Nonlinear and Cooperative Dynamics in the Human Brain: Evidence from Multimodal Neuroimaging

Neuroimaging stands to benefit from emerging ultrahigh-resolution 3D histological atlases of the human brain; the first of which is 'BigBrain'. Here, we review recent methodological advances for the integration of BigBrain with multi-modal neuroimaging and introduce a toolbox, 'BigBrainWarp', that combines these developments. The aim of BigBrainWarp is to simplify workflows and support the adoption of best practices. This is accomplished with a simple wrapper function that allows users to easily map data between BigBrain and standard MRI spaces. The function automatically pulls specialised transformation procedures, based on ongoing research from a wide collaborative network of researchers. Additionally, the toolbox improves accessibility of histological information through dissemination of ready-to-use cytoarchitectural features. Finally, we demonstrate the utility of BigBrainWarp with three tutorials and discuss the potential of the toolbox to support multi-scale investigations of brain organisation.

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Construction of a Multimodal Neuroimaging Data Fusion System and Evaluation of Mental Fatigue Using Nonlinear Analysis

Complexity ◽

10.1155/2021/8478868 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Rui Chen ◽

Zhenzhong Li ◽

Yi Lai

Keyword(s):

Fractal Dimension ◽

Data Fusion ◽

Human Brain ◽

Brain Function ◽

Fusion System ◽

Multimodal Neuroimaging ◽

Neuroimaging Data ◽

Time Accuracy ◽

The Brain ◽

Function Network

The purpose of this research is to explore the optimization and fusion application of multimodal neuroimaging technology and analyze the evaluation method of human brain fatigue based on multimodal neuroimaging technology. Based on electroencephalogram (EEG) and fMRI (functional magnetic resonance imaging), the four-dimensional consistency of local neural activities (FOCA) and local multimodal serial analysis (LMSA) are first introduced to fuse EEG and fMRI organically. Second, the eigenspace maximal information canonical correlation analysis (emiCCA) is introduced to construct the multimodal neuroimaging data fusion system. Finally, how the brain function network is constructed is introduced. Based on the binary and the weighted brain function networks, the relationship between the human brain fatigue and the brain function network is evaluated by calculating the fractal dimension. Results demonstrate that FOCA performs well in temporal and spatial consistency indexes, and the mean level and standard deviation in the case of temporal and spatial consistency are approximately 0.45. The effect of LMSA indexes is significantly better than generalized linear models (GLMs). Under different signal-to-noise ratios (SNRs), the regression coefficient based on LMSA is much larger than the GLM estimate; the corresponding significance level is p < 0.05 ; and the maximum value of the regression coefficient appears near 0.2. In the data fusion system, the time-space matching has good results under the time accuracy based on EEG and the space accuracy based on fMRI, with the time accuracy above 88% and the space accuracy above 89%. The fractal dimension analysis based on the brain function network reveals that the weighted brain function network is more sensitive to mental fatigue. The state of human brain fatigue will make the brain function network more complicated. The fractal dimension with more network edges is around 2.2, while the fractal dimension with fewer network edges is around 1.6. The proposed data analysis and fusion system have great application potential and propose a new idea for analyzing human brain fatigue and brain aging.

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Language processing is not a race against time

Behavioral and Brain Sciences ◽

10.1017/s0140525x15000692 ◽

2016 ◽

Vol 39 ◽

Cited By ~ 1

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.

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Structural and Chemical Studies of Pathological Fibers in Human Neurofibrillary Degeneration

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010012031x ◽

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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Toward a neuroscope: An application of high-performance computing for real-time evaluation of brain function using MRI

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100172346 ◽

1994 ◽

Vol 52 ◽

pp. 922-923

Author(s):

C. S. Potter ◽

C. D. Gregory ◽

H. D. Morris ◽

Z.-P. Liang ◽

P. C. Lauterbur

Keyword(s):

Human Brain ◽

Brain Function ◽

High Performance ◽

Complex Signal ◽

Time Step ◽

Brain Organization ◽

Cognitive Studies ◽

Positron Emission ◽

Imaging And Spectroscopy ◽

3D Anatomy

Over the past few years, several laboratories have demonstrated that changes in local neuronal activity associated with human brain function can be detected by magnetic resonance imaging and spectroscopy. Using these methods, the effects of sensory and motor stimulation have been observed and cognitive studies have begun. These new methods promise to make possible even more rapid and extensive studies of brain organization and responses than those now in use, such as positron emission tomography.Human brain studies are enormously complex. Signal changes on the order of a few percent must be detected against the background of the complex 3D anatomy of the human brain. Today, most functional MR experiments are performed using several 2D slice images acquired at each time step or stimulation condition of the experimental protocol. It is generally believed that true 3D experiments must be performed for many cognitive experiments. To provide adequate resolution, this requires that data must be acquired faster and/or more efficiently to support 3D functional analysis.

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