scholarly journals Sports Augmented Cognitive Benefits: An fMRI Study of Executive Function with Go/NoGo Task

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Qingguo Ding ◽  
Lina Huang ◽  
Jie Chen ◽  
Farzaneh Dehghani ◽  
Juan Du ◽  
...  
Keyword(s):  
Executive Function ◽  
Inhibitory Control ◽  
Exercise Group ◽  
Control Group ◽  
Response Patterns ◽  
Imaging Data ◽  
Fmri Study ◽  
Cognitive Benefits ◽  
Brain Imaging Data ◽  
The Brain

Exercise is believed to have significant cognitive benefits. Although an array of experimental paradigms have been employed to test the cognitive effects on exercising individuals, the mechanism as to how exercise induces cognitive benefits in the brain remains unclear. This study explores the effect of dynamic neural network processing with the classic Go/NoGo task with regular exercisers. We used functional magnetic resonance imaging to analyze the brain activation of areas involved in executive function, especially inhibitory control. Nineteen regular joggers and twenty-one subjects as a control group performed the task, and their brain imaging data were analyzed. The results showed that at the attentive visual period, the frontal and parietal areas, including the prefrontal cortex, putamen, thalamus, lingual, fusiform, and caudate, were significantly enhanced in positive activities than the control group. On the other hand, in the following inhibitory control processing period, almost the same areas of the brains of the exercise group have shown stronger negative activation in comparison to the control group. Such dynamic temporal response patterns indicate that sports augment cognitive benefits; i.e., regular jogging increases the brain’s visual attention and inhibitory control capacities.

scholarly journals Exercise Ameliorates Spinal Cord Injury by Changing DNA Methylation

Cells ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 143
Author(s):  
Ganchimeg Davaa ◽  
Jin Young Hong ◽  
Tae Uk Kim ◽  
Seong Jae Lee ◽  
Seo Young Kim ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Motor Cortex ◽  
Functional Recovery ◽  
Treadmill Exercise ◽  
Exercise Group ◽  
Control Group ◽  
Epigenetic Changes ◽  
Cord Injury ◽  
The Brain

Exercise training is a traditional method to maximize remaining function in patients with spinal cord injury (SCI), but the exact mechanism by which exercise promotes recovery after SCI has not been identified; whether exercise truly has a beneficial effect on SCI also remains unclear. Previously, we showed that epigenetic changes in the brain motor cortex occur after SCI and that a treatment leading to epigenetic modulation effectively promotes functional recovery after SCI. We aimed to determine how exercise induces functional improvement in rats subjected to SCI and whether epigenetic changes are engaged in the effects of exercise. A spinal cord contusion model was established in rats, which were then subjected to treadmill exercise for 12 weeks. We found that the size of the lesion cavity and the number of macrophages were decreased more in the exercise group than in the control group after 12 weeks of injury. Immunofluorescence and DNA dot blot analysis revealed that levels of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) in the brain motor cortex were increased after exercise. Accordingly, the expression of ten-eleven translocation (Tet) family members (Tet1, Tet2, and Tet3) in the brain motor cortex also elevated. However, no macrophage polarization was induced by exercise. Locomotor function, including Basso, Beattie, and Bresnahan (BBB) and ladder scores, also improved in the exercise group compared to the control group. We concluded that treadmill exercise facilitates functional recovery in rats with SCI, and mechanistically epigenetic changes in the brain motor cortex may contribute to exercise-induced improvements.

Supercomputing in the Study and Stimulation of the Brain

2021 ◽  
pp. 290-300
Author(s):  
Laura Dipietro ◽  
Seth Elkin-Frankston ◽  
Ciro Ramos-Estebanez ◽  
Timothy Wagner
Keyword(s):  
High Performance ◽  
Neurological Diseases ◽  
Data Sets ◽  
Imaging Data ◽  
Building Simulations ◽  
History Of ◽  
Brain Imaging Data ◽  
Evolution Of Science ◽  
Computational Systems ◽  
The Brain

The history of neuroscience has tracked with the evolution of science and technology. Today, neuroscience's trajectory is heavily dependent on computational systems and the availability of high-performance computing (HPC), which are becoming indispensable for building simulations of the brain, coping with high computational demands of analysis of brain imaging data sets, and developing treatments for neurological diseases. This chapter will briefly review the current and potential future use of supercomputers in neuroscience.

scholarly journals High-density EEG mobile brain/body imaging data recorded during a challenging auditory gait pacing task

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Johanna Wagner ◽  
Ramon Martinez-Cancino ◽  
Arnaud Delorme ◽  
Scott Makeig ◽  
Teodoro Solis-Escalante ◽  
...  
Keyword(s):  
Pressure Sensors ◽  
Step Length ◽  
High Density ◽  
Imaging Data ◽  
Joint Angles ◽  
Body Imaging ◽  
Cortical Dynamics ◽  
Brain Imaging Data ◽  
Auditory Cueing ◽  
The Brain

Abstract In this report we present a mobile brain/body imaging (MoBI) dataset that allows study of source-resolved cortical dynamics supporting coordinated gait movements in a rhythmic auditory cueing paradigm. Use of an auditory pacing stimulus stream has been recommended to identify deficits and treat gait impairments in neurologic populations. Here, the rhythmic cueing paradigm required healthy young participants to walk on a treadmill (constant speed) while attempting to maintain step synchrony with an auditory pacing stream and to adapt their step length and rate to unanticipated shifts in tempo of the pacing stimuli (e.g., sudden shifts to a faster or slower tempo). High-density electroencephalography (EEG, 108 channels), surface electromyography (EMG, bilateral tibialis anterior), pressure sensors on the heel (to register timing of heel strikes), and goniometers (knee, hip, and ankle joint angles) were concurrently recorded in 20 participants. The data is provided in the Brain Imaging Data Structure (BIDS) format to promote data sharing and reuse, and allow the inclusion of the data into fully automated data analysis workflows.

scholarly journals Integrating the Brain Imaging Data Structure (BIDS) standard into C-PAC

GigaScience ◽  
2016 ◽  
Vol 5 (suppl_1) ◽  
Author(s):  
Daniel Clark ◽  
Krzysztof J. Gorgolewski ◽  
R. Cameron Craddock
Keyword(s):  
Data Structure ◽  
Brain Imaging ◽  
Imaging Data ◽  
Brain Imaging Data ◽  
The Brain

Relationship Between Exercise and 18-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Imaging of Brain in the Elderly

2020 ◽  
Vol 10 (8) ◽  
pp. 1962-1966
Author(s):  
Pengfei Kang
Keyword(s):  
Vascular Occlusion ◽  
The Elderly ◽  
Exercise Group ◽  
Brain Diseases ◽  
Control Group ◽  
Computed Tomography Imaging ◽  
Positron Emission ◽  
Pet Scanning ◽  
Cerebral Vascular Occlusion ◽  
The Brain

CT were analyzed. The subjects were elderly people aged 55–75 who volunteered for brain 18F of the FDG CT and PET scanning. The elderly who maintained exercise were divided into exercise group and non-exercise group into control group. The images obtained by CT examination showed that the brain of the elderly who insisted on exercise showed a significant increase in glucose metabolism, which indicated that exercise had a preventive effect on brain diseases of the elderly, and reduced the risk of cerebral vascular occlusion and brain atrophy.

scholarly journals Common Data Elements, Scalable Data Management Infrastructure, and Analytics Workflows for Large-Scale Neuroimaging Studies

2021 ◽  
Vol 12 ◽  
Author(s):  
Rayus Kuplicki ◽  
James Touthang ◽  
Obada Al Zoubi ◽  
Ahmad Mayeli ◽  
Masaya Misaki ◽  
...  
Keyword(s):  
Data Management ◽  
Large Scale ◽  
Laboratory Data ◽  
Imaging Data ◽  
Common Data Elements ◽  
Level Data ◽  
Reproducible Analysis ◽  
Brain Imaging Data ◽  
Data Elements ◽  
The Brain

Neuroscience studies require considerable bioinformatic support and expertise. Numerous high-dimensional and multimodal datasets must be preprocessed and integrated to create robust and reproducible analysis pipelines. We describe a common data elements and scalable data management infrastructure that allows multiple analytics workflows to facilitate preprocessing, analysis and sharing of large-scale multi-level data. The process uses the Brain Imaging Data Structure (BIDS) format and supports MRI, fMRI, EEG, clinical, and laboratory data. The infrastructure provides support for other datasets such as Fitbit and flexibility for developers to customize the integration of new types of data. Exemplar results from 200+ participants and 11 different pipelines demonstrate the utility of the infrastructure.

scholarly journals The modular and integrative functional architecture of the human brain

2015 ◽  
Vol 112 (49) ◽  
pp. E6798-E6807 ◽  
Author(s):  
Maxwell A. Bertolero ◽  
B. T. Thomas Yeo ◽  
Mark D’Esposito
Keyword(s):  
Human Brain ◽  
Cognitive Functions ◽  
Topic Model ◽  
Brain Activity ◽  
Modular Function ◽  
Imaging Data ◽  
Functional Architecture ◽  
Brain Imaging Data ◽  
The Brain

Network-based analyses of brain imaging data consistently reveal distinct modules and connector nodes with diverse global connectivity across the modules. How discrete the functions of modules are, how dependent the computational load of each module is to the other modules’ processing, and what the precise role of connector nodes is for between-module communication remains underspecified. Here, we use a network model of the brain derived from resting-state functional MRI (rs-fMRI) data and investigate the modular functional architecture of the human brain by analyzing activity at different types of nodes in the network across 9,208 experiments of 77 cognitive tasks in the BrainMap database. Using an author–topic model of cognitive functions, we find a strong spatial correspondence between the cognitive functions and the network’s modules, suggesting that each module performs a discrete cognitive function. Crucially, activity at local nodes within the modules does not increase in tasks that require more cognitive functions, demonstrating the autonomy of modules’ functions. However, connector nodes do exhibit increased activity when more cognitive functions are engaged in a task. Moreover, connector nodes are located where brain activity is associated with many different cognitive functions. Connector nodes potentially play a role in between-module communication that maintains the modular function of the brain. Together, these findings provide a network account of the brain’s modular yet integrated implementation of cognitive functions.

scholarly journals Probing Brain Activation Patterns by Dissociating Semantics and Syntax in Sentences

2020 ◽  
Vol 34 (05) ◽  
pp. 9201-9208
Author(s):  
Shaonan Wang ◽  
Jiajun Zhang ◽  
Nan Lin ◽  
Chengqing Zong
Keyword(s):  
Brain Regions ◽  
Feature Representation ◽  
Semantic Feature ◽  
Imaging Data ◽  
Activation Patterns ◽  
Syntactic Feature ◽  
Syntactic Information ◽  
Brain Imaging Data ◽  
The Right ◽  
The Brain

The relation between semantics and syntax and where they are represented in the neural level has been extensively debated in neurosciences. Existing methods use manually designed stimuli to distinguish semantic and syntactic information in a sentence that may not generalize beyond the experimental setting. This paper proposes an alternative framework to study the brain representation of semantics and syntax. Specifically, we embed the highly-controlled stimuli as objective functions in learning sentence representations and propose a disentangled feature representation model (DFRM) to extract semantic and syntactic information in sentences. This model can generate one semantic and one syntactic vector for each sentence. Then we associate these disentangled feature vectors with brain imaging data to explore brain representation of semantics and syntax. Results have shown that semantic feature is represented more robustly than syntactic feature across the brain including the default-mode, frontoparietal, visual networks, etc.. The brain representations of semantics and syntax are largely overlapped, but there are brain regions only sensitive to one of them. For instance, several frontal and temporal regions are specific to the semantic feature; parts of the right superior frontal and right inferior parietal gyrus are specific to the syntactic feature.

scholarly journals The Amsterdam Open MRI Collection, a set of multimodal MRI datasets for individual difference analyses

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Lukas Snoek ◽  
Maite M. van der Miesen ◽  
Tinka Beemsterboer ◽  
Andries van der Leij ◽  
Annemarie Eigenhuis ◽  
...  
Keyword(s):  
Cognitive Conflict ◽  
Large Set ◽  
Imaging Data ◽  
Open Mri ◽  
Bold Mri ◽  
Multimodal Mri ◽  
Brain Imaging Data ◽  
And Control ◽  
The Brain ◽  
Healthy Participants

AbstractWe present the Amsterdam Open MRI Collection (AOMIC): three datasets with multimodal (3 T) MRI data including structural (T1-weighted), diffusion-weighted, and (resting-state and task-based) functional BOLD MRI data, as well as detailed demographics and psychometric variables from a large set of healthy participants (N = 928, N = 226, and N = 216). Notably, task-based fMRI was collected during various robust paradigms (targeting naturalistic vision, emotion perception, working memory, face perception, cognitive conflict and control, and response inhibition) for which extensively annotated event-files are available. For each dataset and data modality, we provide the data in both raw and preprocessed form (both compliant with the Brain Imaging Data Structure), which were subjected to extensive (automated and manual) quality control. All data is publicly available from the OpenNeuro data sharing platform.

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