Neurofeedback Training to Improve Prefrontal Functioning in Older Adults With Subclinical Depression and Anxiety: a Randomised Control Trial
Phase: NA
Conditions: Depression, Anxiety
Sponsor: The Hong Kong Polytechnic University

NEUROFEEDBACK TRAINING FOR OLDER ADULTS 
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Neurofeedback training to 
improve prefrontal functioning 
in older adults with subclinical 
depression and anxiety: a 
randomised control trial  
HSEARS20221103002  
29-06-2023 
 

NEUROFEEDBACK TRAINING FOR OLDER ADULTS 
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a) Project title: Neurofeedback training to improve prefrontal functioning in older adults with 
subclinical depression and anxiety: a randomised control trial 
b) Research Team: PI: David Shum (PolyU); Co-PI: Michael Yeung (EdUHK), Sally Cao 
(PolyU); Co-Is: Kenneth Fong (PolyU), Bolton Chau (PolyU), Georg Kranz (PolyU), Tomas Ros 
(University of Geneva), and Stefanie Enriquez-Geppert (University of Groningen), Jacqueline 
Chan (PolyU) 
c) Proposed Commencement and End Date: 1 January 2023–31 March 2024 (15 months) 
d) Project 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. 
e) Keywords: depression, anxiety, neurofeedback, prefrontal cortex 
f) Introduction/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 (Bryant et al., 2008; Meeks et al., 2011). These symptoms strongly correlate with each 
other and frequently co-occur in older adults (Beekman et al., 2000; Yochim et al., 2010). In 
older adults without any psychiatric disorder, subclinical depression and anxiety are associated 
with a poor quality of life, adverse health outcomes, cognitive deficits, and self-reported 
functional impairments similar to those seen in patients with mood and anxiety disorders 
(Beaudreau & O’Hara, 2008; Haigh et al., 2018; Laborde-Lahoz et al., 2015; Meeks et al., 2011). 
Most concerningly, 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 (Richard et al., 2013; Steenland 
et al., 2012). Thus, interventions for older people with elevated subclinical symptoms of 
depression and anxiety are crucial for preventing affective disorders and dementia late in life. 
Although the public is highly aware of measures to prevent physical illnesses (e.g., 
vaccination, medication), prevention of mental illnesses in the context of geriatric care has 
been neglected, and effective interventions for subclinical depression and anxiety in older 
adults remain elusive. For example, a meta-analysis of six psychotherapy studies on subclinical 
depression in older adults identified only a small effect-size improvement from psychotherapies 
relative to control interventions (Cuijpers et al., 2014). 
During negative emotional experiences, the prefrontal cortex (PFC) plays a pivotal role in 
downregulating activity in the amygdala and other limbic regions (Etkin et al., 2015; Wager et 

NEUROFEEDBACK TRAINING FOR OLDER ADULTS 
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al., 2008). PFC dysfunction may cause the amygdala to become overactivated and dysregulated, 
resulting in mood and anxiety symptoms. This prefrontal–subcortical model has received 
extensive support from neuropsychological and neuroimaging studies of mood and anxiety 
disorders (Grahek et al., 2019; Mochcovitch et al., 2014; Snyder, 2013; Snyder et al., 2015). Our 
and others’ work also supports the utility of this model for studying subclinical depression 
and anxiety (Mathersul et al., 2008; Szymkowicz et al., 2019; Yeung et al., 2021a, b). For 
example, our recent study showed similar negative relationships between PFC functioning and 
symptoms of depression and anxiety in non-psychiatric older adults (Yeung et al., 2021a). 
In humans, emotion is addressed by the frontal asymmetry model, which posits that the left and 
right frontal lobes mediate positive emotion/approach behaviour and negative emotion/ 
withdrawal behaviour, respectively. In keeping with this model, converging evidence indicates 
that mood and anxiety symptoms are primarily associated with reduced left frontal activity and 
increased right frontal activity, respectively, and both are related to a reduction in left-
asymmetric frontal activity in resting and task states in both clinical and general populations 
(Adoph & Margraf, 2017; Bruder et al., 2017; Mathersul et al., 2008). Therefore, improving 
PFC function, particularly restoring frontal asymmetry, represents a promising trajectory 
for enhancing the mental health and cognitive function of older adults with subclinical 
depression and anxiety. To date, this has remained an unexplored area in neuroscience research 
on ageing. 
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 (Hammond, 
2011; Sitaram et al., 2017). 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 (Hammond, 2005; Marzbani et al., 2016). Randomised controlled trials 
have shown that compared with placebo, approximately eight sessions of EEG neurofeedback 
training, often intended to increase the symmetry of frontal alpha power, can significantly reduce 
symptoms across mood and anxiety disorders (Trambaiolli et al., 2021). According to two meta-
analyses, the estimated effect sizes of the improvement in symptoms of depression or anxiety 
ranged from large to very large (Fernández-Álvarez et al., 2020; Steingrimsson et al., 2020), 
which are similar to, if not greater than, the medium-size effects for pharmacological treatment 
vs. placebo controls (Kirsch et al., 2008). In older adults, a recent systematic review showed that 
most studies (N = 14) reported positive immediate effects of regimens comprising approximately 
8 sessions of EEG neurofeedback training in at least one cognitive domain (Laborda-Sánchez & 
Cansino, 2021). However, the literature is limited by the lack of randomised controlled 
trials with follow-up. The effect of EEG neurofeedback training on negative affective 
symptoms in older adults also remains unclear. 
In recent years, interest in using fNIRS (in which our team has expertise, e.g., Yeung et al., 
2016a, b, 2019a, b, 2021a, b) to deliver neurofeedback training has grown (Ehlis et al., 2018; 
Kohl et al., 2020). The underlying mechanism of such training with fNIRS is different from that 
of training with EEG. Whereas EEG neurofeedback training involves self-regulation of the 

NEUROFEEDBACK TRAINING FOR OLDER ADULTS 
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synchronous activity of neuronal populations, fNIRS neurofeedback training focuses on self-
regulation of the haemodynamic response elicited by neuronal activity. Compared with EEG, 
fNIRS has a lower temporal resolution but a higher spatial resolution and is more resilient to 
movement artifacts. As such, fNIRS can increase the convenience of neurofeedback training 
and allow for the regulation of brain activity at more localised sites (e.g., the dorsolateral 
PFC). Some studies have observed successful regulation of frontal haemodynamics after only 
one fNIRS neurofeedback session in young and/or older adults (Kober et al., 2019; Li et al., 
2019). Hence, fNIRS neurofeedback training may increase the pace of learning and require fewer 
sessions than its EEG counterpart (Kohl et al., 2020). In addition, one recent study showed that 
patients with social anxiety disorder had reduced anxiety symptoms after fNIRS neurofeedback 
training (Kimmig et al., 2019). Nevertheless, whether and to what extent fNIRS 
neurofeedback training improves mental health and cognitive functions in older adults 
with subclinical depression and anxiety remain to be demonstrated. 
g) Objectives: 
The aim of this proposed project will be to compare the mood- and cognitive-enhancing effects 
of 8 sessions of prefrontal EEG and fNIRS neurofeedback training programmes in older adults 
with subclinical depression and anxiety through a randomised controlled trial. We planned to 
compare EEG and fNIRS neurofeedback because in principle they act on two different aspects of 
brain function. Because electrical activity and hemodynamic activity in the brain have a non-
perfect relationship (Shibasaki, 2008), the two neurofeedback methods may yield varying effects. 
In addition, we chose EEG and fNIRS because they are the only two existing neuroimaging 
methods that allow for real-time human-computer interactions conducted through a wearable 
system. The findings will provide crucial knowledge about whether prefrontal neurofeedback 
training can reduce the risks of affective disorders and accelerated cognitive decline in old age 
(Steenland et al., 2012; Richard et al., 2013). 
Three objectives are set, as follows: 
1) To elucidate whether EEG and fNIRS neurofeedback training programmes improve the 
mental health of older adults with subclinical depression and anxiety; 
2) To determine whether EEG and fNIRS neurofeedback training programmes enhance the 
frontal cognitive functions of older adults with subclinical depression and anxiety; and 
3) To compare the relative effectiveness of these two programmes based on different neural 
mechanisms in enhancing the mental health and cognitive functions of older adults with 
subclinical depression and anxiety. 
h) 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 
(CRED-nf; Ros et al., 2020). 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 

NEUROFEEDBACK TRAINING FOR OLDER ADULTS 
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complete a neurophysiological assessment (1) before, (2) immediately after, and (3) 1 month 
after the intervention (see Appendix I).  
Participants: Ninety older adults without dementia will be recruited via advertisements at PolyU 
and community centres for older adults. The inclusion criteria will be as follows: (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 (Gomez, Summers, Summers, Wolf, 
& Summers, 2014; Norton, 2007); (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 text; (viii) normal or corrected-to-normal 
vision; and (ix) a score of at least 19 on the Hong Kong Montreal Cognitive Assessment (HK-
MoCA; Wong et al., 2009). 
The inclusion criteria that we planned to use were based on those employed by prefrontal 
neurofeedback studies in mood or anxiety disorders (e.g., Kimmig et al., 2019; Peeters et al., 
2014). Conventionally, participants are selected based on a certain threshold of depressive or 
anxiety symptoms, or the clinical diagnosis; 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. 
The proposed sample size was determined based on randomised controlled trials on 
neurofeedback training for mood/anxiety disorders, which collectively reported a weighted mean 
Cohen’s f of 0.59 for the group × time interaction on the scores for depression, anxiety, and/or 
post-traumatic stress [(0.37 × 90 + 0.88 × 24 + 0.89 × 44 + 0.63 × 18)/(90 + 24 + 44 + 18)] (Lee 
et al., 2019; van der Kolk et al., 2016; Wang et al., 2019; Zilverstand et al., 2015). Accordingly, 
a power analysis (G*Power v3.1.9.4) indicated that 14 participants per group will be required to 
detect any significant differences between the three groups based on a power of 0.80 and an 
alpha level of 0.017 (three outcome measures per data type). We expect a smaller effect size for 
subclinical populations and a loss of participant data due to dropouts and unusable data. As such, 
we will recruit 30 individuals per group. 
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 8 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 (Kohl et al., 2020). In addition, the participants will undertake several 
experimental tasks under simultaneous EEG–fNIRS recording and complete several 
questionnaires at three 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 (Laborda-Sánchez & Cansino, 
2021; Trambaiolli et al., 2021; Yeung & Chan, 2021). Therefore, we 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 FOR OLDER ADULTS 
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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 25-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 to the training group. 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 (Kothe, 2014) and OpenVibe (Renard et al., 2010) according to 
published guidelines (Kohl et al., 2020) (see the Appendix I for the detailed signal processing 
pipelines).  
Neurophysiological Assessment: A 1.5-h neurophysiological assessment will be administered at 
each of three 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 (Gomez et al., 2014; Norton, 
2007); the Hospital Anxiety and Depression Scale (HADS; Chinese version) to measure their 
signs of anxiousness and depression during the previous week (Flint & Rifat, 2002);  the 
Pittsburgh Sleep Quality Index to measure their sleep quality over the last month (Buysse et al., 
1989); the Satisfaction with Life Scale (Chinese version) to quantify their general life 
satisfaction (Wu & Yao, 2006); and Lawton Instrumental Activities of Daily Living Scale 
(IADL; Chinese version) to assess independent living skills (Tong & Man, 2002). The 
participants will also complete three computerised tasks to assess different components of frontal 
cognitive function (see below) under simultaneous EEG–fNIRS measurements, using the same 
setup described for neurofeedback training. At the first visit, the participants will also complete 
the HK-MoCA to screen for dementia (Wong et al., 2009). Immediately after the intervention, 
they will be asked whether they know their treatment group assignment to check the strength of 
blinding. 

NEUROFEEDBACK TRAINING FOR OLDER ADULTS 
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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 (Barry & De Blasio, 2017). It 
requires participants to maintain their eyes open for 3 minutes. The Emotional Stroop task is 
used to assess inhibitory control (Imbir et al., 2022). 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 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 (Yeung et al., 2016b, 2019b). 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 reaction time (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 (Ros et al., 2020). Linear mixed models with group 
(sham, EEG, fNIRS), time (baseline, post, follow-up), and condition (easy, difficult) as the fixed 
factors; age and education years as covariates; and the subject as a random factor will be used to 
analyse the behavioural, fNIRS, and EEG data. We 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, we will evaluate differences in pre–post changes in mental 
health and cognitive functions between the two real training groups to address Objective 3. 
Moreover, we 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. 
 
 
 

NEUROFEEDBACK TRAINING FOR OLDER ADULTS 
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Appendix: 
Appendix I: Experimental design.  
 
 
For both modalities, features will be extracted online using a Hamming window function applied 
to 2-s moving window epochs (with 0.2-s sliding windows). For EEG groups, the automated 
subspace reconstruction (ASR) method will first be applied to the 3-minute baseline EEG 
recording to derive a filter for artifact correction for the rest of the session. Before calibrating the 
ASR filter, a 0.5-Hz highpass filter will be applied for zero-centreing, and data will be re-
referenced to the average of the two earlobes. During training, the ASR filter will be used to 
remove ocular and muscle artifacts. To yield the target index, an 8–13-Hz bandpass filter will be 
applied to extract EEG power in the alpha band, and after log transformation, the alpha power at 
F4 will be subtracted from that at F3 to yield the frontal alpha asymmetry index. 
For fNIRS, raw signals will be converted to optical density changes and then to changes in HbO 
and deoxyhaemoglobin concentration (Delpy et al., 1988). Correlation-based signal improvement 
that considers both HbO and HbR changes will be used to remove movement artifacts (Cui et al., 
2010). Short-separation channels will be subtracted from long-separation channels to remove 
global physiological confounders, and the CBSI-HbO signals will be averaged across long-

NEUROFEEDBACK TRAINING FOR OLDER ADULTS 
15 
separation channels for each hemisphere. The difference in mean changes in frontal CBSI-HbO 
between hemispheres will be generated.