10970193, 2021, 17, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25650 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [20/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Received: 21 June 2021 Revised: 30 July 2021 Accepted: 23 August 2021 DOI: 10.1002/hbm.25650 RESEARCH ARTICLE The impact of dopaminergic treatment over cognitive networks in Parkinson's disease: Stemming the tide? Ignacio Aracil-Bolaños1,2,3,4 | Frederic Sampedro1,2,3,4 | Jesus Pujol5,6 | Carles Soriano-Mas 6,7,8 |  nzalez-de-Echávarri9 | José María Go Jaime Kulisevsky1,2,3,4 | Javier Pagonabarraga1,2,3,4 1 Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain Abstract 2 Departament de Medicina, Universitat Dopamine-replacing therapies are an effective treatment for the motor aspects of Autònoma de Barcelona (U.A.B.), Barcelona, Spain Parkinson's disease. However, its precise effect over the cognitive resting-state net- 3 Institut d'Investigacions Biomèdiques- Sant Pau (IIB-Sant Pau), Barcelona, Spain works is not clear; whether dopaminergic treatment normalizes their functional 4 n en Red- Centro de Investigacio connectivity-as in other networks- and the links with cognitive decline are presently Enfermedades Neurodegenerativas unknown. We recruited 35 nondemented PD patients and 16 age-matched controls. (CIBERNED), Barcelona, Spain 5 MRI Research Unit, Department of Radiology, Clinical and neuropsychological assessments were performed at baseline, and conver- Hospital del Mar, Barcelona, Spain sion to dementia was assessed in a 10 year follow-up. Structural and functional brain 6 n Biomédica en Red de Centro Investigacio imaging were acquired in both the ON and practical OFF conditions. We assessed Salud Mental, CIBERSAM, Barcelona, Spain 7 functional connectivity in both medication states compared to healthy controls, con- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical nectivity differences within participants related to the ON/OFF condition, and base- Research Institute (IDIBELL), Barcelona, Spain line connectivity of PD participants that converted to dementia compared to those 8 Department of Psychobiology and Methodology in Health Sciences, Universitat who did not convert. PD participants showed and increased frontoparietal connectiv- Autònoma de Barcelona, Barcelona, Spain ity compared to controls: a pattern of higher connectivity between salience (SN) and 9 Barcelonaβeta Brain Research Center (BBRC), default-mode (DMN) networks both in the ON and OFF states. Within PD patients, Pasqual Maragall Foundation and IMIM (Hospital del Mar Medical Research Institute), this higher SN-DMN connectivity characterized the participants in the ON state, Barcelona, Spain while within-DMN connectivity prevailed in the OFF state. Interestingly, participants Correspondence who converted to dementia also showed higher SN-DMN connectivity in their base- Jaime Kulisevsky and Javier Pagonabarraga, line ON scans compared to nonconverters. To conclude, PD patients showed higher Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Mas frontoparietal connectivity in cognitive networks compared to healthy controls, Casanovas, Barcelona 90-08041, Spain. irrespective of medication status, but dopaminergic treatment specifically promoted Email: jkulisevsky@santpau.cat (J. K.) and jpagonabarraga@santpau.cat (J. P.) SN-DM hyperconnectivity. Funding information KEYWORDS Agència de Gestio d'Ajuts Universitaris i de cognitive networks, dopamine, functional MRI, Parkinson's disease Recerca, Grant/Award Number: PERIS SLT008/18/00088; Centro de Investigacio n Biomédica en Red sobre Enfermedades Neurodegenerativas; Fundacio  la Marato  de TV3, Grant/Award Number: 20142910; Instituto de Salud Carlos III, Grant/Award Number: PI14/02058 This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. 5736 wileyonlinelibrary.com/journal/hbm Hum Brain Mapp. 2021;42:5736–5746. 10970193, 2021, 17, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25650 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [20/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License ARACIL-BOLAÑOS ET AL. 5737 1 | I N T RO DU CT I O N (Shine et al., 2019), few have employed ON–OFF paradigms to explore resting-state cognitive networks. A comprehensive review on Parkinson's disease (PD) is a neurodegenerative disease characterized the role of dopaminergic treatment over functional MRI concluded by the progressive loss of nigrostriatal dopaminergic neurons. Its clini- that the DRT tends to normalize the aberrant connectivity present in cal hallmarks are the onset of tremor, rigidity, and bradykinesia the OFF state (Tahmasian et al., 2015), but its effect on cognitive (Postuma et al., 2015). Given the progressive loss of dopaminergic ter- large-scale networks is not well-known. While older studies have minals and the efficacy of dopamine-replacing therapies (DRTs) on focused on the acute effects of dopaminergic treatment over the dor- motor symptoms, levodopa has been the mainstay of PD treatment sal and ventral connections of the striatum (Macdonald & over the past 50 years. However, some nonmotor aspects are not as Monchi, 2011), a perspective that encompasses the diversity of cogni- well addressed by dopaminergic treatments. Chief among them is pro- tive networks, beyond frontostriatal loops, is still lacking. gressive cognitive impairment and dementia, which affects a majority To sum up, no study to date has assessed the differences which of PD patients over the disease course (Hely, Reid, Adena, Halliday, & levodopa causes on large-scale cognitive networks, such as the Morris, 2008). PD patients show dysexecutive symptoms from the default, salience or central executive networks. Furthermore, it is onset of the disease, but the progressive emergence of posterior cor- unclear whether these changes might constitute an adaptive mecha- tical disruptions heralds the slide into cognitive impairment (González- nism or, on the contrary, could represent a vulnerability trait regarding Redondo et al., 2014; Mak et al., 2015; Pagonabarraga & long term conversion to dementia. Thus, in the present study we Kulisevsky, 2012). The neural correlates of these early stages have explored the role of dopaminergic treatment over cognitive networks been defined in structural terms: frontal areas exhibit reduced cortical by recruiting a group of nondemented PD participants and age- thickness in PD patients compared to healthy controls (HCs), with matched HCs, taking into account dopaminergic treatment by acquir- patients with mild cognitive impairment (PD-MCI) showing additional ing functional MRI (fMRI) images both in the ON and the OFF condi- losses of gray matter in temporo-parietal regions (Pagonabarraga, tions. We followed-up a subgroup of participants and evaluated long- Soriano-mas, & Llebaria, 2014; Segura et al., 2014). However, we still term conversion to dementia in order to assess the clinical relevance lack patterns of cognitive network disruption that predate cognitive of network connectivity differences. decline, and structural imaging is not likely to provide them (Lanskey et al., 2018). Using functional MRI, PD-MCI has been linked to altered func- 2 | METHODS tional connectivity and graph theoretical metrics in diverse studies (Baggio et al., 2015; Sala-llonch, Baggio, Valldeoriola, & 2.1 | Participants Compta, 2015), and distinct subtypes of cognitive impairment can be outlined using these parameters (Lopes et al., 2016). More recently, Forty participants with idiopathic PD regularly attending our Move- metrics of dynamic functional connectivity have been adopted to ment Disorders Outparticipant Unit and 16 age-matched HCs who study changes in time-dependent components of brain networks, were willing to participate in this study were prospectively recruited. identifying distinct connectivity states related to cognition (Fiorenzato Inclusion criteria was the diagnosis of PD according to the et al., 2019), and links of network dynamics to visuospatial memory United Kingdom PD Society Brain Bank (Hughes, Daniel, Kilford, & (Engels, Vlaar, McCoy, Scherder, & Douw, 2018). Interestingly, the rel- Lees, 1992) and exclusion criteria were: (a) presence of dementia ative increase of frontoparietal functional connectivity in nonde- according to MDS-PDD Criteria (Emre et al., 2007) and Parkinson's mented PD patients, compared to HCs, might point toward Disease Cognitive Rating Scale (PD-CRS) total score <64 (de Bobadilla compensation or vulnerability features in at-risk patients (Gorges et al., 2013); Hoehn & Yahr scale >III; (b) presence of any other signifi- et al., 2015). These features are distinct at a network level in normal cant psychiatric, neurological, or unstable systemic comorbidities; cognition (PD-NC), and seem to wane in the PD-MCI patients (Aracil- (c) pathological MRI findings beyond mild white matter hyper- Bolaños et al., 2019), disrupting the functional integrity of intensities; (d) presence of head motion or other MRI artifacts; frontoparietal networks in the absence of gray matter loss (Amboni and (e) inability to tolerate MRI acquisition in the OFF state. Four et al., 2015). Thus, the investigation of early disruptions could provide participants were excluded due to image quality-checking and one network signatures of future decline in patients who show no overt participant because of dementia. All participants provided written clinical signs of cognitive impairment. informed consent according to the Declaration of Helsinki. The study These mechanisms might be affected by dopaminergic treatment was approved by the Ethics Committee for Clinical Research at the and therefore the role of DRT has to be accounted for. Studies that Hospital de la Santa Creu i Sant Pau, Barcelona. jointly analyze functional MRI and quantitative levels of dopamine via FP-CIT have shown that dopamine-dependent functional networks comprise motor and cerebellar regions, but also frontoparietal cogni- 2.2 | Clinical assessment tive networks have links to cortical hubs such as the posterior cingu- late cortex (Baik et al., 2014). However, while many excellent studies Participants were assessed using a battery of clinical and neuropsy- have approached the effects of dopamine depletion on brain topology chological tests. All participants were clinically assessed at baseline, 10970193, 2021, 17, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25650 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [20/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 5738 ARACIL-BOLAÑOS ET AL. together with the MRI acquisition, and a subset of participants who thickness 4 mm), both in the ON and practical OFF conditions (12 hr completed follow up were assessed for conversion to dementia in a withdrawal of dopaminergic medications prior to MRI acquisition). 10-year follow-up (2008–2018 period). Motor status was assessed using the Unified Parkinson's disease rating scale part III (UPDRS-III). Anxiety and depression were evaluated using the Hospital Anxiety 2.4 | Cortical thickness analysis and Depression Scale (HADS). At time of inclusion, global cognitive status was addressed using the Parkinson's disease cognitive rating A standard cortical thickness pipeline was applied. Cortical thickness scale (PD-CRS) and the Clinical Dementia Rating (CDR). The PD-CRS analysis was performed using the FreeSurfer 6.0 software package comprises nine subtests that assess immediate verbal memory, nam- (https://surfer.nmr.mgh.harvard.edu/). The specific methods used for ing, sustained attention, working memory, unprompted drawing of a cortical reconstruction of T1-MRI brain images have been described in clock, copy of a clock, delayed free recall, alternating verbal fluency, detail elsewhere (Fischl & Dale, 2000). Briefly, optimized surface defor- and action verbal fluency. The PD-CRS provides a total score ranging mation models following intensity gradients accurately identify white from 0 to 134; cutoff scores <64 and <82 were previously proven to matter and gray matter boundaries in the cerebral cortex, from which be reliable for the screening of dementia and PD-MCI, respectively cortical thickness is computed at each vertex of the resulting surface. (de Bobadilla et al., 2013; Pagonabarraga et al., 2008; Pagonabarraga, Finally, the resulting cortical surfaces were normalized to average space Corcuera-solano, Vives-gilabert, Llebaria, & Garcı, 2013). The CDR and smoothed using a Gaussian kernel of 10 mm FWHH. was used as gold standard for cognitive status in several studies, including the validation study of the PD-CRS (Pagonabarraga et al., 2008). This instrument assesses cognitive and functional perfor- 2.5 | Functional connectivity analysis mance in six areas: memory, orientation, judgment and problem solv- ing, community affairs, home and hobbies, and personal care (Hughes, Functional imaging preprocessing was performed using CONN v20 Berg, Danziger, Coben, & Martin, 1982). A CDR of 0 indicates no cog- software and its standard processing pipeline, described in depth in nitive deficits, 0.5 indicates very mild cognitive impairment, and 1–3 (Whitfield-Gabrieli & Nieto-Castanon, 2012). Briefly, functional scans indicate mild to severe cognitive impairment. As per inclusion criteria, were first slice-timing corrected, realigned, and spatially normalized to all participants were free of cognitive impairment in the range of the Montreal Neurological Institute (MNI) space using co-registration dementia and thus, had a PD-CRS total score >64 and a CDR <1. with the associated anatomical data. Then, resting-state images were All participants were assessed in the practical OFF and ON condi- submitted to CONN's standard denoising pipeline, which combines tions. For the ON acquisitions, and by virtue of being in a fluctuating two steps: linear regression of potential confounding effects and tem- stage of the disease, all participants were scanned after they took poral band-pass filtering. For the first step, factors that are identified their levodopa dose in the OFF state in the morning and their best as potential confounding effects to the estimated BOLD signal are ON was achieved. For the OFF-state acquisitions, participants estimated and removed separately for each voxel and for each partici- observed a strict 12 hr practical OFF period, and they were examined pant and functional run/session using Ordinary Least Squares regres- by a trained neurologist prior to the acquisition to ensure that the sion to project each BOLD signal timeseries to the sub-space scans were reflecting a true OFF state. orthogonal to all potential confounding effects. Potential confounding At follow-up, the CDR was chosen to determine the global cogni- effects used in CONN's default denoising pipeline implement an ana- tive status of participants. Those with a CDR <1 were considered tomical component-based noise correction procedure (aCompCor), nondemented, whereas those with CDR equal or above 1 were con- and include: (a) Noise components from cerebral white matter and sidered as with major cognitive impairment in the range of dementia. cerebrospinal áreas: potential confounding effects are defined from the observed BOLD signal within each of two anatomically-defined noise areas computed by applying a one-voxel binary erosion step to 2.3 | MRI acquisition and preprocessing the masks of voxels with values above 50% in white matter and CSF posterior probability maps. Within each area five potential noise com- MRI acquisition was performed on a 1.5 Tesla Signa Excite system ponents are estimated: (a) the first computed as the average BOLD (General Electric, Milwaukee, WI) station scanner. A high-resolution signal, and the next four computed as the first components in a Princi- T1-weighted anatomical image was obtained for each participant pal Component Analysis of the covariance within the subspace using a three-dimensional fast spoiled gradient inversion-recovery orthogonal to the average BOLD signal and all other potential con- prepared sequence with 130 contiguous slices (TR, 11.8 ms; TE, founding effects. (b) Estimated participant-motion parameters: a total 4.2 ms; flip angle, 15 ; field of view, 30 cm; 256  256 pixel matrix; of 12 potential noise components are defined from the estimated slice thickness, 1.2 mm). participant-motion parameters in order to minimize motion related Resting-state BOLD images during 6 min were obtained using a BOLD variability: three translation and three rotation parameters plus functional MRI sequence consisting of gradient recalled acquisition in their associated first-order derivatives. (c) Identified outlier scans or the steady state (TR = 2,000 ms, TE = 50 ms, flip angle 90 , 64  64 scrubbing: a variable number of noise components (one for each iden- pixel matrix, FOV 240 mm, in-plane voxel size 3.75  3.75 mm, slice tified outlier scan during the outlier identification preprocessing step) 10970193, 2021, 17, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25650 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [20/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License ARACIL-BOLAÑOS ET AL. 5739 are used as potential confounding effects to remove any influence of HC, and also to compare PD participants who converted to dementia these outlier scans on the BOLD signal. Potential outlier scans are with respect to those who did not. Only clusters surviving p-value identified from the observed global BOLD signal and the amount of <.05 after multiple comparison correction by permutation-testing with participant-motion in the scanner. Acquisitions with framewise dis- 10,000 permutations were considered significant. placement above 0.9 mm or global BOLD signal changes above 5 SD For the functional connectivity comparisons, we performed are flagged as potential outliers. Framewise displacement is computed two-sample T-tests (PD-ON vs. controls, PD-OFF vs. controls, at each timepoint by considering a 140  180  115 mm bounding PD-converters vs. PD nonconverters) and a paired T-test (PD-ON box around the brain and estimating the largest displacement among vs. PD-OFF) to compare the groups; age, sex, and other demographics six control points placed at the center of this bounding-box faces. were used as covariates of no interest whenever differences were Global BOLD signal change is computed at each timepoint as the found across groups: sex in PD versus control analyses, and age and change in average BOLD signal within SPM's global-mean mask scaled PD-CRS in dementia converters versus nonconverters (see Tables 1 to standard deviation units. (d) Constant and first-order linear session and S1). Finally, in the subset of participants that completed the effects, and constant task effects, if applicable. 10 year follow-up and had both ON and OFF scans we performed a Then, the obtained data were filtered using a band-pass filter in mixed ANOVA interaction analysis considering both within-participant the range of 0.01–0.1 Hz in order to focus on slow-frequency fluctua- conditions (medication status) and between group conditions (converter tions while minimizing the influence of physiological, head-motion, vs. nonconverter). and other noise sources. Filtering is implemented using a discrete In ROI-to-ROI rsfMRI connectivity analyses there is a need to cosine transform windowing operation to minimize border effects, control Type I errors as the number of comparisons between ROI con- and performed after regression to avoid any frequency mismatch in nections can exceed the thousands. Conservative approaches like the the nuisance regression procedure. Holm–Bonferroni correction might however result in too conservative The entire matrix of ROI-to-ROI functional connectivity values estimations, given that the number of tests grows quadratically with (using the bivariate correlation measure) was computed for each partici- the number of nodes, resulting in p-values lower than .00001 for a pant using the set of functional brain networks described in our previous standard network of 90 nodes and a family-wise data error of α = .05 work (Aracil-Bolaños et al., 2019) and available at https://findlab. (Zalesky, Cocchi, Fornito, Murray, & Bullmore, 2012). This has led to stanford.edu/functional_ROIs.html. In particular, we focused on the development of techniques such as Network-Based Statistics 43 regions of interest (ROIs) located in the default-mode (DMN), (NBS) or Spatial Pairwise Clustering (SPC) that aim to control Type I salience (SN), and Central Executive (CEN) networks, and also per- errors by clustering connections and applying permutation testing to formed analyses on the 11 ROIs pertaining to the sensorimotor net- ascribe a family-wise error (FWE) corrected p-value to each cluster. work. This parcellation scheme has been useful to delineate the SPC shows lower sensibility but higher specificity and a finer resolu- network-phenotype link in neurodegenerative disease (Seeley, tion compared to NBS. Thus, we have used SPC to identify relevant Crawford, Zhou, Miller, & Greicius, 2009), allowing for a defined triple clusters in each of the contrasts of interest; each cluster is network psychopathological model (Menon, 2011) that is useful in dis- eases that show cognitive and affective symptoms, such as PD. Furthermore, this triple network model has been useful in the study TABLE 1 Clinical and sociodemographic data of the study sample of neurodegenerative conditions that span diverse clinical presentations, Group Participants Controls p-value such as frontotemporal dementia (Chiong et al., 2013) or Alzheimer's disease (Zhou et al., 2010). In PD, dopaminergic dysfunction in the N 35 16 N/A salience network has been linked to cognitive decline (Christopher Age, years 65 ± 9 66.8 ± 7.8 .45 et al., 2015), and altered connectivity between salience and default- Sex, % men 74%, 26/35 50%, 8/16 .06 mode networks has also been associated with cognitive impairment in PD onset, years 7.3 ± 4.5 N/A N/A PD (Peraza et al., 2017) Therefore, this parcellation can be considered Education, years 10 ± 5 10 ± 4.8 .99 suitable for the study of the interaction between neurodegenerative dis- MDS UPDRS III 20 ± 7.1 (ON) N/A N/A orders, large-scale cognitive networks and clinical phenomena. 25 ± 10.2 (OFF) A ROI-to-ROI analysis between all the network components was Hoehn & Yahr 1.9 ± 0.3 (ON) N/A N/A performed from the Z-score connectivity matrices of each participant. 2.2 ± 0.6 (OFF) Both intragroup (PD-ON vs. PD-OFF) and intergroup (PD-ON/OFF LEDD 807 ± 447 N/A N/A vs. Controls)) connectivity patterns were studied and compared. A full PD-CRS score 88 ± 15 N/A N/A description of the cognitive ROI location is provided in Table S3. HADS score (ON) 5 ± 3.3 N/A N/A STAI score (ON) 35 ± 14 N/A N/A Fluctuating participants 14/35 N/A N/A 2.6 | Statistical analyses Abbreviations: HADS, Hospital Anxiety and depression scale; LEDD, Levodopa equivalent daily dose; PD, Parkinson disease; PD-CRS, For the cortical thickness analysis, a vertexwise generalized linear Parkinson's disease cognitive rating scale; STAI, State-trait anxiety model was set to compare both nondemented PD participants with inventory; UPDRS, Unified Parkinson's Disease Rating Scale. 10970193, 2021, 17, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25650 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [20/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 5740 ARACIL-BOLAÑOS ET AL. characterized by its mass—sum of F- or T-squared statistics over all 3.2 | Cortical thickness connections within each cluster—and then compared to a distribution of expected cluster mass values under the null hypothesis using per- In the structural imaging comparison, nondemented PD participants mutation testing (10.000 permutations) and a p-value <.05. Finally, a showed cortical thinning in regions of the right superior frontal cortex multiple comparison correction using a stringent FWE correction with compared with controls (Figure S1). Controls did not show any reduc- a p-value <.05 is applied at the cluster level (unless specified as tions in cortical thickness compared to the PD group. Analyzing the uncorrected). baseline scans of the PD group that completed a 10-year follow-up, PD participant that developed dementia (PDD) did not show any cortical thinning compared to PD participants who did not develop dementia. 3 | RESULTS Furthermore, using the cortical thickness of the right superior frontal gyrus as a covariate of no interest when comparing PD and control 3.1 | Clinical and sociodemographic data groups we found similar functional connectivity results (see Figure S1). A regression analysis between the cortical thickness of this cluster and Thirty-five participants in the mid stages of PD (age 65 ± 9 years; dis- the functional connectivity of the PD group showed a trend associating ease duration 7.3 ± 4.5 years, MDS-UPDRS III 23.5 ± 9) and 16 HCs frontal cortical thickness with fronto-parietal connectivity, but did not (age 66.8 ± 7.8 years) were included. PD participants showed no clini- survive multiple comparison testing (not shown). cally relevant depression (HADS-D 5 ± 3.3); anxiety as measured by the STAI showed that some participants cleared the commonly accepted threshold of 44 points (STAI 35 ± 14 in the ON state) but 3.3 | Functional connectivity differences between none showed HADS-A scores above 11 points. All the participants PD and HC in the ON state had simple, predictable motor fluctuations according to their medical records, and upon evaluation, 14 participants were classified as fluctu- PD patients showed higher connectivity than HCs in two clusters ating according to MDS-UPDRS (Part 4.3 ≥1) (Table 1). No partici- when using a parcellation that included both cognitive and sensorimo- pants featured clinically meaningful dyskinesias. MRI scans were tor ROIs (Figure 1). obtained for all controls and PD participants in the ON state, while The first cluster (mass = 410, pval = .006) connected the sensori- 24 participants had scans acquired both in the ON and OFF states motor elements of the parcellation—including both precentral regions within a time period of 7 days; LEDD remained thus constant and the supplementary motor area—with both frontal and posterior between ON and OFF acquisitions. Sociodemographic and clinical regions of the DMN, including the precuneus, posterior cingulate cor- characteristics of participants with no MRI in the OFF state did not tex, and bilateral angular cortex. Some elements of the SN, including differ significantly from participants with MRI in the ON and OFF the mid cingulate gyrus and the SN regions of the precuneus, were states. Regarding quality control of functional scans, PD-ON, PD-OFF, also involved. These connections were not present in HCs, which fur- and controls had no significant differences in framewise displacement thermore showed no increased connectivity compared to PD patients. (controls 0.082, PD-ON 0.106, PD-OFF 0.108, One-way The second cluster with higher connectivity in nondemented PD ANOVA p = .44). featured cognitive hubs of the SN and the DMN (mass = 379, Twenty-five PD patients were evaluated after 10 years of follow- p = .009). Higher connectivity was found among frontal nodes of both up. Ten participants were lost to follow-up: five participants did not networks—featuring superior and mid frontal cortices both of SN and have enough clinical data to ascertain conversion to dementia, two DMN—, but also spanning antero-posterior connections of the bilat- chose to continue follow-up in other hospitals, two had disabling neu- eral precuneus and posterior cingulate cortex with both insular corti- rological events (a debilitating stroke and an intracranial hemorrhage ces and supramarginal gyrii. Again, there was no increased during a deep brain stimulation procedure) and one died shortly after connectivity for HCs in any of these areas. study completion of non-neurological causes. However, the excluded Finally, this increased connectivity of the frontoparietal nodes in group did not differ significantly in age (68 vs. 64 years in excluded the PD-ON group was also correlated with higher PD-CRS scores in a participants, p = .12), UPDRS (23 vs. 20 points in excluded partici- group of frontoparietal regions, headlined by SN nodes such as the pants, p = .29) or LEDD (743 vs. 832 mg in excluded participants, cingulate, superior frontal and supramarginal gyrii, which showed p = .60). Of the 25 participants that completed follow-up, thirteen higher connectivity with frontal and angular nodes of the DMN (mass (52%) were classified as converters according to CDR. Both groups 182, p = .02; see Figure S2). were comparable in disease duration, educational level, UPDRS-III, and LEDD, but converters at baseline were older (p = .02) and had lower PD-CRS scores (p = .03, Table S1). A subset of these partici- 3.4 | Functional connectivity differences between pants (N = 17, with seven dementia converters) had MRI both in the PD and HC in the OFF state ON and OFF conditions. Both groups were comparable in disease duration, educational level, UPDRS-III, LEDD, and PD-CRS, but con- In the OFF state, PD participants featured higher connectivity than verters were older at baseline (p = .049) (see Table S2). HCs between sensory-motor regions of the cortex and cognitive hubs 10970193, 2021, 17, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25650 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [20/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License ARACIL-BOLAÑOS ET AL. 5741 F I G U R E 1 Differences in functional connectivity between nondemented Parkinson's disease participants and healthy, age-matched controls. The three large-scale cognitive networks are considered on the upper renders (labeled “cognitive cluster”), while the changes in the three cognitive networks plus the sensorimotor network are showcased in the lower renders. On the left part of the image, regions with higher functional connectivity in the Parkinson's disease participants in the ON state are highlighted. Regions with higher connectivity compared to controls in the OFF state are shown in the right part of the image. The color code corresponding to the four large-scale networks is shown in the central ring. CEN, central executive network; DMN, default-mode network; SAL, salience network; SeMot, sensorimotor network; PD, Parkinson's disease of the DMN (mass = 333, p = .008), both containing similar compo- 3.5 | Functional connectivity differences within nents to the ON state. Assessing cognitive regions, PD participants nondemented PD: ON–OFF comparisons also showed higher intrinsic connectivity between SN and DMN com- ponents without medication (mass = 252, pval = .02). This contrast Performing within-participant comparisons in the ON and OFF states, showed a similar structure to the ON state but included fewer poste- PD participants showed a reconfiguration of cognitive networks under rior cortical hubs of the DMN, with posterior cingulate and right medication (Figure 2). precuneus not present in this comparison. No instances of higher con- In the ON state, PD participants featured a cluster of connections nectivity were found in HCs (Figure 1). between SN nodes and predominantly posterior DMN nodes 10970193, 2021, 17, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25650 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [20/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 5742 ARACIL-BOLAÑOS ET AL. F I G U R E 2 Changes within nondemented Parkinson's disease participants according to medication status. On the left, regions which showed higher connectivity in PD participants in the ON state; on the right, regions showing higher connectivity in the OFF state. The color code corresponding to the three large-scale cognitive networks is shown in the central ring. CEN, central executive network; DMN, default-mode network; PD, Parkinson's disease; SAL, salience network (mass = 141.46, p = .04). These connections included the bilateral the DMN (Figure 3). Given the disparity in cognitive scores at baseline, supramarginal gyrii and frontal cortices of the SN and bilateral mid we used the PD-CRS score as a covariate of no interest in the analysis, occipital and angular cortices on the DMN. and still found a cluster of increased connectivity across SN and DMN In the OFF state, the relevant cluster showed enhanced connec- nodes (mass = 126, p = .009 uncorrected) No clusters featuring higher tivity of key hubs of the DMN with other DMN and CEN nodes connectivity in nonconverters were found in this analysis. (mass = 142, p = 0.04). Of note, the bilateral precuneus showed Finally, we performed an exploratory analysis—given the small higher connectivity with occipital, frontal and angular cortices of the sample size (seven participants) in the group of patients who same network, with higher connectivity also present in the right fusi- converted to dementia—within the subset of participants that had form and parahippocampal nodes of the DMN. both long-term follow-up and baseline scans in the ON and OFF con- ditions (Figure 3). The participants that converted to dementia showed, in the ON condition, higher connectivity between SN compo- 3.6 | Functional connectivity differences in nents, mainly within the insular cortex, also featuring the participation converters to dementia of the bilateral supramarginal gyri (mass = 98, p = .008 uncorrected). No differences were found in the OFF condition for any of the Participants that converted to dementia in a 10-year follow-up groups, nor were instances of higher connectivity found in the showed distinct connectivity patterns compared to nonconverters in nonconverter group. their baseline ON scans. Dementia converters featured a cluster of connections that cap- tured the higher connectivity between key SN and DMN hubs 4 | DI SCU SSION (mass = 268, p = .01) This higher connectivity was found specifically between the insular cortices and cingulate gyrus of the SN and the pos- In this work, we have explored how cognitive networks in nonde- terior cingulate cortex of the DMN, together with increased connectiv- mented PD are shaped by dopaminergic treatment, both compared to ity in other relevant regions such as the angular and occipital nodes of age-matched HCs and contrasting patients in the ON and OFF states. 10970193, 2021, 17, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25650 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [20/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License ARACIL-BOLAÑOS ET AL. 5743 F I G U R E 3 Cognitive network changes in Parkinson's disease participants in a 10-year follow-up. On the left, changes in functional connectivity comparing converters to nonconverters using baseline scans in the ON state. On the right, mixed interaction analysis according to both conversion to dementia and medication state. CEN, central executive network; DMN, default-mode network; PD, Parkinson's disease; SAL, salience network We first conducted a cortical thickness study to frame our func- cortex and precentral gyrii, and a wide range of predominantly DMN tional results. We found scarce differences between PD participants nodes. The second was the higher connectivity between SN and and age-matched controls, mainly centered around the right superior DMN hubs in PD participants. These differences were similar overall frontal gyrus. While contrasting with previous studies (Mak in the ON and OFF conditions, although the ON state featured more et al., 2015), a recent longitudinal showed that the rate of cortical widespread interactions between normally anticorrelated hubs, such thinning of PD patients and healthy, age-matched controls is indeed as the insular cortices in the SN and the posterior cingulate/precuneus very similar after age 60 (Gorges et al., 2020). Therefore, structural of the DMN. These differences could be interpreted as a decrease of changes in our cohort would be hardly sufficient to explain the differ- normal anticorrelations between these large-scale cognitive networks ences in resting-state cognitive networks, and using cortical thickness within the PD group, a feature that has been previously reported in both as a covariate of no interest or as a regressor in functional con- PD (Aracil-Bolaños et al., 2019; Peraza et al., 2017). With this knowl- nectivity analyses did not yield any significant results. edge, previous reports of higher frontoparietal connectivity in nonde- On the functional analysis, our first goal was to determine mented PD patients (Gorges et al., 2015)—which waned as patients whether PD patients showed differences in cognitive network con- slid into cognitive decline—, can be adscribed to cognitive networks nectivity compared to HCs, and whether these differences were and cannot be explained merely as an effect of dopaminergic dependent on medication. In broad terms, our results showed that medication. nondemented PD participants feature higher frontoparietal cognitive Our second goal with this study was to ascertain which effect network connectivity, irrespective of medication status. These differ- DRTs exerted over cognitive networks when comparing the ON and ences included two main sources of higher functional connectivity. OFF states in PD participants. As previously mentioned, it is widely The first was the higher connectivity compared to controls found accepted that dopaminergic treatment normalizes functional connec- between sensorimotor regions, such as the supplementary motor tivity in brain networks (Tahmasian et al., 2015). This could have 10970193, 2021, 17, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25650 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [20/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 5744 ARACIL-BOLAÑOS ET AL. implications when interpreting connectivity differences in nonde- mechanism, this network reconfiguration under DRT could constitute mented PD, since the aforementioned higher frontoparietal connec- a vulnerability trait in nondemented PD. tivity could be an artifact introduced by the dopaminergic treatment. This study has some limitations. First, not all participants were In our sample, PD participants in the ON state showed clear increases scanned both in the ON and OFF states, given the intrinsic difficulties in SN-DMN connectivity, whereas in the OFF state, a cluster of pre- of dopamine withdrawal. Second, sample size limits the scope and sta- dominantly DMN connections was more prevalent. Consequently, tistical power of our findings, and we acknowledge that the control DRT was associated with lower posterior-DMN connectivity, at the group was age but not sex-matched. Third, cognitive assessment was same time that frontoparietal cognitive networks showed higher func- not performed conforming to Level-II criteria, though the adminis- tional connectivity. Therefore, the effect of DRT on cognitive net- tered Level-I scale is a Movement Disorders Society endorsed tool works does not seem to merely “normalize” connectivity, especially in (Skorvanek et al., 2018) and has shown very good accuracy compared the systems that have a stronger dopaminergic component, such as to Gold-Standard criteria (de Bobadilla et al., 2013). Strengths of this the SN. Instead, DRT seems to promote network configurations that study include the multimodal approach, using both cortical thickness dampen anticorrelations and reduce within-DMN connectivity The and functional connectivity, the standardized methodology and neuro- link between dopaminergic pathways and the SN has been explored imaging pipeline (Aracil-Bolaños et al., 2019; Whitfield-Gabrieli & in a recent study (McCutcheon et al., 2019), in which higher intrinsic Nieto-Castanon, 2012) and the stringent statistical thresholds applied SN functional connectivity was related to higher dopaminergic syn- throughout the analysis. thesis in the mesocorticolimbic pathway, measured using To sum up, this study shows that dopaminergic therapies shape 18-Fluorodopa. It is likely that DRT plays a similar role in PD patients, the functional connectivity of cognitive networks in nondemented PD enhancing the connectivity of SN nodes with strong patients, enhancing the link between normally-anticorrelated SN and mesocorticolimbic input, such as the anterior insula, and depressing DMN. These differences in functional connectivity appear in regions the functional connectivity of the anticorrelated posterior DMN hubs. with relatively preserved mesocorticolimbic input, such as the insular The extent to which these differences might contribute to cogni- regions of the SN, and merit further investigations regarding their rel- tive decline is presently unknown. Previous studies show that the evance in the progression of cognitive decline in PD. decline in dopamine receptor availability in the anterior insula has been linked to the onset of cognitive decline in PD (Christopher DISCLOS URES et al., 2015). The more immediate explanation would be that the In the last 12 months, the work of Dr. Aracil has been supported by a increases in connectivity observed in SN nodes could constitute a research grant (CM19/00156G) from Instituto de Salud Carlos III compensation mechanism that delays cognitive decline. In this line, a (ISCIII). Jesus Pujol has received salary from IMI-Hospital del Mar, Bar- recent study showed an association of preserved cognition with celona, Spain. Carles Soriano-Mas has received salary from Instituto increased functional connectivity within subnetworks of the cingulate de Salud Carlos III (Miguel Servet grant). Frederic Sampedro is cortex—a key SN node—in PD patients, concurrent with deteriorated supported by a research grant from the Government of Spain (ISCIII). structural covariance in this regions (Zhou et al., 2020). We did indeed Dr. González de Echávarri is employed by Barcelonaβeta Brain find that PD-ON participants showed a positive correlation between Research Center (BBRC) and Pasqual Maragall Foundation and has higher frontoparietal functional connectivity and higher PD-CRS received salary from Hospital de la Santa Creu I Sant Pau. Jaime scores at baseline. However, while hyperconnectivity can be consid- Kulisevsky is employed by Hospital de la Santa Creu I Sant Pau and ered a compensation mechanism (Hillary et al., 2015), studies in differ- has received public research support from CIBERNED and Carlos III ent neurological diseases show that this might not always be the case. Institute, unrestrictive research support from Zambon and TEVA, and In Alzheimer's disease, Apolipoprotein E4 carriers, who have an honoraria for lecturing and/or consulting from Zambon and TEVA. increased genetic risk of neurodegeneration, show increased coher- Dr. Javier Pagonabarraga is employed by Hospital de la Santa Creu I ence of the DMN during working memory tasks (Filippini et al., 2009). Sant Pau, has served on advisory or speakers' boards, and received It has been shown that higher functional connectivity implies increas- honoraria from UCB, Zambon, AbbVie, Italfarmaco, Allergan, Ipsen, ing metabolic costs as measured by 18-FDG uptake (Tomasi, Wang, & and Bial, and received grants from CIBERNED & FIS PI14/02058; Volkow, 2013). In our sample, the analysis of baseline scans in the ON  La Marato Spanish Government grants) and Fundacio  de TV3 state showed that the participants who converted to dementia fea- (20142910). tured higher functional connectivity between SN-DMN nodes while under medication, compared to those who staved off cognitive AUTHOR CONTRIBU TIONS decline. We also analyzed a subset of participants, which had data Ignacio Aracil-Bolaños contributed to conception, organization, and regarding conversion to dementia and both ON and OFF scans. execution of the research project; designed and executed the imaging Although these results should be interpreted with caution and consid- and statistical analyses and wrote the first draft. Frederic Sampedro ered as exploratory, when conversion to dementia and medication contributed to execution of the research project, assisted in statistical state were both factored in, higher connectivity within the SN was and imaging analyses, and provided review and critique of the manu- found to be a feature of PD patients that converted to dementia. script. Jesus Pujol contributed to conception, organization, and execu- These preliminary results suggest that rather than a compensation tion of the research project and provided review and critique of the 10970193, 2021, 17, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25650 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [20/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License ARACIL-BOLAÑOS ET AL. 5745 manuscript. Carles Soriano-Mas contributed to conception, organiza- with dementia in Parkinson's disease. Brain, 142, 2860–2872. https:// tion, and execution of the research project and provided review and doi.org/10.1093/brain/awz192 Fischl, B., & Dale, A. M. (2000). Measuring the thickness of the human  nzalez-de-Echávarri contrib- critique of the manuscript. José María Go cerebral cortex from magnetic resonance images. Proceedings of the uted to statistical and imaging analyses and provided review and cri- National Academy of Sciences, 97, 11050–11055. https://doi.org/10. tique of the manuscript. Jaime Kulisevsky contributed to conception, 1073/pnas.200033797 organization, and execution of the research project and provided González-Redondo, R., García-García, D., Clavero, P., Gasca-Salas, C., García-Eulate, R., Zubieta, J. L., … Rodríguez-Oroz, M. C. (2014). Grey review and critique of the manuscript. 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