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Stimulating occipital cortex enhances visual working memory consolidation
Behavioural Brain Research 275 (2014) 84–87
Contents lists available at ScienceDirect
Behavioural Brain Research journal homepage: www.elsevier.com/locate/bbr
Short communication
Stimulating occipital cortex enhances visual working memory consolidation Tal Makovski a,∗ , Michal Lavidor b a b
Department of Education and Psychology, The Open University of Israel, Israel Department of Psychology and The Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Israel
h i g h l i g h t s • • • •
Active and sham tDCS was delivered to the visual cortex before a visual WM task. Active stimulation enhanced performance only when encoding duration was short. In contrast, no improvement was found in the long-encoding condition. Thus, the visual cortex contributes mainly for WM consolidation, not retention.
a r t i c l e
i n f o
Article history: Received 20 July 2014 Received in revised form 31 August 2014 Accepted 1 September 2014 Available online 6 September 2014 Keywords: Visual working memory Transcranial direct current stimulation (tDCS) Change detection Consolidation
a b s t r a c t Visual working memory (WM) enables us to store and manipulate visual information for a short duration. Traditionally, prefrontal and parietal regions have been associated with visual WM processing; however recent fMRI studies have shown that visual WM information can be decoded from the visual cortex as well. In this study, we used transcranial direct current stimulation (tDCS) to investigate the role of the visual cortex in retaining visual WM information. All subjects participated in two sessions of sham and active tDCS followed by a standard visual WM task. Two conditions were tested: in short encoding trials, the memory array (6 colored circles) was presented for 200 ms whereas in long encoding trials it was presented for 500 ms. We hypothesized that if stimulation over visual cortex modulates WM retention, then performance should be enhanced in both encoding conditions. However, if stimulation over visual cortex modulates mainly WM consolidation, then performance should improve only in the short encoding condition. The results supported the latter possibility as stimulation improved performance in the short encoding condition but not in the long encoding condition. Consequently, the robust advantage of the long encoding condition over the short encoding condition after sham stimulation was eliminated after active stimulation. These results suggest that the visual cortex is significant for WM consolidation, while it plays a smaller part in holding visual WM representations. © 2014 Elsevier B.V. All rights reserved.
Visual working memory (WM) is that construct of WM which enables us to buffer visual information after disappearance for a short duration. It integrates high level cognitive processing with visuo-spatial sensory information and is required for a wide range of tasks, from controlling eye movements and maintaining spatiotemporal continuity to more complex everyday tasks such as crossing the street and playing team sports [1]. While there is little debate that prefrontal and parietal regions are important in retaining visual WM information (e.g., [2,3]), the role of the visual cortex is less clear. Recent fMRI studies using
∗ Corresponding author. Tel.: +972 54774449; fax: +972 97780632. E-mail address: [email protected] (T. Makovski). http://dx.doi.org/10.1016/j.bbr.2014.09.004 0166-4328/© 2014 Elsevier B.V. All rights reserved.
multivoxel pattern analyses found that visual WM information can be decoded from early, visual cortex during retention [4–7]. These findings are important in providing evidence that sensory regions are involved in retaining WM representations, however, the extent of this involvement is unclear. For instance, it is not clear whether the visual cortex is in fact important for the active maintenance of WM information or whether the visual cortex mainly contributes to WM consolidation [8]. Furthermore, given the correlational nature of imaging techniques, causal evidence to support the involvement of visual cortex during WM retention is currently lacking. Thus, it is still required to pinpoint the exact nature of the relationship between the visual cortex and visual WM processing. In the present study, we used a brain stimulation technique to further examine the role visual cortex plays in visual WM.
T. Makovski, M. Lavidor / Behavioural Brain Research 275 (2014) 84–87
85
Fig. 1. Change detection trial’s sequence.
Noninvasive brain stimulation (NIBS) techniques are particularly helpful in establishing causality and are an excellent complementary tool for assessing how changes in brain activity affect behavior [9]. One such technique is transcranial direct current stimulation (tDCS). Although electrical stimulation of the brain has a long history, the modern form of tDCS research has been shaped in the past two decades (e.g., [10]) and it is now well established that a weak direct current applied over the scalp can modulate neuronal excitability depending on polarity (for a recent review, see [11]). Consequently, it has been shown that applying anodal tDCS for a short duration (10–20 min) improves various motor and cognitive tasks, including WM (e.g., [12,13]). Previous studies using tDCS to study WM have typically applied direct current over higher brain regions known to enhance WM activity (e.g., [14–16]). Here, in contrast we administered direct current over the visual cortex in order to investigate its role in WM processing. Specifically, we delivered weak direct current over the occipital cortex and measured its effect on a standard change detection task commonly used to measure visual WM [17]. Participants were asked to remember the colors of six items and after a short retention interval to decide whether or not a test probe had changed its color. Notably, the memory array was presented for either a short encoding duration (200 ms) or a long encoding duration (500 ms). Given that 200 ms is enough time to effectively perceive a few highly distinguishable items [18], we did not expect stimulation to affect early, visual processing. However, because visual WM consolidation rate is about 50 ms per item, we expected only the short encoding condition to present consolidation difficulties [18]. Thus, this manipulation enables us to distinguish between two possible effects of tDCS on visual WM: if stimulation over visual cortex mainly assists consolidation into WM, then we would expect performance enhancement only in the short encoding trials. In contrast, if stimulation mainly enhances brain activity related to maintaining information in visual WM, then performance should be enhanced in both encoding durations. 1. Materials and methods Twelve students from Bar Ilan University completed an IRB approved study for payment. Subjects were 18–35 (M = 23.4 years
old, 3 females), had normal or corrected-to-normal visual acuity and were without any known neurological or psychiatric disorders. Participants were tested individually in a room with normal interior lighting. They sat unrestrained approximately 60 cm away from a 17 CRT monitor (1280 × 1024, 75 Hz). The experiment was programmed with Psychtoolbox [19,20] implemented in MATLAB (http://www.mathworks.com). A portable constant current stimulator (Neuroconn DCStimulator, neuroConn GmbH, http://www.neuroconn.com/) was used to deliver direct current of 1 mA. In the active stimulation condition, the current was gradually ramped up for 30 s, applied for 15 min and then ramped down for another 30 s. In the sham condition, the current was also ramped up for 30 s but was then delivered for only 15 s before it was ramped back down (30 s). During the rest of the 15 min period, no actual current was delivered. Two saline soaked surface sponge electrodes (4 cm × 4 cm) were placed using ElectroCap EEG 10–20 montage fitted to participants’ head sizes. The anodal electrode was placed over the occipital cortex (Oz) whereas the reference electrode was placed over the vertex (Cz). Such an Oz–Cz montage was previously proven effective in stimulating the visual cortex (e.g., [21,22]). A standard change detection task was used to measure visual WM. Each trial began with a gray fixation cross (0.8◦ ) presented against a black background for 750 ms. The fixation cross stayed on the screen throughout the trial. The memory items were six filled circles (1.344◦ in diameter), placed equidistantly 3.84◦ from fixation. Colors were randomly selected, without replacement, from nine distinct colors (orange, red, green, blue, white, yellow, purple, brown, and azure). The memory display was displayed for 200 ms in the short encoding condition and for 500 ms in the long encoding condition and was then replaced by a multicolored mask (14.4◦ × 14.4◦ ) presented for 100 ms. The retention interval lasted for 1200 ms and was followed by the test item (Fig. 1). The participants’ task was to press the “s” button if the test item was the same as the memory item previously displayed at the tested location and the “d” button if it was different. On half of the trials, the test item was the same as the memory item at that location. On the other half, it was a new color not previously presented in that trial. Only accuracy was emphasized and feedback (the Hebrew words for “correct” or “wrong”) was presented after each response
86
T. Makovski, M. Lavidor / Behavioural Brain Research 275 (2014) 84–87
75 Long encoding
Percent correct
70
encoding duration, F(1, 11) = 1.19, p = .298. These results rule out a speed accuracy tradeoff as an alternative explanation.
Short encoding
65
3. Discussion
60 55 50 acve
sham Smulaon
Fig. 2. Change detection accuracy data as a function of encoding duration and stimulation. Error bars show ±1 S.E. of the mean.
for 400 ms. To minimize verbal recoding, participants were asked to repeat a one syllable word out loud throughout a block of 20 trials. All subjects completed a sham session and an active session. These sessions were identical except for the actual stimulation duration (15 s vs. 15 min, respectively). An interval of seven days separated the two sessions and their order was counterbalanced across subjects. In each session, participants performed 160 test trials of the change detection task, randomly and evenly divided into two response types (same, different) and two encoding durations (short, long). Participants completed 20 practice trials without the electrodes and another 160 practice trials during the 15 min stimulation period.1 The test trials were administered immediately following stimulation, after the removal of the electrodes. 2. Results Statistical results were generally the same for percent correct, A and for K (an estimation of WM capacity, [23]). Percent correct data are reported below while A , K and correct RT data are listed in Table 1. Fig. 2 depicts change detection performance as a function of encoding duration (long, short) and stimulation (sham, active). A repeated-measures ANOVA using these factors as within subject variables revealed a main effect of encoding duration, F(1, 11) = 6.45, p = .027, 2p = .37, whereby performance was better in the long encoding condition than in the short encoding condition. The main effect of stimulation was not significant, F(1, 11) = 1.45, p = .254, however, crucially, there was a significant interaction between stimulation and encoding duration, F(1, 11) = 5.72, p = .036, 2p = .34. The interaction was driven primarily by a better performance in the active condition relative to the sham condition in the short encoding trials, t(11) = 2.31, p = .042, Cohen’s d = 0.594, but not in the long encoding trials, t < 1. Importantly, while in the sham condition there was a strong effect of encoding duration, t(11) = 3.52, p = .005, Cohen’s d = 0.755, the difference between long encoding and short encoding trials was completely abolished after the active stimulation, t < 1. Although RT was not emphasized we deemed it necessary to ensure that the stimulation effect was not due to speed accuracy tradeoff. Responses were slower in the short encoding condition than in the long encoding condition, F(1, 11) = 9.66, p = .01, 2p = .47. Importantly however, there was no significant effect of stimulation, F(1, 11) = 1.31, p = .278, nor an interaction between stimulation and
1 The task itself lasted around 10–12 min and no effect of stimulation was found during practice [sham: short encoding = 64.6%, long encoding 70.4%, anodal: short encoding = 67.1%, long encoding = 68.4%]. The lack of stimulation effect during practice is in accord with the notion that stimulation effects require time to accumulate (e.g., [13]).
The study examines the effect of tDCS over the occipital cortex on visual WM performance. Our findings are clear: 15 min of a weak stimulation completely eliminated the robust difference between long and short encoding durations. In other words, stimulation boosted change detection performance in the short encoding duration, bringing it up to the level of the long encoding condition. This result is in line with previous studies showing improvement in cognitive tasks after anodal stimulation [11]. Furthermore, it supports the notion that the visual cortex is significant for WM consolidation. This is in accord with a recent study that shows that a transcranial magnetic stimulation (TMS) over the visual cortex impairs visual WM consolidation [24]. Notably, unlike TMS that typically impairs processing, anodal tDCS is thought to enhance neuronal excitability [10] and indeed we found improved consolidation after anodal stimulation over the visual cortex. On the flip side, anodal stimulation over the occipital cortex did not affect performance in the long encoding condition. This result cannot be attributed to a ceiling effect as accuracy was around 70%. It also cannot be easily attributed to lack of power as a stimulation effect was found in the short encoding duration but still was absent in the long encoding condition, suggesting that at the very least the effect the visual cortex has on WM retention is smaller than its effect on WM consolidation. This finding challenges the notion that the occipital cortex plays an active and important role in holding visual WM representations. Consequently, some of the previous findings showing that visual WM information can be decoded from occipital regions during retention [4–7] might reflect consolidation processes taking place after encoding rather than retention per se. So far we have attributed the effect reported above to the anodal stimulation delivered to the occipital cortex. However, given that same sized electrodes were used, one might argue that the cathodal stimulation over the vertex affected (medial) parietal areas known to be involved in visual WM. Yet we found this possibility to be unlikely for a couple of reasons. First, past studies used similar Oz–Cz montages and all were interpreted as affecting visual cortex, primarily because their results showed clear visual effects (e.g., contrast detection – [22], the N70 component of the visual evoked potentials – [21]). Here smaller electrodes than in previous studies were used, making it even less likely that parietal rather than visual regions underlie the current findings. Secondly and more importantly, based on past results one would predict that cathodal activation of parietal regions would diminish (rather than enhance) visual WM performance [14] and this effect should be similar for both encoding durations. Clearly this was not the case. If anything, the fact that we observed better performance in spite of possible destructive cathodal modulation of parietal areas only strengthens the conclusion that anodal stimulation of the occipital cortex improves consolidation of visual WM information. Another possibility is that the improved WM consolidation effect was driven by a remote modulation of the dorsolateral prefrontal cortex. This is plausible given the involvement of the dorsolateral prefrontal cortex in WM (e.g., [12,15]) and its strong connectivity with the visual cortex. However, it is important to note that a recent review concluded that direct tDCS stimulation over dorsolateral prefrontal cortex has no effect on accuracy in WM, N-back tasks, and only a medium size effect on reaction time [15]. Therefore, we find it unlikely that the improvement found for WM consolidation was driven by the dorsolateral prefrontal cortex rather than by the visual cortex. Nevertheless, future studies should
T. Makovski, M. Lavidor / Behavioural Brain Research 275 (2014) 84–87
87
Table 1 Mean (top rows) and standard deviations (in parentheses) of A and Cowan’s K (equals to memory load (i.e., 6) × (hit + correct rejection − 1). The p-values are the results of the t-tests comparing short encoding and long encoding in each stimulation condition. Like in percent correct, the strong effect of encoding duration found in the sham condition was completely abolished in the active condition. Bottom row shows correct RT data (in ms). Sham
A K Correct RT
Active
Short encoding
Long encoding
p-Value
Short encoding
Long encoding
p-Value
.732 (.08) 1.85 (0.8) 1000 (249)
.792 (.09) 2.52 (1.1) 972 (278)
p < .001 p < .001 p = .38
.776 (.08) 2.34 (0.9) 973 (290)
.789 (.09) 2.49 (1.0) 877 (225)
p = .41 p = .48 p = .037
further test alternative electrode arrangements for stimulating the visual cortex. Much of the NIBS research has been devoted to finding ways to enhance cognitive abilities. It has been suggested for instance that tDCS has the potential to improve fundamental cognitive processes such as attention, learning and memory in both healthy and clinical populations (for a recent review, see [25]). Here we found an improvement of 27% in the number of items being held in visual WM (from 1.85 to 2.34) after stimulation. This was found with a single, short stimulation session, but will it increase and persist after repeated stimulations (e.g., [26])? Hence, an important task for future research is to examine whether repeated WM practice coupled with brain stimulation has a long term effect on visual WM. In conclusion, our study provides important causal evidence for the role of the occipital cortex in consolidating information into visual WM. At the same time, we found no evidence to support the idea that the occipital cortex is important for WM maintenance, as tDCS improvement was bound to the short encoding condition and was absent in the long encoding condition. More generally, these findings add to a growing number of studies demonstrating the contribution of electrical brain stimulation to both theoretically driven and applied research. Acknowledgements This study was supported by the I-CORE Program of the Planning and Budgeting Committee and The Israel Science Foundation (grant No. 51/11). We thank Tal Sela for helpful discussions and comments. References [1] Jiang YV, Makovski T, Shim WM. Visual memory for features, conjunctions, objects, and locations. In: Brockmole JR, editor. The visual world in memory. Psychology Press; 2009. p. 33–65. [2] Miller EK, Erickson CA, Desimone R. Neural mechanisms of visual working memory in prefrontal cortex of the macaque. J Neurosci 1996;16:5154–67. [3] Todd JJ, Marois R. Capacity limit of visual short-term memory in human posterior parietal cortex. Nature 2004;428(6984):751–4. [4] Emrich SM, Riggall AC, Larocque JJ, Postle BR. Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory. J Neurosci 2013;33:6516–23. [5] Ester EF, Serences JT, Awh E. Spatially global representations in human primary visual cortex during working memory maintenance. J Neurosci 2009;29:15258–65.
[6] Harrison SA, Tong F. Decoding reveals the contents of visual working memory in early visual areas. Nature 2009;458:632–5. [7] Serences JT, Ester EF, Vogel EK, Awh E. Stimulus-specific delay activity in human primary visual cortex. Psychol Sci 2009;20:207–14. [8] Van de Ven V, Sack AT. Transcranial magnetic stimulation of visual cortex in memory: cortical state, interference and reactivation of visual content in memory. Behav Brain Res 2013;236:67–77. [9] Silvanto J, Pascual-Leone A. Why the assessment of causality in brain–behavior relations requires brain stimulation. J Cogn Neurosci 2012;24:775–7. [10] Nitsche MA, Paulus W. Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation. J Physiol (Lond) 2000;527:633–9. [11] Jacobson L, Koslowsky M, Lavidor M. tDCS polarity effects in motor and cognitive domains: a meta-analytical review. Exp Brain Res 2012;216:1–10. [12] Fregni F, Boggio P, Nitsche M, Bermpohl F, Antal A, Feredoes E, et al. Anodal transcranial direct current stimulation of prefrontal cortex enhances working memory. Exp Brain Res 2005;166:23–30. [13] Ohn SH, Park CI, Yoo WK, Ko MH, Choi KP, Kim GM, et al. Time-dependent effect of transcranial direct current stimulation on the enhancement of working memory. Neuroreport 2008;19:43–7. [14] Berryhill ME, Wencil EB, Branch Coslett H, Olson IR. A selective working memory impairment after transcranial direct current stimulation to the right parietal lobe. Neurosci Lett 2010;479:312–6. [15] Brunoni AR, Vanderhasselt MA. Working memory improvement with non-invasive brain stimulation of the dorsolateral prefrontal cortex: A systematic review and meta-analysis. Brain Cogn 2014;86:1–9, http://dx.doi.org/10.1016/j.bandc.2014.01.008. [16] Tseng P, Hsu TY, Chang CF, Tzeng OJ, Hung DL, Muggleton NG, et al. Unleashing potential: transcranial direct current stimulation over the right posterior parietal cortex improves change detection in low-performing individuals. J Neurosci 2012;32:10554–61. [17] Luck SJ, Vogel EK. The capacity of visual working memory for features and conjunctions. Nature 1997;390(6657):279–81. [18] Vogel EK, Woodman GF, Luck SJ. The time course of consolidation in visual working memory. J Exp Psychol Hum Percept Perform 2006;32(6):1436–51. [19] Brainard DH. The psychophysics toolbox. Spat Vis 1997;10(4):433–6. [20] Pelli DG. The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spat Vis 1997;10(4):437–42. [21] Antal A, Kincses TZ, Nitsche MA, Bartfai O, Paulus W. Excitability changes induced in the human primary visual cortex by transcranial direct current stimulation: direct electrophysiological evidence. Invest Ophthalmol Vis Sci 2004;45:702–7. [22] Antal A, Nitsche MA, Paulus W. External modulation of visual perception in humans. Neuroreport 2001;12:3553–5. [23] Cowan N. The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behav Brain Sci 2001;24:87–114. [24] Van de Ven V, Jacobs C, Sack AT. Topographic contribution of early, visual cortex to short-term memory consolidation: a transcranial magnetic stimulation study. J Neurosci 2012;32:4–11. [25] Coffman BA, Clark VP, Parasuraman R. Battery powered thought: enhancement of attention, learning, and memory in healthy adults using transcranial direct current stimulation. Neuroimage 2014;85:895–908. [26] Richmond L, Wolk D, Chein J, Olson IR. Transcranial direct current stimulation enhances verbal working memory training performance over time and neartransfer outcomes. J Cogn Neurosci 2014 [Epub ahead of print].
Contents lists available at ScienceDirect
Behavioural Brain Research journal homepage: www.elsevier.com/locate/bbr
Short communication
Stimulating occipital cortex enhances visual working memory consolidation Tal Makovski a,∗ , Michal Lavidor b a b
Department of Education and Psychology, The Open University of Israel, Israel Department of Psychology and The Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Israel
h i g h l i g h t s • • • •
Active and sham tDCS was delivered to the visual cortex before a visual WM task. Active stimulation enhanced performance only when encoding duration was short. In contrast, no improvement was found in the long-encoding condition. Thus, the visual cortex contributes mainly for WM consolidation, not retention.
a r t i c l e
i n f o
Article history: Received 20 July 2014 Received in revised form 31 August 2014 Accepted 1 September 2014 Available online 6 September 2014 Keywords: Visual working memory Transcranial direct current stimulation (tDCS) Change detection Consolidation
a b s t r a c t Visual working memory (WM) enables us to store and manipulate visual information for a short duration. Traditionally, prefrontal and parietal regions have been associated with visual WM processing; however recent fMRI studies have shown that visual WM information can be decoded from the visual cortex as well. In this study, we used transcranial direct current stimulation (tDCS) to investigate the role of the visual cortex in retaining visual WM information. All subjects participated in two sessions of sham and active tDCS followed by a standard visual WM task. Two conditions were tested: in short encoding trials, the memory array (6 colored circles) was presented for 200 ms whereas in long encoding trials it was presented for 500 ms. We hypothesized that if stimulation over visual cortex modulates WM retention, then performance should be enhanced in both encoding conditions. However, if stimulation over visual cortex modulates mainly WM consolidation, then performance should improve only in the short encoding condition. The results supported the latter possibility as stimulation improved performance in the short encoding condition but not in the long encoding condition. Consequently, the robust advantage of the long encoding condition over the short encoding condition after sham stimulation was eliminated after active stimulation. These results suggest that the visual cortex is significant for WM consolidation, while it plays a smaller part in holding visual WM representations. © 2014 Elsevier B.V. All rights reserved.
Visual working memory (WM) is that construct of WM which enables us to buffer visual information after disappearance for a short duration. It integrates high level cognitive processing with visuo-spatial sensory information and is required for a wide range of tasks, from controlling eye movements and maintaining spatiotemporal continuity to more complex everyday tasks such as crossing the street and playing team sports [1]. While there is little debate that prefrontal and parietal regions are important in retaining visual WM information (e.g., [2,3]), the role of the visual cortex is less clear. Recent fMRI studies using
∗ Corresponding author. Tel.: +972 54774449; fax: +972 97780632. E-mail address: [email protected] (T. Makovski). http://dx.doi.org/10.1016/j.bbr.2014.09.004 0166-4328/© 2014 Elsevier B.V. All rights reserved.
multivoxel pattern analyses found that visual WM information can be decoded from early, visual cortex during retention [4–7]. These findings are important in providing evidence that sensory regions are involved in retaining WM representations, however, the extent of this involvement is unclear. For instance, it is not clear whether the visual cortex is in fact important for the active maintenance of WM information or whether the visual cortex mainly contributes to WM consolidation [8]. Furthermore, given the correlational nature of imaging techniques, causal evidence to support the involvement of visual cortex during WM retention is currently lacking. Thus, it is still required to pinpoint the exact nature of the relationship between the visual cortex and visual WM processing. In the present study, we used a brain stimulation technique to further examine the role visual cortex plays in visual WM.
T. Makovski, M. Lavidor / Behavioural Brain Research 275 (2014) 84–87
85
Fig. 1. Change detection trial’s sequence.
Noninvasive brain stimulation (NIBS) techniques are particularly helpful in establishing causality and are an excellent complementary tool for assessing how changes in brain activity affect behavior [9]. One such technique is transcranial direct current stimulation (tDCS). Although electrical stimulation of the brain has a long history, the modern form of tDCS research has been shaped in the past two decades (e.g., [10]) and it is now well established that a weak direct current applied over the scalp can modulate neuronal excitability depending on polarity (for a recent review, see [11]). Consequently, it has been shown that applying anodal tDCS for a short duration (10–20 min) improves various motor and cognitive tasks, including WM (e.g., [12,13]). Previous studies using tDCS to study WM have typically applied direct current over higher brain regions known to enhance WM activity (e.g., [14–16]). Here, in contrast we administered direct current over the visual cortex in order to investigate its role in WM processing. Specifically, we delivered weak direct current over the occipital cortex and measured its effect on a standard change detection task commonly used to measure visual WM [17]. Participants were asked to remember the colors of six items and after a short retention interval to decide whether or not a test probe had changed its color. Notably, the memory array was presented for either a short encoding duration (200 ms) or a long encoding duration (500 ms). Given that 200 ms is enough time to effectively perceive a few highly distinguishable items [18], we did not expect stimulation to affect early, visual processing. However, because visual WM consolidation rate is about 50 ms per item, we expected only the short encoding condition to present consolidation difficulties [18]. Thus, this manipulation enables us to distinguish between two possible effects of tDCS on visual WM: if stimulation over visual cortex mainly assists consolidation into WM, then we would expect performance enhancement only in the short encoding trials. In contrast, if stimulation mainly enhances brain activity related to maintaining information in visual WM, then performance should be enhanced in both encoding durations. 1. Materials and methods Twelve students from Bar Ilan University completed an IRB approved study for payment. Subjects were 18–35 (M = 23.4 years
old, 3 females), had normal or corrected-to-normal visual acuity and were without any known neurological or psychiatric disorders. Participants were tested individually in a room with normal interior lighting. They sat unrestrained approximately 60 cm away from a 17 CRT monitor (1280 × 1024, 75 Hz). The experiment was programmed with Psychtoolbox [19,20] implemented in MATLAB (http://www.mathworks.com). A portable constant current stimulator (Neuroconn DCStimulator, neuroConn GmbH, http://www.neuroconn.com/) was used to deliver direct current of 1 mA. In the active stimulation condition, the current was gradually ramped up for 30 s, applied for 15 min and then ramped down for another 30 s. In the sham condition, the current was also ramped up for 30 s but was then delivered for only 15 s before it was ramped back down (30 s). During the rest of the 15 min period, no actual current was delivered. Two saline soaked surface sponge electrodes (4 cm × 4 cm) were placed using ElectroCap EEG 10–20 montage fitted to participants’ head sizes. The anodal electrode was placed over the occipital cortex (Oz) whereas the reference electrode was placed over the vertex (Cz). Such an Oz–Cz montage was previously proven effective in stimulating the visual cortex (e.g., [21,22]). A standard change detection task was used to measure visual WM. Each trial began with a gray fixation cross (0.8◦ ) presented against a black background for 750 ms. The fixation cross stayed on the screen throughout the trial. The memory items were six filled circles (1.344◦ in diameter), placed equidistantly 3.84◦ from fixation. Colors were randomly selected, without replacement, from nine distinct colors (orange, red, green, blue, white, yellow, purple, brown, and azure). The memory display was displayed for 200 ms in the short encoding condition and for 500 ms in the long encoding condition and was then replaced by a multicolored mask (14.4◦ × 14.4◦ ) presented for 100 ms. The retention interval lasted for 1200 ms and was followed by the test item (Fig. 1). The participants’ task was to press the “s” button if the test item was the same as the memory item previously displayed at the tested location and the “d” button if it was different. On half of the trials, the test item was the same as the memory item at that location. On the other half, it was a new color not previously presented in that trial. Only accuracy was emphasized and feedback (the Hebrew words for “correct” or “wrong”) was presented after each response
86
T. Makovski, M. Lavidor / Behavioural Brain Research 275 (2014) 84–87
75 Long encoding
Percent correct
70
encoding duration, F(1, 11) = 1.19, p = .298. These results rule out a speed accuracy tradeoff as an alternative explanation.
Short encoding
65
3. Discussion
60 55 50 acve
sham Smulaon
Fig. 2. Change detection accuracy data as a function of encoding duration and stimulation. Error bars show ±1 S.E. of the mean.
for 400 ms. To minimize verbal recoding, participants were asked to repeat a one syllable word out loud throughout a block of 20 trials. All subjects completed a sham session and an active session. These sessions were identical except for the actual stimulation duration (15 s vs. 15 min, respectively). An interval of seven days separated the two sessions and their order was counterbalanced across subjects. In each session, participants performed 160 test trials of the change detection task, randomly and evenly divided into two response types (same, different) and two encoding durations (short, long). Participants completed 20 practice trials without the electrodes and another 160 practice trials during the 15 min stimulation period.1 The test trials were administered immediately following stimulation, after the removal of the electrodes. 2. Results Statistical results were generally the same for percent correct, A and for K (an estimation of WM capacity, [23]). Percent correct data are reported below while A , K and correct RT data are listed in Table 1. Fig. 2 depicts change detection performance as a function of encoding duration (long, short) and stimulation (sham, active). A repeated-measures ANOVA using these factors as within subject variables revealed a main effect of encoding duration, F(1, 11) = 6.45, p = .027, 2p = .37, whereby performance was better in the long encoding condition than in the short encoding condition. The main effect of stimulation was not significant, F(1, 11) = 1.45, p = .254, however, crucially, there was a significant interaction between stimulation and encoding duration, F(1, 11) = 5.72, p = .036, 2p = .34. The interaction was driven primarily by a better performance in the active condition relative to the sham condition in the short encoding trials, t(11) = 2.31, p = .042, Cohen’s d = 0.594, but not in the long encoding trials, t < 1. Importantly, while in the sham condition there was a strong effect of encoding duration, t(11) = 3.52, p = .005, Cohen’s d = 0.755, the difference between long encoding and short encoding trials was completely abolished after the active stimulation, t < 1. Although RT was not emphasized we deemed it necessary to ensure that the stimulation effect was not due to speed accuracy tradeoff. Responses were slower in the short encoding condition than in the long encoding condition, F(1, 11) = 9.66, p = .01, 2p = .47. Importantly however, there was no significant effect of stimulation, F(1, 11) = 1.31, p = .278, nor an interaction between stimulation and
1 The task itself lasted around 10–12 min and no effect of stimulation was found during practice [sham: short encoding = 64.6%, long encoding 70.4%, anodal: short encoding = 67.1%, long encoding = 68.4%]. The lack of stimulation effect during practice is in accord with the notion that stimulation effects require time to accumulate (e.g., [13]).
The study examines the effect of tDCS over the occipital cortex on visual WM performance. Our findings are clear: 15 min of a weak stimulation completely eliminated the robust difference between long and short encoding durations. In other words, stimulation boosted change detection performance in the short encoding duration, bringing it up to the level of the long encoding condition. This result is in line with previous studies showing improvement in cognitive tasks after anodal stimulation [11]. Furthermore, it supports the notion that the visual cortex is significant for WM consolidation. This is in accord with a recent study that shows that a transcranial magnetic stimulation (TMS) over the visual cortex impairs visual WM consolidation [24]. Notably, unlike TMS that typically impairs processing, anodal tDCS is thought to enhance neuronal excitability [10] and indeed we found improved consolidation after anodal stimulation over the visual cortex. On the flip side, anodal stimulation over the occipital cortex did not affect performance in the long encoding condition. This result cannot be attributed to a ceiling effect as accuracy was around 70%. It also cannot be easily attributed to lack of power as a stimulation effect was found in the short encoding duration but still was absent in the long encoding condition, suggesting that at the very least the effect the visual cortex has on WM retention is smaller than its effect on WM consolidation. This finding challenges the notion that the occipital cortex plays an active and important role in holding visual WM representations. Consequently, some of the previous findings showing that visual WM information can be decoded from occipital regions during retention [4–7] might reflect consolidation processes taking place after encoding rather than retention per se. So far we have attributed the effect reported above to the anodal stimulation delivered to the occipital cortex. However, given that same sized electrodes were used, one might argue that the cathodal stimulation over the vertex affected (medial) parietal areas known to be involved in visual WM. Yet we found this possibility to be unlikely for a couple of reasons. First, past studies used similar Oz–Cz montages and all were interpreted as affecting visual cortex, primarily because their results showed clear visual effects (e.g., contrast detection – [22], the N70 component of the visual evoked potentials – [21]). Here smaller electrodes than in previous studies were used, making it even less likely that parietal rather than visual regions underlie the current findings. Secondly and more importantly, based on past results one would predict that cathodal activation of parietal regions would diminish (rather than enhance) visual WM performance [14] and this effect should be similar for both encoding durations. Clearly this was not the case. If anything, the fact that we observed better performance in spite of possible destructive cathodal modulation of parietal areas only strengthens the conclusion that anodal stimulation of the occipital cortex improves consolidation of visual WM information. Another possibility is that the improved WM consolidation effect was driven by a remote modulation of the dorsolateral prefrontal cortex. This is plausible given the involvement of the dorsolateral prefrontal cortex in WM (e.g., [12,15]) and its strong connectivity with the visual cortex. However, it is important to note that a recent review concluded that direct tDCS stimulation over dorsolateral prefrontal cortex has no effect on accuracy in WM, N-back tasks, and only a medium size effect on reaction time [15]. Therefore, we find it unlikely that the improvement found for WM consolidation was driven by the dorsolateral prefrontal cortex rather than by the visual cortex. Nevertheless, future studies should
T. Makovski, M. Lavidor / Behavioural Brain Research 275 (2014) 84–87
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Table 1 Mean (top rows) and standard deviations (in parentheses) of A and Cowan’s K (equals to memory load (i.e., 6) × (hit + correct rejection − 1). The p-values are the results of the t-tests comparing short encoding and long encoding in each stimulation condition. Like in percent correct, the strong effect of encoding duration found in the sham condition was completely abolished in the active condition. Bottom row shows correct RT data (in ms). Sham
A K Correct RT
Active
Short encoding
Long encoding
p-Value
Short encoding
Long encoding
p-Value
.732 (.08) 1.85 (0.8) 1000 (249)
.792 (.09) 2.52 (1.1) 972 (278)
p < .001 p < .001 p = .38
.776 (.08) 2.34 (0.9) 973 (290)
.789 (.09) 2.49 (1.0) 877 (225)
p = .41 p = .48 p = .037
further test alternative electrode arrangements for stimulating the visual cortex. Much of the NIBS research has been devoted to finding ways to enhance cognitive abilities. It has been suggested for instance that tDCS has the potential to improve fundamental cognitive processes such as attention, learning and memory in both healthy and clinical populations (for a recent review, see [25]). Here we found an improvement of 27% in the number of items being held in visual WM (from 1.85 to 2.34) after stimulation. This was found with a single, short stimulation session, but will it increase and persist after repeated stimulations (e.g., [26])? Hence, an important task for future research is to examine whether repeated WM practice coupled with brain stimulation has a long term effect on visual WM. In conclusion, our study provides important causal evidence for the role of the occipital cortex in consolidating information into visual WM. At the same time, we found no evidence to support the idea that the occipital cortex is important for WM maintenance, as tDCS improvement was bound to the short encoding condition and was absent in the long encoding condition. More generally, these findings add to a growing number of studies demonstrating the contribution of electrical brain stimulation to both theoretically driven and applied research. Acknowledgements This study was supported by the I-CORE Program of the Planning and Budgeting Committee and The Israel Science Foundation (grant No. 51/11). We thank Tal Sela for helpful discussions and comments. References [1] Jiang YV, Makovski T, Shim WM. Visual memory for features, conjunctions, objects, and locations. In: Brockmole JR, editor. The visual world in memory. Psychology Press; 2009. p. 33–65. [2] Miller EK, Erickson CA, Desimone R. Neural mechanisms of visual working memory in prefrontal cortex of the macaque. J Neurosci 1996;16:5154–67. [3] Todd JJ, Marois R. Capacity limit of visual short-term memory in human posterior parietal cortex. Nature 2004;428(6984):751–4. [4] Emrich SM, Riggall AC, Larocque JJ, Postle BR. Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory. J Neurosci 2013;33:6516–23. [5] Ester EF, Serences JT, Awh E. Spatially global representations in human primary visual cortex during working memory maintenance. J Neurosci 2009;29:15258–65.
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