Controlling Brain State Prior to Stimulation of Parietal Cortex Prevents Deterioration of Sustained Attention.

Sustained attention is a limited resource which declines during daily tasks. Such decay is exacerbated in clinical and aging populations. Inhibition of the intraparietal sulcus (IPS), using low-frequency repetitive transcranial magnetic stimulation (LF-rTMS), can lead to an upregulation of functional communication within the attention network. Attributed to functional compensation for the inhibited node, this boost lasts for tens of minutes poststimulation. Despite the neural change, no behavioral correlate has been found in healthy subjects, a necessary direct evidence of functional compensation. To understand the functional significance of neuromodulatory induced fluctuations on attention, we sought to boost the impact of LF-rTMS to impact behavior. We controlled brain state prior to LF-rTMS using high-frequency transcranial random noise stimulation (HF-tRNS), shown to increase and stabilize neuronal excitability. Using fMRI-guided stimulation protocols combining HF-tRNS and LF-rTMS, we tested the poststimulation impact on sustained attention with multiple object tracking (MOT). While attention deteriorated across time in control conditions, HF-tRNS followed by LF-rTMS doubled sustained attention capacity to 94 min. Multimethod stimulation was more effective when targeting right IPS, supporting specialized attention processing in the right hemisphere. Used in cognitive domains dependent on network-wide neural activity, this tool may cause lasting neural compensation useful for clinical rehabilitation.

Introduction

Sustained attention is fundamental for cognitively interacting with the environment (DeGangi and Porges 1990), however, it progressively deteriorates over time (Berardi et al. 2001; Sarter et al. 2001; Whitehurst et al. 2019). This deterioration increases with age (Berardi et al. 2001) and in cognitive disorders, such as attention deficit hyperactivity disorder (ADHD) and bipolar disorder (Barkley, 1997; Clark et al. 2005). Thus, a protocol that stabilizes and improves sustained attention for prolonged durations has population-wide application.

Noninvasive brain stimulation can significantly boost cognitive function (Freedberg et al. 2019; Hermiller et al. 2019; Herpich et al. 2019; Reinhart and Nguyen 2019). Favorable behavioral changes following stimulation may be due to lasting network-wide fluctuation of regions functionally connected to stimulation site (Battelli et al. 2017; Freedberg et al. 2019; Hermiller et al. 2019). In visual attention, low-frequency repetitive transcranial magnetic stimulation (LF-rTMS) to the intraparietal sulcus (IPS) is often associated with inhibitory impact on the underlying cortex, and an acute decrease in contralateral attention (Battelli et al. 2009; Edwards et al. 2017). However, following the initial inhibitory effect, LF-rTMS to IPS also results in a cascade of network-wide effects (Capotosto et al. 2011; Szczepanski and Kastner 2013; Plow et al. 2014; Petitet et al. 2015; Capotosto et al. 2016). For example, inhibition of the IPS with LF-rTMS causes increased functional communication between nodes of the dorsal attention network, 48 min poststimulation (Battelli et al. 2017). One hypothesis is that network-wide functional change compensates for the inhibited node following LF-rTMS (Paus et al. 1997; Grefkes et al. 2010; Lee and D’Esposito 2012; Plow et al. 2014; Battelli et al. 2017). Functional compensation should predict behavioral benefit lasting the duration of the functional change (Grefkes et al. 2010). Lee and D’Esposito (2012) found theta burst TMS to prefrontal cortex (PFC) increased connectivity in the unstimulated PFC homolog which correlated with a reduced disruption of working memory. Yet such behavioral correlate in attention has not been found following network-wide lasting functional changes after LF-rTMS to IPS in healthy participants (Plow et al. 2014; Battelli et al. 2017). Enduring behavioral change is crucial for noninvasive brain stimulation to be considered in clinical intervention (Edwards et al. 2019).

To affect behavior, we employed a method for boosting the impact of LF-rTMS, and therefore, the following compensatory neuromodulation. Multimethod brain stimulation has been successfully applied to the motor cortex to boost the impact of LF-rTMS, inhibiting physiological response up to an hour after stimulation (Iyer et al. 2003). The lasting inhibition was achieved by applying high-frequency prior to low-frequency stimulation, with the aim of extending the long-term depressive effect (Stanton and Sejnowski 1989; Christie and Abraham 1992; Iyer et al. 2003). This effect has been termed “metaplasticity”, the influence of neuronal activation history on subsequent neuronal activity (Abraham and Bear 1996). To date, multimethod stimulation protocols using a variety of high-frequency and low-frequency stimulation combinations have produced enduring cortical inhibition. These methods have been tested physiologically in the motor cortex using HF-rTMS followed by LF-rTMS (Iyer et al. 2003), anodal transcranial direct current stimulation (a-tDCS) followed by LF-rTMS (Siebner et al. 2004; Bocci et al. 2014), and in the visual cortex using a-tDCS followed by cathodal-tDCS (Fricke et al. 2010), but never in the parietal cortex using a cognitive task as the outcome measure. In order to harness the hypothesized behavioral correlate from functional compensation following LF-rTMS to IPS, we aimed to boost the impact of LF-rTMS.

Here, we adapted the multimethod approach to modulate the IPS, a central node of the dorsal attention network, and recorded sustained attention for 94 min poststimulation. In the first experiment, we primed bilateral IPS with high-frequency transcranial random noise stimulation (HF-tRNS), followed by LF-rTMS to initiate long-term inhibition (Christie and Abraham 1992). We selected HF-tRNS as it has been regularly shown to increase cortical excitability (Terney et al. 2008; Moliadze et al. 2012; Herpich et al. 2018), while being well tolerated by participants (Antal et al. 2017). In the second experiment, we aimed to replicate experiment 1, and determine if targeting left or right IPS with multimethod stimulation differentially modulated sustained attention. Furthermore, we ensure our stimulation site selection using functional magnetic resonance imaging (fMRI) localized left and right IPS, and examined if LF-rTMS alone (without prior HF-tRNS priming) could account for attention change across time.

We hypothesized that sustained attention would decrease with time in the control conditions, whereas, we expected functional compensation following multimethod stimulation would result in improved sustained attention. We conjecture multimethod stimulation would result in sustained inhibition of the IPS, similar to the findings in the motor and visual cortex (Iyer et al. 2003; Bocci et al. 2014) and functional compensation from other nodes of the attention network in response (Paus et al. 1997; Grefkes et al. 2010; Lee and D’Esposito 2012; Plow et al. 2014; Battelli et al. 2017). In the second experiment, we hypothesized the functional asymmetry previously reported between right and left parietal regions would be evident in poststimulation behavior in right and left visual fields. The left parietal regions have been shown to orient attention toward the right visual field (Kinsbourne and Hiscock 1977; Kim et al. 1999), therefore left-targeted IPS multimethod stimulation may impact the right visual field only. Although the right represents attention in left and right visual space (Battelli et al. 2001; Corbetta et al. 2005; Sheremata et al. 2010; Sheremata and Silver 2015; Ro and Beauchamp 2020), indicating multimethod stimulation to right IPS should impact both left and right visual fields. Finally, we expected LF-rTMS alone to only initially decrease contralateral visual field attention and have no impact on ipsilateral attention (Dambeck et al. 2006; Battelli et al. 2009).

Methods and Materials

Experiment 1: Multimethod Stimulation to Prevent Attention Deterioration

Experiment 1 was a one-session between-subjects design, whereby participants were randomly assigned to an experimental group when scheduled for the experiment. Experiment 1 is presented first, but was conducted second chronologically. Design choices, such as experimental conditions and stimulation location, in experiment 1 are based on findings from experiment 2.

Participants

A total of 20 volunteers (10 females; age range 20–40 years) participated in the experiment. All participants gave written informed consent, and the study was approved by Harvard University’s Institutional Review Board: The Human Research Protection Program. All 20 participants were included in data analysis. All participants had normal to corrected-to-normal vision.

Stimuli

For behavioral testing during and after stimulation, participants viewed the stimulus on a 13-inch MacBook Pro at a distance of 60 cm (Retina; screen resolution: 1280 × 800). All stimuli were presented using the psychophysical toolbox PsychoPy2 (Peirce et al. 2019).

Standard Bilateral Multiple Object Tracking Paradigm

Participants performed a bilateral multiple object tracking (MOT) paradigm for experiments 1 and 2. Bilateral MOT is a well-established paradigm for recruiting bilateral covert attention (Pylyshyn and Storm 1988), and functionally activating bilateral parietal cortices (Culham et al.1998). On each trial, participants were presented with 4 objects (black dots, radius 0.25°) either side of a central fixation (Fig. 1a). Two objects on either side of the fixation cross flashed (2 Hz for 2 s) to cue the participant to track these objects among the other identical distractors. Importantly, the participant was unaware of which visual field would be tested, necessitating central fixation and covert attentional tracking within both visual fields simultaneously. Overtly tracking the objects through saccades to the targets would be a suboptimal strategy for bilateral visual field monitoring. All objects then moved at a constant speed (degrees per second) for 3 s within a 6° × 6° region and centered 2° to the left and right of the fixation. Speed was set according to the individual participant’s threshold (see Thresholding section). Each object repelled 1 another to maintain a minimum space of 1.5°, never crossed the midline and bounced off of invisible edges within each visual field. After 3 s, the objects stopped moving, 1 object was highlighted in red, and the participant was asked to respond with a key press to indicate if the highlighted object was the “target” or “distractor” to the objects flashed at the beginning. After each trial, the fixation point changed to red to indicate incorrect, or green to indicate correct response.

Figure 1

Sustained attention task and multistimulation montage for experiment 1. 1a) Bilateral MOT was used to record participants’ sustained attention across time after stimulation. 1b) Depiction of each stimulation montage for experiment 1.

Thresholding Stimuli

Participants performed bilateral MOT in a staircase procedure to establish each participant’s 75% correct threshold (Cornsweet 1962). Participants first practiced MOT for 16 trials when the dots moved at the slow speed of 2 deg/s. After the practice block, participants’ threshold was determined by changing the speed of the moving dots on each trial. Participants completed 8 interleaved 3/1 staircases to assess their individual speed thresholds. The staircases increased the speed after 3 correct trials and reduced it following a single incorrect response. The staircases terminated after a combined 16 reversals, with threshold parameters estimated from the last 3 reversals. Speed was adjusted to yield 75% accuracy in the target/distractor judgments. Participants then performed bilateral MOT at their 75% correct threshold speed (degrees per second) for the duration of the experiment. In order to determine a behavioral change with stimulation, all participants should perform below ceiling at the same baseline prior to stimulation. Our participants 75% correct speed ranged from 5 to 14.5 deg/s for experiment 1 (Fig. 2a).

Figure 2

Threshold speed for each participant. 75% correct speed threshold in the bilateral MOT task was calculated for each participants using a staircase procedure. Data sorted lowest to highest for each group of participants. The speeds range from 5 to 14.5 degrees per second across experiments 1 (a) and 2 (b).

Stimulation Equipment and Coil Positioning

Stimulation sites for tRNS and rTMS for left and right IPS were based on averaged fMRI localized coordinates from experiment 2 (see MRI Analysis and localization of posterior IPS in experiment 2 methods). The averaged coordinates were in talariach space (Left IPS: x = −21.33(4.83), y = −83.53(3.01), z = 19.00(4.87); Right IPS x = 20.54(4.80), y = −83.35(4.19), z = 17.96(5.56)). These coordinates are along posterior IPS, often labeled IPS0/V7 (Swisher et al. 2007; Konen and Kastner 2008; Szczepanski et al. 2010; Konen et al. 2013). Prior to stimulation, participants were aligned to the talariach model brain within Brainsight Frameless Stereotaxy System (Rogue Research, Montreal, Canada). The model brain was adjusted to fit each individual participant’s head size. HF-tRNS was delivered for 20 min using electrodes and a DC-Stimulator (Eldith-Plus, Neuroconn), at 1 mA at random frequencies between 101 and 640 Hz. Stimulation began and finished with a 15-s fade-in/fade-out ramp. The electrodes were placed inside saline soaked sponges, and were positioned over averaged left and right IPS coordinates. tRNS stimulation delivered using this protocol has been shown to have an excitatory impact on the cortex (Herpich et al. 2018). The procedure for Sham-tRNS was exactly the same, with a fade-in and fade-out ramp, but stimulation was turned off and not delivered during the 20 min. LF-rTMS was delivered using a MagPro® by MagVenture with a figure-8 coil with an inbuilt cooling system. Stimulation was performed at 1 Hz with 65% machine output intensity (Battelli et al. 2009). Although motor and/or visual thresholding is often used to select individual intensities for each participant, evidence suggests these thresholds do not correlate (Stewart et al. 2001). The lack of correlation between these thresholding measures further indicates that neither threshold may be appropriate for stimulation of IPS. Intensity of 65% was selected as it has shown to be an effective stimulation intensity of TMS stimulation to IPS to produce group effects. The coil was held with the handle pointing backward, in a tangential orientation over the either left or right posterior IPS (Ruff et al. 2008; Battelli et al. 2009; Edwards et al. 2017). The current flowed from posterior to anterior, maximizing the stimulation down the IPS (Ruff et al. 2008). For the sham rTMS condition, the coil was flipped away from the cortex, but in the same tangential orientation over the right posterior IPS. The participants experienced the setup and auditory stimulation of rTMS, without any magnetic stimulation.

Experimental Designs and Statistical Analyses

In the experimental session, each participant was first tested on the bilateral MOT using a staircase procedure to determine the 75% correct speed threshold. This speed was fixed for the remainder of the experiment. Prior to stimulation, participants underwent 6 min of bilateral MOT to ensure equal performance across groups before stimulation. Each participant was randomly assigned to 1 of 2 stimulation protocols (Fig. 1b): i) 20 min of HF-tRNS to bilateral posterior IPS followed by 15 min of LF-rTMS to right IPS, ii) 20 min sham-tRNS to bilateral IPS followed by 15 min sham rTMS to right IPS. None of the participants had experienced brain stimulation previously, and therefore were unable to determine if they received real or sham stimulation. Participants also performed bilateral MOT during tRNS stimulation. After stimulation, participants performed 94 min of MOT across 12 blocks of 6 min each, with 2 min break between each block. Each block comprised a total of 38 trials, with 19 trials with targets probed in the left visual field, and 19 probed in the right visual field. The order of the tested visual field was randomized across trials. Data were collected in 12 6-minute bins; however we collapsed the data every 2 bins to increase the number of trials per bin for analysis. This resulted in 6 14-min bins, 12-min plus the 2-min break between the bins.

We fit a general linear mixed effects regression models to the object tracking accuracy using R (R Core Team, 2019) and the glmer() function within the lme4 package with the binomial distributional family, and logit link function (Bates et al. 2015). The interaction of interest was between stimulation and time; however we were also interested in visual field specific stimulation impact. Stimulation was the between-subjects predictor (Sham-tRNS and rTMS or HF-tRNS and rTMS), Time (6 bins: 0–14, 16–30, 32–46, 48–62, 64–78, and 80–94) and Visual Field (Left and Right) were the within-subject predictors. All these predictors were treated as categorical factors within the model, and random intercepts were included for participants. Chi-squared and P values were reported for the interactions in the model and all the main effects. Model comparisons were also conducted to determine which model best predicted the data. We further present individual contrast between stimulation conditions at each time-point, controlled for multiple comparisons using emmeans() and adjust = “mvt” (Lenth et al. 2020).

To ensure there was no difference between groups prior to stimulation, we also performed a contrast between prestimulation behavior of the sham group and the group which received multimethod stimulation, by visual field.

Finally, we also performed a general linear mixed effect model on the behavior during tRNS stimulation for the sham and multimethod stimulation group across time. tRNS was performed for 20 min, so we blocked the behavior by first and last 10 min to determine if there was a time-specific impact. Random intercepts were included for participants. Chi-squared and P values were reported for the interaction model and all the main effects.

Experiment 2: Multimethod Stimulation in Spatially Specific Reduction of Attention Deterioration

Experiment 2 was a within-subjects design with 5 independent sessions. Participants attended an fMRI session first to localize the stimulation sites, and then attended 4 separate sessions of noninvasive brain stimulation followed by behavioral testing. Each stimulation session involved a different stimulation protocol and was separated by at least 48 h to avoid for stimulation carryover effects (Fig. 3a).

Figure 3

Multistimulation montage and protocol for experiment 2. a) Portrayal of 5-day protocol. b) Depiction of each stimulation session for experiment 2. Note that all left visual field stimulation effects were compared with left visual field ipsilateral rTMS control condition in a) ii), and right stimulation effects with right visual field ipsilateral rTMS control condition in a) iv).

A total of 21 new volunteers (9 females; age range 20–40 years) participated in the second experiment. All participants gave written informed consent, and the study was approved by Harvard University’s Institutional Review Board: The Human Research Protection Program. Data of 5 participants were not analyzed due to incomplete attendance to experiment sessions, leaving 16 participants in total. All participants had normal to corrected-to-normal vision.

During the localizer runs in the fMRI, participants viewed the stimulus on an fMRI-compatible screen positioned in the bore of the magnet at a distance of 104 cm. The screen projected the stimulus from a 13-inch MacBook Pro (Retina; screen resolution: 1280 × 800). During behavioral testing after stimulation, the MOT was presented exactly the same as in experiment 1, where participants viewed the stimulus on the same 13-inch MacBook Pro at a distance of 60 cm.

Standard Bilateral MOT Paradigm

Performed in the exact format as that of experiment 1.

Performed at the beginning of the session for each participant in the same staircase procedure as described for experiment 1. Participants’ 75% correct speed ranged from 5 to 12.75 deg/s for experiment 2 (Fig. 2b).

Localizer Stimuli

Unilateral MOT was used to localize the posterior portion of the IPS in both the right and left cortex. Posterior IPS is typically localized using fMRI with covert attention to the right and left visual field separately (Gitelman et al. 1999). During the localizer scan in the MRI, participants performed unilateral MOT for 1 run of 8.5 min. Each trial was performed similarly to the standard MOT described above, but 2 objects were cued to be tracked from 1 visual field only, rather than 2 objects in each visual field. Therefore, fixation remained central and attention was diverted to 1 visual field in each trial.

MRI Acquisition

In experiment 2, functional and anatomical MRI data were acquired using a 32-channel phased-array head coil with a 3 Tesla MRI system (Siemens Prisma) at the Harvard Center for Brain Sciences. For the functional scans, contrasts of blood oxygenation level-dependent (BOLD) activity were obtained using an echo-planar imaging sequence (parameters: 65 slices; slice thickness = 2.40 mm; FOV = 211 mm; 2.4 × 2.4 × 2.4 voxel size; flip angle = 64; TR = 1; TE = 32.60 ms; multiband accelerator factor of 5). High-resolution T1 scans were acquired using 3D MPRAGE protocol (parameters: 176 slices; FOV = 256 mm; 1 × 1 × 1 mm voxel resolution; gap thickness = 0 mm; TR = 2200 ms; TE = 1.69 ms).

MRI Analysis and Localization of Posterior IPS

The functional and anatomical data from experiment 1 were analyzed using BrainVoyager QX®. The first 2 volumes of each functional run were discarded to avoid saturation effects. Low-frequency noise and drift was removed using high-pass filtering during 3D-motion correction. The functional data were then aligned to the high-resolution anatomical data in native space. We convolved event timing with a hemodynamic model to generate predicted brain responses, with the associated beta weights estimated using a general linear model. To localize left and right posterior IPS, we contrasted the beta estimates for the unilateral MOT attend right > unilateral MOT attend left. With this contrast, activity in left IPS indicates lateralized attention to the right visual field, and activity in right IPS indicates lateralized attention to the left visual field (Fig. 4a). Patches of interest were defined for left and right posterior IPS from t maps thresholded at P < 0.001. The peak activated voxel was selected as the region for stimulation from the patches of interest, individually measured for each subject (averaged coordinates across all subjects: Left IPS: x = −21.33(4.83), y = −83.53(3.01), z = 19.00(4.87); Right IPS x = 20.54(4.80), y = −83.35(4.19), z = 17.96(5.56)). Figure 4b illustrates each of the individual stimulation sites plotted using BrainNet Viewer (Xia et al. 2013). These coordinates are often labeled IPS0/V7 (Swisher et al. 2007; Konen and Kastner 2008; Szczepanski et al. 2010; Konen et al. 2013). These data were saved in native space and retained for tRNS and TMS coil positioning.

Figure 4

fMRI localizer for stimulation sites and modeling of current flow. a) Participants were presented with unilateral MOT in a fast-event related design. In each trial the participant had to fixate centrally and attend to targets in either the left or the right visual field. Right posterior IPS was localized through unilateral tracking in the left visual field, and left posterior IPS localized with unilateral tracking in the right visual field. b) Individual stimulation hotspots in left (blue) and right (green) IPS. c) Modeling of electric field following unilateral rTMS (top 2 models) and bilateral tRNS (bottom model).

Stimulation sites for tRNS and rTMS were selected based on fMRI data which localized each participant’s left and right posterior IPS (see MRI Analysis and localization of posterior IPS and Fig. 4). Brainsight Frameless Stereotaxy System (Rogue Research, Montreal, Canada) was used to align the participant with their native space functional MRI data. HF-tRNS, sham-tRNS, and LF-rTMS were delivered using the exact same methods as in experiment 1. Modeling of the electric field following tRNS and rTMS was performed in SimNIBS (Fig. 4c; Thielscher et al. 2015). Stimulation site distance from scalp was not a significant predictor of stimulation impact (Supplemental Fig. 3).

The experiment was performed as a within-subjects design across 5 separate sessions, each participant performed all conditions of the experiment. On day 1, participants performed unilateral MOT in the MRI to localize the IPS for the following stimulation session, and subsequently perform the bilateral MOT using the staircase procedure to determine individual threshold speed at which each subject performed the task at 75% correct. Day 2 to day 5 were counterbalanced across subjects using Balanced Latin Squares. On each day the participant received 1 of 4 stimulation protocols (Fig. 3b): 20 min of i) HF-tRNS or ii) sham tRNS to bilateral posterior IPS, followed by 15 min of LF-rTMS to left IPS; or 20 min of iii) HF-tRNS or iv) sham tRNS to bilateral posterior IPS, followed by 15 min of LF-rTMS to right IPS. After stimulation, the participant performed bilateral MOT for 94 min, 12 blocks of 6 min separated by 2 min of rest between each block (see procedure of experiment 1 for details).

We fit general linear mixed effects models to examine visual field specific impact of stimulation across time. As with experiment 1, we used the lme4() package in R to perform glmer with the binomial distributional family and logit link function (Bates et al. 2015; R core team, 2019). Our within-subjects predictors were Stimulation (Contra-tRNS-rTMS, Ipsi-tRNS-rTMS, Contra-rTMS, and Ipsi-rTMS), Time (6 bins: 0–14, 16–30, 32–46, 48–62, 64–78, and 80–94 min), and Visual Field (Left and Right). Random intercepts were included for participants. We reported interactions and main effects with Chi-squared and P values. Similar to experiment 1, we also performed model comparisons to ensure we had the model which best fit our data. We further presented individual contrasts between stimulation conditions at each time-point, controlled for multiple comparisons (using emmeans() and adjust = “mvt” in contrast (Lenth et al. 2020).

Stimulation input for the generalized linear mixed effects model was considered by contralateral and ipsilateral visual field impact due to the active control condition, which was visual field specific. Evidence suggests attention performance differences between left and right visual field (Alvarez and Cavanagh 2005; Chen et al. 2013), therefore a visual field specific control for each stimulation condition was necessary. In the LF-rTMS-only sessions, object tracking performance in the hemifield ipsilateral to the LF-rTMS acted as the visual field specific active control. For instance, behavior in the left visual field during LF-rTMS to left IPS was the control behavior for the behavior in the left visual field in each of the other stimulation sessions. For an effective active control, a stimulation site is chosen as it is hypothesized to not impact the behavior of interest (Robertson et al. 2003; Valero-Cabré et al. 2017). In our case, rTMS to a region specifically localized for contralateral visual field attention was not expected to impact ipsilateral visual field attention (Dambeck et al. 2006; Battelli et al. 2009; Edwards et al. 2017).

Results

We examined the effect of multimethod noninvasive brain stimulation on bilateral attention, dependent of visual field. After HF-tRNS to bilateral IPS, followed by LF-rTMS to IPS, we expected to prevent attention deterioration across time.

Prestimulation Performance

Due to the between-subjects design, we ran a post-thresholding, pre-stimulation block of trials to confirm there were no differences between the sham and stimulation groups. There was no significant prestimulation difference between tRNS and rTMS and sham by visual field (χ2(1) = 0.082, P = 0.775), and no main effects of stimulation (χ2(1) = 2.925, P = 0.087), nor visual field (χ2(1) = 0.724, P = 0.395). This indicates the 2 groups were not significantly different prior to stimulation.

During Stimulation Performance

We also examined the impact of tRNS on behavior during stimulation. We found no interaction between stimulation, time and visual field (χ2(1) = 0.506, P = 0.477; Supplemental Fig. 1), or any two-way interactions, nor main effects (P > 0.05, see Supplemental Table 1 for details). Therefore, tRNS did not significantly impact behavior during stimulation in comparison to sham.

Poststimulation Performance

We analyzed the impact of multimethod stimulation across 94 min in comparison to sham and determined if there is a visual field specific effect.

We found a main effect of time on performance (χ2(5) = 66.4683, P < 0.0001, glmer), but no main effect of stimulation (χ2(1) = 1.1685, P = 0.2797, glmer) or visual field χ2(5) = 1.9147, P = 0.1664, glmer). When examining the interactions, we found no significant interaction between stimulation, time, and visual field (χ2(5) = 3.8312, P = 0.5739, glmer). However, we did find a significant interaction between stimulation and time (χ2(5) = 35.6657, P < 0.0001, glmer; Fig. 5a). This indicated that there was a difference between sham and multimethod stimulation across time, but this difference was not modulated by visual field (Fig. 5b, c). Model comparison analysis also supported stimulation x time interaction as the best fit for the data (see Supplemental Information). Therefore, time from stimulation offset significantly impacted the change in behavior. When examining individual time-points to determine when there was a significant difference in attention following stimulation, we found performance was significantly lower in participants for the sham group in comparison to the stimulation group at 64–78 min (average difference = 7.94%, estimate = 1.475, se = 0.589, z = 2.505, P = 0.0497) and at 80–94 min poststimulation (average difference = 14.39%, estimate = 0.630, se = 0.235, z = 2.686, P = 0.0303; emmeans with adjust “mvt”).

Figure 5

Experiment 1: Stimulation impact on MOT performance. a) Impact of tRNS and rTMS on MOT collapsed across visual field. b) Left visual field stimulation effects: Stimulation impact on MOT contralateral to tRNS and rTMS relative to sham. c) Right visual field stimulation effects: Stimulation impact on MOT ipsilateral to tRNS and rTMS relative to sham. • indicates P < 0.05 adjusted for multiple comparisons.

In Experiment 2, we expected to reproduce the lack of attention deterioration up to 94 min after stimulation with tRNS priming prior to LF-rTMS. Furthermore, we performed this experiment to determine if targeting left or right IPS with multimethod stimulation differentially modulated sustained attention in the left and right visual fields.

Importantly, we added another stimulation condition to determine if rTMS alone could result in prevention of attention deterioration up to 94-min. rTMS over IPS has been shown to have contralateral visual field specific impact (Dambeck et al. 2006; Battelli et al. 2009). Therefore, in the rTMS alone stimulation day, we assume the behavior in the contralateral visual field as impacted by rTMS, whereas the ipsilateral behavior acts as an active control, specific to visual field.

Active Control Site: Ipsilateral Visual Field from rTMS

First, we determined if behavior in the ipsilateral visual field from rTMS was a strong control for behavior. We found the ipsilateral visual field was not significantly different from 75% for all 6 time-points (P > 0.05) in both the left and right visual field (Fig. 6a, b). Each participant was thresholded to 75% correct prior to intervention, therefore no deviation from 75% indicates no change in behavior due to rTMS in the ipsilateral visual field.

Figure 6

Experiment 2: Percentage correct MOT in each visual field across time following stimulation. a) Stimulation impact on MOT in the left visual field. b) Stimulation impact on MOT in the right visual field. The • indicates P < 0.05.

Surprisingly, no change in attention across time in our control condition indicated that the participants from experiment 2 did not experience sustained attention decrement. We believe the lack of sustained attention decrement was due to possible training effects across the 4 sessions of the experiment. Testing this hypothesis, we found a significant impact of session (χ2(3) = 9.6934, P = 0.02136) on accuracy in MOT, with performance at 80–94 min in session 3 and session 4 significantly better than in session 1 (Session 4 vs. Session 1: difference = 4.7%, estimate = 0.522, se = 0.189, z-ratio = 2.765, P = 0.0159; Session 3 vs. Session 1: difference = 4.45%, estimate = 0.477, se = 0.188, z-ratio = 2.536, P = 0.0310; Supplemental Fig. 2). This stimulation-type independent increase in task performance across session could account for the lack of sustained attention decrement in control conditions. Through counterbalancing the order of stimulation protocols across sessions, a subset of subjects had their control sessions last, introducing variability in performance, and increasing baseline sustained attention. Irrespective of the lack of decrement, we analyzed the multimethod stimulation effect to determine if it still caused a boost in attention in comparison to the control behavior.

Impact of Stimulation on Sustained Attention

Using generalized linear mixed effects modeling, we found a main effect of stimulation, (χ2(3) = 11.3708, P = 0.009) and visual field (χ2(1) = 8.8315, P = 0.002), but no effect of time (χ2(5) = 10.0352, P = 0.074). We also found a significant 3-way interaction of stimulation x time x visual field (χ2(15) = 26.9615, P = 0.029). The stimulation x time x visual field interaction was further supported as the best fit for the data according to model comparisons (see Supporting Information). This indicates that attention was modulated by stimulation across time and this modulation was dependent upon visual field (Fig. 6).

When computing contrasts on estimated marginal means, we found a significant difference in tracking performance at 80–94 min between the left visual field contralateral to tRNS and rTMS to right IPS and control (difference = 10.03%, estimate = 0.572, se = 0.138, z-ratio = 4.157, P = 0.0006; emmeans(), with adjust “mvt”). We also found the difference in the tracking performance contralateral to tRNS and rTMS was significantly larger than rTMS alone (difference = 8.23%, estimate = 0.466, se = 0.140, z-ratio = 3.335, P = 0.0146; emmeans(), with adjust “mvt”), however not significantly larger than the ipsilateral tRNS and rTMS condition (difference = 6.58%, estimate = 0.392, se = 0.141, z-ratio = 2.792, P = 0.084; emmeans(), with adjust “mvt”). No other time-point was significantly different between conditions in the left visual field. In the right visual field, there was no significant difference between the conditions at any time-point. This analysis indicates that right hemisphere multimethod stimulation impacts contralateral left visual field sustained attention. Although left hemisphere multimethod stimulation does not seem to impact contralateral or ipsilateral attention. rTMS alone also does not impact attention at any time-point, regardless of stimulation site (P > 0.05).

Discussion

We investigated the use of multimethod brain stimulation as an intervention to improve sustained attention over time. In 2 experiments, we found multimethod stimulation maintained and improved sustained attention up to 94 min poststimulation. This is the first evidence to suggest multimethod stimulation has a lasting impact on cognitive behavior, complementing the previous studies demonstrating lasting impact to physiological response (Iyer et al. 2003; Lang et al. 2004; Siebner et al. 2004; Fricke et al. 2010; Bocci et al. 2014).

In previous experiments, high-frequency stimulation immediately followed by low-frequency stimulation has resulted in lasting inhibition, demonstrated physiologically by decreased motor evoked potential amplitude (Iyer et al. 2003), and visual evoked potential amplitude (Bocci et al. 2014). Our effect shows multimethod stimulation improved sustained attention, seemingly at odds with the previous inhibitory multimethod physiological responses. It is important to restate that our effect is likely due to a dynamic change of excitatory-inhibitory balance across the whole dorsal attention network. Like previous multimethod experiments, we expected multimethod stimulation to inhibit IPS, but unlike previous multimethod experiments, we expected the inhibition to cause compensatory activity from other nodes of the dorsal attention network (Paus et al. 1997; Grefkes et al. 2010; Lee and D’Esposito 2012; Plow et al. 2014; Battelli et al. 2017). Experiments recording the impact of a single method protocol of LF-rTMS to the IPS have shown a late boost in attention capability in patients (Brighina et al. 2003; Agosta et al. 2014) and a functional reorganization of the attention network beginning 36 min and lasting for 50 min after stimulation in healthy participants (Battelli et al. 2017). We believe that the lack of attention deterioration following multimethod stimulation is a result of functional reorganization, like that of Battelli et al. (2017). Although behavioral change was not previously detected with network-wide function change following LF-rTMS alone (Battelli et al. 2017), multimethod stimulation may have caused a sustained enough inhibitory effect to result in behavioral impact. The lateness of the behavioral impact is likely due to stimulation improving sustained attention decrement, which begins to deteriorate within 75 min (Whitehurst et al. 2019).

In line with our hypothesis, our first experiment demonstrated a significant impact of tRNS and rTMS on improving sustained attention, regardless of visual field. This indicates that compensation following multimethod stimulation to right IPS impacted attention in both visual fields equally. Our second experiment further demonstrated the impact of multimethod stimulation was specific to right IPS. Multimethod stimulation to right IPS significantly impacted attention in the left visual field, yet right visual field attention modulation was not replicated. The lack of replication in the right visual field could have been driven by the maintenance of sustained attention in the right visual field of the control. We found no impact of multimethod stimulation over the left parietal cortex in either the right or left visual field. Bilateral visual field impact from multimethod stimulation targeted at the right parietal cortex from experiment 1 supports the evidence of bilateral visual field representation in the right parietal cortex, specifically in area IPS0/V7 (Swisher et al. 2007; Konen and Kastner 2008; Sheremata et al. 2010; Sheremata and Silver 2015). The visual field wide attention increase following multimethod stimulation to right IPS may be useful in designing new strategies to sustain and improve attention in healthy and neurological populations.

Along with a late boost in attention, one might expect an initial decrease in attentional capability following HF-tRNS and LF-rTMS multimethod stimulation. The initial decrement in attention could demonstrate the magnified inhibition expected directly following stimulation, however a decrease in attention capability was not found. The lack of behavioral decrement could be explained by the interaction of posterior IPS and its homotopic counterpart in the other hemisphere following targeted inhibitory brain stimulation. Using a different, but mechanistically similar, method to inhibit cortical function, researchers have found that an eye deprived of visual stimuli (through eye patching) strengthens in perceptual response directly after deprivation (Mrsic-Flogel et al. 2007; Lunghi et al. 2015; Kim et al. 2017). Long-term potentiation (LTP) following deprivation and noninvasive brain stimulation hinge on similar underlying mechanisms including activation of NMDA receptors, concomitant GABAergic inhibition and the production of acetylcholine neurotransmitter (Boroojerdi et al. 2001; Cheeran et al. 2010). This strengthening following monocular deprivation is in contrast to the usual functional decline associated with cortical inhibition. Even a short deprivation of 15 min can produce temporary strengthening of the deprived eye resulting in a change in perceptual behavior (Kim et al. 2017). Similar to the mutual inhibition found between visual field specific attentional processing regions in temporoparietal areas, bistable perception between the 2 eyes is controlled via mutual inhibition between the eyes in early visual areas (Binda et al. 2018). In monocular deprivation, a boost in performance of the deprived eye was thought to be due to the subsequent lack of inhibition from the functioning eye (Lunghi et al. 2011). This lack of inhibition is demonstrated by the overall decrease in GABA concentration in the early visual cortex which correlates with postdeprivation perceptual performance of the deprived eye (Lunghi et al. 2015). Therefore, the boost in functionality may be a method for stabilizing homeostatic gain response, where the deprived cortex attempts to restore balance between the homotopic brain regions (such as binocular balance, Zhou et al. 2013). This theory could indeed account for the effects we found following multimethod stimulation of the posterior IPS. Posterior IPS is reliant on mutual inhibition with its homotopic counterpart to adequately induce lateralized attention (Corbetta et al. 2005). It may be that the multimethod stimulation still has an inhibitory effect, but this is mitigated in the behavior by the reduction of mutual inhibition from homotopic posterior IPS. Together these effects could cancel one-another, resulting in no change in behavior.

Interestingly, there was also no effect of LF-rTMS alone to the posterior IPS directly after stimulation, further supporting our interpretation of the initial null effect in the multimethod condition. LF-rTMS can result in an acute inhibitory behavioral response directly after stimulation (e.g., Battelli et al. 2009; Edwards et al. 2017), but has also been reported to have no immediate but a delayed effect after stimulation to posterior IPS (Plow et al. 2014; Agosta et al. 2014), and occasionally, no impact on behavior at all (Edwards et al. 2017).

HF-tRNS stimulation seemed to have no direct impact on behavior during stimulation in experiment 1. Although cortical excitability has been demonstrated almost instantaneously following 20-min HF-tRNS (Snowball et al. 2013; Herpich et al. 2018), the excitability impact can take time to present during stimulation (Tyler et al. 2018) and it can show a cumulative effect across days and sessions (Herpich et al. 2019). Tyler et al. (2018) illustrated the cortical excitability profile during 1 session of HF-tRNS to bilateral IPS, with attention increasing significantly above control 25 min following stimulation. In experiments 1 and 2, it is therefore likely that cortical excitability following HF-tRNS had built significantly in bilateral IPS by the time LF-rTMS was applied.

Finally, regardless of the order of stimulation protocols used in experiment 2, participants’ sustained attention did not deviate from the performance threshold set at the beginning of the experiment. This lack of depreciation of attention across time indicates a training effect across session, further supported by our analysis. Our data are in line with previous studies which demonstrate multiple sessions of training can improve cognitive performance (Jaggi et al. 2008; Herpich et al. 2019; Pergher et al. 2020). Despite the impact of training across session, we still found a significant improvement in attention within the tRNS and rTMS session.

Conclusion

Sustained attention is a limited resource, necessary across multiple cognitive tasks (DeGangi and Porges 1990). Maintenance of attention across time is sought after in both the clinical and healthy populations. Here, we demonstrate attention can be maintained without decrement for up to (and potentially beyond) 94 min following multimethod brain stimulation. Future research should be focused on the underlying network changes following multimethod stimulation. Network-based compensation for inhibition of 1 focal node of a network using multimethod stimulation may prove useful in other cognitive domains, such as working memory (Compte et al. 2000). Efficiency of network-wide communication has been demonstrated to be of utmost importance in conserving cognitive reserve with age (Weiler et al. 2018).

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