Biological Psychology 102 (2014) 130–140

Contents lists available at ScienceDirect

Biological Psychology journal homepage: www.elsevier.com/locate/biopsycho

Transcranial direct current stimulation over left and right DLPFC: Lateralized effects on planning performance and related eye movements Katharina Heinze a,b,c,d,∗,1 , Nina Ruh a,b,c , Kai Nitschke a,b,c,f , Janine Reis a,f , Brita Fritsch a,f , Josef M. Unterrainer e , Benjamin Rahm e , Cornelius Weiller a,b,f , Christoph P. Kaller a,b,f a

Department of Neurology, University Medical Center Freiburg, Germany Freiburg Brain Imaging Center, University of Freiburg, Germany c Biological and Personality Psychology, Department of Psychology, University of Freiburg, Germany d Cochlear Implant Center Erlangen, ENT Department, University Hospital Erlangen, Germany e Med. Psychology and Med. Sociology, University Medical Center, University of Mainz, Germany f BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany b

a r t i c l e

i n f o

Article history: Received 21 January 2014 Accepted 26 July 2014 Available online 4 August 2014 Keywords: Dorsolateral prefrontal cortex Planning Tower of London task tDCS Eye movements Hemispheric asymmetry

a b s t r a c t Left and right dorsolateral prefrontal cortex (dlPFC) were recently found to be differentially affected by unilateral continuous theta-burst stimulation, reflected in an oppositional alteration of initial thinking time (ITT) in the Tower of London planning task. Here, we further explored this finding using bilateral transcranial direct current stimulation (tDCS) and simultaneous tracking of eye movements. Results revealed a decrease in ITT during concurrent cathodal tDCS of left dlPFC and anodal tDCS of right dlPFC. Eye-movement analyses showed that this facilitating tDCS effect was associated with the actual planning phase, thus reflecting a planning-specific impact of stimulation. For the reverse stimulation pattern of cathodal tDCS of right dlPFC and anodal tDCS of left dlPFC, an increase in gaze shifts was observed, without a significant impact on ITT. Taken together, these findings corroborate that enhanced planning performance can be obtained by boosting right dlPFC and dismantling the inhibitory impact of left dlPFC. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Planning ahead future actions is among the highest cognitive functions of the human brain (Morris & Ward, 2005). Based on numerous neuroimaging and lesion studies, planning ability has been linked to the dorsolateral prefrontal cortex (dlPFC), in particular to the mid-dlPFC (Unterrainer & Owen, 2006). However, the extent to which different roles in planning ability are assigned to the left versus the right (mid-)dlPFC varies considerably between studies (e.g., Byrd, Case, & Berg, 2011; Cazalis et al., 2003; Crescentini, Seyed-Allaei, Vallesi, & Shallice, 2012; Dagher,

∗ Corresponding author at: Cochlear Implant Center Erlangen, ENT Department, University Hospital Erlangen, Waldstraße 1, 91054 Erlangen, Germany. Tel.: +49 9131 85 32980. E-mail address: [email protected] (K. Heinze). 1 Katharina Heinze has accomplished the present study as part of her Ph.D. thesis at the University Medical Center Freiburg and works now at the University Hospital Erlangen. http://dx.doi.org/10.1016/j.biopsycho.2014.07.019 0301-0511/© 2014 Elsevier B.V. All rights reserved.

Owen, Boecker, & Brooks, 1999; Morris, Ahmed, Syed, & Toone, 1993; Newman, Carpenter, Varma, & Just, 2003; Owen, Doyon, Petrides, & Evans, 1996; Owen et al., 1998; Rowe, Owen, Johnsrude, & Passingham, 2001; Unterrainer et al., 2004; Van den Heuvel et al., 2003; Wagner, Koch, Reichenbach, Sauer, & Schlosser, 2006; for an overview, see Kaller, Rahm, Spreer, Weiller, & Unterrainer, 2011). In a recent functional magnetic resonance imaging (fMRI) study using the Tower of London (ToL; Shallice, 1982) planning task, bilateral activation during planning was traced back to two separable aspects of cognitive processing, each recruiting a lateralized pattern of mid-dlPFC activation: Left-lateralized mid-dlPFC activation was found to be associated with early processes of internalization, whereas right-lateralized mid-dlPFC activation was found to reflect subsequent processes of planning proper (Kaller et al., 2011; see also Nitschke, Ruh, Kappler, Stahl, & Kaller, 2012; Ruh, Rahm, Unterrainer, Weiller, & Kaller, 2012). The lateralization of these aspects of planning in the middlPFC was further studied by Kaller, Heinze, et al. (2013) applying continuous theta-burst-stimulation (cTBS) as an inhibitory transcranial magnetic stimulation (TMS) protocol (Huang, Edwards,

K. Heinze et al. / Biological Psychology 102 (2014) 130–140

Rounis, Bhatia, & Rothwell, 2005) to either the left or the right mid-dlPFC before assessment of planning processes with the ToL. Results showed a global interaction of stimulation side (left vs. right mid-dlPFC) and stimulation mode (real vs. sham): Initial thinking time was reduced after left-sided inhibitory mid-dlPFC stimulation and increased after right-sided inhibitory mid-dlPFC stimulation. Assuming that cTBS exerts a similar effect on prefrontal cortex as on motor cortex (for a discussion of limitations of this assumption see also Kaller, Heinze, et al., 2013), a possible interpretation of the paradoxical functional facilitation (Kapur, 1996) of initial thinking time after inhibitory stimulation of left mid-dlPFC is the attenuation of the transcallosal inhibition from left to right mid-dlPFC. In this framework, the right mid-dlPFC would play a specific role for planning performance (see also Unterrainer et al., 2004), based on the argumentation that a contralateral release of the right middlPFC leads to decreased initial thinking time, whereas inhibiting the right mid-dlPFC cannot be compensated by the left mid-dlPFC in a similar manner (Kaller, Heinze, et al., 2013). To empirically corroborate these assumptions, the aim of the present follow-up study was, first, to replicate and extend the findings on cTBS-induced changes in initial thinking time by using concurrent cathodal and anodal transcranial direct current stimulation (tDCS) over left and right dlPFC2 and, second, to gain further insight into the neural and cognitive origins of the associated costs and benefits in processing time based on concurrent eye-movement recordings. Although caveat exists regarding the comparability of cTBS and tDCS stimulation (Ziemann et al., 2008; Stagg, Best, et al., 2009; Stagg, Wylezinska, et al., 2009), results from a recent tDCS study using the ToL also imply a decrease of initial thinking time following an inhibitory (cathodal) stimulation of left prefrontal cortex (Dockery, Hueckel-Weng, Birbaumer, & Plewnia, 2009; for discussion also see Kaller, Heinze, et al., 2013). TDCS is a non-invasive stimulation method which exhibits its influence by inducing a light direct current to the underlying brain tissue via an anodal and a cathodal surface electrode on the scalp. Anodal stimulation was shown to enhance cortical excitability, whereas cathodal stimulation was shown to reduce cortical excitability (Nitsche & Paulus, 2000; Nitsche, Nitsche et al., 2003). For testing assumptions of simultaneously enhanced and decreased activity of different brain regions, particularly of homolog areas across both hemispheres, the immanent polarity of tDCS constitutes an advantageous feature compared to TMS (Priori, Hallett, & Rothwell, 2009). For instance, Fecteau et al. (2007) investigated the influence of tDCS over bilateral dlPFC on decision making in a risk-taking task to reassess results from unilateral repetitive TMS (Knoch, Gianotti, et al., 2006). Results confirmed that concurrent down-regulation of left dlPFC and up-regulation of right dlPFC led to decreased risk taking and were interpreted in terms of contralateral inhibition (Fecteau et al., 2007). Testing for a contralateral inhibition with bilateral tDCS may hence provide valuable information on brain-behavior relationships and may complement insights derived from unilateral stimulation approaches (e.g., Williams, Pascual-Leone, & Fregni, 2010). Besides the putative neurophysiological underpinnings of the asymmetric stimulation effect, the cognitive mechanisms behind the observed costs and benefits in initial thinking time remain also elusive (for discussion see Kaller, Heinze, et al., 2013). Analysis of eye movements has a long history in cognitive (neuro-)science (e.g.

2 Application of tDCS is spatially less focal compared to TMS approaches such as cTBS. That is, although in the present study a stimulation of bilateral homologs in mid-dlPFC was intended by electrode placement at the respective scalp positions, a stimulation of brain tissue in surrounding areas within dlPFC and beyond is likely. To account for this spatial imprecision, the prefix ‘mid-’ is consequently omitted when referring to tDCS over left and right mid-dlPFC.

131

Loftus & Mackworth, 1978) and is a fruitful approach to assign overt behavior to underlying and not directly accessible cognitive processes (Liversedge & Findlay, 2000; Hayhoe & Ballard, 2005). For instance, Hodgson, Bajwa, Owen, and Kennard (2000) introduced eye-movement analyses to decompose different stages of cognitive processing during planning in the ToL task (see also Hodgson, Tiesman, Owen, & Kennard, 2002; Huddy et al., 2007). With respect to the present examinations of planning processes during initial thinking time, eye-movement analyses were employed in order to differentiate an early internalization phase of building-up a mental representation of the given problem from a later phase of planning proper (cf. Kaller, Rahm, Bolkenius, & Unterrainer, 2009; Nitschke et al., 2012). In detail, the number of gaze shifts between start and goal state of a planning problem has been shown to be associated with the early internalization phase during the initial thinking time (Ruh et al., 2012; Kaller et al., 2009) and is sensitive to changes in difficulty of matching start and goal state (Kaller et al., 2009; Nitschke et al., 2012). On the other hand, the duration of the last gaze before movement execution has been shown to reflect later stages of the planning process (Ruh et al., 2012; Byrd et al., 2011) and is sensitive to changes in difficulty of intermediate moves which has been supposed to reflect planning proper (Kaller et al., 2009; Nitschke et al., 2012). Building on these previous findings, the rationale of the present multi-methodological approach was to complement tDCS with concurrent eye-movement recordings during planning so as to bridge the gap between the different strands of evidence from brain stimulation (Kaller, Heinze, et al., 2013) and eye movement studies (Kaller et al., 2009; Nitschke et al., 2012; Ruh et al., 2012) on the dissociable contributions of left and right mid-dlPFC to planning processes (Kaller et al., 2011). Thus, besides generally replicating the asymmetric cTBS effect on initial thinking times following inhibitory stimulation of left versus right mid-dlPFC (Kaller, Heinze, et al., 2013), we sought to pinpoint the anticipated effects of tDCS over left and right dlPFC on initial thinking times to separable stages of cognitive processing as revealed by the underlying eyemovement patterns. More specifically, we expected stimulation effects on processes of internalization and planning proper to be reflected in the number of gaze shifts between start and goal state and the duration of the last gaze of the start state before movement execution, respectively (cf. Kaller et al., 2009; Nitschke et al., 2012). 2. Methods 2.1. Subjects A total of 55 right-handed subjects (aged 19–28 years; 27 female) participated in the present study. None of them reported any neurological or psychiatric history or met any exclusion criteria for tDCS and/or eye tracking. Written informed consent was obtained before the tDCS experiment. Subjects received a compensation of D 20 for participation. The study protocol was approved by local ethics authorities and was conducted in accordance with the Declaration of Helsinki. Before analysis, data of three participants had to be excluded: In two participants, recording of eye movements failed, whereas another participant did not follow instructions on how to handle the applied three-button computer mouse (see Section 2.4). During data analysis, another seven subjects were excluded due to initial thinking times more than two standard deviations below/above their groupspecific average. Thus, data of 45 subjects were included in the present analyses. 2.2. Experimental groups For an experimental manipulation of the presence and/or polarity of tDCS stimulation (see Section 2.3), participants were assigned to three groups that were matched in advance with regard to age and sex (see Table 1). That is, participants were pseudo-randomly assigned to the three groups by concurrently accounting for (i.e. minimizing) potential a priori group differences in the mean and distribution of age and sex. Out of the included 45 subjects, 14 subjects simultaneously received cathodal stimulation to the left dlPFC and anodal stimulation to the right dlPFC (left cathodal/right anodal group), 15 subjects received tDCS of the reversed polarity (right cathodal/left anodal group), and another 16 subjects received sham stimulation (sham group).

132

K. Heinze et al. / Biological Psychology 102 (2014) 130–140

Table 1 Overview on descriptive variables. Experimental groups

N (female) Age Planning abilities (max 24) Handedness score (max 22) MWT-B (max 36) Mean h sleep/night

Left cathodal/right anodal

Right cathodal/left anodal

Sham

p

14 (9) 24.20 (2.25) 13.64 (3.46) 19.64 (3.30) 28.14 (3.57) 7.54 (.63)

15 (7) 24.02 (2.57) 14.13 (2.75) 19.40 (2.50) 28.20 (4.21) 7.57 (.53)

16 (8) 24.42 (2.39) 15.13 (3.61) 21.06 (.85) 28.50 (3.71) 7.53 (.86)

.602 .898 .458 .124 .962 .986

Note: Maximum scores are reported for dependent variables if applicable. Except for N, all other data cells report mean values and standard deviations (in parentheses).

Furthermore, several additional variables were assessed immediately before the tDCS session in order to allow for a posteriori examinations of group assignments. To this end, a custom handedness questionnaire based on the Edinburgh Handedness Inventory (Oldfield, 1971; Salmaso & Longoni, 1985) and the Hand Preference Test (Spreen & Strauss, 1998) was administered. Verbal crystallized intelligence was assessed with the Mehrfachwahl–Wortschatz-Intelligenztest (MWT-B, Lehrl, 1999), a German test of passive vocabulary. To ensure comparable levels of planning ability across groups, subjects were tested before the actual planning experiment using a standard version of the Tower of London (ToL) task with 24 four-, five- and sixmove-problems (cf. Kaller, Heinze, et al., 2013). Finally, the mean number of hours of sleep per night was assessed to control for potential sleep-related differences in ongoing brain activity that may affect brain stimulation (Ridding & Ziemann, 2010). Analysis of variance confirmed that the groups did not differ significantly in any of these variables (see Table 1). 2.3. Transcranial direct current stimulation Transcranial direct current stimulation (tDCS) was applied by a battery-driven stimulator (Phoresor, Iomed Inc., Salt Lake City, USA) that delivered direct current with an assumed current density of 40 ␮A/cm2 . Cathodal and anodal electrodes featured an area of 25 cm2 each and were surrounded by a water-soaked sponge. Electrodes were placed at spatial positions F3 and F4 according to the international 10-20-system for electroencephalogram electrode placement (Jasper, 1958) that are commonly considered as surface locations above (mid-)dorsolateral prefrontal cortex (e.g. Homan, Herman & Purdy, 1987). In contrast to the frequently applied placement of the reference electrode above the contralateral orbit, this bilateral dlPFC montage was chosen for several specific reasons: Given (i) the small spatial distance between the orbit and the actual stimulation site above dlPFC and (ii) the low focality of tDCS, an orbital electrode placement would possibly result in an effective stimulation of dlPFC tissue. Given further that anodal and cathodal polarities entail opposing effects of stimulation on the underlying neural tissue, a tDCS stimulation over bilateral dlPFC was hence expected to maximize the effects of a contralateral inhibition between left and right dlPFC as the potential neurophysiological mechanism behind the asymmetric cTBS results found in the study of Kaller, Heinze, et al. (2013). The temporal course of tDCS stimulation was chosen similar to Dockery et al. (2009). For all groups, stimulation was started 5 min prior to the beginning of the planning experiment by ramping up the current to 1 mA with approximately 0.1 mA per second. In the sham group, the current was ramped down stepwise immediately after reaching the peak value of 1 mA. This sham procedure was previously shown to produce the same sensation as real stimulation but without exerting any stimulation effects (Gandiga, Hummel, & Cohen, 2006). After 5 min of real or sham stimulation, the planning experiment was started while tDCS stimulation continued for another 10 min. The planning experiment comprised 96 experimental trials, but tDCS stimulation was applied only during approximately the first 32 experimental trials (see Section 2.6 for further details). After 48 experimental trials, there was a short break of 2 min for eye-tracker recalibration. Importantly, additional analyses confirmed that experimental groups did not differ in stimulation-relevant variables (see Table 2) such as the individual head size in terms of the distances between nasion and inion that were determined for individual electrode placement, thus ruling out differential attenuation of

stimulation effects due to different electrode distances (Datta, Elwassif, Battaglia, & Bikson, 2008). In addition, groups did not differ regarding the duration between cessation of stimulation and break for recalibration. Moreover, the exact times of stimulation before beginning of the planning experiment, the duration of the eyetracker recalibration break, and the duration of the planning experiment after this break did not differ between all three groups (see Table 2). Note that the negligible variations in the stimulation durations before the start of the experimental task were due to slight differences in the duration of the prior eye-tracker calibration. 2.4. Tower of London (ToL) planning task Effects of tDCS stimulation on planning processes were assessed with a computerized version of the ToL identical to the one used by Kaller, Heinze, et al. (2013; see also Kaller et al., 2011; Ruh et al., 2012). In this task, a given start state has to be transformed into a given goal state. In both states, three balls of three different colors (blue, red and yellow) are placed on three pegs of equal size. The transformation of the start state has to follow several rules: Only one ball can be taken at a time, only the topmost ball on each peg can be taken, and the balls must not be placed outside the tower. In the computerized version, rule-breaks were prevented automatically. Start and goal state were presented vertically on the computer screen, with the start state at the bottom. For the execution of each solution, a three-button computer mouse was used. Topmost balls on the left, middle, or right peg of the start state could be selected by pressing the corresponding buttons of the computer mouse that were handled with the index-, middle-, and ring finger of the right hand, respectively (see also Kaller et al., 2009; Kaller, Heinze, et al., 2013; Kaller et al., 2011; Nitschke et al., 2012). Handling of the three-button computer mouse was practiced with a set of one- and two-move-problems before tDCS stimulation. Subjects were instructed (i) to solve each problem in the least possible number of moves and (ii) to plan ahead the solution before starting to execute it. The planning experiment comprised 96 three-move problems which were divided into three parts (online, offline 1, and offline 2) with 32 experimental trials each (Fig. 1C; see also Section 2.6). At the beginning and after completion of 48 experimental trials (i.e. midway in offline period 1), a short eye-tracker (re)calibration was followed by eight (structurally different) dummy three-move problems to account for initial practicing and break effects. Only the 96 experimental problems were analyzed. As in our previous studies (Kaller et al., 2011; Kaller, Heinze, et al., 2013), the experimental problem set consisted of eight basic problems which were each presented in twelve isoforms by permutating the spatial positions of the pegs and the colors of the balls (resulting in 96 different experimental problems). This procedure has been shown to keep learning effects for each problem unspecific and at minimum (Kaller et al., 2011). For each subject, the problem set was created individually with counterbalanced presentation order and pseudo-randomly varied permutations of ball colors and peg positions (cf. Kaller et al., 2011; Kaller, Heinze, et al., 2013). The initial thinking time defined as the time taken to mentally prepare the solution (i.e. the interval from the onset of problem presentation until the start of executing ball movements) was used as dependent measure. 2.5. Eye-movement recording and analysis During the planning experiment, eye movements were recorded using a SMI RED remote eye-tracking system (SMI SensoMotoric Instruments GmbH, Teltow/Berlin,

Table 2 Overview on stimulation-related variables. Experimental groups

Distance nasion–inion (cm) Duration of stimulation before planning experiment (min) Duration between end of stimulation and break (min) Duration of break for eye-tracker recalibration (min) Duration after recalibration break (min)

Left cathodal/right anodal

Right cathodal/left anodal

Sham

p

36.50 (1.65) 5.16 (.15) 3.78 (1.42) 2.13 (.54) 12.75 (.84)

36.17 (.99) 5.22 (.43) 4.54 (1.59) 2.00 (.31) 13.10 (1.06)

36.38 (1.62) 5.60 (1.30) 4.69 (1.97) 2.22 (.27) 13.42 (1.85)

.823 .276 .314 .311 .406

Note: All columns include mean values and standard deviations in parentheses.

K. Heinze et al. / Biological Psychology 102 (2014) 130–140

A

133

B

4.5°

2.3°

4.4°

AOI Center

5.4°

7.3°

AOI Top

12.1°

16.5°

AOI Bottom 12°

C

Cal.

X

Online

Offline 1

Cal.

tDCS Stimulation 0

5

10

X

Offline 1

Offline 2

No Stimulation 15

20

25

Time (min)

Fig. 1. Schematic illustration of spatial layouts of (A) tower states and their (B) vertical arrangements (cf. Nitschke et al., 2012). Numbers refer to visual angles in degree. (C) Schematic illustration of the experimental timeline, the application of tDCS and the resulting three stimulation periods (online, offline 1, and offline 2). As the experiment was self-paced, transitions between the different periods were not temporally fixed. However, after the overall 15 min of tDCS stimulation, one third of the trials was solved on average and thus coinciding with the transition between the online and offline 1 periods. Abbreviations: Cal., break for (re)calibration of eye tracker; X, dummy trials to account for initial practicing and break effects.

Germany). In this system, infrared light is emitted from a spatially constant source at an oblique angle to the subject’s face and reflected by the face, eyeballs, and iris, but not by the pupils (dark-pupil approach). The reflected light is collected by an infrared sensitive camera. By relating the detected pupil location to the first Purkinje-image of the reflected light and projecting it to the calibrated field of view, the gaze direction is inferred. Eye movements were recorded binocularly at a sampling rate of 50 Hz. Subjects were seated at a distance of approximately 57 cm from a screen of 19 inch (48.3 cm) in diameter. The head was placed on a chin rest which was adjusted individually so that the eye level corresponded to the center of the screen. Size and configuration of visual stimuli was identical to the study of Nitschke et al. (2012; see Fig. 1A and B for a schematic illustration). At the beginning and after 48 experimental trials of the planning task (i.e. midway in the offline period 1; cf. Fig. 1C), the eye tracker was calibrated individually for each subject. The recalibration break after 48 experimental trials (see Section 2.4) was necessary to account for slowly accumulating distortion of eye movements caused by head movements and blinks. The subjects’ gaze had to follow a black circle appearing at nine different positions at the corners, flanks, and the center of the screen. Between trials, subjects were instructed to fixate a center cross on the screen to assure a standardized starting point of gaze shifts. Prior to each trial, a center fixation of at least 500 ms was required to allow the program to continue. The calibration was checked after each block of eight problems and eye movements were constantly monitored by the experimenter throughout the task on a control screen. Analogous to Nitschke et al. (2012), eye-movement data was preprocessed using BeGaze 3.0 (SensoMotoric Instruments GmbH, Teltow/Berlin, Germany) and custom algorithms written in MATLAB (The Mathworks Inc., Natick, MA, USA). Automatic detection of saccades was based on a peak velocity threshold of > 80 degree per second and classification of individual fixations had to pass a minimum duration of 40 ms. Instances of gaze were classified concerning three areas of interest (AOIs) in the top half of the screen (ToL goal state, above 2.7 degree from the center), in the center (fixation cross, less than ±2.7 degree from the center), and in the bottom half of the screen (ToL start state, below −2.7 degree from the center) (cf. Fig. 1B). Rare occasions with fixations of the center AOI during the initial thinking time were regarded as peripheral fixations of the state opposite to the prior fixation (1.2% of trials). Based on previous results (Kaller et al., 2009; Nitschke et al., 2012; Ruh et al., 2012), the number of alternating gaze shifts during the initial thinking time and the duration of the last gaze before movement execution were used as dependent measures. 2.6. Data analysis Similar to Dockery et al. (2009), the duration of real tDCS stimulation was fixed to 5 min before and another 10 min during planning (Fig. 1C; see also Section 2.3).

After ten minutes of the planning experiment, on average one third of the trials were solved. As the groups did not differ significantly regarding the durations of the experimental course (see Table 2), the 96 experimental trials were divided into three periods with 32 three-move ToL problems each to separate effects during stimulation (online) from subsequent effects during non-stimulation (offline). Consequently, one period of planning with online stimulation and two periods of planning with offline stimulation were obtained (Fig. 1C). Initial thinking times and gaze durations were mean-aggregated per subject and period. For each group in each of the three periods, subjects with a mean initial thinking time above or below two standard deviations from the mean were identified and excluded from further analysis (n = 7, see Section 2.1). To examine the effects of tDCS on planning and related eye movements, initial thinking time, the number of gaze shifts between the goal and the start state during the initial thinking time, and the duration of the last gaze before execution were analyzed as dependent variables. To assess the specificity of tDCS effects on planning, additional analyses concerned movement execution times.

3. Results 3.1. Effects of tDCS on planning performance Planning accuracy in terms of correct solutions was at ceiling with total accuracy rates for the three groups between 90 and 93%, and therefore not followed after. Only correctly solved trials were included in the subsequent analyses. A 3 × 3 repeated measures analysis of variance (RM-ANOVA) with Stimulation Group (left cathodal/right anodal vs. right cathodal/left anodal vs. sham) as a between-subject factor and Stimulation Period (online, offline 1, offline 2) as a withinsubject factor was performed on initial thinking time. Results showed a main effect of Stimulation Period (F(2,84) = 69.401, p < .001, p 2 = .623) reflecting an unspecific decrease in initial thinking time (Fig. 2) that progressed across the three time periods (online, offline 1, offline 2). Furthermore, a significant interaction of Stimulation Period × Stimulation Group (F(4,84) = 2.677, p = .037, p 2 = .113; see Fig. 2) was obtained. No main effect of Stimulation Group (F(2,42) = .661, p = .522, p 2 = .031) was evident. Post hoc explorative pairwise comparisons (Fisher’s least significant difference,

K. Heinze et al. / Biological Psychology 102 (2014) 130–140

3000

134

Stimulation Group Left cathodal/ right anodal

2400

2600

Sham

2200

Initial Thinking Time (ms)

2800

Right cathodal/ left anodal

Online

Offline 1

Offline 2

Stimulation Period Fig. 2. Estimated marginal means and standard errors of initial thinking time (ms) for the interaction of Stimulation Period and Stimulation Group.

LSD) revealed that the decrease of initial thinking time in the left cathodal/right anodal group compared to the sham group in the online stimulation period tended to result in the interaction of Stimulation Period and Stimulation Group (estimated marginal mean [EMM] difference = −359.5 ms, p = .052). No other comparison reached significance (lowest p = .179 for the difference between left cathodal/right anodal and right cathodal/left anodal in the online period).

bottom (start state), three or five gaze shifts were predominantly found (see Fig. 3B). In order to account for these different patterns of gaze shifts dependent on the first gaze, the location of the first inspection during the initial thinking time was included as an additional factor in the subsequent eye-movement analyses. 3.3. Effects of TDCS on the number of gaze shifts between start and goal state

3.2. Eye-movement patterns Before assessment of stimulation effects on eye-movement data, a general analysis of the observed gaze patterns was conducted. Similar to previous studies using the same paradigm (Kaller et al., 2009; Nitschke et al., 2012), the last gaze during initial thinking time was directed to the bottom (start state) in 84.9% of all trials across all subjects. In contrast to previous studies, in 58.5% of all trials the first gaze was directed to the top (goal state), while in 41.5% of all trials the first gaze was directed to the bottom (start state). The mean number of trials starting at the top did not differ between the experimental groups (F(2,42) = .231, p = .794, p 2 = .011), neither did the distribution of subjects predominant preferences for the location of the first gaze (2 = 2.319, p = .677; cf. Kaller et al., 2009). Concerning the number of gaze shifts, analyses revealed the expected eye-movement patterns dependent on whether the gaze was first directed to the start state or the goal state (cf. Kaller et al., 2009). That is, in trials in which the gaze was first directed to the top, i.e. the goal state, mostly even numbers of gaze shifts were displayed because the last gaze was directed to the bottom in almost all cases. Commonly observed patterns comprised four or six gaze shifts before movement execution of the problem (see Fig. 3A). In trials in which the first gaze was directed to the

To examine the effects of tDCS on the number of gaze shifts, a 3 × 2 × 3 RM-ANOVA with Stimulation Group (left cathodal/right anodal vs. right cathodal/left anodal vs. sham) as a between-subject factor and First Inspection (top vs. bottom) as well as Stimulation Period (online, offline 1, offline 2) as within-subject factors was performed. Results in the number of gaze shifts again revealed a main effect of Stimulation Period (F(2,82) = 53.133, p < .001, p 2 = .564) and a significant interaction of Stimulation Period × Stimulation Group (F(4,82) = 3.096, p = .020, p 2 = .131; see Fig. 4). Post hoc explorative pairwise comparisons (LSD) for the interaction term revealed no significant comparisons, but showed the lowest p for the difference between the left cathodal/right anodal versus the right cathodal/left anodal group during the online stimulation period (EMM difference = −.522 gaze shifts, p = .153). No main effects of Stimulation Group (F(2,41) = .252, p = .778, p 2 = .012) or First Inspection (F(1,41) = .172, p = .681, p 2 = .004) were evident. An interaction of Stimulation Period × First Inspection (F(2,82) = 4.280, p = .017, p 2 = .095) indicated that there were more gaze shifts during the online stimulation period especially when the first gaze was directed to the bottom compared to top (EMM difference = .295 gaze shifts, p = .027), but this finding was not related to the type of

K. Heinze et al. / Biological Psychology 102 (2014) 130–140

B

30 10

20

Percentage of Trials

30 20

0

0

10

Percentage of Trials

40

40

50

50

A

135

1

2

3

4

5

6

7

8

1

Number of Gaze Shifts

2

3

4

5

6

7

8

Number of Gaze Shifts

5.5

Fig. 3. Patterns of gaze shifts following a first inspection directed to the goal state at the top (A) or to the start state at the bottom half of the screen (B). Bars highlighted in dark gray indicate the most prototypical numbers of gaze shifts (4 and 6 shifts vs. 3 and 5 shifts dependent on location of first inspection toward top or bottom, respectively).

Stimulation Group Left cathodal/ right anodal

4.5

Sham

4.0

Number of Gaze Shifts

5.0

Right cathodal/ left anodal

Online

Offline 1

Offline 2

Stimulation Period Fig. 4. Estimated marginal means and standard errors of the number of gaze shifts for the interaction of Stimulation Period and Stimulation Group.

K. Heinze et al. / Biological Psychology 102 (2014) 130–140

800

136

Stimulation Group

700

Right cathodal/ left anodal

600

Sham

500

Last Gaze Durations (ms)

Left cathodal/ right anodal

Online

Offline 1

Offline 2

Stimulation Period Fig. 5. Estimated marginal means and standard errors of the duration of the last gaze for the interaction of Stimulation Period and Stimulation Group. The left cathodal/right anodal group differed significantly from both the sham group as well as the right cathodal/left anodal group during online stimulation.

stimulation (e.g. factor Stimulation Group). None of the remaining interactions reached significance (lowest p = .469). 3.4. Effects of tDCS on the duration of the last gaze For inspection of tDCS effects on the duration of the last gaze, a RM-ANOVA with the within-subject factors Stimulation Period and First Inspection and the between-subject factor Stimulation Group was performed and again yielded a significant effect of Stimulation Period (F(2,82) = 6.971, p = .002, p 2 = .145) and a significant interaction of Stimulation Period × Stimulation Group (F(4,82) = 4.334, p = .003, p 2 = .175; see Fig. 5). The main effect of Stimulation Group also approached significance (F(2,41) = 3.014, p = .060, p 2 = .128). No main effect of First Inspection (F(1,41) = .316, p = .577, p 2 = .008) was found, and none of the remaining interactions reached significance (lowest p = .404). Post hoc pairwise comparisons (LSD) for the interaction of Stimulation Period and Stimulation Group revealed a shorter duration of the last gaze in the left cathodal/right anodal group during online stimulation compared to both the sham group (EMM difference = −252.5 ms, p = .001) and the right cathodal/left anodal group (EMM difference = −138.8 ms, p = .048). No other comparison reached significance, although there was a trend for a difference between the right cathodal/left anodal and the sham group in the online stimulation period as well (EMM difference = −113.8 ms, p = .097). 3.5. Additional analyses 3.5.1. Analyses on movement execution times An additional RM-ANOVA with the between-subject factor Stimulation Group and the within-subject factor Stimulation Period was computed on the averaged times taken to manually

execute the problem solutions (movement execution time) to ensure that stimulation effects were confined to the planning stage and did not influence the execution stage of solving ToL problems. Only the main effect of Stimulation Period reached significance (F(2,84) = 74.214, p < .001, p 2 = .639) and indicated an unspecific acceleration of movement execution times, while neither the main effect of Stimulation Group (F(2,42) = .338, p = .715, p 2 = .016) nor the interaction (F(4,84) = .600, p = .664, p 2 = .028) yielded significant differences. 3.5.2. Analyses on potential bias by inclusion of first inspection as additional factor To further rule out that the inclusion of the additional factor First Inspection for the eye-movement analyses had any influence on trial selection and the comparability with analyses on initial thinking time (Section 3.1), the initial thinking time was also examined with the additional factor First Inspection (cf. Section 3.3). Results confirmed and even sharpened up the previous analysis, showing a main effect of Stimulation Period (F(2,82) = 60.364, p < .001, p 2 = .596), and a significant interaction of Stimulation Period × Stimulation Group (F(4,82) = 4.049, p = .005, p 2 = .165). No main effects of First Inspection (F(1,41) = .325, p = .572, p 2 = .008) or Stimulation Group (F(2,41) = .562, p = .574, p 2 = .027) were evident, and none of the remaining interactions reached significance (lowest p = .709). Post hoc explorative pairwise comparisons (LSD) within this model showed that during online stimulation (stimulation period 1) the left cathodal/right anodal group exhibited significantly shorter initial thinking time not only compared to the sham group (EMM difference = −343.7 ms, p = .044), but also compared to the right cathodal/left anodal group (EMM difference = −364.1 ms, p = .033). No other post hoc comparison reached significance (lowest p = .678).

K. Heinze et al. / Biological Psychology 102 (2014) 130–140

4. Discussion In the present study we sought (i) to replicate previously reported differential effects of unilateral cTBS over left and right mid-dlPFC on planning in the Tower of London task (Kaller, Heinze, et al., 2013) and (ii) to further clarify their cognitive and neural origins. To this end, application of bilateral tDCS over dlPFC was combined with an eye-tracking based decomposition of the affected initial thinking time into dissociable stages of information processing that are suggested to reflect consecutive processes of internalization and planning proper (cf. Kaller et al., 2009; Nitschke et al., 2012; Ruh et al., 2012). Results revealed effects of online tDCS, namely a shorter duration of both the initial thinking time and the last gaze before movement execution when cathodal stimulation over left dlPFC was applied concurrently with anodal stimulation over right dlPFC. A higher number of gaze shifts during the initial thinking time but no differences in initial thinking time itself were found under online tDCS when anodal stimulation was applied to the left dlPFC and cathodal stimulation was simultaneously applied to the right dlPFC. Effects did not sustain after stimulation was set off.

137

In addition, antagonist polarity of tDCS effects regularly shown in motor measures is not uncritically transferable to frontal cognitive output measures. In a meta-analysis, Jacobson, Koslowsky, and Lavidor (2012) compared the polarity effects of tDCS in motor and cognitive domains and revealed that anodal stimulation regularly produces a facilitating effect, whereas the cathodal inhibiting effect is less likely reproduced for frontal stimulation. The present results may have hence been predominantly driven by enhancing effects of anodal stimulation. However, it cannot be excluded that the observed effects have been further influenced by differences and possible interactions between short-term and long-term tDCS effects during and after stimulation as well as between stimulation effects in (initial) resting state and under (subsequent) task load (for examples, see Stagg et al., 2011). Indeed, most of the cognitive studies included by Jacobson et al. (2012) used heterogeneous combinations of resting and online-stimulation, a fact that might indicate that the effect of cathodal stimulation is more susceptible to such kind of interactions. Finally, besides tDCS effects on ipsiand contralateral dlPFC homologs, present findings may have also been driven by stimulation effects on even more remote projection areas of dlPFC fiber connections with posterior cortex (for a discussion in context of cTBS, see Kaller, Heinze, et al., 2013).

4.1. Relation to previous cTBS results

4.2. Implications for left versus right (mid-)dlPFC function

In the previous cTBS study on planning by Kaller, Heinze, et al. (2013), initial thinking time decreased after left-sided stimulation and increased after right-sided mid-dlPFC stimulation. In the present study, initial thinking time decreased during concurrent left cathodal and right anodal tDCS over bilateral dlPFC, whereas the opposite polarity did not lead to significant differences compared to sham stimulation. Thus, present tDCS results for initial thinking time concur in parts directly with our previous cTBS findings. However, the comparability of cTBS and tDCS is not yet completely resolved, as are the mechanisms of frontal tDCS per se. For instance, Stagg, Best, et al. (2009) reported that anodal and cathodal stimulation both lead to a decrease in the concentration of the inhibitory neurotransmitter gamma-aminobutyric acid (GABA) in the stimulated motor cortex, while only cathodal stimulation leads to a reduction in the concentration of the excitatory neurotransmitter glutamate. In a related paper, it was further shown that cTBS, in contrast, does not affect glutamate levels but results in an increase of GABA concentration in the stimulated motor region (Stagg, Wylezinska, et al., 2009). However, these differences in transmitter concentrations relate primarily to the after-effects of both stimulation approaches. TDCS effects during stimulation are believed to reflect a modulation of the resting membrane potential of interneurons rather than synaptic transmission (Nitsche, Fricke, et al., 2003; Nitsche et al., 2005; Stagg & Nitsche, 2011), whereas the after-effects of tDCS and cTBS are believed to originate both from a direct de-/hyperpolarization (though less clear for cathodal tDCS) and from synaptic modulation (Nitsche et al., 2005; Stagg & Nitsche, 2011; Huang et al., 2005). Moreover, transcallosal effects of tDCS are suggested to be mediated by inhibitory interneurons at the stimulation site (that are either excited or inhibited by anodal or cathodal tDCS, respectively) rather than by transcallosal projections toward the contralateral hemisphere (Lang, Nitsche, Paulus, Rothwell, & Lemon, 2004). As the present results are restricted to stimulation effects during online tDCS with a fast return to normal after tDCS offset, a simple explanation would be to attribute these results to changes in resting membrane potential of interneurons. In consequence, although the present tDCS online-effects and previous cTBS after-effects (Kaller, Heinze, et al., 2013) of (mid-)dlPFC stimulation on planning supposedly occurred within the same neural system, they may still be based on different underlying neurophysiological mechanisms.

Irrespective of the presumably distinct and still not fully understood neurophysiological mechanisms behind cTBS and tDCS, present results replicate our previous findings of a paradoxical facilitation compared to normal state (i.e. sham stimulation) given that it was possible to mimic the beneficial behavioral effects of inhibitory cTBS over left mid-dlPFC (Kaller, Heinze, et al., 2013) via simultaneously applied inhibitory cathodal tDCS over left dlPFC and facilitatory anodal tDCS over right dlPFC. These findings point again to a superior role of the right dlPFC for processes of planning proper because significantly reduced initial thinking time after left cathodal/right anodal tDCS can be explained by both a possible release of transcallosal inhibition from left to right dlPFC following cathodal inhibition of left dlPFC (but see Lang et al., 2004) as well as an enhancement by concurrent anodal facilitation of right dlPFC. Based on the above considerations on the comparability of frontal and motor tDCS (Jacobson et al., 2012) and the transcallosal mechanisms of tDCS (Lang et al., 2004), the latter right-hemispheric anodal mode of action may be more likely. Current accounts on the complementarity between left and right prefrontal functioning differentially associate processes of task/criterion setting and monitoring with relatively stronger involvements of left and right lateral prefrontal cortex, respectively (e.g., Shallice, 2002; Stuss & Alexander, 2007; Vallesi, McIntosh, Crescentini, & Stuss, 2012). Processing speed in complex cognitive tasks may hence be related to left dlPFC criterion setting by global requirements to adjust speed-accuracy tradeoffs (Vallesi et al., 2012), as may also be the case in the ToL. For instance, by using exactly the same tDCS protocol as in the present study during a risky decision-making task, Fecteau et al. (2007) observed decreased decision times during concurrent left cathodal/right anodal dlPFC stimulation and, conversely, increased decision times during concurrent left anodal/right cathodal stimulation. Furthermore, increased accuracy (but to some extent also reduced response times, Marshall, Molle, Siebner, & Born, 2005) has been reported after anodal stimulation of left dlPFC for working memory tasks (Fregni et al., 2005; Ohn et al., 2008) as well as for verbal fluency tasks (Iyer et al., 2005). In the present study, a disruption of left dlPFC function may have led to a failure of task-related adjustments to accuracy demands and, in consequence, may have allowed for faster responses, whereas ensuing effects on accuracy might have been marginal in the applied simple three-move ToL

138

K. Heinze et al. / Biological Psychology 102 (2014) 130–140

problems. However, emphasizing cathodal inhibitory effects of left tDCS contradicts the above-mentioned assumptions of a predominantly anodal mode of action. An attribution of present decreases in planning latency to anodal facilitation of right dlPFC monitoring processes may also be feasible and perhaps more likely. A further issue of particular interest concerns the question why left anodal/right cathodal dlPFC stimulation did not cause behavioral costs in initial thinking time as observed after cTBS over right mid-dlPFC (cf. Kaller, Heinze, et al., 2013). A plain explanation refers to the differences between the two stimulation methods (see Section 4.1). Even the replication of behavioral effects (as for cTBS over left mid-dlPFC vs. left cathodal/right anodal tDCS over dlPFC) does not imply that the supposed underlying neurophysiological mechanisms are self-evidently the same. In addition, the present absence of an increased initial thinking time following left anodal/right cathodal dlPFC stimulation contradicts neither previous cTBS findings (Kaller, Heinze, et al., 2013) nor previously reported dissociable contributions of left and right mid-dlPFC toward processes of internalization and planning proper, respectively (Kaller et al., 2011; Ruh et al., 2012). The interpretation of the previous cTBS effects was built upon assumed differences between the effective local and remote modes of action following stimulation of left versus right mid-dlPFC: Decreased initial thinking time after left cTBS was attributed to transcallosal disinhibition of (remote) right middlPFC, whereas increased initial thinking time after right cTBS was attributed to disrupted functioning of (in this case local) right middlPFC. Given the above assumptions of a mainly anodal mode of action, (local) effects of facilitatory anodal tDCS over right dlPFC may have hence been sufficiently strong to cause a beneficial reduction of planning latencies, whereas facilitatory anodal tDCS over left dlPFC may have not been effective (enough) to intensify transcallosal inhibition of (remote) right dlPFC (see also Lang et al., 2004) that would have otherwise entailed a detrimental increase in planning latencies. Taken together, further pinpointing the effective neural (and cognitive) origins of the overtly observable behavioral effects following tDCS over left and right dlPFC in future studies would considerably benefit from the additional inclusion of direct measures on changes in (local and remote) brain activation and functional connectivity following (mid-)dlPFC stimulation. 4.3. Impact of eye movement data on the interpretation of stimulation effects In the present study, a reduction of initial thinking time following left cathodal/right anodal dlPFC stimulation was paralleled by a shorter duration of the last gaze before solution execution. Hayhoe and Ballard (2005) proposed that fixation durations are highly dependent on the specific task and the amount and nature of the information collected. In previous work, the duration of the last gaze before movement execution could be linked to processes of planning proper (Kaller et al., 2009; Nitschke et al., 2012) that in turn were attributed to the right mid-dlPFC (Kaller et al., 2011; Ruh et al., 2012). Assuming a primarily anodal mode of action (see above), the here observed reduced latency of actual planning processes (as reflected by the duration of the last gaze before solution execution) caused by anodal facilitation of right dlPFC would hence fit well to both a serial model of early internalization and later planning processes as well as a functional localization of planning proper toward right (mid-)dlPFC. This view is also supported by recent electro-encephalographical (EEG) data showing that brain activation during initial thinking time shifts from a left frontal focus at early stages to a right frontal focus at later stages (Byrd et al., 2011). A shortening of final evaluation processes (cf. Hodgson et al., 2000) in terms of comparing mental representations of externally predefined goals with internally generated outcomes may also be

associated with an anodal facilitation of right dlPFC monitoring processes (see above). Likewise, the here observed changes in the number of gaze shifts between start and goal state following left anodal/right cathodal dlPFC stimulation can be accommodated with a predominant role of left (mid-)dlPFC for processes of internalization in terms of identifying, matching, and integrating relevant information between start and goal state (Kaller et al., 2011; Ruh et al., 2012). Yet, besides the need for isolating a cognitive candidate process that can globally account for this finding, another major question concerns why an anodal enhancing stimulation provokes behaviorally opposite changes in terms of effective processing costs – namely a shorter duration after right dlPFC stimulation and more gaze shifts after left dlPFC stimulation. Here, further studies are needed to investigate the behavioral function of the fMRI double dissociation shown by Kaller et al. (2011) and Ruh et al. (2012) – a causal relationship or solely an epiphenomenon such as a secondary accumulating effect. In this respect, it is also important to consider possible effects of individual ability on the amount of activation needed for successful task completion: Unterrainer et al. (2004) found a linear increase of activation specifically in the right dlPFC with better planning performance during the initial thinking time. Transferred to the present planning durations – although in the context of easier problems – a shorter duration after supposed enhanced right dlPFC activation might indeed reflect a better performance. However, manipulating excitability of underlying neural tissue and measuring hemodynamic changes in the same area do not necessarily imply the same mechanisms. For example, imaging studies of stimulation effects partly reveal activation changes of the same direction after facilitating as well as inhibitory stimulation (Knoch, Treyer, et al., 2006; Rounis et al., 2005). 4.4. Limitations It should be noted that the reduced focality of the tDCS electrodes as well as their placement based on standard positions of the 10-20 system rather than on individual neuroanatomical landmarks (cf. Kaller, Heinze, et al., 2013) entail the risk of stimulation beyond dlPFC, particularly in the frontal eye fields (FEF), which might have biased the obtained eye movements. For example, Kanai, Muggleton, and Walsh (2012) quantified latencies of saccades in a horizontal prosaccade task after bilateral FEF tDCS and found a shortening of latencies of contralateral saccades after anodal stimulation. However, in the present experiment, even if the FEF were actually stimulated, the vertical arrangement of tower states and the balancing of the horizontal arrangement of balls within tower configurations (based on spatial permutations, see Section 2) render a side-specific influence on saccades unlikely. In addition, potential biases based on saccade-dependent effects would be expected to occur in all instances of gaze during the initial thinking time and not only in the duration of the last gaze before movement execution. Furthermore, the hiatus in the first offline period due to the recalibration break (Fig. 1C) may have led to an underestimation of the tDCS after-effects on initial thinking times and the eyemovement variables (last gaze duration, number of gaze shifts). However, given the primarily quantitative changes of differential stimulation effects across the online and the two offline periods, it seems unlikely that the hiatus has prevented the detection of a qualitatively completely different pattern in the first offline period. In addition, the asymmetric cTBS effects in our previous study were likewise short-lasting (see supplementary analyses in Kaller, Heinze, et al., 2013). Finally, a progressive decrease across periods (online, offline 1, offline 2) was evident for all dependent measures (Figs. 2, 4, 5) that was however independent of the stimulation and hence

K. Heinze et al. / Biological Psychology 102 (2014) 130–140

conformed well to similar findings of unspecific task learning effects in previous studies (e.g. Dockery et al., 2009; Kaller et al., 2011; Kaller, Heinze, et al., 2013). In fact, comprehensive analyses of the changes in initial thinking times across 12 blocks of repeated presentations of eight structurally unique three-move problems in different color- and peg-permutated isoforms (as applied here; cf. Section 2.4) have shown that latency effects of experimental manipulations of task demands on processes of internalization and planning proper remained constant despite progressively decreasing initial thinking times (see supplementary analyses in Kaller et al., 2011). 4.5. Future directions Recent work on the neuroanatomical correlates of interindividual differences in planning ability (Kaller et al., 2012; Kaller, Reisert, et al., in press) indicates that the organizational principles underlying a functional lateralization in mid-dlPFC may be more complex than current theorizing accounts for. For instance, (i) overall planning ability was recently found to be specifically linked to morphological features such as the gray matter density in homolog mid-dlPFCs (Kaller et al., 2012) as well as their transcallosal connectivity (Kaller, Reisert, et al., in press), and (ii) this link was shown to be significantly moderated by additional variables such as age (Kaller et al., 2012; Kaller, Reisert, et al., in press) and to some extent also sex (Kaller et al., 2012). Furthermore, Voineskos et al. (2010) demonstrated that the integrity of transcallosal fibers connecting left and right (mid-)dlPFC mediates TMS-induced signal propagation. Taken together, the specificity and effectiveness of brain stimulation approaches tapping the lateralization of middlPFC homologs in planning may hence rely on several sources of between-subject variation that should be accounted for in future studies. Acknowledgements This work was supported by grants of the German Federal Ministry of Education and Research (BMBF; grant number 01GW0710) and the Brain-Links Brain-Tools Cluster of Excellence funded by the German Research Foundation (DFG; grant number EXC 1086). The authors thank Stefan Spiteri for assistance in data acquisition and Lena Köstering, Sandra Loosli, Lora Minkova, Jessica Peter, and Elisa Scheller for helpful discussions of the manuscript. References Byrd, D. L., Case, K. H., & Berg, W. K. (2011). Planning: Fixed-foreperiod event-related potentials during the Tower of London task. Neuropsychologia, 49(5), 1024–1032. Cazalis, F., Valabregue, R., Pelegrini-Issac, M., Asloun, S., Robbins, T. W., & Granon, S. (2003). Individual differences in prefrontal cortical activation on the Tower of London planning task: Implication for effortful processing. European Journal of Neuroscience, 17, 2219–2225. Crescentini, C., Seyed-Allaei, S., Vallesi, A., & Shallice, T. (2012). Two networks involved in producing and realizing plans. Neuropsychologia, 50, 1521–1535. Dagher, A., Owen, A. M., Boecker, H., & Brooks, D. J. (1999). Mapping the network for planning: A correlational PET activation study with the Tower of London task. Brain, 122, 1973–1987. Datta, A., Elwassif, M., Battaglia, F., & Bikson, M. (2008). Transcranial current stimulation focality using disc and ring electrode configurations: FEM analysis. Journal of Neural Engineering, 5, 163–174. Dockery, C. A., Hueckel-Weng, R., Birbaumer, N., & Plewnia, C. (2009). Enhancement of planning ability by transcranial direct current stimulation. The Journal of Neuroscience, 29(22), 7271–7277. Fecteau, S., Knoch, D., Fregni, F., Sultani, N., Boggio, P., & Pascual-Leone, A. (2007). Diminishing risk-taking behavior by modulating activity in the prefrontal cortex: A direct current stimulation study. The Journal of Neuroscience, 27(46), 12500–12505. Fregni, F., Boggio, P., Nitsche, M., Bermpohl, F., Antal, A., Feredoes, E., et al. (2005). Anodal transcranial direct current stimulation of prefrontal cortex enhances working memory. Experimental Brain Research, 166(1), 23–30.

139

Gandiga, P. C., Hummel, F. C., & Cohen, L. G. (2006). Transcranial DC stimulation (tDCS): A tool for double-blind sham-controlled clinical studies in brain stimulation. Clinical Neurophysiology, 117(4), 845–850. Hayhoe, M., & Ballard, D. (2005). Eye movements in natural behavior. Trends in Cognitive Sciences, 9(4), 188–194. Hodgson, T. L., Bajwa, A., Owen, A. M., & Kennard, C. (2000). The strategic control of gaze direction in the Tower of London task. Journal of Cognitive Neuroscience, 12(5), 894–907. Hodgson, T. L., Tiesman, A., Owen, A. M., & Kennard, C. (2002). Abnormal gaze strategies during problem solving in Parkinson’s disease. Neuropsychologia, 40, 411–422. Homan, R. W., Herman, J., & Purdy, P. (1987). Cerebral location of international 10-20 system electrode placement. Electroencephalography and Clinical Neurophysiology, 66(4), 376–382. Huang, Y.-Z., Edwards, M. J., Rounis, E., Bhatia, K. P., & Rothwell, J. C. (2005). Theta burst stimulation of the human motor cortex. Neuron, 45(2), 201–206. Huddy, V. C., Hodgson, T. L., Kapasi, M., Mutsatsa, S. H., Harrison, I., Barnes, T. R., et al. (2007). Gaze-strategies during planning in first-episode psychosis. Journal of Abnormal Psychology, 116, 589–598. Iyer, M. B., Mattu, U., Grafman, J., Lomarev, M., Sato, S., & Wassermann, E. M. (2005). Safety and cognitive effect of frontal DC brain polarization in healthy individuals. Neurology, 64(5), 872–875. Jacobson, L., Koslowsky, M., & Lavidor, M. (2012). tDCS polarity effects in motor and cognitive domains: A meta-analytical review. Experimental Brain Research, 216(1), 1–10. Jasper, H. H. (1958). Report of the committee on methods of clinical examination in electroencephalography. Electroencephalography and Clinical Neurophysiology, 10, 370–375. Kaller, C. P., Heinze, K., Mader, I., Unterrainer, J. M., Rahm, B., Weiller, C., et al. (2012). Linking planning performance and gray matter density in mid-dorsolateral prefrontal cortex: Moderating effects of age and sex. NeuroImage, 63(3), 1454–1463. Kaller, C. P., Heinze, K., Frenkel, A., Läppchen, C. H., Unterrainer, J. M., Weiller, C., et al. (2013). Differential impact of continuous theta-burst stimulation over left and right DLPFC on planning. Human Brain Mapping, 34(1), 36–51. Kaller, C. P., Rahm, B., Bolkenius, K., & Unterrainer, J. M. (2009). Eye movements and visuospatial problem solving: Identifying separable phases of complex cognition. Psychophysiology, 46(4), 818–830. Kaller, C. P., Rahm, B., Spreer, J., Weiller, C., & Unterrainer, J. M. (2011). Dissociable contributions of left and right dorsolateral prefrontal cortex in planning. Cerebral Cortex, 21(2), 307–317. Kaller, C. P., Reisert, M., Katzev, M., Umarova, R., Mader, I., Hennig, J., et al. (2013). Predicting planning performance from structural connectivity between left and right mid-dorsolateral prefrontal cortex: Moderating effects of age during post-adolescence and mid-adulthood. Cerebral Cortex, http://dx.doi.org/10.1093/cercor/bht276 [in press] Epub ahead of print Kanai, R., Muggleton, N. G., & Walsh, V. (2012). Transcranial direct current stimulation (tDCS) of the frontal eye fields during pro- and antisaccade tasks. Frontiers in Psychiatry, 3(45.) http://dx.doi.org/10.3389/fpsyt.2012.00045. Epub 2012 May 10 Kapur, N. (1996). Paradoxical functional facilitation in brain-behaviour research. A critical review. Brain, 119(Pt 5), 1775–1790. Knoch, D., Gianotti, L. R. R., Pascual-Leone, A., Treyer, V., Regard, M., Hohmann, M., et al. (2006). Disruption of right prefrontal cortex by low-frequency repetitive transcranial magnetic stimulation induces risk-taking behavior. The Journal of Neuroscience, 26(24), 6469–6472. Knoch, D., Treyer, V., Regard, M., Müri, R. M., Buck, A., & Weber, B. (2006). Lateralized and frequency-dependent effects of prefrontal rTMS on regional cerebral blood flow. NeuroImage, 31(2), 641–648. Lang, N., Nitsche, M. A., Paulus, W., Rothwell, J. C., & Lemon, R. N. (2004). Effects of transcranial direct current stimulation over the human motor cortex on corticospinal and transcallosal excitability. Experimental Brain Research, 156, 439–443. Lehrl, S. (1999). Mehrfachwahl-Wortschatz-Intelligenztest MWT-B. Balingen, Germany: Spitta Verlag. Liversedge, S. P., & Findlay, J. M. (2000). Saccadic eye movements and cognition. Trends in Cognitive Sciences, 4(1), 6–14. Loftus, G. R., & Mackworth, N. H. (1978). Cognitive determinants of fixation location during picture viewing. Journal of Experimental Psychology, 4(4), 565–572. Marshall, L., Molle, M., Siebner, H., & Born, J. (2005). Bifrontal transcranial direct current stimulation slows reaction time in a working memory task. BMC Neuroscience, 6(1), 23. Morris, R. G., Ahmed, S., Syed, G. M., & Toone, B. K. (1993). Neural correlates of planning ability: Frontal lobe activation during the tower of London test. Neuropsychologia, 31(12), 1367–1378. Morris, R., & Ward, G. (2005). The cognitive psychology of planning. Hove: Psychology Press. Newman, S. D., Carpenter, P. A., Varma, S., & Just, M. A. (2003). Frontal and parietal participation in problem solving in the Tower of London: fMRI and computational modeling of planning and high-level perception. Neuropsychologia, 41, 1668–1682. Nitsche, M. A., Fricke, K., Henschke, U., Schlitterlau, A., Liebetanz, D., Lang, N., et al. (2003). Pharmacological modulation of cortical excitability shifts induced by transcranial direct current stimulation in humans. The Journal of Physiology, 553(1), 293–301.

140

K. Heinze et al. / Biological Psychology 102 (2014) 130–140

Nitsche, M. A., Nitsche, M. S., Klein, C. C., Tergau, F., Rothwell, J. C., & Paulus, W. (2003). Level of action of cathodal DC polarisation induced inhibition of the human motor cortex. Clinical Neurophysiology, 114(4), 600–604. Nitsche, M. A., & Paulus, W. (2000). Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation. The Journal of Physiology, 527(3), 633–639. Nitschke, K., Ruh, N., Kappler, S., Stahl, C., & Kaller, C. P. (2012). Dissociable stages of problem solving (I): Temporal characteristics revealed by eye-movement analyses. Brain and Cognition, 80(1), 160–169. Nitsche, M. A., Seeber, A., Frommann, K., Klein, C. C., Rochford, C., Nitsche, M. S., et al. (2005). Modulating parameters of excitability during and after transcranial direct current stimulation of the human motor cortex. The Journal of Physiology, 568(1), 291–303. Ohn, S. H., Park, C.-I., Yoo, W.-K., Ko, M.-H., Choi, K. P., Kim, G.-M., et al. (2008). Timedependent effect of transcranial direct current stimulation on the enhancement of working memory. NeuroReport, 19(1), 43–47. Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9(1), 97–113. Owen, A. M., Doyon, J., Petrides, M., & Evans, A. C. (1996). Planning and spatial working memory: A positron emission tomography study in humans. European Journal of Neuroscience, 8, 353–364. Owen, A. M., Doyon, J., Dagher, A., Sadikot, A., & Evans, A. C. (1998). Abnormal basal ganglia outflow in Parkinson’s disease identified with PET. Implications for higher cortical functions. Brain, 121, 949–965. Priori, A., Hallett, M., & Rothwell, J. C. (2009). Repetitive transcranial magnetic stimulation or transcranial direct current stimulation? Brain Stimulation, 2(4), 241–245. Ridding, M. C., & Ziemann, U. (2010). Determinants of the induction of cortical plasticity by non-invasive brain stimulation in healthy subjects. The Journal of Physiology, 588(13), 2291–2304. Rounis, E., Lee, L., Siebner, H. R., Rowe, J. B., Friston, K. J., Rothwell, J. C., et al. (2005). Frequency specific changes in regional cerebral blood flow and motor system connectivity following rTMS to the primary motor cortex. NeuroImage, 26(1), 164–176. Rowe, J. B., Owen, A. M., Johnsrude, I. S., & Passingham, R. E. (2001). Imaging the mental components of a planning task. Neuropsychologia, 39, 315–327. Ruh, N., Rahm, B., Unterrainer, J. M., Weiller, C., & Kaller, C. P. (2012). Dissociable stages of problem solving (II): First evidence for process-contingent temporal order of activation in dorsolateral prefrontal cortex. Brain and Cognition, 80(1), 170–176. Salmaso, D., & Longoni, A. M. (1985). Problems in the assessment of hand preference. Cortex, 21(4), 533–549. Shallice, T. (1982). Specific impairments of planning. Philosophical transactions of the Royal Society of London. Series B, Biological Sciences, 298(1089), 199–209.

Shallice, T. (2002). Fractionation of the supervisory system. In D. Stuss, & R. Knight (Eds.), Principles of frontal lobe function (pp. 261–277). Oxford: Oxford University Press. Spreen, O., & Strauss, E. (1998). A compendium of neuropsychological tests. New York: Oxford University Press. Stagg, C. J., Best, J. G., Stephenson, M. C., O’Shea, J., & Wylezinska, M. (2009). Polaritysensitive modulation of cortical neurotransmitters by transcranial stimulation. Journal of Neuroscience, 29(16), 5202–5206. Stagg, C. J., Jayaram, G., Pastor, D., Kincses, Z. T., Matthews, P. M., & Johansen-Berg, H. (2011). Polarity and timing-dependent effects of transcranial direct current stimulation in explicit motor learning. Neuropsychologia, 49(5), 800–804. Stagg, C. J., & Nitsche, M. A. (2011). Physiological basis of transcranial direct current stimulation. The Neuroscientist, 17(1), 37–53. Stagg, C. J., Wylezinska, M., Matthews, P. M., Johansen-Berg, H., Jezzard, P., Rothwell, J. C., et al. (2009). Neurochemical effects of theta burst stimulation as assessed by magnetic resonance spectroscopy. Journal of Neurophysiology, 101(6), 2872–2877. Stuss, D. T., & Alexander, M. P. (2007). Is there a dysexecutive syndrome? Philosophical Transactions of the Royal Society of London: Biological Sciences, 362B, 901–915. Unterrainer, J. M., Rahm, B., Kaller, C. P., Ruff, C. C., Spreer, J., Krause, B. J., et al. (2004). When planning fails: Individual differences and error-related brain activity in problem solving. Cerebral Cortex, 14(12), 1390–1397. Unterrainer, J. M., & Owen, A. M. (2006). Planning and problem solving: From neuropsychology to functional neuroimaging. Journal of Physiology, 99(4–6), 308–317. Vallesi, A., McIntosh, A. R., Crescentini, C., & Stuss, D. T. (2012). fMRI investigation of speed-accuracy strategy switching. Human Brain Mapping, 33(7), 1677–1688. Van den Heuvel, O. A., Groenewegen, H. J., Barkhof, F., Lazeron, R. H., van Dyck, R., & Veltman, D. J. (2003). Frontostriatal system in planning complexity: A parametric functional magnetic resonance version of Tower of London task. Neuroimage, 18, 367–374. Voineskos, A. N., Farzan, F., Barr, M. S., Lobaugh, N. J., Mulsant, B. H., Chen, R., et al. (2010). The role of the corpus callosum in transcranial magnetic stimulation induced interhemispheric signal propagation. Biological psychiatry, 68(9), 825–831. Wagner, G., Koch, K., Reichenbach, J. R., Sauer, H., & Schlosser, R. G. (2006). The special involvement of the rostrolateral prefrontal cortex in planning abilities: An event-related fMRI study with the Tower of London paradigm. Neuropsychologia, 44, 2337–2347. Williams, J. A., Pascual-Leone, A., & Fregni, F. (2010). Interhemispheric modulation induced by cortical stimulation and motor training. Physical Therapy, 90(3), 398–410. Ziemann, U., Paulus, W., Nitsche, M. A., Pascual-Leone, A., Byblow, W. D., Berardelli, A., et al. (2008). Consensus: Motor cortex plasticity protocols. Brain Stimulation, 1(3), 164–182.