Standard‐space atlas of the viscoelastic properties of the human brain

The exact shape of every human brain - including its micro- and macroscopic features - is as unique as a human fingerprint, resulting in inter-individual anatomical variability. In the past two decades, the understanding of this variability advanced dramatically not only at the level of sulcal/gyral patterns, anatomical features (e.g. cortical thickness, volume and shape) and extent of cytoarchitectonic areas defined at the microscopic level, but also in the anatomical and functional connectivity of the brain. The core concept within the field of brain mapping is the use of a standardized 3D coordinate frame for data analysis and reporting of findings from neuroimaging experiments. This simple construct allows brain researchers to combine (even structural or functional) data from many subjects to create group-averaged signals. Also, where the signal is robust enough to be detected in individuals, it allows for the exploration of inter-individual variance in the location of that signal. Spatial standardization requires two basic components: (i) the specification of the 3D standard coordinate space, and (ii) a mapping function that transforms a 3D brain image from “native” space to that standard space. The first component is usually expressed by the choice of a representative 3D MR image that serves as target (template or atlas). The native image is re-sampled to standard space under the mapping function that may have few or many degrees of freedom, depending upon the experimental design. The optimal choice of atlas template and mapping function depends upon considerations of age, gender, hemispheric asymmetry, anatomical correspondence, spatial normalization methodology and disease-specificity (1). In our studies we investigated some of these aspects, e.g. 1) how gender and normal aging influences brain morphology, 2) how normal hemispheric asymmetry plays a role in lateralized neurological diseases, such as cluster headache, 3) how progressive neurodegenerative disorders, such as Huntington’s disease affect the brain structure, or 4) how we can deal with inter-individual variability in case of neurosurgical interventions, such as thalamotomy in the therapy of medication resistant tremor.

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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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