The study of correlation and spectral characteristics of human brain activity while performing cognitive tasks

Author(s):  
Valentin Yunusov ◽  
Sergey Demin ◽  
Tatyana Panferova
2021 ◽  
Vol 11 ◽  
Author(s):  
Albert Batalla ◽  
Julian Bos ◽  
Amber Postma ◽  
Matthijs G. Bossong

Background: Accumulating evidence suggests that the non-intoxicating cannabinoid compound cannabidiol (CBD) may have antipsychotic and anxiolytic properties, and thus may be a promising new agent in the treatment of psychotic and anxiety disorders. However, the neurobiological substrates underlying the potential therapeutic effects of CBD are still unclear. The aim of this systematic review is to provide a detailed and up-to-date systematic literature overview of neuroimaging studies that investigated the acute impact of CBD on human brain function.Methods: Papers published until May 2020 were included from PubMed following a comprehensive search strategy and pre-determined set of criteria for article selection. We included studies that examined the effects of CBD on brain function of healthy volunteers and individuals diagnosed with a psychiatric disorder, comprising both the effects of CBD alone as well as in direct comparison to those induced by ∆9-tetrahydrocannabinol (THC), the main psychoactive component of Cannabis.Results: One-ninety four studies were identified, of which 17 met inclusion criteria. All studies investigated the acute effects of CBD on brain function during resting state or in the context of cognitive tasks. In healthy volunteers, acute CBD enhanced fronto-striatal resting state connectivity, both compared to placebo and THC. Furthermore, CBD modulated brain activity and had opposite effects when compared to THC following task-specific patterns during various cognitive paradigms, such as emotional processing (fronto-temporal), verbal memory (fronto-striatal), response inhibition (fronto-limbic-striatal), and auditory/visual processing (temporo-occipital). In individuals at clinical high risk for psychosis and patients with established psychosis, acute CBD showed intermediate brain activity compared to placebo and healthy controls during cognitive task performance. CBD modulated resting limbic activity in subjects with anxiety and metabolite levels in patients with autism spectrum disorders.Conclusion: Neuroimaging studies have shown that acute CBD induces significant alterations in brain activity and connectivity patterns during resting state and performance of cognitive tasks in both healthy volunteers and patients with a psychiatric disorder. This included modulation of functional networks relevant for psychiatric disorders, possibly reflecting CBD’s therapeutic effects. Future studies should consider replication of findings and enlarge the inclusion of psychiatric patients, combining longer-term CBD treatment with neuroimaging assessments.


2017 ◽  
Vol 47 (4) ◽  
pp. 474-483
Author(s):  
L. B. Shestopalova ◽  
E. A. Petropavlovskaya ◽  
N. I. Nikitin ◽  
S. F. Vaitulevich

2019 ◽  
Vol 9 (22) ◽  
pp. 4749
Author(s):  
Lingyun Jiang ◽  
Kai Qiao ◽  
Linyuan Wang ◽  
Chi Zhang ◽  
Jian Chen ◽  
...  

Decoding human brain activities, especially reconstructing human visual stimuli via functional magnetic resonance imaging (fMRI), has gained increasing attention in recent years. However, the high dimensionality and small quantity of fMRI data impose restrictions on satisfactory reconstruction, especially for the reconstruction method with deep learning requiring huge amounts of labelled samples. When compared with the deep learning method, humans can recognize a new image because our human visual system is naturally capable of extracting features from any object and comparing them. Inspired by this visual mechanism, we introduced the mechanism of comparison into deep learning method to realize better visual reconstruction by making full use of each sample and the relationship of the sample pair by learning to compare. In this way, we proposed a Siamese reconstruction network (SRN) method. By using the SRN, we improved upon the satisfying results on two fMRI recording datasets, providing 72.5% accuracy on the digit dataset and 44.6% accuracy on the character dataset. Essentially, this manner can increase the training data about from n samples to 2n sample pairs, which takes full advantage of the limited quantity of training samples. The SRN learns to converge sample pairs of the same class or disperse sample pairs of different class in feature space.


Science ◽  
2020 ◽  
Vol 367 (6482) ◽  
pp. 1086.8-1087
Author(s):  
Peter Stern
Keyword(s):  

1988 ◽  
Vol 35 (11) ◽  
pp. 960-966 ◽  
Author(s):  
J.C. de Munck ◽  
B.W. van Dijk ◽  
H. Spekreijse
Keyword(s):  

2006 ◽  
Vol 96 (25) ◽  
Author(s):  
Itai Doron ◽  
Eyal Hulata ◽  
Itay Baruchi ◽  
Vernon L. Towle ◽  
Eshel Ben-Jacob

NeuroImage ◽  
2000 ◽  
Vol 11 (5) ◽  
pp. 359-369 ◽  
Author(s):  
Armin Fuchs ◽  
Viktor K. Jirsa ◽  
J.A.Scott Kelso

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