Attention shifting in Parkinson's disease: an analysis of behavioral and cortical responses.

Neuropsychology 2014, Vol. 28, No. 6, 929 –944

© 2014 American Psychological Association 0894-4105/14/$12.00 http://dx.doi.org/10.1037/neu0000099

Attention Shifting in Parkinson’s Disease: An Analysis of Behavioral and Cortical Responses Nabi Rustamov, Rea Rodriguez-Raecke, Lydia Timm, Deepashri Agrawal, Dirk Dressler, Christoph Schrader, Pawel Tacik, Florian Wegner, Reinhard Dengler, Matthias Wittfoth, and Bruno Kopp

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Hannover Medical School Objective: The study was designed to examine persistent (input selection) versus transient (input shifting) mechanisms of attention control in Parkinson’s disease (PD). Method: The study identifies behavioral and neural markers of selective control and shifting control using a novel combination of a flanker task with an attentional set-shifting task, and it compares patients with PD with matched controls. Eventrelated brain potentials (ERPs) were recorded, and analyses focused on frontally distributed N2 waves, parietally distributed P3 waves, and error-related negativities (Ne/ERN). Results: Controls showed robust shifting costs (prolonged response times), but patients with PD did not show evidence for comparable shifting costs. Patients with PD made more errors than controls when required to shift between attentional sets, but also when they had to initially maintain an attentional set. At the neural level it was found that contrary to controls, patients with PD did not display any N2 and P3 augmentations on shift trials. Patients with PD further did not display any error-related activity or posterror N2 augmentation. Conclusions: Our results reveal that intact selective control and disrupted shifting control are dissociable in patients with PD, but additional work is required to dissect the proportionate effects of disease and treatment on shifting control in PD. Our ERP-based approach opens a new window onto an understanding of motor and cognitive flexibility that seems to be associated with the dopaminergic innervation of cortico-striatal loops. Keywords: Parkinson’s disease, attention, N2, P3, Ne/ERN Supplemental materials: http://dx.doi.org/10.1037/neu0000099.supp

tion device, developed to resolve conflicts over access to limited cognitive or motor resources (Gurney, Frank, & Redgrave, 2001; Mink, 1996; Redgrave, Vautrelle, & Reynolds, 2011). In early stages of disease progression, PD is associated with a loss of dopaminergic projections from the substantia nigra to the dorsal striatum, a major input nucleus of the BG (Graybiel, 2008; Haber, 2003). This has led to the hypothesis that early stage PD is related to disrupted selective control (Aron, 2011; Seiss & Praamstra, 2004). The efficiency of stimulus selection by attention can be studied with congruency tasks (Rustamov et al., 2013). On those tasks, participants have to make a speeded response to one stimulus or stimulus feature, while ignoring another distracting stimulus/feature. On any given trial, the distractor is either associated with the same response as the target (congruent trial) or with a different response (incongruent trial). Responses are typically slower and more error-prone on incongruent than on congruent trials. This congruency effect emerges because incongruent distractors trigger processes of response preparation that interfere with the intended response (Kopp, Rist, & Mattler, 1996). It is therefore no surprise that congruency tasks served repeatedly as a tool for probing selective control in PD. The emerging literature, however, provides contradictory results that do not unambiguously support the selective control hypothesis. A number of congruency studies found that patients with PD show impaired selective control (Dujardin, Degreef, Rogelet, Defebvre, & Destee, 1999; Praamstra, Plat, Meyer, & Horstink, 1999; Praamstra, Stegeman, Cools, &

The basal ganglia (BG) have long been considered to play an important role in the control of movement and the pathophysiology of movement disorders, such as Parkinson’s disease (PD). Research over the past decades has considerably broadened this view, indicating that the BG participate in multiple, largely segregated cortico-striato-thalamo-cortical reentrant loops involving motor and cognitive functions (Alexander, DeLong, & Strick, 1986; DeLong & Wichmann, 2007; Haber, 2003; Middleton & Strick, 2000). An overarching theoretical framework of BG function in health and disease is to consider them as a general purpose selec-

This article was published Online First July 28, 2014. Nabi Rustamov, Rea Rodriguez-Raecke, Lydia Timm, Deepashri Agrawal, Dirk Dressler, Christoph Schrader, Pawel Tacik, Florian Wegner, Reinhard Dengler, Matthias Wittfoth, and Bruno Kopp, Department of Neurology, Hannover Medical School. Deepashri Agrawal is now at MRC Cognition and Brain Science Unit, Cambridge, United Kingdom. Matthias Wittfoth is now at Department of Clinical Psychology and Sexual Medicine, Clinic for Psychiatry, Social Psychiatry, and Psychotherapy, Hannover Medical School. The research reported here was supported by grants to Reinhard Dengler, Matthias Wittfoth, and Bruno Kopp from the Petermax-Müller-Stiftung, Hannover, Germany, and from the ParkinsonFonds, Berlin, Germany. Correspondence concerning this article should be addressed to Bruno Kopp, Hannover Medical School, Department of Neurology, CarlNeuberg-Str. 1, 30625 Hannover, Germany. E-mail: [email protected] 929


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Horstink, 1998; Wylie, Stout, & Bashore, 2005; Wylie et al., 2009), but an equal number of congruency studies did not report such disturbances in patients with PD (Cagigas, Filoteo, Stricker, Rilling, & Friedrich, 2007; Falkenstein, Willemssen, Hohnsbein, & Hielscher, 2006; Lee, Wild, Hollnagel, & Grafman, 1999; Rustamov et al., 2013). A more consistent pattern of findings suggests that PD is linked with changes in the temporal dynamics of selective control. Specifically, congruency effects are subject to sequential modulation: They are smaller following incongruent trials than following congruent ones (Egner, 2007; Gratton, Coles, & Donchin, 1992). We and others have shown that the sequential modulation of congruency effects is strongly attenuated in patients with PD (Bonnin, Houeto, Gil, & Bouquet, 2010; Cagigas et al., 2007; Fielding, Georgiou-Karistianis, Bradshaw, Millist, & White, 2005; Praamstra & Plat, 2001; Rustamov et al., 2013; but see Wylie, Ridderinkhof, Bashore, & van den Wildenberg, 2010). Based on these findings, we explore here the possibility that patients with PD are characterized by disturbed dynamics of selective control rather than by impaired selective control per se. Hereafter, we refer to this hypothesis as the shifting control hypothesis, implying that PD is associated with a disruption of the temporal dynamics of selective control. Shifting represents a core component of executive functions (Diamond, 2013; Dirnberger & Jahanshahi, 2013; Hedden & Gabrieli, 2010; Miyake et al., 2000; Robbins, 2007). Many brain imaging studies have observed shifting-related fronto-parietal neural activity, including an inferior region in the parietal lobe (Badre & Wagner, 2006; Yeung, Nystrom, Aronson, & Cohen, 2006), the presupplementary motor area extending into the dorsal anterior cingulate cortex (ACC), and regions of the middle frontal gyrus (Badre & Wagner, 2006; Yeung et al., 2006). The BG, as a major component of fronto-striatal circuits, display coordinated activation with prefrontal and parietal regions during shifting tasks (Bissonette, Powell, & Roesch, 2013; van Schouwenburg, den Ouden, & Cools, 2010; van Schouwenburg, O’Shea, Mars, Rushworth, & Cools, 2012). The importance of the BG for shifting is indicated by disruption of shifting following dopaminergic depletion, striatal lesions, and in PD (Cools, 2006; Cools et al., 2009; Cools & Robbins, 2004; Hayes, Davidson, Keele, & Rafal, 1998; Marklund et al., 2009; Monchi et al., 2004; Monchi, Petrides, Mejia-Constain & Strafella, 2007; Nagano-Saito et al., 2008; Owen, 2004; Ravizza & Ivry, 2001; Sawada et al., 2012; Slabosz et al., 2006; Yehene, Meiran, & Soroker, 2008). Work by Monchi and colleagues (2007) provides a paradigmatic example for the disruption of shifting control in PD. They used functional magnetic resonance imaging in a set shifting task that was closely modeled to the Wisconsin Card Sorting Test (Berg, 1948; Grant & Berg, 1948) and compared early phase patients with PD with matched controls. The main result was that shifting-related differences in cortical (orbito-frontal, medial-frontal, lateral-frontal, parietal), as well as BG activation were seen between groups such that patients with PD showed diminished transient cortico-striatal activation for shifting control. Shifting should not be considered as a unitary construct (Kopp, Tabeling, Moschner, & Wessel, 2006). There seem to exist a number of dissociable shifting-related systems corresponding to different domains and time scales. Among the identifiable domains are shifting from one stimulus—response mapping to another,

directing attention toward different information sources (i.e., different stimuli or stimulus features), and directing attention shifts within versus across stimulus dimensions (i.e., intradimensional vs. extradimensional set shifting; Owen, 2004; Robbins, 2007). Furthermore, the previously mentioned sequential modulation of selective control represents shifting at the shortest time scale. Typical shifting studies, such as for example Monchi et al. (2007), examine shifting control on a more extended time scale. Here, participants perform a discrete task on each trial (e.g., to maintain the attentional focus on a particular source of information). The task changes on some trials (shift trials), but it does not change on a series of other consecutive trials (the repetition trials that constitute a task run). Performance on shift trials is compared with that on repetition trials, and the basic phenomenon is that there are highly robust shifting costs in both response time (reaction time [RT]) and error rates (Kiesel et al., 2010). Shifting costs may have multiple origins: Shift trials are more surprising than repetition trials (Kopp & Lange, 2013), they are associated with contextual novelty (Barceló, Escera, Corral, & Periáñez, 2006), and they signal temporarily enhanced demands for selective control (Kopp et al., 1996). In addition, there are benefits related to task repetition, such as lower levels of surprise, higher levels of contextual familiarity, and decreased demands for selective control because of increasingly automatic task skills (Chein & Schneider, 2012). Figure 1 depicts a synopsis of the logic and key elements of our study. The upper panels of the figure show the case of normal shifting control. Figure 1a illustrates selective control, which may be typical for repeatedly practiced, automatized tasks (Chein & Schneider, 2012). Limited parts of the sensory information (input A) are persistently gated for access to the output systems (which constitute limited resources) according to the rules of the task at hand. Figure 1b shows shifting control with a comparatively more transient profile; that is, the shutting of gate A and the opening of gate B, to occur on demand. The lower panels of the figure show the case of disrupted shifting control. Figure 1c shows that selective control on repeatedly practiced, automatized tasks may be maintained at normal levels. Figure 1d illustrates disrupted shifting control, which may itself be attributable to (a) a missing demand for shifting or (b) a failure to implement the demanded shift. Shifting control thus represents a transient event that changes the input gating for an updated access to limited cognitive or motor resources (see Braver & Cohen, 2000; Chatham, Frank, & Badre, 2014; D’Ardenne et al., 2012; Frank, Loughry, & O’Reilly, 2001; Frank & O’Reilly, 2006; Gruber, Dayan, Gutkin, & Solla, 2006; McNab & Klingberg, 2008; O’Reilly, 2006, for similar conceptualizations). It can be gleaned from inspection of Figure 1 that one of the consequences of disrupted shifting control lies in more persistent, that is, perseverative, appearance of automatized task performance. To put the shifting control hypothesis to test in patients with PD, we created a new task that basically combined three elements: (1) it consisted of a classical congruency task, (2) it corresponded to a shifting task, and (3) it invited the recording of event-related brain potentials. On the flanker task (Eriksen & Eriksen, 1974), a (central) target stimulus is flanked, in immediate vicinity, either by response-congruent or by response-incongruent distractor stimuli. The flanker task is associated with strong and reliable congruency effects, which are related to less than optimal selective control and can be decomposed into facilitative effects that are exerted by


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Figure 1. Cartoon of the selective control hypothesis and the shifting control hypothesis of basal ganglia (BG) function and dysfunction. There are two aspects of control over the flow of information between multiple input channels (arbitrarily labeled A and B) and limited output resources on congruency tasks. Selective control is equivalent to persistent positioning of the “gates” as a function of repetitive experience on the task, whereas shifting control is the (transient) adjustment of gate positions, in the service of cognitive demands (input updating). Here, we hypothesize that the BG support dynamic transient updating, but not persistent selective control, over access to the output system. Upper panels: A cartoon of BG function: (a) Gates A and B are shown in persistent positions with Gate A opened and Gate B closed (equaling a biased access of input A to the output system). (b) The case of dynamic shifting, corresponding to an updating, that is, a repositioning, of both gates (i.e., closing Gate A and opening Gate B), as defined by contextual demands. Lower panels: A cartoon of BG dysfunction: (c) Selective control operates at normal levels, provided sufficient repetitive experience on the task. (d) Dynamic shifting (i.e., input updating by the closing of Gate A and the opening of Gate B) is disrupted, provoking perseverative access of input A to the output system.

congruent flankers and interfering effects by incongruent flankers (Kopp et al., 1996). The flanker task was extended to a shifting task by requesting subjects to adjust the spatial spotlight of attention in one of the following ways: Figure 2a shows that the attention spotlight can be formed either like a “Mexican hat” (i.e., an “on-center, off-surround” attention field; Hopf et al., 2006; Müller, Mollenhauer, Rösler, & Kleinschmidt, 2005) or like a doughnut (i.e., an “off-center, on-surround” attention field; Chen, Marshall, Weidner, & Fink, 2009; Müller & Hübner, 2002), depending on whether central or peripheral information is attended or ignored. If one asks subjects to shift back and forth between these two attentional sets, there exist two potential shifting operations: (1) “zooming in” to a central, “Mexican hat”-like attention field, (2) “zooming out” to a peripheral, doughnut-like attention field. Figure 2b shows how shifts between these two types of attentional sets can be used to create a shifting paradigm in which either central or peripheral stimuli of a flanker task must be attended to across runs of trials of unpredictable length. Termination of those trial runs was signaled by “incorrect response”-feedback stimuli, which indicated, on incongruent trials, that the wrong sensory information had been gated toward the response systems, and consequently that an attention shift was necessary on the upcoming shift trial. Thus, to be able to decide whether a “zooming in”-shift or a “zooming out”-shift was required on any particular shift trial, subjects had to keep in mind which part of the visual field (central

or peripheral stimuli, respectively) they had been attending to on the current trial. In contrast, a particular attentional set could be maintained as long as subjects received “correct response”feedback stimuli; that is, across task runs of variable length. We recorded event-related potentials (ERPs), focusing our analysis on the N2 wave, which peaks around 250 to 300 ms after the onset of the eliciting stimulus. The N2 is usually evoked on incongruent trials of the flanker task (Gehring, Gratton, Coles, & Donchin, 1992; Kopp et al., 1996; Yeung, Botvinick, & Cohen, 2004). Its appearance on incongruent trials cannot be accounted for by the sensory mismatch between targets and distractors (Folstein & van Petten, 2008). The N2 wave achieves maximum amplitudes at fronto-central electrodes, and neural activity in the ACC contributes to the scalp-recorded N2 (Nieuwenhuis, Yeung, van den Wildenberg, & Ridderinkhof, 2003; van Veen & Carter, 2002). We recently found normal N2 amplitudes on incongruent trials of the flanker task in patients with PD; however, the sequential modulation of the N2 wave (which is smaller following incongruent trials than following congruent ones in controls; Clayson & Larson, 2011a,b; Clayson & Larson, 2012; Forster, Carter, Cohen, & Cho, 2011; Freitas, Banai, & Clark, 2009; Wendt, Heldmann, Münte, & Kluwe, 2007) was absent in patients with PD (Rustamov et al., 2013). In sum, the scalp-recorded N2 wave reflects mechanisms of selective control, is sensitive to dynamic modulations of selective control, and medial-frontal activity contributes to this ERP wave.


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Figure 2. Illustration of the attentional shifting task. (a) The left side shows an OFF-center (dark gray), ON-surround (light gray) doughnut-like attentional field. The right side shows an ON-center (light gray), OFF-surround (dark gray) “Mexican hat”-like attentional field. Arrows indicate potential set-shifts. The leftpointing arrow equals a “zooming out” attention shift; the right-pointing arrow equals a “zooming in” attention shift. Light gray: To-be-attended spatial region. Dark gray: To-be-ignored spatial region. (b) The attentional shifting task consisted of trial runs of variable length during which a particular attentional set had to be maintained. Attentional shifts were required when feedbacks informed about a performance error (FB: “wrong’”), such as for example on trial n1. In the depicted example, this “wrong”-feedback indicates that a “zooming out”-shift was required because the attentional set on trial n1 equaled an ON-center, OFF-surround field. Feedback stimuli on subsequent trials (eventually) signaled successful performance throughout trial runs of variable length. In the depicted example, another “wrong”-feedback on trial n2 indicated that a further attentional shift was required. This attentional shift concerned a “zooming in”-shift because the attentional set on trial n2 equaled an OFF-center, ON-surround field. FB denotes feedback.



Beyond that, medial-frontal activity contributes to another scalp-recorded ERP wave that is associated with the occurrence of error responses, variably termed error negativity (Ne; Falkenstein, Hohnsbein, Hoormann, & Blanke, 1991) or error-related negativity (ERN; Gehring, Goss, Coles, Meyer, & Donchin, 1993). The Ne achieves maximum amplitudes about 50 –100 ms after erroneous responses, and it is considered to constitute a neural substrate of internal mechanisms for performance monitoring (Ullsperger, Danielmeier, & Jocham, 2014; Yeung et al., 2004). The Ne has a fronto-central scalp distribution, and the ACC contributes to the scalp-recorded Ne (Debener, Siegel, Fiehler, von Cramon, & Engel, 2005; Hoffmann & Falkenstein, 2010; Ridderinkhof, Ullsperger, Crone, & Nieuwenhuis, 2004; Wessel, 2012); it has also been conjectured that striatal dopamine projections contribute to the Ne wave (Holroyd & Coles, 2002). Earlier studies repeatedly found reduced Ne amplitudes in patients with PD (Beste, Dziobek, Hielscher, Willemssen, & Falkenstein, 2009; Falkenstein et al., 2001; Ito & Kitagawa, 2006; Stemmer, Segalowitz, Dywan, Panisset, & Melmed, 2007; Willemssen, Müller, Schwarz, Falkenstein, & Beste, 2009; Willemssen, Müller, Schwarz, Hohnsbein, & Falkenstein, 2008; but see Holroyd, Praamstra, Plat, & Coles, 2002). The present investigation aims to contribute to the literature by addressing the following issues: First, it provides a test of the shifting control hypothesis according to which PD is associated with a disruption of shifting-related dynamics of selective control, along the lines of reasoning that were presented above. Second, it examines neural substrates of dynamic modulations of selective control (i.e., the N2 ERP wave). Based on the shifting control hypothesis and our earlier finding (Rustamov et al., 2013), we predicted the absence of shifting-related modulations of the N2 wave in patients with PD. Third, it explores a potential role of internal performance monitoring for disrupted shifting control. Based on earlier findings (mentioned earlier), we expected to find reduced Ne waves in patients with PD.

Materials and Methods Participants Forty individuals (20 patients with PD, 20 healthy controls) participated in the experiment. All patients received a clinical diagnosis of idiopathic PD by experienced clinical neurologists. Control participants had no known neurological or psychiatric disorders and had not been prescribed any psychiatric or neurological medications. Table 1 summarizes demographic and, when applicable, clinical characteristics of the participants. Neither group demonstrated signs of elevated depression (as assessed by the Beck Depression scale; Beck, Ward, Mendelson, Mock, & Erbaugh, 1961) apathy (as assessed by the Apathy scale; Marin, Biedrzycki, & Firinciogullari, 1991), or impulsiveness (as assessed by the Total BIS-11 scale; Patton, Stanford, & Barratt, 1995). All patients with PD were under their normal medication regime at the time of testing. Three patients were taking levodopa as their only form of therapy. Eleven patients were taking the combination of levodopa plus benserazide, two patients received levodopa plus carbidopa, and two patients took levodopa plus carbidopa plus entacapone. The remaining two patients were on different combinations of dopamine agonists (pramipexol, rotigotin), monoamine oxidase inhibitors (rasagilin), and N-Methyl-D-aspartate receptor

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Table 1 Demographical and Clinical Information About the Participants of the Study M (SD)

Age (y) Male/female SF-36 PCS MCS BDI Apathy scalea Total BIS-11 UPDRS part 3 Hoehn/Yahr scaleb Disease duration (y) NMS-PD PANDA Total LEDD (mg)

PD ON (N ⫽ 20)

HC (N ⫽ 20)

59.75 (9.83) 11/9

56.05 (4.03) 10/10

40.78 (10.50) 51.06 (8.70) 7.35 (5.20) 25.15 (6.32) 44.20 (10.99) 15.85 (6.71) 2.10 (0.90) 5.65 (4.64) 9.60 (6.39) 21.85 (3.13) 551.98 (359.72)

45.93 (9.05) 52.89 (7.56) 5.80 (4.02) 25.05 (4.30) 40.35 (7.51) NA NA NA NA NA NA

Note. PD ON ⫽ patients with Parkinson’s disease on medication; HC⫽ healthy controls; SF-36 ⫽ 36-Item Short-Form Health Survey (Ware & Sherbourne, 1992); PCS ⫽ SF-36-Physical Component Summary; MCS ⫽ SF-36-Mental Component Summary; BDI ⫽ Beck Depression Inventory (Beck, Ward, Mendelson, Mock, & Erbaugh, 1961); BIS-11 ⫽ Barratt Impulsiveness Scale-11 (Patton, Stanford, & Barratt, 1995); UPDRS ⫽ Unified Parkinson’s Disease Rating Scale (Fahn & Elton, 1987); NA ⫽ not applicable; NMS-PD ⫽ Nonmotor Symptoms Questionnaire for Parkinson’s Disease (Chaudhuri et al., 2006); PANDA ⫽ Parkinson Neuropsychometric Dementia Assessment (Kalbe et al., 2008); LEDD ⫽ Levodopa Equivalent Daily Dose (Herzog, Volkmann, & Krack, 2003). a Apathy scale (Marin, Biedrzycki, & Firinciogullari, 1991). b Hoehn/ Yahr scale (Hoehn & Yahr, 1967).

antagonists (amantadine). Average disease duration amounted to around 68 months, and average disease staging was 2 (range ⫽ 1–3) on the Hoehn/Yahr scale (Hoehn & Yahr, 1967). The motor subscale of the Unified Parkinson’s disease Rating Scale (UPDRS; Fahn & Elton, 1987) was used to measure the level of motor impairment on the day of testing (mean score ⫽ 15.9, range ⫽ 9 –29). The Parkinson Neuropsychometric Dementia Assessment (PANDA; Kalbe et al., 2008) was used to assess possible dementia in patients with PD. They achieved a mean score of 21.9 (SD ⫽ 3.1), which lies within the normal range (18⫹). All individual patients surpassed the cutoff score of 14 (range ⫽ 17–27), indicating that none of the patients with PD was demented. This research was approved by the Ethics Committee of the Medical School Hannover. All participants provided informed consent in accordance with the Declaration of Helsinki.

Materials and Procedure Stimuli were presented in white against a black background on a computer screen at a distance of 60 cm from the participant. Each stimulus array subtended a visual angle of 5° ⫻ 1° and consisted of five horizontally arranged arrows, – – – – – (congruent right-sided response), • • – • • (incongruent right-sided response), • • • • • (congruent left-sided response), – – • – – (incongruent left-sided response) peripheral stimuli associated with the same response. The participants were instructed to respond either (1) to the central arrow or (2) to the peripheral arrows by pressing a spatially compatible key


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on the computer mouse (left or right) with their left or right index finger, respectively. They were told to respond as quickly as possible while avoiding errors. A distinction was made between congruent (i.e., central and peripheral stimuli associated with the same response; e.g., – – – – –) and incongruent (i.e., central and peripheral stimuli associated with different responses; e.g., • • – • •) stimulus arrays. Central and peripheral stimuli were presented simultaneously. The entire stimulus array remained on the screen until the participant’s response was registered (maximum ⫽ 1.000 ms). The intertrial interval amounted to 800 ms (feedback-stimulus interval). Participants received a block of 62 practice trials before entering the experimental phase, which contained 158 congruent and 158 incongruent trials. The presentation order of the congruency of the stimulus arrays was pseudorandomized. Participants were informed that task runs would continue for a variable number of trials. They were further instructed that they would receive visual feedback (1.000-ms duration) immediately following their responses (“correct,” “wrong”). Under particular circumstances, these feedback stimuli would signal that a task run had ended. Specifically, negative feedback on incongruent trials gave the information that an attentional set-shift was required because they had responded to the incorrect part of the stimulus on the current trial. There was no additional external cue (such as background color and the like) that informed participants about an attentional set-shift. All task runs ended on incongruent trials. Task runs consisted of 8 to 13 trials (the very last task run amounted to 14 trials); each of these run lengths occurred five times in the experimental phase. Overall, 30 set-shift trials were included in the experimental phase. Participants were compensated with payment (25 €).

Analysis of Behavioral Data Behavioral task performance was quantified in two ways: First, the median of the RTs on correctly completed trials was computed for each individual participant. These median individual correct RTs were subjected to statistical analysis. Second, the accuracy of the behavioral responses was computed for each individual participant. The resulting error percentages were subjected to statistical analysis. To identify behavioral correlates of set-shifting, RTs and error rates on incongruent trials were analyzed across the initial eight trials of task runs (eight trials equaled the shortest task run). The restriction to incongruent trials is a consequence of the fact that set-compatible responses can only be identified safely on incongruent trials (on congruent trials, responses can be correct despite the reliance on the wrong attentional set). Specifically, RTs and error rates on shift (1st) trials were compared with those evoked on all remaining trials (2nd to 8th), ERPs elicited on 2nd and 3rd trials were compared with those on 4th to 8th trials, and finally ERPs evoked on 4th to 6th to those evoked on the 7th and 8th trials (i.e., by Helmert contrasts). An additional analysis targeted behavioral adjustments, which usually follow the occurrence of an error in choice-response tasks. The term posterror slowing describes the prolonged RTs on trials subsequent to an error compared with RTs on trials following correct trials. We therefore compared RTs on incongruent correct

trials, which followed an erroneous incongruent trial with those which followed a correct incongruent trial.

Electrophysiological Recording and Data Analysis Continuous electroencephalogram (EEG) was recorded by means of a 32-channel BrainAmp amplifier (Brain Products, Gilching, Germany), using active electrodes (Brain Products, Gilching, Germany), which were mounted on an actiCAP (Brain Products, Gilching, Germany) in an International 10 –20 System montage. Electrode impedance was kept below 10 k⍀. All EEG electrodes were referenced to FCz. Ocular artifacts were monitored by means of electrodes that were positioned at the suborbital ridge (vertical electrooculogram, vEOG) and at the external ocular canthus (horizontal electrooculogram, hEOG) of the right eye. The EEG and EOG channels were amplified with a band-pass of 0.01 to 100 Hz, and they were digitized at 500 Hz). EEG data were analyzed in MATLAB (Mathworks, Nattick, MA) environment using EEGLAB v10.2.2.4b (Delorme & Makeig, 2004). The data were rereferenced to common average off-line, down-sampled to 250 Hz and filtered offline using a FIR filter with the lower edge of the frequency pass band at 1 Hz and a higher edge of the frequency pass band at 30 Hz. Data were screened for extreme values exceeding ⫺200 to ⫹ 200 mV, as well as for infrequent and unstereotyped artifacts using the in-built probability function (pop_jointprob) with a threshold of 3 SD (Debener, Hine, Bleeck, & Eyles, 2008). For further artifact attenuation, Infomax independent component analysis was applied. Artifacts were identified using the EEGLAB-Runica function, and independent components found to reflect blinks, lateral eye movements, muscle-related and cardiac artifacts were removed from the data in patients with PD and controls. Following independentcomponent-analysis-based artifact attenuation, the EEG recordings were segmented into stimulus-locked epochs from ⫺100 ms to 800 ms relative to stimulus onset, with a baseline from ⫺100 to 0 ms. Response-locked ERPs were time-locked to the response, starting 500 ms before the response and ending 600 ms thereafter. Baseline correction was applied from ⫺500 ms to ⫺400 ms. Only correctly completed trials were included in the analyses, unless otherwise stated. To identify neuronal correlates of setshifting, stimulus-locked ERPs on incongruent trials were analyzed across the initial eight trials of task runs (eight trials equaled the shortest task run). The restriction to incongruent trials is a consequence of two factors: (a) Erroneous set use can only be identified on incongruent trials, and (b) the N2 component was only elicited on incongruent trials. Specifically, ERPs on shift (1st) trials were compared with those evoked on all remaining trials (2nd to 8th), ERPs elicited on 2nd and 3rd trials were compared with those on 4th to 8th trials, and finally ERPs evoked on 4th to 6th to those evoked on the 7th and 8th trials (i.e., by Helmert contrasts). N2 amplitude was measured as mean amplitudes in a ⫺40 to ⫹40 ms interval around individual peak N2 latencies, which were defined as the maximum negative amplitude in a 200to 350-ms poststimulus interval at electrode Fz. Likewise, P3 amplitude was measured as mean amplitudes in a ⫺40 to ⫹40 ms interval around individual peak P3 latencies, which were defined as the maximum positive amplitude in a 400- to 600-ms poststimulus interval at electrode Pz.



To identify neuronal correlates of performance monitoring, response-locked ERPs were analyzed separately for correct and erroneous responses. Specifically, ERPs on correct incongruent trials were compared with those evoked on incongruent trials, to examine the effect of stimulus-congruency on response-locked ERPs. Furthermore, ERPs on correct (incongruent) trials were compared with those evoked on erroneous (incongruent) trial to examine error-related neuronal activity. Nc and Ne amplitude, respectively, were measured as mean amplitudes in a ⫺40to ⫹40-ms interval around individual peak Nc and Ne latencies, which were defined as the maximum negative amplitude in a 10to 90-ms postresponse interval at electrode Fz. An additional analysis targeted neuronal adjustments which might follow the occurrence of an error in choice-response tasks. Specifically, we compared N2 amplitude (as defined above) on incongruent correct trials, which followed an erroneous incongruent trial (N2e) with those which followed a correct incongruent trial (N2c). We report the mean, standard deviation, and range of amplitudes for the ERP components of interest (all stimulus-locked N2 waves, response-locked negativities) separately for groups. Because signal-to-noise ratio is a common problem in ERP research, we also report the mean, standard deviation, and range for the number of trials used for each of these ERP components separately for groups to ensure that signal-to-noise ratio did not differ between groups (see Online Supplementary Material, Table 1).

Results Attentional Set-Shifting Response times. Figure 3 shows mean response times (left panel) and error rates (right panel) on incongruent trials across four stages of the task runs from the two groups of subjects, separately for the two zooming conditions. These stages are: 1st (i.e., shift), 2nd and 3rd, 4th to 6th, 7th and 8th trial. RTs were examined in an analysis of variance (ANOVA) with Between-Subjects Factor Group (HCs, patients with PD) ⫻ Within-Subjects Factor Stage (1) . . . , (4) ⫻

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Within-Subjects Factor Zooming (in, out). Patients with PD were generally slower than HCs, F(1, 38) ⫽ 6.95, p ⬍ .05, ␩p2 ⫽ 0.155. The interaction Group ⫻ Stage was significant, F(3, 114) ⫽ 3.84, p ⬍ .05, ␩p2 ⫽ 0.092, indicating an overall difference between groups with regard to RTs as a function of stage. The first Group ⫻ Stage Helmert contrast compared RTs on shift trials with those on all remaining trials in control subjects and in patients with PD, F(1, 38) ⫽ 9.78, p ⬍ .05, ␩p2 ⫽ 0.205, indicating that RT shift costs differed significantly between groups (HCs ⬎ patients with PD). The second and third Helmert contrast compared the remaining stages with one another: stage (2) versus the remaining trials, F(1, 38) ⫽ 0.04, p ⫽ .84, ␩p2 ⫽ 0.001, and stage (3) versus stage (4), F(1, 38) ⫽ 0.33, p ⫽ .57, ␩p2 ⫽ 0.009, indicating that groups did not differ with regard to the RT gradients across these later stages of task runs. Error rates. In the Group ⫻ Stage ⫻ Zooming ANOVA, group, F(1, 38) ⫽ 20.03, p ⬍ .05, ␩p2 ⫽ 0.345 and the interaction Group ⫻ Stage proved significant, F(3, 114) ⫽ 13.73, p ⬍ .05, ␩p2 ⫽ 0.265, indicating that patients with PD were more error prone across the early stages of task runs. The first Group ⫻ Stage Helmert contrast (shift trials vs. all other trials) revealed that shift costs on error rates did not differ significantly between groups, F(1, 38) ⫽ 4.02, p ⫽ .052, ␩p2 ⫽ 0.096. However, the second, stage (2) versus the remaining trials, F(1, 38) ⫽ 27.93, p ⬍ .05, ␩p2 ⫽ 0.424, and third, stage (3) versus stage (4), F(1, 38) ⫽ 17.11, p ⬍ .05, ␩p2 ⫽ 0.310, comparisons showed that error rates gradually declined across stages (2) to (4) in patients with PD, whereas HCs achieved a stable level of erroneous responses on stage (2). N2. Figure 4 shows grand-average stimulus-locked ERP activity at midline electrodes for incongruent trials, separately for groups across the four stages of task runs. Inspection of these waveforms revealed a negativity on shift trials (labeled N2s), which achieved its maximum around 300-ms poststimulus at electrode Fz in HCs. However, similar shift-related N2s could not be detected in patients with PD. The interaction Group ⫻ Stage proved significant, F(3, 114) ⫽ 7.70, p ⬍ .05, ␩p2 ⫽ 0.168, in the Group ⫻ Stage ANOVA. The first group ⫻ stage Helmert contrast, comparing shift trials with all remaining trials

Figure 3. Reaction times (RTs; in ms) and error rates (as a percentage) in controls (HC; square shapes) and in patients (PD; diamond shapes), as a function of stage across task runs, separately for “zooming in” (solid lines) and “zooming out” (dashed lines) conditions. Error bars represent ⫾ 1 SE.


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Figure 4. Grand-average stimulus-locked event-related potential (ERP) activity at midline electrodes in controls (HC; left panels) and in patients (PD; right panels), as a function of stage across task runs. The N2 and P3 components of the ERP waveform are of particular importance. Note that HCs show enhanced N2 and P3 amplitudes on shift trials; these enhancements are labeled N2s and P3s, respectively. No comparable amplitude modulations were observed in patients with PD. The colored maps show N2 (260 –340 ms; medio-frontal maximum) and P3 (460 –540 ms; parietal maximum) scalp topographies. The color version of this figure appears in the online article only.

in HCs and patients with PD, revealed that N2s amplitudes were associated with group, F(1, 38) ⫽ 9.89, p ⬍ .05, ␩p2 ⫽ 0.207. The second and third Helmert contrast compared the remaining stages with one another: stage (2) versus the remaining trials, F(1, 38) ⫽ 0.04, p ⫽ .84, ␩p2 ⫽ 0.001, and stage (3) versus stage (4), F(1, 38) ⫽ 1.87, p ⫽ .18, ␩p2 ⫽ 0.047, indicating that N2 amplitudes on nonshift trials did not differ between groups. Thus, no N2 amplification (N2s) was triggered on shift trials in patients with PD, whereas the N2 on nonshift trials had normal amplitude in patients with PD. P3. Further inspection of the waveforms depicted in Figure 4 reveals that shift trials also triggered a parietal positivity that has its peak around 450-ms poststimulus in HCs (labeled P3s). The P3s could not be detected in patients with PD. The Group ⫻ Stage interaction proved significant, F(3, 114) ⫽ 8.79, p ⬍ .05, ␩p2 ⫽ 0.188, in the Group ⫻ Stage ANOVA at electrode Pz. The first Group ⫻ Stage Helmert contrast, comparing shift trials with all remaining trials in HCs and patients with PD, revealed that P3s amplitudes were associated with group, F(1, 38) ⫽ 6.85, p ⬍ .05, ␩p2 ⫽ 0.153. The second and third Helmert contrast compared the remaining stages with one another: stage (2) versus the remaining trials, F(1, 38) ⫽ 2.07, p ⫽

.16, ␩p2 ⫽ 0.052, and stage (3) versus stage (4), F(1, 38) ⫽ 1.09, p ⫽ .30, ␩p2 ⫽ 0.028, indicating that P3 amplitudes on nonshift trials did not differ between groups. Thus, no P3 amplification (P3s) was triggered on shift trials in patients with PD, whereas the P3 on nonshift trials had normal amplitude in patients with PD.

Performance Monitoring Figure 5 shows grand-average response-locked ERP activity at midline electrodes for congruent and incongruent trials, separately for group. There are three waveforms: (a) those triggered on congruent correct trials, (b) those triggered on incongruent correct trials, and (c) those triggered on incongruent erroneous trials. Inspection of these waveforms revealed two effects: (a) a congruency-related frontal negativity (Nc, I ⬎ Nc, C in both groups), and (b) an error-related negativity (Ne, I ⬎ Nc, I in HCs, but not in patients with PD). These observations were corroborated in a Group ⫻ Trial Type ANOVA at electrode Fz. The interaction Group ⫻ Trial Type (congruent, correct; incongruent, correct; incongruent, erroneous) was significant, F(2, 76) ⫽ 9.89, p ⬍ .05, ␩p2 ⫽ 0.206, indicating that groups differed with regard to the waveform amplitudes. The first Group ⫻ Trial Type



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Figure 5. Grand-average response-locked event-related potential (ERP) activity at midline electrodes in controls (HC; left panels) and in patients (PD; right panels), as a function of trial type (blue lines, “Nc, C”: congruent, correct; green lines, “Nc, I”: incongruent, correct; red lines, “Ne, I”: incongruent, erroneous). Patients with PD show a robust effect of congruency (i.e., Nc, I ⬎ Nc, C), but no evidence for an error-related modulation (i.e., Ne, I ⫽ Nc, I), whereas HCs show a nice ordinal relationship (i.e., Ne, I ⬎ Nc, I ⬎ Nc, C). The colored maps show the typical fronto-central Ne and Nc (10 –90 ms; medio-frontal maximum). The color version of this figure appears in the online article only.

Helmert contrast compared Nc, C with the average of Nc, I and Ne, I in HCs and patients with PD, F(1, 38) ⫽ 1.84, p ⫽ .67, ␩p2 ⫽ 0.005, indicating that the congruency-related effects on the response-locked frontal negativity did not differ between groups. The second Helmert contrast compared Nc, I with Ne, I trials, F(1, 38) ⫽ 12.66, p ⬍ .05, ␩p2 ⫽ 0.250, indicating that error-related effects on the responselocked frontal negativity differed between groups. Thus, a reliable Ne was elicited in HCs, whereas patients with PD did not show ERP evidence for error-related neuronal activity.

Posterror Adjustments Response times. Figure 6 shows mean RTs on incongruent trials, separately for groups and for postcorrect (icIc) and posterror (ieIc) trials. The Group ⫻ Previous Trial interaction proved significant, F(1, 38) ⫽ 5.10, p ⬍ .05, ␩p2 ⫽ 0.118, in a Group ⫻ Previous Trial (correct, erroneous) ANOVA, indicating that groups differed with regard to posterror slowing. Separate ANOVAs for HCs, F(1, 19) ⫽ 12.16, p ⬍ .05, ␩p2 ⫽ 0.390, and patients with PD, F(1, 19) ⫽

0.01, p ⫽ .91, ␩p2 ⫽ 0.001, showed reliable posterror slowing in HCs, whereas this effect was absent in patients with PD. N2. Figure 7 shows grand-average stimulus-locked ERP activity at midline electrodes for incongruent trials on postcorrect (icIc) and posterror (ieIc) trials, separately for groups. The N2 amplitudes were analyzed by a Group ⫻ Previous Trial (correct, erroneous) ANOVA. The interaction Group ⫻ Previous Trial proved significant, F(1, 38) ⫽ 4.42, p ⬍ .05, ␩p2 ⫽ 0.104, indicating that the groups differed with regard to this posterror modulation of the N2 (labeled N2e). Separate ANOVAs for HCs, F(1, 19) ⫽ 7.51, p ⬍ .05, ␩p2 ⫽ 0.283, and patients with PD, F(1, 19) ⫽ 0.17, p ⫽ .68, ␩p2 ⫽ 0.009, showed evidence for the presence of a reliable N2e in HCs, whereas the N2e was unverifiable in patients with PD.

Discussion This study explored behavioral and neural correlates of stimulus selection by attention in patients with PD and matched controls, and it revealed intact selective control and disrupted shifting


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Figure 6. Reaction times (RTs; in ms) in controls (HC; square shapes) and in patients (PD; diamond shapes) on correctly responded, incongruent trials (Ic) as a function of previous trial correctness (ic,ie). HCs show posterror slowing, that is, RTs (icIC) ⬍ RTs (ieIc), but patients with PD lack any visible evidence for posterror slowing, that is, RTs (icIC) ⫽ RTs (ieIc). Error bars represent ⫾ 1 SE.

control in early stage medicated patients with PD. Subjects shifted back and forth between central, “Mexican hat”-like and peripheral, doughnut-like attention sets in a flanker task, guided by feedback on response accuracy. There was reliable evidence for behavioral shifting costs in controls (i.e., prolonged RTs and enhanced error rates on shift trials), but patients with PD did not display shifting costs in RTs. Patients with PD committed more errors than controls, and this error proneness of patients with PD was pronounced on the initial three trials of task runs. On final trials of task runs, however, controls and patients with PD showed nearly identical, low levels of error rates. In controls, there were two separable shifting-related ERP components which could be easily distinguished by their sign and topography: A shifting-related frontocentrally distributed negative-going ERP wave (N2s) and a parietally distributed positive-going ERP wave (P3s). These two shifting-related ERP waves represent amplifications of ERP waves, on shift trials, that are commonly observed on (incongruent) nonshift trials of the flanker task, that is, the fronto-central N2 and the parietal P3. The ERP waves that were obtained from patients with PD comprised normal N2 and P3 waves on nonshift trials. It is important that these ERP waves were completely unaffected by shifting demands in patients with PD; that is, they did not show any evidence for a transient amplification on shift trials (N2s, P3s). In similar vein, whereas patients with PD presented normal response-locked ERP waves on all correct response trials, no evidence for the generation of an additional negativity that was related to erroneous responding (Ne) could be discerned in patients with PD, suggesting deficient internal performance monitoring in patients with PD. Finally, behavioral and neural (N2e) indices revealed the absence of posterror adjustments in patients

with patients with PD. Implications of these findings are discussed later. It is widely accepted that cognitive impairments in patients with PD are characterized by attentional disturbances (Miller, Neargarder, Risi, & Cronin-Golomb, 2013). Spatial attention, for example, allows to analyze specific parts of the visual field and to select behaviorally relevant stimuli. In our flanker task, subjects shifted back and forth between central (“Mexican hat”-like) and peripheral (doughnut-like) spatially selective attention (Chen et al., 2009; Hopf et al., 2006; Müller et al., 2005; Müller & Hübner, 2002). Here, we found in patients with PD a clear dissociation between unimpaired selective control on final trials of task runs (in terms of response accuracy as well as N2 and P3 amplitudes) and disrupted shifting control on shift trials (in terms of response accuracy as well as N2s and P3s amplitudes). The conclusion from this dissociation is that the presence of PD does not affect spatial selectivity per se, but rather the ability to shift the attentional focus back and forth, supporting the shifting control hypothesis. Such a specific disruption of attentional shifting is not an isolated finding, but attentional shifting ability has been widely studied in PD (Bowen, Kamienny, Burns, & Yahr, 1975; Brown & Marsden, 1988; Gotham, Brown, & Marsden, 1988; Hayes et al., 1998; Owen, 2004; Ravizza & Ivry, 2001; Slabosz et al., 2006; Taylor, Saint-Cyr, & Lang, 1986). Two cognitively distinct processes may contribute to disrupted shifting control in PD: perseveration and learned irrelevance (Owen, Roberts, Hodges, & Robbins, 1993; Slabosz et al., 2006; see also Figure 1). Perseveration refers to an inability to disengage attention from the previously relevant information. In contrast, learned irrelevance refers to an inability to attend to previously irrelevant information (Filoteo, Rilling, & Strayer, 2002; Mackintosh, 1973). These two processes yield distinguishable predictions with regard to their effect on shifting-related behavior: First, learned irrelevance in the absence of perseveration should induce RT prolongation, but not error proneness, because the main difficulty is to overcome irrelevance. Second, perseveration in the absence of learned irrelevance should lead to error proneness, but not necessarily to RT prolongation, because attention is continuously paid to meanwhile irrelevant information. Patients with PD did not show shifting costs in RTs; they displayed high error proneness on the initial three trials of task runs, and these unprecedented error rates decreased only slowly to normal levels on the final trials. This pattern of behavioral findings therefore suggests that perseveration contributed to disrupted shifting control in patients with PD (see also Fallon, Williams-Gray, Barker, Owen, & Hampshire, 2013; Hughes, Altena, Barker, & Rowe, 2013; Moustafa, Sherman, & Frank, 2008). Shifting costs were completely restricted to shift trials in controls, implying that these subjects were able to accomplish attentional shifting within a single trial. This holds true for all indices of shifting costs, both behavioral (RTs, error rates) and neural (N2s, P3s). Taken together, these data suggest that additional transient neural recruitment in medial-frontal areas allowed for this efficient transition between attentional sets, as evidenced by the N2 to N2s amplification that occurred on shift trials. The N2 has been established as a neural signature of selective control (Folstein & Van Petten, 2008; Kopp et al., 1996) so that the shifting-related N2 to N2s amplification implies additional recruitment of medialfrontal areas in the service of more intense selective control.



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Figure 7. Grand-average stimulus-locked event-related potential (ERP) activity at midline electrodes on correctly responded, incongruent trials (Ic) as a function of previous trial correctness (ic,ie). HCs show posterror N2 enhancement, that is, N2e ⬎ N2c, but patients with PD lack any visible evidence for posterror N2 enhancement, that is, N2e ⫽ N2c. The colored maps show N2 (260 –340 ms; medio-frontal maximum) scalp topographies. The color version of this figure appears in the online article only.

Apparently, the response that was compatible with the previously relevant information interfered to a greater extent with the intended response on shift trials than on nonshift trials, as evidenced by higher error rates and by amplified medial-frontal activation. Comparably less can be said about the functional significance of the shifting-related P3 to P3s amplification because the P3 wave on congruency tasks has not been extensively studied. Patients with PD did not seem to be able to accomplish the requested attentional shifting within a single trial. Specifically, they tended toward a multitude of perseveration errors on trials at the beginning of task runs. Attentional shifting in patients with PD thus evolved slowly, across a series of trials, possibly driven by reinforcement from correct responses and/or by punishment from incorrect responses (see Frank, Seeberger, & O’Reilly, 2004, for an analysis of feedback-driven learning in patients with PD). It was only after repeated practice on the task that patients with PD were successful in establishing normal levels of spatial selectivity. Task repetition may be related to the development of task routine (Hikosaka & Isoda, 2010; Isoda & Hikosaka, 2011) and eventually to automaticity (Ashby, Turner, & Horvitz, 2010; Chein & Schneider, 2012). Thus, patients with PD were able to select behaviorally relevant stimuli from specific parts of the visual field,

provided that some degree of routine and automaticity had been achieved (see also Cameron, Watanabe, Pari, & Munoz, 2010). However, patients with PD clearly showed disrupted shifting control on shift trials. Neither behavioral (RTs, error rates) nor neural (N2s, P3s) shifting costs were observed in these subjects. Thus, no shifting-related N2 to N2s amplification on shift trials—that would indicate additional recruitment of medial-frontal areas in the service of selective control— could be observed in patients with PD. This lack of shifting-related transient neural activation is not an isolated finding in patients with PD (e.g., Monchi et al., 2007). In a more general sense, shift trials are associated with surprise, contextual novelty and increased demands for selective control. All characteristics represent situations that likely elicit goaldirected behavior (Barceló et al., 2006; Kopp & Lange, 2013; Kopp et al., 1996). It has been suggested that motor and cognitive impairments in PD specifically concern goal-directed behavior (Brown & Marsden, 1990; Fielding, Georgiou-Karistianis, Millist, & White, 2006; but see Redgrave et al., 2010) that is, in turn, supported by neural activity in medial-frontal areas (Haggard, 2008). Our N2s data imply that it was this transient medial-frontal activation in the service goal-directed control that could not be observed in patients with PD.


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Taken together, behavior and neural activity are part of a converging picture: Controls shifted back and forth between two persistent attentional sets in such a way that their actions were performed under goal-directed control. Patients with PD, in contrast, relied on exogenous sources of information (i.e., multiple feedbacks on response accuracy) such that their actions were performed to a greater extent under stimulus control (Brown & Marsden, 1988). The need to shift was signaled by “incorrect response”-feedbacks, but whether a “zooming in”-shift or a “zooming out”-shift was required on any particular shift trial could only be determined after endogenously maintained information was taken into account (Figure 2). The availability of this information presupposes internal monitoring of one’s own performance. Specifically, subjects had to keep in mind whether they had been attending to central or peripheral stimuli on the current trial, and this memory trace had to be updated on each trial. We may define a demand as a concrete voluntary command for an attentional shift (e.g., “zoom in” or “zoom out”; Figure 1). Given this definition, a demand originates from retrieval of the memory trace—that has its origin in internal performance monitoring—in the presence of an exogenous signal to shift attention. With regard to internal performance monitoring, it is of importance that the response-locked ERP waves revealed an additional dissociation in patients with PD: We found that the amplification of the incongruency-related negativity on incorrect trials (Ne, I) in comparison to the incongruency-related negativity on correct trials (Nc, I) was absent in patients with PD, whereas the amplification of the incongruency-related negativity on correct trials (Nc, I) in comparison to the congruency-related negativity on correct trials (Nc, C) was present in patients with PD. Thus, response-locked ERP waves were sensitive to the incongruency and the correctness of a response in controls, whereas they were sensitive to the incongruency of a response, but not to its correctness, in patients with PD. This finding is in accordance with previous studies according to which PD is associated with Ne attenuation (Beste et al., 2009; Falkenstein et al., 2001; Ito & Kitagawa, 2006; Stemmer, Segalowitz, Dywan, Panisset, & Melmed, 2007; Willemssen et al., 2009; Willemssen, Müller, Schwarz, Hohnsbein, & Falkenstein, 2008; but see Holroyd et al., 2002). Medial-frontal areas, in particular the ACC, contribute to the scalp-recorded Ne, and these areas as well as their connections to the striatum (Ullsperger, Danielmeier, & Jocham, 2014; Ullsperger & von Cramon, 2006) form a neural network for internal performance monitoring. Finally, it is worth mentioning that no evidence for posterror slowing could be discerned in patients with PD. These subjects also showed a remarkably specific reduction of neural activity, namely a lack of posterror N2 augmentation (N2e) in the presence of normal N2c amplitudes. This pattern of findings suggests that patients with PD relied to a lesser extent on internal performance monitoring, thereby detracting them from endogenous control of action. As a caveat, it must be kept in mind that these results were obtained from medicated patients with PD and may thus be confounded by effects of dopaminergic medication. It is well recognized that the relation between dopamine and performance follows an inverted U-shaped function, implying that both insufficient and excessive levels of dopamine impair performance on cognitive tasks (Cools & D’Esposito, 2011; Fallon et al., 2013). In early clinical stages of PD, the degeneration of dopamine-producing cells is most pronounced in the substantia nigra, leading to severe

dopamine depletion in the dorsal striatum, whereas meso-cortical dopamine projections as well as ventral cortico-striatal loops are less affected. Dopaminergic medication, administered to alleviate motor symptoms associated with the affected dorsal cortico-striatal loops, can at the same time impair, through overdosing, functions relying on otherwise intact prefrontal (Gotham et al., 1988) and ventral cortico-striatal loops (Cools, 2006). Thus, it remains a possibility that our findings occurred as a corollary of excessive levels of dopamine in the prefrontal cortex and/or in the ventral striatum in medicated patients with PD (Cools, Miyakawa, Sheridan, & D’Esposito, 2010; Duthoo et al., 2013), rather than consequent to dopamine depletion in the dorsal striatum. In any case, the results point into the direction that the midbrain dopamine system exerts control over attentional shifting ability (Au et al., 2012; Lewis, Slaboszc, Robbins, Barker, & Owen, 2005; Marklund et al., 2009; Robbins, 2007; Stelzel, Fiebach, Cools, Tafazoli, & D’Esposito, 2013; van Holstein et al., 2011; Williams-Gray, Hampshire, Barker, & Owen, 2008). Dopaminergic shifting control is putatively implemented via transient inhibition of routinized behavior (“gate closure”), as reflected in our shift-related N2s findings, thereby supporting contextually novel behavior (input updating via “gate opening”) that emerges via selective disinhibition of cortico-striato-thalamo-cortical loops, possibly via phasic midbrain dopamine release (Aron, 2011; Chatham et al., 2014; D’Ardenne et al., 2012; Frank et al., 2001; Hazy, Frank, & O’Reilly, 2007; Kriete, Noelle, Cohen, & O’Reilly, 2013; O’Reilly, 2006). To conclude, our results reveal that intact selective control and disrupted shifting control are dissociable in early stage medicated patients with PD, but additional work is required to dissect the proportionate effects of disease and treatment on shifting control in Parkinson’s disease. Our ERP-based approach opens a new window onto an understanding of neuropsychological dysfunctions that are associated with PD, and such knowledge represents a prerequisite for an effective clinical management of the often difficult to handle behavioral and cognitive changes in PD (Dalrymple-Alford et al., 2011; Kehagia, Murray, & Robbins, 2010; Tang & Strafella, 2012; Voon et al., 2013; Weintraub & Burn, 2011).

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Received October 14, 2013 Revision received February 28, 2014 Accepted April 11, 2014 䡲

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