Is neurofeedback effective for depression?

Is neurofeedback effective for depression?

Can neurofeedback support depression treatment? Explore the evidence, mechanisms and limits of this emerging, non-invasive brain-based approach.

Overview.

Depression affects an estimated 4% of the global population, around 332 million people worldwide [1]. Beyond persistent low mood, depressive disorder is strongly associated with rumination and impaired emotional regulation, which contribute to symptom persistence and relapse. Neurofeedback has emerged as a non-invasive approach aiming to help individuals regulate their own brain activity. But how effective is neurofeedback for depression, and what does current scientific evidence actually show? Let’s find out.

Key takeaways.

Neurofeedback is a closed-loop brain training method that uses real-time neural signals to reinforce adaptive brain states through learning mechanisms.

In depression treatment, neurofeedback targets neural dysregulation linked to rumination, particularly within large-scale networks such as the Default Mode Network (DMN).

Current evidence suggests that neurofeedback may reduce depressive symptoms in some individuals, particularly by targeting neural processes such as rumination.

Treatment response appears to depend on individual brain patterns and engagement, highlighting the importance of personalised approaches.

Neurofeedback should be considered a complementary intervention, not a cure, used alongside established treatments such as psychotherapy or medication.

01

What is neurofeedback?

Activation map for Upregulation versus View in the experimental group from the study Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback
Figures shown in the study Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback [4]. (A) Activation map for Upregulation versus View in the experimental group (pcorrected = 0.01), (B) activation map masked by amygdala.

Definition.

Neurofeedback is defined as a non-invasive method that provides real-time feedback on brain activity, typically measured using electroencephalography (EEG) or functional MRI (fMRI) [2].

This activity is translated into visual, auditory or immersive signals, allowing individuals to observe and gradually regulate patterns associated with different mental states. The process relies on a closed-loop system, where specific brain activity is reinforced through immediate feedback, supporting learning via neuroplasticity.

Neurofeedback is therefore considered a form of self-regulation training, rather than a direct intervention on brain chemistry. Experimental studies suggest it can induce measurable changes in brain function, particularly in networks involved in emotional regulation [3][4].

02

How does neurofeedback help with depression?

Large-Scale Network Dysfunction in Major Depressive Disorder meta-analysis results
Figure shown in the study Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity [6]. The results present regions in which abnormal resting-state functional connectivity (rsFC) was observed in individuals with MDD as compared to healthy controls.

Neural mechanisms.

Depression is associated with altered activity in brain networks involved in self-referential thinking, emotional regulation and attention. More broadly, neurocognitive models suggest that depression involves interactions between cognitive biases, emotional dysregulation and underlying neural circuitry [5].

In particular, large-scale network dysfunction has been observed in major depressive disorders, affecting interactions between the Default Mode Network (DMN), salience network and executive control networks [6].

Hyperactivity of the Default Mode Network has been linked to persistent rumination, a maladaptive pattern of repetitive negative thinking that contributes to symptom maintenance and relapse [7][8].

Neurofeedback aims to modulate these processes by helping individuals:

reduce maladaptive self-focused thinking;

improve attentional flexibility;

regulate emotional responses.

Experimental studies have shown that patients can learn to regulate activity in specific brain regions, such as the amygdala or prefrontal cortex, which are central to emotional processing [9][10].

Recent research further suggests that clinical response may depend on whole-brain activation patterns during training, rather than a single targeted region [11].

03

What does the scientific literature say about neurofeedback and depression?

Research into neurofeedback for depression has expanded in recent years, with studies exploring both EEG-based and fMRI-based approaches.

Evidence of clinical effects.

A meta-analysis of biofeedback and neurofeedback interventions reported moderate reductions in depressive symptoms, particularly in controlled trials [12].

More recent systematic reviews focusing on fMRI-based neurofeedback indicate that patients can learn to regulate brain activity, with associated improvements in mood [13].

Experimental studies findings.

Experimental studies have shown that:

patients can learn to regulate emotion-related brain regions such as the amygdala [6][7];

changes in functional connectivity may be associated with symptom improvement [14].

Key limitations.

Despite promising results, several limitations remain in the studies so far:

relatively small sample sizes;

heterogeneity of protocols and targets;

variability in outcome measures.

Another important consideration is the role of non-specific effects. Some studies using so-called sham neurofeedback (where participants receive feedback not directly linked to their own brain activity) have shown that part of the observed improvements may be related to factors such as expectation, motivation or the therapeutic context itself [15].

This does not invalidate neurofeedback for depression, but highlights the complexity of isolating its specific effects and the importance of well-controlled clinical trials.

04

Can neurofeedback replace antidepressants or psychotherapy?

HDRS-17 scores showing neurofeedback produced clinical improvement not seen in the imagery control group
Figure shown in the study Real-time self-regulation of emotion networks in patients with depression [9]. Neurofeedback (NF) produced clinical improvement on the 17-item Hamilton Depression Rating scale that was not seen in the imagery (IM) control group.

Complementary role.

Neurofeedback is not intended to replace established treatments such as antidepressants or psychotherapy.

Current clinical guidelines recommend evidence-based approaches such as cognitive behavioural therapy (CBT), pharmacological treatment or a combination of both, depending on the severity of the depressive symptoms. These methods have demonstrated efficacy across a wide range of depressive and anxiety disorders [16].

However, a significant proportion of patients do not respond fully to first-line treatments such as antidepressants or psychotherapy, which has led to growing interest in complementary approaches such as neurofeedback [11].

In this context, neurofeedback may be used as an adjunctive intervention, targeting specific neural and cognitive processes such as rumination or attentional control [15].

05

What are the limitations and precautions regarding neurofeedback therapy for depression?

Precautions.

While neurofeedback is generally considered safe, several limitations should be acknowledged.

First, clinical response is highly variable. Recent research shows that outcomes may depend on individual brain activation patterns during training, highlighting the need for personalised approaches [11].

Second, neurofeedback requires repeated sessions and active engagement. Outcomes may depend on individual factors such as motivation and learning capacity.

Third, it should not be used as a substitute for medical care, particularly in moderate to severe depression. A comprehensive clinical evaluation remains essential throughout the process.

06

Why combine neurofeedback with virtual reality and mindfulness for depression?

Neuromind VR headset with EEG sensors and dashboard for neurofeedback-based depression treatment

Neuromind approach.

At Neuromind, we have developed a multimodal neuromodulation approach targeting the Default Mode Network overactivity that drives relapse. Our platform combines wearable EEG sensors, artificial intelligence and immersive virtual reality within a closed-loop system.

By integrating neurofeedback with immersive environments and principles derived from mindfulness-based cognitive therapy (MBCT), our aim is to help individuals disengage from maladaptive self-referential thought patterns and improve emotional regulation.

Virtual reality enhances engagement and provides adaptive, real-time feedback, while mindfulness-based approaches are supported by strong evidence in relapse prevention in depression [17].

Integrating neurofeedback with VR, as well as mindfulness, may therefore provide a more comprehensive approach, targeting both neural activity and cognitive processes involved in depression.

Therefore, Neuromind is designed as a precision augmentation layer that:

provides clinicians an objective, real-time view into the neurophysiological states associated with relapse vulnerability;

offers patients an active tool to strengthen the regulatory capacities that help prevent recurrence.

 

If your institution is working on depression relapse prevention, DMN-targeted interventions, digital therapeutics or neurofeedback-augmented psychotherapy, we would be delighted to explore a partnership.

Neurofeedback provides a real-time window on brain activity, which may help individuals learn to regulate patterns associated with rumination, attention and emotional processing.

References

[1] World Health Organization, Depressive disorder (depression) fact sheet, 2025.

[2] 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. doi: 10.1038/s41583-019-0161-1. PMID: 28003656.

[3] Ros T, Frewen P, Théberge J, Michela A, Kluetsch R, Mueller A, Candrian G, Jetly R, Vuilleumier P, Lanius RA. Neurofeedback Tunes Scale-Free Dynamics in Spontaneous Brain Activity. Cereb Cortex. 2017 Oct 1;27(10):4911-4922. doi: 10.1093/cercor/bhw285. PMID: 27620975.

[4] Dehghani A, Soltanian-Zadeh H, Hossein-Zadeh GA. Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback. Front Hum Neurosci. 2023 Jan 6;16:988890. doi: 10.3389/fnhum.2022.988890. PMID: 36684847; PMCID: PMC9853008.

[5] Disner SG, Beevers CG, Haigh EA, Beck AT. Neural mechanisms of the cognitive model of depression. Nat Rev Neurosci. 2011 Jul 6;12(8):467-77. doi: 10.1038/nrn3027. PMID: 21731066.

[6] Kaiser RH, Andrews-Hanna JR, Wager TD, Pizzagalli DA. Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity. JAMA Psychiatry. 2015 Jun;72(6):603-11. doi: 10.1001/jamapsychiatry.2015.0071. PMID: 25785575; PMCID: PMC4456260.

[7] Hamilton JP, Farmer M, Fogelman P, Gotlib IH. Depressive Rumination, the Default-Mode Network, and the Dark Matter of Clinical Neuroscience. Biol Psychiatry. 2015 Aug 15;78(4):224-30. doi: 10.1016/j.biopsych.2015.02.020. Epub 2015 Feb 24. PMID: 25861700; PMCID: PMC4524294.

[8] Nolen-Hoeksema S, Wisco BE, Lyubomirsky S. Rethinking Rumination. Perspect Psychol Sci. 2008 Sep;3(5):400-24. doi: 10.1111/j.1745-6924.2008.00088.x. PMID: 26158958.

[9] Linden DE, Habes I, Johnston SJ, Linden S, Tatineni R, Subramanian L, Sorger B, Healy D, Goebel R. Real-time self-regulation of emotion networks in patients with depression. PLoS One. 2012;7(6):e38115. doi: 10.1371/journal.pone.0038115. Epub 2012 Jun 4. PMID: 22675513; PMCID: PMC3366978.

[10] Young KD, Zotev V, Phillips R, Misaki M, Yuan H, Drevets WC, Bodurka J. Real-time FMRI neurofeedback training of amygdala activity in patients with major depressive disorder. PLoS One. 2014 Feb 11;9(2):e88785. doi: 10.1371/journal.pone.0088785. PMID: 24523939; PMCID: PMC3921228.

[11] Misaki M, Young K, Tsuchiyagaito A, Savitz J, Guinjoan SM. Clinical Response to Neurofeedback in Major Depression Relates to Subtypes of Whole-Brain Activation Patterns During Training. bioRxiv [Preprint]. 2024 May 16:2024.05.01.592108. doi: 10.1101/2024.05.01.592108. Update in: Mol Psychiatry. 2025 Jun;30(6):2707-2717. doi: 10.1038/s41380-024-02880-3. PMID: 38746338; PMCID: PMC11092668.

[12] Fernández-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. PMID: 34776024; PMCID: PMC8842225.

[13] Khaleghi A, Samiei H, Zarafshan H, Baloochi SA, Mohammadi MR. Effectiveness of fMRI-based Neurofeedback Therapy on Depression: A Systematic Review. Clin Psychopharmacol Neurosci. 2025 Aug 31;23(3):337-355. doi: 10.9758/cpn.25.1295. Epub 2025 Jun 9. PMID: 40660681; PMCID: PMC12264674.

[14] Taylor, J.E., Yamada, T., Kawashima, T. et al. Depressive symptoms reduce when dorsolateral prefrontal cortex-precuneus connectivity normalizes after functional connectivity neurofeedback. Sci Rep 12, 2581 (2022). https://doi.org/10.1038/s41598-022-05860-1.

[15] Thibault RT, Lifshitz M, Raz A. The self-regulating brain and neurofeedback: Experimental science and clinical promise. Cortex. 2016 Jan;74:247-61. doi: 10.1016/j.cortex.2015.10.024. Epub 2015 Nov 18. PMID: 26706052.

[16] Cuijpers P, Sijbrandij M, Koole SL, Andersson G, Beekman AT, Reynolds CF 3rd. The efficacy of psychotherapy and pharmacotherapy in treating depressive and anxiety disorders: a meta-analysis of direct comparisons. World Psychiatry. 2013 Jun;12(2):137-48. doi: 10.1002/wps.20038. PMID: 23737423; PMCID: PMC3683266.

[17] Kuyken W, Warren FC, Taylor RS, Whalley B, Crane C, Bondolfi G, Hayes R, Huijbers M, Ma H, Schweizer S, Segal Z, Speckens A, Teasdale JD, Van Heeringen K, Williams M, Byford S, Byng R, Dalgleish T. Efficacy of Mindfulness-Based Cognitive Therapy in Prevention of Depressive Relapse: An Individual Patient Data Meta-analysis From Randomized Trials. JAMA Psychiatry. 2016 Jun 1;73(6):565-74. doi: 10.1001/jamapsychiatry.2016.0076. PMID: 27119968; PMCID: PMC6640038.

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