The Real-time fMRI Neurofeedback Based Stratification of Default Network Regulation Neuroimaging Data Repository

McDonald, Amalia; Muraskin, Jordan; Dam, Nicholas T. Van; Froehlich, Caroline; Puccio, Benjamin; Pellman, John; Bauer, Clemens; Akeyson, Alexis; Breland, Melissa; Calhoun, Vince D.; Carter, Stephen; Chang, Tiffany; Gessner, Chelsea; Giannone, Alyssa; Giavasis, Steven; Glass, Jamie; Homann, S J; King, Margaret D.; Kramer, Melissa; Landis, Drew; Lieval, Alexis; Lisinski, Jonathan; MacKay‐Brandt, Anna; Miller, Brittny; Panek, Laura J.; Reed, Hayley; Santiago, Christine; Schoell, Eszter D.; Sinning, Richard; Sital, Melissa; Taverna, Elise C.; Tobe, Russell H.; Trautmann, Kristin; Varghese, Betty; Walden, Lauren; Wang, Runtang; Waters, Abigail B.; Wood, Dylan; Castellanos, F. Xavier; Leventhal, Bennett L.; Colcombe, Stanley J.; LaConte, Stephen M.; Milham, Michael P.; Craddock, R. Cameron

doi:10.1101/075275

Cited by 6 publications

(12 citation statements)

References 76 publications

(92 reference statements)

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“…Participants were residents of the Rockland County (New York, U.S.A.) and participated voluntarily in the Rockland Sample Real-Time Neurofeedback project, a large study aiming to create a sample with extensive neuropsychological and medical profiling, including several functional neuroimaging tasks (McDonald et al, 2017;Nooner et al, 2012). In order to include participants with a range of clinical and sub-clinical symptoms, minimally restrictive exclusion criteria were applied to exclude individuals with severe illnesses that would compromise compliance with experimental instructions (e.g.…”

Section: Participantsmentioning

confidence: 99%

“…Participants completed a variety of assessments and functional neuroimaging tasks comprising the Enhanced Nathan Kline Institute-Rockland Sample (NKI-RS) protocol, described in detail elsewhere (McDonald et al, 2017;Nooner et al, 2012). The protocol included a six-minute resting state fMRI acquisition, followed by a twelve-minute neurofeedback task.…”

Section: Experimental Designmentioning

confidence: 99%

“…Physiological measures including galvanic skin response, pulse oximetry, rate of breathing and depth of breathing were measured during the functional acquisitions. Functional scanning included a six-minute resting state, prior to NF and other functional tasks using counterbalanced orders (McDonald et al, 2017).…”

Section: Mri Data Acquisitionmentioning

confidence: 99%

“…Prior to the NF session, the DMN of each participant was delineated, based on the data from the resting state scan, using data preprocessing and support vector machines described elsewhere (McDonald et al, 2017). All neuroimaging data were subjected to the 'Preprocessed Connectomes Project Quality Assessment Protocol' (GitHub; RRID:SCR_002630; https://git.io/vptfA; Shehzad et al, 2015).…”

Section: Mri Data Processingmentioning

confidence: 99%

“…Neuroimaging data, further described in(McDonald et al, 2017), are available online via theNeuroimaging Informatics Tools Resources Clearinghouse (NITRC; RRID:SCR_003430). Diagnostic assessment data are available following the completion of a data transfer agreement with the Nathan Kline Institute (Nathan S. Kline Institute for Psychiatric Research; New York; USA, RRID:SCR_004334) via the Collaborative Informatics and Neuroimaging Suite Data Exchange (COINS; Mind Research Network RRID:SCR_000805).…”

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confidence: 99%

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The effects of psychiatric history and age on self-regulation of the default mode network

Skouras

Scharnowski

2018

Preprint

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Real-time neurofeedback enables human subjects to learn to regulate their brain activity, effecting behavioral changes and improvements of psychiatric symptomatology. Neurofeedback up-regulation and downregulation have been assumed to share common neural correlates. Neuropsychiatric pathology and aging incur suboptimal functioning of the default mode network. Despite the exponential increase in real-time neuroimaging studies, the effects of aging, pathology and the direction of regulation on neurofeedback performance remain largelyunknown. Using open-access analyses and real-time fMRI data shared through the Rockland Sample Real-Time Neurofeedback project (N=136), we first modeled neurofeedback performance and learning in a group of subjects with psychiatric history (n a =74) and a healthy control group (n b =62). Subsequently, we examined the relationship between up-regulation and down-regulation learning, the relationship between age and neurofeedback performance in each group and differences in neurofeedback performance between the two groups. Results show that in an initial session of default mode network neurofeedback with real-time fMRI, up-regulation and down-regulation learning scores are negatively correlated. Moreover, age correlates negatively with default mode network neurofeedback performance, only in absence of psychiatric history. Finally, adults with psychiatric history outperform healthy controls in default mode network up-regulation. Interestingly, the performance difference is related to no upregulation learning in controls. attention) is unknown. Third, key performance constraints, such as the effect of age, in relation to self-regulation of brain function and pathology, have not been investigated.Here we address these three open issues regarding self-regulation of brain function, using the largest publicly available rt-fMRI NF repository, comprising data from healthy participants and psychiatric patients, during bidirectional self-regulation of the default mode network (DMN). The DMN is a large-scale cerebral network (Raichle et al., 2001) associated with a variety of brain functions, including perception (Kelly et al., 2008), attention (Weissman et al., 2006 and working memory (Mayer et al. 2010), which has become highly relevant for clinical applications (Zhang and Raichle, 2010;Brakowski et al., 2017;Mulders et al., 2015;Hamilton et al., 2015).Similarly to psychiatric pathology, aging also incurs suboptimal functioning of the human brain's DMN (Whitfield-Gabrieli and Ford, 2012;Damoiseaux et al., 2008). Recent studies have demonstrated that DMN activity can be

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Section: Participantsmentioning

confidence: 99%

Section: Experimental Designmentioning

confidence: 99%

Section: Mri Data Acquisitionmentioning

confidence: 99%

Section: Mri Data Processingmentioning

confidence: 99%

mentioning

confidence: 99%

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The effects of psychiatric history and age on self-regulation of the default mode network

Skouras

Scharnowski

2018

Preprint

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Self‐regulation of ventromedial prefrontal cortex activation using real‐time fMRI neurofeedback—Influence of default mode network

Mayeli

Misaki

Zotev

et al. 2019

Human Brain Mapping

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The ventromedial prefrontal cortex (vmPFC) is involved in regulation of negative emotion and decision-making, emotional and behavioral control, and active resilient coping. This pilot study examined the feasibility of training healthy subjects (n = 27) to self-regulate the vmPFC activity using a real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf). Participants in the experimental group (EG, n = 18) were provided with an ongoing vmPFC hemodynamic activity (rtfMRI-nf signal represented as variable-height bar). Individuals were instructed to raise the bar by self-relevant value-based thinking. Participants in the control group (CG, n = 9) performed the same task; however, they were provided with computer-generated sham neurofeedback signal. Results demonstrate that (a) both the CG and the EG show a higher vmPFC fMRI signal at the baseline than during neurofeedback training; (b) no significant positive training effect was seen in the vmPFC across neurofeedback runs; however, the medial prefrontal cortex, middle temporal gyri, inferior frontal gyri, and precuneus showed significant decreasing trends across the training runs only for the EG; (c) the vmPFC rtfMRI-nf signal associated with the fMRI signal across the default mode network (DMN). These findings suggest that it may be difficult to modulate a single DMN region without affecting other DMN regions. Observed decreased vmPFC activity during the neurofeedback task could be due to interference from the fMRI signal within other DMN network regions, as well as interaction with taskpositive networks. Even though participants in the EG did not show significant positive increase in the vmPFC activity among neurofeedback runs, they were able to learn to accommodate the demand of self-regulation task to maintain the vmPFC activity with the help of a neurofeedback signal.K E Y W O R D S brain, default mode network, emotion, fMRI Neurofeedback, functional connectivity, selfregulation, vmPFC

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Resting‐state fMRI and social cognition: An opportunity to connect

Doruyter

Groenewold

Dupont

et al. 2017

Human Psychopharmacology

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Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain.

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The Real-time fMRI Neurofeedback Based Stratification of Default Network Regulation Neuroimaging Data Repository

Cited by 6 publications

References 76 publications

The effects of psychiatric history and age on self-regulation of the default mode network

The effects of psychiatric history and age on self-regulation of the default mode network

Self‐regulation of ventromedial prefrontal cortex activation using real‐time fMRI neurofeedback—Influence of default mode network

Resting‐state fMRI and social cognition: An opportunity to connect

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