Covariations between pupil diameter and supplementary eye field activity suggest a role in cognitive effort implementation.

In both human and nonhuman primates (NHP), the medial prefrontal region, defined as the supplementary eye field (SEF), can indirectly influence behavior selection through modulation of the primary selection process in the oculomotor structures. To perform this oculomotor control, SEF integrates multiple cognitive signals such as attention, memory, reward, and error. As changes in pupil responses can assess these cognitive efforts, a better understanding of the precise dynamics by which pupil diameter and medial prefrontal cortex activity interact requires thorough investigations before, during, and after changes in pupil diameter. We tested whether SEF activity is related to pupil dynamics during a mixed pro/antisaccade oculomotor task in 2 macaque monkeys. We used functional ultrasound (fUS) imaging to examine temporal changes in brain activity at the 0.1-s time scale and 0.1-mm spatial resolution concerning behavioral performance and pupil dynamics. By combining the pupil signals and real-time imaging of NHP during cognitive tasks, we were able to infer localized cerebral blood volume (CBV) responses within a restricted part of the dorsomedial prefrontal cortex, referred to as the SEF, an area in which antisaccade preparation activity is also recorded. Inversely, SEF neurovascular activity measured by fUS imaging was found to be a robust predictor of specific variations in pupil diameter over short and long-time scales. Furthermore, we directly manipulated pupil diameter and CBV in the SEF using reward modulations. These results bring a novel understanding of the physiological links between pupil and SEF, but it also raises questions about the role of anterior cingulate cortex (ACC), as CBV variations in the ACC seems to be negligible compared to CBV variations in the SEF.

Introduction

Seminal studies revealed that pupil dilation varies with increasing task demands, including perception, attention, task consolidation, learning, and memory [1-6]. Two dominant interpretations for these findings have been proposed. Numerous authors concluded that pupil dilation reflects the demands of a task, whereas others took it a step further and proposed that pupil dilation reflects the effort exerted in response to such demands [1,2,7]. The precise neural substrates by which such cognitive processes influence pupil diameter are still unclear, but inputs from the dorsal part of the medial prefrontal cortex (dmPFC), which mediates arousal, are likely involved.

The dmPFC contains the frontal eye fields (FEF), supplementary motor area (SMA), and supplementary eye field (SEF). The FEF is known to be involved in the control of eye movements and attention, and recent studies have shown that the amplitude of pupil responses depends on the combination of the light stimulus and subthreshold FEF electrical microstimulation [8,9]. Strongly interconnected to the FEF and anterior cingulate cortex (ACC), the SEF is a key region that integrates attentional, short-term memory, and oculomotor tasks [10,11]. The SEF also directly projects to the brainstem oculomotor nucleus. dPMC, including the ACC, SEF, and FEF networks may directly modulate the olivary pretectal nucleus, which encodes retinal illumination and directly activates the pupil-constrictor pathway [8,12-14]. In addition, the ACC, SEF, and FEF networks may act indirectly through the occipital visual cortical areas, or superior colliculus (SC), in which the visual responses are modulated by FEF and may, in addition to programming the oculomotor plan, participate in the pupil light reflex (PLR) [15-18]. Although the function of the SEF in oculomotor tasks is reasonably well defined, involvement of SEF activity in the frontal controller circuit of pupil dynamics is still unknown.

Pupil dynamics have been studied during preparation and before the execution of eye movements during oculomotor protocols [19] providing unique insights into the neuronal substrate coordinating cognitive processing, sensor-motor transformation, and pupil diameter. In the context of the antisaccade task, subjects are instructed before the appearance of a stimulus to either automatically look at the peripheral stimulus (prosaccade) or suppress the automatic response and voluntarily look in the opposite direction from the stimulus (antisaccade). In this type of paradigm, pupil diameter was found to be larger in preparation for correct antisaccades than in preparation for correct prosaccades and erroneous prosaccades made in the antisaccade condition [20]. When an incorrect saccade is executed with latencies in the range of express saccades, execution of the movement indicates that subjects are unable to inhibit involuntary actions, whereas they have no difficulties in generating voluntary saccades if they correct such directional errors. In humans, during saccade preparation, pupil size appeared to be larger in preparation for correct antisaccades than in preparation for correct prosaccades. Given that the SEF is known to be critically involved in the production of antisaccades [21], the precise dynamics through which pupil diameter and SEF activities are conjugated merits further investigation before, during, and after pupil diameter modulation. In a previous study on short sessions (of about 200 seconds), we noticed different slopes and different evolution of CBV depending on the sessions, the subjects and tasks (see Fig 1 from Dizeux and colleagues [22]). In order to understand the origin of these variations, we decided in this new study to study and manipulate specifically these variations of CBVs during a session: in much longer sessions (more than 2,000 seconds), with a randomization of the nature of the trials and by manipulating the level of reward.

Fig 1

Task timeline.

(a) The heads of the monkeys are fixed in a chair with a 15-MHz ultrasonic probe in a recording chamber. An EyeLink recording system records the eye position and pupillary diameter in real time. During the task, there is a baseline of 200 to 220 s (randomized) and a fixation point is shown. If the animal succeeds, a prosaccade (vertical rectangle) or an antisaccade (horizontal rectangle) is shown on the screen. Based on the cue, the animal performs a saccade or an antisaccade and, if he succeeds, receives a reward associated with a specific color of the fixation point (red: 0.5 times the normal reward, blue: 1 time the normal reward, green: 1.5 times the normal reward). This action is followed by a gray screen of 3 to 4 s (randomized) used as an intertrial before repeating from the fixation point. (b) The average saccade response time for Monkey S for all sessions was 197.0 ± 15 ms, and the antisaccade response time 262.0 ± 10 ms, with a total correct rate of 88.2 ± 4.2%. (c) The average saccade response time for Monkey G was 218 ± 32 ms, and the antisaccade response time 267 ± 24 ms, with a correct rate of 85.7 ± 4.6%. The data underlying the graphs shown in the figure can be found in https://osf.io/2q357/.

This question can be addressed using modern neuroimaging techniques, such as functional ultrasound (fUS) imaging. This innovative imaging technique allows very precise mapping of fine temporal changes in brain neurovascular activity at high spatial resolution in large cortical areas in nonhuman primates [22,23]. In the present series of experiments, we tested whether pupil dynamics are linked to SEF activity during an antisaccade task on awake monkeys.

We obtained 2 primary results: (1) SEF activity is a robust predictor of specific variations of pupil diameter over both short (milliseconds) and long (minutes) time scales; and (2) strong covariations of pupil diameter and CBV can be selectively observed in the SEF by manipulating reward and cognitive effort.

Results

We recorded SEF activity by fUS imaging in 2 monkeys (n = 26 sessions for Monkey S and n = 20 sessions for Monkey G) trained to perform a pro/antisaccade task (Fig 1A). The task differs from the usual pro and antisaccade task where the information about the nature of the trial is conveyed by the fixation point and not by the peripheral target. We decided to train our animals in this variant so that future experiments parametrically manipulate the perceptual difficulty of target selection on each trial (by varying the ratio (height/width)). Both monkeys performed the task reliably across all recording sessions, and the average correct rate of both monkeys was approximately 85% (Fig 1B and 1C). The 2 monkeys showed significant shorter latencies for prosaccades than antisaccades, confirming a higher cognitive effort when an antisaccade was planned (Monkey S: 197 ± 15 ms for prosaccades, 262 ± 10 ms for antisaccades, p = 7e-9; Monkey G: 218 ± 32 ms for prosaccades, 267 ± 24 for antisaccades, p = 2e-4, using Wilcoxon’s rank test). All trials were used for futher analysis regardless of their nature (prosaccades versus antisaccades, right versus left) or whether they were successful or not, unless stated otherwise.

1 –Pupil diameter covaries with supplementary eye field CBV at short time scale

We wished to investigate the relationship between pupil diameter and brain activity without any a priori choice concerning the activated area. To map those areas, we applied the generalized linear model (GLM) to the fUS data using pupil diameter as the input matrix. In total, 600 trials were used for these analyses. Each trial is separated from one another by a random interval of 3 to 4 s, this jitter allowing avoidance of monkey anticipation between trials. We constructed the input matrix by realigning all pupil diameters with the target presentation time using the peak value of the pupil diameter during the presentation stage. Indeed, the pupil diameter was higher for the first trials (in blue in Fig 2A–2E) than for the last (in red in Fig 2A–2E). We choose, for reproducible measurements, the pupil diameter during the trials as the pupil diameter at the median first local maximum dilation (at 0.8 s for Monkey S (Fig 2A) and 0.6 s for Monkey G (Fig 2E)). The highlighted pixels in Fig 2B–2F are those for which p < 0.05 (before Bonferroni correction), indicating the pixels highly correlated with the pupil diameter in our cortical imaging plane. In these activated pixels, mostly consisting of the surface of the cortex, we found the activated area to be in the SEF, bilaterally for Monkey S and mostly in the left area for Monkey G. Such activation is consistent with the Paxinos atlas for the localization of the SEF. High correlations of the fUS signals with the pupil diameter were found in the SEF regions for both animals. Finally, we extracted the cerebral blood volume (CBV) temporal signal from our fUS data by spatially averaging the signal isolated in the functionally activated area (Fig 2C–2G). By looking at the very first trial of each task, we observed that the covariation between CBV and pupil signals occurred over short time scales, as both the fUS and pupil diameter signal exhibited a large and sharp increase (zoom in Fig 2C–2G). The CBV sharp increase is consistent with the results of the previous studies [22]. Finally, we can infer a similar activity in the pupil and in the SEF, as denoted by the application of the GLM.

Fig 2

Example of 1 session for each monkey of the vascular and pupillary responses and multiple sessions covariation of pupillary and vascular responses.

(a) Pupillary response over time. The color represents the number of the trial (blue: first trial, red: last trials), whereas the temporal abscissa represents the time prior to the presentation of the saccade or antisaccade cue. The vertical line represents the chosen time for the maximal dilation (0.8 s for Monkey S). (b) The vascular response of Monkey S using Fig 2D as an input matrix for the GLM. The background image consists of an anatomical image obtained by averaging all the Doppler films. The Z-score map was obtained using the GLM and thresholded using the Bonferroni correction (p < 0.05 uncorrected). (c) Example of a CBV response during the starting of a task for Monkey S., showing a step at the end of the baseline and the beginning of the task. The small square represents a zoom on the first trial. (d) Maximum pupillary dilation at 0.8 s after presentation of the cue using the same color code as in B. Black stars represent the pupillary diameter during baseline. (e) Same as for 2.a for Monkey G. The vertical line is at 0.6 s after presentation of the cue. (f) Same as for 2.b for Monkey G, using 2.h as an input matrix. (g) Same as for 2.c for Monkey G. (h) Same as for 2.d for Monkey G. (i and j) Scatter plot of the ΔCBV slope in function of pupil slope in SEF (blue), ACC (purple) et Control area (green) for both Monkey S (Fig 2I), and Monkey G. (Fig 2J), prediction intervals are the 95% prediction interval. The session represented in full lozenge is the session taken as example in a–d for Monkey S and e–h for Monkey G. (k) Pearson’s correlation coefficient between pupil diameter (see d and h) and 3 areas in the brain: SEF (blue), ACC (purple), and Control (green) for all nonreward-modulated sessions for both animals (n = 21 sessions for Monkey S, n = 13 sessions for Monkey G), *** p < 0.001, ns: not significant. The data underlying the graphs shown in the figure can be found in https://osf.io/2q357/. All vertical green bars represent the end of the baseline and the start of the task. ACC, anterior cingulate cortex; CBV, cerebral blood volume; GLM, generalized linear model; SEF, supplementary eye field.

2 –Pupil diameter covaries with supplementary eye field CBV at long time scale

We are now interested in knowing if the pupil diameter and the activity in the SEF is not only having covariation at short time scales, but also as long time scale, i.e., during a whole session.

During the successive trials of a nonreward-modulated prosaccade and antisaccade task, we observed a large and reproducible decrease in the relative CBV (rCBV) of the SEF, defined anatomically using the monkey brain atlas and functionally using the GLM, as previously described (Fig 2C–2G) (‒23 ± 2%/h for Monkey S and ‒21 ± 5%/h for Monkey G) after the initial step induced by the start of the task (the first saccade) as described by Dizeux and colleagues [22]. Given the strong correlation between pupil diameter and cognitive engagement in the task, we examined the pupil diameter after a prosaccade or antisaccade task. We also observed a large and reproducible decrease in pupil diameter throughout the session (Fig 2D–2H, ‒9.3 ± 0.3%/h for Monkey S and ‒9.7 ± 3.1%/h for Monkey G) on a long time scale. The decrease in pupil diameter is correlated with the change in the activity of the SEF, as quantified next.

Because the step played an important part in the correlation between the pupil diameter and the Doppler signal in the SEF, we also performed an analysis on the decays without taking the step into account. We fitted the slope of the fUS signal (normalized by the baseline) in 3 regions: SEF, ACC, and Control, and the slope of the pupil during the task over different sessions. We then looked at the relationship between those slopes, by plotting the former as a function of the latter (Fig 2I for Monkey S, Fig 2J for Monkey G) and observed a relation between the slope of the pupil and the SEF (R2 = 0.28 for Monkey S and R2 = 0.40 for Monkey G). This relation is weaker for the ACC (R2 = 0.20 for Monkey S, R2 = 0.045 for Monkey G) and for the Control area (R2 = 0.0094 for Monkey S and R2 = 0.13 for Monkey G) indicating the relationship between the CBV in the SEF and the pupil even without the initial step.

Furthermore, we compared the squared Pearson’s R2 correlation coefficient between 3 regions of the brain (SEF, ACC, and a control area, anatomically chosen for the SEF and ACC and to be the non-activated cortical area farthest from the SEF) and the pupil signal. The R2 was significantly higher (using a linear mixed-effects statistical model) in the SEF (0.31 ± 0.03, SEM) than in the ACC (0.12 ± 0.02, SEM) or control area (0.14 ± 0.02, SEM) (Fig 2K).

Those results seems to indicate that pupil activity, and SEF activity are linked together during the time of a session.

3 –Stronger vascular response in antisaccades compared to prosaccade trials in the SEF accompanied by larger pupil response

Given the correlation between the activity of the pupil and in the SEF, we were also interested in the difference of activity for a given cognitive load.

The successive trials consist of randomized prosaccades and antisaccades, as described in Fig 1. The cognitive effort required to perform an antisaccade is higher than the one required to perform a prosaccade. All sessions were kept for further analysis, without any discrimination between them. In those analyses, only the correctly performed pro or antisaccades were kept for analysis. Then, we analyzed the difference between the pupillary response for prosaccades and antisaccades. In 2015, Wang and colleagues [20] showed that the pupillary diameter is slightly bigger in preparation for antisaccades than it is for prosaccades. Here, we showed, with the same principle, that pupillary diameter is slightly larger for antisaccades than it is for prosaccades, even without a gap between the cue presentation and the realization of the saccade (p < 0.001). We measured the area between the antisaccade curve (Fig 3A, in red) and the prosaccade curve (Fig 3A, in blue) to quantify those slight differences in the pupillary diameter (n = 32 sessions), between 0 ms and 320 ms, as it corresponds to the median onset time for antisaccades plus the fixation of the targeted region of interest on the screen. A quite important hypothesis was to test the difference between pro- and antisaccades in the ΔCBV of the SEF to see if this area is not only responding to long-term monitoring of motivation and effort, but also short-term effort. We have realigned fUS signals on target presentations (Fig 3B, blue for prosaccades, red for antisaccades) to see if the SEF had a different vascular response for pro and antisaccades. We showed, here, that the vascular response for antisaccades is higher than the vascular response induced by prosaccades (p < 0.01, integration of the signal between 0 s and 4 s as it corresponds to the time for estimated HRF to return to the baseline), showing that the SEF is not only sensitive to long-term variations (minute variations) but also short-term effort-related variations (single trial variations).

Fig 3

Effect of cognitive effort (prosaccades versus antisaccades) on pupil diameter and cerebral blood flow.

(a) Pupillary diameter for prosaccade (in blue) and antisaccade (in red) +/− SEM averaged over all kept sessions in 2 animals. Purple area corresponds to the difference in the area under the curve one of both curves. (b) Same as (a) but for the ΔCBV. The data underlying the graphs shown in the figure can be found in https://osf.io/2q357/.

4—Reward magnitude modulates both SEF activity and pupil diameter

Since correlation does not imply causation, we wanted to manipulate reward to test the causality of our measures. We measured engagement in the task by slightly adapting our paradigm by adding a color code at the fixation point on each given block of 100 trials and modifying the magnitude of the reward. The potential reward delivered for each correct pro or antisaccade was red for 0.5 reward units, blue for 1.0 reward unit, and green for 1.5 reward units (Fig 4A and 4B). During the task, the ΔCBV changed during the transition from one reward level to another, as did pupil dilation. We also observed a slight disengagement of monkeys when the task is high-cognitive demanding (e.g., antisaccade) for a low reward (e.g., 0.5 reward unit for red fixation point). The observed saturation for pupil size and CBV for the largest reward changes may reflect the limited delta of the subjective perception of reward manipulated in our experiments.

Fig 4

Reward modulation during the task for both Monkey S and Monkey G.

(a) CBV and pupillary response over 1 session for Monkey S. The colors represent the quantity of reward obtained after a successful trial (green: 1.5× the base reward, blue: 1× the base reward, and red: 0.5× the base reward). (b) Same as for (a) for Monkey G. (c) Pupil dilation according to the change in reward for Monkeys S and G. Mean ± standard error of the mean. (d) The CBV changed according to the change in reward, all sessions for Monkeys S and G. Blue represent the SEF, red the ACC, and green the control area. Mean ± standard error of the mean. (e) Animal disengagement during the task for antisaccades for low (red), normal (blue), and high (green) reward. Mean ± standard error of the mean. ns: not significant, *** p < 0.001. The data underlying the graphs shown in the figure can be found in https://osf.io/2q357/. ACC, anterior cingulate cortex; CBV, cerebral blood volume; SEF, supplementary eye field.

We wanted to quantify pupil dilation and the ΔCBV during such transitions. We computed the transition between the 2 levels of reward by computing the average CBV and pupil diameter for 10 trials before the transition and 10 trials after. The difference between the values after versus before the transition gives the increase or decrease induced by the transition. Pupil dilation decreased in the transition from a higher to lower reward and increased in the transition from a lower to higher reward (Fig 4C). We observed an increase in the ΔCBV in the SEF during a transition from a lower to higher reward, but no statistically significant measure was obtained for a transition from higher to lower reward (Fig 4D, in blue). We did not identify any significant difference in covariations between the different reward manipulations.

Interestingly, we observed a marginal effect on the ACC (Fig 4D, in red) for the reward transition from 0.5 units to 1.5 units and 1.5 units to 0.5 units. More rostral investigations of the ACC would be required to measure such effects in this area. A control area showed no augmentation or decrease (Fig 4D, in green). Finally, increasing the reward resulted in augmentation of both pupil dilation (Fig 4C) and ΔCBV in the SEF (Fig 4D, blue) but also a modification of the engagement to perform the task (Fig 4E): Animals were less engaged for the antisaccades in the task during low rewarded block than for normal or highly rewarded blocks (56.2 ± 4.4% and 85.3 ± 3.7% for Monkey S and G, respectively, compared to 77.1 ± 2.9% and 91.1 ± 2.3% for a normal reward for monkey S and G, respectively), indicating that our manipulation of reward was accounted by the animals to adapt their behavior according to the trial difficulty. Between blocks of distinct reward values, we did not observe significant changes in covariations between pupil and fUS responses in SEF. The duration of the periods (only 100 trials) during reward manipulation may not allow us to quantify such modulations observed at the session length (approximately 600 trials). Overall, at a transient time scale (few trials), the fUS activity in the SEF was strongly modulated in real time by the reward, as was pupil diameter.

Discussion

We combined pupil signals and real-time fUS imaging of NHP during cognitive tasks, which allowed us to infer localized CBV responses within a restricted part of the dorsomedial prefrontal cortex, referred to as the SEF, an area in which antisaccade preparation activity is also recorded. Inversely, SEF neurovascular activity measured by fUS imaging was found to be a robust predictor of specific variations in pupil diameter over short and long time scales. The manipulation of reward and cognitive efforts performed by the animals resulted in strong temporal covariation of pupil diameter and CBV within the SEF. Overall, these results show the region of the SEF to be an underestimated pivotal element within the medial frontal cortex of primates for monitoring and implementing the cognitive effort signals observed within autonomous networks.

In previous studies, SEF neurons have been shown to participate in the selection of eye movements by representing the context-dependent action value of various possible oculomotor behaviors [24]. However, the SEF alone does not have the aptitude to directly select eye movements [24]. In the same vein, the SEF does not directly participate in the rapid inhibitory control of eye movements in response to sudden changes in task requirements.

In both human and nonhuman primates, seminal studies have shown that SEF can indirectly influence the selection of behavior through modulation of this primary selection process in the motor structures. In humans, numerous studies suggest a role for the SEF in controlling “internally generated” eye movements during the performance of complex learned behavior [25-27].

Rare studies have been capable of further examination. Some reports from sporadic patients with focal lesions of SEF have shown great difficulty for these patients across a range of saccadic tasks [25-28], as well as changing from an initial saccade plan to an alternative one [29,30]. These results were confirmed by functional imaging of healthy individuals performing a change-of-plan saccadic task, resulting in enhanced SEF activity when subjects successfully changed their saccadic plans compared to following a predictive plan [31]. Finally, some studies in human neuroimaging experiments have related these voluntary controls of saccade plan to a more general influence in the context of speed-accuracy tradeoff experiments [32,33].

Based on these findings, it has been proposed that a significant role of the SEF lies in implementing control over conflicting internally generated saccadic plans [30,31]. In macaques, SEF also shows systematic changes in activity during learning of new stimulus-response associations [32].

Even after the task set has been learned, monitoring of behavior is necessary to catch changes in the environment or possible mistakes due to response conflict or inadequate attention that guides their behavior as long as they are motivated to do so [33-36]. Our results reinforce these interpretations of the role of SEF in the monitoring of behavior. However, they may have extra critical implications because variations in pupil diameter have been observed for various tasks [1-5]. Two principal explanations have been provided to account for such pupil-effort covariation. First, a direct “bottom-up” influence on decisions produces a bias toward accepting an effort. This would be consistent with the widely held view that the strength of neural representations for choice attributes directly influence the decision. For example, it has been shown that intensifying encoded rewards through the simulation of future episodic events is linked with decisions that promote higher long-term payoffs and even increase prosocial behavior.

As for neural implementation, phasic locus coeruleus (LC) activity is known to transmit feedforward information to the SEF via ascending projections to the prefrontal cortex (PFC), providing a plausible pathway for such a bottom-up influence. Recent work has shown that LC neurons can reflect both cognitive and physical efforts with a subsecond precision [37].

Therefore, the neural readout of the autonomous activation associated with arousal could provide an additional mechanism by which the arousal signal observed here may bias choices, serving as a signal that the organism is indeed ready to accept the physical challenge.

In the ACC, unlike the SEF, there was not even a tendency of heightened CBV modulation under conditions of cognitive effort. This finding is compatible with an earlier report showing that ACC neurons in the monkey are not selectively active during the countermanding of saccades, an operation assumed to involve cognitive effort and inhibition of action [38]. However, it stands in sharp contrast to a large body of literature, based on functional MRI imaging in humans, indicating that activation in the ACC is strongly heightened under conditions of effort [39-42]. Here, we report that during a sustained execution of a demanding oculomotor task over more than 1 h, the neurovascular coupling (as assessed by fast ultrasound imaging, fUS) in the SEF of macaques, progressively drops with time, correlating with a simultaneous drop in pupil size and performance. When changing reward ratio, intrinsic brain mechanisms might compensate for the progressive drop in cognitive performance by instantiating alternations of high and low performance. These variations in behavioral performance might be phase-locked to variations in attention- and perception-related information as shown in macaque FEF neuronal populations [43].

There are several possible explanations for this discrepancy. There may be a species-specific difference, such that neurons in the human ACC monitor cognitive effort, whereas those in the monkey ACC do not. This seems improbable because, in general, anatomically homologous areas appear to serve similar functions in the 2 species [44]. This cannot, however, be altogether ruled out. The human ACC possesses a cell type not found in the monkey ACC [45] and, therefore, may serve a function not served by the monkey ACC. It is possible that our recording sites lay outside the region of the ACC responsible for effort-related activity [46]. This also seems improbable because we deliberately recorded in the subregion that is connected to the SEF [47] and in which, accordingly, it would be most reasonable to expect to find activity sensitive to cognitive effort in an oculomotor task. It is also possible that the cognitive-specific bold signals detected in human fMRI studies are related to neural events other than spiking activity and CBV, for example, presynaptic potentials [48]. It may be the case that ACC activity, even in humans, does not exhibit enhanced spiking activity under conditions of cognitive effort. For the ACC to serve a cognitive effort and alert the rest of the cortex to the presence of cognitive effort would require enhanced spiking activity because spikes are the currency used between the ACC and other cortical areas. Thus, the remaining conclusion is that the ACC does not monitor cognitive effort.

Overall, our observations are consistent with a possible top-down influence from the SEF to the noradrenaline arousal system, which may serve to transmit information about the commitment to overcome a great physical demand, thus resulting in automatic accelerating upregulation of arousal states to prepare the organism for the upcoming challenge associated with the recent choice. As SEF activity and pupil are strongly correlated over large time scales, our results also allow us to conclude that within the medial frontal cortex of primates, aside from the ACC, the SEF may also play a role in the implementation of the arousal signals observed within autonomous networks.

Methods

Animal model and behavioral data

All experimental procedures were designed in association with the veterinarians of the ICM Brain and Spine Institute, approved by the Regional Ethical Committee for Animal Experiment (CREEA IDF n°3, agreement number A-75-13-19; Ministère de l’Education, de l’Enseignement Supérieur et de la Recherche under the project reference APAFIS #6355–2016080911065046), and performed in compliance with the European Community Council Directives (86/609/EEC). Functional data were acquired from 2 captive-born rhesus monkeys (Macaca mulatta), S and G, trained to perform various types of visual tasks. In the saccade task, the animal has to fix its gaze on the cue object presented on the right or left side of the screen; in the antisaccade task, it has to fix its gaze on the opposite side from where the cue appeared. Each animal performed at baseline (200 to 220 s, random) followed by saccades and antisaccades (randomized) over 1 h. During data acquisition, the eye position of the primate was monitored at 1 kHz using an infrared video eye tracker (Eyelink 1k, SR-Research), which enabled live control of the behavioral paradigm and the delivery of a reward based on the success or failure of a visual task [49].

Experimental setup

We recorded 46 sessions (26 for Monkey S and 20 for Monkey G) of a variant of prosaccade and antisaccade tasks [50], with 2 kinds of sessions (Fig 1).

The conventional session, without reward modulation, consisted of only a blue square before the prosaccade or antisaccade cue, and the reward was kept constant within and between all sessions. For the second type of task, with reward modulation, the same basal reward was retained and the animal was presented with 3 colored dots (red for 0.5 reward unit, blue for 1 reward unit, and green for 1.5 reward unit) before the prosaccade or antisaccade cue. Behavioral data, such as pupil diameter, were recorded with an EyeLink system and CBV using a functional ultrasound scanner for all sessions.

All tasks were driven by EventIDE software (OkazoLab, the Netherlands).

The reward was calibrated to the weight of the primate and the model of the rewarding tube (approximately 30 ms/kg for the electronic valve), which delivered sugary water. Primates were under mild fluid restriction (approximately 30 mL/kg/day) and could drink ad libitum while working.

Implant and probe for functional ultrasound imaging for awake cooperative monkeys

The head of the monkey was fixed using a surgically implanted titanium head post (Crist Instrument, Maryland, United States of America). After behavioral training of the animals, a recording chamber (CILUX chamber, Crist Instrument, Maryland, USA) was implanted, and a craniotomy (diameter 19 mm) was performed (mediolateral: +0 mm, antero-posterior: +26 mm). The ultrasonic probe with sterile ultrasonic gel was then inserted into the chamber.

Functional ultrasound (fUS) recording

Changes in CBV were measured using a real-time functional ultrasound scanner prototype (Iconeus and Inserm U1273, Paris, France) with a custom linear probe (128 elements, 15 MHz, 100 × 100 μm2 of spatial resolution). The probe was positioned in the recording chamber using an home made adapter (represented in black on the image on the left) with a small notch allowing the probe to be positioned at the same position for each recording session. Moreover, the thickness of the imaging plane (from 700 μm at the start to 400 μm at the focal plane, around 8 mm from the probe) allowed a repeatable field of view even though the position was slightly variable. This scheme is now presented in S1 Fig. Data were acquired by emitting continuous groups of 11 planar ultrasonic waves tilted at angles varying from ‒10° to 10°. Ultrasonic echoes were summed to create a single compound image acquired every 2 ms. Final Doppler images were created by averaging 200 compound ultrasonic images after spatiotemporal filtering based on the singular value decomposition of the ultrasonic images. The acquired images have a pixel diameter of 100 × 100 μm and a slice thickness of 400 μm. The CBV is acquired continuously at the rate of 2.5 Hz and extracted at each trial on a time window of ‒1.2 to 4.4 s (from target onset). Those values were chosen as they are a multiple of 0.4 s, which is the sampling of the fUS imaging.

Eye movements and pupil recordings

Eye movements and pupil diameter were recorded during the tasks using a video eye tracker (Eyelink 1k, SR-Research) connected to an analog-to-digital converter (Plexon, Texas, USA). All data were collected using Plexon software and analyzed using MATLAB (MathWorks, Massachusetts, USA). Saccades were detected when the eye’s horizontal velocity went over 30° s−1.

Data processing

Generalized linear model

Doppler data were analyzed using a GLM approach implemented in Matlab. The stimulation pattern in the design matrix was convoluted with the fUS-determined HRF and a Z-score and CBV change map were obtained. The activation maps show the Z-score of all pixels in the images with a p-value < 0.05 (before Bonferroni correction). We chose the region of interest (ROI) within the SEF based on the Z-score map and Paxinos atlas for macaque brains and the signal was averaged to obtain a single temporal signal. The spatially averaged signal was then expressed as the relative increase in CBV (in percent) by subtracting the baseline CBV (calculated during the baseline at the beginning of an acquisition) normalized to the baseline CBV.

Determination of the pupil diameter

The pupil diameter was expressed in percent by subtracting the baseline value and then dividing the difference by the baseline value (in which we excluded all blinks and moments in which the eyes were closed). We then determined the maximum dilation diameter following a task by realigning the pupil diameter at the onset of the cue presentation. We chose the first local maximum of the pupil diameter (0.8 s after target onset for Monkey S and 0.6 s after target onset for Monkey G) to extract the pupil diameter for the ith trial.

Fitting of the hemodynamic response

The hemodynamic response was determined by averaging the CBV response of all trials and fitting the average by an inverse-gamma probability distribution using MATLAB lsqcurvefit (Optimization Toolbox) algorithm for least square nonlinear fitting, as previously described by other authors [51].

Statistical analysis of the hemodynamic responses

Statistical analysis between 2 groups was performed using the Wilcoxon rank test, due to the non-normality of our data, using the Matlab ranksum function, the null hypothesis being no statistical difference between the 2 groups. If more than 2 groups were available and the data hierarchically organized, we used a linear mixed statistical model. Data was homogenized using a square root transformation and the variance of homogeneity assessed using the Bartlett test and residual normality the Shapiro–Wilk test.

Custom Holder for fUS recording and average of all sessions for the ΔCBV in the SEF, ACC, and control area for the 2 animals.

(a) Custom holder for adaptation of the ultrasonic probe (15 MHz) to the recording chamber on the animal. (b) ΔCBV for the SEF (in blue), the ACC (in red), and the control area (in green) +/− SEM across all sessions. The data underlying the graphs shown in the figure can be found in https://osf.io/2q357/. ACC, anterior cingulate cortex; CBV, cerebral blood volume; fUS, functional ultrasound; SEF, supplementary eye field.

(TIF)

Click here for additional data file.

Average trial response in function of the reward for the ΔCBV and the pupil for the 2 animals.

(a) Average ΔCBV response for low (red), medium (blue), and high (green) reward. (b) Integration between t = 0 s and t = 4.4 s of the previous ΔCBV curve. (c) and (d) Same for the pupil diameter. Integration is calculated between t = 0 ms and t = 320 ms. n.s.: not significant, *** p < 0.001 The data underlying the graphs shown in the figure can be found in https://osf.io/2q357/

(TIF)

Click here for additional data file.

17 Aug 2021

Dear Pierre,

Thank you for submitting your manuscript entitled "The Supplementary Eye Field Tracks Cognitive Efforts" for consideration as a Research Article by PLOS Biology.

Your manuscript has now been evaluated by the PLOS Biology editorial staff, as well as by an academic editor with relevant expertise, and I am writing to let you know that we would like to send your submission out for external peer review. Please accept my apologies for the delay in sending this decision to you.

However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.

Please re-submit your manuscript within two working days, i.e. by Aug 19 2021 11:59PM.

Login to Editorial Manager here: https://www.editorialmanager.com/pbiology

During resubmission, you will be invited to opt-in to posting your pre-review manuscript as a bioRxiv preprint. Visit http://journals.plos.org/plosbiology/s/preprints for full details. If you consent to posting your current manuscript as a preprint, please upload a single Preprint PDF when you re-submit.

Once your full submission is complete, your paper will undergo a series of checks in preparation for peer review. Once your manuscript has passed all checks it will be sent out for review.

Given the disruptions resulting from the ongoing COVID-19 pandemic, please expect delays in the editorial process. We apologise in advance for any inconvenience caused and will do our best to minimize impact as far as possible.

Feel free to email us at plosbiology@plos.org if you have any queries relating to your submission.

Kind regards,

Gabriel Gasque

Senior Editor

PLOS Biology

ggasque@plos.org

19 Oct 2021

Dear Pierre,

Thank you for submitting your manuscript "The Supplementary Eye Field Tracks Cognitive Efforts" for consideration as a Research Article at PLOS Biology. Your manuscript has been evaluated by the PLOS Biology editors, by an Academic Editor with relevant expertise, and by four independent reviewers. Please accept my apologies for the long delay in sending the decision below to you.

In light of the reviews (below), we will not be able to accept the current version of the manuscript, but we would welcome re-submission of a much-revised version that takes into account the reviewers' comments. We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent for further evaluation by the reviewers.

We expect to receive your revised manuscript within 3 months.

Please email us (plosbiology@plos.org) if you have any questions or concerns, or would like to request an extension. At this stage, your manuscript remains formally under active consideration at our journal; please notify us by email if you do not intend to submit a revision so that we may end consideration of the manuscript at PLOS Biology.

**IMPORTANT - SUBMITTING YOUR REVISION**

Your revisions should address the specific points made by each reviewer. Please submit the following files along with your revised manuscript:

1. A 'Response to Reviewers' file - this should detail your responses to the editorial requests, present a point-by-point response to all of the reviewers' comments, and indicate the changes made to the manuscript.

*NOTE: In your point by point response to the reviewers, please provide the full context of each review. Do not selectively quote paragraphs or sentences to reply to. The entire set of reviewer comments should be present in full and each specific point should be responded to individually, point by point.

You should also cite any additional relevant literature that has been published since the original submission and mention any additional citations in your response.

2. In addition to a clean copy of the manuscript, please also upload a 'track-changes' version of your manuscript that specifies the edits made. This should be uploaded as a "Related" file type.

*Re-submission Checklist*

When you are ready to resubmit your revised manuscript, please refer to this re-submission checklist: https://plos.io/Biology_Checklist

To submit a revised version of your manuscript, please go to https://www.editorialmanager.com/pbiology/ and log in as an Author. Click the link labelled 'Submissions Needing Revision' where you will find your submission record.

Please make sure to read the following important policies and guidelines while preparing your revision:

*Published Peer Review*

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out. Please see here for more details:

https://blogs.plos.org/plos/2019/05/plos-journals-now-open-for-published-peer-review/

*PLOS Data Policy*

Please note that as a condition of publication PLOS' data policy (http://journals.plos.org/plosbiology/s/data-availability) requires that you make available all data used to draw the conclusions arrived at in your manuscript. If you have not already done so, you must include any data used in your manuscript either in appropriate repositories, within the body of the manuscript, or as supporting information (N.B. this includes any numerical values that were used to generate graphs, histograms etc.). For an example see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5

*Blot and Gel Data Policy*

We require the original, uncropped and minimally adjusted images supporting all blot and gel results reported in an article's figures or Supporting Information files. We will require these files before a manuscript can be accepted so please prepare them now, if you have not already uploaded them. Please carefully read our guidelines for how to prepare and upload this data: https://journals.plos.org/plosbiology/s/figures#loc-blot-and-gel-reporting-requirements

*Protocols deposition*

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Thank you again for your submission to our journal. We hope that our editorial process has been constructive thus far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Gabriel Gasque

Senior Editor

PLOS Biology

ggasque@plos.org

*****************************************************

REVIEWS:

Reviewer #1: In this study, Claron et al. used functional ultrasound imaging while measuring the pupil diameter in macaque monkeys performing a saccade task to investigate the link between SEF activity and cognitive effort.

The paper is interesting, well written and overall pointing out a relationship between SEF and cognitive effort. However, the quality of the manuscript could be greatly improved by adressing several concerns.

1. Further clarifications are needed regarding the data analysis. It is unclear why the values of pupillary diameter were chosen at 0.8s and 0.6s for the data analysis in Fig.2; for instance, why not using 0.8s for monkey G, since the diameter is higher than at 0.6s ? Additionally, the temporal profile of the pupil size variation is different during the first trials as compared to the last trials in monkey S, making it difficult to chose a consistent time point. Therefore, these time points seem quite arbitrary and should be more justified, especially since it may have an important impact on the results.

2. In this regard, the interest of using only the pupil diameter at maximum dilation for further analyses is not clear to me and should be better explained. Is this step used for all results depicted in Fig 2, and if yes, why not using all pupil diameter values (after temporal realignment and resampling with the fUS signal) ? This would enable to study the correlation between cognitive effort and SEF activity at shorter time scales occuring in a single trial (which is something discussed later but only in terms of difference between antisaccade and prosaccade: as variations of pupil size are also occuring at the trial level, it would be more convincing to take them into account).

3. It would be valuable to show more results at the group level instead of examples of one session for each monkey. The supplementary figure is useful and should also include the average of all sessions for the pupil diameter variations. The variability across the Z-score maps for the different sessions should also be shown or discussed.

4. In Figure 3, the same time scales should be used for pupil diameter and CBV in order to visualize the full temporal profiles of the responses and discuss the correlation between them at the trial level.

5. How was performed the positioning of the probe in the cranial window to select a repeatable field of view ?

Reviewer #2: In this paper entitled 'The supplementary eye field tracks cognitive efforts', Claron et al. use fast ultrasound imaging to monitor in real-time the hemodynamic response evoked in the supplementary eye field (SEF) during the execution of a demanding cognitive task. Pupil size has been shown to track cognitive effort both at the single trial level and at the session level of such tasks. The authors thus seek to characterize the relationship between pupil size and SEF cerebral blood volume variations (CBV). They show that SEF hemodynamic activity is a robust predictor of pupil size variations at multiple time-scales including when experimentally manipulating cognitive effort and reward expectation.

The data is compelling and quite surprisingly shows that this correlation between CBV and pupil size is restricted to the SEF and does not extend into the adjacent cingulate cortex or along the adjacent cortical convexity. While this brings a very novel understanding of the physiological underpinnings of cognitive effort, it also raises a lot of crucial questions for upcoming research projects.

I thus strongly recommend the publication of this work once my comments below have been addressed (page and line numbers would have been useful to the reviewing process):

Major:

1. Abstract: the authors use in their concluding statement the expression 'SEF is an underestimated but pivotal cortical area for the monitoring and implementation of cognitive effort signals': I strongly recommend the authors to reformulate as this suggests a causal role, which has actually not been demonstrated in the study. More generally speaking, I recommend the abstract to be reworked in depth as it does not make justice to the results: key concepts (e.g. cognitive effort, CBV) are not defined and the text can be clarified (e.g. 'Here, we tested […] is also recorded' appears like the same information comes up multiple times in multiple sentences).

2. I recommend the authors also scrutinize the introduction in order to enhance the impact of their work. For example: 1) '..; which mediates arousal, are likely involved': references should be added; 2) Second paragraph 'In principle … Alternatively ….', please reformulate and back up with strong references; 3) 'Although the function …': I think this statement is extremely vague. The authors use anatomical evidence to suggest a role of SEF activity in the control of pupil size. This should be made explicit (control? Single controller? Why not FEF as a controller? Why not ACC?); 4) 'suggesting valid qualities': please reformulate, I am not sure I get the actual meaning here; 5) 'Given that the SEF is known …': I am missing the logic link here: why is the fact that the SEF is crucial to anti-saccades calls to investigate pupil size in this context? This should be made explicit.

3. CBV is extracted "using a random interval of 3 to 4 s after each trial": why random? Please describe trial length statistics and reward timing. It might be useful to increment the GLM with variables of non interest at this stage, such as trial outcome (i.e. reward / no reward or trial type anti- pro-saccade).

4. In section 3 of the results, better describe how many sessions were excluded per monkey. Also, rather than using an arbitrary threshold of 0.6 you might want to consider using IQR.

5. Section 3 is conceptually very important. What would further strengthen it is 1) to produce the equivalent of figures 2i,j,k for pro- and anti-saccades independently and 2) compare the strength of correlation between CBV and pupil for anti- and pro-saccades across sessions. The idea is to test whether correlation is strictly equivalent or is stronger in high demand trials relative to lower demand trials.

6. Can the authors produce the plots of figure 4c,d for performance and the plots of 4e for CBV and pupil size as the information provided by each is different. In this context, can the authors say something about the observed saturation for both pupil size and CBV as a function of reward change. Is the coding of relative reward only qualitative? Last, can the authors quantify the correlation between the delta pupil size and the delta CBV across all reward transitions and across all sessions. This would strengthen their point, all the more that the single example shown in figure 4a,b does not suggest a strict correspondence as illustrated in figure 2 in the absence of reward manipulation. The underlying question is whether the correlation between SEF CBV and pupil size is comparable across all modelled variables or whether correlation is stronger for some of them? This would help better qualify the mechanism under consideration.

7. Can the authors speculate on why CBV and pupil size decrease linearly when reward is constant (figure 2c,g) but not when it is not (figure 4a,b) -I apologize in advance if I missed some methodological detail here.

8. Does covariation between SEF CBV and pupil size change between correct and incorrect trials? If this is the case, this would be quite interesting functionally speaking.

9. The discussion includes an extensive discussion of human ACC. A recap of human SEF activity in effort and motivational tasks would be useful.

10. At the end of the discussion, there is a mention that CBV changes precede pupil size changes. I apologize upfront if I missed this analysis, but I couldn't find it in the manuscript. This is obviously a very useful and important information. Can you please clarify. If this is indeed the case that CBV precedes pupil size change, and depending of the latency between the two signals, the authors will want to explain if and how this impacts the reward manipulation section, as the data of both signals is sampled on the same number of trials around the time of shift in in reward size.

11. Overall, the manuscript should be re-read thoroughly for English phrasing and fluidity. Generally speaking, the impact of the work can be strengthened by initiating every result section by a statement of the question being asked (this often comes quite late in the section), and a conclusion statement wrapping out what has been demonstrated.

Minor:

1- Introduction, second paragraph: replace short memory by short-term memory

2- Results, title 1: I sugget something more specific for example 'Pupil size covaries with SEF CBV at short time scales'

3- Figure 1, indicate time scale in panel a for pupil diameter and rCBV

4- Did the authors mean "after" rather than before Bonferroni correction in first paragraph of section 1 and elswhere? If not, then this is a pb

5- Results: "using a random interval of 3 to 4 s after each trial ONSET"

6- Results: monkey G. (Fig. 2.e) not Fig. 2.d

7- Figure 2: panels I and j : indicate monkey identity + indicate p of correlation

8- Results, title 2: I suggest something in the line of 'Pupil size covaries with SEF CBV at the time scale of the session'

9- Results '… after the initial step': please specify

10- Results 'The decrease (no s) in pupil size correlated with the change in the activity of the SEF. THIS IS QUANTIFIED NEXT'

11- Results, I would place the description of the behavioral performance of the monkeys on the pro- and anti-saccades under section 3. Because that's where it is relevant. At the beginning of the results, you might consider describing more general behavioral features such as success rate.

12- Results, section 3: 'even without preparation': please clarify what you mean by this

13- Results, section 4: 'Reward magnitude modulates BOTH SEF activity and pupil diameter

14- I would suggest to uniformly use pupil size or diameter but not both.

15- The authors will want to use the word CUE instead of hint.

Reviewer #3: In this manuscript, the authors address the role that the supplementary eye fields (SEF) may play in relating to pupillary responses during a cognitively demanding task. The work is done in macaque monkeys, which is an important animal model to help establish the underlying neural mechanisms linking cognitively demanding tasks to pupil dilation, which is commonly observed in humans. Neural activity in the SEF is inferred by measures of cerebral blood volume (CBV) via functional ultrasound, a technique in which the authors are world leaders. Measuring SEF activity via CBV is akin to functional neuroimaging in some ways, with the exception that it comes with a better temporal resolution. The authors also manipulate reward levels to further examine the relationship between SEF-CBV and pupil dilation.

There are a number of positives to the manuscript. The experiments were conducted with great skill, and the authors present largely common trends across two animals. Further, the authors identify of a gap in knowledge in the literature, and have found interesting distinctions between what was found in the SEF (which did relate to the pupil) versus the nearby anterior cingulate cortex (which did not). The paper is also largely well written, although I do have a number of comments below which I think may help convey the core message more clearly.

Main points

While I really enjoyed this manuscript, I struggled with whether it is fundamentally about establishing the relationship between SEF-CBV activity and pupillary responses (implied in the abstract) or about linking SEF activity to cognitive effort (implied by the title). My view is that the paper is more strongly positioned as the former. Further, the notion of how cognitive effort can be dissociated from other related phenomena, like attention or motivation, is complicated, and I am not convinced that the manipulations of reward used here do indeed dissociate effort from attention/motivation. If the authors agree with my sense that the paper is about establishing the SEF as an additional frontal area influencing the pupil, then aspects of the title and introduction could change (e.g., the reward manipulation becomes another way to test the link between SEF activity and the pupil). Alternatively, if the authors feel that the paper is about cognitive effort, then I think they need to do a better job rationalizing the additional value of pupil measurements.

The authors do a good job establishing short- and long-term correlations between SEF-CBV values and the pupil. For the short-term correlations however, and specifically regarding the fact that higher SEF-CBV values and greater pupil dilation accompany anti-saccades, I do worry that these results may reflect a confound of more saccades made on anti- vs pro-saccade trials, due to the inclusion of error trials. Is it possible to redo the analyses shown in Fig 3 using only correctly-performed anti-saccade trials?

In the variant of the anti-saccade trial used here, the orientation of the peripheral target conveys the instruction to generate a pro- or anti-saccade. This variant differs from that used both by the Schlags in their seminal SEF work, as well as by the Wang studies in humans, where a feature of the initial fixation point conveyed task instruction. The latter variant introduces a greater separation in time of task preparation (which precedes target onset) from the saccadic response. I was curious as to the rationale for the authors to choose the variant of the anti-saccade task that they did. I think it would also help readers if the authors were more explicit about the difference in their task from that used by the work cited previously (the rationale and distinctions from previous work could go in the first paragraph of Results).

Upon first reading, I struggled a bit with aspects of Figure 2. Regarding panels 2c/g and 2d/h, it would help if the authors could convey when the task actually started, and whether this coincided with changes in luminance/overall illumination. Am I correct in presuming that the task started at around the 300s point? Also, regarding panels 2i/j/k, please specify in the results narrative that these are no longer single-session data, but instead summarize data across a larger sample of days. This information is currently only available deep in the Figure legend for Fig 2 (as an aside, showing data across multiple experimental session would seem to contradict the title to the Figure 2 legend, which emphasizes that the data is single-session data; this could also be corrected).

In the second paragraph of the discussion, the authors reference "two principal explanations" for their data. The first explanation follows in the next sentence, but I was not clear about the second explanation. Indeed the next few paragraphs would seem to be about qualifying the bottom-up explanation (which I presume is the first "principal explanation"), and the absence of increased CBV in the ACC. I could not find the second explanation; is it the top-down influence mentioned in the final paragraph? Regardless, please clarify these explanations in the Discussion.

Minor points

It is admittedly a stylistic point, but I felt there were aspects of abstract and introduction that were perhaps overstated. Notions like "underestimated yet pivotal" may be stretching thing a bit, and one could argue that the "pivotal" nature hasn't been established in this manuscript, since there was no true causal manipulation via stimulation or lesioning. Further, while I agree it is important to address the role of the SEF in pupil responses, I don't think many would be overly surprised that SEF activity relates to the pupil (given results from the FEF and ACC); others perhaps simply haven't measured it. Similar concerns about "pivot" relate to the usage of terms like "critically involved"; these strike me as terms that are just too strong to apply for the current dataset.

Please define CBV on first use in the abstract

3rd paragraph of Introduction "…suggesting valid qualities for ongoing…". Not sure "qualities" is the right word here. Do the authors mean that pupil dynamics can provide a "proxy for" or "reflection of" cortical processing?

Please consider adding references to: 1) The first paragraph of intro where it states that the dmPFC mediates arousal. 2) Second paragraph of intro; consider references for the SEF projections to the oculomotor nucleus, and references for how the ACC/SEF/FEF may modulate the olivary pretectal nucleus.

Reviewer #4: In an excellent paper, Claron and colleagues report results of a pupillometry and fUS study of macaca mulatta cortex activity while monkeys perform in a rewarded saccade / anti-saccade task. The authors show fairly convincingly that SEF activity correlates more strongly than do ACC and control regions with pupil dilation (otherwise linked with cognitive effort), and that both SEF signal and pupil diameter covary reliably with reward magnitude, cross-session dynamics, and response to anti- vs pro-saccade trials and errors - all hallmarks of cognitive effort.

On the basis of these correlations, the Authors argue that SEF activity tracks cognitive effort, yet additional tests might provide stronger evidence. Presumably, for example, if animals exert more effort on a given trial, they would be more accurate and faster, or (better yet), faster controlling for accuracy and vice versa. As such, it would be nice to show that when SEF activity were higher on a trial, the animals perform better.

Also, while greater SEF activity for higher incentive trials and for anti- vs pro-saccades are both consistent with the hypothesis that the SEF tracks cognitive effort, a more convincing test is whether the two dimensions interact in predicting SEF activity. An interaction is more convincing because, conceptually, these two dimensions are also correlated with arousal, independently, but high arousal is not the same thing as high effort. Effort, in contrast, is the conversion of motivation into action to overcome a challenge. Thus, as a result of effort, the effects of task difficulty will vary as a function of motivational state, and vice versa. IF SEF activity tracks effort, we should therefore expect that the effect of anti- vs pro-saccades on SEF activity should differ under high vs. low rewards (or, indeed that the effects of incentive magnitude on SEF activity should differ on anti- vs pro-saccade trials).

Also, it is unclear whether effort follows the same low-frequency trends (downward, cross-session slopes) in pupil dilation and SEF activity. If pupil dilation and SEF activity are trending downwards across a session and they are also tracking effort, does that mean that monkeys are performing progressively worse across a session? If not, that seems to complicate the main inference.

Minor comments

- In the results section, the Authors state that they "observed a slight disengagement of monkeys when the task is high-cognitive demanding … for a lower reward…" but they do not state their evidence of disengagement

- In Fig. 3, it is unclear why the shaded region between the anti- and pro-saccade conditions stops at 0,325 sec for the pupil diameter and at 4,0 sec for the CBV measurement?

- It wasn't clear why the Authors used a somewhat arbitrary threshold (the ratio of accuracy on anti- vs pro-saccades < 0.6) to retain trials for analyses. I would like to know the sensitivity of the results to this arbitrary threshold (would conclusions changed if they used values like 0.8 or 0.4, for example? It's also unclear why this threshold was used in the first place. Importantly, if the Authors only analyse sessions in which monkeys perform worse on anti-saccade trials by definition, then they are ensuring a positive correlation between errors and trial difficulty in a way that one would expect to covary with cognitive effort. That is, they are intentionally leaving out sessions where the presumably more difficult anti-saccade trials are performed equally well or better, and these sessions might provide and these sessions might be more revealing about if and how the SEF tracks cognitive effort. Finally, the Authors should stipulate the amount of data not retained for analyses according to their thresholding.

25 Jan 2022

Submitted filename: Review_Claron_et_al_pupille_24012021.docx

Click here for additional data file.

15 Mar 2022

Dear Dr Pouget,

Thank you for submitting your revised Research Article entitled "Short and long time scales covariations between pupil diameter and Supplementary Eye Field activity" for publication in PLOS Biology. I have now obtained advice from the original reviewers and have discussed their comments with the Academic Editor.

Based on the reviews (attached below), we will probably accept this manuscript for publication, provided you satisfactorily address the remaining points raised by Reviewers 3 and 4. Nevertheless, we do not think that further analyses are necessary and revisions to the text to address their concerns should be sufficient. Please also make sure to address the following data and other policy-related requests.

In addition, we would like to suggest a title that is more informative and appealing to a broad readership:

“Covariations between pupil diameter and Supplementary Eye Field activity suggest a role in cognitive effort implementation”

However, we would be happy to work with you on an alternative if you think our suggestion misrepresents your findings.

As you address these items, please take this last chance to review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the cover letter that accompanies your revised manuscript.

We expect to receive your revised manuscript within two weeks.

To submit your revision, please go to https://www.editorialmanager.com/pbiology/ and log in as an Author. Click the link labelled 'Submissions Needing Revision' to find your submission record. Your revised submission must include the following:

-  a cover letter that should detail your responses to any editorial requests, if applicable, and whether changes have been made to the reference list

-  a Response to Reviewers file that provides a detailed response to the reviewers' comments (if applicable)

-  a track-changes file indicating any changes that you have made to the manuscript.

NOTE: If Supporting Information files are included with your article, note that these are not copyedited and will be published as they are submitted. Please ensure that these files are legible and of high quality (at least 300 dpi) in an easily accessible file format. For this reason, please be aware that any references listed in an SI file will not be indexed. For more information, see our Supporting Information guidelines:

https://journals.plos.org/plosbiology/s/supporting-information

*Published Peer Review History*

Please note that you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out. Please see here for more details:

https://blogs.plos.org/plos/2019/05/plos-journals-now-open-for-published-peer-review/

*Press*

Should you, your institution's press office or the journal office choose to press release your paper, please ensure you have opted out of Early Article Posting on the submission form. We ask that you notify us as soon as possible if you or your institution is planning to press release the article.

*Protocols deposition*

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please do not hesitate to contact me should you have any questions.

Sincerely,

Ines

--

Ines Alvarez-Garcia, PhD

Senior Editor

PLOS Biology

ialvarez-garcia@plos.org

------------------------------------------------------------------------

ETHICS STATEMENT:

Thank you for including an ethics statement. Please include also the specific national or international regulations/guidelines to which your animal care and use protocol adhered. Note that institutional or accreditation organization guidelines (such as AAALAC) do not meet this requirement.

------------------------------------------------------------------------

DATA POLICY: IMPORTANT - PLEASE READ

You may be aware of the PLOS Data Policy, which requires that all data be made available without restriction: http://journals.plos.org/plosbiology/s/data-availability. For more information, please also see this editorial: http://dx.doi.org/10.1371/journal.pbio.1001797

Note that we do not require all raw data. Rather, we ask that all individual quantitative observations that underlie the data summarized in the figures and results of your paper be made available in one of the following forms:

1) Supplementary files (e.g., excel). Please ensure that all data files are uploaded as 'Supporting Information' and are invariably referred to (in the manuscript, figure legends, and the Description field when uploading your files) using the following format verbatim: S1 Data, S2 Data, etc. Multiple panels of a single or even several figures can be included as multiple sheets in one excel file that is saved using exactly the following convention: S1_Data.xlsx (using an underscore).

2) Deposition in a publicly available repository. Please also provide the accession code or a reviewer link so that we may view your data before publication.

Regardless of the method selected, please ensure that you provide the individual numerical values that underlie the summary data displayed in the following figure panels as they are essential for readers to assess your analysis and to reproduce it:

Fig 1B, C; Fig. 2A-K; Fig. 3; Fig. 4A-E; Fig. S1B and Fig. S2A-D.

NOTE: the numerical data provided should include all replicates AND the way in which the plotted mean and errors were derived (it should not present only the mean/average values).

Please also ensure that figure legends in your manuscript include information on WHERE THE UNDERLYING DATA CAN BE FOUND, and ensure your supplemental data file/s has a legend.

Please ensure that your Data Statement in the submission system accurately describes where your data can be found.

-------------------------------------------------------------------------

BLURB

Please also provide a blurb which (if accepted) will be included in our weekly and monthly Electronic Table of Contents, sent out to readers of PLOS Biology, and may be used to promote your article in social media. The blurb should be about 30-40 words long and is subject to editorial changes. It should, without exaggeration, entice people to read your manuscript. It should not be redundant with the title and should not contain acronyms or abbreviations. For examples, view our author guidelines: https://journals.plos.org/plosbiology/s/revising-your-manuscript#loc-blurb

------------------------------------------------------------------------

Reviewers' comments:

Rev. 1:

All my previous concerns have been adressed in great details by the authors, I am therefore happy to recommend the manuscript for publication.

Rev. 2:

I command the authors for their revision. I now think that the manuscript quality is highly improved and ready for publication. I also think that the change in title and abstract enhances the impact of this work. Congratulations to the authors !

Rev. 3:

I have read the authors' response, and well as their revised manuscript. I appreciate the level of attention to my comments, and the efforts exerted by the authors to revise their manuscript. From my perspective, things are largely resolved, and I only have a few minor points.

The abstract mentions the ACC without any context as to why this may be important. I'd suggest either deleting mention of the ACC in the abstract, or emphasizing how the SEF results contrast with negligible ACC signal changes. The ACC is also not defined in the abstract, nor upon first use in the introduction (line 55).

Line 106 to 107, "...in order to ambition in future…" sounds a bit strange. Consider "… so that future.."

Lines 114 to 116 indicates that all trials were used in the analyses, regardless of whether they were correctly or incorrectly performed. This seems to contradict their responses to one of my concerns (Reviewer 3, 3rd main point in original review). I think all that is required is some qualifying statement in lines 114-116 (e.g., a statement to the effect that all data was used, unless noted otherwise). As an example lines 196-197 indeed do specify that only correct trials were used for a particular analysis.

Line 154, "i.e." instead of "id est"?

I appreciate that the authors have rewritten much of the Discussion, and for the most part It reads well. The exception are the four paragraphs from lines 286-297, which read more like bullet points summarizing findings from four sets of studies. This portion of the Discussion could be improved with some edits to establish a cohesive narrative.

Rev. 4:

In their revision, Claron and colleagues address some concerns and also provide additional analyses to address questions about whether the SEF and pupil dynamics track cognitive effort or not. On re-review, I agree with their decision to shift the emphasis (at least in the title) away from discussing cognitive effort. While there appears to be at least a nice long-term covariation between pupil dilation and SEF activity, and while changes in reward levels and demand level (anti- vs pro-saccade) seem to have similar impacts on pupil and SEF dynamics, evidence that these two features map to cognitive effort is relatively weak. Specifically, for example, there are no interactions between reward and demand level, as you might expect if these systems track the cognitive effort involved. There is no close, trial-by-trial coupling between task performance and pupil or SEF dynamics. The Authors do find that slow timescale performance drops off in the same way that pupil dilation and SEF response do, over trials, but this effect could also be explained by a general fatigue effect, or accommodation to the task over time that is not specific to changes in effort. In none of their analyses do the Authors show that a trial-level increase in SEF (because of, say, a temporary increase in endogenously or exogenously driven motivation levels) predicts trial-level changes in pupil dilation - much less that such changes predict better trial-level performance…

A new concern has also arisen for me, in the Authors' response to a question about exclusion criteria, that also impacts on whether we can infer anything about effort from this dataset. Previously, the Authors had excluded data where ratio of accuracy on anti-vs pro-saccades was less than 0.6. When asked to consider all data, their response revealed a striking difference in the pattern of pupillary and SEF dynamics on anti- vs pro-saccades between the two monkeys in this study. Namely, while monkey S shows the expected pattern (pupil dilates more and performance is worse, on average, for anti-saccade trials, for most sessions), monkey G shows a very different pattern (pupil mostly dilates more, on average for pro-saccade trials, for most sessions, and average cross-session performance ratio is closer to 1.0 - indicating more similar performance between anti- and pro-saccade trials). In fact, excluding what look to be two outlier sessions, in terms of the ratio of dilation to anti- vs pro-saccade trials, monkey G appears to have, on average, a higher dilation to pro-saccade trials. What do the Authors make of the fact that, more often than not, monkey G's pupil dilates more for pro-saccade trials? In any case, monkey G's dilation patterns suggest that their dilation doesn't faithfully track effort because pro-saccade trials aren't harder that anti-saccade trials. On a related note, I would like to know what the Authors make of the huge difference in the ratio of pupil dilation on anti- vs pro-saccade trials for monkey G on the two sessions. What was so different about these sessions that could explain why the dilation ratio was so dramatically different than it was for all other sessions for monkey G?

This divergence between monkeys raises serious questions about what can be inferred about effort, because it is unclear - for monkey G at least - whether greater dilation reflects greater effort.

The complications with monkey G's data make me wonder how results would differ if the Authors analyzed monkey S's data only and asked whether trial-by-trial pupil dilation and SEF response to demand level or reward level predict better performance. If there is no strong coupling between trial-level data and performance, I recommend removing inferences about cognitive effort from the abstract. It is okay to speculate about it in the discussion, but it seems unwarranted to make claims about effort in the abstract when it is unclear how well the current experimental design is reliably sensitive to differences in effort. In fact, it seems that the design neither reveals reliable patterns of dilation / SEF activity across monkeys nor reliable patterns about effort from trial-to-trial.

Instead, I think the abstract, and conclusions should be focused on the much more compelling inference that long-term changes in pupil dilation map to long-term changes in SEF activity, and that two seem more strongly coupled than do pupil dilation and ACC on this timescale.

23 Mar 2022

Submitted filename: Claron_et_al_SEF_Pupille_resp_Reviewers2.docx

Click here for additional data file.

4 Apr 2022

Dear Dr Pouget,

Thank you for submitting your revised Research Article entitled "Covariations between pupil diameter and Supplementary Eye Field activity suggest a role in cognitive effort implementation" for publication in PLOS Biology.

I have checked the revision and there are still several data and other policy-related requests that remain to be addressed. They are all included below my signature, so please read them carefully and submit all the information required.

We expect to receive your revised manuscript within one week.

To submit your revision, please go to https://www.editorialmanager.com/pbiology/ and log in as an Author. Click the link labelled 'Submissions Needing Revision' to find your submission record. Your revised submission must include the following:

-  a cover letter that should detail your responses to any editorial requests, if applicable, and whether changes have been made to the reference list

-  a Response to Reviewers file that provides a detailed response to the reviewers' comments (if applicable)

-  a track-changes file indicating any changes that you have made to the manuscript.

NOTE: If Supporting Information files are included with your article, note that these are not copyedited and will be published as they are submitted. Please ensure that these files are legible and of high quality (at least 300 dpi) in an easily accessible file format. For this reason, please be aware that any references listed in an SI file will not be indexed. For more information, see our Supporting Information guidelines:

https://journals.plos.org/plosbiology/s/supporting-information

Please do not hesitate to contact me should you have any questions.

Sincerely,

Ines

Ines Alvarez-Garcia, PhD,

Senior Editor,

ialvarez-garcia@plos.org,

PLOS Biology

------------------------------------------------------------------------

ETHICS STATEMENT:

Thank you for including an ethics statement. Please include also the specific national or international regulations/guidelines to which your animal care and use protocol adhered. Note that institutional or accreditation organization guidelines (such as AAALAC) do not meet this requirement. For example, some of these studies adhere to the recommendations of the Weatherall report.

------------------------------------------------------------------------

DATA POLICY: IMPORTANT - PLEASE READ

You may be aware of the PLOS Data Policy, which requires that all data be made available without restriction: http://journals.plos.org/plosbiology/s/data-availability. For more information, please also see this editorial: http://dx.doi.org/10.1371/journal.pbio.1001797

Note that we do not require all raw data. Rather, we ask that all individual quantitative observations that underlie the data summarized in the figures and results of your paper be made available in one of the following forms:

1) Supplementary files (e.g., excel). Please ensure that all data files are uploaded as 'Supporting Information' and are invariably referred to (in the manuscript, figure legends, and the Description field when uploading your files) using the following format verbatim: S1 Data, S2 Data, etc. Multiple panels of a single or even several figures can be included as multiple sheets in one excel file that is saved using exactly the following convention: S1_Data.xlsx (using an underscore).

2) Deposition in a publicly available repository. Please also provide the accession code or a reviewer link so that we may view your data before publication.

Regardless of the method selected, please ensure that you provide the individual numerical values that underlie the summary data displayed in the following figure panels as they are essential for readers to assess your analysis and to reproduce it:

Fig 1B, C; Fig. 2A-K; Fig. 3; Fig. 4A-E; Fig. S1B and Fig. S2A-D.

NOTE: the numerical data provided should include all replicates AND the way in which the plotted mean and errors were derived (it should not present only the mean/average values).

Please also ensure that figure legends in your manuscript include information on WHERE THE UNDERLYING DATA CAN BE FOUND, and ensure your supplemental data file/s has a legend.

Please ensure that your Data Statement in the submission system accurately describes where your data can be found.

***In addition, please note that ALL data should be included in the manuscript or deposited in a publicly available database. Thus the data from the "SEF tracks cognitive effort" should be also made available before the manuscript can enter Production.

-------------------------------------------------------------------------

BLURB

Please also provide a blurb which (if accepted) will be included in our weekly and monthly Electronic Table of Contents, sent out to readers of PLOS Biology, and may be used to promote your article in social media. The blurb should be about 30-40 words long and is subject to editorial changes. It should, without exaggeration, entice people to read your manuscript. It should not be redundant with the title and should not contain acronyms or abbreviations. For examples, view our author guidelines: https://journals.plos.org/plosbiology/s/revising-your-manuscript#loc-blurb

5 Apr 2022

Submitted filename: Claron_et_al_SEF_Pupille_resp_Reviewers2.docx

Click here for additional data file.

29 Apr 2022

Dear Dr Pouget,

On behalf of my colleagues and the Academic Editor, Matthew Apps, I am happy to say that we can in principle accept your Research Article entitled "Covariations between pupil diameter and Supplementary Eye Field activity suggest a role in cognitive effort implementation" for publication in PLOS Biology, provided you address any remaining formatting and reporting issues. These will be detailed in an email that will follow this letter and that you will usually receive within 2-3 business days, during which time no action is required from you. Please note that we will not be able to formally accept your manuscript and schedule it for publication until you have completed any requested changes.

Please take a minute to log into Editorial Manager at http://www.editorialmanager.com/pbiology/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process.

PRESS

We frequently collaborate with press offices. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximise its impact. If the press office is planning to promote your findings, we would be grateful if they could coordinate with biologypress@plos.org. If you have previously opted in to the early version process, we ask that you notify us immediately of any press plans so that we may opt out on your behalf.

We also ask that you take this opportunity to read our Embargo Policy regarding the discussion, promotion and media coverage of work that is yet to be published by PLOS. As your manuscript is not yet published, it is bound by the conditions of our Embargo Policy. Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit http://www.plos.org/about/media-inquiries/embargo-policy/.

Many congratulations and thank you again for choosing PLOS Biology for publication and supporting Open Access publishing. We look forward to publishing your study.

Sincerely,

Ines

--

Ines Alvarez-Garcia, PhD

Senior Editor

PLOS Biology

ialvarez-garcia@plos.org