Fmri-based Neurofeedback With Anxious Adolescents Study

NCT ID: NCT02463136

Last Updated: 2016-11-10

Basic Information

• Recruitment Status: UNKNOWN
• Clinical Phase: PHASE1
• Total Enrollment: 50 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2015-11-30
• Study Completion Date: 2017-10-31

Brief Summary

Adolescents are particularly vulnerable to psychological problems, partly because of dramatic changes in the brain, along with changes in social interactions patterns as they move from childhood towards adulthood. One of the most common problems is anxiety, which affects up to 1 in 4 adolescents. Moreover, paediatric anxiety predicts lifelong persistent mental health problems, which are estimated to cost the UK taxpayer £8.6 billion annually. Young people with anxiety experience intense fears and worries, leading to problems with friendships, poor school performance, and long-term mental health difficulties. Research investigating how and why some young people develop anxiety is therefore critically needed so that strategies for early intervention can be developed.

This research will test the hypothesis that using a novel training intervention, - which teaches participants to change the way that their brain responds to emotional stimuli - will allow the investigators to influence response strategies while they are being established and possibly reduce the risk for anxiety in the long run. To achieve this, the investigators will test 50 adolescent females (aged 14-17 years) varying in anxiety levels to investigate whether brain responses in emotion regulation regions can be up/down regulated using fMRI-based neurofeedback.The rationale behind this research approach is that successful changes in brain response may then provide the participant with an additional, 'bodily' feeling of how respond to an emotional stimulus in real life situations, thereby paving the path towards the development of effective, age-appropriate intervention approaches.

Detailed Description

This study is part of workpackage 4 of the Braintrain project (EU-FP7 n°602186), which responds to a huge clinical need for mechanism-driven therapies in psychiatry. Advances in neuroimaging and other neuroscience techniques have produced a wealth of information about the neural networks that can contribute to these disorders and their treatment (Linden, 2012). This information can now be harnessed to pinpoint both dysfunction and potential compensatory mechanisms in individual patients. It is important for the choice of neuroimaging technique that major nodes of such disordered networks are in deep regions of the brain such as subcortical nuclei (amygdala and nucleus accumbens) and/or midline cortical regions (medial prefrontal cortex, subgenual cingulate cortex, retrosplenial cortex), which are very difficult to probe via EEG alone. Through the development of fMRI-based NF (henceforth NF) techniques over the last decade by collaboration of members of this consortium (Weiskopf et al., 2004a; Weiskopf et al., 2004b), it has become a realistic proposition to train patients in the self-regulation of these networks and thus obtain clinical benefits (deCharms, 2007). In addition to this therapeutic option, NF can also take the investigation of the neural mechanisms of mental disorders to a new level because it allows the investigators to establish causal relationships by changing regional activity and assessing effects on behaviour and mental states in real-time.

In the current study, the investigators aim to provide proof of concept for using NF with adolescents with varying anxiety levels aged 14-17 years. Anxiety disorders are common, having an estimated lifetime prevalence of 10-25%, and often begin in late childhood/early adolescence. There are currently no effective prevention programmes and current treatments yield variable outcomes. Improving our understanding of the mechanisms by which anxiety disorders first develop can inform the design of effective and targeted interventions for prevention. The transition to adolescence may mark one such developmentally-sensitive juncture for the onset of lifelong persistent anxiety problems, where new interventions such as NF may be particularly effective (Cohen Kadosh et al., 2013). Particularly, it has been suggested that increased emotionality and ongoing development in the neuro-cognitive bases of emotion regulation abilities during adolescence may be one of the factors contributing to the increased risk of anxiety disorders in this age group (Haller et al., in press).

This study builds on previous work by the investigators, which has established the suitability of using NF with paediatric populations (Cohen Kadosh et al., in preparation). Specifically, here, the investigators will use NF to train 50 adolescent girls with varying anxiety levels to increase effective connectivity in the neural networks involved in emotion regulation abilities (Cohen Kadosh et al., in preparation; Kohn et al., 2014; Ruiz et al., 2013). The rationale for this approach is that by improving the information flow in these brain regions, emotion regulation abilities will also improve. Moreover, the investigators hope to be able to show that in turn, improvements in emotion regulation abilities will affect overall anxiety levels. Last, by recruiting participants across a wide range of anxiety levels, the investigators will also be able to assess variations in regulation success as a function of individual anxiety levels.

Conditions

Anxiety

Keywords

Adolescence; Brain Development; Neuroimaging; Neurofeedback; Anxiety

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: BASIC_SCIENCE
• Blinding Strategy: NONE

Study Groups

Behaviour and brain training

fMRI-based neurofeedback

Group Type: EXPERIMENTAL

questionnaires

Intervention Type: BEHAVIORAL

Clinical questionnaires and behavioural computer-based paradigms, such as the Overlap task (Cohen Kadosh et al., 2014)

Functional magnetic resonance imaging w neurofeedback

Intervention Type: DEVICE

The general framework of the scanning part of this experiment consists of a localiser task (lasting approximately 8 minutes), 4 neurofeedback runs (each lasting approximately 5 minutes) and an anatomical scan (approximately 10 minutes).

Immediately prior and following the scanning session, participants will also be asked to completed several), as well as an attentional control task with emotional stimuli, such as a behavioural version of the Overlap task (Cohen Kadosh et al., 2014).

Interventions

questionnaires

Clinical questionnaires and behavioural computer-based paradigms, such as the Overlap task (Cohen Kadosh et al., 2014)

Intervention Type: BEHAVIORAL

Functional magnetic resonance imaging w neurofeedback

The general framework of the scanning part of this experiment consists of a localiser task (lasting approximately 8 minutes), 4 neurofeedback runs (each lasting approximately 5 minutes) and an anatomical scan (approximately 10 minutes).

Immediately prior and following the scanning session, participants will also be asked to completed several), as well as an attentional control task with emotional stimuli, such as a behavioural version of the Overlap task (Cohen Kadosh et al., 2014).

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• Female
• Aged 14-17 years
• Trait-anxiety score between 20-60

Exclusion Criteria

• A past or current diagnosis of a psychological or psychiatric disorder, such as anxiety, depression, psychosis, autism, substance abuse, learning difficulties.
• Known incompatibility with the scanner requirements, such as braces, non-removable piercings, tattoos or pregnancy.

• Minimum Eligible Age: 14 Years
• Maximum Eligible Age: 17 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: Yes

Sponsors

King's College London

OTHER

Sponsor Role: collaborator

Cardiff University

OTHER

Sponsor Role: collaborator

University of Oxford

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Kathrin ' Cohen Kadosh, PhD

Role: PRINCIPAL_INVESTIGATOR

University of Oxford

Locations

University of Oxford

Oxford, Oxfordshire, United Kingdom

Site Status: RECRUITING

Countries

United Kingdom

Central Contacts

Kathrin Cohen Kadosh, PhD

Role: CONTACT

Phone: 01865

Email: kathrin.cohenkadosh@psy.ox.ac.uk

Jennifer YF Lau, PhD

Role: CONTACT

Phone: 0207790

Email: j.lau@kcl.ac.uk

Facility Contacts

Kathrin Cohen Kadosh, PhD

Role: primary

References

Cohen Kadosh K, Linden DE, Lau JY. Plasticity during childhood and adolescence: innovative approaches to investigating neurocognitive development. Dev Sci. 2013 Jul;16(4):574-83. doi: 10.1111/desc.12054. Epub 2013 May 28.

Reference Type: BACKGROUND

PMID: 23786475 (View on PubMed)

deCharms RC. Reading and controlling human brain activation using real-time functional magnetic resonance imaging. Trends Cogn Sci. 2007 Nov;11(11):473-81. doi: 10.1016/j.tics.2007.08.014. Epub 2007 Nov 7.

Reference Type: BACKGROUND

PMID: 17988931 (View on PubMed)

Haller SP, Cohen Kadosh K, Scerif G, Lau JY. Social anxiety disorder in adolescence: How developmental cognitive neuroscience findings may shape understanding and interventions for psychopathology. Dev Cogn Neurosci. 2015 Jun;13:11-20. doi: 10.1016/j.dcn.2015.02.002. Epub 2015 Feb 28.

Reference Type: BACKGROUND

PMID: 25818181 (View on PubMed)

Kohn N, Eickhoff SB, Scheller M, Laird AR, Fox PT, Habel U. Neural network of cognitive emotion regulation--an ALE meta-analysis and MACM analysis. Neuroimage. 2014 Feb 15;87:345-55. doi: 10.1016/j.neuroimage.2013.11.001. Epub 2013 Nov 9.

Reference Type: BACKGROUND

PMID: 24220041 (View on PubMed)

Linden DE. The challenges and promise of neuroimaging in psychiatry. Neuron. 2012 Jan 12;73(1):8-22. doi: 10.1016/j.neuron.2011.12.014.

Reference Type: BACKGROUND

PMID: 22243743 (View on PubMed)

Ruiz S, Lee S, Soekadar SR, Caria A, Veit R, Kircher T, Birbaumer N, Sitaram R. Acquired self-control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia. Hum Brain Mapp. 2013 Jan;34(1):200-12. doi: 10.1002/hbm.21427. Epub 2011 Oct 22.

Reference Type: BACKGROUND

PMID: 22021045 (View on PubMed)

Weiskopf N, Mathiak K, Bock SW, Scharnowski F, Veit R, Grodd W, Goebel R, Birbaumer N. Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI). IEEE Trans Biomed Eng. 2004 Jun;51(6):966-70. doi: 10.1109/TBME.2004.827063.

Reference Type: BACKGROUND

PMID: 15188865 (View on PubMed)

Weiskopf N, Scharnowski F, Veit R, Goebel R, Birbaumer N, Mathiak K. Self-regulation of local brain activity using real-time functional magnetic resonance imaging (fMRI). J Physiol Paris. 2004 Jul-Nov;98(4-6):357-73. doi: 10.1016/j.jphysparis.2005.09.019. Epub 2005 Nov 10.

Reference Type: BACKGROUND

PMID: 16289548 (View on PubMed)

Haugg A, Renz FM, Nicholson AA, Lor C, Gotzendorfer SJ, Sladky R, Skouras S, McDonald A, Craddock C, Hellrung L, Kirschner M, Herdener M, Koush Y, Papoutsi M, Keynan J, Hendler T, Cohen Kadosh K, Zich C, Kohl SH, Hallschmid M, MacInnes J, Adcock RA, Dickerson KC, Chen NK, Young K, Bodurka J, Marxen M, Yao S, Becker B, Auer T, Schweizer R, Pamplona G, Lanius RA, Emmert K, Haller S, Van De Ville D, Kim DY, Lee JH, Marins T, Megumi F, Sorger B, Kamp T, Liew SL, Veit R, Spetter M, Weiskopf N, Scharnowski F, Steyrl D. Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis. Neuroimage. 2021 Aug 15;237:118207. doi: 10.1016/j.neuroimage.2021.118207. Epub 2021 May 25.

Reference Type: DERIVED

PMID: 34048901 (View on PubMed)

Zich C, Johnstone N, Luhrs M, Lisk S, Haller SP, Lipp A, Lau JY, Kadosh KC. Modulatory effects of dynamic fMRI-based neurofeedback on emotion regulation networks in adolescent females. Neuroimage. 2020 Oct 15;220:117053. doi: 10.1016/j.neuroimage.2020.117053. Epub 2020 Jun 20.

Reference Type: DERIVED

PMID: 32574803 (View on PubMed)

Other Identifiers

MSD-IDREC-C2-2013-014

Identifier Type: -

Identifier Source: org_study_id