Keyword search (4,164 papers available)

"Khalili-Mahani N" Authored Publications:

Title Authors PubMed ID
1 Web-based processing of physiological noise in fMRI: addition of the PhysIO toolbox to CBRAIN Valevicius D; Beck N; Kasper L; Boroday S; Bayer J; Rioux P; Caron B; Adalat R; Evans AC; Khalili-Mahani N; 37841811
ENCS
2 The association between information and communication technologies, loneliness and social connectedness: A scoping review Petersen B; Khalili-Mahani N; Murphy C; Sawchuk K; Phillips N; Li KZH; Hebblethwaite S; 37034933
PSYCHOLOGY
3 Double-Bind of Recruitment of Older Adults Into Studies of Successful Aging via Assistive Information and Communication Technologies: Mapping Review Khalili-Mahani N; Sawchuk K; 36563033
CONCORDIA
4 Toward a digital citizen lab for capturing data about alternative ways of self-managing chronic pain: An attitudinal user study Khalili-Mahani N; Woods S; Holowka EM; Pahayahay A; Roy M; 36188996
PERFORM
5 A Simulation Toolkit for Testing the Sensitivity and Accuracy of Corticometry Pipelines OmidYeganeh M; Khalili-Mahani N; Bermudez P; Ross A; Lepage C; Vincent RD; Jeon S; Lewis LB; Das S; Zijdenbos AP; Rioux P; Adalat R; Van Eede MC; Evans AC; 34381348
PERFORM
6 What Media Helps, What Media Hurts: A Mixed Methods Survey Study of Coping with COVID-19 Using the Media Repertoire Framework and the Appraisal Theory of Stress Pahayahay A; Khalili-Mahani N; 32701459
PERFORM
7 Reflective and Reflexive Stress Responses of Older Adults to Three Gaming Experiences In Relation to Their Cognitive Abilities: Mixed Methods Crossover Study. Khalili-Mahani N, Assadi A, Li K, Mirgholami M, Rivard ME, Benali H, Sawchuk K, De Schutter B 32213474
PERFORM
8 Cyberinfrastructure for Open Science at the Montreal Neurological Institute. Das S, Glatard T, Rogers C, Saigle J, Paiva S, MacIntyre L, Safi-Harab M, Rousseau ME, Stirling J, Khalili-Mahani N, MacFarlane D, Kostopoulos P, Rioux P, Madjar C, Lecours-Boucher X, Vanamala S, Adalat R, Mohaddes Z, Fonov VS, Milot S, Leppert I, Degroot C, Durcan TM, Campbell T, Moreau J, Dagher A, Collins DL, Karamchandani J, Bar-Or A, Fon EA, Hoge R, Baillet S, Rouleau G, Evans AC 28111547
IMAGING
9 Affective Game Planning for Health Applications: Quantitative Extension of Gerontoludic Design Based on the Appraisal Theory of Stress and Coping. Khalili-Mahani N, De Schutter B 31172966
PERFORM
10 Biomarkers, designs, and interpretations of resting-state fMRI in translational pharmacological research: A review of state-of-the-Art, challenges, and opportunities for studying brain chemistry. Khalili-Mahani N, Rombouts SA, van Osch MJ, Duff EP, Carbonell F, Nickerson LD, Becerra L, Dahan A, Evans AC, Soucy JP, Wise R, Zijdenbos AP, van Gerven JM 28145075
PERFORM
11 To Each Stress Its Own Screen: A Cross-Sectional Survey of the Patterns of Stress and Various Screen Uses in Relation to Self-Admitted Screen Addiction Khalili-Mahani N; Smyrnova A; Kakinami L; 30938685
PERFORM

 

Title:Web-based processing of physiological noise in fMRI: addition of the PhysIO toolbox to CBRAIN
Authors:Valevicius DBeck NKasper LBoroday SBayer JRioux PCaron BAdalat REvans ACKhalili-Mahani N
Link:https://pubmed.ncbi.nlm.nih.gov/37841811/
DOI:10.3389/fninf.2023.1251023
Publication:Frontiers in neuroinformatics
Keywords:brain imaging data structure (BIDS)fMRIhigh performance computing (HPC)neuroimagingphysiological noise correctionsoftware
PMID:37841811 Category: Date Added:2023-10-16
Dept Affiliation: ENCS

Description:

Neuroimaging research requires sophisticated tools for analyzing complex data, but efficiently leveraging these tools can be a major challenge, especially on large datasets. CBRAIN is a web-based platform designed to simplify the use and accessibility of neuroimaging research tools for large-scale, collaborative studies. In this paper, we describe how CBRAIN's unique features and infrastructure were leveraged to integrate TAPAS PhysIO, an open-source MATLAB toolbox for physiological noise modeling in fMRI data. This case study highlights three key elements of CBRAIN's infrastructure that enable streamlined, multimodal tool integration: a user-friendly GUI, a Brain Imaging Data Structure (BIDS) data-entry schema, and convenient in-browser visualization of results. By incorporating PhysIO into CBRAIN, we achieved significant improvements in the speed, ease of use, and scalability of physiological preprocessing. Researchers now have access to a uniform and intuitive interface for analyzing data, which facilitates remote and collaborative evaluation of results. With these improvements, CBRAIN aims to become an essential open-science tool for integrative neuroimaging research, supporting FAIR principles and enabling efficient workflows for complex analysis pipelines.





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