scholarly journals Mapping Brain Anatomical Connectivity Using Diffusion Magnetic Resonance Imaging: Structural connectivity of the human brain

2016 ◽  
Vol 33 (3) ◽  
pp. 36-51 ◽  
Author(s):  
Junning Li ◽  
Yonggang Shi ◽  
Arthur W. Toga
2020 ◽  
Vol 117 (17) ◽  
pp. 9566-9576 ◽  
Author(s):  
Morten L. Kringelbach ◽  
Josephine Cruzat ◽  
Joana Cabral ◽  
Gitte Moos Knudsen ◽  
Robin Carhart-Harris ◽  
...  

Remarkable progress has come from whole-brain models linking anatomy and function. Paradoxically, it is not clear how a neuronal dynamical system running in the fixed human anatomical connectome can give rise to the rich changes in the functional repertoire associated with human brain function, which is impossible to explain through long-term plasticity. Neuromodulation evolved to allow for such flexibility by dynamically updating the effectivity of the fixed anatomical connectivity. Here, we introduce a theoretical framework modeling the dynamical mutual coupling between the neuronal and neurotransmitter systems. We demonstrate that this framework is crucial to advance our understanding of whole-brain dynamics by bidirectional coupling of the two systems through combining multimodal neuroimaging data (diffusion magnetic resonance imaging [dMRI], functional magnetic resonance imaging [fMRI], and positron electron tomography [PET]) to explain the functional effects of specific serotoninergic receptor (5-HT2AR) stimulation with psilocybin in healthy humans. This advance provides an understanding of why psilocybin is showing considerable promise as a therapeutic intervention for neuropsychiatric disorders including depression, anxiety, and addiction. Overall, these insights demonstrate that the whole-brain mutual coupling between the neuronal and the neurotransmission systems is essential for understanding the remarkable flexibility of human brain function despite having to rely on fixed anatomical connectivity.


2016 ◽  
Vol 37 (6) ◽  
pp. 2210-2222 ◽  
Author(s):  
Nico Papinutto ◽  
Sebastiano Galantucci ◽  
Maria Luisa Mandelli ◽  
Benno Gesierich ◽  
Jorge Jovicich ◽  
...  

2012 ◽  
Vol 11 (04) ◽  
pp. 1250032 ◽  
Author(s):  
P. KATSALOULIS ◽  
J. HIZANIDIS ◽  
D. A. VERGANELAKIS ◽  
A. PROVATA

Diffusion Magnetic Resonance Imaging (dMRI) is a novel technique that mirrors the complex architecture of the neuron axons fiber networks in the human brain. Based on the dMRI scans, fractal dimensions (Box Counting and Multifractal Dimensions) are used to quantify the complexity of the neuron axons networks. The values of the fractal dimensions are calculated as a function of the intensity threshold τ in an effort to remove the effects of stochastic noise, always present in the molecular diffusion of water in the brain. It is shown that intermediate values of the noise threshold τ are better for estimating the complexity of the neuron network architecture, because for small τ the presence of stochastic noise often masks the underlying structure, while for τ > 0.6 important parts of the axon network structure are ignored. Calculations of the multifractal dimensions in healthy brains as a function of τ, give consistent scaling results in the medium intensity thresholds, where the neuron axons activity is better discerned. In these intermediate τ scales, deviations are recorded in the multifractal spectra of pathological brains, which indicate damaged network architectures.


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