Assessing the Effect of Early Visual Cortex Transcranial - IA de Investigación especializada en el MIT

Evaluación del efecto de la corteza visual transcraneal temprana
Magnetic Stimulation on Working
Memory Consolidation

Amanda E. van Lamsweerde and Jeffrey S. Johnson

Abstracto

■ Maintaining visual working memory ( VWM) representaciones
recruits a network of brain regions, including the frontal, posterior
parietal, and occipital cortices; sin embargo, it is unclear to what ex-
tent the occipital cortex is engaged in VWM after sensory encoding
is completed. Noninvasive brain stimulation data show that stim-
ulation of this region can affect working memory (W.M.) durante el
early consolidation time period, but it remains unclear whether it
does so by influencing the number of items that are stored or their
precisión. en este estudio, we investigated whether single-pulse
transcranial magnetic stimulation (spTMS) to the occipital cortex
during VWM consolidation affects the quantity or quality of VWM
representaciones. In three experiments, we disrupted VWM consol-

idation with either a visual mask or spTMS to retinotopic early vi-
sual cortex. We found robust masking effects on the quantity of
VWM representations up to 200 msec poststimulus offset and
smaller, more variable effects on WM quality. Similarmente, spTMS
decreased the quantity of VWM representations, but only when
it was applied immediately following stimulus offset. Like visual
masks, spTMS also produced small and variable effects on WM
precisión. The disruptive effects of both masks and TMS were
greatly reduced or entirely absent within 200 msec of stimulus
offset. Sin embargo, there was a reduction in swap rate across all time
intervals, which may indicate a sustained role of the early visual
cortex in maintaining spatial information. ■

INTRODUCCIÓN

Research examining the neural bases of working memory
( W.M.) has suggested that, whereas early sensory cortex is
primarily engaged during stimulus encoding, the forma-
tion and maintenance of WM representations are most
likely mediated by sustained activation in “higher-level”
areas such as the parietal and frontal cortex (Postle,
2006; Xu & Chun, 2006; Todd & Marois, 2004; Courtney,
Ungerleider, Keil, & Haxby, 1997; Goldman-Rakic, 1995).
More recent evidence, sin embargo, has demonstrated that
stimulus attributes, such as the color or direction of mo-
tion of a stimulus, can be decoded from delay period ac-
tivity in sensory cortex using pattern classifiers (Emrich,
Riggall, LaRocque, & Postle, 2013; Ester, anderson, &
serencias, 2013; harrison & Tong, 2009; serencias, Ester,
Vogel, & Awh, 2009), and the accuracy of these classifiers
has been correlated with the precision of stored informa-
ción (Emrich et al., 2013). These data suggest that early
sensory areas may play an important role in the forma-
tion and short-term retention of WM representations, en
addition to their well-established role in perceptual en-
codificación. The correlational nature of the majority of these
estudios, sin embargo, has made it difficult to draw strong in-
ferences regarding the causal role of early sensory areas

North Dakota State University

in WM functions. To address this, several studies have
used noninvasive brain stimulation methods to demon-
strate a causal link between early sensory areas and WM
(Makovski & Lavidor, 2014; van de Ven & Sack, 2013; camioneta
de Ven, Jacobs, & Sack, 2012; cattáneo, Vecchi, Pascual-
Leone, & Silvanto, 2009).

Por ejemplo, van de Ven et al. (2012) used single-pulse
transcranial magnetic stimulation (spTMS) to examine
the contribution of the early visual cortex to visual work-
ing memory ( VWM). Results showed that spTMS of the
visual cortex produced a retinotopically specific disrup-
tion of performance on a shape change detection task
when applied 200 msec poststimulus offset (350 mseg
poststimulus onset), but not when applied at 100 o
400 mseg. Además, this disruption was only observed
in a high-load condition in which three shapes were
remembered; no effects of spTMS were observed when
only a single item was remembered. Fundamentalmente, the TMS-
related decrease in performance occurred at the same time
period as visual mask-related decreases in performance
observed in a second experiment. The authors concluded
from these results that occipital-cortex-mediated VWM con-
solidation occurs early during the retention interval (ver
also Cattaneo et al., 2009) and is both topographically orga-
nized and highly capacity limited. Underlying this conclu-
sion is the idea that spTMS and visual masks disrupt
performance in an all-or-none fashion by interfering with

Revista de neurociencia cognitiva 29:7, páginas. 1226–1238
doi:10.1162/jocn_a_01113

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visual cortex activity that is critical for the formation of
stimulus representations in WM. Eso es, TMS prevents
one or more items from being successfully consolidated
and maintained in WM. This possibility appears consistent
with evidence suggesting that the functional effect of TMS
is to interrupt ongoing neural activity, rather than to add
random noise to the signal (harris, Clifford, & Miniussi,
2008; but see Abrahamyan, Clifford, Arabzadeh, & harris,
2011; Schwarzkopf, Silvanto, & rees, 2011). Otro
possibility, sin embargo, is that both forms of disruption
produce their effects by reducing mnemonic precision
(es decir., the quality of information in VWM), en vez de
preventing the consolidation or maintenance of some
elementos (es decir., the quantity of information in VWM). This could
happen if the disruption caused by TMS (or visual masks)
prevents the further accumulation of high-resolution
stimulus information for a subset of the remembered
elementos, rather than having an all-or-none effect on
consolidation. Previous TMS studies, which have relied
exclusively on variants of the change detection paradigm,
are not well suited to addressing this possibility, porque
they do not allow the quantity and quality of WM represen-
tations to be separately estimated.

en este estudio, we sought to clarify the functional role of
early visual cortex in WM by applying single pulses of
TMS to retinotopic visual cortex while participants per-
formed a cued recall WM task. This task required partic-
ipants to remember three colors presented in either the
lower left or lower right visual field, randomly deter-
mined by a spatial cue presented at the beginning of each
trial ( Vogel & Machizawa, 2004), and to estimate a given
remembered color at test by selecting its value from a
continuous representation of the color space (zhang &
Luck, 2008; Wilken & Mamá, 2004). críticamente, although the
visual field location of memory stimuli varied from trial to
trial, the stimulated hemisphere was held constant. adi-
cionalmente, the timing of TMS relative to the offset of the
memory display was varied randomly across trials. Estos
design elements allowed us to assess the topographic
and temporal specificity of TMS effects on performance
(as in van de Ven et al., 2012). To assess the functional
contribution of early visual cortex activity to WM, nosotros
adopted a mixture modeling approach (Laureles, Catalao, &
Husain, 2009; zhang & Luck, 2008) that attributes recall
response errors to three different underlying sources: (1)
response variability, measured as the standard deviation
(Dakota del Sur) of a circular Gaussian (von Mises) distribution cen-
tered on the target color, a proxy for memory quality; (2)
the probability of uniform responding (es decir., guessing,
denoted as g), proposed to reflect the proportion of trials
on which no information about the cued item is present
in WM, a proxy for WM capacity; y (3) nontarget
respuestas, in which participants mistakenly report the
color of one of the un-cued items at test.

Our initial hypothesis was that TMS would produce
retinotopically specific effects on estimates of the SD
(rather than g). This was based on previous findings,

suggesting that the ability to decode stimulus identity
from patterns of activation in early visual cortex is predic-
tive of SD (Emrich et al., 2013), and on theories, sugerir-
ing that the representation of high-precision featural
information in WM involves the recruitment by attention
of early visual areas involved in the initial processing of that
información (D'Esposito, 2007; Postle, 2006; Pasternak &
verdelee, 2005). Sin embargo, a previous study examining
the effects of visual masks on recall performance (zhang
& Luck, 2008) revealed selective effects on random
responding, rather than SD. If TMS influences WM through
a similar mechanism, it could also be expected to affect the
rate of random responding. Finalmente, if retinotopic early
visual cortex plays a functional role in both the initial en-
coding as well as maintenance of information in VWM,
we expected TMS pulses to continue to exert an influence
on behavior across each of the time points tested (0, 100,
o 200 msec poststimulus offset).

Results showed that, contrary to our initial prediction,
TMS-related declines in performance were most promi-
nently reflected in a decrease in g, although smaller ef-
fects were also observed on SD. Además, TMS
produced retinotopically specific improvements in per-
rendimiento; the likelihood of making a swap error was
reduced for targets contralateral to the stimulated
hemisferio. In a corresponding experiment, we found
a similar pattern of disruptive effects when visual masks
were used to interfere with performance; visual masks
produced a significant increase in g and smaller more var-
iable effects on SD. Visual masks had no effect on swap
tasa. Although the disruptive effects of visual masks were
larger and extended further into the delay than the TMS-
induced effects, in both cases the effects were either ab-
sent or considerably reduced by 200 msec poststimulus
(350 msec after stimulus onset).

EXPERIMENT 1: EFFECTS OF VISUAL MASKS
ON CHANGE DETECTION

Before examining the effects of masks and TMS on recall
actuación, we conducted an initial experiment to de-
termine the timing of masking effects in the context of
detección de cambios, the VWM task utilized by van de Ven
et al. (2012). In a change detection task, Participantes
are asked to remember a small set of simple objects
(p.ej., colored squares, oriented bars, abstract shapes,
etc.) across a short retention interval (∼800 msec to
3 segundo), by asking them to judge whether the items in a
test display are the same as or different than the items
they saw originally (Luck & Vogel, 1997). In a shape
change detection task, van de Ven et al. (2012) found
masking effects at 200 msec poststimulus offset (350 mseg
post onset), but not at 100 o 400 msec poststimulus off-
colocar. A diferencia de, Vogel, Woodman, and Luck (2006) found
that visual masks disrupted performance on a color
change detection task until approximately 183 mseg después
the onset of the memory display (33 msec poststimulus

van Lamsweerde and Johnson

1227

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offset). Por lo tanto, in Experiment 1, we utilized a change
detection task with masks at three time points: 0, 100, o
200 msec following the offset of the stimulus display. Este
way, we could determine whether mask timings differ for
change detection versus recall tasks before administering
spTMS in a cued recall task (Experimento 3).

Métodos

Participantes

Thirteen undergraduate students (10 women, promedio
age = 24.5 años) participated in this experiment for
monetary compensation ($10/hr). All participants had normal or corrected-to-normal visual acuity and normal color vision and provided informed consent before participation. Study protocols for this and all subsequent experiments were approved by the North Dakota State University institutional review board. Stimuli Stimulus presentation and response recording was con- trolled by a PC running Matlab (The Mathworks, Cª, Natick, MAMÁ) with Psychophysics Toolbox extensions (Brainard, 1997; Pelli, 1997). Stimulus displays contained three colored squares subtending 1.23° × 1.23° of visual angle on either side of fixation at a viewing distance of 70 cm (ver figura 1). Individual colors were selected at random from a set of 180 colors equally distributed in CIELAB (1976) color space (centered at CIE L*a*b* coor- dinates: L = 70, A = 28, B = 12). All objects were pre- sented in the lower left and right visual hemifields, equally spaced on an invisible circle centered at fixation with a radius of 6.31° of visual angle and squares within each hemifield were spaced 3.3° from each other, center to center. Procedure The task is shown in Figure 1A. Each trial began with a precue (500 mseg), directing participants to attend to either the left or right visual hemifield, followed by a 500-msec fixation screen, then the stimulus display (150 mseg), and then a 1000-msec delay. During the de- lay, a pattern mask (composed of randomly selected colors from the possible colorspace) flashed for 200 msec over the spatial location occupied by each object on the left side of the screen. Por lo tanto, when cued to attend to the left visual hemifield, the memory representations were masked, but when cued to attend to the right visual hemifield, memory representations were unmasked (the left side alone was masked to correspond with the TMS experiment, in which stimulation was always applied to the right hemisphere). Masks appeared at delays of 0, 100, o 200 msec after the offset of the stimulus display (randomly intermixed). Because the duration of the stim- ulus display was 150 mseg, these timings correspond to SOAs between the onset of the stimulus display and the onset of the mask of 150, 250, y 350 mseg, respetar- activamente. These timings were selected on the basis of previ- ous findings related to the time course of consolidation of color stimuli in VWM, which revealed that visual masks continue to disrupt memory performance at SOAs up to183 msec (see Vogel et al., 2006, Experimento 2). Fol- lowing the delay, the test display was presented, which was either identical to the memory display or contained a color change in one of the objects. When a color changed, the new color was selected at random from the total set of possible colors, with the constraint that it must be different from the sample stimulus by at least 20° in color space. Participants indicated whether the test display was the same as or different than the stimulus display by pressing one of two keys on their keyboards. Participants completed 60 experimental trials in each condition (30 cambiar, 30 no change; 360 trials total) divided into 10 blocks with an even number of each trial type, plus a block of 36 practice trials. Results A mask-related decrease in performance was found at 0 y 100 msec poststimulus offset, pero no 200 mseg (ver figura 2). This was supported by a 2 (Mask: mask, no mask) × 3 (Timing: 0, 100, 200 mseg) repeated-measures ANOVA. Where the assumption of sphericity was violated, a Greenhouse–Geisser correction was applied. In this and all subsequent experiments, post hoc tests were cor- rected with the Holm–Bonferroni correction for family- wise error. With this correction, comparisons are ranked from smallest to largest p value and are compared against a critical p value, calculated separately for each hypothesis using the formula P(k) > α/m + 1 − k, where P refers to the obtained p value, α represents the selected criterion for rejecting the null hypothesis (.05 in the present case), m is an index representing the order of p values for each hypothesis tested, from lowest to highest, and k is the minimal index for which the obtained p value does not exceed the significance criterion (α/m + 1 − k; Holm, 1979). En todos los casos, three comparisons were made. De este modo, the threshold for significance for the smallest p value is p < .0167, the second largest p < .025, and the largest p value p < .05. The ANOVA revealed a significant effect of Mask, F(1, 12) = 12.83, p = .004, ηp 2 = 0.52, no main effect of Tim- ing, F(1.33, 15.924) = 2.33, p = .14, ηp 2 = 0.16, and a sig- nificant Mask × Timing interaction, F(2, 24) = 20.62, p < .001, ηp 2 = 0.63. Post hoc t tests revealed a significant dif- ference between the mask and no-mask conditions at 0 msec, t(12) = −7.39, p < .001 (critical p = .0167), a marginally significant effect at 100 msec, t(12) = −2.53, p = .03 (critical p = .025), and no effect at 200 msec, t(12) = .01, p = .99 (critical p = .05). 1228 Journal of Cognitive Neuroscience Volume 29, Number 7 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 9 / 7 2 9 1 / 2 7 2 / 6 1 1 2 9 2 5 6 2 / 7 1 5 7 7 8 o 6 c 4 n 0 _ 3 a / _ j 0 o 1 c 1 n 1 3 _ a p _ d 0 1 b 1 y 1 g 3 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j t . f / u s e r o n 1 7 M a y 2 0 2 1 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 9 / 7 2 9 1 / 2 7 2 / 6 1 1 2 9 2 5 6 2 / 7 1 5 7 7 8 o 6 c 4 n 0 _ 3 a / _ j 0 o 1 c 1 n 1 3 _ a p _ d 0 1 b 1 y 1 g 3 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j f t / . u s e r o n 1 7 M a y 2 0 2 1 Figure 1. Tasks used in Experiments 1–3. In Experiment 1 (A), participants detected changes in a single color between stimulus and test displays; visual masks were displayed 0, 100, or 200 msec into the 1000-msec delay period. In Experiment 2, the task was identical to Experiment 1, except that a recall task was used, rather than change detection. In Experiment 3 (B), the task was identical to Experiment 2, except that instead of a visual mask, spTMS was applied at 0, 100, or 200 msec into the delay period. Brain regions targeted for stimulation (C) were selected before the experiment with a phosphene localization procedure. This figure shows the targeted brain region for one participant, based on the phosphene area circled by that participant. Phosphene localization response is shown overlayed on top of a sample stimulus, for illustrative purposes only. The stimulus display was not present during phosphene localization. van Lamsweerde and Johnson 1229 change detection. The task was identical to the change detection task up until the presentation of the test dis- play. In this task, the participant is asked to recall a par- ticular cued item by selecting its value from a continuous representation of the feature space (Zhang & Luck, 2008; Wilken & Ma, 2004). We then examined the impact of visual masks on both total error (the absolute difference between the recalled and actual color across trials) and on different putative sources of error using a mixture modeling approach (Bays et al., 2009; Zhang & Luck, 2008), which allows both the quantity and quality of VWM representations to be separately estimated. Methods Participants Twenty-two undergraduate and graduate students (age M = 22.09 years, 19 women) participated in this experi- ment for either course credit or monetary compensation ($10/ hr). All participants had normal or corrected-to- normal vision and normal color vision. Stimuli and Procedure The stimuli and procedure were identical to Experiment 1, with the exception that a cued recall rather than change detection test was used (Figure 1B). The test display contained a filled white square at the location of a ran- domly selected test item, with empty white box place- holders in the locations of the nontargets in the attended hemifield only. These boxes were surrounded by a color wheel centered at fixation with a radius of 8.13° of visual angle, which contained all possible colors equally distribut- ed in steps of 2° and was randomly rotated on each trial so that participants could not generate anticipatory responses before the onset of the test display. Participants were in- structed to report the color of the cued item by clicking on the color wheel using the computer mouse (see Figure 1). As participants moved the mouse around the color wheel, the cued square was filled with the selected color. Once participants made a response, the target square was filled with the response color, and a border of the correct color was added so that participants could compare their response to the correct one. Additional feedback was provided in the form of a black bar that appeared on the outside the color wheel, marking the correct color. Partici- pants completed 100 trials in each condition (600 trials total), evenly distributed across 10 experimental blocks, plus one practice block of 60 trials. Modeling Recall Response Distributions Participants’ data were analyzed using the MemToolbox (Suchow, Brady, Fougnie, & Alvarez, 2013). To analyze performance in the recall task, we made use of analytic techniques proposed by Zhang and Luck (2008) and Bays Figure 2. Results from Experiment 1. Mask-related decreases in performance were found at 0 and 100 msec, but not 200 msec. Discussion Visual masks produced a temporally graded pattern of disruption of color change detection, producing a large effect when the mask appeared immediately after stimu- lus offset, a marginal effect 100 msec later, and no effect at all by 200 msec (SOA between onset of stimulus and onset of mask = 350 msec), similar to the timing effects found by Vogel et al. (2006). This is in contrast to van de Ven et al. (2012), who found masking-related decreases in performance only at 200 msec (sample-mask onset SOA = 350 msec), but not at either earlier (100 msec) or later (400 msec) time points. The reasons for this dis- crepancy are unclear. van de Ven et al. suggest that the timing of the interference effect observed in their exper- iment could be due to interference with a later-occurring sweep of feedback input from higher-level areas to the visual cortex, which, they propose, may be critical for suc- cessful consolidation. Differences in the timing of mask- ing effects between our studies could potentially be explained if we assume that the timing and/or necessity of such feedback interactions for consolidation differ de- pending on the specific stimuli used (e.g., complex shapes vs. colors). Determining whether this is in fact the case is beyond the scope of this study and will re- quire further research, ideally using neuroimaging methods that make it possible to carefully track the pat- terns of activity involved in task performance. Of greater relevance, the results of Experiment 1 provide a range of sample-mask SOAs that were utilized in Experiment 2 in the context of a recall WM task. Use of recall, rather than change detection, allowed us to determine whether visu- al masks influence g (as a proxy for capacity) or SD (as a proxy for mnemonic precision). EXPERIMENT 2: EFFECTS OF VISUAL MASKS ON RECALL PERFORMANCE Experiment 2 was identical to Experiment 1, with the ex- ception that a cued recall test was used, rather than 1230 Journal of Cognitive Neuroscience Volume 29, Number 7 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 9 / 7 2 9 1 / 2 7 2 / 6 1 1 2 9 2 5 6 2 / 7 1 5 7 7 8 o 6 c 4 n 0 _ 3 a / _ j 0 o 1 c 1 n 1 3 _ a p _ d 0 1 b 1 y 1 g 3 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j t . f / u s e r o n 1 7 M a y 2 0 2 1 et al. (2009), in which recall response distributions are assumed to reflect a mixture of response types drawn from different distributions. According to the logic of this approach, when the cued item is successfully remembered, recall responses are drawn from a circular Gaussian (i.e., Von Mises) distribution, in which the mean indicates how close recall responses were on average to the actual target value across trials, and the standard deviation reflects the precision (quality) of the recalled items. If the item was not successfully stored, recall responses are assumed to be drawn from a uniform distribution in which individual colors are selected equiprobably from the color wheel; this “guess rate” can then be used to estimate the quantity of items stored in VWM. Finally, accurate performance on this task necessitates keeping track of which colors appeared in each location in the original memory display. A failure to do so can result in a third type of recall response in which one of the noncued memory items is recalled instead of the cued item, known as a “swap error” (Bays et al., 2009). Therefore, this method makes it possible to separately estimate the quantity and quality of stored information, as well as the likelihood of mistaking the cued item for one of the other items in WM. For each participant, we compared goodness of fit between the three-component variant of the mixture model and the two-component model proposed by Zhang and Luck (2008), which does not include swap errors, using the log likelihood and the corrected Akaike information criteria (cAIC). For all model comparisons, the three-component model provided the superior fit for the majority of participants (100% and 86% for the log likelihood and cAIC, respectively). For both the log likelihood and cAIC, we compared the computed scores for each model with a paired sample t test and report the mean difference between the scores as the two component score minus the three component score. The three component model provided a signifi- cantly superior fit for both the cAIC, t(21) = −.30, p < .001 (mean difference = 13.53, SD = 14.76), and log likelihood, t(21) = −5.49, p < .001 (mean difference = −8.07, SD = 6.89). Therefore, the three-component model was used for all analyses. Results Analysis of Absolute Error The present experiment manipulated the timing of visual masks and whether the attended visual field location was masked or unmasked. To examine the effects of mask timing and presence/absence on recall performance, we first performed a two-way (2 Mask × 3 Timing) repeated- measures ANOVA on the absolute error (absolute differ- ence between the recalled and the actual target color). This revealed a significant main effect of Mask, F(1, 21) = 45.78, p < .0001, ηp 2 = 0.69, a significant main effect of Timing, F(2, 42) = 27.99, p < .0001, ηp 2 = 0.57, and a significant Mask × Timing interaction, F(2, 42) = 14.145, p < .0001, ηp 2 = 0.40. Post hoc t tests revealed significant mask-related elevations in absolute error at each sample- mask timing (all ps < .001), although the effect grew substantially smaller at longer sample-mask delays (see Figure 3A). D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 9 / 7 2 9 1 / 2 7 2 / 6 1 1 2 9 2 5 6 2 / 7 1 5 7 7 8 o 6 c 4 n 0 _ 3 a / _ j 0 o 1 c 1 n 1 3 _ a p _ d 0 1 b 1 y 1 g 3 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j / . f t u s e r o n 1 7 M a y 2 0 2 1 Figure 3. Results from Experiment 2. Mask-related decreases in (A) absolute error were found at all time periods. In the mixture model parameters, mask-related decreases were found at all time points for guess rate (B), with a decreasing effect of mask with increased time. Standard deviation was overall greater with a mask (C) and no effects were found on swap rate (D). van Lamsweerde and Johnson 1231 Analysis of Mixture Model Fits Results of the mixture model analysis can be seen in Figure 3B–D. Differences between conditions were assessed with separate 2 (Mask: mask, no mask) × 3 (Timing: 0, 100, 200) repeated-measures ANOVAs con- ducted for each parameter (g, SD, swap rate). When the assumption of sphericity was violated, a Greenhouse– Geisser correction was applied. Guess rate. The results indicate a masking-related in- crease in guess rate at all three time points, although effects tended to decrease over time. Confirming this pat- tern, ANOVA revealed a main effect of Mask, F(1, 21) = 19.29, p < .001, ηp 2 = 0.48, no effect of Timing, F(2, 42) = 1.14, p = .33, ηp 2 = 0.05, and a significant Mask × Timing interaction, F(2, 42) = 3.72, p = .03, ηp 2 = 0.15. Post hoc t tests revealed a significant increase in guess rate as a result of the mask at 0 msec, t(21) = 4.63, p < .001 (critical p = .0167), and 100 msec, t(21) = 3.56, p = .002 (critical p = .025), and a smaller effect at 200 msec, t(21) = 2.09, p = .049 (critical p = .05). Standard deviation. The ANOVA only revealed a main effect of Mask, F(1, 21) = 4.39, p = .049, ηp 2 = 0.17, with a marginal effect of Timing, F(1.55, 32.49) = 3.20, p = .065, ηp 2 = 0.13, and no significant interaction, F(1.51, 31.77) = 1.58, p = .22, ηp 2 = 0.07. Swap rate. No masking effects on swap rate were found. The ANOVA revealed no effects of Mask, F(1, 21) = 2.73, p = .11, ηp 2 = 0.12, Timing, F(2, 42) = 2.43, p = .10, ηp 2 = 0.10, or a Mask × Timing interaction, F(2, 42) = 1.00, p = .38, ηp 2 = 0.05. Discussion Using a recall test, Experiment 2 revealed the presence of masking effects at all tested intervals, although the mag- nitude of the effect decreased over time. Although the greater number of participants in Experiment 2 makes it difficult to directly compare these results to Experi- ment 1, this result suggests that the recall task may have greater sensitivity to reveal masking effects than the change detection task. The time required to fully consol- idate VWM representations may therefore be somewhat longer than suggested by studies examining this issue using the change detection task ( Vogel et al., 2006). In keeping with the findings of Zhang and Luck (2008), the masks in this experiment primarily influenced the likelihood of generating a guess-like response. However, we also observed a small, mask-related increase in SD that did not vary based on mask timing. Thus, these find- ings are broadly consistent with the proposal that encod- ing in VWM is an all-or-none process, as opposed to a process characterized by a gradual accumulation of fea- tural information over time (Zhang & Luck, 2008). EXPERIMENT 3: EFFECTS OF spTMS OF RETINOTOPIC VISUAL CORTEX ON RECALL PERFORMANCE The goal of Experiment 3 was to determine whether TMS affects the quantity and quality of information in VWM in a manner similar to the visual masks used in Experiment 2. The same procedure was used as in Experiment 2, ex- cept that instead of visual masks, spTMS was applied to retinotopic visual cortex at variable delays relative to stimulus offset. It was expected that disruptions in per- formance would occur when participants encoded infor- mation presented in the visual field contralateral to the stimulated hemisphere (as in van de Ven et al., 2012); contralateral stimulation trials therefore served the same function as the “mask” trials in Experiments 1 and 2. The trials in which participants attended to the hemifield ip- silateral to stimulation (i.e., right hemifield during right- occipital stimulation) served as a hemispheric control. Although it is common to also include a sham control condition in TMS experiments, the use of a control hemisphere has the advantage that (1) trials probing the control and target hemispheres are randomly inter- mixed throughout the session, ensuring that the state of the participant is roughly equivalent across conditions, and (2) the tactile sensation produced by the coil’s dis- charge is identical across conditions (acoustic sensations were largely eliminated by the use of masking noise dur- ing the session). For these reasons, a sham control was not included. Methods Participants Twenty-two participants recruited from the North Dakota State University undergraduate and graduate population completed the experiment for paid compensation ($20/hr). All participants were between the ages of 18 and 35 years, (age M = 22 years, 15 women), were right- handed, reported normal or corrected-to-normal visual acuity, and had normal color vision (as established with the Ishihara color vision test). Participants gave informed consent and were screened for the presence of neurolog- ical and psychiatric conditions and other risk factors related to the application of both MRI and TMS before par- ticipation (based on guidelines for TMS safety set forth in Rossi, Hallett, Rossini, & Pascual-Leone, 2009). One partic- ipant was excluded because of very low performance (guess rate > 2 Sds below the mean across all conditions),
bringing the final N to 21. The results do not change when
this participant is included.

TMS Targeting and Stimulation

TMS was delivered with a Magstim Super Rapid 2 mag-
netic stimulator fit with a focal bipulse, figure of eight
70-mm stimulating coil (Magstim, Whitland, Reino Unido). TMS

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targeting and online guidance was achieved using a
Visor2 neuronavigation system (Advanced Neuro Tech-
nología, Enschede, Los países bajos) that uses infrared-
based frameless stereotaxy to map the position of the coil
and the participant’s head within the reference space of
the individual’s high-resolution anatomical MRI. Whole-
brain T1-weighted anatomical MRI scans were acquired
with a GE Signa HD 1.5-T MRI scanner for each partici-
pant before participation (206 axial slices, with a resolu-
ción de 1 mm). Throughout the experiment, Participantes
listened to constant masking noise played through a pair
of inserted earplugs. The volume of the masking noise,
which never exceeded 90 dB, was adjusted immediately
before the experimental session for each participant until
the “click” produced by the discharge of the TMS coil
could no longer be heard ( Johnson, Kundu, Casali, &
Postle, 2012; Esser et al., 2006).

Phosphene Localization and Thresholding

Phosphene localization procedures and all subsequent
stimulus presentation and response recording were con-
trolled by a PC running Matlab with Psychophysics Tool-
box extensions (Brainard, 1997; Pelli, 1997). The right
primary visual cortex was first identified and targeted
on the basis of individual anatomy, and target coordi-
nates were further refined by determining the coil posi-
tion and orientation that elicited visual phosphenes in a
particular region of visual space (van de Ven et al., 2012).
Para hacer esto, participants fixated a central white cross pre-
sented against a black background while single pulses of
TMS were administered to visual cortex at 70% of stimu-
lator output. Coil position and orientation were then ad-
justed until reproducible phosphenes were visible in the
hemifield contralateral to stimulation. Once phosphenes
were induced, participants used a computer mouse to
draw a circle around the region in the visual field where
the phosphenes appeared. Responses were recorded as
both an image file and as the x–y coordinates of all
mouse locations. The coil position was then adjusted un-
til reliable phosphenes were produced overlapping or ad-
jacent to the location of the sample display items (para
stimulus positions, see Experiment 1 Métodos). Phos-
phenes were considered to be elicited when the follow-
ing criteria were met: Phosphenes could be localized in
both left and right hemispheres, phosphenes were elicit-
ed with eyes shut, and phosphenes moved with fixation
(Kammer, 1998). Following phosphene localization,
phosphene thresholds were established. Stimulator in-
tensity was reduced by increments of 5%, y 10 pulses
were delivered at each intensity until phosphene thresh-
viejo, defined as the minimum intensity required to elicit
phosphenes 50% of the time, was established. durante el
experimento, pulses were administered to the right hemi-
sphere at 110% of phosphene threshold. Average stimu-
lation intensity was at 67% of stimulator output (range =
57–82%). Postexperiment debriefing confirmed that TMS

at this intensity did not give rise to visible phosphenes
during performance of the color recall task, en el cual
stimuli were presented against a light gray background
and attention was focused on the task.

Stimuli and Procedure

Stimuli and procedure were identical to Experiment 2,
except that TMS pulses, rather than visual masks, eran
applied at varying intervals relative to stimulus onset
(see Figure 1C). Viewing distance was held constant at
70 cm, and head position was stabilized using a chinrest.
spTMS was administered either 0, 100, o 200 msec post-
stimulus offset.

Resultados

Analysis of Absolute Error

Absolute error for each combination of TMS side and tim-
ing can be seen in Figure 4A. As in Experiment 2, differ-
ences in absolute error across conditions were assessed
by a two-way (2 Mask × 3 Timing) repeated-measures
ANOVA. Contrary to the masking data, neither main
effect reached significance ( ps = .20 y .23 for side
and timing, respectivamente). Sin embargo, there was a trend to-
ward a significant Side × Timing interaction, F(2, 40) =
2.608, pag = .086, ηp
2 = 0.12, with somewhat elevated
absolute error for targets contra versus ipsi to the stimu-
lated hemisphere when TMS was applied 0-msec post-
stimulus offset.

Analysis of Mixture Model Fits

As with Experiment 2, estimates of response errors were
derived from the three-component mixture model pro-
posed by Bays et al. (2009). Comparison of model fits
using the log likelihood and cAIC suggested that the
three-component model performed better than the
two-component model for the majority of participants
(100% versus 82% for log likelihood and cAIC, respetar-
activamente). Average estimated model parameters are de-
picted in Figure 4B. As in Experiment 2, three separate
2 (Visual hemifield: contra vs. ipsi to stimulated hemi-
sphere) × 3 (TMS timing: 0, 100, o 200 msec after stim-
ulus display offset) repeated-measures ANOVAs were
conducted, one each for g, Dakota del Sur, and swap errors. For both
the log likelihood and cAIC, we compared the computed
scores for each model with a paired sample t test. El
three component model provided a significantly superior
fit for both the cAIC, t(20) = 2.34, pag = .03 (mean differ-
ence = 26.41, DE = 51.70), and log likelihood, t(20) =
−2.52, pag = .02 (mean difference = −14.22, DE = 25.85).

Guess rate. A TMS-related increase in g was found when
stimulation was applied coincident with stimulus offset.
Específicamente, the ANOVA revealed no main effects of

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pag = .02, which was just above the corrected threshold
value for significance (critical p = .0167). No effects of
TMS on guess rate were found at either 100 mseg, t(20) =
.48, pag = .63, o 200 mseg, t(20) = .99, pag = .33.

Standard deviation. The ANOVA revealed a main effect
of Stimulation side, F(1, 20) = 5.05, pag = .04, ηp
2 = 0.20, pero
no main effect of Timing, F(2, 40) = 1.45, pag = .25, ηp
2 =
0.07, and a marginal interaction, F(2, 40) = 2.80, pag = .07,
ηp
2 = 0.12. Sin embargo, post hoc t tests revealed no significant
differences in standard deviation between the contralateral
and ipsilateral hemifield when TMS was applied at 0, t(20) =
−1.40, pag = .18, 100, t(20) = 2.14, pag = .045 (critical p =
.0167), o 200 mseg, t(20) = .83, pag = .42.

Curiosamente, analysis of swap rate revealed
Swap rate.
an overall decrease in swap errors for targets in the con-
tralateral hemifield, but this was not specific to a particu-
lar TMS timing. The ANOVA revealed a main effect of
Stimulation side, F(1, 20) = 5.44, pag = .03, ηp
2 = 0.21,
but no effects of timing, F(2, 40) = .44, pag = .65, ηp
2 =
0.02, and no interaction, F(2, 40) = 1.14, pag = .33, ηp
2 =
0.05.

Discusión

These data demonstrate that TMS of the early visual cor-
tex produced temporally and topographically specific ef-
fects on g, an index of the number of items that were
successfully stored in VWM. Específicamente, when applied
coincident with the offset of the stimulus display, spTMS
increased the likelihood of making a guess response for
targets appearing in the visual hemifield contralateral to
the stimulated cortex (es decir., the left visual field following
right visual cortex stimulation). Contrary to our predic-
ciones, TMS only produced a small effect on SD. A pesar de
the effect on SD appeared to be specific to the 100-msec
condición, the TMS Timing × Visual Hemifield interac-
tion of the ANOVA was not significant, nor was the
post hoc t test looking at differences in SD at this interval.
Además, contrary to our predictions, the effects of
spTMS on both g and SD were entirely absent by
200 msec after stimulus offset (es decir., 350 msec poststimu-
lus onset). Contrasting with these disruptive effects,
spTMS also produced a temporally nonspecific reduction
in the likelihood of making swap errors for targets in the
contralateral hemifield (es decir., swap errors were less likely
when estimating the color of targets contra vs. ipsi to
the stimulated hemisphere). The effects of TMS on g
and SD are qualitatively similar to the findings of van
de Ven et al. (2012), who found that spTMS was no lon-
ger effective at later time points, when consolidation is
presumably already completed. Sin embargo, these results
go beyond their findings by demonstrating temporally
and topographically specific effects on the parameters
of the mixture model, which may map on to qualitatively
distinct sources of error in recall WM tasks.

Cifra 4. Results from Experiment 3. A TMS-related increase in guess
rate was found in (A) absolute error and (B) guess rate at 0 mseg
poststimulus offset and an increase in standard deviation (C) was found
en 100 msec post offset. A TMS-related increase in swap rate was found
across all time points (D).

either stimulation side, F(1, 20) = 2.41, pag = .14, ηp
2 =
0.11, or TMS timing, F(2, 40) = 1.33, pag = .28, ηp
2 =
0.06, but there was a significant interaction between Tim-
ing and Stimulation side, F(2, 40) = 3.69, pag = .03, ηp
2 =
0.16. Follow-up post hoc t tests revealed an increase in
guess rate for targets in the contralateral versus ipsilateral
hemifield when TMS was applied at 0 mseg, t(20) = 2.50,

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GENERAL DISCUSSION

This study sought to clarify the functional relevance of
early visual cortex contributions to VWM. Para hacer esto,
we presented visual pattern masks or administered single
pulses of TMS to retinotopic visual cortex at different
time points relative to the offset of a stimulus display.
To determine the nature of the influence of masks and
TMS on the formation of VWM representations, parti-
cipants’ memory for the sample display colors was
assessed using either delayed recognition (change detec-
ción) or cued recall, which made it possible to separately
estimate the number of items stored in WM and the pre-
cision of the stored information. críticamente, a pesar de
memory stimuli could be encoded from either the lower
left or lower right visual fields, as determined by a spatial
cue presented at the beginning of each trial, both masks
and TMS selectively targeted the lower left visual field.
De este modo, performance for stimuli encoded from the lower
right visual field served as a within-subject control (como
in van de Ven et al., 2012). Across experiments, we ob-
served similar effects of masks and TMS on memory for
items appearing in the affected visual field, although the
effects of masks were generally more pronounced. Spe-
cifically, visual masks impaired change detection perfor-
mance (Experimento 1) and increased the likelihood of
making a guess-like response (Experimento 2) for targets
appearing in the lower-left visual field, and spTMS in-
duced a similar increase in guessing for stimuli in the vi-
sual field contralateral to the targeted hemisphere
(Experimento 3). Both masks and TMS produced the larg-
est effects when applied coincident with stimulus offset,
with the disruption either entirely dissipating (Experi-
mentos 1 y 3) or growing progressively smaller (Exper-
mento 2) the further into the retention interval it was
aplicado. Visual masks and TMS also produced small and
variable effects on the standard deviation of responses.
Finalmente, TMS produced an unexpected decrease in swap
errors for targets appearing in the affected hemifield.
These findings have several implications for our under-
standing of the time course and functional relevance of
early visual cortex to VWM.

Regarding the question of whether masks (and TMS)
affect the number of items stored or their quality, resultados
of the mixture model analysis in Experiment 2 confirmed
the findings of Zhang and Luck (2008), who found that
masks primarily affect performance by reducing the prob-
ability that an item is encoded into VWM, rather than in-
creasing the variability of recall responses (Dakota del Sur). Similarmente,
Experimento 3 revealed that TMS applied to early visual
cortex coincident with stimulus offset produced an in-
crease in guess rate for targets presented in the contra-
lateral visual field. Although there were also effects on
Dakota del Sur, these effects were more variable, and post hoc tests
suggested that they were not reliable at any of the tested
latencies. De este modo, taken together, these results support the
proposal of van de Ven et al. (2012) that interfering with
activity in early visual cortex likely disrupts an ongoing
process of memory consolidation, suggesting a functional

role for early sensory areas in the initial formation of
VWM representations.

Although the mechanisms underlying the functional
effects of spTMS are not well understood, research by
Harris and colleagues (2008) suggests that the pattern
of disruption observed here and in the study of van de
Ven et al. (2012) may have been caused by a TMS-related
decrease in signal intensity, rather than an increase in ran-
dom image noise (Abrahamyan et al., 2011; Schwarzkopf
et al., 2011). This would explain the finding of more robust
and reliable effects on guessing, rather than standard devi-
ación. Although the precise mechanism by which TMS in-
duces these effects is unclear, a recent optical imaging
study examining the effects of TMS on cat visual cortex ac-
tivity suggests that the reduction in signal intensity may be
caused by TMS-induced local cortical inhibition (Kozyrev,
Eysel, & Jancke, 2014). In their study, single pulses of
TMS applied to the visual cortex were found to induce a
localized pattern of inhibition that lasted approximately
300 msec before returning to baseline. Assuming similar
mechanisms are at work in human visual cortex, this brief
period of inhibition may be adequate to disrupt the initial
formation of WM representations, without affecting later
activity once consolidation is complete. Whether this is cor-
rect will require further work examining the neural effects
of TMS. En particular, this question could be profitably ad-
dressed by the adoption of a computational neurostimula-
tion approach, in which the effects of simulated TMS
pulses are examined in the context of realistic neural
models of the consolidation and maintenance of informa-
tion in WM (for discussion of this approach, see Bestmann
& Feredoes, 2013).

Another notable aspect of the data that speaks to the
functional role of the early visual cortex in VWM is the
time course of the effects of masks and TMS on perfor-
mance. If activity in the early visual cortex is critical for
both the initial consolidation and later maintenance of
information in VWM, as has been proposed by sensory
recruitment models of WM (D'Esposito & Postle, 2015),
we expected TMS to disrupt performance at all latencies
probado. Contrary to this possibility, in each experiment,
the effects of TMS and of masks were either substantially
reduced or entirely absent when stimulation was applied
at later time points, when consolidation was nearing
completion and short-term maintenance had presumably
begun. These findings match those of van de Ven et al.
(2012), who observed a significant disruption of perfor-
mance when spTMS was applied 200 msec after memory
display offset, pero no 200 msec later. Similarmente, Beckers
and Hömberg (1991) reported no effect on performance
when spTMS was applied to the visual cortex during the
retention interval of a delayed match to sample task re-
quiring memory for faces, although performance was dis-
rupted by TMS applied during retrieval.

These findings suggest that early visual cortex in-
volvement in VWM may be restricted to an early consol-
idation time window during which fragile sensory

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representations are being transformed into more dura-
ble VWM representations.

This conclusion is consistent with several lines of evi-
dence suggesting that, although initial perceptual process-
ing depends on activity in early visual areas, maintenance in
VWM likely depends on activity in higher-order cortical
areas, such as the parietal or frontal cortex (Bettencourt
& Xu, 2016; Mendoza-Halliday, Torres, & Martinez-Trujillo,
2014; Xu, 2010; Xu & Chun, 2006; Todd & Marois, 2004,
2005). Por ejemplo, using fMRI and multivoxel pattern
clasificación, Bettencourt and Xu (2016) reported that
the ability to decode the orientation of a remembered
stimulus from patterns of activity in specific regions of
the occipital and parietal cortex differed depending on
whether new, task-irrelevant stimuli were presented
during the delay. Although it was possible to decode item
orientation from both areas during an unfilled delay,
when task-irrelevant distractors were presented, decoding
from early visual areas was no longer possible, incluso
though task performance was unaffected by the new in-
put. Por el contrario, decoding from the superior intraparietal
sulcus, a region that has been implicated in setting capac-
ity limits in WM (Todd & Marois, 2004, 2005), remained
intact and closely tracked WM task performance.

Similarmente, a recent neurophysiological recording study
in macaques (Mendoza-Halliday et al., 2014) found that,
although the direction of motion of a stored stimulus
could be decoded from local field potential activity
recorded in the motion-selective middle temporal area
(MONTE), stimulus-specific spiking activity was only ob-
served in higher-order, multimodal areas. Además, bajo-
frequency neural oscillations in MT were phase-coherent
with spiking activity in the frontal cortex, suggesting that
the local field potential activity supporting decoding in
MT was likely driven by feedback inputs from the frontal
or parietal cortex, rather than reflecting memory-related
activity arising in early visual area MT itself. Findings such
as these suggest that, although it may be possible to
decode stimulus identity from the early visual cortex in
some cases, this activity may not be causally necessary
for storage in WM.

In a reply to the study of Bettencourt and Xu (2016),
Ester, Rademaker, and Sprague (2016) pointed out that a
failure to decode from a given area does not constitute
strong evidence against this area’s involvement in the
process in question. Por ejemplo, it remains possible that
the visual cortex was engaged in storage in the distractor
condition of Bettencourt and Xu (2016), but at a level
that was inaccessible to multivoxel decoding analyses
(see Dubois, de Berker, & Tsao, 2015, for evidence dem-
onstrating such a failure of decoding in the macaque face
patch system). Similar arguments have been forwarded
to explain several notable failures to decode item identity
from delay period activity in both frontal and parietal re-
gions (Emrich et al., 2013; Linden, Oosterhof, Klein, &
Downing, 2012; Riggall & Postle, 2012). Por ejemplo, en
a recent review paper, Riley and Constantinidis (2016)

argue that the spatial resolution of fMRI may be insuffi-
cient to support successful decoding of item identity
from the frontal cortex, which is characterized by non-
topographic organization and the representation of in-
formation at spatial scales that can be an order of
magnitude finer than the resolution of fMRI. Given this,
failures to decode the contents of WM from the frontal
cortex would be expected, even if this information is
robustly represented in this area.

This discussion highlights potential limitations in the
kinds of inferences that can be drawn from pattern clas-
sification analyses alone. Por un lado, as noted by
Ester et al. (2016) and Riley and Constantinidis (2016),
a failure to decode does not necessarily constitute strong
evidence against a particular area’s involvement in a
given process. Por otro lado, the results of
Bettencourt and Xu (2016) and Mendoza-Halliday et al.
(2014) suggest that the ability to decode from a particular
area is no guarantee that this area is causally necessary
for storage. One way of addressing these inferential lim-
itations is to adopt causal methods such as TMS, as we
have done here. Fundamentalmente, in both our study and that of
van de Ven et al. (2012), TMS only disrupted perfor-
mance when applied relatively early in the delay period
(see also Beckers & Hömberg, 1991). Estos hallazgos
strongly suggest that, although it is sometimes possible
to decode item identity from this area, the early visual
cortex is likely not causally necessary to represent item
information beyond the time period of initial memory
consolidation.

Finalmente, in addition to the temporally specific disruptive
effects of TMS on guess rate, we also observed a signifi-
cant main effect of stimulation side on swap rate (es decir., en
the likelihood of confusing the cued item with one of the
other items in memory). Contrary to what we would have
esperado, the swap rate was significantly reduced for tar-
gets appearing in the affected hemifield across all inter-
vals tested. Eso es, TMS appears to have had a reliable
enhancing effect for contralateral targets, increasing the
likelihood of correctly binding individual colors to specif-
ic locations. According to Bays et al. (2009), swap errors
likely arise as a result of coarse coding of the spatial po-
sitions of remembered features. This can lead to confu-
sion about which item to report at test, particularly when
either a large number of items need to be remembered
(Bays et al., 2009) or when stimuli are presented very
close together in space (Emrich & Ferber, 2012). Uno
means by which TMS could reduce this type of error,
por lo tanto, is if it serves to sharpen the spatial tuning of
neurons in the stimulated area. Although we are unaware
of any direct evidence supporting this possibility, the re-
sults of Kozyrev et al. (2014) discussed above are sugges-
tivo. In their study, single pulses of TMS were found to
produce a short-lived, localized increase in inhibition,
which they attribute to a selective effect of TMS on inhib-
itory interneurons. Increased inhibition has, Sucesivamente, estado
shown to produce a sharpening of neural tuning in

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various sensory cortical areas (Isaacson & Scanziani,
2011). If spTMS of the visual cortex in our study in-
creased inhibition and this increase sharpened the tuning
of cells coding for the spatial position of remembered
elementos, this could explain the beneficial effect of TMS on
color–location binding. This possibility is frankly specula-
tivo, but it could be tested by assessing the impact of
spTMS of early visual cortex on recall of the spatial posi-
ción, rather than color, of a remembered item. If this were
the case, we would expect TMS to produce an improve-
ment in the resolution of spatial recall (es decir., reduced SD).
TMS as applied here is a powerful method of determin-
ing the functional relevance of a particular brain area.
Future work could benefit by stimulating a wider range
of areas and/or localizing TMS targets using functional
criteria. Por ejemplo, current models and data suggest
that WM functions are likely supported by distributed ac-
tivity within a network of partly functionally specialized
regiones del cerebro, rather than being mediated by a single area
(Ester et al., 2016; D'Esposito & Postle, 2015; Ester,
sprague, & serencias, 2015). Future research could ben-
efit by targeting other regions within this network, semejante
as the parietal or pFC, to determine their specific contri-
butions to WM. Además, although the current study
suggests that early visual cortex is not causally necessary
for WM storage, different results may be achieved by
targeting specific subregions of the visual cortex on the
basis of functional criteria, rather than phosphene
perception alone. Por ejemplo, TMS targeting could be
guided by fMRI scans aimed at localizing specific areas
exhibiting particular functional characteristics (p.ej., color
selectivity or load sensitivity) by selecting regions on the
basis of accurate classification of stimulus features or via
TMS-based localization of feature-specific regions. As an
example of the latter, Banissy, Walsh, and Muggleton
(2012) have shown that continuous theta-burst stimula-
tion applied to area V4 disrupted color priming effects
in a subsequent task. A procedure such as this one could
be used to localize color-selective areas of visual cortex
before the application of TMS during a color WM task.
It is possible that localizing stimulus-selective regions in
this way could reveal a role of visual cortex in WM main-
tenance. This is still to be determined however, and ad-
ditional research will be required to determine the
functional roles of each region in the network of brain
areas associated with WM functioning.

En conclusión, results of this study suggest that inter-
fering with visual cortex activity by either presenting
visual masks or directly stimulating the cortex with TMS
disrupts performance primarily by influencing the num-
ber of items that are successfully stored, with smaller,
more variable disruptions of the quality of VWM repre-
sentation. En cada caso, observed disruptive effects were
largest when interference was applied very early during
the retention interval, growing smaller or disappearing
altogether at later intervals. Además, TMS also pro-
duced longer-lasting, location-specific improvements in

color–location binding. Tomados juntos, this pattern of
results echoes recent findings suggesting that early visual
cortex involvement in VWM for object features may be
restricted to the period of time during which fragile
sensory representations are being transformed into more
durable VWM representations, with its role dissipating
the further one goes into the retention interval.

Reprint requests should be sent to Amanda E. van Lamsweerde,
North Dakota State University, departamento. 2765, P.O. Box 6050,
Fargo, ND 58108, o por correo electrónico: amanda.vanlamsweerde@
ndsu.edu.

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