Louis, D. N. et al. The 2016 World Well being Group Classification of Tumors of the Central Nervous System: a abstract. Acta Neuropathol. 131, 803–820 (2016).
Ostrom, Q. T., Cioffi, G., Waite, Ok., Kruchko, C. & Barnholtz-Sloan, J. S. CBTRUS statistical report: main mind and different central nervous system tumors recognized in the US in 2014–2018. Neuro Oncol. https://doi.org/10.1093/neuonc/noab200 (2021).
Boele, F. W., Klein, M., Reijneveld, J. C., Verdonck-de Leeuw, I. M. & Heimans, J. J. Symptom administration and high quality of life in glioma sufferers. CNS Oncol. 3, 37–47 (2014).
Weller, M. et al. EANO tips on the prognosis and remedy of diffuse gliomas of maturity. Nat. Rev. Clin. Oncol. 18, 170–186 (2021).
Stommel, M., Kurtz, M. E., Kurtz, J. C., Given, C. W. & Given, B. A. A longitudinal evaluation of the course of depressive symptomatology in geriatric sufferers with most cancers of the breast, colon, lung, or prostate. Well being Psychol. 23, 564–573 (2004).
Krebber, A. M. H. et al. Prevalence of melancholy in most cancers sufferers: a meta-analysis of diagnostic interviews and self-report devices. Psychooncology. 23, 121–130 (2014).
Hu, Y. et al. Melancholy and high quality of life in sufferers with gliomas: a story evaluate. J Clin. Med. 11, 4811 (2022).
Rooney, A. G., Carson, A. & Grant, R. Melancholy in cerebral glioma sufferers: a scientific evaluate of observational research. J. Natl Most cancers Inst. 103, 61–76 (2011).
Music, L. et al. Irritation and behavioral signs in preoperational glioma sufferers: is melancholy, anxiousness, and cognitive impairment associated to markers of systemic irritation? Mind Behav. 10, e01771 (2020).
Campanella, F., Shallice, T., Ius, T., Fabbro, F. & Skrap, M. Affect of mind tumour location on emtion and persona: a voxel-based lesion–symptom mapping examine on mentalization processes. Mind 137, 2532–2545 (2014).
Boele, F. W., Rooney, A. G., Grant, R. & Klein, M. Psychiatric signs in glioma sufferers: from prognosis to administration. Neuropsychiatr. Dis. Deal with. 11, 1413–1420 (2015).
Lewandowska, A., Rudzki, G., Lewandowski, T. & Rudzki, S. The issues and desires of sufferers recognized with most cancers and their caregivers. Int. J. Environ. Res. Public Well being 18, 87 (2021).
Christensen, M. C., Ren, H. & Fagiolini, A. Emotional blunting in sufferers with melancholy. Half II: relationship with functioning, well-being, and high quality of life. Ann. Gen. Psychiatry 21, 20 (2022).
Gläscher, J. et al. Lesion mapping of cognitive skills linked to intelligence. Neuron 61, 681–691 (2009).
Pisoni, A. et al. The neural correlates of auditory–verbal short-term reminiscence: a voxel-based lesion–symptom mapping examine on 103 sufferers after glioma elimination. Mind Struct. Funct. 224, 2199–2211 (2019).
Hendriks, E. J. et al. Linking late cognitive final result with glioma surgical procedure location utilizing resection cavity maps. Hum. Mind Mapp. 39, 2064–2074 (2018).
Bates, E. et al. Voxel-based lesion–symptom mapping. Nat. Neurosci. 6, 448–450 (2003).
Gleichgerrcht, E., Fridriksson, J., Rorden, C. & Bonilha, L. Connectome-based lesion–symptom mapping (CLSM): a novel method to map neurological perform. Neuroimage Clin. 16, 461–467 (2017).
Zhang, Y., Kimberg, D. Y., Coslett, H. B., Schwartz, M. F. & Wang, Z. Multivariate lesion–symptom mapping utilizing help vector regression. Hum. Mind Mapp. 35, 5861–5876 (2014).
Achilles, E. I. S. et al. Utilizing multi-level Bayesian lesion–symptom mapping to probe the body-part-specificity of gesture imitation abilities. Neuroimage 161, 94–103 (2017).
Boes, A. D. et al. Community localization of neurological signs from focal mind lesions. Mind 138, 3061–3075 (2015).
Thiebaut de Schotten, M., Foulon, C. & Nachev, P. Mind disconnections hyperlink structural connectivity with perform and behavior. Nat. Commun. 11, 5094 (2020).
Salvalaggio, A., De Filippo De Grazia, M., Zorzi, M., Thiebaut de Schotten, M. & Corbetta, M. Publish-stroke deficit prediction from lesion and oblique structural and useful disconnection. Mind 143, 2173–2188 (2020).
Trapp, N. T. et al. Massive-scale lesion symptom mapping of melancholy identifies mind areas for danger and resilience. Mind 146, 1672–1685 (2023).
Weaver, N. A. et al. Strategic infarct areas for poststroke depressive signs: a lesion- and disconnection–symptom mapping examine. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 8, 387–396 (2023).
Pan, C. et al. Neural substrates of poststroke melancholy: present opinions and methodology traits. Entrance. Neurosci. 16, 812410 (2022).
van Grinsven, E. E. et al. The impression of etiology in lesion–symptom mapping—a direct comparability between tumor and stroke. Neuroimage Clin. 37, 103305 (2023).
Leonetti, A. et al. Elements influencing temper issues and well being associated high quality of life in adults with glioma: a longitudinal examine. Entrance. Oncol. 11, 662039 (2021).
Bunevicius, A., Deltuva, V. P. & Tamasauskas, A. Affiliation of pre-operative depressive and anxiousness signs with five-year survival of glioma and meningioma sufferers: a potential cohort examine. Oncotarget 8, 57543–57551 (2017).
Li, Y., Jin, Y., Wu, D. & Zhang, L. A melancholy community brought on by mind tumours. Mind Struct. Funct. 227, 2787–2795 (2022).
Arnold, S. D. et al. Analysis and characterization of generalized anxiousness and melancholy in sufferers with main mind tumors. Neuro Oncol. 10, 171–181 (2008).
Catani, M., Dell’Acqua, F. & Thiebaut de Schotten, M. A revised limbic system mannequin for reminiscence, emotion and behavior. Neurosci. Biobehav. Rev. 37, 1724–1737 (2013).
Conner, A. Ok. et al. A connectomic atlas of the human cerebrum—chapter 13: tractographic description of the inferior fronto-occipital fasciculus. Oper. Neurosurg. 15, S436–S443 (2018).
Drevets, W. C., Value, J. L. & Furey, M. L. Mind structural and useful abnormalities in temper issues: implications for neurocircuitry fashions of melancholy. Mind Struct. Funct. 213, 93–118 (2008).
Hilland, E. et al. Exploring the hyperlinks between particular melancholy signs and mind construction: a community examine. Psychiatry Clin. Neurosci. 74, 220–221 (2020).
Li, B. J. et al. A mind community mannequin for melancholy: from symptom understanding to illness intervention. CNS Neurosci. Ther. 24, 1004–1019 (2018).
Grey, J. P., Müller, V. I., Eickhoff, S. B. & Fox, P. T. Multimodal abnormalities of mind construction and performance in main depressive dysfunction: a meta-analysis of neuroimaging research. Am. J. Psychiatry 177, 422–434 (2020).
Wijeratne, T. & Gross sales, C. Understanding why post-stroke melancholy will be the norm relatively than the exception: the anatomical and neuroinflammatory correlates of post-stroke melancholy. J. Clin. Med. 10, 1674 (2021).
Richey, L. N. et al. Neuroimaging correlates of syndromal melancholy following traumatic mind damage: a scientific evaluate of the literature. J. Concussion 63, 119–132 (2022).
Shen, Q. et al. Impaired white matter microstructure related to extreme depressive signs in sufferers with PD. Mind Imaging Behav. 16, 169–175 (2022).
Elkommos, S. & Mula, M. A scientific evaluate of neuroimaging research of melancholy in adults with epilepsy. Epilepsy Behav. 115, 107695 (2021).
Herbet, G., Yordanova, Y. N. & Duffau, H. Left spatial neglect evoked by electrostimulation of the proper inferior fronto-occipital fasciculus. Mind Topogr. 30, 747–756 (2017).
Herbet, G., Moritz-Gasser, S. & Duffau, H. Direct proof for the contributive function of the proper inferior fronto-occipital fasciculus in non-verbal semantic cognition. Mind Struct. Funct. 222, 1597–1610 (2017).
Nys, G. M. S. et al. Early cognitive impairment predicts long-term depressive signs and high quality of life after stroke. J. Neurol. Sci. 247, 149–156 (2006).
Pan, C. et al. Structural disconnection-based prediction of poststroke melancholy. Transl. Psychiatry 12, 461 (2022).
He, E. et al. White matter alterations in depressive dysfunction. Entrance. Immunol. 13, 826812 (2022).
Turner, R. J. & Noh, S. Bodily incapacity and melancholy: a longitudinal evaluation. J. Well being Soc. Behav. 29, 23–37 (1988).
Bjelland, I. et al. Does the next academic degree shield in opposition to anxiousness and melancholy? The HUNT examine. Soc. Sci. Med. 66, 1334–1345 (2008).
Schaepe, Ok. S. Dangerous information and first impressions: affected person and household caregiver accounts of studying the most cancers prognosis. Soc. Sci. Med. 73, 912–921 (2011).
Infurna, F. J., Gerstorf, D. & Ram, N. The character and correlates of change in depressive signs with most cancers prognosis: response and adaptation. Psychol. Getting older 28, 386–401 (2013).
Vos, M. S., Putter, H., van Houwelingen, H. C. & de Haes, H. C. J. M. Denial in lung most cancers sufferers: a longitudinal examine. Psychooncology 17, 1163–1171 (2008).
Vos, M. S., Putter, H., van Houwelingen, H. C. & de Haes, H. C. J. M. Denial and social and emotional outcomes in lung most cancers sufferers: the protecting impact of denial. Lung Most cancers 72, 119–124 (2011).
Andrewes, H. E., Drummond, Ok. J., Rosenthal, M., Bucknill, A. & Andrewes, D. G. Consciousness of psychological and relationship issues amongst mind tumour sufferers and its affiliation with carer misery. Psychooncology 22, 2200–2205 (2013).
Starkstein, S. E., Jorge, R. E. & Robinson, R. G. The frequency, scientific correlates, and mechanism of anosognosia after stroke. Can. J. Psychiatry 55, 355–361 (2010).
Starkstein, S. E., Fedoroff, J. P., Value, T. R., Leiguarda, R. & Robinson, R. G. Anosognosia in sufferers with cerebrovascular lesions: a examine of causative elements. Stroke. 23, 1446–1453 (1992).
Cocchini, G., Crosta, E., Allen, R., Zaro, F. & Beschin, N. Relationship between anosognosia and melancholy in aphasic sufferers. J. Clin. Exp. Neuropsychol. 35, 337–347 (2013).
Conde-Sala, J. L. et al. Severity of dementia, anosognosia, and melancholy in relation to the standard of lifetime of sufferers with Alzheimer illness: discrepancies between sufferers and caregivers. Am. J. Geriatr. Psychiatry 22, 138–147 (2014).
Mograbi, D. C. & Morris, R. G. On the relation amongst temper, apathy, and anosognosia in Alzheimer’s illness. J. Int. Neuropsychol. Soc. 20, 2–7 (2014).
Yoo, H. S. et al. Cognitive anosognosia is related to frontal dysfunction and decrease melancholy in Parkinson’s illness. Eur. J. Neurol. 27, 951–958 (2020).
Le Heron, C., Apps, M. A. J. & Husain, M. The anatomy of apathy: a neurocognitive framework for amotivated behaviour. Neuropsychologia 118, 54–67 (2018).
Hollocks, M. J. et al. Differential relationships between apathy and melancholy with white matter microstructural adjustments and useful outcomes. Mind 138, 3803–3815 (2015).
Manca, R., Jones, S. A. & Venneri, A. Macrostructural and microstructural white matter alterations are related to apathy throughout the scientific Alzheimer’s illness spectrum. Mind Sci. 12, 1383 (2022).
Steffens, D. C., Fahed, M., Manning, Ok. J. & Wang, L. The neurobiology of apathy in melancholy and neurocognitive impairment in older adults: a evaluate of epidemiological, scientific, neuropsychological and organic analysis. Transl. Psychiatry 12, 525 (2022).
Mulin, E. et al. Diagnostic standards for apathy in scientific follow. Int. J. Geriatr. Psychiatry. 26, 158–165 (2011).
Fahed, M. & Steffens, D. C. Apathy: neurobiology, evaluation and remedy. Clin. Psychopharmacol. Neurosci. 19, 181–189 (2021).
Miller, D. S. et al. Diagnostic standards for apathy in neurocognitive issues. Alzheimers Dement. 17, 1892–1904 (2021).
Van Reekum, R., Donald, F. R. C. P. C., Stuss, T. L. & Ostrander, R. N. Apathy: why care? J. Neuropsychiatry Clin. Neurosci. 17, 7–19 (2005).
Levy, R. & Dubois, B. Apathy and the useful anatomy of the prefrontal cortex-basal ganglia circuits. Cereb. Cortex 16, 916–928 (2006).
Aubignat, M. et al. Poststroke apathy: main function of cognitive, depressive and neurological issues over imaging determinants. Cortex 160, 55–66 (2023).
Schei, S., Sagberg, L. M., Bø, L. E., Reinertsen, I. & Solheim, O. Affiliation between patient-reported cognitive perform and placement of glioblastoma. Neurosurg. Rev. 46, 282 (2023).
Hahn, C. et al. Apathy and white matter integrity in Alzheimer’s illness: a complete mind evaluation with tract-based spatial statistics. PLoS ONE 8, e53493 (2013).
Powers, J. P. et al. White matter illness contributes to apathy and disinhibition in behavioral variant frontotemporal dementia. Cogn. Behav. Neurol. 27, 206–214 (2014).
Setiadi, T. M. et al. Widespread white matter aberration is related to the severity of apathy in amnestic gentle cognitive impairment: tract-based spatial statistics evaluation. Neuroimage Clin. 29, 102567 (2021).
Bopp, M. H. A. et al. White matter integrity and symptom dimensions of schizophrenia: a diffusion tensor imaging examine. Schizophr. Res. 184, 59–68 (2017).
Whitford, T. J. et al. Localized abnormalities within the cingulum bundle in sufferers with schizophrenia: a diffusion tensor tractography examine. Neuroimage Clin. 5, 93–99 (2014).
Hoare, J. et al. White matter correlates of apathy in HIV-positive topics: a diffusion tensor imaging examine. J. Neuropsychiatry Clin. Neurosci. 22, 313–320 (2010).
Rowland, L. M. et al. White matter alterations in deficit schizophrenia. Neuropsychopharmacology 34, 1514–1522 (2009).
Nakajima, R., Kinoshita, M., Shinohara, H. & Nakada, M. The superior longitudinal fascicle: reconsidering the fronto-parietal neural community primarily based on anatomy and performance. Mind Imaging Behav. 14, 2817–2830 (2020).
Padmanabhan, J. L. et al. A human melancholy circuit derived from focal mind lesions. Biol. Psychiatry 86, 749–758 (2019).
Dean, J. & Keshavan, M. The neurobiology of melancholy: an built-in view. Asian J. Psychiatry 27, 101–111 (2017).
Monje, M. Synaptic communication in mind most cancers. Most cancers Res. 80, 2979–2982 (2020).
Bosma, I. et al. Disturbed useful mind networks and neurocognitive perform in low-grade glioma sufferers: a graph theoretical evaluation of resting-state MEG. Nonlinear Biomed. Phys. 3, 9 (2009).
Derks, J. et al. Understanding international mind community alterations in glioma sufferers. Mind Join. 11, 865–974 (2021).
Hart, M. G., Romero-Garcia, R., Value, S. J. & Suckling, J. International results of focal mind tumors on useful complexity and community robustness: a potential cohort examine. Neurosurgery 84, 1201–1213 (2019).
Numan, T. et al. Non-invasively measured mind exercise and radiological development in diffuse glioma. Sci. Rep. 11, 18990 (2021).
Venkatesh, H. S. et al. Focusing on neuronal activity-regulated neuroligin-3 dependency in high-grade glioma. Nature 549, 533–537 (2017).
Venkataramani, V. et al. Glutamatergic synaptic enter to glioma cells drives mind tumour development. Nature 573, 532–538 (2019).
Cuddapah, V. A., Robel, S., Watkins, S. & Sontheimer, H. A neurocentric perspective on glioma invasion. Nat. Rev. Neurosci. 15, 455–465 (2014).
Venkatesh, H. S. et al. Electrical and synaptic integration of glioma into neural circuits. Nature. 573, 539–545 (2019).
Krishna, S. et al. Glioblastoma remodelling of human neural circuits decreases survival. Nature 617, 599–607 (2023).
Traut, T. et al. MEG imaging of recurrent gliomas reveals useful plasticity of hemispheric language specialization. Hum. Mind Mapp. 40, 1082–1092 (2019).
Guggisberg, A. G. et al. Mapping useful connectivity in sufferers with mind lesions. Ann. Neurol. 63, 193–203 (2008).
Seghier, M. L. The elusive metric of lesion load. Mind Struct. Funct. 228, 703–716 (2023).
Hope, T. M. H., Seghier, M. L., Prejawa, S., Leff, A. P. & Value, C. J. Distinguishing the impact of lesion load from tract disconnection within the arcuate and uncinate fasciculi. Neuroimage 125, 1169–1173 (2016).
Joutsa, J., Corp, D. T. & Fox, M. D. Lesion community mapping for symptom localization: current developments and future instructions. Curr. Opin. Neurol. 35, 453–459 (2022).
Duffau, H. Diffuse low-grade gliomas and neuroplasticity. Diagn. Interv. Imaging 95, 945–955 (2014).
Kong, N. W., Gibb, W. R. & Tate, M. C. Neuroplasticity: insights from sufferers harboring gliomas. Neural Plast. 2016, 2365063 (2016).
Visser, M. et al. Inter-rater settlement in glioma segmentations on longitudinal MRI. Neuroimage Clin. 22, 101727 (2019).
Visser, M. et al. Correct MR picture registration to anatomical reference area for diffuse glioma. Entrance. Neurosci. 14, 585 (2020).
Radloff, L. S. The CES-D scale: a self-report melancholy scale for analysis within the common inhabitants. Appl. Psychol. Meas. 1, 385–401 (1977).
Sekely, A. et al. Neurocognitive impairment, neurobehavioral signs, fatigue, sleep disturbance, and depressive signs in sufferers with newly recognized glioblastoma. Neurooncol. Pract. 10, 89–96 (2022).
Röttgering, J. G. et al. Symptom networks in glioma sufferers: understanding the multidimensionality of signs and high quality of life. J Most cancers Surviv. 18, 1032–1041 (2023).
Verhage, F. Intelligentie en leeftijd onderzoek bij Nederlanders van twaalf tot zevenenzeventig jaar (Van Gorcum, 1964).
Schag, C. C., Heinrich, R. L. & Ganz, P. A. Karnofsky efficiency standing revisited: reliability, validity, and tips. J. Clin. Oncol. 2, 187–193 (1984).
Ware, J. E. J. & Sherbourne, C. D. The MOS 36-item short-form well being survey (SF-36). I. Conceptual framework and merchandise choice. Med. Care. 30, 473–483 (1992).
Chen, B. et al. Psychiatric and behavioral unwanted side effects of antiepileptic medication in adults with epilepsy. Epilepsy Behav. 76, 24–31 (2017).
Hann, D., Winter, Ok. & Jacobsen, P. Measurement of depressive signs in most cancers sufferers: analysis of the Middle for Epidemiological Research Melancholy Scale (CES-D). J. Psychosom. Res. 46, 437–443 (1999).
Bouma, J., Ranchor, A. V., Sanderman, R. & van Sonderen, E. Het meten van symptomen van depressie met de CES-D: Een handleiding (Noordelijk Centrum voor Gezondheidsvraagstukken, Rijksuniversiteit Groningen, 1995).
Lally, R. M. et al. CaringGuidanceTM after breast most cancers prognosis eHealth psychoeducational intervention to cut back early post-diagnosis misery. Assist. Care Most cancers 28, 2163–2174 (2020).
Pemberton, H.G. et al. Multi-class glioma segmentation on real-world knowledge with lacking MRI sequences: comparability of three deep studying algorithms. Sci. Rep. 13, 18911 (2023).
Kikinis, R., Pieper, S. D., Vosburgh, Ok. G. in Intraoperative Imaging and Picture-Guided Remedy (ed. Jolesz, F. A.) 277–289 (Springer, 2014); https://doi.org/10.1007/978-1-4614-7657-3_19
Fedorov, A. et al. 3D Slicer as a picture computing platform for the quantitative imaging community. Magn. Reson. Imaging 30, 1323–1341 (2012).
Avants, B. B., Epstein, C. L., Grossman, M. & Gee, J. C. Symmetric diffeomorphic picture registration with cross-correlation: evaluating automated labeling of aged and neurodegenerative mind. Med. Picture Anal. 12, 26–41 (2008).
Isensee, F. et al. Automated mind extraction of multisequence MRI utilizing synthetic neural networks. Hum. Mind Mapp. 40, 4952–4964 (2019).
Foulon, C. et al. Superior lesion symptom mapping analyses and implementation as BCBtoolkit. Gigascience https://doi.org/10.1093/gigascience/giy004 (2018).
Vu, A. T. et al. Excessive decision complete mind diffusion imaging at 7T for the Human Connectome Challenge. Neuroimage 122, 318–331 (2015).
Klein, A. et al. Analysis of 14 nonlinear deformation algorithms utilized to human mind MRI registration. Neuroimage 46, 786–802 (2009).
Avants, B. B. et al. A reproducible analysis of ANTs similarity metric efficiency in mind picture registration. Neuroimage 54, 2033–2044 (2011).
Wang, R. & Benner, T. Diffusion toolkit: a software program package deal for diffusion imaging knowledge processing and tractography. Proc. Intl Soc. Magn. Reson. Med. 15, 3720 (2007).
Warrington, S. et al. XTRACT—standardised protocols for automated tractography within the human and macaque mind. Neuroimage 217, 116923 (2020).
Thomas Yeo, B. T. et al. The group of the human cerebral cortex estimated by intrinsic useful connectivity. J. Neurophysiol. 106, 1125–1165 (2011).
Makris, N. et al. Decreased quantity of left and whole anterior insular lobule in schizophrenia. Schizophr. Res. 83, 155–171 (2006).
Frazier, J. A. et al. Structural mind magnetic resonance imaging of limbic and thalamic volumes in pediatric bipolar dysfunction. Am. J. Pyschiatry 162, 1256–1265 (2005).
Desikan, R. S. et al. An automatic labeling system for subdividing the human cerebral cortex on MRI scans into gyral primarily based areas of curiosity. Neuroimage. 31, 968–980 (2006).
Goldstein, J. M. et al. Hypothalamic abnormalities in schizophrenia: intercourse results and genetic vulnerability. Biol. Psychiatry 61, 935–945 (2007).
Thiebaut De Schotten, M. et al. Injury to white matter pathways in subacute and continual spatial neglect: a gaggle examine and a couple of single-case research with full digital ‘in vivo’ tractography dissection. Cereb. Cortex 24, 691–706 (2014).
Capretto, T. et al. Bambi: a easy interface for becoming Bayesian linear fashions in Python. J. Stat. Softw. https://doi.org/10.18637/jss.v103.i15 (2022).
Pustina, D., Avants, B., Faseyitan, O. Ok., Medaglia, J. D. & Coslett, H. B. Improved accuracy of lesion to symptom mapping with multivariate sparse canonical correlations. Neuropsychologia 115, 154–166 (2018).
Gervini Zampieri Centeno, E., Moreni, G., Vriend, C., Douw, L. & Nóbrega Santos, A. A hands-on tutorial on community and topological neuroscience. Mind Struct. Funct. 227, 741–762 (2021).
Golbeck, J. in Analyzing the Social Net (ed. Golbeck, J.) 25–44 (Morgan Kaufmann, 2013); https://doi.org/10.1016/B978-0-12-405531-5.00003-1
Latora, V. & Marchiori, M. Environment friendly habits of small-world networks. Phys. Rev. Lett. 87, 198701 (2001).
Tijhuis, F. et al. Human Connectome undertaking rfMRI repository. GitHub https://github.com/floristijhuis/HCP-rfMRI-repository (2023).
Schaefer, A. et al. Native–international parcellation of the human cerebral cortex from intrinsic useful connectivity MRI. Cereb. Cortex 28, 3095–3114 (2018).
Tian, Y., Margulies, D. S., Breakspear, M. & Zalesky, A. Topographic group of the human subcortex unveiled with useful connectivity gradients. Nat. Neurosci. 23, 1421–1432 (2020).
Tijhuis, F. B. et al. Human connectome undertaking resting-state fMRI connectivity matrices (younger grownup + getting older). Zenodo https://zenodo.org/doi/10.5281/zenodo.6770119 (2022).
