scholarly journals Analysis of task-based functional MRI data preprocessed with fMRIPrep

2019 ◽  
Author(s):  
Oscar Esteban ◽  
Rastko Ciric ◽  
Karolina Finc ◽  
Ross Blair ◽  
Christopher J. Markiewicz ◽  
...  
Keyword(s):  
Ad Hoc ◽  
Brain Activity ◽  
Imaging Data ◽  
Modeling And Analysis ◽  
Manual Intervention ◽  
Standard Tool ◽  
History Of ◽  
Brain Imaging Data ◽  
Many Sources ◽  
The Brain

Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study. This approach is time-consuming, error-prone, and unsuitable for combining datasets from many sources. Here we showcase fMRIPrep (http://fmriprep.org), a robust tool to prepare human fMRI data for statistical analysis. This software instrument addresses the reproducibility concerns of the established protocols for fMRI preprocessing. By leveraging the Brain Imaging Data Structure (BIDS) to standardize both the input datasets —MRI data as stored by the scanner— and the outputs —data ready for modeling and analysis—, fMRIPrep is capable of preprocessing a diversity of datasets without manual intervention. In support of the growing popularity of fMRIPrep, this protocol describes how to integrate the tool in a task-based fMRI investigation workflow.

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 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 The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data

2020 ◽  
Author(s):  
Elise Bannier ◽  
Gareth Barker ◽  
Valentina Borghesani ◽  
Nils Broeckx ◽  
Patricia Clement ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Modern Science ◽  
Imaging Data ◽  
General Data Protection Regulation ◽  
Data User ◽  
History Of ◽  
General Data ◽  
Brain Imaging Data ◽  
The Brain ◽  
The Eu

Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavour is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants’ privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU General Data Protection Regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere.

scholarly journals MEG-BIDS: an extension to the Brain Imaging Data Structure for magnetoencephalography

2017 ◽  
Author(s):  
Guiomar Niso ◽  
Krzysztof J. Gorgolewski ◽  
Elizabeth Bock ◽  
Teon L. Brooks ◽  
Guillaume Flandin ◽  
...  
Keyword(s):  
Data Structure ◽  
Brain Imaging ◽  
Brain Activity ◽  
Large Data ◽  
Imaging Data ◽  
Source Imaging ◽  
Standard Data ◽  
Magnetic Resonance Imaging Mri ◽  
Brain Imaging Data ◽  
The Brain

AbstractWe present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG provides direct measurement of brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS has provided a solution to structure the organization of magnetic resonance imaging (MRI) data, which nature and acquisition parameters are different. Despite the lack of standard data format for MEG, MEG-BIDS is a principled solution to store, organize and share the typically-large data volumes produced. It builds on BIDS for MRI, and therefore readily yields a multimodal data organization by construction. This is particularly valuable for the anatomical and functional registration of MEG source imaging with MRI. With MEG-BIDS and a growing range of software adopting the standard, the MEG community has a solution to minimize curation overheads, reduce data handling errors and optimize usage of computational resources for analytics. The standard also includes well-defined metadata, to facilitate future data harmonization and sharing efforts.

scholarly journals BIDSonym - a BIDSapp for the pseudo-anonymization of neuroimaging datasets

2021 ◽  
Author(s):  
Peer Herholz ◽  
Rita M. Ludwig ◽  
Jean-Baptiste Poline
Keyword(s):  
Data Structure ◽  
Brain Imaging ◽  
Data Sharing ◽  
Sensitive Information ◽  
Imaging Data ◽  
Manual Intervention ◽  
Neuroimaging Data ◽  
Brain Imaging Data ◽  
The Brain ◽  
Infor Mation

The amount of neuroimaging data being shared increased exponentially in recent years. While thisdevelopment introduces prominent advantages concerning open, reproducible and sustainable neu-roimaging, the process of data sharing must ensure the privacy of participant data. A requirement fromboth, Ethics Review Boards and data sharing resources, datasets need to be (pseudo-) anonymized priorto sharing in order to limit participant re-identification. Depending on the dataset at hand, this processcan however become cumbersome and prone to errors. Here we introduce BIDSonym, a tool for auto-mated pseudo-anonymization of neuroimaging datasets. BIDSonym supports multiple de-identificationprocedures and operates on neuroimaging, as well as metadata files. In addition, all metadata infor-mation present in the respective files is gathered and evaluated. Its outputs furthermore allow usersto conduct a more in-depth assessment of potentially sensitive information present in a given dataset.Through its workflow and utilization of the Brain Imaging Data Structure (BIDS), BIDSonym’s appli-cation is reproducible, requires no manual intervention and is agnostic to idiosyncrasies of small andlarge scale datasets.

Cannabidiol Has a Unique Effect on Global Brain Activity: A Pharmacological, Functional MRI Study in Awake Mice 

2021 ◽  
Author(s):  
Aymen Sadaka ◽  
Ana Ozuna ◽  
Richard Ortiz ◽  
Praveen Kulkarni ◽  
Clare Johnson ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Brain Activity ◽  
Stress Disorders ◽  
Functional Coupling ◽  
Specific Information ◽  
Imaging Data ◽  
Post Traumatic Stress ◽  
Brain Areas ◽  
Dose Dependent ◽  
The Brain

Abstract Background: The phytocannabinoid cannabidiol (CBD) is a potential treatment for post-traumatic stress disorders. How does CBD interact with the brain to alter behavior? We hypothesized that CBD would produce a dose-dependent reduction in brain activity and functional coupling in neural circuitry associated with fear and defense. Methods: During the scanning session awake mice were given vehicle or CBD (3, 10, or 30 mg/kg I.P.) and imaged for 10 min post treatment. Mice were also treated with the 10 mg/kg dose of CBD and imaged one hr later for resting state BOLD functional connectivity (rsFC). Imaging data were registered to a 3D MRI mouse atlas providing site-specific information on 138 different brain areas. Blood samples were collected for CBD measurements.Results: CBD produced a dose-dependent polarization of activation along the rostral-caudal axis of the brain. The olfactory bulb and prefrontal cortex showed an increase in positive BOLD whereas the brainstem and cerebellum showed a decrease in BOLD signal. This negative BOLD affected many areas connected to the ascending reticular activating system (ARAS). The ARAS was decoupled to much of the brain but was hyperconnected to the olfactory system and prefrontal cortex. The pattern of ARAS connectivity closely overlapped with brain areas showing high levels N-acyl-phosphatidylethanolamines-specific phospholipase D (NAPE-PLD) messenger RNA.Conclusion: The CBD-induced decrease in ARAS activity is consistent with an emerging literature suggesting that CBD reduces autonomic arousal under conditions of emotional and physical stress. The putative target and mechanism of action is NAPE-PLD the enzyme responsible for the biosynthesis of lipid signaling molecules like anandamide.

The Effect of Crystal Dependence on Brain Activity Related to the Perception of Pleasure Using fMRI

2021 ◽  
Vol 8 (3) ◽  
Author(s):  
Ali Yoonessi ◽  
Seyed Amir Hossein Batouli ◽  
Iman Ahmadnezhad ◽  
Hamid Soltanian-zadeh
Keyword(s):  
Case Control Study ◽  
Brain Activity ◽  
Economic Status ◽  
Smoking History ◽  
Control Group ◽  
Human Society ◽  
Significant Difference ◽  
History Of ◽  
The Brain ◽  
Control Study

Background: Addiction is currently one of the problems of human society. Drug abuse is one of the most important issues in the field of addiction. Methamphetamine (crystal) is one of the drugs that has been abused in recent decades. Methods: In this case-control study, 10 individuals aged 20 to 40 years old with at least 2 years of experience of methamphetamine consumption without any history of drug use or other stimulants from clients and drug withdrawal centers in Tehran City, and 10 healthy volunteers were selected. Age, social status, and economic status of addicts were included in the fMRI apparatus, and 90 selected pleasurable, non-pleasurable, and neutral images (IAPS) were displayed by the projector through an event-related method. The playback time of each photo was 3 s, and after this process, the person outside the device, without the time limit selected the enjoyable and unpleasant images. Results: The results showed that there was no significant difference between the groups in terms of age, alcohol use, and smoking history (P < 0.05). There was no significant difference in terms of the age at first use between members of the methamphetamine-dependent group. Also, the methamphetamine-dependent group showed more brain activity in their pre-center and post-center gyrus than the normal (control) group. Conclusions: According to the results obtained in this study, in general, it can be concluded that there are some areas in the brain of addicts that are activated when watching pleasant photos, while these areas are not active in the brains of normal people.

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
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