Odor identification (OI) impairment in mild cognitive impairment (MCI) elevates the risk for Alzheimer's disease (AD). The present study was designed to clarify the underlying neural mechanisms by investigating brain network aberrations in MCI patients with OI impairment using dynamic resting-state functional magnetic resonance imaging (rs-fMRI).
Objective
This study aimed to delineate the profile of dynamic intrinsic brain activity in MCI patients with and without OI impairment. It further aimed to establish the clinical relevance of these dynamic neural signatures by linking them to cognitive and olfactory function.
Methods
In 194 participants (97 MCI and 97 healthy controls [HC]), we analyzed dynamic metrics including dynamic fractional Amplitude of Low-Frequency Fluctuations (dfALFF), dynamic Amplitude of Low-Frequency Fluctuations (dALFF), dynamic Degree Centrality (dDC), and dynamic Regional Homogeneity (dReHo), and their correlation with cognitive performance and OI.
Results
The MCI with OI impairment (MCI-OII) group (n = 22) performed worse across all cognitive domains than both HC and the MCI without OI impairment (MCI-NOII) group (n = 75, p < 0.001). These patients exhibited elevated dALFF, dfALFF, dDC, and dReHo variability in regions including the fusiform gyrus, insula, precuneus, and cingulate cortex (p < 0.001). These dynamic metrics correlated with olfactory and cognitive scores (p < 0.05). Additionally, dReHo in the right precuneus partially mediated the relationship between olfactory function and delayed recall memory.
Conclusions
This study demonstrates that MCI patients with OI impairment exhibit widespread disruptions in dynamic brain activity. These alterations correlate with clinical deficits, and precuneus dReHo may partially link olfactory and cognitive decline in MCI.
CataldiRSachdevPSChowdharyN, et al.A WHO blueprint for action to reshape dementia research. Nat Aging2023; 3: 469–471.
2.
LiF-FWangJ-PZhangW-J, et al.Trends and mechanisms of Alzheimer’s disease and hearing impairment: a 20-year perspective. Ageing Res Rev2025; 110: 102799.
3.
SerbyMLarsonPKalksteinD. The nature and course of olfactory deficits in Alzheimer’s disease. Am J Psychiatry1991; 148: 357–360.
4.
DevanandDPMichaels-MarstonKSLiuX, et al.Olfactory deficits in patients with mild cognitive impairment predict Alzheimer’s disease at follow-up. Am J Psychiatry2000; 157: 1399–1405.
5.
BraakHDel TrediciK. The pathological process underlying Alzheimer’s disease in individuals under thirty. Acta Neuropathol2011; 121: 171–181.
6.
MinoharaTOharaTNakazawaT, et al.Association of impaired olfactory identification with prevalent mild cognitive impairment and regional brain atrophy: the Hisayama Study. Psychiatry Clin Neurosci2025; 79: 370–377.
7.
PorsteinssonAPIsaacsonRSKnoxS, et al.Diagnosis of early Alzheimer’s disease: clinical practice in 2021. J Prev Alzheimers Dis2021; 8: 371–386.
8.
LloretAEsteveDLloretM-A, et al.When does Alzheimer’s disease really start? The role of biomarkers. Int J Mol Sci2019; 20: 5536.
DongYLiYLiuK, et al.Anosmia, mild cognitive impairment, and biomarkers of brain aging in older adults. Alzheimers Dement2023; 19: 589–601.
11.
RoalfDRMobergMJTuretskyBI, et al.A quantitative meta-analysis of olfactory dysfunction in mild cognitive impairment. J Neurol Neurosurg Psychiatry2017; 88: 226–232.
12.
SuM-WNiJ-NCaoT-Y, et al.The correlation between olfactory test and hippocampal volume in Alzheimer’s disease and mild cognitive impairment patients: a meta-analysis. Front Aging Neurosci2021; 13: 755160.
13.
LiangXDingDZhaoQ, et al.Association between olfactory identification and cognitive function in community-dwelling elderly: the Shanghai aging study. BMC Neurol2016; 16: 199.
14.
RobertsROChristiansonTJHKremersWK, et al.Association between olfactory dysfunction and amnestic mild cognitive impairment and Alzheimer disease dementia. JAMA Neurol2016; 73: 93–101.
15.
DevanandDPLeeSManlyJ, et al.Olfactory deficits predict cognitive decline and Alzheimer dementia in an urban community. Neurology2015; 84: 182–189.
16.
KnightJEYonedaTLewisNA, et al.Transitions between mild cognitive impairment, dementia, and mortality: the importance of olfaction. J Gerontol A Biol Sci Med Sci2023; 78: 1284–1291.
17.
WangS-MKangDWUmYH, et al.Olfactory dysfunction is associated with cerebral amyloid deposition and cognitive function in the trajectory of Alzheimer’s disease. Biomolecules2023; 13: 1336.
18.
ShresthaSZhuXGriswoldME, et al.Olfaction and plasma biomarkers of Alzheimer disease and neurodegeneration in the Atherosclerosis Risk in Communities Study. Neurology2025; 104: e213706.
19.
GravesABBowenJDRajaramL, et al.Impaired olfaction as a marker for cognitive decline: interaction with apolipoprotein E ε4 status. Neurology1999; 53: 1480–1487.
20.
BhattaraiJPEtyemezSJaaro-PeledH, et al.Olfactory modulation of the medial prefrontal cortex circuitry: implications for social cognition. Semin Cell Dev Biol2022; 129: 31–39.
21.
WallaP. Olfaction and its dynamic influence on word and face processing: cross-modal integration. Prog Neurobiol2008; 84: 192–209.
22.
DanieliKGuyonABethusI. Episodic Memory formation: a review of complex Hippocampus input pathways. Prog Neuropsychopharmacol Biol Psychiatry2023; 126: 110757.
23.
ZhouGLaneGCooperSL, et al.Characterizing functional pathways of the human olfactory system. Elife2019; 8: e47177.
24.
SagarVShanahanLKZelanoCM, et al.High-precision mapping reveals the structure of odor coding in the human brain. Nat Neurosci2023; 26: 1595–1602.
25.
CourtiolEWilsonDA. The olfactory thalamus: unanswered questions about the role of the mediodorsal thalamic nucleus in olfaction. Front Neural Circuits2015; 9: 49.
26.
Martín-SignesMPaz-AlonsoPMThiebaut de SchottenM, et al.Integrating brain function and structure in the study of the human attentional networks: a functionnectome study. Brain Struct Funct2024; 229: 1665–1679.
27.
ShineJMLewisLDGarrettDD, et al.The impact of the human thalamus on brain-wide information processing. Nat Rev Neurosci2023; 24: 416–430.
28.
SeubertJKalpouzosGLarssonM, et al.Temporolimbic cortical volume is associated with semantic odor memory performance in aging. Neuroimage2020; 211: 116600.
29.
RomboutsSABarkhofFGoekoopR, et al.Altered resting state networks in mild cognitive impairment and mild Alzheimer’s disease: an fMRI study. Hum Brain Mapp2005; 26: 231–239.
30.
VasavadaMMWangJEslingerPJ, et al.Olfactory cortex degeneration in Alzheimer's disease and mild cognitive impairment. J Alzheimers Dis2015; 45: 647–958.
31.
ZhangHJiDYinJ, et al.Olfactory fMRI activation pattern across different in concentrations changes in Alzheimer's disease. Front Neurosci2019; 13: 786.
32.
JobinBBollerBFrasnelliJ. Volumetry of olfactory structures in mild cognitive impairment and Alzheimer’s disease: a systematic review and a meta-analysis. Brain Sci2021; 11: 1010.
33.
LuJYangQXZhangH, et al.Disruptions of the olfactory and default mode networks in Alzheimer’s disease. Brain Behav2019; 9: e01296.
34.
CȋrneciDOnuMPapasteriCC, et al.Neural networks implicated in autobiographical memory training. eNeuro2022; 9: ENEURO.0137–22.2022.
35.
YaoCShanYCuiB, et al.Hyperconnectivity and connectome gradient dysfunction of cerebello-thalamo-cortical circuitry in Alzheimer’s disease spectrum disorders. Cerebellum2025; 24: 43.
36.
ChenBEspinMHaussmannR, et al.The effect of olfactory training on olfaction, cognition, and brain function in patients with mild cognitive impairment. J Alzheimers Dis2022; 85: 745–754.
37.
YanC-GYangZColcombeSJ, et al.Concordance among indices of intrinsic brain function: insights from inter-individual variation and temporal dynamics. Sci Bull (Beijing)2017; 62: 1572–1584.
38.
LiaoWWuG-RXuQ, et al.DynamicBC : a MATLAB toolbox for dynamic brain connectome analysis. Brain Connect2014; 4: 780–790.
39.
LuoZChenGJiaY, et al.Shared and specific dynamics of brain segregation and integration in bipolar disorder and major depressive disorder: a resting-state functional magnetic resonance imaging study. J Affect Disord2021; 280: 279–286.
40.
SongCZhangXHanS, et al.Static and temporal dynamic alteration of intrinsic brain activity in MRI-negative temporal lobe epilepsy. Seizure2023; 108: 33–42.
41.
LuoLLiQWangY, et al.Shared and disorder-specific alterations of brain temporal dynamics in obsessive-compulsive disorder and schizophrenia. Schizophr Bull2023; 49: 1387–1398.
42.
ChenZChenKLiY, et al.Structural, static, and dynamic functional MRI predictors for conversion from mild cognitive impairment to Alzheimer’s disease: inter-cohort validation of Shanghai Memory Study and ADNI. Hum Brain Mapp2024; 45: e26529.
43.
JingRChenPWeiY, et al.Altered large-scale dynamic connectivity patterns in Alzheimer’s disease and mild cognitive impairment patients: a machine learning study. Hum Brain Mapp2023; 44: 3467–3480.
44.
ShiYLiYCiR, et al.Dynamic functional connectivity and transcriptomic signatures reveal stage-dependent brain network dysfunction in Alzheimer’s disease spectrum. Alzheimers Res Ther2025; 17: 247.
45.
LiHJiaJYangZ. Mini-Mental State Examination in elderly Chinese: a population-based normative study. J Alzheimers Dis2016; 53: 487–496.
46.
GuoQSunYYuP, et al.Norm of auditory verbal learning test in the normal aged in China community. Chin J Clin Psych2007; 15: 132–134.
47.
GuoQLvCHongZ. Application of Rey-Osterrieth complex figure test in Chinese normal old people. Chin J Clin Psych2000; 8: 205–207.
48.
LuJGuoQHongZ, et al.Trail Making Test used by chinese elderly patients with mild cognitive impairment and mild Alzheimer’s dementia. Chin J Clin Psych2006; 14: 118–120.
49.
GuoQHongZLvC. Application of Stroop color-word test on Chinese elderly patients with mild cognitive impairment and mild Alzheimer’s dementia. Chin J Neuromed2005; 4: 701–704.
50.
ShaoKDongFGuoS, et al.Clock-drawing test: normative data of three quantitative scoring methods for Chinese-speaking adults in Shijiazhuang City and clinical utility in patients with acute ischemic stroke. Brain Behav2020; 10: e01806.
51.
CheungRWCheungM-CChanAS. Confrontation naming in Chinese patients with left, right or bilateral brain damage. J Int Neuropsychol Soc2004; 10: 46–53.
52.
MengQWangHStraussJ, et al.Validation of neuropsychological tests for the China Health and Retirement Longitudinal Study Harmonized Cognitive Assessment Protocol. Int Psychogeriatr2019; 31: 1709–1719.
53.
LiangB-YYangY-PPanC-Y, et al.Nasal microbiota as a potential therapeutic target for allergic rhinitis: an emerging perspective. Curr Pharm Des2025; 32: 1326–1335.
54.
HummelTKonnerthCGRosenheimK, et al.Screening of olfactory function with a four-minute odor identification test: reliability, normative data, and investigations in patients with olfactory loss. Ann Otol Rhinol Laryngol2001; 110: 976–981.
55.
YanC-GWangX-DZuoX-N, et al.DPABI: data processing & analysis for (resting-state) brain imaging. Neuroinform2016; 14: 339–351.
JiaX-ZSunJ-WJiG-J, et al.Percent amplitude of fluctuation: a simple measure for resting-state fMRI signal at single voxel level. PLoS One2020; 15: e0227021.
58.
ChenZXieHYaoL, et al.Olfactory impairment and the risk of cognitive decline and dementia in older adults: a meta-analysis. Braz J Otorhinolaryngol2021; 87: 94–102.
59.
FatuzzoINiccoliniGFZoccaliF, et al.Neurons, nose, and neurodegenerative diseases: olfactory function and cognitive impairment. Int J Mol Sci2023; 24: 2117.
60.
ZottBSimonMMHongW, et al.A vicious cycle of β amyloid–dependent neuronal hyperactivation. Science2019; 365: 559–565.
61.
KirsebomB-ENilssonJVromenE, et al.Cerebrospinal fluid markers link to synaptic plasticity responses and Alzheimer’s disease genetic pathways. Mol Neurodegener2025; 20: 107.
62.
UhlhaasPJRouxFRodriguezE, et al.Neural synchrony and the development of cortical networks. Trends Cogn Sci2010; 14: 72–80.
63.
WuMWKourdougliNPortera-CailliauC. Network state transitions during cortical development. Nat Rev Neurosci2024; 25: 535–552.
64.
BokdeALWLopez-BayoPMeindlT, et al.Functional connectivity of the fusiform gyrus during a face-matching task in subjects with mild cognitive impairment. Brain2006; 129: 1113–1124.
65.
HanPWinklerNHummelC, et al.Alterations of brain gray matter density and olfactory bulb volume in patients with olfactory loss after traumatic brain injury. J Neurotrauma2018; 35: 2632–2640.
66.
IbrahimBSuppiahSIbrahimN, et al.Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer’s disease and mild cognitive impairment: a systematic review. Hum Brain Mapp2021; 42: 2941–2968.
67.
TangXGuoZChenG, et al.A multimodal meta-analytical evidence of functional and structural brain abnormalities across Alzheimer’s disease spectrum. Ageing Res Rev2024; 95: 102240.
68.
HeYWangLZangY, et al.Regional coherence changes in the early stages of Alzheimer’s disease: a combined structural and resting-state functional MRI study. Neuroimage2007; 35: 488–500.
69.
WangZYanCZhaoC, et al.Spatial patterns of intrinsic brain activity in mild cognitive impairment and Alzheimer’s disease: a resting-state functional MRI study. Hum Brain Mapp2011; 32: 1720–1740.
70.
Molnar-SzakacsIUddinLQ. Anterior insula as a gatekeeper of executive control. Neurosci Biobehav Rev2022; 139: 104736.
71.
JiangPCuiSYaoS, et al.The hierarchical organization of the precuneus captured by functional gradients. Brain Struct Funct2023; 228: 1561–1572.
72.
SerraLCercignaniMMastropasquaC, et al.Longitudinal changes in functional brain connectivity predicts conversion to Alzheimer’s disease. J Alzheimers Dis2016; 51: 377–389.
73.
StromAIaccarinoLEdwardsL, et al.Cortical hypometabolism reflects local atrophy and tau pathology in symptomatic Alzheimer’s disease. Brain2022; 145: 713–728.
74.
GiliTCercignaniMSerraL, et al.Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution. J Neurol Neurosurg Psychiatry2011; 82: 58–66.
