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image of MRS Perspectives: Neurotransmitter and Metabolic Alterations in Cognitive Decline and Mental/Neurological Disorders

Abstract

Cognitive function refers to the brain's ability to process information and perform various cognitive tasks. These include sustaining attention, acquiring knowledge, storing memories, executing complex functions, accurately expressing language, perceiving external stimuli, and maintaining spatial orientation. Numerous studies have demonstrated that good cognitive function is closely linked to the balance and normal function of neurobiochemical metabolites. Magnetic Resonance Spectroscopy (MRS), as a non-invasive and quantitative advanced neuroimaging technique, can accurately measure the concentration and distribution of neurobiochemical metabolites in the brain. This provides rich data and key insights for in-depth research on cognitive function and related clinical disorders. This paper comprehensively reviews MRS and its quantitative research on biochemical metabolites in the field of cognitive function. It aims to deeply evaluate the clinical value and significance of the metabolic substances involved in this technology for the early detection and diagnosis of mental and neurological diseases caused by cognitive decline. The goal is to provide useful references and inspiration for research and practice in this domain.

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2025-10-20
2025-12-15
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References

  1. Latino F. Tafuri F. Physical activity and cognitive functioning. Medicina 2024 60 2 216 10.3390/medicina60020216 38399504
    [Google Scholar]
  2. Friedman N.P. Miyake A. Unity and diversity of executive functions: Individual differences as a window on cognitive structure. Cortex 2017 86 186 204 10.1016/j.cortex.2016.04.023 27251123
    [Google Scholar]
  3. Halloway S. Wagner M. Tangney C. Lange-Maia B.S. Bennett D.A. Arvanitakis Z. Schoeny M.E. Profiles of lifestyle health behav-iors and cognitive decline in older adults. Alzheimers Dement. 2024 20 1 472 482 10.1002/alz.13459 37676928
    [Google Scholar]
  4. Kouli A. Spindler L.R.B. Fryer T.D. Hong Y.T. Malpetti M. Aigbirhio F.I. White S.R. Camacho M. O’Brien J.T. Williams-Gray C.H. Neuroinflammation is linked to dementia risk in Parkinson’s disease. Brain 2024 147 3 923 935 10.1093/brain/awad322 37757857
    [Google Scholar]
  5. Dhana K. Agarwal P. James B.D. Leurgans S.E. Rajan K.B. Aggarwal N.T. Barnes L.L. Bennett D.A. Schneider J.A. Healthy lifestyle and cognition in older adults with common neuropathologies of dementia. JAMA Neurol. 2024 81 3 233 239 10.1001/jamaneurol.2023.5491 38315471
    [Google Scholar]
  6. Hong Y.J. Choi S.H. Kim S. Jeong J.H. Park K.H. Wang M.J. Kang S. Yang D.W. Cognitive and neurodegenerative trajectories of subjective cognitive decline according to baseline biomarkers: Results of the CoSCo study. Alzheimers Dement. 2025 21 2 e14473 10.1002/alz.14473 39732514
    [Google Scholar]
  7. Dark H.E. An Y. Duggan M.R. Joynes C. Davatzikos C. Erus G. Lewis A. Moghekar A.R. Resnick S.M. Walker K.A. Alz-heimer’s and neurodegenerative disease biomarkers in blood predict brain atrophy and cognitive decline. Alzheimers Res. Ther. 2024 16 1 94 10.1186/s13195‑024‑01459‑y 38689358
    [Google Scholar]
  8. Lin Y. Shan P.Y. Jiang W.J. Sheng C. Ma L. Subjective cognitive decline: Preclinical manifestation of Alzheimer’s disease. Neurol. Sci. 2018 39 12 2121 2131 10.1007/s10072‑018‑3620‑y 30397816
    [Google Scholar]
  9. Takado Y. Takuwa H. Sampei K. Urushihata T. Takahashi M. Shimojo M. Uchida S. Nitta N. Shibata S. Nagashima K. Ochi Y. Ono M. Maeda J. Tomita Y. Sahara N. Near J. Aoki I. Shibata K. Higuchi M. MRS-measured glutamate versus GABA reflects excitatory versus inhibitory neural activities in awake mice. J. Cereb. Blood Flow Metab. 2022 42 1 197 212 10.1177/0271678X211045449 34515548
    [Google Scholar]
  10. Jembrek M. Vlainic J. GABA receptors: Pharmacological potential and pitfalls. Curr. Pharm. Des. 2015 21 34 4943 4959 10.2174/1381612821666150914121624 26365137
    [Google Scholar]
  11. Encarnación-Rosado J. Sohn A.S.W. Biancur D.E. Lin E.Y. Osorio-Vasquez V. Rodrick T. González-Baerga D. Zhao E. Yoko-yama Y. Simeone D.M. Jones D.R. Parker S.J. Wild R. Kimmelman A.C. Targeting pancreatic cancer metabolic dependencies through glutamine antagonism. Nat. Cancer 2023 5 1 85 99 10.1038/s43018‑023‑00647‑3 37814010
    [Google Scholar]
  12. Bottino F. Lucignani M. Napolitano A. Dellepiane F. Visconti E. Rossi Espagnet M.C. Pasquini L. In vivo brain GSH: MRS meth-ods and clinical applications. Antioxidants 2021 10 9 1407 10.3390/antiox10091407 34573039
    [Google Scholar]
  13. Jun S. Altmann A. Sadaghiani S. Modulatory neurotransmitter genotypes shape dynamic functional connectome reconfigurations. J. Neurosci. 2025 45 10 e1939242025 10.1523/JNEUROSCI.1939‑24.2025 39843237
    [Google Scholar]
  14. Fu X.N. Wang J. The clinical research progress of gamma-aminobutynic acid quantification based on MEGA-PRESS in neurological diseases. Chin J. Magn. Reson. Imaging 2023 14 6 89 93
    [Google Scholar]
  15. Buonocore M.H. Maddock R.J. Magnetic resonance spectroscopy of the brain: A review of physical principles and technical methods. Rev. Neurosci. 2015 26 6 609 632 10.1515/revneuro‑2015‑0010 26200810
    [Google Scholar]
  16. Guo Z. Liu X. Hou H. Wei F. Chen X. Shen Y. Chen W. 1H-MRS asymmetry changes in the anterior and posterior cingulate gyrus in patients with mild cognitive impairment and mild Alzheimer’s disease. Compr. Psychiatry 2016 69 179 185 10.1016/j.comppsych.2016.06.001 27423359
    [Google Scholar]
  17. Bishnoi A. Hernandez M.E. Dual task walking costs in older adults with mild cognitive impairment: A systematic review and meta-analysis. Aging Ment. Health 2021 25 9 1618 1629 10.1080/13607863.2020.1802576 32757759
    [Google Scholar]
  18. Zhu S. Noviello C.M. Teng J. Walsh R.M. Kim J.J. Hibbs R.E. Structure of a human synaptic GABAA receptor. Nature 2018 559 7712 67 72 10.1038/s41586‑018‑0255‑3 29950725
    [Google Scholar]
  19. Li Y. Wang L. Sun X. Progress in biological functions of γ-aminobutyric acid. Agric. Tech. 2024 44 10 12 14
    [Google Scholar]
  20. Callewaert B. Jones E.A.V. Himmelreich U. Gsell W. Non-invasive evaluation of cerebral microvasculature using pre-clinical MRI: Principles, advantages and limitations. Diagnostics 2021 11 6 926 10.3390/diagnostics11060926 34064194
    [Google Scholar]
  21. Pasanta D. Htun K.T. Pan J. Tungjai M. Kaewjaeng S. Kim H. Kaewkhao J. Kothan S. Magnetic resonance spectroscopy of hepat-ic fat from fundamental to clinical applications. Diagnostics 2021 11 5 842 10.3390/diagnostics11050842 34067193
    [Google Scholar]
  22. McKiernan E. Su L. O’Brien J. MRS in neurodegenerative dementias, prodromal syndromes and at‐risk states: A systematic review of the literature. NMR Biomed. 2023 36 7 e4896 10.1002/nbm.4896 36624067
    [Google Scholar]
  23. Stanley J.A. Raz N. Functional magnetic resonance spectroscopy: The “New” MRS for cognitive neuroscience and psychiatry research. Front. Psychiatry 2018 9 76 10.3389/fpsyt.2018.00076 29593585
    [Google Scholar]
  24. Demco D.E. Oros-Peusquens A.M. Shah N.J. Nonlinear effects in magnetic resonance localized spectroscopy and images. Prog. Nucl. Magn. Reson. Spectrosc. 2025 146-147 101557 10.1016/j.pnmrs.2025.101557 40306800
    [Google Scholar]
  25. Handra C. Coman O.A. Coman L. Enache T. Stoleru S. Sorescu A-M. Ghita I. Fulga I. The connection between different neuro-transmitters involved in cognitive processes. Farmacia 2019 67 2 193 201 10.31925/farmacia.2019.2.1
    [Google Scholar]
  26. Héja L. Simon Á. Szabó Z. Kardos J. Feedback adaptation of synaptic excitability via Glu:Na+ symport driven astrocytic GABA and Gln release. Neuropharmacology 2019 161 107629 10.1016/j.neuropharm.2019.05.006 31103619
    [Google Scholar]
  27. Xue L. Gong P. Wang Z. Neurobiological mechanisms of glutamate in the pathogenesis and treatment of depression. Chin J. Psychiatry 2023 50 4 600 604 10.13479/j.cnki.jip.2023.04.075
    [Google Scholar]
  28. Lyall L.M. Cullen B. Lyall D.M. Leighton S.P. Siebert S. Smith D.J. Cavanagh J. The associations between self-reported depres-sion, self-reported chronic inflammatory conditions and cognitive abilities in UK Biobank. Eur. Psychiatry 2019 60 63 70 10.1016/j.eurpsy.2019.05.007 31158611
    [Google Scholar]
  29. Zhao T. Liu T. Wang L. Xie K. Tang H. Tang M. Dysfunction of neurotransmitter metabolism is associated with the severity of depression in first-diagnosed, drug-naïve depressed patients. J. Affect. Disord. 2024 349 332 341 10.1016/j.jad.2024.01.023 38199403
    [Google Scholar]
  30. Hu X. Xiao H. Zhou S. Application of proton magnetic resonance spectroscopy imaging technique in cognitive impairment after trau-matic brain injury. Chin J. Neurosurg. Neurol. 2021 48 2 197 201 10.16636/j.cnki.jinn.1673‑2642.2021.02.021
    [Google Scholar]
  31. Feigin V.L. Vos T. Nichols E. Owolabi M.O. Carroll W.M. Dichgans M. Deuschl G. Parmar P. Brainin M. Murray C. The global burden of neurological disorders: Translating evidence into policy. Lancet Neurol. 2020 19 3 255 265 10.1016/S1474‑4422(19)30411‑9 31813850
    [Google Scholar]
  32. Shaw B.C. Anders V.R. Tinkey R.A. Habean M.L. Brock O.D. Frostino B.J. Williams J.L. Immunity impacts cognitive deficits across neurological disorders. J. Neurochem. 2023 168 10 3512 3535 10.1111/jnc.15999 37899543
    [Google Scholar]
  33. Mai W. Zhang A. Liu Q. Tang L. Wei Y. Su J. Duan G. Teng J. Nong X. Yu B. Li C. Shao L. Deng D. Chen S. Zhao L. Effects of moxa cone moxibustion therapy on cognitive function and brain metabolic changes in MCI patients: A pilot 1H-MRS study. Front. Aging Neurosci. 2022 14 773687 10.3389/fnagi.2022.773687 35721029
    [Google Scholar]
  34. Li F. Zong W. Xin C. Ren F. Li N. Li H. Li X. Wu L. Dai Z. Chen W. Li M. Gao F. Wang G. Unlocking the link: How hip-pocampal glutathione-glutamate coupling predicts cognitive impairment in multiple sclerosis patients. Cereb. Cortex 2024 34 1 bhad400 10.1093/cercor/bhad400 37943724
    [Google Scholar]
  35. Kondo H.M. Terashima H. Kihara K. Kochiyama T. Shimada Y. Kawahara J.I. Prefrontal GABA and glutamate–glutamine levels affect sustained attention. Cereb. Cortex 2023 33 19 10441 10452 10.1093/cercor/bhad294 37562851
    [Google Scholar]
  36. Tseng H.H. Wu C.Y. Chang H.H. Lu T.H. Chang W.H. Hsu C.F. Lin R.Y. Yeh D.R. Shaw F.Z. Yang Y.K. Chen P.S. Posterior cingulate and medial prefrontal excitation-inhibition balance in euthymic bipolar disorder. Psychol. Med. 2024 54 11 3168 3176 10.1017/S0033291724001326 38825858
    [Google Scholar]
  37. Hone-Blanchet A. Vallet W. Shahid S. Ende G. Editorial: Proton magnetic resonance spectroscopy in brain aging: Inflammation, bloodflow, connectivity and cognitive decline. Front. Psychiatry 2022 13 1040967 10.3389/fpsyt.2022.1040967 36299543
    [Google Scholar]
  38. Fogel Y. Cognitive strategies: Moderating the relationship between executive functions and daily functioning. Int. J. Environ. Res. Public Health 2022 19 24 16845 10.3390/ijerph192416845 36554722
    [Google Scholar]
  39. Bieri G. Schroer A.B. Villeda S.A. Blood-to-brain communication in aging and rejuvenation. Nat. Neurosci. 2023 26 3 379 393 10.1038/s41593‑022‑01238‑8 36646876
    [Google Scholar]
  40. Huang C.Y. Lin L.L. Hwang I.S. Age-related differences in reorganization of functional connectivity for a dual task with increasing postural destabilization. Front. Aging Neurosci. 2017 9 96 10.3389/fnagi.2017.00096 28446874
    [Google Scholar]
  41. McQuail J.A. Frazier C.J. Bizon J.L. Molecular aspects of age-related cognitive decline: The role of GABA signaling. Trends Mol. Med. 2015 21 7 450 460 10.1016/j.molmed.2015.05.002 26070271
    [Google Scholar]
  42. Chalavi S. Pauwels L. Heise K.F. Zivari Adab H. Maes C. Puts N.A.J. Edden R.A.E. Swinnen S.P. The neurochemical basis of the contextual interference effect. Neurobiol. Aging 2018 66 85 96 10.1016/j.neurobiolaging.2018.02.014 29549874
    [Google Scholar]
  43. Porges E.C. Woods A.J. Edden R.A.E. Puts N.A.J. Harris A.D. Chen H. Garcia A.M. Seider T.R. Lamb D.G. Williamson J.B. Cohen R.A. Frontal gamma-aminobutyric acid concentrations are associated with cognitive performance in older adults. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 2017 2 1 38 44 10.1016/j.bpsc.2016.06.004 28217759
    [Google Scholar]
  44. Marsman A. Mandl R.C.W. Klomp D.W.J. Cahn W. Kahn R.S. Luijten P.R. Hulshoff Pol H.E. Intelligence and brain efficiency: Investigating the association between working memory performance, glutamate, and GABA. Front. Psychiatry 2017 8 154 10.3389/fpsyt.2017.00154 28966597
    [Google Scholar]
  45. Marenco S. Meyer C. van der Veen J.W. Zhang Y. Kelly R. Shen J. Weinberger D.R. Dickinson D. Berman K.F. Role of gamma-amino-butyric acid in the dorsal anterior cingulate in age-associated changes in cognition. Neuropsychopharmacology 2018 43 11 2285 2291 10.1038/s41386‑018‑0134‑5 30050047
    [Google Scholar]
  46. Hone-Blanchet A. Bohsali A. Krishnamurthy L.C. Shahid S. Lin Q. Zhao L. Loring D. Goldstein F. John S.E. Fleischer C.C. Levey A. Lah J. Qiu D. Crosson B. Relationships between frontal metabolites and Alzheimer’s disease biomarkers in cognitively normal older adults. Neurobiol. Aging 2022 109 22 30 10.1016/j.neurobiolaging.2021.09.016 34638000
    [Google Scholar]
  47. Koyun A.H. Talebi N. Werner A. Wendiggensen P. Kuntke P. Roessner V. Beste C. Stock A.K. Interactions of catecholamines and GABA+ in cognitive control: Insights from EEG and 1H-MRS. Neuroimage 2024 293 120619 10.1016/j.neuroimage.2024.120619 38679186
    [Google Scholar]
  48. Zhao Y. Feng S. Dong L. Wu Z. Ning Y. Dysfunction of large‐scale brain networks underlying cognitive impairments in shift work disorder. J. Sleep Res. 2024 33 4 e14080 10.1111/jsr.14080 37888149
    [Google Scholar]
  49. Sha P. Dong X. Research on adolescents regarding the indirect effect of depression, anxiety, and stress between tiktok use disorder and memory loss. Int. J. Environ. Res. Public Health 2021 18 16 8820 10.3390/ijerph18168820 34444569
    [Google Scholar]
  50. Kherchouche A. Ben-Ahmed O. Guillevin C. Tremblais B. Julian A. Fernandez-Maloigne C. Guillevin R. Attention-guided neural network for early dementia detection using MRS data. Comput. Med. Imaging Graph. 2022 99 102074 10.1016/j.compmedimag.2022.102074 35728368
    [Google Scholar]
  51. Kumar J. Liddle E.B. Fernandes C.C. Palaniyappan L. Hall E.L. Robson S.E. Simmonite M. Fiesal J. Katshu M.Z. Qureshi A. Skelton M. Christodoulou N.G. Brookes M.J. Morris P.G. Liddle P.F. Glutathione and glutamate in schizophrenia: A 7T MRS study. Mol. Psychiatry 2020 25 4 873 882 10.1038/s41380‑018‑0104‑7 29934548
    [Google Scholar]
  52. Sonmez A.I. Lewis C.P. Port J.D. Cabello-Arreola A. Blacker C.J. Seewoo B.J. McKean A.J. Leffler J.M. Frye M.A. Croarkin P.E. Glutamatergic correlates of bipolar symptoms in adolescents. J. Child Adolesc. Psychopharmacol. 2020 30 10 599 605 10.1089/cap.2020.0082 33179961
    [Google Scholar]
  53. Jeon P. Limongi R. Ford S.D. Branco C. Mackinley M. Gupta M. Powe L. Théberge J. Palaniyappan L. Glutathione as a molecu-lar marker of functional impairment in patients with at-risk mental state: 7-Tesla 1H-MRS study. Brain Sci. 2021 11 7 941 10.3390/brainsci11070941 34356175
    [Google Scholar]
  54. Wang M. Barker P.B. Cascella N.G. Coughlin J.M. Nestadt G. Nucifora F.C. Sedlak T.W. Kelly A. Younes L. Geman D. Pal-aniyappan L. Sawa A. Yang K. Longitudinal changes in brain metabolites in healthy controls and patients with first episode psychosis: A 7-Tesla MRS study. Mol. Psychiatry 2023 28 5 2018 2029 10.1038/s41380‑023‑01969‑5 36732587
    [Google Scholar]
  55. Kosová E. Pajuelo D. Greguš D. Brunovský M. Stopková P. Fajnerová I. Horáček J. Glutamatergic abnormalities in the pregenual anterior cingulate cortex in obsessive-compulsive disorder using magnetic resonance spectroscopy: A controlled study. Psychiatry Res. Neuroimaging 2023 335 111721 10.1016/j.pscychresns.2023.111721 37832259
    [Google Scholar]
  56. Wang X. Peng L. Zhan S. Yin X. Huang L. Huang J. Yang J. Zhang Y. Zeng Y. Liang S. Alterations in hippocampus-centered morphological features and function of the progression from normal cognition to mild cognitive impairment. Asian J. Psychiatr. 2024 93 103921 10.1016/j.ajp.2024.103921 38237533
    [Google Scholar]
  57. Lopez F.V. O’Shea A. Huo Z. DeKosky S.T. Trouard T.P. Alexander G.E. Woods A.J. Bowers D. Frontal–temporal regional differences in brain energy metabolism and mitochondrial function using 31P MRS in older adults. Geroscience 2024 46 3 3185 3195 10.1007/s11357‑023‑01046‑3 38225480
    [Google Scholar]
  58. Ambrose C.T. A therapeutic approach for senile dementias. Neuroangiogenesis. J. Alzheimers Dis. 2014 43 1 1 17 10.3233/JAD‑140498 25061056
    [Google Scholar]
  59. Smailovic U. Ferreira D. Ausén B. Ashton N.J. Koenig T. Zetterberg H. Blennow K. Jelic V. Decreased electroencephalography global field synchronization in slow-frequency bands characterizes synaptic dysfunction in amnestic subtypes of mild cognitive impair-ment. Front. Aging Neurosci. 2022 14 755454 10.3389/fnagi.2022.755454 35462693
    [Google Scholar]
  60. Vijayakumari A.A. Menon R.N. Thomas B. Arun T.M. Nandini M. Kesavadas C. Glutamatergic response to a low load working memory paradigm in the left dorsolateral prefrontal cortex in patients with mild cognitive impairment: A functional magnetic resonance spectroscopy study. Brain Imaging Behav. 2020 14 2 451 459 10.1007/s11682‑019‑00122‑7 31102169
    [Google Scholar]
  61. Liu W. Li J. Yang M. Ke X. Dai Y. Lin H. Wang S. Chen L. Tao J. Chemical genetic activation of the cholinergic basal forebrain hippocampal circuit rescues memory loss in Alzheimer’s disease. Alzheimers Res. Ther. 2022 14 1 53 10.1186/s13195‑022‑00994‑w 35418161
    [Google Scholar]
  62. Cao G. Edden R.A.E. Gao F. Li H. Gong T. Chen W. Liu X. Wang G. Zhao B. Reduced GABA levels correlate with cognitive impairment in patients with relapsing-remitting multiple sclerosis. Eur. Radiol. 2018 28 3 1140 1148 10.1007/s00330‑017‑5064‑9 28986640
    [Google Scholar]
  63. Oeltzschner G. Wijtenburg S.A. Mikkelsen M. Edden R.A.E. Barker P.B. Joo J.H. Leoutsakos J.M.S. Rowland L.M. Workman C.I. Smith G.S. Neurometabolites and associations with cognitive deficits in mild cognitive impairment: A magnetic resonance spectros-copy study at 7 Tesla. Neurobiol. Aging 2019 73 211 218 10.1016/j.neurobiolaging.2018.09.027 30390554
    [Google Scholar]
  64. Delli Pizzi S. Franciotti R. Ferretti A. Edden R.A.E. Zöllner H.J. Esposito R. Bubbico G. Aiello C. Calvanese F. Sensi S.L. Tartaro A. Onofrj M. Bonanni L. High γ-aminobutyric acid content within the medial prefrontal cortex is a functional signature of so-matic symptoms disorder in patients with Parkinson’s disease. Mov. Disord. 2020 35 12 2184 2192 10.1002/mds.28221 32744357
    [Google Scholar]
  65. Gozdas E. Hinkley L. Fingerhut H. Dacorro L. Gu M. Sacchet M.D. Hurd R. Hosseini S.M.H. 1H-MRS neurometabolites and associations with neurite microstructures and cognitive functions in amnestic mild cognitive impairment. Neuroimage Clin. 2022 36 103159 10.1016/j.nicl.2022.103159 36063758
    [Google Scholar]
  66. Fu X. Sun P. Zhang X. Zhu D. Qin Q. Lu J. Wang J. GABA in the anterior cingulate cortex mediates the association of white matter hyperintensities with executive function: A magnetic resonance spectroscopy study. Aging 2024 16 5 4282 4298 10.18632/aging.205585 38441529
    [Google Scholar]
  67. Li H. Heise K.F. Chalavi S. Puts N.A.J. Edden R.A.E. Swinnen S.P. The role of MRS-assessed GABA in human behavioral perfor-mance. Prog. Neurobiol. 2022 212 102247 10.1016/j.pneurobio.2022.102247 35149113
    [Google Scholar]
  68. Taube W. Lauber B. Changes in the cortical GABAergic inhibitory system with ageing and ageing‐related neurodegenerative diseases. J. Physiol. 2024 602 1 JP285656 10.1113/JP285656 39722574
    [Google Scholar]
  69. Gao Y. Liu Y. Zhao S. Liu Y. Zhang C. Hui S. Mikkelsen M. Edden R.A.E. Meng X. Yu B. Xiao L. MRS study on the corre-lation between frontal GABA+/Glx ratio and abnormal cognitive function in medication-naive patients with narcolepsy. Sleep Med. 2024 119 1 8 10.1016/j.sleep.2024.04.004 38626481
    [Google Scholar]
  70. Ribeiro M.J. Violante I.R. Bernardino I. Edden R.A.E. Castelo-Branco M. Abnormal relationship between GABA, neurophysiology and impulsive behavior in neurofibromatosis type 1. Cortex 2015 64 194 208 10.1016/j.cortex.2014.10.019 25437375
    [Google Scholar]
  71. Silaidos C. Pilatus U. Grewal R. Matura S. Lienerth B. Pantel J. Eckert G.P. Sex-associated differences in mitochondrial function in human peripheral blood mononuclear cells (PBMCs) and brain. Biol. Sex Differ. 2018 9 1 34 10.1186/s13293‑018‑0193‑7 30045765
    [Google Scholar]
  72. Bravi B. Paolini M. Colombo F. Palladini M. Bettonagli V. Mazza M.G. Lorenzo R.D. Rovere-Querini P. Benedetti F. Poletti S. Long term effect of COVID-19 on brain metabolism and connectivity. Neuroscience 2025 580 1 8 10.1016/j.neuroscience.2025.06.015 40516783
    [Google Scholar]
  73. Baek J.H. Park H. Kang H. Kim R. Kang J.S. Kim H.J. The role of glutamine homeostasis in emotional and cognitive functions. Int. J. Mol. Sci. 2024 25 2 1302 10.3390/ijms25021302 38279303
    [Google Scholar]
  74. Woo J. Min J.O. Kang D.S. Kim Y.S. Jung G.H. Park H.J. Kim S. An H. Kwon J. Kim J. Shim I. Kim H.G. Lee C.J. Yoon B.E. Control of motor coordination by astrocytic tonic GABA release through modulation of excitation/inhibition balance in cerebellum. Proc. Natl. Acad. Sci. 2018 115 19 5004 5009 10.1073/pnas.1721187115 29691318
    [Google Scholar]
  75. Niu B. Liao K. Zhou Y. Wen T. Quan G. Pan X. Wu C. Application of glutathione depletion in cancer therapy: Enhanced ROS-based therapy, ferroptosis, and chemotherapy. Biomaterials 2021 277 121110 10.1016/j.biomaterials.2021.121110 34482088
    [Google Scholar]
  76. Finkelman T. Furman-Haran E. Paz R. Tal A. Quantifying the excitatory-inhibitory balance: A comparison of SemiLASER and MEGA-SemiLASER for simultaneously measuring GABA and glutamate at 7T. Neuroimage 2022 247 118810 10.1016/j.neuroimage.2021.118810 34906716
    [Google Scholar]
  77. Francis J.S. Nguyen Q. Markov V. Leone P. Over‐expression of N‐acetylaspartate synthase exacerbates pathological energetic deficit and accelerates cognitive decline in the 5xFAD mouse. J. Neurochem. 2024 168 2 69 82 10.1111/jnc.16044 38178803
    [Google Scholar]
  78. Lopes J.J. Rae C.D. Meyer D. Yolland C. Neill E. Castle D. Dean B. Rossell S.L. Glutamate concentrations and cognitive deficits in ultra-treatment-resistant Schizophrenia: An exploratory and comparative 1H-MRS study. Psychiatry Res. Neuroimaging 2025 347 111926 10.1016/j.pscychresns.2024.111926 39642669
    [Google Scholar]
  79. Penet M.F. Kakkad S. Wildes F. Bhujwalla Z.M. Water and collagen content are high in pancreatic cancer: Implications for quantitative metabolic imaging. Front. Oncol. 2021 10 599204 10.3389/fonc.2020.599204 33585215
    [Google Scholar]
  80. Li H. Rodríguez-Nieto G. Chalavi S. Seer C. Mikkelsen M. Edden R.A.E. Swinnen S.P. MRS-assessed brain GABA modulation in response to task performance and learning. Behav. Brain Funct. 2024 20 1 22 10.1186/s12993‑024‑00248‑9 39217354
    [Google Scholar]
  81. Baeshen A. Wyss P.O. Henning A. O’Gorman R.L. Piccirelli M. Kollias S. Michels L. Test-retest reliability of the brain metabo-lites GABA and Glx with JPRESS, PRESS, and MEGA-PRESS MRS sequences in vivo at 3T. J. Magn. Reson. Imaging 2020 51 4 1181 1191 10.1002/jmri.26921 31667944
    [Google Scholar]
  82. Wu X. Yuan J. Yang Y. Han S. Dai H. Wang L. Li Y. Elevated GABA level in the precuneus and its association with pain intensity in patients with postherpetic neuralgia: An initial proton magnetic resonance spectroscopy study. Eur. J. Radiol. 2022 157 110568 10.1016/j.ejrad.2022.110568 36279626
    [Google Scholar]
  83. Ito T. Tanaka-Mizuno S. Iwashita N. Tooyama I. Shiino A. Miura K. Fukui S. Proton magnetic resonance spectroscopy assess-ment of metabolite status of the anterior cingulate cortex in chronic pain patients and healthy controls. J. Pain Res. 2017 10 287 293 10.2147/JPR.S123403 28203104
    [Google Scholar]
  84. Zhang H. Zou Y. Lei H. Regional metabolic differences in rat prefrontal cortex measured with in vivo 1H‐MRS correlate with regional histochemical differences. NMR Biomed. 2019 32 1 e4024 10.1002/nbm.4024 30376204
    [Google Scholar]
  85. Zacharopoulos G. Emir U. Cohen Kadosh R. The cross‐sectional interplay between neurochemical profile and brain connectivity. Hum. Brain Mapp. 2021 42 9 2722 2733 10.1002/hbm.25396 33835605
    [Google Scholar]
  86. Kühn S. Schubert F. Mekle R. Wenger E. Ittermann B. Lindenberger U. Gallinat J. Neurotransmitter changes during interference task in anterior cingulate cortex: Evidence from fMRI-guided functional MRS at 3 T. Brain Struct. Funct. 2016 221 5 2541 2551 10.1007/s00429‑015‑1057‑0 25976598
    [Google Scholar]
  87. Günay O. Abamor E. Environmental radiation dose rate arising from patients of PET/CT. Int. J. Environ. Sci. Technol. 2019 16 9 5177 5184 10.1007/s13762‑018‑2040‑0
    [Google Scholar]
  88. Kim M.S. Luo S. Azad A. Campbell C.E. Felix K. Cabeen R.P. Belcher B.R. Kim R. Serrano-Gonzalez M. Herting M.M. Pre-frontal cortex and amygdala subregion morphology are associated with obesity and dietary self-control in children and adolescents. Front. Hum. Neurosci. 2020 14 563415 10.3389/fnhum.2020.563415 33343315
    [Google Scholar]
  89. McQueen G. Sendt K.V. Gillespie A. Avila A. Lally J. Vallianatou K. Chang N. Ferreira D. Borgan F. Howes O.D. Barker G.J. Lythgoe D.J. Stone J.M. McGuire P. MacCabe J.H. Egerton A. Changes in brain glutamate on switching to clozapine in treat-ment-resistant Schizophrenia. Schizophr. Bull. 2021 47 3 662 671 10.1093/schbul/sbaa156 33398325
    [Google Scholar]
  90. Hong S. Shen J. Neurochemical correlations in short echo time proton magnetic resonance spectroscopy. NMR Biomed. 2023 36 7 e4910 10.1002/nbm.4910 36681860
    [Google Scholar]
  91. Wang J. Ji B. Lei Y. Liu T. Mao H. Yang X. Denoising magnetic resonance spectroscopy (MRS) data using stacked autoencoder for improving signal‐to‐noise ratio and speed of MRS. Med. Phys. 2023 50 12 7955 7966 10.1002/mp.16831 37947479
    [Google Scholar]
  92. Zeng Z. He J. Yao T. Characteristic early changes of Glu and Cho in brain regions affected by different types of subjective cognitive decline and their clinical significance. Medicine 2023 102 49 e36457 10.1097/MD.0000000000036457 38065860
    [Google Scholar]
  93. Sabihi S. Goodpaster C. Maurer S. Leuner B. GABA in the medial prefrontal cortex regulates anxiety-like behavior during the postpar-tum period. Behav. Brain Res. 2021 398 112967 10.1016/j.bbr.2020.112967 33075397
    [Google Scholar]
  94. Overcast W.B. Davis K.M. Ho C.Y. Hutchins G.D. Green M.A. Graner B.D. Veronesi M.C. Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors. Curr. Oncol. Rep. 2021 23 3 34 10.1007/s11912‑021‑01020‑2 33599882
    [Google Scholar]
  95. Haider L. Zrzavy T. Hametner S. Höftberger R. Bagnato F. Grabner G. Trattnig S. Pfeifenbring S. Brück W. Lassmann H. The topograpy of demyelination and neurodegeneration in the multiple sclerosis brain. Brain 2016 139 3 807 815 10.1093/brain/awv398 26912645
    [Google Scholar]
  96. Kim J.W. Lee C.H. Yang Z. Kim B.H. Lee Y.S. Kim K.A. The spectrum of magnetic resonance imaging proton density fat fraction (MRI-PDFF), magnetic resonance spectroscopy (MRS), and two different histopathologic methods (artificial intelligence vs. pathologist) in quantifying hepatic steatosis. Quant. Imaging Med. Surg. 2022 12 11 5251 5262 10.21037/qims‑22‑393 36330193
    [Google Scholar]
  97. Unruh D. Kolluru V.S.C. Baskaran A. Chen Y. Chan M.K.Y. Theory+AI/ML for microscopy and spectroscopy: Challenges and opportunities. MRS Bull. 2022 47 10 1024 1035 10.1557/s43577‑022‑00446‑8
    [Google Scholar]
  98. Dao T.N.P. Dang H.N.T. Pham M.T.K. Nguyen H.T. Tran Chi C. Le M.V. Prognosticating global functional outcome in the recur-rent ischemic stroke using baseline clinical and pre‐clinical features: A machine learning study. J. Eval. Clin. Pract. 2025 31 1 e14100 10.1111/jep.14100 39031001
    [Google Scholar]
  99. Uddin M. Wang Y. Woodbury-Smith M. Artificial intelligence for precision medicine in neurodevelopmental disorders. NPJ Digit. Med. 2019 2 1 112 10.1038/s41746‑019‑0191‑0 31799421
    [Google Scholar]
  100. Cuypers K. Hehl M. van Aalst J. Chalavi S. Mikkelsen M. Van Laere K. Dupont P. Mantini D. Swinnen S.P. Age-related GA-BAergic differences in the primary sensorimotor cortex: A multimodal approach combining PET, MRS and TMS. Neuroimage 2021 226 117536 10.1016/j.neuroimage.2020.117536 33186716
    [Google Scholar]
  101. Acosta J.N. Falcone G.J. Rajpurkar P. Topol E.J. Multimodal biomedical AI. Nat. Med. 2022 28 9 1773 1784 10.1038/s41591‑022‑01981‑2 36109635
    [Google Scholar]
/content/journals/cn/10.2174/011570159X402624250926110831
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  • Article Type:
    Review Article
Keywords: mental disorders ; GABA ; MRS ; metabolic substances ; cognitive function ; neurological diseases ; Glu
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