Enhancing switching abilities: Improving practice effect by stimulating the dorsolateral pre frontal cortex

Neuroscience 313 (2016) 92–98

ENHANCING SWITCHING ABILITIES: IMPROVING PRACTICE EFFECT BY STIMULATING THE DORSOLATERAL PRE FRONTAL CORTEX Y. TAYEB AND M. LAVIDOR *

trials usually demand longer times than repeat ones (switching cost), which also demand longer times than trials in a single task block (mixing cost; see Monsell, 2003 for a review). Despite many years of research, an agreement about the exact cognitive mechanisms taking part in task switching is still absent. Nevertheless, it is widely accepted that reconfigurations of task sets (e.g., Meiran, 1996; Mayr and Keele, 2000) as well as overcoming proactive interference of previous task (e.g., Allport et al., 1994) are involved (for other theories see Kiesel et al., 2010). Considering these cognitive tasks, it is not surprising that several neuroimaging studies concluded that task switching appeared to be executed by a predominantly fronto-parietal network that includes the dorsolateral prefrontal cortex (DLPFC), inferior frontal gyrus and inferior lobe, mostly in the left hemisphere (Kim et al., 2012; Witt and Stevens, 2013). Additional support comes from a lesion study which showed that damage to frontal regions resulted in task-switching impairments (Aron et al., 2004a). Their findings suggest a different role for left and right hemispheres, mapping response time impairments mostly to the left hemisphere and accuracy to the right one. While neuroimaging or lesion studies help us better understand brain areas involved in cognitive processing, other techniques aim to intervene in these processes and enhance them. Transcranial direct current stimulation (tDCS) is a noninvasive, painless cortical stimulation technique which can increase or decrease brain excitability by adjusting the polarity of a weak current flow (Nitsche and Paulus, 2000). Many studies use this technique in order to manipulate a variety of cognitive abilities, such as memory (e.g., Tseng et al., 2012), attention (e.g., Moos et al., 2012), language abilities (e.g., Flo¨el et al., 2008), and executive functions (e.g., Fregni et al., 2005; Karim et al., 2010). Considering the unique advantages of tDCS, and, more specifically, in light of the possible lateralization issues in task switching (Aron et al., 2004a), we designed a tDCS task-switching study. First attempts to manipulate task switching with tDCS achieved initial, but not conclusive results (Leite et al., 2012). In addition, to the best of our knowledge, there were no attempts to examine the effect of tDCS stimulation on task switching for more than a single session. In recent years, adding brain stimulation such as tDCS to a regular training protocol was found to reduce training time and increase proficiency (e.g., Parasuraman and McKinley, 2014). The aim of the

Department of Psychology and the Gonda Brain Research Center, Bar Ilan University, Israel

Abstract—Task switching is our ability to abandon an old, irrelevant task in order to perform a new, more relevant one. Data from neuropsychology and neuroimaging studies indicate hemispheric asymmetries in task switching, however the neural mechanisms subtending switching, and in particular protocols to improve switching abilities are yet to be established. The present study aimed to assess hemispheric asymmetry and practice effects in task switching by using transcranial direct current stimulation (tDCS). To this end, tDCS has been applied to the dorsolateral prefrontal cortex (DLPFC) of both hemispheres while subjects were performing a well-established task-switching paradigm. The task was repeated three times in three separate sessions in order to test practice effects with and without stimulation. Results show that increased hemispheric asymmetry in dorsolateral prefrontal areas improved switching performance as measured by a better practice effect, compared to sham condition. Our results support the hypothesis of dynamic hemispheric asymmetry in task switching and reinforce the notion of utilizing brain stimulation with traditional training methods in order to enhance cognitive abilities. Ó 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Key words: task switching, practice effect, tDCS, DLPFC.

INTRODUCTION Mind-set shifting is a central executive function which is needed when one switches between tasks (Miyake et al., 2000). In order to study this ability, researchers often use task-switching paradigm (e.g., Jersild, 1927; Allport et al., 1994; Rogers and Monsell, 1995). In typical task-switching experiments, participants perform a discrete task in each trial. In some trials, the task changes (switch trials), and on others it does not (repeat trials). Some blocks, however, contain only one task, making switching unnecessary (single task trials). Response times vary across trial types. Within a mixed block, switch *Corresponding author. Tel: +972-3-5318171. E-mail address: [email protected] (M. Lavidor). Abbreviations: ANOVA, analysis of variance; DLPFC, dorsolateral prefrontal cortex; LA, left anodal; PFC, prefrontal cortex; POR, percentage of reduction; RA, right anodal; tDCS, transcranial direct current stimulation. http://dx.doi.org/10.1016/j.neuroscience.2015.11.050 0306-4522/Ó 2015 IBRO. Published by Elsevier Ltd. All rights reserved. 92

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present study was therefore to investigate whether using tDCS to modulate activity in the DLPFC can enhance task-switching practice effects. We were especially interested in the effect of left DLPFC stimulation on practicing task switching based on Aron et al. (2004a) lesion studies. We used a well-known task-switching paradigm for three sessions and applied anodal tDCS to the right or the left prefrontal cortex, coupled with cathodal tDCS over the contralateral region.

stimulus was presented on the screen until participant’s response. If the response was not detected after three seconds or in case of a faulty response, a red cross appeared in the screen center until the participant pressed the right key. After 50 ms, the next trial began (Fig. 1). Participants were instructed to respond as fast and as accurately as possible.

EXPERIMENTAL PROCEDURES

Direct current was induced by two saline-soaked surface sponge electrodes (16 cm2) and delivered by a batterydriven, constant current stimulator (Starstim, Neuroelectrics, Barcelona, Spain). Two homotopic regions were selected as cortical targets: left PFC and right PFC. tDCS was delivered for 20 min, starting 10 min before the paradigm began. The active electrodes were placed over F3 (for the left PFC) and F4 (for the right PFC) according to the 10–20 electrode system and their polarity was differentiated according to the specific condition.

Participants Forty two healthy university students (mean age: 23.9; 33 females) participated in the study. All were right-handed with normal or corrected to normal vision, without present or past history of neurological or psychiatric disorders and were not on chronic medications. All participants completed consent forms prior to their inclusion in the study. The study was approved by the local ethics committee and was conducted in accordance with the Declaration of Helsinki guidelines.

tDCS

RESULTS Procedure Participants came to the lab three times within a week and performed the parity/magnitude task-switching paradigm while receiving a specific stimulation montage that was randomly assigned to them in their first session. There were three stimulations montages: Left anodal (LA)/right cathodal tDCS with 1.5 mA intensity (LA; n = 10), Left cathodal/right anodal (RA) tDCS with 1.5 mA intensity (RA; n = 9), and sham (n = 23). All stimulations began with a current ramp up for 30 s. The sham condition applied the same electrode configuration but consisted only of a 30-s ramp up and then 30-s ramp down with the electrodes remaining on the head for the entire task duration, keeping participant’s physical feeling identical to the active conditions while receiving no real current. Parity/magnitude task-switching paradigm The main paradigm consisted of a number stimulus which was always presented in the screen center surrounded by a colored square. The colored square was used as a visual cue, instructing the participants what task to perform. With blue cues, the participant was required to respond to the magnitude feature of the stimuli, pressing the ‘‘Q” key for numbers smaller than five and the ‘‘P” key for numbers bigger than five. Gray cues indicated that the task was to judge parity. Participants were instructed to press the ‘‘Q” key for odd numbers and the ‘‘P” key for even ones. Both responses were univalent. The left index finger was used to press the ‘‘Q” key and the right index finger was used to press the ‘‘P” key when needed, regardless of the task to perform. The paradigm included two single-task practice blocks, followed by nine experimental blocks (five mixed and four single blocks) in a mixed-single sequence. There were 32 trials per block. Each block started with a fixation cross (100 ms) followed by a number stimulus surrounded by a colored cue (background color). The

None of the participants experienced adverse effects during or after stimulation. Participants sometimes felt a slight itching sensation under the electrodes that disappeared after few seconds. Subjects in the sham stimulation group reported the same initial itching sensation. The results of one participant were excluded due to technical problems during task recording. The first trial in a block and trials in which response time was longer than 3000 ms or shorter than 300 ms were excluded from analysis (about 1.5% of all trials). Response time analyses were only conducted for correct responses. Since switching cost is calculated by both switch and repeat trials, its improvement can be a result of responding to switch trials quicker as well as responding to repeat trials slower. To contend with this possible confound we compared practice effect in switch and repeat trials separately. First, two one-way ANOVAs revealed no significant enhancement of any stimulation montage following a single session, for both switch trials response time (F(2,40) = 1.21, p = ns, partial g2 = 0.06) and repeat trials response time (F(2,40) = 1.55, p = ns, partial g2 = 0.07). Then, a percentage of reduction in RT (POR) variable was created for both switch and repeat trials. POR formula was POR = (session 1x – session Nx)/ session 1x. The formula calculated the difference between the first session and a certain session N (divided by RT in the first session). The same formula was applied for switch trials, where the ratio was calculated for mean RT of switch trials, and similarly for repeat trials. Table 1 shows the PORs for each session, both for switch and repeat trials, grouped for all stimulation conditions. To investigate the effect of tDCS condition, practice and trial type, a mixed design MANOVA with repeated measures was conducted. Stimulation montage (RA, LA, sham) and practice (first, second, third session) were used as independent variables, and repeat and switch trial PORs and accuracy as dependent variables.

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Fig. 1. Schematic representation of the experimental design. Each participant started to perform the parity/magnitude task-switching paradigm after receiving 10 min of stimulation. Stimulation continued throughout the paradigm.

Table 1. Percentage of reduction in response time (PORs) for both switch and repeat trials compared to baseline (session 1) Variable

Session 2

Switch trials Repeat trials

Session 3

M

SD

M

SD

14.56 9.35

7.6 7.27

20.25 12.04

7.99 8.09

Table 2b. Response time for both switch and repeat trials in every session of practicing for every stimulation condition. LA – anodal stimulation of left DLPFC with cathodal stimulation of the right DLPFC; RA – anodal stimulation of the right DLPFC with cathodal stimulation of the left DLPFC Condition

LA

Table 2a. Percentage of reduction in response time (PORs) for both switch and repeat trials in session two and three for every stimulation condition. LA – anodal stimulation of left DLPFC with cathodal stimulation of the right DLPFC; RA – anodal stimulation of the right DLPFC with cathodal stimulation of the left DLPFC Condition

Variable

Session 2

Session 3

M

SD

M

SD

LA

Switch trials POR Repeat trials POR

17.71 14.43

9.94 8.72

26.54 18.2

7.17 7.24

RA

Switch trials POR Repeat trials POR

17.58 11.66

5.62 4.89

22.14 14.23

6.27 7.28

Sham

Switch trials POR Repeat trials POR

11.87 6.02

6.13 5.56

16.5 8.25

6.94 6.77

Analysis revealed a significant multivariate effect for practice (F(6,148) = 39.21, p < 0.001, Wilks’K = 0.15, partial g2 = 0.61), as well as for the interaction of practice and stimulation montage (F(12,196) = 2.88, p = 0.001, Wilks’K = 0.65, partial g2 = 0.13). A series of univariate analyses showed a significant main effect of stimulation montage on both repeat trials POR (F(2,38) = 9.88, p < 0.001, partial g2 = 0.34) and switch trials POR (F(2,38) = 6.21, p = 0.005, partial g2 = 0.25). The interaction of stimulation montage and practice was also significant for both repeat trials POR (F(2,38) = 8.26, p = 0.001, partial g2 = 0.3) and switch trials POR (F(2,38) = 7.63, p = 0.005, partial g2 = 0.28). Full description of PORs of switch and repeat trials on the second and third sessions, as well as the raw data per session are reported in Tables 2a and 2b. No significant interaction of practice and stimulation montage was found for accuracy (F(2,38) = 1.91, p = ns, partial g2 = 0.09).

RA

Sham

Variable

Session 1

Session 2

Session 3

M

SD

M

SD

M

SD

Switch trials POR Repeat trials POR

1092

180

895

151

801

140

766

104

650

69

623

66

Switch trials POR Repeat trials POR

1020

230

836

177

787

147

716

102

631

88

609

64

Switch trials POR Repeat trials POR

1006

90

888

104

842

112

775

72

730

91

711

81

In order to examine whether LA stimulation was more beneficial than right one regarding the POR for both switch and repeat trials, a planned contrast was made for the second and third sessions individually. On the second session, LA stimulation improved POR more than RA stimulation and sham for repeat (t(40) = 2.43, p = 0.02, Cohen’s d = 0.77), but not switch trials (t(40) = 1.16, p = ns, Cohen’s d = 0.37). Furthermore, on the third session, LA stimulation had a better impact over POR compared with RA stimulation and sham for both repeat (t(40) = 2.76, p = 0.009, Cohen’s d = 0.87) and switch trials (t(40) = 2.92, p = 0.006, Cohen’s d = 0.92). Additionally, RA stimulation generated better POR scores than sham for both repeat (t(40) = 2.17, p = 0.04, Cohen’s d = 0.69) and switch trials (t(40) = 2.08, p = 0.04, Cohen’s d = 0.66). POR rates by stimulation montage changing for switch and repeat trials are illustrated in Fig. 2a, b. These results together with an insignificant difference at the first session across all three conditions suggest that overall, LA stimulation was most beneficial for improving mindset shifting as depicted in best-enhanced practice performance on both repeat and switch trials and that this effect is an accumulated one.

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Fig. 2. The progress of the average percentage of reduction in response time for each stimulation group in three sessions for switch trials (panel A) and repeat trials (panel B). Error bars indicate SEM. LA – anodal stimulation of left DLPFC with cathodal stimulation of the right DLPFC; RA – anodal stimulation of the right DLPFC with cathodal stimulation of the left DLPFC.

A possible criticism might be that our results indicate a general left DLPFC stimulation effect on task acquisition, rather than a specific mind-set shifting effect. To refute this argument, a two-way mixed design ANOVA with practice and stimulation montage as independent variables and single task RT as a dependent variable was conducted. If LA stimulation is not specific to mind-set shifting, we should expect a main effect for stimulation montage and a significant interaction between them. However, in accordance with our interpretation, stimulation montage had no significant effect on single task performance (F(2,40) = .14,

p = ns, partial g2 = 0.007) and no significant interaction between stimulation montage and practice (F(4,80) = 1.34, p = ns, partial g2 = 0.06).

DISCUSSION In the present study we found that modulation of the activity in the DLPFC facilitated mind-set shifting. Overall, healthy participants who received anodal stimulation over the left DLPFC coupled with cathodal stimulation over the right DLPFC, showed greater improvement in both their ability to switch between

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tasks and their ability to repeat the same task in a multiple task set environment over the course of three sessions then participants in sham condition. In the same way but to a lesser extent, anodal stimulation over the right DLPFC coupled with cathodal stimulation over the left DLPFC showed the same results. This pattern of improvement was not seen regarding single-task trials for either montage, suggesting that stimulation was specific to mind-set shifting components rather than boosting all task components. In addition, accuracy was high for all conditions and was not differentiated by stimulation condition, maybe due to a ceiling effect. Our findings reinforces previous attempts to utilize brain stimulation to modify task switching (e.g., Leite et al., 2011, 2012) and support previous evidence coming from neuroimaging studies on healthy subjects, displaying more left than right hemispheric activity and a general lack of symmetry in the fronto-parietal network active during task switching (Kim et al., 2012; Witt and Stevens, 2013). This lack of symmetry was also found when examining performance of task switching among patients with lesion of the right or left prefrontal cortex. Aron and his colleagues (2004a) reported unique deficits in task-switching performance to both patients with distinct right frontal lesion as well as patients with distinct left frontal lesion. They concluded that inhibition of inappropriate responses or task-sets requires right hemisphere activity while the left hemisphere is required for appropriate topdown control of task-sets. While this differentiation is clear with patients, it is reasonable to assume that similar processes might take place with healthy participants, perhaps to a lesser degree. Our results can be explained by this differentiation. We propose that anodal stimulation over the left DLPFC with cathodal stimulation over the right DLPFC facilitated top-down processes involving task switching on account of inhibition processes needed for task switching. In addition, we suggest that the mirrored montage facilitated inhibition processes needed for switching on account of top-down processes. Recent tDCS studies support our hypothesis by showing that anodal stimulation to the right DLPFC can enhance inhibition performance (e.g., Jacobson et al., 2011; Jeon and Han, 2012) and anodal stimulation to the left DLPFC can enhance top-down processes (e.g., Metuki et al., 2012). It is important to note, that given the bilateral nature of our montages, we cannot conclude to what extent the processes we employed are similar to the processes reported in these previous studies. An alternative explanation to our results could have been a general facilitation of higher level cognitive processing that is shifting from the right to the left hemisphere with practice, as suggested by Shadmehr et al. (2010). If that was the case, one would expect to see two findings in our results. The first one is a superiority of sham condition over anodal stimulation of the right DLPFC coupled with cathodal stimulation of the left DLPFC in which we increased right hemisphere activity at the expense of the activity of the left hemisphere. The second one would be a significant interaction of stimulation condition and performance of single-task trials. In

other words, we would expect anodal stimulation of the left DLPFC coupled with cathodal stimulation of the right DLPFC stimulation condition to outperform sham condition even in a task that does not require switching abilities. We did not find evidence for such findings and therefore we suggest that our stimulation montage employed cognitive abilities of both hemispheres and that stimulation did not generate a general facilitation tendency but a more switching specific one. What might be the cognitive mechanism that we managed to facilitate by combining stimulation and practice? Considering task-switching theories, improvement can be achieved by facilitating inhibition, top down control, or both. There are two central theories about the cognitive processes underlying switching. The first one is task-set inertia, which suggests that proactive interference (resulting from having previously performed a competing task) is the cause for switching deficits and that proper switching can only take place after deactivation of a previous task (e.g., Allport et al., 1994; Wylie and Allport, 2000). While some researchers suggest that this deactivation is an unspecific activation decay (e.g., Altmann and Gray, 2008), there are phenomena in the context of task switching that are better explained as task inhibition procedures (Mayr and Keele, 2000; for a review see Koch et al., 2010). A second theory about the processes underline task switching is task-set reconfiguration theory, suggesting that in order to properly switch, one need first to actively reconfigure a new mind set (e.g., Meiran, 1996; Mayr and Keele, 2000), a process that depends on both topdown and bottom-up influences (Meiran, 1996; Ruthruff et al., 2001). Despite the notion to explain all task-switching phenomena in terms of just one mechanism, most authors now acknowledge a plurality of causes, while continue to argue over the exact blend (Monsell, 2003; Vandierendonck et al., 2010). Our findings support the latter explanation, since it assumes parallel brain mechanisms which took part in enhancing task-switching performance. The current findings see eye to eye with accumulated data regarding hemispheric laterality in executive functions, such as inhibition (Aron et al., 2004a,b; Forstmann et al., 2008; Jacobson et al., 2011), hypothesis formation (Wolford et al., 2000) or problem solving (Newman et al., 2003) and should be considered when one aims to enhance cognitive ability using brain stimulation. We suggest that future studies and training programs would consider combining traditional cognitive training methods with brain stimulation. Previous results regarding task-switching improvement which only use non-stimulation approaches were very limited (Zinke et al., 2012; Redick et al., 2012) and therefore it seems strongly reasonable to seek new approach to manipulate and improve switching abilities. Since switching between mind-sets is a frequent cognitive process, the benefits of having a proper switching training paradigm cannot be undervalued. This is especially the case when one pays attention to the

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correlation between switching deficits and a range of psychological difficulties such as depression (e.g., Davis and Nolen-Hoeksema, 2000; Koster et al., 2011), OCD (e.g., Gu et al., 2008) or anxiety (e.g., Derakshan et al., 2009).

LIMITATIONS As far as we know this is the first tDCS study that examines the effect of stimulation on practice effect in task-switching paradigms. Because of that, our design used a well known montage that was found to modify task switching (Leite et al., 2012). Nevertheless, mind-set shifting functions demand a joined activation of several areas in a fronto-parietal brain network and the effect of stimulating other parts of this network were are yet to be established. One of these locations can be the vmPFC that was recently found relevant for inhibition processes (Yu et al., 2015). Another future research aim could be to examine the peripheral enhancement of the current stimulation on cortical areas near the electrodes using functional MRI, or stimulation effect on signal complexity (see Liang et al., 2014). Additionally, in this study we used one task-switching paradigm and therefore we cannot assume that our stimulation montage will have the same effect on different task-switching paradigms. Future studies should include additional task-switching paradigms in the last session, in order to check for the transferability of joined stimulation and traditional training methods. Acknowledgements—This study was supported by the Israel Academy of Sciences, Grant no. 367/14, and the Israeli Center of Research Excellence (I-CORE) in Cognition (I-CORE Program 51/11). The authors declare no competing financial interests.

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(Accepted 20 November 2015) (Available online 26 November 2015)