Mapping dopaminergic projections in the human brain with resting-state fMRI

  1. Marianne Oldehinkel  Is a corresponding author
  2. Alberto Llera
  3. Myrthe Faber
  4. Ismael Huertas
  5. Jan K Buitelaar
  6. Bastiaan R Bloem
  7. Andre F Marquand
  8. Rick C Helmich
  9. Koen V Haak
  10. Christian F Beckmann
  1. Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Netherlands
  2. Department of Cognitive Neuroscience, Radboud University Medical Centre, Netherlands
  3. Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Australia
  4. Department of Communication and Cognition, Tilburg Centre for Cognition and Communication, Tilburg University, Netherlands
  5. Institute of Biomedicine of Seville (IBiS), Spain
  6. Department of Neurology, and Centre of Expertise for Parkinson & Movement Disorders, Radboud University Medical Centre, Netherlands
  7. Centre for Neuroimaging Sciences, Institute of Psychiatry, King’s College London, United Kingdom
  8. Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, United Kingdom
6 figures, 9 tables and 1 additional file

Figures

The connectopic mapping pipeline.

The functional MRI (fMRI) time-series data from a predefined region of interest (ROI), here the striatum, are rearranged into a time-by-voxels matrix A, as are the time series from all voxels outside the ROI (matrix B). For reasons of computational tractability, the dimensionality of B is losslessly reduced using singular value decomposition (SVD), yielding ∼B. For every voxel within the ROI, its connectivity fingerprint is computed as the Pearson’s correlation (CORR) between the voxel-wise time-series and the SVD-transformed data, yielding matrix C. Then similarity between voxels is computed using the η2 coefficient, resulting in matrix S. Manifold learning using Laplacian eigenmaps is then applied to this matrix, yielding a set of overlapping, but independent, connection topographies or ‘connectivity modes’ that together describe the functional organization of the striatum. These connection topographies indicate how the connectivity profile with the rest of the brain changes across striatum. Voxels that have similar colours in these connectivity modes have similar connectivity patterns with the rest of the brain. Finally, trend surface modelling is applied to summarize the connectivity modes by fitting a set of trend coefficients (β) that optimally combine a set of spatial polynomial basis functions. See Haak et al., 2018 for further details.

Figure 2 with 3 supplements
High spatial correspondence between the second-order mode of connectivity in striatum and the DaT SPECT image.

The figure displays the DaT SPECT image averaged across 209 Parkinson’s Progression Markers Initiative (PPMI) controls and the group-level connectivity modes obtained in 839 Human Connectome Project (HCP) subjects. The group-level modes were modelled separately for the left and right putamen and caudate-nucleus accumbens (caudate-NAcc) subregions and have been combined in this figure to aid in visualization. The voxel-wise spatial correlation between the second-order mode of connectivity in striatum and the DaT SPECT image is very high: r = 0.884 (p<0.001). Similarly, the correlation between the orthogonal trend surface model (TSM) coefficients modelling the second-order connectivity mode and the DaT SPECT scan in striatum is very high: r = 0.925 (p<0.001, bottom row). R-fMRI, resting-state fMRI; L, left; R, right.

Figure 2—figure supplement 1
The correlation between trend surface model (TSM) coefficients modelling the second-order connectivity mode and the DaT SPECT scan is highly significant and substantially higher than all other position emission tomography (PET)-derived markers indexing other neurotransmitter systems.

The top panel displays the absolute, Fisher’s Z normalized correlations between the TSM coefficients modelling the second-order connectivity mode and the TSM coefficients of various SPECT- and PET-derived markers. The dotted lines represent significance values of p=0.01 and p=0.0008 (i.e., p=0.01/12 PET/SPECT scans; Bonferroni-corrected) derived from the null distribution in the bottom panel, which was generated by permuting the TSM coefficients obtained for each of the PET markers (N = 10,000) and computing the absolute (Fisher r-to-z normalized) correlations with the TSM coefficients of the connectivity mode.

Figure 2—figure supplement 2
The second-order connectivity mode obtained in the 10% lowest and 10% highest movers of the Human Connectome Project (HCP) dataset is comparable to the mode obtained in the full sample.
Figure 2—figure supplement 3
Inter-subject and inter-session (within-subject) variability in the second-order mode of connectivity in striatum.

Individual-subject connectivity modes are shown for 10 randomly selected Human Connectome Project (HCP) subjects (from a total of 839). This figure shows variations between subjects as well as variations between sessions for the same subjects.

Figure 3 with 2 supplements
Within-subject correlations between the second-order connectivity mode and the DaT SPECT scan from subjects in the Parkinson’s Progression Markers Initiative (PPMI) cohort where both resting-state functional MRI (fMRI) and DaT SPECT data is available.

These correlations were obtained in a subsample of the PPMI dataset (6–8 datasets from controls and 73–82 datasets from Parkinson’s disease patients depending on the striatal subregion) with good-quality connectivity modes as defined by a high spatial correlation (r > 0.5) with the group-average Human Connectome Project (HCP) connectivity mode. Red dots represent control participants; black dots represent Parkinson’s disease patients.

Figure 3—figure supplement 1
Spatial correlations of the subject-specific second-order connectivity modes with the mean Human Connectome Project (HCP) connectivity mode and DaT SPECT scan.

These plots show that when the connectivity mode of a subject resembles the HCP group-average connectivity mode – assumed to be an index of good quality – a high spatial similarity can be observed between the connectivity mode and the DaT SPECT scan of that subject. Red dots represent control participants, black dots represent Parkinson’s disease patients.

Figure 3—figure supplement 2
Within-subject correlations between the second-order connectivity mode and the DaT SPECT scan in a low motion and high motion subsample.

These correlations were obtained in a subsample of the Parkinson’s Progression Markers Initiative (PPMI) dataset with good-quality connectivity modes as defined by a high spatial correlation (r > 0.5) with the group-average Human Connectome Project (HCP) connectivity mode. The meanFD cutoff = 0.126, meaning that if the meanFD of a subject was below 0.126 that subject was part of the low motion subsample, if the meanFD was above 0.126, the subject was part of the high motion subsample. Red dots represent control participants; black dots represent Parkinson’s disease patients.

The second-order striatal connectivity mode is altered in right-dominant Parkinson’s disease.

(A) Significant difference between the control group and the right-dominant Parkinson’s disease group under placebo in putamen (omnibus test of all trend surface model [TSM] coefficients for putamen: X2 = 27.17, p=0.007). Images represent the mean connectivity modes across each of the investigated groups. The slices at MNI coordinates x = –26 and x = 26, respectively, show views of the striatal connectivity mode across left and right putamen where the connectivity mode is significantly different between groups (*); the slices at MNI coordinates x = –14 and x = 14, respectively, show views of the mode across left and right caudate-nucleus accumbens (caudate-NAcc) (no significant difference). (B) Trend-level association between the Unified Parkinson’s Disease Rating Scale (UPDRS) symptom severity score and the TSM coefficients modelling the second-order connectivity mode in putamen under placebo across patients in the right-dominant Parkinson’s disease group (general linear model [GLM] omnibus test of all TSM coefficients: X2 = 22.28, p=0.035). Post-hoc Pearson correlations revealed that this effect was driven by the quadratic TSM coefficients modelling the striatal connectivity mode in the right putamen in the Y (i.e., anterior-posterior) direction (right Y2: r = 0.476, p=0.034) and Z (i.e., superior-inferior) direction (right Z2: r = −0.460, p=0.041). The correlation between UPDRS symptom severity scores is displayed for the right Y2 coefficient. To visualize this association, the reconstructed second-order connectivity mode in the right putamen is shown for five Parkinson’s disease patients (data points circled) with increasing UPDRS symptom severity scores.

Levodopa-benserazide (L-DOPA)-induced reduction in Unified Parkinson’s Disease Rating Scale (UPDRS) symptom severity score is associated with the L-DOPA-induced change in the second-order mode of connectivity in putamen in right-dominant Parkinson’s disease (PD) (general linear model [GLM] omnibus test of all trend surface model [TSM] coefficients modelling putamen: X2 = 25.48, p=0.012).

Post-hoc Pearson correlations revealed that this effect was driven by the linear TSM coefficient modelling the striatal connectivity mode in the left putamen in the Y direction (left Y1: r = −0.548, p=0.012). To visualize this association, the difference in the reconstructed second-order connectivity modes between the placebo and L-DOPA session is shown for the left putamen (at slice X = –24) for five PD patients (data points circled). Red-coded voxels are hypothesized to map onto an increase in dopaminergic connectivity, blue-coded voxels onto a decrease. A significant effect was also observed for the left-dominant PD group (GLM omnibus test of all TSM coefficients: X2 = 34.07, p=0.001), but as post-hoc Pearson correlations did not reveal significant associations with one of the individual TSM coefficients in this group, this association is not shown. ant, anterior; post, posterior putamen.

Figure 6 with 2 supplements
The second-order mode of connectivity in striatum is associated with the amount of tobacco use (top) and alcohol use (bottom).

Strong associations were observed between the trend surface model (TSM) coefficients modelling the connectivity mode in the caudate-nucleus accumbens (caudate-NAcc) region and the total amount of tobacco use as well as alcohol use over the past week (general linear model [GLM] omnibus test tobacco use: X2 = 49.55, p=0.002; alcohol use: X2 = 64.45, p<0.001). To visualize these relationships, Pearson correlations between one of the significant TSM coefficients and the amount of use are shown as well as the reconstructed second-order connectivity mode in the right caudate-NAcc (at slice X = 14) for four tobacco users and in the left caudate-NAcc (at slice X = –14) for four alcohol users with increasing of amounts of use (data points circled). Circles and arrows indicate where in the connectivity mode tobacco and alcohol use-related changes can be observed. Correlation plots for the other TSM coefficients can be found in Figure 6—figure supplements 1 and 2.

Figure 6—figure supplement 1
The second-order mode of connectivity in striatum is associated with the amount of tobacco use.

A strong association was observed between the trend surface model (TSM) coefficients modelling the connectivity mode in the caudate-nucleus accumbens (caudate-NAcc) region and the total amount of tobacco use over the past week (general linear model [GLM] omnibus test: X2 = 49.55, p=0.002). To visualize this relationship, Pearson correlations between the individual TSM coefficients and the amount of use were computed, and the correlations reaching significance (p<0.05) are shown in this figure.

Figure 6—figure supplement 2
The second-order mode of connectivity in striatum is associated with the amount of alcohol use.

A strong association was observed between the trend surface model (TSM) coefficients modelling the connectivity mode in the caudate-nucleus accumbens (caudate-NAcc) region and the total number of alcoholic drinks over the past week (general linear model [GLM] omnibus test: X2 = 64.45, p<0.001). To visualize this relationship, Pearson correlations between the individual TSM coefficients and the amount of use were computed, and the correlations reaching significance (p<0.05) are shown in this figure.

Tables

Table 1
Interclass correlation coefficients (ICCs) between the two scanning sessions and the session 1 to session 2 within-subject and between-subject spatial correlations.
Striatal subregionICC[bootstrapped 95% CI]Within-subject correlationBetween-subject correlationWithin vs. between permutation test(Nperm = 10,000)
Left putamen0.960 [0.951–0.965]0.9690.965p<0.0001
Right putamen0.961 [0.952–0.967]0.9700.966p<0.0001
Left caudate-NAcc0.974 [0.968–0.978]0.9810.976p<0.0001
Right caudate-NAcc0.974 [0.968–0.978]0.9810.977p<0.0001
  1. CI = confidence interval; NAcc = nucleus accumbens.

Table 2
Participant characteristics.
Demographic information(mean, SD)ControlsN = 20PDN = 39Test statistic
Age, years61.910.460.910.7t(57) = 0.337NS
Sex, male (number, %)1155.0%1641.0%X2(1) = 0.086NS
FAB, total score17.60.6717.30.97t(57) = 0.23NS
Disease duration, yearsNA3.964.57NA
L-DOPA equivalent at home (mg/day)NA467.8227.3 (range: 0–1100)NA
UPDRS total score (mean, SD)
Placebo sessionNA40.516.4t(38) = 5.58p<0.001
L-DOPA sessionNA31.913.1
  1. For the FAB, lower scores indicate worse functioning; for the UPDRS, higher scores indicate worse functioning. The FAB score was evaluated off medication.

  2. FAB = frontal assessment battery (score 0–18); UPDRS = Unified Parkinson’s Disease Rating Scale part III (score 0–132); NS = not significant; NA = not applicable; PD = Parkinson’s disease; L-DOPA = levodopa-benserazide.

Appendix 2—table 1
Post-hoc analyses of age and sex.
Original analysisOriginal analysis +age and sexAge and sex only
X2p-ValueX2p-ValueX2p-Value
Putamen
Patients vs. controlsRight tremor-dominant Parkinson’s disease27.170.00727.210.0180.480.786
UPDRS symptom severityRight tremor-dominant Parkinson’s disease22.280.03523.460.0532.380.305
L-DOPA-placebo differenceLeft tremor-dominant Parkinson’s disease34.070.00146.14<0.0012.420.299
L-DOPA-placebo differenceRight tremor-dominant Parkinson’s disease25.480.01237.530.0017.180.028
Caudate-NAcc
Tobacco useHCP dataset49.550.00253.560.0011.040.594
Alcohol useHCP dataset64.45<0.001174.87<0.0019.260.010
  1. UPDRS = Unified Parkinson’s Disease Rating Scale; L-DOPA = levodopa-benserazide; HCP = Human Connectome Project; NAcc = nucleus accumbens.

Appendix 2—table 2
Post-hoc analyses using different thresholds for tobacco use.
Original analysis:≥5× tobacco use a dayN = 38≥2× tobacco use a dayN = 62≥8× tobacco use a dayN = 30
X2p-ValueX2p-ValueX2p-Value
Tobacco useHCP dataset caudate-NAcc49.550.00237.960.03570.54<0.001
  1. HCP = Human Connectome Project; NAcc = nucleus accumbens.

Appendix 2—table 3
Post-hoc analyses using different thresholds for alcohol use.
Original analysis:≥3× light alcoholic and/or ≥1× hard liquor drinks a dayN = 30≥1× alcoholic drinks a day (light and/or hard liquor)N = 103≥3× alcoholic drinks a day (light and/or hard liquor) *N = 26
X2p-ValueX2p-ValueX2p-Value
Alcohol useHCP dataset caudate-NAcc64.45<0.00129.940.187196.57<0.001
  1. HCP = Human Connectome Project; NAcc = nucleus accumbens.

Appendix 2—table 4
Subject IDs from the 839 HCP subjects used in the connectopic mapping analysis.
100206129129155635181636212823385450580044784565
100610129331155938182032213017386250580347788674
101006129533156031182436213421387959580650789373
101107129634156435183034213522389357580751792766
101309129937156536183337214524391748581450792867
101410130114157437183741214625392447583858793465
101915130316157942185341214726392750585256800941
102008130417158136185442217126393247587664802844
102109130619158338185846219231393550588565803240
102311130720158843185947220721394956589567804646
102513130821159138186040221218395251590047809252
102614131217159340186141223929395756592455810439
102715131419159441186545227432395958594156810843
103010131722159744186848227533397154597869812746
103111131823159845187143228434397861599065814548
103212132017159946187345231928406432599469814649
104012132118160729187547233326406836599671815247
104416133019160830187850236130412528601127816653
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105014134223161630188347238033419239609143818859
105620134425161832188448239136421226611938820745
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106016134829162228188751250932424939613538825048
106521135124162733189349255740432332615441825553
106824135225162935189450256540436239615744825654
107018135528163129191033257542436845616645826454
107220135629163331191235257845441939617748827052
107321135730163836191336257946445543618952828862
107422136126164030191841263436449753620434832651
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108121136732164939192136270332454140623844835657
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108323137229165234192641275645459453627852837964
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109123137633165941193845281135467351635245844961
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115017144125171330199352304727513736679568884064
115219144731171431199453305830516742679770886674
115724144832171532200008308129517239680250888678
115825144933171633200109308331518746680452891667
116221145127171734200311309636519647683256894067
116423145531172029200513310621519950686969894774
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116726145834172433201414314225521331689470901038
117021146129172534201717316633522434690152901442
117728146331172635201818316835523032692964902242
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122418150928176744207426350330555954731140947668
122620151021176845208024352132557857734247952863
122822151324177140208125352738558657735148953764
123420151425177241208327353740558960737960955465
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123824151930178142209127358144561949748662962058
123925152225178243209228360030562345749058965771
124220152427178647209329361234562446751550966975
124624152831178748209531361941565452753150970764
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125222153126178950210011365343567052759869972566
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128026154734180836212015380036576255774663992673
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128329154936181131212217381543578158782561996782
128935155231181232212419382242579867783462788674
  1. HCP = Human Connectome Project.

Appendix 2—table 5
Subject IDs from the 209 PPMI controls with DaT SPECT data used in our analysis.
PPMIsubject IDImage IDDaT SPECTPPMIsubject IDImage IDDaT SPECTPPMIsubject IDImage IDDaT SPECT
300032366233503399013637388521
300434119433513399023639388523
300834119533533399043651339008
300934119633553412363651355956
301134119833573399073656339014
301334120033583399083658339016
301634120233613399113662355221
302938846833623399123668388528
305334120733633387803750388535
305534120933683399173754360616
305734121133693399183756360617
306434121733703399193759363950
306934122133893885043765363951
307034122233903885053767388536
307134122334013403453768363952
307234122434043403463769360618
307334122534053403473779453700
307434122634103403513794388545
307534122734113403523796388147
308538847034143403543803355230
308738847234243403633804354344
310034123034383403883805354345
310334123334503403983806354346
310433953634523399233807355231
310634041834533399243811360620
310934042334573399283812355232
311234042634583399293813355233
311434043034603412433816363953
311534043134643412453817388148
315134101834663399323850337832
315634102134683399343851337833
315734102234783606133852337834
316034102334793639453853337835
316134102434803885093854337836
316534102734813885103855337445
316934103135033404003857337837
317134103335153404083859337839
317234103435173412483907388556
318838848335183395373908363957
319138848635213395393917388563
320034103635233395413950341083
320134103735243395423952341085
320234103835253395433955388565
320434104035263395443959355241
320634104235273395453965388573
320834104435413552153966388574
321334104935433639463967388576
321534105135443885143968388577
321634105235513395503969388578
321734105335543395524004339032
321934105535543581384007339035
322134105735553395534008339036
322234105835633395594009339037
323538848835653395614010339038
323738849035693395644014389268
325734106735703395654018339045
326034106835713892454032388583
326434107035723387814063355246
327034107435763387854067388593
327134107536003387884079388596
327434107736113387974090343886
327634107936133387994095354353
327738849136143388004100360623
328638849436153388014104363963
330033988936193390014105388600
330133989036203390024116388613
331033989636243412514118388615
331634218736273422044139388627
331834218936353885194140388628
33203421913636388520
  1. PPMI = Parkinson’s Progression Markers Initiative; DaT = dopamine transporter; SPECT = single-photon emission computed tomography.

Appendix 2—table 6
Subject IDs from PD patients and controls with resting-state fMRI data and DaT SPECT data from the PPMI dataset used in our analysis.
PPMI subject IDImage ID DaT SPECTImage ID MRIDiagnosis
3310339896369414Control
3318342189374882Control
3350339901515208Control
3351339902508245Control
3353339904515216Control
3361339911581042Control
3369339918544617Control
3389388504367349Control
3551339550548987Control
3563339559548989Control
3565339561560369Control
3769360618362609Control
4018339045365285Control
4032388583367390Control
3107419849378215PD
3108419850378223PD
3116418649366137PD
3116419854417052PD
3118418470362555PD
3118446107430138PD
3119418650382277PD
3119446108430147PD
3120418651374854PD
3122419241382284PD
3123418652382289PD
3123449008440114PD
3124418653387304PD
3124449009440118PD
3125418654387314PD
3125449010440128PD
3126418655397752PD
3126449011440131PD
3128419553395434PD
3128504427466848PD
3130360608355962PD
3130419554417000PD
3132436066423718PD
3132504428498892PD
3134388480369013PD
3134436067436351PD
3327389212362478PD
3327486550412180PD
3332388500378540PD
3352418905372319PD
3354418906372327PD
3359419866397593PD
3360419867393662PD
3364419868393672PD
3365419659397597PD
3366419869397624PD
3367419870393674PD
3371418673365166PD
3372436070369487PD
3372446121420330PD
3373418674387316PD
3373449019440174PD
3374418675393614PD
3374446122430165PD
3377418677393628PD
3377449020440186PD
3378418678387324PD
3380418679393636PD
3380468270449575PD
3383355208351070PD
3383419560415707PD
3385360612353398PD
3385436861415713PD
3386388502369048PD
3387389214357590PD
3387436071417033PD
3392388507372995PD
3392442969436390PD
3552418922378354PD
3556418923372348PD
3556504848482323PD
3557504849482329PD
3559418926372359PD
3559504850491605PD
3574419676414623PD
3575419677581115PD
3575418690365225PD
3585449026440198PD
3586468275449581PD
3587468276449584PD
3591388516373018PD
3591504435491626PD
3592388517373035PD
3592442973436404PD
3593388518369096PD
3593436073430199PD
3593504436507400PD
3758418698374893PD
3758419880402067PD
3760418499362591PD
3787419576412194PD
3800389258393684PD
3808419885402071PD
3815419886581145PD
3818446139440242PD
3819419270395448PD
3822419271382366PD
3822449035440262PD
3823419272395585PD
3823449036440267PD
3824419579395592PD
3824468279449614PD
3825419273393639PD
3825504450549048PD
3826419274395600PD
3826468280449625PD
3828419580395605PD
3828468281449661PD
3829419581395614PD
3830419582412202PD
3830495006468929PD
3831419583402267PD
3832419584412209PD
3832495007468935PD
3834419585415724PD
3834504454473094PD
3835436875415731PD
3838436075423748PD
3838504456515249PD
3869436077415744PD
3870363956395313PD
3870486557415751PD
4005419890397646PD
4011418504402285PD
4019418710362640PD
4019446143417057PD
4021419277430178PD
4022418712365294PD
4022446145417065PD
4029468288468943PD
4030363959356036PD
4030419596415756PD
4030495322468949PD
4034388585367425PD
4034436083423755PD
4035388587369183PD
4035436084423762PD
4035504466475680PD
4038388590367446PD
4038436085430210PD
  1. PD = Parkinson’s disease; DaT = dopamine transporter; fMRI = functional MRI; SPECT = single-photon emission computed tomography; PPMI = Parkinson’s Progression Markers Initiative.

Author response table 1
meanFD
NMeanSDRange
HCP8390.08710.03620.0375-0.3155
PPMI all DaT SPECT controls209Not available for DaT SPECT scan
PPMI within-subject analysis, full sample1440.13080.06200.0438-0.3124
PPMI within-subject analysis, patients1300.12920.06090.0438-0.3124
PPMI within-subject analysis, controls140.14630.05410.0722-0.2778
Local PD dataset, full sample placebo590.11040.05350.0352-0.2762
Local PD dataset, patients placebo390.11650.04920.0490-0.2363
Local PD dataset, controls placebo200.09870.06040.0352-0.2762
Local PD dataset, patients LDOPA390.12770.08250.0376-0.5252*
*There was 1 subject with a meanFD of 0.5252, but also after excluding this subject results remained significant. All other subjects had a meanFD<0.3.

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  1. Marianne Oldehinkel
  2. Alberto Llera
  3. Myrthe Faber
  4. Ismael Huertas
  5. Jan K Buitelaar
  6. Bastiaan R Bloem
  7. Andre F Marquand
  8. Rick C Helmich
  9. Koen V Haak
  10. Christian F Beckmann
(2022)
Mapping dopaminergic projections in the human brain with resting-state fMRI
eLife 11:e71846.
https://doi.org/10.7554/eLife.71846