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Research progress on targeting the default mode network with real-time fMRI neurofeedback for mental disorders
ZHAO Di  SUN Yongbing  ZHANG Xueyi  CHEN Keke  ZOU Zhi  LI Zhonglin  WU Xiaoling  ZHOU Jing  HAO Yibin  LIU Min  LI Yongli 

DOI:10.12015/issn.1674-8034.2026.05.018.


[Abstract] The Default Mode Network (DMN), as the core brain network involved in self-referential thinking and episodic memory, exhibits functional dysregulation that is related to depression, insomnia, post-traumatic stress disorder (PTSD), and schizophrenia. Real-time fMRI neurofeedback (rt-fMRI-NF) technology provides a new approach for the non-pharmacological intervention of mental disorders by regulating individual brain activities in real time. However, there is currently a lack of systematic reviews on rt-fMRI-NF targeting DMN intervention for the above four diseases. This article first summarizes the abnormal manifestations and pathological associations of the DMN in depression, insomnia, PTSD and schizophrenia. Then, it focuses on reviewing the latest research progress of rt-fMRI-NF technology targeting the DMN to improve the above diseases, and analyzes and compares aspects such as intervention targets and therapeutic effect evaluation. Finally, this paper points out the limitations of the current research in terms of sample size, long-term effects, and mechanism exploration, and analyzes the future research directions, aiming to provide a theoretical basis and new ideas for the precise application of rt-fMRI-NF technology in the clinical intervention of mental disorders, thereby guiding clinical practice and improving the diagnosis and treatment effects.
[Keywords] depression；insomnia；post-traumatic stress disorder；real-time functional magnetic resonance imaging neurofeedback；magnetic resonance imaging；default mode network

ZHAO Di1   SUN Yongbing2   ZHANG Xueyi2   CHEN Keke3   ZOU Zhi2   LI Zhonglin2   WU Xiaoling4   ZHOU Jing5   HAO Yibin6   LIU Min7   LI Yongli8*  

1 Department of Medical Imaging, Henan University People's Hospital/Henan Provincial People's Hospital, Zhengzhou 450003, China

2 Department of Medical Imaging, Zhengzhou University People's Hospital, Zhengzhou 450003, China

3 Department of Medical Imaging, Henan Medical University/Henan Provincial People's Hospital, Zhengzhou 450003, China

4 Department of Nuclear Medicine, Henan Provincial People's Hospital, Zhengzhou 450003, China

5 Department of Health Management, Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Chronic Disease, Zhengzhou 450003, China

6 Hospital Offices, Henan University People's Hospital, Zhengzhou 450003, China

7 Department of Hypertension, Henan University People's Hospital,Zhengzhou 450003, China

8 Department of Medical Imaging, Henan University People's Hospital, Zhengzhou 450003, China

Corresponding author: LI Y L, E-mail: shyliyongli@126.com

Conflicts of interest   None.

Received  2026-02-10
Accepted  2026-04-14
DOI: 10.12015/issn.1674-8034.2026.05.018
DOI:10.12015/issn.1674-8034.2026.05.018.

[1]
PAPPA S, SHAH M, YOUNG S, et al. Care pathways, prescribing practices and treatment outcomes in major depressive disorder and treatment-resistant depression: retrospective, population-based cohort study[J/OL]. BJPsych Open, 2024, 10(1): e32 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/38240079/. DOI: 10.1192/bjo.2023.627.
[2]
KAMEI H. Polypharmacy management of antipsychotics in patients with schizophrenia[J/OL]. Medicina, 2022, 58(11): 1584 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/36363541/. DOI: 10.3390/medicina58111584.
[3]
AZARIAS F R, ALMEIDA G H D R, DE MELO L F, et al. The journey of the default mode network: development, function, and impact on mental health[J/OL]. Biology, 2025, 14(4): 395 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/40282260/. DOI: 10.3390/biology14040395.
[4]
PINDI P, HOUENOU J, PIGUET C, et al. Real-time fMRI neurofeedback as a new treatment for psychiatric disorders: a meta-analysis[J/OL]. Prog Neuropsychopharmacol Biol Psychiatry, 2022, 119: 110605 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/35843369/. DOI: 10.1016/j.pnpbp.2022.110605.
[5]
XIA G Y, HU Y X, CHAI F X, et al. Abnormalities of the default mode network functional connectivity in patients with insomnia disorder[J/OL]. Contrast Media Mol Imaging, 2022, 2022: 9197858 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/36101797/. DOI: 10.1155/2022/9197858.
[6]
KIM B H, BAEK J, KIM O, et al. North Korean defectors with PTSD and complex PTSD show alterations in default mode network resting-state functional connectivity[J/OL]. BJPsych Open, 2024, 10(1): e25 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/38179593/. DOI: 10.1192/bjo.2023.636.
[7]
WEISS F, ZHANG J Y, ASLAN A, et al. Feasibility of training the dorsolateral prefrontal-striatal network by real-time fMRI neurofeedback[J/OL]. Sci Rep, 2022, 12(1): 1669 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/35102203/. DOI: 10.1038/s41598-022-05675-0.
[8]
WEISKOPF N, VEIT R, ERB M, et al. Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data[J]. Neuroimage, 2003, 19(3): 577-586. DOI: 10.1016/s1053-8119(03)00145-9.
[9]
ZHANG Y, ZHANG Q, BECKER B, et al. Self-navigating the "island of reil": a systematic review of real-time fMRI neurofeedback training of insula activity[J/OL]. Neuroscience, 2022 [2025-11-12]. http://biorxiv.org/lookup/doi/10.1101/2022.03.07.483236. DOI: 10.1101/2022.03.07.483236.
[10]
GANESAN S, MISAKI M, ZALESKY A, et al. Functional brain network dynamics of brooding in depression: Insights from real-time fMRI neurofeedback[J/OL]. J Affect Disord, 2025, 380: 191-202 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/40122254/. DOI: 10.1016/j.jad.2025.03.121.
[11]
LONG Z Y, GUO Z X, GUO Z T, et al. Dynamic functional network connectivity changes associated with fMRI neurofeedback of right premotor cortex[J/OL]. Brain Sci, 2021, 11(5): 582 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/33946251/. DOI: 10.3390/brainsci11050582.
[12]
KAVROULAKIS E, VAN KEMENADE B M, ARIKAN B E, et al. The effect of self-generated versus externally generated actions on timing, duration, and amplitude of blood oxygen level dependent response for visual feedback processing[J]. Hum Brain Mapp, 2022, 43(16): 4954-4969. DOI: 10.1002/hbm.26053.
[13]
ZHANG Z H, ZHANG Y J, WANG H, et al. Resting-state network alterations in depression: a comprehensive meta-analysis of functional connectivity[J/OL]. Psychol Med, 2025, 55: e63 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/40008424/. DOI: 10.1017/S0033291725000303.
[14]
XUE C, ZHANG X L, CAO P, et al. Evidence of functional abnormalities in the default mode network in bipolar depression: a coordinate-based activation likelihood estimation meta-analysis[J/OL]. J Affect Disord, 2023, 326: 96-104 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/36717032/. DOI: 10.1016/j.jad.2023.01.088.
[15]
LUO L, DIMITROVSKI M, WISE T, et al. Transdiagnostic functional neuroimaging connectivity features in depression and anxiety in adolescence: a systematic review[J/OL]. Neurosci Biobehav Rev, 2025, 176: 106309 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/40738212/. DOI: 10.1016/j.neubiorev.2025.106309.
[16]
TAO Y Q, ZHOU Y H, LI W Q, et al. Altered default mode network and glymphatic function in insomnia with depression: a multimodal MRI study[J/OL]. Sleep Med, 2025, 131: 106482 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/40188802/. DOI: 10.1016/j.sleep.2025.106482.
[17]
RUNIA N, YÜCEL D E, LOK A, et al. The neurobiology of treatment-resistant depression: a systematic review of neuroimaging studies[J/OL]. Neurosci Biobehav Rev, 2022, 132: 433-448 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/34890601/. DOI: 10.1016/j.neubiorev.2021.12.008.
[18]
YU R Q, TAN H, PENG G, et al. Anomalous functional connectivity within the default-mode network in treatment-naive patients possessing first-episode major depressive disorder[J/OL]. Medicine, 2021, 100(23): e26281 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/34115028/. DOI: 10.1097/md.0000000000026281.
[19]
YANG H, CHEN X, CHEN Z B, et al. Disrupted intrinsic functional brain topology in patients with major depressive disorder[J]. Mol Psychiatry, 2021, 26(12): 7363-7371. DOI: 10.1038/s41380-021-01247-2.
[20]
GUAN C B, AMDANEE N, LIAO W X, et al. Altered intrinsic default mode network functional connectivity in patients with remitted geriatric depression and amnestic mild cognitive impairment[J]. Int Psychogeriatr, 2022, 34(8): 703-714. DOI: 10.1017/S1041610221001174.
[21]
BEZMATERNYKH D D, MELNIKOV M Y, SAVELOV A A, et al. Brain networks connectivity in mild to moderate depression: resting state fMRI study with implications to nonpharmacological treatment[J/OL]. Neural Plast, 2021, 2021(1): 8846097 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/33510782/. DOI: 10.1155/2021/8846097.
[22]
AUPPERLE R L, KUPLICKI R, TSUCHIYAGAITO A, et al. Ventromedial prefrontal cortex activation and neurofeedback modulation during episodic future thinking for individuals with suicidal thoughts and behaviors[J/OL]. Behav Res Ther, 2024, 176: 104522 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/38547724/. DOI: 10.1016/j.brat.2024.104522.
[23]
ZHANG J H, RAYA J, MORFINI F, et al. Reducing default mode network connectivity with mindfulness-based fMRI neurofeedback: a pilot study among adolescents with affective disorder history[J]. Mol Psychiatry, 2023, 28(6): 2540-2548. DOI: 10.1038/s41380-023-02032-z.
[24]
TAYLOR J E, YAMADA T, KAWASHIMA T, et al. Depressive symptoms reduce when dorsolateral prefrontal cortex-precuneus connectivity normalizes after functional connectivity neurofeedback[J/OL]. Sci Rep, 2022, 12(1): 2581 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/35173179/. DOI: 10.1038/s41598-022-05860-1.
[25]
ZHANG L Y, GUO Z G, HAN Y D, et al. Altered cerebral functional activity and its associated genetic profiles underlying chronic insomnia disorder before and after treatment[J]. World J Biol Psychiatry, 2025, 26(5): 211-223. DOI: 10.1080/15622975.2025.2503938.
[26]
ZHANG H Y, ZHAO Z R, ZHANG S, et al. Altered cingulate gyrus subregions functional connectivity in chronic insomnia disorder with anxiety[J/OL]. Sleep Med, 2024, 123: 42-48 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/39236464/. DOI: 10.1016/j.sleep.2024.08.031.
[27]
ZHENG H, ZHOU Q, YANG J J, et al. Altered functional connectivity of the default mode and frontal control networks in patients with insomnia[J]. CNS Neurosci Ther, 2023, 29(8): 2318-2326. DOI: 10.1111/cns.14183.
[28]
GEORGIEV T, PAUNOVA R, TODEVA-RADNEVA A, et al. Aberrant effective connectivity within and between the default mode, executive control, and salience networks in chronic insomnia disorder-toward identifying the hyperarousal state[J/OL]. Biomedicines, 2025, 13(6): 1293 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/40564013/. DOI: 10.3390/biomedicines13061293.
[29]
XIN W Y, XUE T, CHENG Y X, et al. Reconfigurations of dynamic functional network connectivity after 1HZ repetitive transcranial magnetic stimulation in insomnia disorder[J/OL]. Sleep Med, 2025, 126: 239-247 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/39721360/. DOI: 10.1016/j.sleep.2024.12.025.
[30]
JESPERSEN K V, STEVNER A, KRINGELBACH M, et al. Reduced switching between brain states in insomnia: evidence from modeling of fMRI brain dynamics[J/OL]. Cereb Cortex, 2025, 35(11): bhaf314 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/41283931/. DOI: 10.1093/cercor/bhaf314.
[31]
JIA S L, ZHANG M, GU Y A, et al. Role of real-time functional magnetic resonance imaging neurofeedback in treating insomnia disorder via regulating amygdala activity[J]. J Chin Pract Diagn Ther, 2024, 38(8): 762-767. DOI: 10.13507/j.issn.1674-3474.2024.08.002.
[32]
GU Y A, ZHANG M, JIA S L, et al. Impact of regulating amygdala activity in patients with insomnia disorders using rtfMRI-NF technology on the centrality of the brain[J]. Chin J Magn Reson Imaging, 2024, 15(7): 64-69. DOI: 10.12015/issn.1674-8034.2024.07.011.
[33]
ZHANG M, WU X L, LI Z L, et al. Regulation of amygdala by rtfMRI-NF technique in improving insomnia disorder[J]. Chin J Magn Reson Imaging, 2023, 14(7): 5-9. DOI: 10.12015/issn.1674-8034.2023.07.002.
[34]
LV Z W, FAN Y H, ZHANG H B, et al. Resting-state brain change on treatment improvement in insomnia disorder: a coordinate-based meta-analysis[J/OL]. Sleep Med, 2025, 133: 106601 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/40499260/. DOI: 10.1016/j.sleep.2025.106601.
[35]
SUSSMAN T J, POSNER J, JACKOWSKI A P, et al. The relationship between recent PTSD secondary to sexual assault, hippocampal volume and resting state functional connectivity in adolescent girls[J/OL]. Neurobiol Stress, 2022, 17: 100441 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/35257017/. DOI: 10.1016/j.ynstr.2022.100441.
[36]
SHEYNIN J, DUVAL E R, KING A P, et al. Associations between resting-state functional connectivity and treatment response in a randomized clinical trial for posttraumatic stress disorder[J]. Depress Anxiety, 2020, 37(10): 1037-1046. DOI: 10.1002/da.23075.
[37]
JOSHI S A, DUVAL E R, KUBAT B, et al. A review of hippocampal activation in post-traumatic stress disorder[J/OL]. Psychophysiology, 2020, 57(1): e13357 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/30829407/. DOI: 10.1111/psyp.13357.
[38]
SUO X L, LAN H, ZUO C, et al. Multilayer analysis of dynamic network reconfiguration in pediatric posttraumatic stress disorder[J/OL]. Cereb Cortex, 2024, 34(1): bhad436 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/37991275/. DOI: 10.1093/cercor/bhad436.
[39]
LIEBERMAN J M, RABELLINO D, DENSMORE M, et al. Posterior cingulate cortex targeted real-time fMRI neurofeedback recalibrates functional connectivity with the amygdala, posterior Insula, and default-mode network in PTSD[J/OL]. Brain Behav, 2023, 13(3): e2883 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/36791212/. DOI: 10.1002/brb3.2883.
[40]
LIEBERMAN J M, RABELLINO D, DENSMORE M, et al. A tale of two targets: examining the differential effects of posterior cingulate cortex- and amygdala-targeted fMRI-neurofeedback in a PTSD pilot study[J/OL]. Front Neurosci, 2023, 17: 1229729 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/38094001/. DOI: 10.3389/fnins.2023.1229729.
[41]
KRAKOWSKI M, HOPTMAN M J, CZOBOR P. Dysfunctional activation of the default mode network in response inhibition in schizophrenia[J/OL]. J Psychiatr Res, 2024, 180: 411-417 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/39536502/. DOI: 10.1016/j.jpsychires.2024.11.020.
[42]
HILLAND E, JOHANNESSEN C, JONASSEN R, et al. Aberrant default mode connectivity in adolescents with early-onset psychosis: a resting state fMRI study[J/OL]. Neuroimage Clin, 2022, 33: 102881 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/34883402/. DOI: 10.1016/j.nicl.2021.102881.
[43]
CAO C L, LIU W Q, HOU C S, et al. Disrupted default mode network connectivity and its role in negative symptoms of schizophrenia[J/OL]. Psychiatry Res, 2025, 348: 116489 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/40203641/. DOI: 10.1016/j.psychres.2025.116489.
[44]
FAN F M, TAN S P, HUANG J C, et al. Functional disconnection between subsystems of the default mode network in schizophrenia[J]. Psychol Med, 2022, 52(12): 2270-2280. DOI: 10.1017/S003329172000416X.
[45]
PENG Y, ZHANG S, ZHOU Y Q, et al. Abnormal functional connectivity based on nodes of the default mode network in first-episode drug-naive early-onset schizophrenia[J/OL]. Psychiatry Res, 2021, 295: 113578 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/33243520/. DOI: 10.1016/j.psychres.2020.113578.
[46]
SASABAYASHI D, TAKAHASHI T, TAKAYANAGI Y, et al. Resting state hyperconnectivity of the default mode network in schizophrenia and clinical high-risk state for psychosis[J]. Cereb Cortex, 2023, 33(13): 8456-8464. DOI: 10.1093/cercor/bhad131.
[47]
RONG B, HUANG H, GAO G Q, et al. Widespread intra- and inter-network dysconnectivity among large-scale resting state networks in schizophrenia[J/OL]. J Clin Med, 2023, 12(9): 3176 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/37176617/. DOI: 10.3390/jcm12093176.
[48]
WANG Y M, CAI X L, ZHANG R T, et al. Altered brain structural and functional connectivity in schizotypy[J]. Psychol Med, 2022, 52(5): 834-843. DOI: 10.1017/s0033291720002445.
[49]
SENDI M S E, ZENDEHROUH E, ELLIS C A, et al. Aberrant dynamic functional connectivity of default mode network in schizophrenia and links to symptom severity[J/OL]. Front Neural Circuits, 2021, 15: 649417 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/33815070/. DOI: 10.3389/fncir.2021.649417.
[50]
XI Y B, GUO F, LIU W M, et al. Triple network hypothesis-related disrupted connections in schizophrenia: a spectral dynamic causal modeling analysis with functional magnetic resonance imaging[J/OL]. Schizophr Res, 2021, 233: 89-96 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/34246865/. DOI: 10.1016/j.schres.2021.06.024.
[51]
ADAMCZYK P, WIĘCŁAWSKI W, WOJCIK M, et al. Aberrant information flow within resting-state triple network model in schizophrenia-An EEG effective connectivity study[J/OL]. Psychiatry Res Neuroimaging, 2025, 349: 111985 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/40121818/. DOI: 10.1016/j.pscychresns.2025.111985.
[52]
MARTIN-SUBERO M, FUENTES-CLARAMONTE P, SALGADO-PINEDA P, et al. Autobiographical memory and default mode network function in schizophrenia: an fMRI study-CORRIGENDUM[J/OL]. Psychol Med, 2021, 51(1): 129 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/32375924/. DOI: 10.1017/S0033291720001361.
[53]
ZHANG J H, TUSUZIAN E, MORFINI F, et al. Brain structural and functional neuroimaging features are associated with improved auditory hallucinations in patients with schizophrenia after real-time fMRI neurofeedback[J/OL]. Depress Anxiety, 2025, 2025: 2848929 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/40236821/. DOI: 10.1155/da/2848929.
[54]
BAUER C C C, OKANO K, GHOSH S S, et al. Real-time fMRI neurofeedback reduces auditory hallucinations and modulates resting state connectivity of involved brain regions: Part 2: Default mode network-preliminary evidence[J/OL]. Psychiatry Res, 2020, 284: 112770 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/32004893/. DOI: 10.1016/j.psychres.2020.112770.
[55]
PAOLINI M, KEESER D, RAUCHMANN B S, et al. Correlations between the DMN and the smoking cessation outcome of a real-time fMRI neurofeedback supported exploratory therapy approach: descriptive statistics on tobacco-dependent patients[J]. Clin EEG Neurosci, 2022, 53(4): 287-296. DOI: 10.1177/15500594211062703.
[56]
FEDE S J, KISNER M A, DEAN S F, et al. Selecting an optimal real-time fMRI neurofeedback method for alcohol craving control training[J/OL]. Psychophysiology, 2023, 60(11): e14367 [2026-02-09]. https://pubmed.ncbi.nlm.nih.gov/37326428/. DOI: 10.1111/psyp.14367.

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