Skip to main content

Advertisement

Log in

Investigating the contribution of white matter hyperintensities and cortical thickness to empathy in neurodegenerative and cerebrovascular diseases

  • Original Article
  • Published:
GeroScience Aims and scope Submit manuscript

Abstract

Change in empathy is an increasingly recognised symptom of neurodegenerative diseases and contributes to caregiver burden and patient distress. Empathy impairment has been associated with brain atrophy but its relationship to white matter hyperintensities (WMH) is unknown. We aimed to investigate the relationships amongst WMH, brain atrophy, and empathy deficits in neurodegenerative and cerebrovascular diseases. Five hundred thirteen participants with Alzheimer’s disease/mild cognitive impairment, amyotrophic lateral sclerosis, frontotemporal dementia (FTD), Parkinson’s disease, or cerebrovascular disease (CVD) were included. Empathy was assessed using the Interpersonal Reactivity Index. WMH were measured using a semi-automatic segmentation and FreeSurfer was used to measure cortical thickness. A heterogeneous pattern of cortical thinning was found between groups, with FTD showing thinning in frontotemporal regions and CVD in left superior parietal, left insula, and left postcentral. Results from both univariate and multivariate analyses revealed that several variables were associated with empathy, particularly cortical thickness in the fronto-insulo-temporal and cingulate regions, sex (female), global cognition, and right parietal and occipital WMH. Our results suggest that cortical atrophy and WMH may be associated with empathy deficits in neurodegenerative and cerebrovascular diseases. Future work should consider investigating the longitudinal effects of WMH and atrophy on empathy deficits in neurodegenerative and cerebrovascular diseases.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

The datasets presented in this article are not readily available because the ONDRI data will be made publicly available through an application process. For more information on the ONDRI project, please visit http://ondri.ca/. Requests to access the datasets should be directed to http://ondri.ca/.

Abbreviations

AD:

Alzheimer’s disease

ALS:

Amyotrophic lateral sclerosis

bvFTD:

Behavioural variant frontotemporal dementia

CVD:

Cerebrovascular disease

CBS:

Corticobasal syndrome

CT:

Computed tomography

dWMH:

Deep white matter hyperintensities

dx:

Diagnostic

EC:

Emotional concern

FTD:

Frontotemporal dementia

IRI:

Interpersonal Reactivity Index

MCI:

Mild cognitive impairment

MRI:

Magnetic resonance imaging

MoCA:

Montreal Cognitive Assessment

MSE:

Mean square error

nfvPPA:

Non-fluent primary progressive aphasia

ONDRI:

Ontario Neurodegenerative Disease Research Initiative

OFC:

Orbitofrontal cortex

PeD:

Personal distress

PLSc:

Partial least square correlation

PT:

Perspective taking

PD:

Parkinson’s disease

PSP:

Progressive supranuclear palsy

pWMH:

Periventricular white matter hyperintensities

svPPA:

Semantic variant primary progressive aphasia

ST-TIV:

Supratentorial total intracranial volume

SVD:

Small vessel disease

WMH:

White matter hyperintensities

References

  1. Davis MH. Measuring individual differences in empathy: evidence for a multidimensional approach. J Pers Soc Psychol. 1983;44:113–26.

    Article  Google Scholar 

  2. Baron-Cohen S, Wheelwright S. The empathy quotient: an investigation of adults with Asperger syndrome or high functioning autism, and normal sex differences. J Autism Dev Disord. 2004;34:163–75.

    Article  PubMed  Google Scholar 

  3. Christidi F, Migliaccio R, Santamaría-García H, Santangelo G, Trojsi F. Social cognition dysfunctions in neurodegenerative diseases: neuroanatomical correlates and clinical implications. Behav Neurol. 2018;2018:1–18.

    Article  Google Scholar 

  4. Pick E, Kleinbub JR, Mannarini S, Palmieri A. Empathy in neurodegenerative diseases: a systematic review. Neuropsychiatr Dis Treat. 2019;15:3287–304.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Multani N, Taghdiri F, Anor CJ, Varriano B, Misquitta K, Tang-Wai DF, Keren R, Fox S, Lang AE, Vijverman AC, Marras C, Tartaglia MC. Association between social cognition changes and resting state functional connectivity in frontotemporal dementia, Alzheimer’s disease, Parkinson’s disease, and healthy controls. Front Neurosci. 2019;13:1–14.

  6. Eslinger PJ, Moore P, Anderson C, Grossman M. Social cognition, executive functioning, and neuroimaging correlates of empathic deficits in frontotemporal dementia. J Neuropsychiatry Clin Neurosci. 2011;23:74–82.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Rankin KP, Gorno-Tempini ML, Allison SC, Stanley CM, Glenn S, Weiner MW, Miller BL. Structural anatomy of empathy in neurodegenerative disease. Brain. 2006;129:2945–56.

    Article  PubMed  Google Scholar 

  8. Baez S, Manes F, Huepe D, Torralva T, Fiorentino N, Richter F, Huepe-Artigas D, Ferrari J, Montaes P, Reyes P, Matallana D, Vigliecca NS, Decety J, Ibanez A. Primary empathy deficits in frontotemporal dementia. Front Aging Neurosci. 2018;6:1–11.

  9. Cosentino S, Zahodne LB, Brandt J, Blacker D, Albert M, Dubois B, Stern Y. Social cognition in Alzheimer’s disease: a separate construct contributing to dependence. Alzheimer’s Dement. 2014;10:818–26.

    Article  Google Scholar 

  10. Gray HM, Tickle-Degnen L. A meta-analysis of performance on emotion recognition tasks in Parkinson’s disease. Neuropsychology. 2010;24:176–91.

    Article  PubMed  Google Scholar 

  11. Kleinbub JR, Palmieri A, Broggio A, Pagnini F, Benelli E, Sambin M, Soraru G. Hypnosis-based psychodynamic treatment in ALS: a longitudinal study on patients and their caregivers. Front Psychol. 2015; 6:1–14.

  12. Bodden ME, Mollenhauer B, Trenkwalder C, Cabanel N, Eggert KM, Unger MM, Oertel WH, Kessler J, Dodel R, Kalbe E. Affective and cognitive theory of mind in patients with Parkinson’s disease. Parkinsonism Relat Disord. 2010;16:466–70.

    Article  PubMed  Google Scholar 

  13. Dermody N, Wong S, Ahmed R, Piguet O, Hodges JR, Irish M. Uncovering the neural bases of cognitive and affective empathy deficits in Alzheimer’s disease and the behavioral-variant of frontotemporal dementia. J Alzheimer’s Dis. 2016;53:801–16.

    Article  Google Scholar 

  14. Ariatti A, Benuzzi F, Nichelli P. Recognition of emotions from visual and prosodic cues in Parkinson’s disease. Neurol Sci. 2008;29:219–27.

    Article  PubMed  Google Scholar 

  15. Assogna F, Pontieri FE, Cravello L, Peppe A, Pierantozzi M, Stefani A, Stanzione P, Pellicano C, Caltagirone C, Spalletta G. Intensity-dependent facial emotion recognition and cognitive functions in Parkinson’s disease. J Int Neuropsychol Soc. 2010;16:867–76.

    Article  PubMed  Google Scholar 

  16. Kan Y, Kawamura M, Hasegawa Y, Mochizuki S, Nakamura K. Recognition of emotion from facial, prosodic and written verbal stimuli in Parkinson’s disease. Cortex. 2002;38:623–30.

    Article  PubMed  Google Scholar 

  17. Martinez M, Multani N, Anor CJ, Misquitta K, TangWai DF, Keren R, Fox S, Lang AE, Marras C, Tartaglia MC. Emotion detection deficits and decreased empathy in patients with Alzheimer’s disease and Parkinson’s disease affect caregiver mood and burden. Front Aging Neurosci. 2018;10:1–9.

  18. Skuse DH, Gallagher L. Dopaminergic-neuropeptide interactions in the social brain. Trends Cogn Sci. 2009;13:27–35.

    Article  CAS  PubMed  Google Scholar 

  19. Ibarretxe-Bilbao N, Junque C, Tolosa E, Marti M-J, Valldeoriola F, Bargallo N, Zarei M. Neuroanatomical correlates of impaired decision-making and facial emotion recognition in early Parkinson’s disease. Eur J Neurosci. 2009;30:1162–71.

    Article  PubMed  Google Scholar 

  20. Baggio HC, Segura B, Ibarretxe-Bilbao N, Valldeoriola F, Marti MJ, Compta Y, Tolosa E, Junqué C. Structural correlates of facial emotion recognition deficits in Parkinson’s disease patients. Neuropsychologia. 2012;50:2121–8.

    Article  CAS  PubMed  Google Scholar 

  21. Cerami C, Dodich A, Canessa N, Crespi C, Iannaccone S, Corbo M, Lunetta C, Consonni M, Scola E, Falini A, Cappa SF. Emotional empathy in amyotrophic lateral sclerosis: a behavioural and voxel-based morphometry study. Amyotroph Lateral Scler Front Degener. 2014;15:21–9.

    Article  Google Scholar 

  22. Leigh R, Oishi K, Hsu J, Lindquist M, Gottesman RF, Jarso S, Crainiceanu C, Mori S, Hillis AE. Acute lesions that impair affective empathy. Brain. 2013;136:2539–49.

    Article  PubMed  PubMed Central  Google Scholar 

  23. De Groot JC, De Leeuw F-E, Oudkerk M, Van Gijn J, Hofman A, Jolles J, Breteler MMB. Periventricular cerebral white matter lesions predict rate of cognitive decline. Ann Neurol. 2002;52:335–41.

    Article  PubMed  Google Scholar 

  24. Garde E, Mortensen EL, Krabbe K, Rostrup E, Larsson HB. Relation between age-related decline in intelligence and cerebral white-matter hyperintensities in healthy octogenarians: a longitudinal study. Lancet. 2000;356:628–34.

    Article  CAS  PubMed  Google Scholar 

  25. Wardlaw JM, Valdés Hernández MC, Muñoz‐Maniega S. What are white matter hyperintensities made of? J Am Heart Assoc. 2015; 4:1–19.

  26. Barber R, Scheltens P, Gholkar A, Ballard C, McKeith I, Ince P, Perry R, O’Brien J. White matter lesions on magnetic resonance imaging in dementia with Lewy bodies, Alzheimer’s disease, vascular dementia, and normal aging. J Neurol Neurosurg Psychiatry. 1999;67:66–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Park KH, Lee J-Y, Na DL, Kim SY, Cheong H-K, Moon SY, Shim YS, Park KW, Ku BD, Choi SH, Joo H, Lee JS, Go SM, Kim SH, Kim SangYun, Cha KR, Lee J, Seo SW. Different associations of periventricular and deep white matter lesions with cognition, neuropsychiatric symptoms, and daily activities in dementia. J Geriatr Psychiatry Neurol. 2011;24:84–90.

    Article  PubMed  Google Scholar 

  28. Starkstein SE, Mizrahi R, Capizzano AA, Acion L, Brockman S, Power BD. Neuroimaging correlates of apathy and depression in Alzheimer’s disease. J Neuropsychiatry Clin Neurosci. 2009;21:259–65.

    Article  PubMed  Google Scholar 

  29. Soennesyn H, Oppedal K, Greve OJ, Fritze F, Auestad BH, Nore SP, Beyer MK, Aarsland D. White matter hyperintensities and the course of depressive symptoms in elderly people with mild dementia. Dement Geriatr Cogn Dis Extra. 2012;2:97–111.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Anor CJ, O’Connor S, Saund A, Tang-Wai DF, Keren R, Tartaglia MC. Neuropsychiatric symptoms in Alzheimer disease, vascular dementia, and mixed dementia. Neurodegener Dis. 2017;17:127–34.

    Article  PubMed  Google Scholar 

  31. Kim HJ, Kang SJ, Kim C, Kim GH, Jeon S, Lee JM, Oh SJ, Kim JS, Choe YS, Lee KH, Noh Y, Cho H, Yoon CW, Chin J, Cummings JL, Lee JH, Na DL, Seo SW. The effects of small vessel disease and amyloid burden on neuropsychiatric symptoms: a study among patients with subcortical vascular cognitive impairments. Neurobiol Aging. 2013;34:1913–20.

    Article  CAS  PubMed  Google Scholar 

  32. Desmarais P, Gao AF, Lanctôt K, Rogaeva E, Ramirez J, Herrmann N, Stuss DT, Black SE, Keith J, Masellis M. White matter hyperintensities in autopsy-confirmed frontotemporal lobar degeneration and Alzheimer’s disease. Alzheimers Res Ther. 2021;13:129.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Farhan SMK, Bartha R, Black SE, Corbett D, Finger E, Freedman M, Greenberg B, Grimes DA, Hegele RA, Hudson C, Kleinstiver PW, Lang AE, Masellis M, McIlroy WE, McLaughlin PM, Montero-Odasso M, Munoz DG, Munoz DP, Strother S, Swartz RH, Symons S, Tartaglia MC, Zinman L, Strong MJ. The Ontario Neurodegenerative Disease Research Initiative (ONDRI). Can J Neurol Sci. 2017;44:196–202.

    Article  PubMed  Google Scholar 

  34. Sunderland KM, Beaton D, Arnott SR, Kleinstiver P, Kwan D, Lawrence-Dewar JM, Ramirez J, Tan B, Bartha R, Black SE, Borrie M, Brien D, Casaubon LK, Coe B, Cornish B, Dilliott AA, Dowlatshahi D, Finger E, Fischer C, Frank A, Fraser J, Freedman M, Greenberg B, Grimes DA, Hassan A, Hatch W, Hegele RA, Hudson C, Jog M, Kumar S, Lang A, Levine B, Lou W, Mandzia J, Marras C, McIlroy W, Montero-Odasso M, Munoz DG, Munoz DP, Orange JB, Park DS, Pasternak SH, PierucciniFaria F, Rajji TK, Roberts AC, Robinson JF, Rogaeva E, Sahlas DJ, Saposnik G, Scott CJM, Seitz D, Shoesmith C, Steeves TDL, Strong MJ, Strother SC, Swartz RH, Symons S, Tang-Wai DF, Tartaglia MC, Troyer AK, Turnbull J, Zinman L, McLaughlin PM, Masellis M, Binns MA. The Ontario Neurodegenerative Disease Research Initiative. medRxiv. 2020: 1–41.

  35. Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, Gamst A, Holtzman DM, Jagust WJ, Petersen RC, Snyder PJ, Carrillo MC, Thies B, Phelps CH. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7:270–9.

    Article  PubMed  PubMed Central  Google Scholar 

  36. McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7:263–9.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Brooks BR. El Escorial World Federation of Neurology criteria for the diagnosis of amyotrophic lateral sclerosis. Subcommittee on Motor Neuron Diseases/Amyotrophic Lateral Sclerosis of the World Federation of Neurology Research Group on Neuromuscular Diseases and th. J Neurol Sci. 1994;124(Suppl):96–107.

    Article  PubMed  Google Scholar 

  38. Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, van Swieten JC, Seelaar H, Dopper EG, Onyike CU, Hillis AE, Josephs KA, Boeve BF, Kertesz A, Seeley WW, Rankin KP, Johnson JK, Gorno-Tempini ML, Rosen H, Prioleau-Latham CE, Lee A, Kipps CM, Lillo P, Piguet O, Rohrer JD, Rossor MN, Warren JD, Fox NC, Galasko D, Salmon DP, Black SE, Mesulam M, Weintraub S, Dickerson BC, Diehl-Schmid J, Pasquier F, Deramecourt V, Lebert F, Pijnenburg Y, Chow TW, Manes F, Grafman J, Cappa SF, Freedman M, Grossman M, Miller BL. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain. 2011;134:2456–77.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, Ogar JM, Rohrer JD, Black S, Boeve BF, Manes F, Dronkers NF, Vandenberghe R, Rascovsky K, Patterson K, Miller BL, Knopman DS, Hodges JR, Mesulam MM, Grossman M. Classification of primary progressive aphasia and its variants. Neurology. 2011;76:1006–14.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Hauw J-J, Daniel SE, Dickson D, Horoupian DS, Jellinger K, Lantos PL, McKee A, Tabaton M, Litvan I. Preliminary NINDS neuropathologic criteria for Steele-Richardson-Olszewski syndrome (progressive supranuclear palsy). Neurology. 1994;44:2015–2015.

    Article  CAS  PubMed  Google Scholar 

  41. Armstrong MJ, Litvan I, Lang AE, Bak TH, Bhatia KP, Borroni B, Boxer AL, Dickson DW, Grossman M, Hallett M, Josephs KA, Kertesz A, Lee SE, Miller BL, Reich SG, Riley DE, Tolosa E, Tröster AI, Vidailhet M, Weiner WJ. Criteria for the diagnosis of corticobasal degeneration. Neurology. 2013;80:496–503.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Gibb WR, Lees AJ. The relevance of the Lewy body to the pathogenesis of idiopathic Parkinson’s disease. J Neurol Neurosurg Psychiatry. 1988;51:745–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Hachinski V, Iadecola C, Petersen RC, Breteler MM, Nyenhuis DL, Black SE, Powers WJ, Decarli C, Merino JG, Kalaria RN, Vinters HV, Holtzman DM, Rosenberg GA, Wallin A, Dichgans M, Marler JR, Leblanc GG. National Institute of Neurological Disorders and Stroke-Canadian Stroke Network vascular cognitive impairment harmonization standards. Stroke. 2006;37:2220–41.

    Article  PubMed  Google Scholar 

  44. Rankin KP, Kramer JH, Miller BL. Patterns of cognitive and emotional empathy in frontotemporal lobar degeneration. Cogn Behav Neurol. 2005;18:28–36.

    Article  PubMed  Google Scholar 

  45. Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, Cummings JL, Chertkow H. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53:695–9.

    Article  PubMed  Google Scholar 

  46. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9:179–86.

    Article  CAS  PubMed  Google Scholar 

  47. Scott CJM, Arnott SR, Chemparathy A, Dong F, Solovey I, Gee T, Schmah T, Lobaugh N, Nanayakkara N, Liang S, Zamyadi M, Ozzoude M, Holmes MF, Szilagyi GM, Ramirez J, Symons S, Black SE, Bartha R, Strother S. An overview of the quality assurance and quality control of magnetic resonance imaging data for the Ontario Neurodegenerative Disease Research Initiative (ONDRI): pipeline development and neuroinformatics. bioRxiv. 2020: 1–16.

  48. Ramirez J, Holmes MF, Scott CJM, Ozzoude M, Adamo S, Szilagyi GM, Gao F, Arnott SR, Dewar JML, Beaton D, Strother SC, Douglas P, Masellis M, Swartz RH, Bartha R, Symons S, Black SE, Investigators O. Ontario Neurodegenerative Disease Research Initiative (ONDRI): structural MRI methods & outcome measures. Front Neurol. 2020; 17: 1–11.

  49. Duchesne S, Chouinard I, Potvin O, Fonov VS, Khademi A, Bartha R, Bellec P, Collins DL, Descoteaux M, Hoge R, McCreary CR, Ramirez J, Scott CJM, Smith EE, Strother SC, Black SE, CIMA-Q group and the CCNA group,. The Canadian dementia imaging protocol: harmonizing national cohorts. J Magn Reson Imaging. 2019;49:456–65.

    Article  PubMed  Google Scholar 

  50. Dade LA, Gao FQ, Kovacevic N, Roy P, Rockel C, O’Toole CM, Lobaugh NJ, Feinstein A, Levine B, Black SE. Semiautomatic brain region extraction: a method of parcellating brain regions from structural magnetic resonance images. Neuroimage. 2004;22:1492–502.

    Article  CAS  PubMed  Google Scholar 

  51. Gibson E, Gao F, Black SE, Lobaugh NJ. Automatic segmentation of white matter hyperintensities in the elderly using FLAIR images at 3T. J Magn Reson. 2010;31:1311–22.

    Google Scholar 

  52. Kovacevic N, Lobaugh NJ, Bronskill MJ, Levine B, Feinstein A, Black SE. A robust method for extraction and automatic segmentation of brain images. Neuroimage. 2002;17:1087–100.

    Article  CAS  PubMed  Google Scholar 

  53. Ramirez J, McNeely AA, Scott CJM, Masellis M, Black SE. White matter hyperintensity burden in elderly cohort studies. The Sunnybrook Dementia Study. Alzheimer Disease Neuroimaging Initiative, and Three-City Study. Alzheimers Dement. 2015;12:203–10.

  54. Ramirez J, McNeely AA, Scott CJ, Stuss DT, Black SE. Subcortical hyperintensity volumetrics in Alzheimer’s disease and normal elderly in the Sunnybrook Dementia Study: correlations with atrophy, executive function, mental processing speed, and verbal memory. Alzheimers Res Ther. 2014;6:49.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Ramirez J, McNeely A, Scott CJM, Stuss DT, Black SE. Strategic regional subcortical hyperintensity volumetrics in Alzheimer’s disease and normal elderly: correlations with executive function, mental processing speed, and verbal memory. Alzheimers Res Ther. 2014;49:1–12.

  56. Ramirez J, Gibson E, Quddus A, Lobaugh NJ, Feinstein A, Levine B, Scott CJM, Levy-Cooperman N, Gao FQ, Black SE. Lesion explorer: a comprehensive segmentation and parcellation package to obtain regional volumetrics for subcortical hyperintensities and intracranial tissue. Neuroimage. 2011;54:963–73.

    Article  CAS  PubMed  Google Scholar 

  57. Sunderland KM, Beaton D, Fraser J, Kwan D, McLaughlin PM, Montero-Odasso M, Peltsch AJ, Pieruccini-Faria F, Sahlas DJ, Swartz RH, Strother SC, Binns MA, Binns MA. The utility of multivariate outlier detection techniques for data quality evaluation in large studies: an application within the ONDRI project. BMC Med Res Methodol. 2019;19:102.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Fischl B. FreeSurfer Neuroimage. 2012;62:774–81.

    Article  PubMed  Google Scholar 

  59. Fischl B, Liu A, Dale AM. Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex. IEEE Trans Med Imaging. 2001;20:70–80.

    Article  CAS  PubMed  Google Scholar 

  60. Ozzoude M, Ramirez J, Raamana PR, Holmes MF, Walker K, Scott CJM, Gao F, Goubran M, Kwan D, Tartaglia MC, Beaton D, Saposnik G, Hassan A, LawrenceDewar J, Dowlatshahi D, Strother SC, Symons S, Bartha R, Swartz RH, Black SE. Cortical thickness estimation in individuals with cerebral small vessel disease, focal atrophy, and chronic stroke lesions. Front Neurosci. 2020;14:1–12.

  61. Wickham H. ggplot2: Elegant Graphics for Data Analysis. 2009;35:1–3.

  62. Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, Buckner RL, Dale AM, Maguire RP, Hyman BT, Albert MS, Killiany RJ. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 2006;31:968–80.

    Article  PubMed  Google Scholar 

  63. Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc Ser B Statistical Methodol. 2005;67:301–20.

    Article  Google Scholar 

  64. Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw. 2010;33:1–22.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Krishnan A, Williams LJ, McIntosh AR, Abdi H. Partial least squares (PLS) methods for neuroimaging: a tutorial and review. Neuroimage. 2011;56:455–75.

    Article  PubMed  Google Scholar 

  66. McIntosh AR, Bookstein FL, Haxby JV, Grady CL. Spatial pattern analysis of functional brain images using partial least squares. Neuroimage. 1996;3:143–57.

    Article  CAS  PubMed  Google Scholar 

  67. Beaton D, Chin Fatt CR, Abdi H. An ExPosition of multivariate analysis with the singular value decomposition in R. Comput Stat Data Anal. 2014;72:176–89.

    Article  Google Scholar 

  68. De Vos M, Prince J, Buchanan T, FitzGerald JJ, Antoniades CA. Discriminating progressive supranuclear palsy from Parkinson’s disease using wearable technology and machine learning. Gait Posture. 2020;77:257–63.

    Article  PubMed  Google Scholar 

  69. Bouts MJRJ, Möller C, Hafkemeijer A, van Swieten JC, Dopper E, van der Flier WM, Vrenken H, Wink AM, Pijnenburg YAL, Scheltens P, Barkhof F, Schouten TM, de Vos F, Feis RA, van der Grond J, de Rooij M, Rombouts SARB. Single subject classification of Alzheimer’s disease and behavioral variant frontotemporal dementia using anatomical, diffusion tensor, and resting-state functional magnetic resonance imaging. J Alzheimer’s Dis. 2018;62:1827–39.

    Article  Google Scholar 

  70. Tosun D, Schuff N, Rabinovici GD, Ayakta N, Miller BL, Jagust W, Kramer J, Weiner MM, Rosen HJ. Diagnostic utility of ASL-MRI and FDG-PET in the behavioral variant of FTD and AD. Ann Clin Transl Neurol. 2016;3:740–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Teipel SJ, Grothe MJ, Metzger CD, Grimmer T, Sorg C, Ewers M, Franzmeier N, Meisenzahl E, Klöppel S, Borchardt V, Walter M, Dyrba M. Robust detection of impaired resting state functional connectivity networks in Alzheimer’s disease using elastic net regularized regression. Front Aging Neurosci. 2017;8:1–9.

  72. James G, Witten D, Hastie T, Tibshirani R. An introduction to statistical learning. New York, New York, NY: Springer; 2013.

    Book  Google Scholar 

  73. Berry KJ, Johnston JE, Mielke PW. Permutation methods. Wiley Interdiscip Rev Comput Stat. 2011;3:527–42.

    Article  Google Scholar 

  74. Peres-Neto PR, Jackson DA, Somers KM. How many principal components? Stopping rules for determining the number of non-trivial axes revisited. Comput Stat Data Anal. 2005;49:974–97.

    Article  Google Scholar 

  75. Efron B, Tibshirani R. Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy. Stat Sci. 1986;1:54–75.

  76. Hesterberg T. Bootstrap. Wiley Interdiscip Rev. Comput Stat. 2011;3:497–526.

    Article  Google Scholar 

  77. Piguet O, Hornberger M, Mioshi E, Hodges JR. Behavioural-variant frontotemporal dementia: diagnosis, clinical staging, and management. Lancet Neurol. 2011;10:162–72.

    Article  PubMed  Google Scholar 

  78. Bartochowski Z, Gatla S, Khoury R, Al-Dahhak R, Grossberg GT. Empathy changes in neurocognitive disorders: a review. Ann Clin Psychiatry. 2018;30:220–32.

    PubMed  Google Scholar 

  79. Lough S, Kipps CM, Treise C, Watson P, Blair JR, Hodges JR. Social reasoning, emotion and empathy in frontotemporal dementia. Neuropsychologia. 2006;44:950–8.

    Article  PubMed  Google Scholar 

  80. Decety J, Jackson PL. The functional architecture of human empathy. Behav Cogn Neurosci Rev. 2004;3:71–100.

    Article  PubMed  Google Scholar 

  81. Narme P, Mouras H, Roussel M, Devendeville A, Godefroy O. Assessment of socioemotional processes facilitates the distinction between frontotemporal lobar degeneration and Alzheimer’s disease. J Clin Exp Neuropsychol. 2013;35:728–44.

    Article  PubMed  Google Scholar 

  82. Sturm VE, Yokoyama JS, Seeley WW, Kramer JH, Miller BL, Rankin KP. Heightened emotional contagion in mild cognitive impairment and Alzheimer’s disease is associated with temporal lobe degeneration. Proc Natl Acad Sci. 2013;110:9944–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Fernandez-Duque D, Hodges SD, Baird JA, Black SE. Empathy in frontotemporal dementia and Alzheimer’s disease. J Clin Exp Neuropsychol. 2009;32:1–12.

  84. Narme P, Mouras H, Roussel M, Duru C, Krystkowiak P, Godefroy O. Emotional and cognitive social processes are impaired in Parkinson’s disease and are related to behavioral disorders. Neuropsychology. 2013;27:182–92.

    Article  PubMed  Google Scholar 

  85. van der Hulst E-J, Bak TH, Abrahams S. Impaired affective and cognitive theory of mind and behavioural change in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry. 2015;86:1208–15.

    Article  PubMed  Google Scholar 

  86. Schmidt N, Paschen L, Deuschl G, Witt K. Reduced empathy scores in patients with Parkinson’s disease: a non-motor symptom associated with advanced disease stages. J Parkinsons Dis. 2017;7:713–8.

    Article  PubMed  Google Scholar 

  87. Coundouris SP, Adams AG, Henry JD. Empathy and theory of mind in Parkinson’s disease: a meta-analysis. Neurosci Biobehav Rev. 2020;109:92–102.

    Article  PubMed  Google Scholar 

  88. Shamay-Tsoory SG, Tomer R, Goldsher D, Berger BD, Aharon-Peretz J. Impairment in cognitive and affective empathy in patients with brain lesions: anatomical and cognitive correlates. J Clin Exp Neuropsychol. 2004;26:1113–27.

    Article  CAS  PubMed  Google Scholar 

  89. Shamay-Tsoory SG, Aharon-Peretz J. Dissociable prefrontal networks for cognitive and affective theory of mind: a lesion study. Neuropsychologia. 2007;45:3054–67.

    Article  PubMed  Google Scholar 

  90. Di Tella M, Miti F, Ardito RB, Adenzato M. Social cognition and sex: are men and women really different? Pers Individ Dif. 2020;162:110045.

    Article  Google Scholar 

  91. Martínez-Velázquez ES, Ahuatzin González AL, Chamorro Y, Sequeira H. The influence of empathy trait and gender on empathic responses. A study with dynamic emotional stimulus and eye movement recordings. Front Psychol. 2020;11:1–11.

  92. Eisenberg N, Lennon R. Sex differences in empathy and related capacities. Psychol Bull. 1983;94:100–31.

    Article  Google Scholar 

  93. Baez S, Flichtentrei D, Prats M, Mastandueno R, García AM, Cetkovich M, Ibáñez A.Men, women…who cares? A population-based study on sex differences and gender roles in empathy and moral cognition. PLoS One. 2017;12, e0179336.

  94. Hillis AE. Inability to empathize: brain lesions that disrupt sharing and understanding another’s emotions. Brain. 2014;137:981–97.

    Article  PubMed  Google Scholar 

  95. Kim EJ, Son J-W, Park SK, Chung S, Ghim H-R, Lee S, Lee S-I, Shin C-J, Kim S, Ju G, Park H, Lee J. Cognitive and emotional empathy in young adolescents: an fMRI study. Soa--ch’ongsonyon chongsin uihak = J child Adolesc psychiatry. 2020;31:121–30.

    Google Scholar 

  96. Naor N, Rohr C, Schaare LH, Limbachia C, Shamay-Tsoory S, Okon-Singer H. The neural networks underlying reappraisal of empathy for pain. Soc Cogn Affect Neurosci. 2020;15:733–44.

    Article  PubMed  PubMed Central  Google Scholar 

  97. Seeley WW, Allman JM, Carlin DA, Crawford RK, Macedo MN, Greicius MD, Dearmond SJ, Miller BL. Divergent social functioning in behavioral variant frontotemporal dementia and Alzheimer disease: Reciprocal networks and neuronal evolution. Alzheimer Dis Assoc Disord. 2007;21:S50–7.

  98. Couto B, Sedeño L, Sposato LA, Sigman M, Riccio PM, Salles A, Lopez V, Schroeder J, Manes F, Ibanez A. Insular networks for emotional processing and social cognition: comparison of two case reports with either cortical or subcortical involvement. Cortex. 2013;49:1420–34.

    Article  PubMed  Google Scholar 

  99. Gu X, Gao Z, Wang X, Liu X, Knight RT, Hof PR, Fan J. Anterior insular cortex is necessary for empathetic pain perception. Brain. 2012;135:2726–35.

    Article  PubMed  PubMed Central  Google Scholar 

  100. Yeh Z-T, Tsai C-F. Impairment on theory of mind and empathy in patients with stroke. Psychiatry Clin Neurosci. 2014;68:612–20.

    Article  PubMed  Google Scholar 

  101. Zhong Y, Utriainen D, Wang Y, Kang Y, Haacke EM. Automated white matter hyperintensity detection in multiple sclerosis using 3D T2 FLAIR. Int J Biomed Imaging. 2014;2014:1–7.

    Article  Google Scholar 

  102. Zhou T, Ahmad TK, Gozda K, Truong J, Kong J, Namaka M. Implications of white matter damage in amyotrophic lateral sclerosis. Mol Med Rep. 2017;16:4379–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Matsusue E, Sugihara S, Fujii S, Kinoshita T, Nakano T, Ohama E, Ogawa T. Cerebral cortical and white matter lesions in amyotrophic lateral sclerosis with dementia: correlation with MR and pathologic examinations. Am J Neuroradiol. 2007;28:1505–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Mascalchi M. Neurodegenerative diseases with associated white matter pathology. MR imaging in white matter diseases of the brain and spinal cord. 2006;27:377–388.

  105. Dadar M, Manera AL, Ducharme S, Louis CD. White matter hyperintensities, grey matter atrophy, and cognitive decline in Alzheimer's disease and frontotemporal dementia. Neurobiology of aging. 2022;111:54–63.

  106. Woollacott IOC, Bocchetta M, Sudre CH, Ridha BH, Strand C, Courtney R, Ourselin S, Cardoso MJ, Warren JD, Rossor MN, Revesz T, Fox NC, Holton JL, Lashley T, Rohrer JD. Pathological correlates of white matter hyperintensities in a case of progranulin mutation associated frontotemporal dementia. Neurocase. 2018;24:166–74.

    Article  PubMed  PubMed Central  Google Scholar 

  107. McAleese KE, Walker L, Graham S, Moya ELJ, Johnson M, Erskine D, Colloby SJ, Dey M, Martin-Ruiz C, Taylor J-P, Thomas AJ, McKeith IG, De Carli C, Attems J. Parietal white matter lesions in Alzheimer’s disease are associated with cortical neurodegenerative pathology, but not with small vessel disease. Acta Neuropathol. 2017;134:459–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Kynast J, Lampe L, Luck T, Frisch S, Arelin K, Hoffmann K-T, Loeffler M, Riedel-Heller SG, Villringer A, Schroeter ML. White matter hyperintensities associated with small vessel disease impair social cognition beside attention and memory. J Cereb Blood Flow Metab. 2018;38:996–1009.

    Article  PubMed  Google Scholar 

  109. Dvash J, Shamay-Tsoory SG. Theory of mind and empathy as multidimensional constructs. Top Lang Disord. 2014;34:282–95.

    Article  Google Scholar 

  110. Oishi K, Faria AV, Hsu J, Tippett D, Mori S, Hillis AE. Critical role of the right uncinate fasciculus in emotional empathy. Ann Neurol. 2015;77:68–74.

    Article  PubMed  Google Scholar 

  111. Parkinson C, Wheatley T. Relating anatomical and social connectivity: white matter microstructure predicts emotional empathy. Cereb Cortex. 2014;24:614–25.

    Article  PubMed  Google Scholar 

  112. Multani N, Galantucci S, Wilson SM, Shany-Ur T, Poorzand P, Growdon ME, Jang JY, Kramer JH, Miller BL, Rankin KP, Gorno-Tempini ML, Tartaglia MC. Emotion detection deficits and changes in personality traits linked to loss of white matter integrity in primary progressive aphasia. NeuroImage Clin. 2017;16:447–54.

    Article  PubMed  PubMed Central  Google Scholar 

  113. Crespi C, Cerami C, Dodich A, Canessa N, Iannaccone S, Corbo M, Lunetta C, Falini A, Cappa SF. Microstructural correlates of emotional attribution impairment in non-demented patients with amyotrophic lateral sclerosis. PLoS One. 2016;11:e0161034.

    Article  PubMed  PubMed Central  Google Scholar 

  114. Comes-Fayos J, Romero-Martinez A, Moya-Albiol L. Role of major long fiber tracts association in empathy. Rev Neurol. 2018;67:263–72.

    CAS  PubMed  Google Scholar 

  115. Crespi C, Cerami C, Dodich A, Canessa N, Arpone M, Iannaccone S, Corbo M, Lunetta C, Scola E, Falini A, Cappa SF. Microstructural white matter correlates of emotion recognition impairment in amyotrophic lateral sclerosis. Cortex. 2014;53:1–8.

    Article  PubMed  Google Scholar 

  116. Shamay-Tsoory SG, Lester H, Chisin R, Israel O, Bar-Shalom R, Peretz A, Tomer R, Tsitrinbaum Z, Aharon-Peretz J. The neural correlates of understanding the other’s distress: a positron emission tomography investigation of accurate empathy. Neuroimage. 2005;27:468–72.

    Article  CAS  PubMed  Google Scholar 

  117. Kapasi A, DeCarli C, Schneider JA. Impact of multiple pathologies on the threshold for clinically overt dementia. Acta Neuropathol. 2017;134:171–86.

    Article  PubMed  PubMed Central  Google Scholar 

  118. Hua AY, Sible IJ, Perry DC, Rankin KP, Kramer JH, Miller BL, Rosen HJ, Sturm VE. Enhanced positive emotional reactivity undermines empathy in behavioral variant frontotemporal dementia. Front Neurol. 2018;9:1–14.

  119. Sollberger M, Stanley CM, Wilson SM, Gyurak A, Beckman V, Growdon M, Jang J, Weiner MW, Miller BL, Rankin KP. Neural basis of interpersonal traits in neurodegenerative diseases. Neuropsychologia. 2009;47:2812–27.

    Article  PubMed  PubMed Central  Google Scholar 

  120. Miller LA, Mioshi E, Savage S, Lah S, Hodges JR, Piguet O. Identifying cognitive and demographic variables that contribute to carer burden in dementia. Dement Geriatr Cogn Disord. 2013;36:43–9.

    Article  PubMed  Google Scholar 

  121. Brown CL, Lwi SJ, Goodkind MS, Rankin KP, Merrilees J, Miller BL, Levenson RW. Empathic accuracy deficits in patients with neurodegenerative disease: association with caregiver depression. Am J Geriatr Psychiatry. 2018;26:484–93.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to thank the ONDRI participants for the time, consent, and participation in our study. The manuscript has been submitted to bioRxiv preprint.

CONSORTIUM NAME: ONDRI Investigators; Members: Michael Strong1, Peter Kleinstiver2, Jane Lawrence-Dewar3, Natalie Rashkovan4, Susan Bronskil5,6,7, Julia Fraser8, Bill McIlroy8, Ben Cornish8, Karen Van Ooteghem8, Frederico Faria9, Yanina Sarquis-Adamson9, Alanna Black9, Barry Greenberg10, Wendy Hatch11, Chris Hudson11,12, Elena Leontieva12,13, Ed Margolin11, Efrem Mandelcorn11, Faryan Tayyari12, Sherif Defrawy11, Don Brien14, Ying Chen14, Brian Coe14, Doug Munoz14, Alisia Southwell4, Dennis Bulman15,16,17, Allison Ann Dilliott18,19, Mahdi Ghani20, Rob Hegele21, John Robinson1, Ekaterina Rogaeva20, Sali Farhan22, Seyyed Mohammad Hassan Haddad1, Nuwan Nanayakkara1, Courtney Berezuk23, Sabrina Adamo23,24, Malcolm Binns25,26, Wendy Lou26, Athena Theyers25, Abiramy Uthirakumaran25, Guangyong (GY) Zou27, Sujeevini Sujanthan28, Mojdeh Zamyadi25, David Munoz29, Roger A. Dixon30, John Woulfe31, Brian Levine25,32, JB Orange33,34, Alicia Peltsch35, Angela Troyer36,37, Marvin Chum38,39.

Affiliations:

1Robarts Research Institute, Western University, London, ON, Canada

2Schulich School of Medicine & Dentistry, Western University, London, ON, Canada

3Thunder Bay Regional Research Institute, ON, Canada

4Sunnybrook Health Sciences Centre, Toronto, ON, Canada.

5Institute of Clinical Evaluative Science, Toronto, ON, Canada

6Institute of Health Policy, Management & Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada

7Sunnybrook Research Institute, Toronto, ON, Canada

8Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada

9Gait and Brain Lab, Western University, London, ON, Canada

10Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada

11Department of Ophthalmology and Vision Sciences, University of Toronto, ON, Canada

12School of Optometry and Vision Science, University of Waterloo, Waterloo, ON, Canada

13Kensington Eye Institute, Toronto, ON, Canada

14Centre for Neuroscience Studies, Queen’s University, Kingston, ON, Canada

15University of Ottawa Brain and Mind Research Institute,, Ottawa, ON, Canada

16Department of Pediatrics, Faculty of Medicine, University of Ottawa, ON, Canada

17Regenerative Medicine, Ottawa Health Research Institute, ON, Canada

18Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada

19Robarts Research Institute, Western University, London, ON, Canada

20Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada

21Department of Medicine and Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada

22Department of Neurology and Neurosurgery, Department of Human Genetics, The Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada

23Department of Psychological Clinical Science, University of Toronto Scarborough, Scarborough, ON, Canada

24Toronto Western Hospital Neuropsychology Research, University Health Network, Toronto, ON, Canada

25Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada

26Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada

27Department of Epidemiology and Biostatistics, Western University, London, ON, Canada

28Department of Ophthalmology and Visual Sciences, Research Institute of the McGill University Health Center, Quebec, Canada

29Department of Laboratory medicine, St Michael's Hospital, Unity Health, Toronto, ON, Canada

30Department of Psychology (Science), Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada

31Ottawa Hospital Research Institute and University of Ottawa, Ottawa, ON, Canada

32Department of Psychology and Medicine (Neurology), University of Toronto, Toronto, ON, Canada

33School of Communication Sciences and Disorders, Faculty of Health Sciences, Western University, London, ON, Canada

34Canadian Centre for Activity and Aging, Western University, London, ON, Canada

35Faculty of Engineering and Applied Science, Queen's University, Kingston, ON, Canada

36Neuropsychology and Cognitive Health Program, Baycrest Health Sciences, Toronto, ON, Canada

37Department of Psychology, University of Toronto, Toronto, ON, Canada

38Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada

39Department of Medicine, McMaster University, Hamilton, ON, Canada

Funding

This research was conducted with the support of the Ontario Brain Institute, an independent non-profit corporation, funded partially by the Ontario government. The opinions, results, and conclusions are those of the authors and no endorsement by the Ontario Brain Institute is intended or should be inferred. Matching funds were provided by participant hospital and research foundations, including the Baycrest Foundation, Bruyere Research Institute, Centre for Addiction and Mental Health Foundation, London Health Sciences Foundation, McMaster University Faculty of Health Sciences, Ottawa Brain and Mind Research Institute, Queen’s University Faculty of Health Sciences, the Thunder Bay Regional Health Sciences Centre, the University of Ottawa Faculty of Medicine, University Health Network, Sunnybrook, and the Windsor/Essex County ALS Association. The Temerty Family Foundation provided the major infrastructure matching funds.

Author information

Authors and Affiliations

Authors

Consortia

Contributions

MO: conceptualisation, data curation, formal analysis, investigation, methodology, project administration, software, visualisation, and writing (draft, review, and editing). BV: conceptualisation, investigation, methodology, project administration, writing (review and editing). DB: data curation, formal analysis, supervision, methodology, software, visualisation, and writing (draft, review, and editing). JR: data curation, supervision, and writing (review and editing). MFH, PM, AR, CJMS, and BT: data curation and writing (review and editing). KS: data curation, software, writing (review and editing). JR, SA, and MG: writing (review and editing). DK: data curation, project administration, writing (review and editing). FG: data curation, validation, resources, writing (review and editing). RB: data curation, resources, funding acquisition, writing (review and editing). AR, SS, RHS, AA, GS, MM, AEL, CM, SEB, LZ, CS, MM, CF, AF, MF, MMO, SK, SP, BP, TKR, DS, DT, MC, JT, DD, AH, LC, JM, DS, DPB, DG, MJ, TS, and EF: resources, funding acquisition, writing (review and editing). MCT: conceptualisation, investigation, methodology, supervision, resources, funding acquisition, writing (review and editing). All authors contributed to the article and approved the submitted version.

Corresponding author

Correspondence to Maria Carmela Tartaglia.

Ethics declarations

Ethics approval and consent to participate

The studies involving human participants were reviewed and approved by ONDRI. Study participants were recruited at various health centres across Ontario, Canada: London Health Science Centre and Parkwood Institute in London; Hamilton General Hospital and McMaster Medical Centre in Hamilton; The Ottawa Civic Hospital in Ottawa; Thunder Bay Regional Health Sciences Centre in Thunder Bay; and St. Michael’s Hospital, Sunnybrook Health Sciences Centre, Baycrest Health Sciences, Centre for Addiction and Mental Health, and Toronto Western Hospital (University Health Network) in Toronto. Ethics approval was obtained from all participating institutions and performed in accordance with the Declaration of Helsinki. All participants and study partners provided informed consent. The patients/participants provided their written informed consent to participate in this study.

Conflict of interest

TKR has received research support from Brain Canada, Brain and Behavior Research Foundation, BrightFocus Foundation, Canada Foundation for Innovation, Canada Research Chair, Canadian Institutes of Health Research, Centre for Aging and Brain Health Innovation, National Institutes of Health, Ontario Ministry of Health and Long-Term Care, Ontario Ministry of Research and Innovation, and the Weston Brain Institute. TKR also received in-kind equipment support for an investigator-initiated study from Magstim, and in-kind research accounts from Scientific Brain Training Pro. DPB is supported by a Wellcome Clinical Research Career Development Fellowship (214571/Z/18/Z). Other authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

ONDRI Investigators and their affiliations are listed under the CONSORTIUM NAME section.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 177 KB)

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ozzoude, M., Varriano, B., Beaton, D. et al. Investigating the contribution of white matter hyperintensities and cortical thickness to empathy in neurodegenerative and cerebrovascular diseases. GeroScience 44, 1575–1598 (2022). https://doi.org/10.1007/s11357-022-00539-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11357-022-00539-x

Keywords

Navigation