scholarly journals Correction to: A comparison of diffusion tractography techniques in simulating the generalized Ising model to predict the intrinsic activity of the brain

Author(s):  
Pubuditha M. Abeyasinghe ◽  
Marco Aiello ◽  
Carlo Cavaliere ◽  
Adrian M. Owen ◽  
Andrea Soddu
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Anton Lindberg ◽  
Ryosuke Arakawa ◽  
Tsuyoshi Nogami ◽  
Sangram Nag ◽  
Magnus Schou ◽  
...  

Abstract Background Over the last decade, a few radioligands have been developed for PET imaging of brain 5-HT1B receptors. The 5-HT1B receptor is a G-protein-coupled receptor (GPCR) that exists in two different agonist affinity states. An agonist ligand is expected to be more sensitive towards competition from another agonist, such as endogenous 5-HT, than an antagonist ligand. It is of interest to know whether the intrinsic activity of a PET radioligand for the 5-HT1B receptor impacts on its ability to detect changes in endogenous synaptic 5-HT density. Three high-affinity 11C-labeled 5-HT1B PET radioligands with differing intrinsic activity were applied to PET measurements in cynomolgus monkey to evaluate their sensitivity to be displaced within the brain by endogenous 5-HT. For these experiments, fenfluramine was pre-administered at two different doses (1.0 and 5.0 mg/kg, i.v.) to induce synaptic 5-HT release. Results A dose-dependent response to fenfluramine was detected for all three radioligands. At the highest dose of fenfluramine (5.0 mg/kg, i.v.), reductions in specific binding in the occipital cortex increased with radioligand agonist efficacy, reaching 61% for [11C]3. The most antagonistic radioligand showed the lowest reduction in specific binding. Conclusions Three 5-HT1B PET radioligands were identified with differing intrinsic activity that could be used in imaging high- and low-affinity states of 5-HT1B receptors using PET. From this limited study, radioligand sensitivity to endogenous 5-HT appears to depend on agonist efficacy. More extensive studies are required to substantiate this suggestion.


2015 ◽  
Vol 370 (1668) ◽  
pp. 20140172 ◽  
Author(s):  
Marcus E. Raichle

Traditionally studies of brain function have focused on task-evoked responses. By their very nature such experiments tacitly encourage a reflexive view of brain function. While such an approach has been remarkably productive at all levels of neuroscience, it ignores the alternative possibility that brain functions are mainly intrinsic and ongoing, involving information processing for interpreting, responding to and predicting environmental demands. I suggest that the latter view best captures the essence of brain function, a position that accords well with the allocation of the brain's energy resources, its limited access to sensory information and a dynamic, intrinsic functional organization. The nature of this intrinsic activity, which exhibits a surprising level of organization with dimensions of both space and time, is revealed in the ongoing activity of the brain and its metabolism. As we look to the future, understanding the nature of this intrinsic activity will require integrating knowledge from cognitive and systems neuroscience with cellular and molecular neuroscience where ion channels, receptors, components of signal transduction and metabolic pathways are all in a constant state of flux. The reward for doing so will be a much better understanding of human behaviour in health and disease.


1982 ◽  
Vol 25 (9) ◽  
pp. 5875-5881 ◽  
Author(s):  
J. Naudts ◽  
S. D. Mahant

2020 ◽  
Vol 9 (5) ◽  
pp. 1342 ◽  
Author(s):  
Pubuditha M. Abeyasinghe ◽  
Marco Aiello ◽  
Emily S. Nichols ◽  
Carlo Cavaliere ◽  
Salvatore Fiorenza ◽  
...  

The data from patients with severe brain injuries show complex brain functions. Due to the difficulties associated with these complex data, computational modeling is an especially useful tool to examine the structure–function relationship in these populations. By using computational modeling for patients with a disorder of consciousness (DoC), not only we can understand the changes of information transfer, but we also can test changes to different states of consciousness by hypothetically changing the anatomical structure. The generalized Ising model (GIM), which specializes in using structural connectivity to simulate functional connectivity, has been proven to effectively capture the relationship between anatomical structures and the spontaneous fluctuations of healthy controls (HCs). In the present study we implemented the GIM in 25 HCs as well as in 13 DoC patients diagnosed at three different states of consciousness. Simulated data were analyzed and the criticality and dimensionality were calculated for both groups; together, those values capture the level of information transfer in the brain. Ratifying previous studies, criticality was observed in simulations of HCs. We were also able to observe criticality for DoC patients, concluding that the GIM is generalizable for DoC patients. Furthermore, dimensionality increased for the DoC group as compared to healthy controls, and could distinguish different diagnostic groups of DoC patients.


2020 ◽  
Vol 131 (3) ◽  
pp. 447-455
Author(s):  
E. S. Tsuvarev ◽  
F. A. Kassan-Ogly ◽  
A. I. Proshkin

2018 ◽  
Vol 8 (7) ◽  
pp. 444-455 ◽  
Author(s):  
Pubuditha M. Abeyasinghe ◽  
Demetrius Ribeiro de Paula ◽  
Sina Khajehabdollahi ◽  
Sree Ram Valluri ◽  
Adrian M. Owen ◽  
...  

2004 ◽  
Vol 18 (26n27) ◽  
pp. 1347-1366 ◽  
Author(s):  
J. M. CASADO ◽  
B. IBARZ ◽  
M. A. F. SANJUÁN

The brain can be described as a very complex dynamical system whose autonomous, intrinsic activity is modulated by a great variety of external inputs. In the last decade, the simulation of this activity by using networks of neurons has led to the development of new approaches to describe the processing of information by the nervous system. In this review paper we focus on winnerless competition, a new concept allowing the analysis of the emergent behavior associated with collective synchronization, multi-stability and adaptation — properties which seem to be at the basis of brain performance. The relationship between winnerless competition and the concept of chaotic itinerancy is stressed by pointing out their common association with the formation of complex heteroclinic orbits in the high-dimensional phase space associated with the dynamics of complex neuronal systems. The potentialities of networks of coupled map neurons to the study of activation and synchronization regimes in neural systems are suggested by means of different simulations showing a great variety of dynamical phenomena.


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