques to investigate brain functions of human and animals. Since it is difficult and hardly practical to record vivo neural activity from human brain, fMRI provides an substitute measurement of neural activity which is based on the haemodynamic response in blood flow during the neural activity, also known as bloodoxygen-level dependent (BOLD) signal.

scholarly journals Learning massive interpretable gene regulatory networks of the human brain by merging Bayesian Networks

2020 ◽  
Author(s):  
Nikolas Bernaola ◽  
Mario Michiels ◽  
Pedro Larrañaga ◽  
Concha Bielza
Keyword(s):  
Human Brain ◽  
Bayesian Networks ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Search Algorithm ◽  
Experimental Tests ◽  
Brain Structures ◽  
Brain Atlas ◽  
Gene Regulatory ◽  
Using Data

AbstractWe present FGES-Merge, a new method for learning the structure of gene regulatory networks via merging locally learned Bayesian networks, based on the fast greedy equivalent search algorithm. The method is competitive with the state of the art in terms of the recall of the true structure while also improving upon it in terms of speed, scaling up to the tens of thousands of variables and being able to use empirical knowledge about the topological structure of gene regulatory networks. We apply this method to learning the gene regulatory network for the full human genome using data from samples of different brain structures (from the Allen Human Brain Atlas). Our goal is to develop a Bayesian network model that predicts interactions between genes in a way that is clear to experts, following the current trends in interpretable artificial intelligence. To achieve this, we also present a new open-access visualization tool that facilitates the exploration of massive networks and can aid in finding nodes of interest for experimental tests.

scholarly journals Emergence of symmetry selectivity in the visual areas of the human brain: fMRI responses to symmetry presented in both frontoparallel and slanted planes

2018 ◽  
Vol 39 (10) ◽  
pp. 3813-3826 ◽  
Author(s):  
Bruce D. Keefe ◽  
André D. Gouws ◽  
Aislin A. Sheldon ◽  
Richard J. W. Vernon ◽  
Samuel J. D. Lawrence ◽  
...  
Keyword(s):  
Human Brain ◽  
Visual Areas ◽  
Brain Fmri

A Brief History of Arguments in Resting state Functional Magnetic Resonance Imaging Research

2018 ◽  
pp. 1-4
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Human Brain ◽  
Neural Activity ◽  
Blood Oxygen Level Dependent ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Brain Functions ◽  
Brain Fmri

All scientific research needs to go through years of arguments and debates to polish itself, including research of functional magnetic resonance imaging (fMRI) in human brain. fMRI is one of the state-of-the-art non- invasive techniques to investigate brain functions of human and animals. Since it is difficult and hardly practical to record vivo neural activity from human brain, fMRI provides an substitute measurement of neural activity which is based on the haemodynamic response in blood flow during the neural activity, also known as blood- oxygen-level dependent (BOLD) signal.

scholarly journals Disentangling dimensions of animacy in human brain and behaviour

2021 ◽  
Author(s):  
Kamila M Jozwik ◽  
Elias Najarro ◽  
Jasper JF van den Bosch ◽  
Ian Charest ◽  
Nikolaus Kriegeskorte ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Human Brain ◽  
The Other ◽  
Five Dimensions ◽  
Behavioural Responses ◽  
Visual Areas ◽  
Differential Pattern ◽  
Similarity Judgments ◽  
Explained Variance ◽  
Brain Fmri

The perception of animate things is of great behavioural importance to humans. Despite the prominence of the distinct brain and behavioural responses to animate and inanimate things, however, it remains unclear which of several commonly entangled properties underlie these observations. Here, we investigate the importance of five dimensions of animacy: being alive, looking like an animal, having agency, having mobility, and being unpredictable in brain (fMRI, EEG) and behaviour (property and similarity judgments) of 19 subjects using a stimulus set of 128 images that disentangles the five dimensions (optimized by a genetic algorithm). Our results reveal a differential pattern across brain and behaviour. The living/non-living distinction (being alive) was prominent in judgments, but despite its prominence in neuroscience literature, did not explain variance in brain representations. The other dimensions of animacy explained variance in both brain and behaviour. The having agency dimension explained more variance in higher-level visual areas, consistent with higher cognitive contributions. The being unpredictable dimension instead captured representations in both lower and higher-level visual cortex, possibly because unpredictable things require attention. Animacy is multidimensional and our results show that distinct dimensions are differentially represented in human brain and behaviour.

Language processing is not a race against time

2016 ◽  
Vol 39 ◽  
Author(s):  
Giosuè Baggio ◽  
Carmelo M. Vicario
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Language Processing ◽  
Cognitive Functions ◽  
Memory Systems ◽  
Language System ◽  
Moderating Factors

AbstractWe agree with Christiansen & Chater (C&C) that language processing and acquisition are tightly constrained by the limits of sensory and memory systems. However, the human brain supports a range of cognitive functions that mitigate the effects of information processing bottlenecks. The language system is partly organised around these moderating factors, not just around restrictions on storage and computation.

Structural and Chemical Studies of Pathological Fibers in Human Neurofibrillary Degeneration

1985 ◽  
Vol 43 ◽  
pp. 726-729
Author(s):  
K.S. Kosik ◽  
L.K. Duffy ◽  
S. Bakalis ◽  
C. Abraham ◽  
D.J. Selkoe
Keyword(s):  
Monoclonal Antibodies ◽  
Alzheimer Disease ◽  
Human Brain ◽  
Neurofibrillary Tangles ◽  
Morphological Analysis ◽  
High Specificity ◽  
Cytoskeletal Proteins ◽  
Neuritic Plaque ◽  
Protein Chemistry ◽  
Chemical Studies

The major structural lesions of the human brain during aging and in Alzheimer disease (AD) are the neurofibrillary tangles (NFT) and the senile (neuritic) plaque. Although these fibrous alterations have been recognized by light microscopists for almost a century, detailed biochemical and morphological analysis of the lesions has been undertaken only recently. Because the intraneuronal deposits in the NFT and the plaque neurites and the extraneuronal amyloid cores of the plaques have a filamentous ultrastructure, the neuronal cytoskeleton has played a prominent role in most pathogenetic hypotheses.The approach of our laboratory toward elucidating the origin of plaques and tangles in AD has been two-fold: the use of analytical protein chemistry to purify and then characterize the pathological fibers comprising the tangles and plaques, and the use of certain monoclonal antibodies to neuronal cytoskeletal proteins that, despite high specificity, cross-react with NFT and thus implicate epitopes of these proteins as constituents of the tangles.

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