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Journal of Parkinson’s Disease 4 (2014) 453–465 DOI 10.3233/JPD-130341 IOS Press

Research Report

Resting State Functional Connectivity is Associated with Cognitive Dysfunction in Non-Demented People with Parkinson’s Disease E.A. Disbrowa,b,∗ , O. Carmichaelc , J. Hec , K.E. Lannid , E.M. Dresslerc,e , L. Zhangf , N. Malhado-Changf and K.A. Sigvardtf a Overton

Brooks VA Medical Center, Shreveport, LA, USA Health Sciences Center, Shreveport, LA, USA c Center for Neuroscience, UC Davis, Davis, CA, USA d Department of Psychology, William Jessup University, Rocklin, CA, USA e VA Northern California Health Care System, Martinez, CA, USA f Department of Neurology, UC Davis, Sacramento, CA, USA b LSU

Abstract. Background: Parkinson’s disease (PD) can result in cognitive impairment. Executive dysfunction often appears early, followed by more widespread deficits later in the course of the disease. Disruption of parallel basal ganglia thalamo-cortical loops that subserve motor and cognitive function has been described in PD. However, there is emerging evidence that the default mode network, a cortical network that is active at rest with reduced activation during task performance, may also play a role in disease related cognitive decline. Objective: To determine the relative contribution of the executive control and default mode networks to parkinsonian executive dysfunction in medicated non-demented patients. Methods: We used BOLD fMRI to measure resting state functional connectivity in the executive control and default mode (DM) networks, and examined switching, processing speed, working memory/attention and motor performance in 14 medicated non-demented PD participants and 20 controls. Results: Performance on neuropsychological measures was similar across groups. Functional connectivity was not different across disease conditions in the executive control network. DMN functional connectivity was decreased in the PD group, specifically between posterior cingulate, medial prefrontal, and inferior parietal nodes. Greater DMN functional connectivity was associated with faster processing speed in the PD group. Conclusions: The continuous relationship between DMN disconnection and executive task performance indicates a possible biological contributor to parkinsonian cognitive deficits. The dynamics of executive control network change may be different than that of the DMN, suggesting less sensitivity to early cognitive deficits. Keywords: Executive control network, default mode network, switching, fMRI

INTRODUCTION ∗ Correspondence to: Elizabeth Disbrow, Ph.D., Department of Neurology, LSU Health Sciences Center, PO Box 33932, Shreveport, LA 71130-3932, USA, Tel.: +318 675 7184; Fax: +318 675 6382; E-mail: [email protected].

Though Parkinson’s disease (PD) has traditionally been defined as a motor disorder, PD can also result in widespread cognitive impairments [1–5], even in

ISSN 1877-7171/14/$27.50 © 2014 – IOS Press and the authors. All rights reserved

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the early stages of the disease [6–9], with estimates of prevalence as high as 55% in newly diagnosed patients [10]. While widespread cognitive decline, including memory, verbal, and visuospatial processing abnormalities can be seen in advanced PD, executive dysfunction and processing speed difficulties are frequently observed in the early stages of disease [11–14]. For example, task switching, or the ability to modify a plan due to evolving environmental conditions, has been shown to be impaired in PD. The basal ganglia dysfunction associated with PD results in impairment of attentional set shifting [3, 9, 15–17] and people with PD show deficits on standard neuropsychological tests with a large task switching component [7, 17–19]. For example Shook and colleagues [17], found increased switch costs in people with PD both for switching of motor response and for switching of cognitive set. Switch costs were reduced with the administration of dopamine replacement therapy. In addition, speed of processing has been shown to be impaired in PD [20] separate from motor disturbance [13]. Using a serial updating tasks, Sawamoto and colleagues (2002) showed increased error rate with increasing task difficulty in mildly cognitively impaired people with PD compared to controls. However, the pathophysiology underlying cognitive deficits in PD is not entirely clear. The motor signs of PD stem from death of dopaminergic neurons in the substantia nigra that disrupt a basal ganglia thalamocortical loop that includes the motor cortex (see [21] for review). In contrast, executive deficits are hypothesized to be tied to the deterioration of a parallel executive control BG-thalamocortical network [22] that includes large portions of the anterior medial basal ganglia, medial dorsal thalamus, and prefrontal cortical areas [23, 24, see 21 for review]. In addition, there is accumulating evidence that the default mode network (DMN) may contribute to cognitive dysfunction in PD as well. The DMN is defined as a network that is active at rest, showing reduced activation during cognitively complex tasks [25, 26]. It includes the posterior cingulate, inferior parietal, and medial prefrontal cortex [25]. Normal cognitive function requires interaction between the DMN and networks like the central executive network during the transition from resting state deactivation to network activation. Furthermore, DMN function is disrupted in neurodegenerative diseases such as Huntington’s [27] and Alzheimer’s [28; for review see 29]. In Alzheimer’s disease, there is evidence that DMN disruption is preclinical, and has been measured in people at risk for AD

[30, 31]. Furthermore, longitudinal studies show connectivity changes in posterior cingulate and precuneus that reflect disease progression [28, see 32 for review]. Thus DMN function may represent a sensitive clinical endpoint for studies of disease onset, progression and treatment in neurodegenerative disease. While less studied in PD, resting state DMN connectivity appears to be reduced [33], and the presence of PD can be reliably identified based on resting state oscillatory fluctuations in the DMN BOLD signal [34]. Furthermore, greater DMN connectivity reduction may be associated with greater memory and visuospatial deficits [35]. However, not all findings agree [36]. Better understanding the relationship between resting state DMN characteristics and cognitive performance has the potential to further define the utility of the DMN as a biological indicator of some of the earliest cognitive dysfunction in PD. To that end, we tested the hypothesis that resting state executive control and default mode network characteristics are relevant to the success of executive and processing speed task performance in PD. We used fMRI to measure resting state functional connectivity between regions involved in both the executive control network and the DMN, and administered a battery of neuropsychological measures of cognitive and motor function in a group of medicated, non-demented PD subjects and matched controls.

MATERIALS AND METHODS Subjects Seventeen people with Parkinson’s disease (8 female) and 22 age-matched control subjects (10 female), were initially recruited from movement disorders clinics at the UC Davis Medical Center and the community, respectively. Subjects with Parkinson’s disease had all received a formal diagnosis by their neurologist and responded to dopamine replacement as confirmed using the UPDRS. Subjects were all right handed and PD subjects all had right side dominant PD. Prior to enrollment, subjects were screened over the phone and were excluded if they had contraindications to MRI, a preexisting neurological condition, a history of substance abuse, stroke, significant head trauma, or brain surgery. Additional exclusion criteria included uncorrected visual impairment, global cognitive deterioration (Mini Mental State Exam score 15), or immediate memory

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impairment (WAIS-III Digit Span scaled score 3) or dyskinetic or freezing periods. Current medication information was obtained and converted to dopamine equivalents [37]. Clinical evaluations were performed by a certified nurse practitioner and neuropsychological tests were administered by trained research assistants. The study was conducted with the approval of the University of California, Davis committee for human research. All participants provided written consent. Neuropsychological testing and evaluation of motor performance Subjects completed the 3-hour assessment battery at the UC Davis Center for Neuroscience in a quiet windowless room. Tests included: Clinical evaluation • The Unified Parkinson’s Disease Rating Scale (UPDRS; [38]). This multi-part scale is commonly used to measure progression of Parkinson’s disease. • Hoehn and Yahr Scale (H&Y; [39]). This scale is commonly used to categorize Parkinson’s disease severity and track progression on a scale from 0 (no signs of disease) to 5 (bedridden). • The Mini Mental State Examination (MMSE; [40]). Subjects were administered this brief, 30-item measure of general cognition to screen for cognitive deterioration. • Geriatric Depression Scale (GDS; [41]). Subjects completed this self-report measure to screen for depressive symptoms. Neuropsychological tests • Test of Everyday Attention: Visual Elevator (TEA; [42]). Subjects were asked to count the floors as an elevator presented visually traveled within a multi-story building. Intermittent upward or downward arrows depicted a change in direction, after which successful performance required a switch in counting (up versus down). Time per switch was calculated based on the number of switches included in correctly completed trials of the test divided by the total seconds for completion of correct trials. • Symbol Digit Modality Test (SDMT; [43]). This test of visuomotor processing speed provides subjects with a key in which geometric symbols are paired with numbers (1–9) and the subject is required to produce

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the numbers associated with a sequence of symbols as quickly as possible. Total scores were calculated based on the number of correct responses generated in 90 seconds. • WAIS-III Digit Span [44]. This measure of auditory attention and working memory required subjects to repeat a sequence of numbers forward (in the order presented) and backward (in the reversed order). Test of motor function Functional Dexterity Test [45]. Subjects were required to turn eight round wooden pegs upside down using one hand, from one hole to the next on a 4 × 8 hole board. The test was performed using each hand. Scores were calculated based on the sum of time for completion with dominant hand, non-dominant hand, and bimanual trials. Functional MRI Image acquisition Imaging was performed on a 3 T Siemens MAGNETOM TrioTim syngo MR system using a 32-channel head coil. Following common practice in resting state fMRI studies to date [e.g., 46, 47], subjects were instructed to keep their eyes closed and move as little as possible during image acquisition. Foam pads and head phones were used to reduce head motion and scanner noise. A T1- weighted MP-RAGE (multiplanar rapidly acquired gradient echo) structural scan was acquired with the following parameters: repetition time (TR), 1900 ms; echo time (TE), 2.88 ms; flip angle, 7 degrees; slices, 208; field of view, 256 mm; resolution 1 × 1 × 1 mm. Functional T2*-weighted blood oxygen level dependent (BOLD) images were acquired using an echo planar imaging sequence with the following parameters: TR, 2 s; TE, 29 ms; flip angle, 85 degrees; acquisition matrix, (64 × 64 × 64); field of view, 217 mm; slices 33; resolution, 3.4 mm isotropic. fMRI preprocessing Temporal and spatial processing of the fMRI data were performed in Statistical Parametric Mapping (SPM5, http://www.fil.ion.ucl.ac.uk/spm). The first four time points were discarded to eliminate the nonequilibrium effects of magnetization [48]. Images for the remaining time points were corrected for slice timing and aligned to the first time point image to correct for head motion. The magnitude of the alignment parameters were then analyzed to identify time points for which excessively large magnitude head motion may have led to artifacts in the BOLD signal [49]. The

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Table 1 Demographic data (Mean (SD)). Groups are matched except for Geriatric Depression Scale (GDS) score

N Age (years) Years of education MMSE score ∗ GDS score Years of disease H & Y scale score Dopamine replacement (mg)

PD participants

Age-matched controls

14 [7F] 65.86 (5.33) 16.71 (2.76) 28.93 [28–30] 5.00 (4.42) 5.00 (3.16) 2.21 (0.47) 641.96 (549.14)

20 [8F] 66.70 (4.67) 17.75 (2.59) 28.60 [25–30] 1.55 (1.28) – – –

MMSE = Mini Mental State Examination, H&Y = Hoehn and Yahr Scale. *p < 0.05.

number of time points in each fMRI time series with excessive head motion, defined as translation in any direction greater than 1.5 mm and/or rotation about any axis greater than 1.5º, and time series with greater than 50 such time points were excluded from subsequent analysis. Among the 39 fMRI scans acquired for this study, 5 were excluded due to excessive head motion. The remaining 34 fMRI scans (14 PD and 20 control; Table 1, Fig. 1) were then normalized to the SPM5 EPI template and smoothed with a Gaussian kernel (6 mm FWHM). Data were then de-trended and filtered using Resting-State fMRI Data Analysis Toolkit V1.3 (REST1.3, http://restfmri.net/forum/?q=rest). Following prior work [50, 51], time series at each voxel were band-pass filtered to preserve frequency components between 0.01 and 0.08 Hz. Time courses of each of the estimated head motion parameters were regressed out of the resulting time series. In addition, three mean time series were estimated by taking the average time series for all voxels labeled as white matter, cerebrospinal fluid and the entire brain respectively. These three mean time series were regressed out of each voxel’s time series [52, 53].

Fig. 1. Graph showing the distribution of H&Y scale scores for the PD group.

rior cingulate cortex (PCC, MNI coordinates: 0, −51, 33); medial prefrontal cortex (MPF: −3, 63, 24); left and right inferior parietal cortices (LIP: −45, −69, 39 and RIP: 54 −66 33); and left and right ventral temporal cortex (LT: −63, −27, −18, and RT: 63, −6, −27). These regions are broadly agreed upon to be DMN constituents [29, 56]. For both the executive control and default mode networks, the average time series within a 4 mm radius of each seed was calculated, and Pearson correlations between all possible pairs of such average time series were calculated. The resulting correlation coefficients were used as summary measures of functional connectivity between pairs of executive control or DMN nodes in subsequent analysis. Measures of statistical significance

Functional connectivity measurement Functional connectivity within the executive network was measured using the nodes described by Seeley and colleagues [54] (dorsolateral PFC right MNI coordinates: 46, 36, 18; left: −42, 34, 20; lateral parietal: right: 46, −54, 42; left: −42, −50, 48; frontal operculum: −58, 14, 12; and dorsal medial PFC: 8, 28, 46). The DMN was defined by a set of seed voxels provided by a prior study of relationships between DMN connectivity and cognitive function in healthy elders ([55]; Fig. 2). That study identified DMN nodes within each of the following anatomical compartments: poste-

Multivariate ANCOVAs were run (␣ threshold = 0.05, two tailed) to identify differences between groups for performance on behavioral measures and connectivity, for the executive and default mode networks. Covariates were GDS and age. We also identified connectivity associated with performance on behavioral measures for the Parkinson’s disease group. We created a composite connectivity score for the executive control and DMN networks by adding connectivity values from ROI pairs for each network. We then used these scores as dependent variables in 2 separate stepwise linear regression

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Fig. 2. Locations for the executive control and DMN networks. For the executive control network (black circles) DLPFC = dorsolateral prefrontal cortex, DMPFC = dorsomedial prefrontal cortex, FO = frontoinsula, R & L P = right and left lateral parietal respectively. For the DMN (white circles), PCC = posterior cingulate cortex, RIP = right inferior parietal cortex, LIP = left inferior parietal cortex, MPF = medial prefrontal cortex, RT = right temporal cortex, LT = left temporal cortex.

analyses per group (PD and control). Independent variables included TEA, SDMT, GDS, UPDRS, dopamine equivalent dose data age and disease duration for the PD regressions. Disease related variables (UPDRS, dopamine equivalent dose and disease duration) were not included in the control regressions. These values were entered as possible regressors in a stepwise fashion (probability-of-F-to-enter ≤0.01; probability–of-F-to-remove ≥0.10). Finally, we calculated Pearson’s correlations between connectivity (executive control and DM network composite scores) and cognitive (TEA, SDMT, Digit Span) and motor (FDT) measures to examine the specificity of the relationship between connectivity and cognitive and motor behavior. The ANCOVA, linear regression and correlation analyses were done using SPSS (SPSS Inc., Chicago, IL).

RESULTS Behavioral data Data from 14 PD and 20 control subjects were included in the analysis (Table 1). Groups were matched for age, years of education, and MMSE score. There was a significant difference between groups for depression (GDS; (4, 29)=13.24, p = 0.036). There were no significant differences in performance between non-demented PD subjects and controls for the cognitive evaluation which included the TEA, SDMT and Digit Span. Subjects with Parkinson’s disease had significantly longer completion times than controls for the measure of complex motor performance (FDT; F(4, 29) = 3.18, p < 0.039). Results for neuropsychological and motor tests are shown in Table 2.

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Table 2 Neuropsychological and motor test scores. Mean (SD) scores for the test battery used to evaluate cognitive and motor function TEA (sec.) SDMT (# correct) Digit Span ∗ FDT total (sec.)

PD participants

Controls

4.75 (1.58) 51.5 (8.10) 17.79 (3.83) 201.67 (83.76)

4.23 (1.18) 55.0 (8.25) 17.75 (4.47) 145.73 (53.71)

TEA = Test of Everyday Attention visual elevator task, SDMT = Symbol Digit Modality Test, FDT = Functional Dexterity Test, *p < 0.05. Table 3 Executive control network connectivity values DLPFC Right Lat Parietal Right DLPFC Left FO Left DLPFC Left Lat Parietal Left DLPFC Right DLPFC Left DMPFC DLPFC Left Lat Parietal Right Lat Parietal Left Lat Parietal Left FO Left DMPFC Lat Parietal Left DMPFC FO Left DMPFC DLPFC Right DMPFC Lat Parietal Right

PD participants

Controls

0.47 (0.39) 0.38 (0.26) 0.72 (0.22) 0.68 (0.32) 0.38 (0.29) 0.70 (0.30) 0.35 (0.27) 0.43 (0.21) 0.20 (0.26) 0.49 (0.33) 0.61 (0.22)

0.68 (0.26) 0.36 (0.35) 0.68 (0.24) 0.78 (0.27) 0.46 (0.30) 0.72 (0.28) 0.33 (0.35) 0.46 (0.51) 0.35 (0.34) 0.64 (0.39) 0.73 (0.37)

DLPFC = Dorso-lateral prefrontal cortex, DMPFC = Dorsomedial prefrontal cortex, FO = frotoinsula, Lat Parietal = Lateral Parietal. No significant differences between PD and control groups.

Group differences in functional connectivity For the executive control network, functional connectivity analysis was done between dorsomedial and dorsolateral prefrontal cortex, lateral parietal cortex and the frontal operculum for the right and left hemispheres. A multivariate ANCOVA revealed that there were no significant differences between the PD and control groups for connectivity values for these regions. Connectivity values for the executive control network are shown in Table 3. Functional connectivity analyses of regions in the DMN were done between the posterior cingulate cortex (PCC), medial prefrontal cortex (MPF), left and right inferior parietal cortex (LIP, RIP), and left and right ventral temporal cortex (LT and RT). Connectivity differences between the Parkinson’s population and their age-matched counterparts were found for LIP-RIP (F(4, 29) = 3.38, p = 0.022); MPF-LIP (F(4,29) = 3.22, p = 0.027); PCC-LIP (F(4,29) = 3.39, p = 0.022); and PCC-MPF (F(4,29) = 3.29, p = 0.024). In all cases, the connectivity values were higher in the control group (Fig. 3). DMN connectivity values are shown in Table 4.

Fig. 3. Regions of interest and comparison of functional connectivity across groups. A) Averaged axial MR images illustrating LIP (top left) and RIP (bottom left) ROI connectivity (indicated by white line). Box plot on the right represents mean (black and white interface) and standard deviation of connectivity values. B) Similarly, MPF (top left) and LIP (bottom left) ROI connectivity are indicated by white line on axial views with box plots of connectivity values. PCC (C, top left) and LIP (C, bottom left) as well as PCC and MPF (D, top and bottom left respectively) ROI connectivity values are also shown on the right. Conventions as in previous figure. *p < 0.05.

E.A. Disbrow et al. / Cognitive Dysfunction in PD Table 4 DMN Connectivity values LIP-LT ∗ LIP-RIP LT-RT ∗ MPF-LIP MPF-LT MPF-RIP MPF-RT ∗ PCC-LIP PCC-LT ∗ PCC-MPF PCC-RIP PCC-RT RIP-RT

PD participants

Controls

0.50 (0.21) 0.50 (0.3) 0.37 (0.29) 0.24 (0.24) 0.39 (0.30) 0.45 (0.27) 0.14 (0.42) 0.51 (0.30) 0.55 (0.20) 0.26 (0.33) 0.37 (0.24) 0.32 (0.27) 0.18 (0.41)

0.52 (0.25) 0.64 (0.15) 0.29 (0.34) 0.50 (0.24) 0.40 (0.34) 0.50 (0.24) 0.31 (0.34) 0.62 (0.17) 0.54 (0.24) 0.47 (0.20) 0.54 (0.21) 0.36 (0.24) 0.29 (0.33)

PCC = Posterior Cingulate Cortex, RIP = Right Inferior Parietal Cortex, LIP = Left Inferior Parietal Cortex, MPF = Medial Prefrontal Cortex, RT = Right Temporal Cortex, LT = Left Temporal Cortex. *p < 0.05 for multivariate ANCOVA.

Connectivity and neuropsychological and motor performance Stepwise linear regression analysis was performed to determine the extent to which functional connectivity in the executive control and default mode networks was associated with executive function in PD. We created a composite connectivity score for the executive control network by adding all connectivity values from all ROI pairs together (no pairs were different across groups). For the DMN composite score we added together the 4 DMN connectivity pairs that showed differences between PD and control groups (LIP-RIP, MPF-LIP, PCC-LIP and PCC-MPF). Cognitive measures (TEA, SDMT and Digit Span) as well as possible confounding variables (GDS, UPDRS score, dopamine equivalent dose, age and disease duration) were entered as possible regressors in the two analyses, with composite scores as the dependent variable for both regressions. For the PD group executive function network composite score, none of the independent variables (switching, processing speed, memory/attention or possible confounding variables) were significant regressors. For the DMN, both executive function (TEA) and processing speed (SDMT) were correlated with composite connectivity score (Table 5). However, only processing speed was a significant regressor (β = 0.674, t(11) = 3.164, p = .008). Scatterplots are shown in Fig. 4. In addition, the correlation analysis showed no relationship between DMN connectivity composite and memory/attention or motor performance (Table 5). Thus the relationship between connectivity and cognitive and motor function was

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restricted to DMN connectivity and the measure of processing speed. For the control group executive function network composite score, again none of the independent variables (switching, processing speed, memory/attention or possible confounding variables) were significant regressors. For the DMN in the control group, the measure of depression (GDS) was significantly correlated with the composite connectivity score β = −0.464, t(18) = −2.221, p < 0.0001. Scatterplots are shown in Fig. 4.

DISCUSSION Our two key findings are first, that among nondemented people with Parkinson’s disease, functional connectivity within the DMN is compromised while at rest, even in the absence of clinically-significant cognitive deficits. In contrast, we found no differences in functional connectivity across groups in the executive control network. Second, among PD subjects, greater DMN functional connectivity at rest was continuously associated with greater performance, specifically on the processing speed task. Greater connectivity in DMN regions (LIP-RIP, MPF-LIP, PCC-LIP, and PCCMPF), was associated with faster speed of processing even after correction for age, depression and dopamine replacement therapy. The measures of working memory/attention and of complex motor performance were not correlated with executive control or default mode network connectivity. Our results confirm prior reports of intrinsic (i.e., not provoked by task burden) DMN disruptions in PD [57, 35]. For example, Tinaz and colleagues [33] used fMRI to examine activation during a sequencing task in a group of 13 medicated non-demented PD patients and 13 controls. They showed that the PD group failed to recruit DMN regions based on a comparison of the active task condition (picture sequencing) to the control condition. As in the current study, task performance was not significantly different across groups. In addition, correlation analysis of the time course data revealed no differences across groups for activity in dorsolateral prefrontal cortex, a key node of the executive control network. Thus the pattern of results showing normal task performance and executive network connectivity in addition to disrupted DMN function in non-demented medicated PD patients is in line with the current findings. However, not all previous results agree. Krajcovicova and colleagues [36] evaluated the DMN in a

∗ Correlation

Digit Span

Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed) Pearson Correlation Sig. (2-tailed)

0.567∗ 0.035 −0.021 0.943 −0.300 0.297

Age −0.068 0.817 −0.093 0.753 0.136 0.642

−0.265 0.360 −0.313 0.275 0.327 0.253 0.344 0.228 0.176 0.547 −0.074 0.801 −0.146 0.618 0.752∗∗ 0.002 0.446 0.110

Disease UPDRS Total DA Equivalent Duration (years) Score Dose

is significant at the 0.05 level (2-tailed). ∗∗ Correlation is significant at the 0.01 level (2-tailed).

TEA Time/Switch

SDMT

GDS

DA Equivalent Dose

UPDRS Total Score

Disease Duration

Age

DMN Composite

EF Composite

EF DMN Composite Composite

Table 5 Correlation matrix for connectivity, demographic and behavioral data

−0.214 0.462 −0.327 0.254 0.088 0.765 0.502 0.067 −0.143 0.625 0.352 0.217

GDS −0.163 0.577 −0.553∗ 0.040 0.042 0.886 0.315 0.273 0.188 0.521 0.276 0.340 0.101 0.732

SDMT −0.505 0.066 −0.654∗ 0.011 0.207 0.477 0.236 0.417 0.503 0.067 0.257 0.375 0.278 0.336 0.578∗ 0.030

−0.007 0.982 0.122 0.678 0.345 0.227 −0.145 0.622 0.329 0.250 −0.227 0.434 −0.223 0.444 −0.542∗ 0.045 −0.265 0.360

TEA Digit Span Time/Switch

−0.509 0.063 −0.473 0.088 −0.075 0.800 0.571∗ 0.033 0.239 0.411 0.415 0.140 0.281 0.331 0.693∗∗ 0.006 0.517 0.058 −0.436 0.120

FDT

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Fig. 4. Scatterplots showing the relationship between connectivity values in the executive control network (bottom row) and default mode network (DMN, top row) with the processing speed (SDMT) and executive function measures (TEA) in individual subjects. Increased processing speed and decreased switch time was associated with increased connectivity.

group of non-demented non-depressed PD subjects on dopamine replacement therapy compared to an age and gender matched control group. They analyzed DMN fMRI data in three ways, and found no differences across groups using independent components analysis of the resting-state data. They examined BOLD signal decreases during the performance of a cognitive task, or using seed functional connectivity similar to the technique used in the current study. One possible explanation for the discrepancy is related to sample homogeneity: our PD subjects were all right handed with right side dominant PD, reducing noise and boosting statistical power. Side of disease onset has been previously linked to performance on cognitive tasks in PD [58, 59]. DMN pathophysiology It is not clear why the pathophysiology of PD is linked to intrinsic DMN connectivity deficits, how-

ever studies of Alzheimer’s disease may provide some insight. In Alzheimer’s disease, pathology has been shown to preferentially accumulate in the default network even before symptoms emerge [60]. Buckner and colleagues [30] have proposed a “metabolism hypothesis,” whereby the continuous activity in the DMN creates vulnerability to a metabolism-dependent cascade that is associated with the formation of, for example, toxic forms of the β amyloid protein (for review see [29]). Recent work suggests that ␤ amyloid deposition begins many years prior to the onset of cognitive impairment, resulting in a long prodromal phase. In fact, amyloid deposition in the DMN has been shown to be associated with cognitive impairment, specifically of memory [61] and decreased functional connectivity in non-demented adults [62]. The deposition of fibrillar forms of ␤-amyloid protein is a major pathological feature of Alzheimer’s disease, and ␤-amyloid protein has been implicated in dementia in PD as well [e.g. 63], suggesting a

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possible similarity in the mechanism underlying cognitive decline in Alzheimer’s and Parkinson’s diseases. It has been suggested that memory may be impaired in Alzheimer’s disease because the interaction between the DMN and a memory-related network that includes the hippocampal formation is disrupted. For example, the two networks interact during normal episodic memory (e.g., [30, 64, 65]. It is possible that, as in Alzheimer’s disease, ␤-amyloid protein accumulation disrupts the interaction between the executive and default mode networks. In fact, there is some evidence that the interaction between the DMN and a central executive network is disrupted during the transition from resting state deactivation to network activation during task performance [66].

ing. For example, Spraker and colleagues 72] examined de novo PD subjects using a paced grip task. Performance was the same across PD and control groups. However, the PD group showed decreased BOLD signal over the course of the task in the nuclei of the basal ganglia, and other regions compared to control for the high grip rate (maximal switching) condition. Thus abnormalities in brain activation were observed prior to behavioral deficits. In addition, neuropathological studies suggest that as many as 70–80% of cells that project from the substantia nigra in the midbrain to the neostriatum may be lost prior to the emergence of clinical symptoms [73–75]. Our findings support the idea that such brain structural changes prior to behavioral impairment may be detectable through functional neuroimaging.

DMN as a marker of cognitive impairment in PD Anatomy of the DMN Previous work has demonstrated a relationship between DMN connectivity and such cognitive functions as memory and visuospatial processing [35]. Furthermore, DMN connectivity is correlated with processing speed in older adults [47] and TBI patients [67]. In addition, white matter integrity is correlated with processing speed in older healthy adults [68, 69] and in MS [70] and white matter structure correlates with default mode connectivity [67]. Prefronto-striatal connectivity has also been linked to set shifting in young healthy adults [66]. We found that decreased DMN connectivity was associated with decreased processing speed and increased switch time. This relationship is consistent with past research, showing a similar relationship between processing speed and anterior DMN where decreased connectivity was associated with a trend toward increased processing speed [47]. This relationship was only evident in the healthy elderly group, the young group showed no such relationship. Similarly Sharp and colleagues [67] showed that TBI patients with the highest functional connectivity had the least cognitive impairment for example in information processing speed. Interestingly, the TBI patient group also showed greater deactivation in a task versus rest contrast in the ventromedial prefrontal cortex These findings support the idea that greater functional connectivity within the default mode network is associated with more efficient network function [71]. We extend these findings by noting that DMN connectivity is relevant to cognitive function in PD even when performance is not significantly impaired. The observed brain dysfunction was pre-clinical, that is, evident in the absence of clinically significant cognitive deficits, and prior reports are consistent with this find-

The anatomical pattern of cortical connectivity that we found to be associated with cognitive function is consistent with previous work on the organization and function of the cortex. For example, our inferior parietal DMN seed was located in Brodmann’s area 39, a region thought to play a role in maintaining attentive control on the current task [76]. Present research suggests that MPF (BA 10) is involved in retrieval and executive functions [e.g. 77, 78], such as switching (e.g. [79]). Furthermore, both PCC (BA 31) and MPF have been identified as part of an error processing network [80, 81]. Thus previous work supports the hypothesized role of the DMN in attentional processes associated with executive function as evaluated in the current study. The impact of dopamine on DMN function DMN abnormalities were present in medicated PD subjects, supporting the idea that dopamine replacement therapy does not eradicate pathophysiology in PD. Dopamine has been shown to modulate activity in the DMN. For example, deactivation was reduced in DMN during set-shifting tasks in healthy young subjects after transient dopamine depletion [66]. These findings are consistent with work in PD [81], indicating that, during a facial emotion recognition task, PD subjects receiving placebo failed to show DMN deactivation compared to a control group. Administration of an acute dose of dopamine restored the normal pattern of de-activation. Similarly, Esposito and colleagues [82] found that the administration of levodopa to drug na¨ıve PD patients resulted in increased functional

E.A. Disbrow et al. / Cognitive Dysfunction in PD

connectivity in the sensorimotor network, specifically in the supplementary motor area. Thus there is evidence that dopamine improves DMN function and connectivity, though not all reports agree. NaganoSaito and colleagues [83] found no difference in PD or control subjects in MPF or PCC connectivity before versus after the administration of the dopamine receptor agonist apomorphine. Thus our findings, that DMN connectivity is reduced in PD subjects on dopamine replacement therapy may represent dysfunction over and above the effects of dopamine replacement, making it relevant to the bulk of the PD population.

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ACKNOWLEDGMENTS [16]

This work was supported by grants from the National Institute of Neurological Disorders and Stroke (R01NS064040) and from the Department of Veterans Affairs Office of Research and Development, Rehabilitation R&D Service (1I01RX000181) to ED. CONFLICT OF INTEREST

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The authors have no conflict of interest to report. [19]

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