Neurofeedback Training For Older Adults

Depression, Anxiety Clinical Trial

Official title:

Neurofeedback Training to Improve Prefrontal Functioning in Older Adults With Subclinical Depression and Anxiety: a Randomised Control Trial

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05936697
• Other study ID #: HSEARS20221103002
• Status: Recruiting
• Phase: N/A
• Start date: February 15, 2023
• Est. completion date: October 31, 2024

Study information

• Verified date: March 2024
• Source: The Hong Kong Polytechnic University
• Contact: Lai Man Jacqueline Chan
• Phone: +852 34002664
• Email: Jacqueline-lm.chan[@]polyu.edu.hk
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Symptoms of depression and anxiety are common in older adults and are associated with poor outcomes and the risk of dementia. The prefrontal cortex (PFC) is crucial for emotion regulation. Poor PFC function may underlie subclinical depression and anxiety symptoms in older people, which could progress to clinical conditions. Neurofeedback training based on electroencephalography (EEG) or functional near-infrared spectroscopy (fNIRS) teaches individuals to self-regulate different aspects of brain activity and induce neurocognitive improvements. This proposed project will examine whether prefrontal EEG and fNIRS neurofeedback training programmes can enhance the mood and cognition of older adults with subclinical depression and anxiety.

Description:

Background:

Subclinical symptoms of depression and anxiety are common in older adults, with some estimates indicating that these symptoms are present in 10-52% of community-dwelling older adults. Some studies have shown that older adults with subclinical depression and anxiety are more likely than those with low levels of relevant symptoms to be diagnosed with affective disorders and mild cognitive impairment or dementia later in life. Thus, interventions for older people with elevated subclinical symptoms of depression and anxiety are crucial for preventing affective disorders and dementia late in life. During negative emotional experiences, the prefrontal cortex (PFC) plays a pivotal role in downregulating activity. PFC dysfunction may cause different mood and anxiety symptoms.

Neurofeedback training is a non-pharmaceutical neurorehabilitation technique that can potentially improve prefrontal function and enhance mental health and cognitive functions. This technique uses sensory feedback to teach individuals to self-regulate specific brain activities, with the goal of inducing long-term neuroplasticity and functional improvements. Traditionally, neurofeedback training has been conducted using EEG, and much research has applied such training interventions for the treatment of a variety of psychiatric disorders. In recent years, interest in using fNIRS to deliver neurofeedback training has grown. The underlying mechanism of such training with fNIRS is different from that of training with EEG. Compared with EEG, fNIRS has a lower temporal resolution but a higher spatial resolution and is more resilient to movement artifacts. In addition, one recent study showed that patients with social anxiety disorder had reduced anxiety symptoms after fNIRS neurofeedback training.

Research Plan and Methodology:

Design: This proposed project has been designed in accordance with current consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies. The participants will be randomly and equally assigned to one of three neurofeedback training groups: (1) sham, (2) EEG, and (3) fNIRS. Each participant will complete a neurophysiological assessment (1) before, (2) immediately after, and (3) 1 month after intervention.

Participants: 90 older adults without dementia will be recruited via advertisements at PolyU and NGOs. The inclusion criteria is: (i) age of 60-79 years; (ii) right-handedness as assessed using the short form of the Edinburgh Handedness Inventory; (iii) a moderate or higher score on at least one of the depression and anxiety subscales (but not necessarily both) of the Depression Anxiety Stress Scale-21 (DASS-21); (iv) no history of neurological or psychiatric disorder; (iv) no history of traumatic brain injury requiring hospitalisation; (vi) not currently using psychotropic medication; (vii) ability to read Traditional Chinese; (viii) normal or corrected-to-normal vision; and (ix) a score of at least 19 on the Hong Kong Montreal Cognitive Assessment (HK-MoCA).

The inclusion criteria that the investigators planned to use were based on those employed by prefrontal neurofeedback studies in mood or anxiety disorders. Conventionally, participants are selected based on a certain threshold of depressive or anxiety symptoms, neither cognitive nor brain dysfunction constitutes an inclusion criterion. Nevertheless, since variation in cognitive and PFC functioning levels may affect the treatment response, subsequent analyses will consider baseline cognitive and PFC functioning levels.

Study Procedures: Potential participants will first be subjected to a screening evaluation to assess eligibility. Eligible individuals will be invited to PolyU for assessment and training. The training will comprise 10 60-min sessions conducted within 4 weeks. Each session will include 25-min effective training time, for a total training time of 250 min, in keeping with recent recommendations. In addition, the participants will undertake 3 experimental tasks under simultaneous EEG-fNIRS recording and complete several questionnaires at 3 time points, as described in the 'Neurophysiological Assessment' section. Multiple studies have demonstrated that EEG, fNIRS, and neurofeedback training can be applied to older adults over 70, and even to individuals with dementia. Therefore, the investigators expect that older adults who are screened for dementia by the HK-MoCA will be able to follow both the assessment and training protocols.

Neurofeedback Training: During training, participants will be asked to follow the instructions on a computer screen. They will complete five rounds of training task. Each round starts with a 30-s rest phase followed by 4.5 min of self-regulation phase. During the rest phase, a fixation cross will appear onscreen, and the participants will be instructed to sit still and relax. During the regulation period, the participants will be asked to make the square change from white to black (i.e., an intrinsic social reward) but will not be given specific strategies. The darkness of colour will represent the increase in either frontal alpha asymmetry or frontal oxyhaemoglobin (HbO) asymmetry. The values at the moment will be compared against the 20-s pre-regulation baseline. In the sham condition, participants will receive visual feedback based on pre-recordings and/or other participants' recordings. Participants will undergo a 3-min rest period before and after each training session to track changes in resting-state brain activity within and across sessions.

During each training session, a cap adjusted to the participant's head size will be used to mount the EEG and fNIRS sensors. The hardware setup will be the same for all groups to ensure that both the participant and the experimenter are blinded. For EEG to be recorded by the ANT eego rt8 amplifier (ANT Neuro, Hengelo, The Netherlands), electrodes will be placed at Fp1, F3, F4, Fz, Fpz, Cz, GND (ground), lower VEOG, and on the two earlobes (references). Data will be collected at 2,048 Hz. For fNIRS to be recorded by the wearable OctaMon+ system (Artinis Medical Systems, Gelderland, The Netherlands), two sources, each surrounded by four detectors positioned approximately 3 cm apart, will be placed on the scalp such that the two channels near the cerebral fissure on each side of the hemispheres are surrounded F3 and F4. Data will be sampled at 50 Hz. Depending on the training group, frontal asymmetry in terms of the difference in alpha power (8-13 Hz) between F3 and F4 and the mean change in HbO concentration between the left and right PFC will be chosen as the target objective. For both real training groups, real-time data streaming will be performed using the Lab Streaming Layer and OpenVibe according to published guidelines.

Neurophysiological Assessment: A 1.5-h neurophysiological assessment will be administered at each of 3 time points (pre, post, and 1-month follow-up) to evaluate the effects of neurofeedback training. The participants will complete the DASS-21 (Chinese version) to measure their depressive and anxiety symptoms over the last week; the Hospital Anxiety and Depression Scale (HADS; Chinese version) to measure their signs of anxiousness and depression during the previous week; the Pittsburgh Sleep Quality Index to measure their sleep quality over the last month; the Satisfaction with Life Scale (Chinese version) to quantify their general life satisfaction; and Lawton Instrumental Activities of Daily Living Scale (IADL; Chinese version) to assess independent living skills. The participants will also complete three computerised tasks to assess different components of frontal cognitive function under simultaneous EEG-fNIRS measurements, using the same setup as neurofeedback training. At the first visit, the participants will also complete the HK-MoCA to screen for dementia. Immediately after the intervention, they will be asked whether they know their treatment group assignment to check the strength of blinding.

Each assessment task (eyes open, Emotional Stroop, n-back) proposed for this research will comprise a difficult and an easy condition. The eyes open test is used to let the machine measure the activation baseline when the participants open their eyes. It requires participants to maintain their eyes open for 3 minutes. The Emotional Stroop task is used to assess inhibitory control. Participants are shown photos of different emotions with unrelated traditional Chinese emotion names. They are asked to name the photos by emotion. It requires participants to inhibit their emotions lead by the wordings and react to the content of the photo. Differences in accuracy and mean reaction time (RT) and changes in the prefrontal HbO concentration and theta power between the two conditions will be the dependent variables. The n-back task is used to assess working memory. During the task, participants are shown a sequence of digits and asked to judge via button press whether the digit they are seeing is zero (0-back; easy) or the same as the digit they saw two trials before (2-back; difficult). Differences in accuracy and mean RT and changes in the prefrontal HbO concentration and theta power between the two conditions will be the dependent variables.

Data Analysis: In this project, the primary outcome measures are mood and anxiety measures (i.e., DASS-21 and HADS scores), and the secondary outcome measures are task performance and PFC measures, as well as other mental health measures. The outcome measures will be analysed according to the CRED-nf checklist. Linear mixed models with group (sham, EEG, fNIRS), time (baseline, post, follow-up), and condition (easy, difficult) as the fixed factors; and the subject as a random factor will be used to analyse the behavioural, fNIRS, and EEG data. The investigators expect that participants in the two real neurofeedback training groups will demonstrate significant improvements in mental health, cognitive function, and frontal lobe function at the post and follow-up assessments relative to the sham group participants. In addition, the investigators will evaluate differences in pre-post changes in mental health and cognitive functions between the two real training groups. Moreover, the investigators will examine the correlation between baseline cognitive and PFC functioning levels and the pre-post changes in DASS-21 scores to elucidate individual differences in the treatment response for each neurofeedback group.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 90
• Est. completion date: October 31, 2024
• Est. primary completion date: October 31, 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: 60 Years to 79 Years

Eligibility

Inclusion Criteria:

• (i) age of 60-79 years;

• (ii) right-handedness as assessed using the short form of the Edinburgh Handedness Inventory (Veale, 2014);

• (iii) a moderate or higher score on at least one of the depression and anxiety subscales (but not necessarily both) of the Depression Anxiety Stress Scale-21 (DASS-21), which has been shown to yield reliable and valid scores;

• (iv) no history of neurological or psychiatric disorder;

• (v) no history of traumatic brain injury requiring hospitalisation;

• (vi) not currently using psychotropic medication;

• (vii) ability to read Traditional Chinese text;

• (viii) normal or corrected-to-normal vision; and

• (ix) a score of at least 19 on the Hong Kong Montreal Cognitive Assessment

Exclusion Criteria:

• does not fulfill any of the above criteria

Related Conditions & MeSH terms

• Depression
• Depression, Anxiety

Intervention

Device:
• fNIRS
For fNIRS to be recorded by the wearable OctaMon+ system (Artinis Medical Systems, The Netherlands), two sources, each surrounded by four detectors positioned approximately 3 cm apart, will be placed on the scalp such that the two channels near the fissure on each side of the head are surrounded F3 and F4. Data will be sampled at 50 Hz.
• EEG
For EEG to be recorded by the ANT eego rt8 amplifier (ANT Neuro, Hengelo, The Netherlands), electrodes will be placed at Fp1, F3, F4, Fz, Fpz, Cz, GND (ground), lower VEOG, and on the two earlobes (references). Data will be collected at 2,048 Hz.

Other:
• Baseline Training
In the sham condition, participants will receive visual feedback based on pre-recordings and/or other participants' recordings. Participants will undergo a 3-min rest period before and after each training session to track changes in resting-state brain activity within and across sessions.

Locations

Country	Name	City	State
Hong Kong	Faculty of Health and Social Sciences OF The Hong Kong Polytechnic University	Hong Kong

Sponsors (1)

Lead Sponsor	Collaborator
The Hong Kong Polytechnic University

Country where clinical trial is conducted

Hong Kong, 

References & Publications (62)

Adolph D, Margraf J. The differential relationship between trait anxiety, depression, and resting frontal alpha-asymmetry. J Neural Transm (Vienna). 2017 Mar;124(3):379-386. doi: 10.1007/s00702-016-1664-9. Epub 2016 Dec 16. — View Citation

Barry RJ, De Blasio FM. EEG differences between eyes-closed and eyes-open resting remain in healthy ageing. Biol Psychol. 2017 Oct;129:293-304. doi: 10.1016/j.biopsycho.2017.09.010. Epub 2017 Sep 21. — View Citation

Beaudreau SA, O'Hara R. Late-life anxiety and cognitive impairment: a review. Am J Geriatr Psychiatry. 2008 Oct;16(10):790-803. doi: 10.1097/JGP.0b013e31817945c3. — View Citation

Beekman AT, de Beurs E, van Balkom AJ, Deeg DJ, van Dyck R, van Tilburg W. Anxiety and depression in later life: Co-occurrence and communality of risk factors. Am J Psychiatry. 2000 Jan;157(1):89-95. doi: 10.1176/ajp.157.1.89. — View Citation

Bruder GE, Stewart JW, McGrath PJ. Right brain, left brain in depressive disorders: Clinical and theoretical implications of behavioral, electrophysiological and neuroimaging findings. Neurosci Biobehav Rev. 2017 Jul;78:178-191. doi: 10.1016/j.neubiorev.2017.04.021. Epub 2017 Apr 23. — View Citation

Bryant C, Jackson H, Ames D. The prevalence of anxiety in older adults: methodological issues and a review of the literature. J Affect Disord. 2008 Aug;109(3):233-50. doi: 10.1016/j.jad.2007.11.008. Epub 2007 Dec 26. — View Citation

Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989 May;28(2):193-213. doi: 10.1016/0165-1781(89)90047-4. — View Citation

Cui X, Bray S, Reiss AL. Functional near infrared spectroscopy (NIRS) signal improvement based on negative correlation between oxygenated and deoxygenated hemoglobin dynamics. Neuroimage. 2010 Feb 15;49(4):3039-46. doi: 10.1016/j.neuroimage.2009.11.050. Epub 2009 Nov 26. — View Citation

Cuijpers P, Koole SL, van Dijke A, Roca M, Li J, Reynolds CF 3rd. Psychotherapy for subclinical depression: meta-analysis. Br J Psychiatry. 2014 Oct;205(4):268-74. doi: 10.1192/bjp.bp.113.138784. — View Citation

Delpy DT, Cope M, van der Zee P, Arridge S, Wray S, Wyatt J. Estimation of optical pathlength through tissue from direct time of flight measurement. Phys Med Biol. 1988 Dec;33(12):1433-42. doi: 10.1088/0031-9155/33/12/008. — View Citation

Ehlis, A. C., Barth, B., Hudak, J., Storchak, H., Weber, L., Kimmig, A. C. S., ... & Fallgatter, A. J. (2018). Near-infrared spectroscopy as a new tool for neurofeedback training: Applications in psychiatry and methodological considerations. Japanese Psychological Research, 60(4), 225-241.

Etkin A, Buchel C, Gross JJ. The neural bases of emotion regulation. Nat Rev Neurosci. 2015 Nov;16(11):693-700. doi: 10.1038/nrn4044. — View Citation

Fernandez-Alvarez J, Grassi M, Colombo D, Botella C, Cipresso P, Perna G, Riva G. Efficacy of bio- and neurofeedback for depression: a meta-analysis. Psychol Med. 2022 Jan;52(2):201-216. doi: 10.1017/S0033291721004396. Epub 2021 Nov 15. — View Citation

Flint AJ, Rifat SL. Factor structure of the hospital anxiety and depression scale in older patients with major depression. Int J Geriatr Psychiatry. 2002 Feb;17(2):117-23. doi: 10.1002/gps.535. — View Citation

Gomez, R., Summers, M., Summers, A., Wolf, A., & Summers, J. J. (2014). Depression Anxiety Stress Scales-21: Factor structure and test-retest invariance, and temporal stability and uniqueness of latent factors in older adults. Journal of Psychopathology and Behavioral Assessment, 36(2), 308-317.

Grahek I, Shenhav A, Musslick S, Krebs RM, Koster EHW. Motivation and cognitive control in depression. Neurosci Biobehav Rev. 2019 Jul;102:371-381. doi: 10.1016/j.neubiorev.2019.04.011. Epub 2019 May 27. — View Citation

Haigh EAP, Bogucki OE, Sigmon ST, Blazer DG. Depression Among Older Adults: A 20-Year Update on Five Common Myths and Misconceptions. Am J Geriatr Psychiatry. 2018 Jan;26(1):107-122. doi: 10.1016/j.jagp.2017.06.011. Epub 2017 Jun 16. — View Citation

Hammond, D. C. (2005). Neurofeedback treatment of depression and anxiety. Journal of Adult Development, 12(2), 131-137.

Hammond, D. C. (2011). What is neurofeedback: An update. Journal of Neurotherapy, 15(4), 305-336.

Imbir KK, Duda-Golawska J, Pastwa M, Sobieszek A, Wielgopolan A, Jankowska M, Modzelewska A, Zygierewicz J. Inhibitory control effectiveness can be improved: The role of arousal, subjective significance and origin of words in modified Emotional Stroop Test. PLoS One. 2022 Jun 28;17(6):e0270558. doi: 10.1371/journal.pone.0270558. eCollection 2022. — View Citation

Kimmig AS, Dresler T, Hudak J, Haeussinger FB, Wildgruber D, Fallgatter AJ, Ehlis AC, Kreifelts B. Feasibility of NIRS-based neurofeedback training in social anxiety disorder: behavioral and neural correlates. J Neural Transm (Vienna). 2019 Sep;126(9):1175-1185. doi: 10.1007/s00702-018-1954-5. Epub 2018 Nov 29. — View Citation

Kirsch I, Deacon BJ, Huedo-Medina TB, Scoboria A, Moore TJ, Johnson BT. Initial severity and antidepressant benefits: a meta-analysis of data submitted to the Food and Drug Administration. PLoS Med. 2008 Feb;5(2):e45. doi: 10.1371/journal.pmed.0050045. — View Citation

Kober SE, Spork R, Bauernfeind G, Wood G. Age-related differences in the within-session trainability of hemodynamic parameters: a near-infrared spectroscopy-based neurofeedback study. Neurobiol Aging. 2019 Sep;81:127-137. doi: 10.1016/j.neurobiolaging.2019.05.022. Epub 2019 Jun 5. — View Citation

Kohl SH, Mehler DMA, Luhrs M, Thibault RT, Konrad K, Sorger B. The Potential of Functional Near-Infrared Spectroscopy-Based Neurofeedback-A Systematic Review and Recommendations for Best Practice. Front Neurosci. 2020 Jul 21;14:594. doi: 10.3389/fnins.2020.00594. eCollection 2020. Erratum In: Front Neurosci. 2022 Aug 22;16:907941. — View Citation

Kothe, C. (2014a). Lab Streaming Layer (LSL). Available online at: https://code.google.com/p/labstreaminglayer/

Laborda-Sanchez F, Cansino S. The Effects of Neurofeedback on Aging-Associated Cognitive Decline: A Systematic Review. Appl Psychophysiol Biofeedback. 2021 Mar;46(1):1-10. doi: 10.1007/s10484-020-09497-6. Epub 2021 Jan 2. — View Citation

Laborde-Lahoz P, El-Gabalawy R, Kinley J, Kirwin PD, Sareen J, Pietrzak RH. Subsyndromal depression among older adults in the USA: prevalence, comorbidity, and risk for new-onset psychiatric disorders in late life. Int J Geriatr Psychiatry. 2015 Jul;30(7):677-85. doi: 10.1002/gps.4204. Epub 2014 Oct 23. — View Citation

Lee YJ, Kim HG, Cheon EJ, Kim K, Choi JH, Kim JY, Kim JM, Koo BH. The Analysis of Electroencephalography Changes Before and After a Single Neurofeedback Alpha/Theta Training Session in University Students. Appl Psychophysiol Biofeedback. 2019 Sep;44(3):173-184. doi: 10.1007/s10484-019-09432-4. — View Citation

Li K, Jiang Y, Gong Y, Zhao W, Zhao Z, Liu X, Kendrick KM, Zhu C, Becker B. Functional near-infrared spectroscopy-informed neurofeedback: regional-specific modulation of lateral orbitofrontal activation and cognitive flexibility. Neurophotonics. 2019 Apr;6(2):025011. doi: 10.1117/1.NPh.6.2.025011. Epub 2019 Jun 8. — View Citation

Marzbani H, Marateb HR, Mansourian M. Neurofeedback: A Comprehensive Review on System Design, Methodology and Clinical Applications. Basic Clin Neurosci. 2016 Apr;7(2):143-58. doi: 10.15412/J.BCN.03070208. — View Citation

Mathersul D, Williams LM, Hopkinson PJ, Kemp AH. Investigating models of affect: relationships among EEG alpha asymmetry, depression, and anxiety. Emotion. 2008 Aug;8(4):560-72. doi: 10.1037/a0012811. — View Citation

Meeks TW, Vahia IV, Lavretsky H, Kulkarni G, Jeste DV. A tune in "a minor" can "b major": a review of epidemiology, illness course, and public health implications of subthreshold depression in older adults. J Affect Disord. 2011 Mar;129(1-3):126-42. doi: 10.1016/j.jad.2010.09.015. — View Citation

Mochcovitch MD, da Rocha Freire RC, Garcia RF, Nardi AE. A systematic review of fMRI studies in generalized anxiety disorder: evaluating its neural and cognitive basis. J Affect Disord. 2014;167:336-42. doi: 10.1016/j.jad.2014.06.041. Epub 2014 Jul 2. Erratum In: J Affect Disord. 2014 Oct;167():259-60. — View Citation

Norton PJ. Depression Anxiety and Stress Scales (DASS-21): psychometric analysis across four racial groups. Anxiety Stress Coping. 2007 Sep;20(3):253-65. doi: 10.1080/10615800701309279. — View Citation

Peeters F, Oehlen M, Ronner J, van Os J, Lousberg R. Neurofeedback as a treatment for major depressive disorder--a pilot study. PLoS One. 2014 Mar 18;9(3):e91837. doi: 10.1371/journal.pone.0091837. eCollection 2014. — View Citation

Renard, Y., Lotte, F., Gibert, G., Congedo, M., Maby, E., Delannoy, V., ... & Lécuyer, A. (2010). Openvibe: An open-source software platform to design, test, and use brain-computer interfaces in real and virtual environments. Presence, 19(1), 35-53.

Richard E, Reitz C, Honig LH, Schupf N, Tang MX, Manly JJ, Mayeux R, Devanand D, Luchsinger JA. Late-life depression, mild cognitive impairment, and dementia. JAMA Neurol. 2013 Mar 1;70(3):374-82. doi: 10.1001/jamaneurol.2013.603. — View Citation

Ros T, Enriquez-Geppert S, Zotev V, Young KD, Wood G, Whitfield-Gabrieli S, Wan F, Vuilleumier P, Vialatte F, Van De Ville D, Todder D, Surmeli T, Sulzer JS, Strehl U, Sterman MB, Steiner NJ, Sorger B, Soekadar SR, Sitaram R, Sherlin LH, Schonenberg M, Scharnowski F, Schabus M, Rubia K, Rosa A, Reiner M, Pineda JA, Paret C, Ossadtchi A, Nicholson AA, Nan W, Minguez J, Micoulaud-Franchi JA, Mehler DMA, Luhrs M, Lubar J, Lotte F, Linden DEJ, Lewis-Peacock JA, Lebedev MA, Lanius RA, Kubler A, Kranczioch C, Koush Y, Konicar L, Kohl SH, Kober SE, Klados MA, Jeunet C, Janssen TWP, Huster RJ, Hoedlmoser K, Hirshberg LM, Heunis S, Hendler T, Hampson M, Guggisberg AG, Guggenberger R, Gruzelier JH, Gobel RW, Gninenko N, Gharabaghi A, Frewen P, Fovet T, Fernandez T, Escolano C, Ehlis AC, Drechsler R, Christopher deCharms R, Debener S, De Ridder D, Davelaar EJ, Congedo M, Cavazza M, Breteler MHM, Brandeis D, Bodurka J, Birbaumer N, Bazanova OM, Barth B, Bamidis PD, Auer T, Arns M, Thibault RT. Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist). Brain. 2020 Jun 1;143(6):1674-1685. doi: 10.1093/brain/awaa009. — View Citation

Shibasaki H. Human brain mapping: hemodynamic response and electrophysiology. Clin Neurophysiol. 2008 Apr;119(4):731-43. doi: 10.1016/j.clinph.2007.10.026. Epub 2008 Jan 9. — View Citation

Sitaram R, Ros T, Stoeckel L, Haller S, Scharnowski F, Lewis-Peacock J, Weiskopf N, Blefari ML, Rana M, Oblak E, Birbaumer N, Sulzer J. Closed-loop brain training: the science of neurofeedback. Nat Rev Neurosci. 2017 Feb;18(2):86-100. doi: 10.1038/nrn.2016.164. Epub 2016 Dec 22. Erratum In: Nat Rev Neurosci. 2019 May;20(5):314. — View Citation

Snyder HR, Miyake A, Hankin BL. Advancing understanding of executive function impairments and psychopathology: bridging the gap between clinical and cognitive approaches. Front Psychol. 2015 Mar 26;6:328. doi: 10.3389/fpsyg.2015.00328. eCollection 2015. — View Citation

Snyder HR. Major depressive disorder is associated with broad impairments on neuropsychological measures of executive function: a meta-analysis and review. Psychol Bull. 2013 Jan;139(1):81-132. doi: 10.1037/a0028727. Epub 2012 May 28. — View Citation

Steenland K, Karnes C, Seals R, Carnevale C, Hermida A, Levey A. Late-life depression as a risk factor for mild cognitive impairment or Alzheimer's disease in 30 US Alzheimer's disease centers. J Alzheimers Dis. 2012;31(2):265-75. doi: 10.3233/JAD-2012-111922. — View Citation

Steingrimsson S, Bilonic G, Ekelund AC, Larson T, Stadig I, Svensson M, Vukovic IS, Wartenberg C, Wrede O, Bernhardsson S. Electroencephalography-based neurofeedback as treatment for post-traumatic stress disorder: A systematic review and meta-analysis. Eur Psychiatry. 2020 Jan 31;63(1):e7. doi: 10.1192/j.eurpsy.2019.7. — View Citation

Szymkowicz SM, Woods AJ, Dotson VM, Porges EC, Nissim NR, O'Shea A, Cohen RA, Ebner NC. Associations between subclinical depressive symptoms and reduced brain volume in middle-aged to older adults. Aging Ment Health. 2019 Jul;23(7):819-830. doi: 10.1080/13607863.2018.1432030. Epub 2018 Jan 30. — View Citation

Tong, A. Y., & Man, D. W. (2002). The validation of the Hong Kong Chinese version of the Lawton Instrumental Activities of Daily Living Scale for institutionalized elderly persons. OTJR: Occupation, Participation and Health, 22(4), 132-142.

Trambaiolli LR, Cassani R, Mehler DMA, Falk TH. Neurofeedback and the Aging Brain: A Systematic Review of Training Protocols for Dementia and Mild Cognitive Impairment. Front Aging Neurosci. 2021 Jun 9;13:682683. doi: 10.3389/fnagi.2021.682683. eCollection 2021. — View Citation

Trambaiolli LR, Kohl SH, Linden DEJ, Mehler DMA. Neurofeedback training in major depressive disorder: A systematic review of clinical efficacy, study quality and reporting practices. Neurosci Biobehav Rev. 2021 Jun;125:33-56. doi: 10.1016/j.neubiorev.2021.02.015. Epub 2021 Feb 12. — View Citation

van der Kolk BA, Hodgdon H, Gapen M, Musicaro R, Suvak MK, Hamlin E, Spinazzola J. A Randomized Controlled Study of Neurofeedback for Chronic PTSD. PLoS One. 2016 Dec 16;11(12):e0166752. doi: 10.1371/journal.pone.0166752. eCollection 2016. Erratum In: PLoS One. 2019 Apr 24;14(4):e0215940. — View Citation

Veale JF. Edinburgh Handedness Inventory - Short Form: a revised version based on confirmatory factor analysis. Laterality. 2014;19(2):164-77. doi: 10.1080/1357650X.2013.783045. Epub 2013 May 10. — View Citation

Wager TD, Davidson ML, Hughes BL, Lindquist MA, Ochsner KN. Prefrontal-subcortical pathways mediating successful emotion regulation. Neuron. 2008 Sep 25;59(6):1037-50. doi: 10.1016/j.neuron.2008.09.006. — View Citation

Wang SY, Lin IM, Fan SY, Tsai YC, Yen CF, Yeh YC, Huang MF, Lee Y, Chiu NM, Hung CF, Wang PW, Liu TL, Lin HC. The effects of alpha asymmetry and high-beta down-training neurofeedback for patients with the major depressive disorder and anxiety symptoms. J Affect Disord. 2019 Oct 1;257:287-296. doi: 10.1016/j.jad.2019.07.026. Epub 2019 Jul 5. — View Citation

Wong A, Xiong YY, Kwan PW, Chan AY, Lam WW, Wang K, Chu WC, Nyenhuis DL, Nasreddine Z, Wong LK, Mok VC. The validity, reliability and clinical utility of the Hong Kong Montreal Cognitive Assessment (HK-MoCA) in patients with cerebral small vessel disease. Dement Geriatr Cogn Disord. 2009;28(1):81-7. doi: 10.1159/000232589. Epub 2009 Aug 11. — View Citation

Wu, C. H., & Yao, G. (2006). Analysis of factorial invariance across gender in the Taiwan version of the Satisfaction with Life Scale. Personality and Individual Differences, 40(6), 1259-1268.

Yeung MK, Lee TL, Chan AS. Depressive and anxiety symptoms are related to decreased lateral prefrontal cortex functioning during cognitive control in older people. Biol Psychol. 2021 Nov;166:108224. doi: 10.1016/j.biopsycho.2021.108224. Epub 2021 Nov 14. — View Citation

Yeung MK, Lee TL, Chan AS. Frontal lobe dysfunction underlies the differential word retrieval impairment in adolescents with high-functioning autism. Autism Res. 2019 Apr;12(4):600-613. doi: 10.1002/aur.2082. Epub 2019 Feb 13. — View Citation

Yeung MK, Lee TL, Chan AS. Negative mood is associated with decreased prefrontal cortex functioning during working memory in young adults. Psychophysiology. 2021 Jun;58(6):e13802. doi: 10.1111/psyp.13802. Epub 2021 Mar 4. — View Citation

Yeung MK, Lee TL, Chan AS. Right-lateralized frontal activation underlies successful updating of verbal working memory in adolescents with high-functioning autism spectrum disorder. Biol Psychol. 2019 Nov;148:107743. doi: 10.1016/j.biopsycho.2019.107743. Epub 2019 Aug 22. — View Citation

Yeung MK, Sze SL, Woo J, Kwok T, Shum DH, Yu R, Chan AS. Altered Frontal Lateralization Underlies the Category Fluency Deficits in Older Adults with Mild Cognitive Impairment: A Near-Infrared Spectroscopy Study. Front Aging Neurosci. 2016 Mar 29;8:59. doi: 10.3389/fnagi.2016.00059. eCollection 2016. — View Citation

Yeung MK, Sze SL, Woo J, Kwok T, Shum DH, Yu R, Chan AS. Reduced Frontal Activations at High Working Memory Load in Mild Cognitive Impairment: Near-Infrared Spectroscopy. Dement Geriatr Cogn Disord. 2016;42(5-6):278-296. doi: 10.1159/000450993. Epub 2016 Oct 27. — View Citation

Yochim, B. P., Mueller, A. E., June, A., & Segal, D. L. (2010). Psychometric properties of the geriatric anxiety scale: comparison to the beck anxiety inventory and geriatric anxiety inventory. Clinical Gerontologist, 34(1), 21-33.

Zilverstand A, Sorger B, Sarkheil P, Goebel R. fMRI neurofeedback facilitates anxiety regulation in females with spider phobia. Front Behav Neurosci. 2015 Jun 8;9:148. doi: 10.3389/fnbeh.2015.00148. eCollection 2015. — View Citation

* Note: There are 62 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Mood symptoms (post)	Change in the HADS depression score (The Hospital Anxiety and Depression Scale (HADS) depression score has a minimum value of 0 and a maximum value of 21. Higher scores indicate a worse outcome. A score of 0-7 indicates normal, 8-10 indicates mild depression, 11-14 indicates borderline depression, and 15-21 indicates depression.)	Within 1 week before the first training session, and within 1 week after the last training session
Primary	Mood symptoms (follow-up)	Change in the HADS depression score at follow up (The Hospital Anxiety and Depression Scale (HADS) depression score has a minimum value of 0 and a maximum value of 21. Higher scores indicate a worse outcome. A score of 0-7 indicates normal, 8-10 indicates mild depression, 11-14 indicates borderline depression, and 15-21 indicates depression.)	Within 1 week before the first training session, and within 1 month after the last training session
Primary	Anxiety symptoms (post)	Change in the HADS anxiety score (The Hospital Anxiety and Depression Scale (HADS) anxiety score has a minimum value of 0 and a maximum value of 21. Higher scores indicate a worse outcome. A score of 0-7 indicates normal, 8-10 indicates mild anxiety, 11-14 indicates borderline anxiety, and 15-21 indicates anxiety.)	Within 1 week before the first training session, and within 1 week after the last training session
Primary	Anxiety symptoms (follow-up)	Change in the HADS anxiety score at follow-up (The Hospital Anxiety and Depression Scale (HADS) anxiety score has a minimum value of 0 and a maximum value of 21. Higher scores indicate a worse outcome. A score of 0-7 indicates normal, 8-10 indicates mild anxiety, 11-14 indicates borderline anxiety, and 15-21 indicates anxiety.)	Within 1 week before the first training session, and within 1 month after the last training session
Secondary	Stroop (post; RT)	Change in Stroop mean reaction time	Within 1 week before the first training session, and within 1 week after the last training session
Secondary	Stroop (follow-up; RT)	Change in Stroop mean reaction time at follow-up	Within 1 week before the first training session, and within 1 month after the last training session
Secondary	Stroop (post; accuracy)	Change in Stroop accuracy	Within 1 week before the first training session, and within 1 week after the last training session
Secondary	Stroop (follow-up; accuracy)	Change in Stroop accuracy at follow-up	Within 1 week before the first training session, and within 1 month after the last training session
Secondary	Stroop (post; fNIRS)	Change in mean change in oxyhemoglobin concentration measured by fNIRS	Within 1 week before the first training session, and within 1 week after the last training session
Secondary	Stroop (follow-up; fNIRS)	Change in mean change in oxyhemoglobin concentration measured by fNIRS at follow-up	Within 1 week before the first training session, and within 1 month after the last training session
Secondary	Stroop (post; EEG)	Change in stimulus-locked N450 amplitude measured by EEG	Within 1 week before the first training session, and within 1 week after the last training session
Secondary	Stroop (follow-up; EEG)	Change in stimulus-locked N450 amplitude measured by EEG at follow-up	Within 1 week before the first training session, and within 1 month after the last training session
Secondary	n-back (post; RT)	Change in n-back mean reaction time	Within 1 week before the first training session, and within 1 week after the last training session
Secondary	n-back (follow-up; RT)	Change in n-back mean reaction time at follow-up	Within 1 week before the first training session, and within 1 month after the last training session
Secondary	n-back (post; accuracy)	Change in n-back accuracy	Within 1 week before the first training session, and within 1 week after the last training session
Secondary	n-back (follow-up; accuracy)	Change in n-back accuracy at follow-up	Within 1 week before the first training session, and within 1 month after the last training session
Secondary	n-back (post; fNIRS)	Change in mean change in oxyhemoglobin concentration measured by fNIRS	Within 1 week before the first training session, and within 1 week after the last training session
Secondary	n-back (follow-up; fNIRS)	Change in mean change in oxyhemoglobin concentration measured by fNIRS at follow-up	Within 1 week before the first training session, and within 1 month after the last training session
Secondary	n-back (post; EEG)	Change in stimulus-locked P300 amplitude measured by EEG at follow-up	Within 1 week before the first training session, and within 1 week after the last training session
Secondary	n-back (follow-up; EEG)	Change in stimulus-locked P300 amplitude measured by EEG at follow-up	Within 1 week before the first training session, and within 1 month after the last training session