Overlapping activity periods in early visual cortex and posterior intraparietal area in conscious visual shape perception: A TMS study

NeuroImage 84 (2014) 765–774

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Overlapping activity periods in early visual cortex and posterior intraparietal area in conscious visual shape perception: A TMS study Mika Koivisto a,b,⁎, Mikko Lähteenmäki a,b, Valtteri Kaasinen c,d, Riitta Parkkola d,e, Henry Railo a,b a

Department of Psychology, University of Turku, FI-20014 Turun yliopisto, Finland Centre for Cognitive Neuroscience, University of Turku, FI-20014 Turun yliopisto, Finland Division of Clinical Neurosciences, University of Turku and Turku University Hospital, FI-20521 Turku, Finland d Turku PET Centre, University of Turku and Turku University Hospital, FI-20521 Turku, Finland e Department of Radiology, University of Turku, FI-20014 Turun yliopisto, Finland b c

a r t i c l e

i n f o

Article history: Accepted 20 September 2013 Available online 29 September 2013 Keywords: Consciousness Parietal cortex TMS V1

a b s t r a c t Parietal cortex is often activated in brain imaging studies on conscious visual processing, but its causal role and timing in conscious and nonconscious perception are poorly understood. We studied the role of posterior intraparietal sulcus (IPS) and early visual areas (V1/V2) in conscious and nonconscious vision by interfering with their functioning with MRI-guided transcranial magnetic stimulation (TMS). The observers made binary forced-choice decisions concerning the shape or color of the metacontrast masked targets and rated the quality of their conscious perception. TMS was applied 30, 60, 90, or 120 ms after stimulus-onset. In the shape discrimination task, TMS of V1/V2 impaired conscious perception at 60, 90, and 120 ms and nonconscious perception at 90 ms. TMS of IPS impaired only conscious shape perception, also around 90 ms. Conscious color perception was facilitated or suppressed depending on the strength of the TMS-induced electric field in V1/V2 at 90 ms. The results suggest that simultaneous activity in V1/V2 and IPS around 90 ms is necessary for visual awareness of shape but not for nonconscious perception. The overlapping activity periods of IPS and V1/V2 may reflect recurrent interaction between parietal cortex and V1 in conscious shape perception. © 2013 Elsevier Inc. All rights reserved.

Introduction What kind of neural activity is able to create conscious, subjective experiences? In recent cognitive neuroscience, this issue has been studied intensively by focusing on the neural correlates of visual awareness and contrasting them with the correlates of nonconscious perception. A broad distinction between ventral and dorsal visual streams has been suggested to correspond to the distinction between conscious and nonconscious perception (Goodale and Milner, 1992; Ungerleider and Mishkin, 1982). The ventral stream projects from the primary visual cortex (V1) to occipitotemporal cortex. It constitutes a vision-forperception system which constructs a consciously accessible representation. The dorsal stream projects to posterior parietal cortex which also receives direct projections from superior colliculus, bypassing V1 (Benevento and Standage, 1983; Goodale and Milner, 1992). The dorsal stream transforms the object parameters for control of action and its representations are not assumed to be accessible to consciousness (Milner and Goodale, 1995).

⁎ Corresponding author at: Centre for Cognitive Neuroscience, University of Turku, Assistentinkatu 7, FI-20014 Turun yliopisto, Finland. E-mail address: mika.koivisto@utu.fi (M. Koivisto). 1053-8119/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.neuroimage.2013.09.051

Functional magnetic resonance imaging (fMRI) has confirmed that neural activity in the ventral stream correlates with conscious visual perception, but conscious perception is often associated also with the activation of parietal and prefrontal cortices (Dehaene and Changeux, 2011; Rees, 2007). The same parietal and frontal areas are associated with attention and it is not clear whether their activation is the cause or consequence of consciousness (Tallon-Baudry, 2012). On the other hand, the activity of parietal areas has been suggested to explain how perceptual information may influence behavior such as reaction times even when the information is not consciously experienced (i.e., nonconscious perception; e.g., Danckert and Rossetti, 2005). This proposal is plausible because the parietal cortex is involved in visuomotor processing (Grefkes and Fink, 2005), and receives direct input from subcortex (Benevento and Standage, 1983; Goodale and Milner, 1992). In the present study, we interfered with the activity of parietal cortex with transcranial magnetic stimulation (TMS) to examine whether the parietal cortex has a causal role in the early stages of processing that lead to conscious or nonconscious perception. A fast activation of coarse low-resolution representations in the dorsal stream has been proposed to modulate the slower construction of high-resolution representations in the ventral stream in top-down manner (Bar, 2003; Bullier, 2001; Chen et al., 2007). Indeed, microstimulation and single-cell recordings in macaques have shown reciprocal pathways between the fronto-

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parietal network and occipital areas (Moore and Armstrong, 2003). Neurons in the lateral intraparietal area (LIP) of monkeys are activated within 50 ms after the onset of the visual stimulus, indicating that LIP receives a rapid sensory signal that might be used for modulating ongoing activity in the early visual areas (Bisley et al., 2005). In humans, TMS of parietal cortex modulates the excitability of the early visual cortex (Silvanto et al., 2009) as well as the activity level of visual cortex during visual stimulation (Leitão et al., 2013), but the timing and the possible causal contribution of parietal areas to conscious or nonconscious perception of visual stimuli remain unclear. Most of the previous TMS studies on human parietal cortex during visual processing have focused on attention, visual search, or feature binding. The parietal cortex has been shown to contribute to attention (Chambers et al., 2004; Lee et al., 2013), to search and binding of feature conjunctions (Ashbridge et al., 1997; Koivisto and Silvanto, 2012; Muggleton et al., 2008, 2011) and to spatial binding (Zaretskaya et al., 2013), but causal evidence for the involvement of parietal areas specifically in visual consciousness is rare. However, Kanai et al. (2008) observed that TMS applied over the intraparietal sulcus (IPS) before the onset of a visual stimulus sped up the fading of the stimulus from consciousness. The posterior intraparietal area (IPS1, IPS2) is a candidate area that might play a role in conscious perception by sending top-down signals to early visual cortex (Lauritzen et al., 2009). Furthermore, recent brain imaging has revealed that the posterior intraparietal area responds strongly to visual shape (Konen and Kastner, 2008), suggesting that it might contribute directly to shape perception. Thus, the posterior IPS1 in the caudal end of IPS, which may correspond to monkey cIPS (Culham and Kanwisher, 2001), was targeted with single pulse TMS at different latencies during shape and color perception tasks. The aim was to examine whether it plays a critical role in conscious or nonconscious perception of shape. Conscious and nonconscious perception were distinguished on the basis of perceptual awareness scale (Ramsøy and Overgaard, 2004; Sandberg et al., 2010). TMS was applied also over V1 in order to compare the timing of IPS's possible contribution with that of early visual areas. In addition to the standard statistical analyses of the effects of TMS on group level performance, we examined whether the strength of the TMS-induced electric field (E-field) in the IPS and V1/V2 target areas influence the probability of conscious perception. Material and methods Participants Fourteen healthy, right-handed, 21–34 years old undergraduate or graduate students (5 males) from the University of Turku were recruited. They all had normal or corrected-to-normal vision, but one of them was excluded as she could not perceive the shape of the visual target stimuli during the pre-experimental practice blocks. The experiment was conducted in accordance with the Declaration of Helsinki and with the understanding and written consent of each subject. The study was accepted by the Ethics Committee of The Hospital District of Southwest Finland. TMS Single biphasic TMS pulses were administrated with a Nexstim Ltd. (Helsinki, Finland) eXimiaTM stimulator and Nexstim biphasic 70 mm figure-of-eight coil. Earplugs were used to attenuate the sound of the TMS-induced noise and a chin rest was used to keep the head position stable. The coil was fixed on a holder and the coil plane was positioned tangentially on the head. For each participant, a high-resolution T1-weighted anatomical MRIimage of the brain was acquired (1.5-T Philips Intera scanner or 3-T Signa VH/I; 3D-sequence 256 × 256 matrix, 1 mm slice thickness, and 0 mm slice gap). The TMS pulses were directed to the targeted areas

by using MRI-guided eXimia Navigated Brain Stimulation (NBS) system (Nexstim Ltd.) which continuously registers the relationship between the brain and the TMS coil with a spatial resolution of 2 mm. V1, located in the calcarine fissure, was localized on the basis of individual MRI images. Note, however, that TMS of V1 will inevitably stimulate also the near-by surrounding early visual areas (Salminen-Vaparanta et al., 2012; Thielscher et al., 2010); therefore we refer to stimulation of early visual cortex or V1/V2 rather than V1. The upper bank of the calcarine fissure represents the lower visual field and is closer to the skull than the lower bank which represents the upper visual field. The lower VF representation is more easily accessible with TMS (SalminenVaparanta et al., 2012) and therefore in the V1/V2 stimulation condition the TMS pulses were targeted to the occipital pole, to the midline between the upper banks of the left and right calcarine fissures (average Talairach coordinates: −2, −77, 26) (Fig. 1). The stimulation of this site was thus expected to influence the processing of the visual stimuli presented in the lower VF. The IPS target area was located in the posterior part of the intraparietal sulcus in the right hemisphere. The IPS in the right hemisphere was targeted as previous studies on parietal cortex have produced successful effects by stimulating the right hemisphere (e.g., Ashbridge et al., 1997; Koivisto and Silvanto, 2012). The area was first coarsely localized on the basis of normalized MRI images of each individual by using the Talairach coordinates of IPS1 (−24, −74, 40) from Konen and Kastner (2008). A marker for the target area was then entered into the NBS system and its final position was manually adjusted so that it was located between the walls of the sulcus. During the experimental stimulus blocks, TMS intensity was set to 67% of the maximum output of the stimulator. Consistent with our previous experience using 65–70% output power with the same equipment (Koivisto and Silvanto, 2012; Koivisto et al., 2011a, 2011b, 2012), this intensity did not produce eye blinks, muscle twitches, or other uncomfortable sensations. The direction of electric current in the second phase of the biphasic TMS pulse was from left to right during the V1/V2 stimulation and from top to bottom during the IPS stimulation. The strength of the TMS-induced electric field (E-field) in the V1/V2 and IPS target areas was estimated with the eXimia NBS system that models the intracranial TMS-induced E-field by using the spherical conductor model (Heller and van Hulsteyn, 1992; Sarvas, 1987). This procedure takes into account the shape of the copper spirals inside the TMS coil, the orientation and location of the coil, current direction, and the overall shape of the head and the brain. The accuracy of the spherical modeling is sufficient for analyzing correlations between the E-field strength in the visual cortex and the TMS-induced visual suppression (Koivisto et al., 2011a) but for more detailed description and discussion of the E-field modeling with eXimia and the spherical conductor model, see Salminen-Vaparanta et al. (2012). Stimuli The stimuli appeared on a white background (51cd/m2) in a 19″ CRT monitor (75 Hz, 1024 × 768 pixels), presented with E-prime software (Psychology Software Tools, Inc.) from a viewing distance of 150 cm. In the shape task, the targets (0.8° × 0.3°) were gray arrows pointing either to the left or to the right (Fig. 2). In the color task, the shape of the target was identical to that in the shape task with the exception that the arrowhead of the target was removed so that the stimulus was symmetrical (i.e., neutral) in the left–right orientation. The luminance of the gray, blue and red colors was matched (3.7 cd/m2). The shape of the mask was identical in both tasks (1.3° × 0.5°). It was a typical metacontrast mask (Breitmeyer and Öğmen, 2006): its inner center was white so that the outer contour of the target touched but did not overlap with the inner contour of the mask. In the shape task, the mask was gray. The color task needed a more effective mask which was achieved by presenting the mask in black (0.4 cd/m2). The stimuli were centered 2.1° away from the fixation cross and presented randomly to the lower VF or to the upper VF.

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Fig. 1. Left: The orange spot shows the V1/V2 target area in the upper bank of the calcarine fissure from the sagittal view in the MRI image of a representative participant. Right: The posterior intraparietal target area is indicated by the orange spot for the same participant in the 3-dimensional image from the NBS system. The red color identifies the hotspot of the TMSinduced E-field during the intraparietal stimulation; the colors red–yellow–green–blue indicate in decreasing order the E-field strength. The red spot in the midline shows the V1/V2 target area.

Experimental procedure Each participant was tested in two separate sessions. In each session, they accomplished eight experimental stimulus blocks, four in the shape task and four in the color task. The task was changed after four blocks. In half of the blocks, V1/V2 was stimulated with TMS and in half of the blocks IPS was stimulated. The stimulation area was changed after two blocks. The order of the tasks and the order in which the areas were stimulated were balanced across the participants. For each participant, the task and stimulation order that was used in the first session was reversed in the second session. Each trial (Fig. 2) began with the presentation of the fixation point for 560 ms, followed by the target for 13 ms. The target appeared randomly in half of the trials in the lower VF and in half in the upper VF. After individually adjusted target-mask delay (on average 75 ms), the mask was presented for 160 ms. In the shape task, the participants made a forced-choice discrimination response concerning the left or right orientation of the target. In the color task, they made a forced-

choice discrimination response concerning the color (red or blue) of the target. After the forced-choice response, they were asked to report their subjective awareness of the target by pressing one of four buttons (0 = “I did not see the target at all”; 1 = “I saw a glimpse of something but I did not have any trace of the orientation/color of the target”; 2 = “I had a weak conscious perception of the orientation/color”; 3 = “I had a clear conscious perception of the orientation/color”). It was stressed that ratings 0 and 1 meant that the participant did not have any conscious perception of the orientation/color of the target. Each stimulus block involved 16 NoTMS trials (in which the visual stimuli were presented without TMS pulses) and 48 TMS trials. In the TMS trials, the pulse was delivered randomly at visual target-TMS onset-asyncronies (SOAs) of 30, 60, 90, or 120 ms. The blocks involved also 4 NoTMS catch trials and 4 TMS catch trials in which no visual target was presented. For each participant, each stimulation area condition (i.e., V1/V2 and IPS) in the shape task involved in total 64 NoTMS trials, 48 TMS trials at each pulse delay, as well as 16 catch trials with and 16 without TMS. In the color task, the number of corresponding trials was the same. The target-mask delay was adjusted for each participant with the aid of practice blocks which were performed before the experimental blocks in each task. Each practice block consisted of 24 trials (20 targets and 4 catch trials) without TMS. The aim was to find a target-mask delay at which the forced-choice accuracy would be about 75% correct in NoTMS trials in both shape and color tasks. In the first block, the delay was 93 ms. If the participant scored below 60% or higher than 90%, the delay was increased or decreased by one frame (i.e., 13 ms) in the next block. This procedure was continued until a stable accuracy level of about 75% correct was found and the first experimental block started with the corresponding delay. The accuracy level in the NoTMS trials was monitored after each block. If performance in the NoTMS trials deviated from the expected 60–90% range, the delay was increased or decreased for the next block similarly as in the practice blocks. Statistical analyses

Fig. 2. An example of the sequence of visual stimulation in the shape task. The target appeared randomly in the lower or upper field, followed by the mask in the same field. After the offset of the mask, the participants gave a forced-choice decision concerning the left–right orientation of the target and rated the quality of their perception. The sequences were identical in the color task, but the targets were red or blue and the forcedchoice decision and the rating concerned the color of the target.

In the analyses of variance (ANOVAs) with repeated measures, we report Huynh–Feldt corrected p-values always when the degrees of freedom are higher than 1, that is, when TMS is included as a factor. Multiple comparisons of the results at each SOA to the NoTMS condition at the alpha level of 0.05 were corrected with the Benjamini and Hochberg's linear step-up procedure (Benjamini and Hochberg, 1995). The relationships between the strength of the TMS-induced E-field in the brain and visual suppression were analyzed with Pearson's correlation coefficients. As a total of 32 correlations were computed, we used an alpha level of 0.025 in the correlation analyses to reduce the

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probability of Type 1 error (with this alpha level less than one correlation could be expected to be significant due to chance).

condition can serve as a baseline against which to compare the results at each TMS condition also in the analyses of nonconscious perception.

Results

Conscious perception

Baseline performance in the NoTMS trials

Conscious perception (Fig. 4) was operationalized as the proportion of trials in which the subjective rating of awareness indicated that the participant was conscious of target's orientation (in the shape task) or color (in the color task) (“weak conscious perception of the orientation/color” or “clear conscious perception of the orientation/color”) and the forcedchoice response was correct (Koivisto and Silvanto, 2012; Koivisto et al., 2012). First a general Task (2: shape, color)×Area (2: V1/V2, IPS)×Field (2: lower, upper) × TMS (5: NoTMS, 30, 60, 90, 120 ms SOAs) ANOVA was conducted on these scores (for all F and p-values, see Inline Supplementary Table S1). It revealed that TMS impaired conscious perception of targets more in the lower field than in the upper field, and that the performance difference between the lower VF and the upper VF (across TMS conditions) was larger in the shape task than in the color task. Given that this pattern of results suggests that particularly in the shape task TMS influenced perception in the lower field, and we were specifically interested in processing of shape, we studied the effects of TMS in more detail by analyzing the tasks separately. Inline Supplementary Table S1 can be found online at http://dx.doi. org/10.1016/j.neuroimage.2013.09.051. In the shape task, TMS suppressed conscious perception more strongly in the lower than in the upper field (Inline Supplementary Table S2). The influence of TMS was statistically significant only in the lower VF (F(4,48) = 6.30, p b 0.001, η2p = .34) where perception was suppressed in relation to NoTMS baseline at the SOAs of 60, 90, and 120 ms (ps b 0.05, Benjamini–Hochberg corrected). Although the suppressive effects of V1/V2 and IPS stimulation do not reliably differ from each other in the lower VF (F = 1.02, p = 0.404, η2p = .34), inspection of Fig. 4 reveals that at the SOA of 60 ms the suppression effect seems to occur only in the V1/V2 condition. Therefore we tested the statistical reliability of the suppression effects at each SOA separately in the V1/V2 and IPS stimulation conditions by comparing the scores to the NoTMS baseline stimulation conditions. In these analyses, the V1/V2 stimulation suppressed conscious perception significantly at the SOAs of 60, 90, and 120 ms (ps b 0.05, Benjamini–Hochberg corrected), while the stimulation of IPS suppressed conscious perception significantly only at the SOA of 90 ms (p b 0.05, Benjamini–Hochberg corrected). Inline Supplementary Table S2 can be found online at http://dx.doi. org/10.1016/j.neuroimage.2013.09.051.

Fig. 3A shows the distribution of the awareness ratings into the four categories in the shape and color tasks when TMS was not applied (i.e., in the NoTMS trials). A Task (2) × Rating (2) ANOVA reveals a main effect for Rating (F(3,36) = 9.27, p = 0.001, η2p = .44), indicating that the most often used category was “seeing a glimpse of something” which was reported significantly more often than the other three ratings (ps ≤ 0.016). These results show that in most of the NoTMS trials (64%) the participants did not report awareness of the shape or color of the target, but reported that they saw “nothing” or “glimpse of something”. In the catch trials (that is, when only a mask but no target was presented), the participants reported observing “nothing” in 88% of the trials, “glimpse of something” in 8% of the trials, and weak (2%) or clear conscious perception (2%) in the remaining trials. Accuracy of the forced-choice discrimination performance in the NoTMS trials was analyzed as a function reported awareness and task (Fig. 3B). Because some of the participants did not use either the lowest or the highest awareness rating in one of the tasks, we performed the analysis on items with the nonparametric Logit Loglinear analysis which allows examination of interactions in categorical data. The Task × Rating interaction approached statistical significance (Z = 1.79, p = 0.074). Most importantly, accuracy increased as a function of rated awareness (Z = 8.55, p b 0.001). Accuracy in the “seeing nothing” category (61%) was significantly higher than expected by chance (50%), as tested with the chi-square test (χ2 = 26.47, p b 0.001). The same was true for “seeing a glimpse of something” (80%) (χ2 = 578.44, p b 0.001), “weak conscious perception” (87%) (χ2 = 432.65, p b 0.001) and “clear conscious perception” (94%) (χ2 = 336.80, p b 0.001). In summary, these analyses show that the awareness reports were reliable as the forced-choice accuracy increased together with reported awareness. The paradigm was sensitive to influences of nonconscious perception because the accuracy rate was above the chance level also when the participants reported having no awareness of the target or only a glimpse of something. In addition, the procedure can be used for measuring the effects of TMS on both conscious and nonconscious perception, because 36% of the ratings indicated awareness of the orientation or of the color of the target and correspondingly 64% of the ratings indicated unawareness of them. The performance in the NoTMS

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Fig. 3. Performance in the trials without TMS. A) The distribution of ratings into the four categories in the awareness rating scale. B) Discrimination accuracy as a function of the awareness ratings. The error bars in Figs. 3–5 indicate S.E.M.

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Fig. 4. The proportion of trials with conscious perception (A) in the shape task and (B) in the color task when NoTMS or a TMS pulse was applied 30–120 ms after the onset of the visual target over the early visual cortex (V1/V2) or posterior parietal cortex (IPS). The asterisks indicate the situations where TMS impaired conscious perception in relation to NoTMS baseline (Benjamini–Hochberg corrected pair-wise comparisons).

Separate analysis of conscious perception in the color task did not reveal any statistically significant main effects or interactions (Inline Supplementary Table S2).

comparisons of the results at each SOA to those in the NoTMS condition (p b 0.05, Benjamini–Hochberg corrected). Inline Supplementary Table S3 can be found online at http://dx.doi. org/10.1016/j.neuroimage.2013.09.051.

Nonconscious perception

Correlations between the TMS-induced E-field and visual suppression

Due to the frequency distribution of the awareness ratings (Fig. 3), it was possible to study whether TMS influences performance in the trials without reported awareness of the shape or color of the target (“seeing nothing” or “glimpse of something”) in relation to NoTMS baseline. The data of one of the participants was eliminated from the analyses of nonconscious perception, because she reported lack of awareness on average only in 5 trials per cell, while the range was 10–24 for the other participants (N = 12). A Task (2)× Area (2) ×Field (2) ×TMS (5) ANOVA on accuracy in the trials without reported (Fig. 5) revealed a significant four-way interaction (F(4,44) = 3.10, p = 0.026, η2p = .22), suggesting that TMS influenced accuracy differently depending on the stimulation area, task and visual field. Further examination of this interaction with oneway ANOVAs separately on each VF in the V1/V2 and IPS stimulation conditions of the two tasks (Inline Supplementary Table S3) showed that TMS of V1/V2 influenced performance in the shape task when targets appeared in the lower VF. In the lower VF, TMS over V1/V2 decreased accuracy at the SOA of 90 ms, as indicated by pairwise

Suppression scores in the lower and upper VF were calculated by subtracting the scores for conscious perceptions at each TMS SOA in both VFs from those of the corresponding NoTMS conditions in the shape and color tasks. The correlations between these scores with the modeled E-field strength in the V1/V2 and IPS target areas were computed (2 stimulation conditions × 2 tasks × 2 VFs × 4 SOAs = 32 correlations). We found that four correlations were statistically significant (at the alpha level of 0.025) (Fig. 6; Inline Supplementary Table S4). Note that negative suppression scores indicate that TMS did not suppress perception but improved it. Inline Supplementary Table S4 can be found online at http://dx.doi. org/10.1016/j.neuroimage.2013.09.051. Perhaps the most important finding was that in the color task (Fig. 6A), the strength of the E-field in V1/V2 target area and suppression at the SOA of 90 ms in the lower VF correlated positively. Thus, although at group level (Fig. 4) we did not find any effect of TMS on color perception, the correlation reveals that TMS influenced conscious color perception.

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Fig. 5. Nonconscious perception: the proportion of correct discrimination responses in trials without reported awareness in (A) the shape task and in (B) the color task when noTMS or a TMS pulse was applied 30–120 ms after the onset of the visual target over the early visual cortex (V1/V2) or posterior parietal cortex (IPS). The asterisk indicates the situation where TMS impaired conscious perception in relation to NoTMS baseline (Benjamini–Hochberg corrected pair-wise comparisons).

Suppression of conscious perception correlated positively with the strength of the E-field also in the upper VF. In the shape task, a significant correlation was found between the E-field strength in the V1/V2 target area and suppression in the upper VF at the SOAs of 120 ms (Fig. 6B); the nonsignificant positive correlations of V1/V2 field strength with suppression in the upper VF at the SOA of 60 ms and at the SOA of 90 ms are consistent with this finding. In addition, the correlation between the E-field strength in the IPS target area and suppression in the upper VF at 60 ms was significant (Fig. 6C). We found a negative correlation between the strength of the E-field in V1/V2 and suppression in the lower VF at the 120ms SOA in the shape task (Fig. 6D). This finding indicates that the stronger the E-field in V1/V2 was, the less TMS suppressed perception at the longest SOA. This can be explained by the influence of TMS on processing the mask: when TMS is delivered so late that it hits the mask, the masking effectiveness decreases and the visibility of the target increases (Koivisto et al., 2012; Ro et al., 2003). Thus, at the longest SOA, a strong E-field interfered with the masking effectiveness of the visual mask in the shape task. The effect of TMS on the effectiveness of the mask in the lower VF was, however, relatively weak as significant suppression of target was still observed at group level in the ANOVAs. It is plausible that the possible stimulation of the mask representation in the upper VF condition (when lower VF was targeted with V1/V2 TMS) was even weaker, and therefore we did not find a similar negative correlation between E-field and suppression in the upper field. There was no significant relationship between the E-Field strength and visual suppression in the lower VF at those of the SOAs at which TMS of V1/V2 (with the exception of the 120 ms SOA) or IPS produced

statistically significant suppression in the standard ANOVAs. That is because in those conditions the variation in suppression scores was relatively small as most of the participants showed suppression rather than facilitation (e.g., at the SOA of 90 ms, both in V1/V2 and IPS TMS conditions 11 out of the 13 participants showed suppression, while none in the V1/V2 and one in the IPS condition showed facilitation). All the positive correlations occurred in conditions where the visual suppression effects were not significant at group level. This patter was possible because at group level the suppression effects in the participants with strong E-fields were canceled out by the facilitative effects of TMS in the participants with weaker E-fields. This was confirmed with linear regression analyses which revealed that the intercept effects were statistically significant (ps b 0.05) in all the conditions in which the positive correlation between the field and suppression score was found. These findings imply that low TMS-induced E-field produces enhancement of conscious perception, whereas strong E-field causes suppression. Did the effects of V1/V2 stimulation on perception of stimuli in the upper field result from a residual stimulation of the lower bank of the calcarine fissure which is located deeper in the occipital lobe and where the retinotopic V1 representation of the upper VF is located? The mean TMS-induced E-field strength in the posterior lower calcarine fissure was 62.9V/m (SD=14.3), while it was significantly higher in the upper calcarine fissure (101.8, SD = 15.3) (t(12) = 8.08, p b 0.001). The strength of the E-field in the posterior part of the lower bank of the calcarine fissure did not correlate significantly with the visual suppression scores in the upper field (r-values range from −.27 to .22, ps N 0.368), neither did it correlate with the strength of the E-field in the upper bank of the calcarine fissure (r = .32, p = 0.293). This pattern

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Fig. 6. Correlations between the strength of the TMS-induced E-field and suppression of conscious perception.

suggests that the residual E-field in the lower bank of the calcarine fissure was not responsible for the observed correlations in the upper VF. Discussion The contributions of posterior parietal cortex (IPS) and early visual cortex (V1/V2) on conscious and nonconscious perception of shape and color at early latencies were studied with TMS. The results provide causal evidence for the contribution of the posterior IPS on conscious perception of shape. The activity of IPS was critical for conscious perception of shape about 90ms after the onset of the visual stimulus, but it did not play a role in nonconscious perception. The role of V1/V2 was critical for conscious perception of shapes at 60–120ms after the stimulus onset and for nonconscious perception of shapes at 90 ms. These effects were retinotopic, occurring for stimuli presented to the lower VF but not for stimuli in the upper VF. The present results imply a causal role for the posterior IPS in the conscious perception of shape. Thus, our findings are consistent with the idea that the dorsal stream areas are crucial for perception of shape. In fMRI studies, posterior intraparietal areas have been shown to be sensitive to drawings of familiar 2D and 3D object shapes (Durand et al., 2009; Konen and Kastner, 2008), suggesting that the present results probably generalize from the directional arrow shapes, which may be stimuli fitting well to processing characteristic of the dorsal stream (Milner and Goodale, 1995), to other types of stimuli as well. The color task was included in the present experiment as a control task in which the contribution of IPS was not expected to be critical. However, one should be cautious in concluding on the basis of the

present findings alone that the stimulated IPS area does not contribute also to perception of color, because perception of color was not efficiently suppressed by the stimulation of the upper bank of calcarine fissure (V1/V2) either. This result is in conflict with previous TMS studies showing that occipital TMS can suppress conscious color perception (Boyer et al., 2005; Railo et al., 2012). As the baseline performance level was matched between the color and shape tasks, the lack of suppression in the color task (in the group level analysis) was not due to any difference in the difficulty levels between these tasks. However, the previous studies (Boyer et al., 2005; Railo et al., 2012) presented the targets (size: 0.25–0.3 in diameter) to the left or right from the fixation and stimulated the contralateral occipital cortex, whereas in the present study the targets were larger (0.8° × 0.3°) and presented to the vertical meridian below the fixation while TMS was targeted to the medial plane. It is likely that the stimulation of more lateral areas and the use of smaller targets in the earlier studies produced more complete suppression of the whole target, including its color and all other features. The less complete suppression in the current study may have been sufficient for conscious perception of color but not of shape. On the other hand, the strength of the TMS-induced E-field in V1/V2, but not in IPS, correlated with conscious perception of colors in the lower VF at the TMS SOA of 90 ms, that is, at the latency where TMS of V1/V2 has been shown to suppress conscious perception of color (Railo et al., 2012). Thus, our V1/V2 stimulation indeed had a causal effect on conscious color perception. The critical activity period of V1/V2 in conscious perception of shape occurred 60–120 ms post stimulus, replicating previous findings around 100 ms with similar arrow stimuli (Jacobs et al., 2012; Koivisto et al.,

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2011b, 2012; Sack et al., 2009). Notably, these studies have revealed a single post-stimulus activity period whose onset and offset may vary depending on the experiment but which is always most clearly observable at 80–100 ms. This activity period corresponds to the classical ~100 ms “dip” produced by occipital stimulation (Amassian et al., 1989). This dip has been interpreted to reflect the first feedforward pass of information via V1 to higher areas (Camprodon et al., 2010) or recurrent activity between V1 and higher areas (Breitmeyer et al., 2004). Koivisto et al. (2011b) suggested that the early part of the period (until about 90–100 ms) corresponds to feedforward activity, whereas the later part of it, which can last even until 180 ms (Koivisto et al., 2011a, 2012), reflects recurrent processing between early visual cortex and higher cortical areas. The present finding that the activity of IPS was critical for conscious perception around 90 ms provides converging evidence for the view that recurrent processing occurs during the classical occipital (~100 ms) dip, at least in the late part of it which continues after 90 ms. A plausible interpretation for the present pattern of results can be based on the accounts (Bar, 2003; Bullier, 2001; Chen et al., 2007) in which a rapid coarse magnocellular representation is projected to the dorsal stream, and this representation modulates via feedback connections the processing of the slower parvocellular high-resolution information that is used by the ventral stream for constructing a detailed conscious representation. Because magnocellular neurons do not process color, this would also explain why IPS stimulation affected shape processing only. Nonconscious perception did not depend on the activity in posterior IPS. Thus, the framework in which nonconscious perception is attributed to the dorsal stream (Milner and Goodale, 1995), or at least to the posterior IPS area which was stimulated, was not supported. On the other hand, it has been suggested that nonconscious vision might be mediated via direct routes from lateral geniculate or superior collicus to extrastriate areas, thus bypassing V1 (Danckert and Rossetti, 2005; Ptito et al., 1999; Stoerig and Cowey, 1997). Such routes would explain the residual visual abilities in patients with blindsight. These patients have damages in V1, causing a blind area in the visual field. Although these patients claim to have no conscious experience of the stimuli in the blind part of the field, they are able to make forced-choice decisions concerning some aspects of the visual stimuli presented to the blind area. The present finding that TMS of V1/V2 suppressed nonconscious perception of shape, together with recent similar results (Jacobs et al., 2012; Koivisto et al., 2011b, 2012; Sack et al., 2009), suggests that the contribution of V1 is necessary for nonconscious perception of shape in normal brain. The neural routes that bypass V1 may be sufficient only for rather simple visual discriminations, such as detection of the appearance or localization of the stimulus (Christensen et al., 2008; Koivisto et al., 2011b; Railo and Koivisto, 2012; Ro, 2008) or detection of simple features (Alexander and Cowey, 2010). The finding that V1/V2 but not IPS was critical for nonconscious perception fits the account that nonconscious perception also is mediated by the slow parvocellular activity from V1 to higher areas along the ventral stream (Koivisto et al., 2012; Tapia and Breitmeyer, 2011) but the modulation from the parietal cortex is not critical for the processes that support nonconscious perception. The results do not, however, exclude the possibility that the posterior parietal cortex (IPS1 or other subarea) indeed processes shape or color information nonconsciously. The results imply that processing of shape in the stimulated parietal area is not necessary for nonconscious perception — it may succeed at normal level on the basis of the activity of the ventral system alone. As expected on the basis of the retinotopic organization of V1, the stimulation of the upper bank of the calcarine fissure suppressed the perception of shape in the lower VF. Similarly, the stimulation of the posterior IPS area suppressed conscious perception in the lower VF. The topography of IPS follows a similar phase reversal to that seen in the boundaries of the cortical areas in the early visual cortex. The lower VF is represented in the posterior part of IPS, in the boundary between V7 and IPS1, and the representation reverses to that of the upper

VF when one progress in anterior direction to the boundary between IPS1 and IPS2 (Konen and Kastner, 2008; Silver et al., 2005). We targeted the TMS to the posterior IPS and most probably the hotspot of stimulation was in the cortical area representing the lower VF near the boundary between IPS1 and V7. There is also evidence that neurons within visuomotor areas, including parieto-occipital cortex, overrepresent the lower VF in macaques (Galletti et al., 1999) and in humans (e.g., Rossit et al., 2013). We did not use fMRI-based topographic maps to target the TMS pulses specifically to the lower VF representations and, thus, did not expect the spatial resolution of the parietal TMS to be precise enough to suppress perception selectively in the lower VF, but such a prediction would not have been implausible in the light of the above notions. Our results contribute to the recent discussion about the mechanisms of TMS-induced visual suppression and the effects of TMS intensity on visual perception. There is some evidence that a strong TMS intensity produces visual suppression, whereas weak intensity tends to facilitate perception under certain conditions (Abrahamyan et al., 2011; Schwarzkopf et al., 2011). Thus, TMS does not simply inhibit processing or produce a “virtual lesion”, but it can also enhance performance. The facilitative effect of weak TMS pulses can be explained by assuming that the TMS-induced neural activity sums with the stimulus-evoked neural activity (Abrahamyan et al., 2011). This increases the activity level of neurons, which may be beneficial especially when the stimulus-evoked activity is low. In the present study the TMS intensity was constant, but we found correlations between the strength of the modeled TMSinduced E-field in the brain and conscious perception. The E-field strength in the V1/V2 target area in the upper calcarine fissure correlated positively with the strength of visual suppression in the lower VF in the color task and with suppression in the upper VF in the shape task. Regression analyses confirmed that a weak E-field in the V1/V2 target area produced facilitation while strong fields tended to produce suppression, although in the group level ANOVAs the facilitative and suppressive effects were canceled out. The correlations of the E-field strength in the upper VF could be explained by assuming that the stronger the E-field in the V1/V2 target area was, the stronger the induced neural activation in the near-by areas representing the upper VF as well. However, the modeled strength of the E-field in the lower bank of calcarine fissure, in which representations of the upper VF are located, did not correlate with suppression in the upper VF. Neither did the E-field strength in the upper bank correlate with the E-field in the lower bank. These results suggest that the TMS-induced changes in perception of shapes in the upper VF, as revealed by the correlations, were probably not generated directly by the residual TMSinduced E-field in the upper field representations of the lower bank of the calcarine fissure. It is possible, however, that the neural activation induced directly by TMS in the upper bank spread via neural connections to the representations of the upper VF in V1, or other visual areas. That kind of indirect effect due to spreading via neural connections cannot be modeled with the present procedure, but there are several demonstrations in the literature how TMS of one region can change the neural activity in remote areas (Ilmoniemi et al., 1997; Ruff et al., 2009; Silvanto et al., 2009). The strength of the E-field in the posterior IPS also correlated with suppression of shape perception in the upper VF, showing also that facilitation of conscious perception with weak E-field turned to suppression as the E-field increased. This finding thus gives converging evidence for the involvement of IPS in conscious perception of shape. Here it is plausible that the strength of the neural activation in the upper VF representation in the anterior parts of IPS1, or in the boundary between IPS1 and IPS2, explains the pattern of facilitation versus suppression. Taken together, all these positive correlations are consistent with the results of previous manipulations of TMS output intensity (Abrahamyan et al., 2011; Schwarzkopf et al., 2011). The correlations link the changes in perceptual sensitivity more directly to the TMS-induced E-field in the brain and suggest that weak TMS-induced activations in the brain sum

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with the stimulus-evoked neural activity and enhance perception, whereas summing of stronger TMS-induced activations with stimulusrelated activity leads to an over-activation of the system (i.e., neural noise) and impairs perception. These notions rely on the assumption that the intensity of sensory stimulation and the magnitude of neural response follow a sigmoid function (Abrahamyan et al., 2011) in which a weak TMS-induced E-field brings the activity in the sensory neurons closer to their threshold for conscious perception, whereas strong E-field intensity makes the discrimination between the sensory signal and the additional noise more difficult.

Conclusions The present study indicates a causal role for the posterior intraparietal area in conscious, but not in nonconscious, perception of shape. The critical activity period of the early visual cortex in conscious perception overlapped with that of the posterior intraparietal cortex and continued to the end of the measured time range (i.e., 120 ms). In the context of recent accounts of visual processing (Bar, 2003; Bullier, 2001; Chen et al., 2007; Hochstein and Ahissar, 2002) and visual awareness (Lamme, 2004; Pascual-Leone and Walsh, 2001; Tapia and Breitmeyer, 2011), this finding implicates that the posterior parietal cortex contributes to conscious perception via top-down modulation of ongoing activity in the early visual areas. Nonconscious perception of shape in the intact brain depends on the activity of early visual areas but it can proceed normally without the top-down modulation from the posterior intraparietal area that is critical for conscious perception. The correlations between the strength of the TMS-induced E-field and perceptual suppression suggest that single pulse TMS may both facilitate and suppress conscious perception, depending on the level of the additional activation induced in the perceptual system. Furthermore, the strength of the E-field in the targeted brain area may determine how far to other non-targeted cortical areas the neural activation spreads and whether this extra activation will produce facilitation (when the activation is relatively weak) or suppression (when the activation is relatively strong) in the processes carried out by the non-targeted area. However, these observations must be considered as preliminary and should be tested explicitly in further experiments.

Acknowledgments This work was supported by the Academy of Finland (grant numbers 125175 and 218272).

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