Abstract

Numerous studies have established a role for the ACC in cognitive control. Current theories are at odds as to whether ACC itself directly engages or alternatively recruits other frontal cortical areas that implement control. The antisaccade task, in which subjects are required to make a saccade to the location opposite a suddenly appearing visual stimulus, is a simple oculomotor paradigm that has been used extensively to investigate flexible oculomotor control. Here, we tested a causal role of the dorsal ACC in cognitive control by applying electrical microstimulation during a preparatory period while monkeys performed alternating blocks of pro- and antisaccade trials. Microstimulation induced significant changes in saccadic RTs (SRTs) in both tasks. On prosaccade trials, SRTs were increased for saccades contralateral to and decreased for saccades ipsilateral to the stimulated hemisphere. In contrast, SRTs were decreased for both ipsi- and contralaterally directed antisaccades. These data show that microstimulation administered during response preparation facilitated the performance of antisaccades and are suggestive of a direct role of ACC in the implementation of cognitive control.

INTRODUCTION

The ability to use contextual information to select the appropriate response from multiple competing alternatives when faced with identical external events is a fundamental aspect of cognitive control (Miller & Cohen, 2001). For example, a ringing telephone demands to be answered if in one's own office, but the same response to the identical stimulus would be quite inappropriate when visiting the office of a colleague. The implementation of such control has been linked extensively with the function of frontal cortical areas, including the ACC (Carter & van Veen, 2007; Paus, 2001; Duncan & Owen, 2000).

In the oculomotor domain, development and dysfunction of flexible control have been investigated extensively using the antisaccade task (Everling & Fischer, 1998; Hallett, 1978). In this task, a visual stimulus is briefly presented in the peripheral visual field, and subjects are required to generate a saccadic eye movement toward the opposite visual field. Correct performance of this simple oculomotor paradigm necessitates the deployment of cognitive control, as presentation of a single identical peripheral visual stimulus sets in opposition two mutually exclusive responses: the automatic, task-irrelevant tendency to generate a prosaccade toward the stimulus and the voluntary task-relevant antisaccade in the opposite direction.

Evidence from functional imaging studies in humans and single neuron recordings in nonhuman primates have revealed that performance of this task is dependent upon a distributed network of cortical and subcortical areas. fMRI studies have consistently shown greater activation of many cortical and subcortical areas including the FEFs, supplementary eye fields (SEF), dorsolateral PFC (DLPFC), ACC, posterior parietal cortex, pulvinar, and striatum on antisaccade trials relative to prosaccade trials (Brown, Goltz, Vilis, Ford, & Everling, 2006; Ford, Goltz, Brown, & Everling, 2005; Curtis & D'Esposito, 2003). Single neuron recordings in behaving primates have investigated the response properties of neurons in the FEF (Everling & Munoz, 2000), SEF (Amador, Schlag-Rey, & Schlag, 2003; Schlag-Rey, Amador, Sanchez, & Schlag, 1997), DLPFC (Johnston & Everling, 2006; Everling & Desouza, 2005; Funahashi, Chafee, & Goldman-Rakic, 1993), lateral intraparietal area (LIP; Zhang & Barash, 2000; Gottlieb & Goldberg, 1999), BG (Ford & Everling, 2009; Watanabe & Munoz, 2009; Yoshida & Tanaka, 2009), and midbrain superior colliculus (SC; Everling, Dorris, Klein, & Munoz, 1999) in this task. Although these studies have led to a mechanistic model of the processes of response suppression and voluntary saccade generation in the antisaccade task (Munoz & Everling, 2004), the specific role of ACC in the engagement of the neural circuitry underlying these aspects of cognitive control remains controversial.

Two main hypotheses have been proposed with respect to the role of ACC in the implementation of cognitive control (Mansouri, Tanaka, & Buckley, 2009). According to the “conflict-monitoring hypothesis,” ACC monitors or detects conflicting coactivation of information processing streams (Carter & van Veen, 2007). In such accounts, ACC acts to recruit other frontal regions, such as PFC, which are in turn responsible for the engagement of control mechanisms (Kerns et al., 2004; Carter et al., 2000). In contrast, according to the “regulatory hypothesis,” ACC actually is part of the circuitry that biases processing of task-relevant information in those situations that require engagement of control mechanisms (Brown & Braver, 2005; Holroyd & Coles, 2002).

Although much evidence in support of conflict monitoring exists within the human literature, neural correlates of conflict-monitoring have not been observed in either the spiking activity of single neurons (Nakamura, Roesch, & Olson, 2005; Ito, Stuphorn, Brown, & Schall, 2003) or local field potentials (Emeric et al., 2008) in the monkey (for a review, see Cole, Yeung, Freiwald, & Botvinick, 2009). Recently, we investigated the role of ACC in cognitive control by recording the activity of single ACC neurons while monkeys performed alternating blocks of pro- and antisaccades. We observed activity differences during the preparatory period immediately before stimulus presentation that mirrored the control demands of the task, a finding more consistent with regulatory than conflict monitoring theories of ACC function (Johnston, Levin, Koval, & Everling, 2007). Here, we sought to extend this finding by using a causal neurophysiological method to test whether ACC directly implements control in the antisaccade task. We artificially activated ACC via electrical microstimulation during response preparation in a task in which monkeys performed alternating blocks of pro- and antisaccades. We predicted that microstimulation-induced enhancement of preparatory ACC signals would facilitate performance of the more cognitively demanding antisaccade trials, as reflected by decreases in RT and improved performance, while leaving performance on prosaccade trials unaffected.

METHODS

Subjects

Three male rhesus monkeys (Macaca mulatta) weighing 7.7, 11.3, and 13.7 kg were subjects in the experiment. All methods were in accordance with the guidelines of the Canadian Council on Animal Care policy on the use of laboratory animals and an ethics protocol approved by the Animal Use Subcommittee of the University of Western Ontario Council on Animal Care.

Details of the surgical procedures involved in animal preparation have been described previously (Desouza & Everling, 2004). Briefly, each monkey underwent a surgical procedure in preparation for chronic electrophysiological experiments in which an acrylic implant with a recording chamber and a head post were attached to the skull using ceramic screws (Thomas Recording, Inc., Giessen, Germany). The recording chamber was placed over a 19-mm diameter craniotomy situated above the lateral PFC of the right hemisphere at an angle that permitted access to the ACC. A preformed eye coil was implanted behind the conjunctiva of one eye (Judge, Richmond, & Chu, 1980).

Behavioral Task

The monkeys performed an experimental task in which they had to alternate between blocks of pro- and antisaccade trials. On prosaccade trials, monkeys were required to look to a suddenly appearing visual stimulus, whereas on antisaccade trials, they were required to suppress this response and instead look to the opposite location. In this task, animals received no explicit instruction as to which behavior would be rewarded but were required to determine the task rule on the basis of trial and error. We have used this task in previous studies (Johnston et al., 2007; Johnston & Everling, 2006; Everling & Desouza, 2005). Each trial began with the presentation of a small white fixation point at the center of the stimulus display. Stimuli were presented on a 21-in. CRT monitor at a viewing distance of 42 cm from the animals (Figure 1A). The monkeys were required to fixate within a 0.5° × 0.5° window for a variable duration of 1100–1400 msec. Following this, a visual stimulus (0.15°) was presented pseudorandomly, with equal probability either 8° to the left or right of fixation. The animals had to generate a saccade within 500 msec and received a liquid reward if the saccade endpoint fell within an 8° × 6° window centered on the stimulus location (prosaccade trials) or the mirror location (antisaccade trials). Upon completion of 30 correct trials, the task rule switched, and the monkeys had to switch their response to continue receiving reward. On average, monkeys performed 10 task switches per session (5 blocks each of pro- and antisaccades). Eye movements were recorded at 1000 Hz using the magnetic search coil technique (Fuchs & Robinson, 1966; David Northmore Inc., Newark, DE). Eye positions and trial events were stored using the Plexon MAP system (Plexon Inc., Dallas, TX). Stimulus presentation, administration of the behavioral paradigm, control of the microstimulator, and reward delivery were controlled by the CORTEX experimental control system (NIMH, Bethesda, MD).

Figure 1. 

Behavioral paradigm. (A) Visual stimuli sequence for switch paradigm. The paradigm consisted of alternating blocks of 30 correct prosaccades and 30 correct antisaccades. Length of fixation was varied (1100–1400 msec). Fixation point (FP) and peripheral stimuli (S) remained unchanged throughout the paradigm, as the task rule switched. Animals acquired the appropriate task rule by trial-and-error based on reward delivery or omission. (B) Microstimulation protocol. The timing of microstimulation administration (Stim) targeted the end of the preparatory period, before a saccadic response was generated (Eh—horizontal eye position), and was delivered during 30% of the trials (50 μA, 100 Hz, 0.3-msec biphasic pulses, 300-msec train duration). SRT was defined as the time interval from peripheral stimulus onset to saccade onset.

Figure 1. 

Behavioral paradigm. (A) Visual stimuli sequence for switch paradigm. The paradigm consisted of alternating blocks of 30 correct prosaccades and 30 correct antisaccades. Length of fixation was varied (1100–1400 msec). Fixation point (FP) and peripheral stimuli (S) remained unchanged throughout the paradigm, as the task rule switched. Animals acquired the appropriate task rule by trial-and-error based on reward delivery or omission. (B) Microstimulation protocol. The timing of microstimulation administration (Stim) targeted the end of the preparatory period, before a saccadic response was generated (Eh—horizontal eye position), and was delivered during 30% of the trials (50 μA, 100 Hz, 0.3-msec biphasic pulses, 300-msec train duration). SRT was defined as the time interval from peripheral stimulus onset to saccade onset.

Microstimulation Protocol

The locations of the implanted recording chambers were visualized in situ by MRI. High-resolution, T2-weighted MR images were acquired in a 4-T MR-scanner. Plastic grids with 1-mm spacing were inserted into the recording chambers, and the chambers were filled with an iodine solution. This allowed visualization of the grid locations relative to the cortical surface in the MR images, which allowed us to localize ACC (Figure 2). Locations for electrode placement were chosen using these MR images and previous recording locations from two of the animals (monkeys R and W; Johnston et al., 2007).

Figure 2. 

MRI reconstruction of stimulation sites. Anatomical MR images from each animal. Leftmost images are of transverse slices (orientation is illustrated using the following abbreviations: medial (M), lateral (L), anterior (A), and posterior (P)), whereas succeeding images are of coronal sections. Red dots on transverse sections indicate stimulation sites. Recording chambers containing plastic grids with 1-mm spacing and filled with iodine solution appear at the top of the coronal images. ps = principal sulcus; as = arcuate sulcus; cs = cingulate sulcus.

Figure 2. 

MRI reconstruction of stimulation sites. Anatomical MR images from each animal. Leftmost images are of transverse slices (orientation is illustrated using the following abbreviations: medial (M), lateral (L), anterior (A), and posterior (P)), whereas succeeding images are of coronal sections. Red dots on transverse sections indicate stimulation sites. Recording chambers containing plastic grids with 1-mm spacing and filled with iodine solution appear at the top of the coronal images. ps = principal sulcus; as = arcuate sulcus; cs = cingulate sulcus.

In each session, a single dura-puncturing tungsten microelectrode (UEWLGDSMNN1E, FHC Inst., Bowdoinham, Maine) was driven within the recording chamber using either a computer-controlled microelectrode drive (NAN; Plexon Inc.) or a manually controlled, hydraulic microdrive (Narishige, Tokyo, Japan). Extracellular neural activity was monitored to verify that the electrode tip was in the gray matter. Each experimental session commenced once a suitable site within ACC was found. To be deemed suitable, a site was required to lie within the dorsal bank of the cingulate sulcus, as determined by noting the correspondence between gray and white matter boundaries in the MRI scans, depth of the recording electrode below the cortical surface, and extracellular multiunit activity. In some sessions, data were obtained from more than one stimulation site. In these cases, once data collection was complete at the initial site, the electrode was lowered further by 500 μm, and data were collected from this second site.

Within each session, microstimulation pulse trains (300 msec, 100 Hz, 0.3-msec biphasic pulses, 50 μA) were delivered on 30% of trials, with those remaining serving as controls. The onset of stimulation was timed to coincide with the onset of preparatory activity in ACC in this task (Johnston et al., 2007). The 300-msec train encompassed the final 200 msec of the fixation period and continued into the succeeding 100 msec (Figure 1B). We reasoned that this 300-msec stimulation window was entirely within the preparatory period and did not entail any processing of the visual stimulus on the basis of the finding that visual response latency in macaque ACC is at least 100 msec (Pouget, Emeric, Stuphorn, Reis, & Schall, 2005). Microstimulation trains were delivered using a Grass S88 microstimulator with a PSIU6 photoelectric stimulus isolation unit (Astro-Med Inc., West Warwick, RI). Microstimulation using these parameters did not evoke saccades at any sites.

Data Analysis

Off-line data analyses were conducted using custom-written programs in MATLAB (Mathworks, Natick, MA). Saccade onset was defined as the time when the horizontal eye velocity exceeded 30°/s, and the time at which this parameter fell below this velocity was considered to be the endpoint. Trials were inspected visually to verify that the marking of saccade onset and offset was accurate. Trials characterized by saccadic RTs (SRTs) of less than 80 msec (taken as anticipatory in nature), greater than 500 msec (taken as no response), or broken fixation were excluded. In all analyses, ipsilateral and contralateral refer to saccade direction with respect to the hemisphere to which microstimulation was applied. In total, there were four task conditions in this experiment: contralateral prosaccades, ipsilateral prosaccades, contralateral antisaccades, and ipsilateral antisaccades. At each site, for each of the four task conditions, mean SRTs for trials on which microstimulation was delivered and mean SRTs for control trials were computed. We also examined the effects of microstimulation on error rate. For prosaccades, errors were considered as trials on which saccades were directed toward the mirror location rather than toward the peripheral stimulus (i.e., an antisaccade was performed). For antisaccades, trials in which saccades were directed toward the location of the peripheral stimulus rather than the mirror location (i.e., a prosaccade was performed) were considered errors. Error rate was computed as number of direction errors divided by the total number of performed trials (correct trials and error trials) and multiplied by 100.

To evaluate the effects of ACC microstimulation, we computed a microstimulation effect index (MEI) for each of the four experimental conditions for each microstimulation site separately. For SRTs, the MEI was defined as the contrast ratio between microstimulation and control trials within each condition and computed as follows:
formula
MEI for error rates (ER) was defined similarly. Values of this index range from −1 to 1, with positive values indicating greater SRTs or error rates for microstimulation than control trials and negative values indicating the converse. For example, SRTs of 220 msec in the microstimulation condition and 200 msec in the control condition would yield an MEI of .0476. Statistical comparisons were carried out using a Wilcoxon signed rank test for zero median. Significance of all comparisons was assessed at p < .05.

We also tested the effects of microstimulation on additional saccade parameters such as peak velocity, duration, and amplitude. Following the conclusion of these experiments, we discovered that horizontal eye position signals often saturated for rightward saccades in Monkey A. We therefore analyzed saccade parameters for leftward saccades only in this animal. This did not affect our ability to measure SRTs or error rates for rightward saccades in this animal.

RESULTS

Electrical microstimulation was administered at a total of 103 ACC sites (20 in Monkey R, 53 in Monkey W, and 30 in Monkey A).

ACC Microstimulation Affects SRTs

On the basis of our previous finding of differences in preparatory activity in ACC neurons between pro- and antisaccade trials (Johnston et al., 2007), we reasoned that microstimulation during the preparatory period might facilitate the more cognitively demanding antisaccades with little to no detrimental effects on prosaccades. Figure 3A depicts MEIs for contralateral and ipsilateral pro- and antisaccades. Mean SRTs for the three animals are given in Table 1. Considering all 103 stimulation sites, microstimulation resulted in increased SRTs for contralateral prosaccades (MEI = .0205, p < .0001). Of the three animals, two showed this effect (Monkey W, MEI = .0256, p < .0001; Monkey R, MEI = .0563, p < .01), whereas no effect was observed in the third (Monkey A, MEI = −.0018, p = .68). For ipsilateral prosaccades, microstimulation induced an overall decrease in SRTs (MEI = −.0211, p < .0001). This effect was present in two animals (Monkey W, MEI = −.035, p < .00001; Monkey A, MEI = −.0119, p < .05), whereas Monkey R showed the opposite effect (MEI = .089, p < .001).

Figure 3. 

Distributions of MEIs. (A) Distributions of MEIs computed from SRTs for each animal for each experimental condition as described in Methods. Top—prosaccade trials; bottom—antisaccade trials. Left panels—eye movements contralateral to stimulated hemisphere; right panels—ipsilateral to stimulated hemisphere. (B) Distributions of MEIs computed from error rates for each experimental condition. Conditions as displayed in panel A.

Figure 3. 

Distributions of MEIs. (A) Distributions of MEIs computed from SRTs for each animal for each experimental condition as described in Methods. Top—prosaccade trials; bottom—antisaccade trials. Left panels—eye movements contralateral to stimulated hemisphere; right panels—ipsilateral to stimulated hemisphere. (B) Distributions of MEIs computed from error rates for each experimental condition. Conditions as displayed in panel A.

Table 1. 

SRTs (C = Contralateral; I = Ipsilateral)


Monkey
Direction
Microstimulation
Control
Mean (SEM)
Mean (SEM)
Prosaccades (msec) 145 (2)* 138 (1) 
135 (1)* 144 (1) 
223 (8)** 201 (9) 
252 (9)* 211 (9) 
191 (4) 190 (3) 
202 (4) 207 (5) 
Antisaccades (msec) 126 (2)* 146 (2) 
134 (2)* 160 (2) 
226 (6)*** 242 (5) 
275 (4)** 265 (5) 
178 (3)*** 185 (2) 
177 (3)* 189 (4) 

Monkey
Direction
Microstimulation
Control
Mean (SEM)
Mean (SEM)
Prosaccades (msec) 145 (2)* 138 (1) 
135 (1)* 144 (1) 
223 (8)** 201 (9) 
252 (9)* 211 (9) 
191 (4) 190 (3) 
202 (4) 207 (5) 
Antisaccades (msec) 126 (2)* 146 (2) 
134 (2)* 160 (2) 
226 (6)*** 242 (5) 
275 (4)** 265 (5) 
178 (3)*** 185 (2) 
177 (3)* 189 (4) 

*p < .001.

**p < .05.

***p < .01.

For antisaccades, microstimulation resulted in an overall decrease in SRTs for both contralateral (MEI = −.0415, p < .000001) and ipsilateral (MEI = −.0554, p < .000001) directions. This effect was observed consistently across all animals for contralateral antisaccades (Monkey W, MEI = −.0853, p < .000001; Monkey R, MEI = −.0369, p < .005; Monkey A, MEI = −.0202, p < .005). For ipsilateral antisaccades, this effect was observed for two animals (Monkey W, MEI = −.0853, p < .000001; Monkey A, MEI = −.0312, p < .0001). Monkey R showed significantly greater SRTs for ipsilateral antisaccades on stimulation trials (MEI = .02, p < .01). The overall pattern of these data indicates that microstimulation increased contralateral prosaccade SRTs, decreased SRTs of ipsilateral prosaccades, and decreased antisaccade SRTs bilaterally.

ACC Microstimulation Does Not Consistently Affect Error Rates

Mean error rates are listed in Table 2. The only significant effect on error rates, considering all 103 stimulation sites together, was observed for contralateral prosaccades (MEI = −.0224, p < .01; Figure 3B). These errors took the form of incorrect antisaccades on these prosaccade trials. This effect was observed for one animal only (Monkey W, MEI = −.0490, p < .000001) and not in Monkey R (MEI = −.0293, p = .27) and Monkey A (MEI = .0128, p = .07). These findings indicate that microstimulation did not consistently affect error rates in the alternating pro- and antisaccade paradigm.

Table 2. 

Error Rates (C = Contralateral; I = Ipsilateral)


Monkey
Direction
Microstimulation
Control
Mean (SEM)
Mean (SEM)
Prosaccades (% of errors) 20.3 (1.5)* 12.3 (1.3) 
17.2 (1.3) 15.2 (1.2) 
19.3 (3.1) 16.2 (3.0) 
30.8 (4.3) 23.9 (4.5) 
14.5 (1.3) 14.5 (2.1) 
13.2 (1.9) 15.6 (1.6) 
Antisaccades (% of errors) 9.6 (0.9) 8.4 (0.6) 
9.0 (0.8) 8.1 (0.7) 
8.9 (2.5) 13.4 (1.8) 
16.6 (1.9) 13.7 (2.2) 
9.7 (0.8) 8.2 (1.0) 
12.9 (1.3) 11.2 (1.1) 

Monkey
Direction
Microstimulation
Control
Mean (SEM)
Mean (SEM)
Prosaccades (% of errors) 20.3 (1.5)* 12.3 (1.3) 
17.2 (1.3) 15.2 (1.2) 
19.3 (3.1) 16.2 (3.0) 
30.8 (4.3) 23.9 (4.5) 
14.5 (1.3) 14.5 (2.1) 
13.2 (1.9) 15.6 (1.6) 
Antisaccades (% of errors) 9.6 (0.9) 8.4 (0.6) 
9.0 (0.8) 8.1 (0.7) 
8.9 (2.5) 13.4 (1.8) 
16.6 (1.9) 13.7 (2.2) 
9.7 (0.8) 8.2 (1.0) 
12.9 (1.3) 11.2 (1.1) 

*p < .001.

ACC Microstimulation Does Not Affect Saccade Metrics

We found no differences between microstimulation and control trials for saccadic duration, peak velocity, or horizontal amplitude in any of the conditions (Supplementary Tables 1–3).

DISCUSSION

ACC has been proposed to play a critical role in cognitive control, but it is unclear whether this area is directly responsible for engaging control mechanisms or recruiting other cortical areas that carry out this function. To test a causal involvement of ACC in control implementation, we artificially activated ACC using intracortical microstimulation while monkeys performed alternating blocks of pro- and antisaccades. A consistent finding for all three subjects was a decrease in SRTs of contralateral antisaccades on microstimulation trials. In addition, two of the three subjects showed a significant increase in contralateral prosaccade SRTs. ACC microstimulation had no effects on saccade duration, peak velocity, and amplitude. Taken together, these findings suggest that ACC plays a causal facilitatory role in the performance of antisaccades.

A central tenet of conflict-monitoring accounts of ACC function is that ACC acts to recruit other areas, such as the PFC, which engage control in response to increased task demands (Carter et al., 2000; Botvinick, Nystrom, Fissell, Carter, & Cohen, 1999). The most convincing evidence marshaled in support of this is the correlated changes in behavior and fMRI signal intensity observed in human subjects on trials following those that engender conflict. Enhanced ACC activation is observed on trials in which response conflict is present and subsequent trials show enhanced PFC activation and shorter RTs, consistent with the implementation of control adjustments (Kerns et al., 2004). Thus, ACC is thought to simply report changes in the need for control on the current trial that are implemented by other areas on subsequent trials. Here, we found immediate microstimulation-induced changes in RT on those trials in which stimulation was applied. We assert that this result is consistent with a direct role of ACC in the implementation of control functions, embodied, in this case, in the form of oculomotor control. Our findings are thus more consistent with regulatory than conflict-monitoring accounts of ACC function.

In addition to our current results, several studies in nonhuman primates using various measures of neural activity have failed to find evidence in support of conflict monitoring (Emeric et al., 2008; Nakamura et al., 2005; Ito et al., 2003). Whether this is a result of differences in training, experimental tasks, measures of neural activity, effector systems used, or neural architecture between humans and nonhuman primates remains open to debate (Cole et al., 2009). It is intriguing to note, however, that our finding of antisaccade facilitation as a result of artificial enhancement of ACC activity dovetails nicely with the reduction in antisaccade performance observed in human patients with ACC lesions. Gaymard et al. (1998) studied two patients with right ACC lesions and found a significant increase in SRTs for left- and rightward antisaccades compared with control subjects. These patients also showed a substantial bilateral increase in direction errors in the antisaccade task. In the present study, we found no reductions of error rates for antisaccades on microstimulation trials. Contrary to human patients, all three of our animal subjects received extensive training and consequently made very few errors. Thus, any performance enhancement as a result of microstimulation may have been obscured by a ceiling affect.

A clear difference between our microstimulation data and these patient data concerns the role of ACC on prosaccade trials. Gaymard et al. (1998) observed significantly greater RTs for leftward prosaccades (i.e., contralateral to the lesion) in an overlap condition, with no differences in a gap condition. The authors argued that prosaccades are more voluntary in the overlap condition compared with the gap condition and that the main role of ACC lies in the generation of voluntary saccades. In the present study, the effects of microstimulation on prosaccade trials were quite variable. Two of three animals (Monkeys W and R) showed a significant increase in contralateral prosaccade SRTs, whereas the third (Monkey A) showed no difference in SRTs between microstimulation and control trials. For ipsilateral prosaccade trials, Monkey W showed an increase in SRTs on stimulation trials, whereas Monkey R showed a decrease and Monkey A showed no effects. These differences might be related to the nature of our task. The human subjects in the Gaymard et al. study performed pro- and antisaccade trials in separate blocks with clear task instructions at the beginning of each block. Our monkey subjects alternated between pro- and antisaccade blocks with no explicit instruction and acquired the current task rule by trial and error. The absence of a task cue is likely responsible for the unusually high error rates on prosaccade trials in our study (12–24% on control trials).

There are several potential mechanisms by which ACC may carry out an oculomotor control function. ACC shares reciprocal connections with other cortical areas involved in eye movement control such as the FEF (Wang, Matsuzaka, Shima, & Tanji, 2004; Bates & Goldman-Rakic, 1993) and the SEF (Huerta & Kaas, 1990) as well as the PFC (Bates & Goldman-Rakic, 1993). In addition, there is evidence that ACC projects to the midbrain SC (Field, Johnston, Gati, Menon, & Everling, 2008; Leichnetz, Spencer, Hardy, & Astruc, 1981), a critical oculomotor structure (Sparks & Hartwich-Young, 1989), although further studies are needed to confirm these projections. Single neurons in each of these brain regions have been shown to exhibit set-related activity on antisaccade trials that is predictive of task performance (for a review, see Johnston & Everling, 2008), and all are therefore candidates through which ACC might exert control over saccadic eye movements.

Saccade neurons of the FEF show attenuated preparatory, visual, and saccade-related responses on antisaccade trials relative to prosaccade whereas neurons with fixation-related activity are more active on antisaccade than prosaccade trials (Munoz & Everling, 2004; Everling & Munoz, 2000). Given the aforementioned connectivity of this area with ACC, it is plausible that ACC signals could directly modulate the activity of FEF saccade and fixation neurons to facilitate antisaccade performance. Because cortical outputs are exclusively excitatory (Creutzfeldt, 1993), there are two physiologically plausible mechanisms by which an enhanced ACC signal could result in the pattern of activity observed in FEF fixation and saccade neurons: the first being via a direct excitatory enhancement of fixation neuron activity and the second via direct synapses of ACC efferents on inhibitory interneurons. In both cases, ACC microstimulation would act to suppress automatic prosaccades and facilitate performance on antisaccade trials. On prosaccade trials, such an effect would result in a reduction of activity in saccade neurons and could account for the microstimulation-induced increases in contralateral SRTs we observed. In either case, ACC microstimulation would result in a modulation of the activity of saccade neurons and exert an immediate and direct effect on task performance.

In addition to the FEF, the activity of saccade neurons in the SEF has also been shown to differentially reflect preparatory set for pro- and antisaccades. In this region, saccade-related neurons discharge at a higher rate during the preparatory period on correct antisaccade trials, whereas neural activity is attenuated on prosaccade trials (Amador et al., 2003; Schlag-Rey et al., 1997). ACC stimulation may act to enhance this increased antisaccade-related activity in the SEF, which could in turn modulate activity in the FEF, SC, and oculomotor areas of the brainstem, to which it sends direct projections (Shook, Schlag-Rey, & Schlag, 1990). Modulation of SEF activity by intracortical microstimulation has been shown to exert context-specific control over saccadic eye movements in other oculomotor tasks requiring suppression of automatic saccades (Stuphorn & Schall, 2006).

ACC may also act via the BG to exert control functions, either through projections to the caudate nucleus of the striatum (Calzavara, Mailly, & Haber, 2007; Selemon & Goldman-Rakic, 1985) or through the so-called “hyperdirect” corticosubthalamic pathway (Nambu, Tokuno, & Takada, 2002). The caudate sends a direct inhibitory projection to the substantia nigra pars reticulata (SNr), which tonically inhibits the SC (for a review, see Hikosaka, Takikawa, & Kawagoe, 2000) and is thus thought to perform an oculomotor “gating” function. Direct projections from the cortex to the subthalamic nucleus (STN) have been implicated in the suppression of automatic behaviors (Hazy, Frank, & O'Reilly, 2007; Aron & Poldrack, 2006; Yasoshima et al., 2005). Data from human studies have provided evidence for either a direct or a functional connection between ACC and STN (Boecker, Jankowski, Ditter, & Scheef, 2008; Sestini et al., 2002). In monkeys, direct connections between these areas have yet to be identified; however, the STN is known to receive direct input from a broad region of frontal cortex including PFC, SEF, and pre-SMA (Inase, Tokuno, Nambu, Akazawa, & Takada, 1999; Monakow, Akert, & Kunzle, 1978).

Recently, on the basis of their observation of “switch” type neurons in the pre-SMA and STN during an oculomotor switching task, Isoda and Hikosaka (2007, 2008) proposed that the hyperdirect pathway may represent a neural substrate for behavioral switching. They proposed parallel no-go and go pathways. The no-go pathway links the cortex, STN, SNr, and SC and is thought to be involved in the suppression of responses. Excitatory connections between the cortex, STN, and SNr would lead to increased SNr output and thus enhanced tonic inhibition of the SC, inhibiting eye movements. A microstimulation-induced enhancement of this proposed pathway could account for the results we observed here. On antisaccade trials, activation of this pathway would reduce the responses of SC saccade neurons to the visual stimulus and thus suppress automatic saccades, thereby facilitating antisaccade performance. Activation of the same pathway could account for the increases in SRT we observed on prosaccade trials. Interestingly, projections between the SNr and the SC have been shown to be bilateral (Beckstead, Edwards, & Frankfurter, 1981; Jayaraman, Batton, & Carpenter, 1977) but asymmetrical, such that the ipsilateral SNr-SC projection, which would inhibit contralateral saccades, is stronger than the contralateral projection, which would inhibit ipsilateral saccades. This pattern of projections could account for our observation of consistent increases in SRT for contralateral prosaccades and the inconsistency of effects between animals for ipsilateral prosaccades. Such mechanisms are of course speculative and await confirmation in the form of studies investigating the responses of STN and SNr neurons in the antisaccade task.

Acknowledgments

This work was supported by the Canadian Institutes of Health Research.

Reprint requests should be sent to Dr. Stefan Everling, The Centre for Brain and Mind, Robarts Research Institute, 100 Perth Drive, London, Ontario, Canada N6A 5K8, or via e-mail: severlin@uwo.ca.

REFERENCES

REFERENCES
Amador
,
N.
,
Schlag-Rey
,
M.
, &
Schlag
,
J.
(
2003
).
Primate antisaccade II. Supplementary eye field neuronal activity predicts correct performance.
Journal of Neurophysiology
,
91
,
1672
1689
.
Aron
,
A. R.
, &
Poldrack
,
R. A.
(
2006
).
Cortical and subcortical contributions to Stop signal response inhibition: Role of the subthalamic nucleus.
Journal of Neuroscience
,
26
,
2424
2433
.
Bates
,
J. F.
, &
Goldman-Rakic
,
P. S.
(
1993
).
Prefrontal connections of medial motor areas in the rhesus monkey.
Journal of Comparative Neurology
,
336
,
211
.
Beckstead
,
R. M.
,
Edwards
,
S. B.
, &
Frankfurter
,
A.
(
1981
).
A comparison of the intranigral distribution of nigrotectal neurons labeled with horseradish peroxidase in the monkey, cat, and rat.
Journal of Neuroscience
,
1
,
121
125
.
Boecker
,
H.
,
Jankowski
,
J.
,
Ditter
,
P.
, &
Scheef
,
L.
(
2008
).
A role of the basal ganglia and midbrain nuclei for initiation of motor sequences.
Neuroimage
,
39
,
1356
1369
.
Botvinick
,
M.
,
Nystrom
,
L. E.
,
Fissell
,
K.
,
Carter
,
C. S.
, &
Cohen
,
J. D.
(
1999
).
Conflict monitoring versus selection-for-action in anterior cingulate cortex.
Nature
,
402
,
179
181
.
Brown
,
J. W.
, &
Braver
,
T. S.
(
2005
).
Learned predictions of error likelihood in the anterior cingulate cortex.
Science
,
307
,
1118
1121
.
Brown
,
M. R.
,
Goltz
,
H. C.
,
Vilis
,
T.
,
Ford
,
K. A.
, &
Everling
,
S.
(
2006
).
Inhibition and generation of saccades: Rapid event-related fMRI of prosaccades, antisaccades, and nogo trials.
Neuroimage
,
33
,
644
659
.
Calzavara
,
R.
,
Mailly
,
P.
, &
Haber
,
S. N.
(
2007
).
Relationship between the corticostriatal terminals from areas 9 and 46, and those from area 8A, dorsal and rostral premotor cortex and area 24c: An anatomical substrate for cognition to action.
European Journal of Neuroscience
,
26
,
2005
2024
.
Carter
,
C. S.
,
Macdonald
,
A. M.
,
Botvinick
,
M.
,
Ross
,
L. L.
,
Stenger
,
V. A.
,
Noll
,
D.
,
et al
(
2000
).
Parsing executive processes: Strategic vs. evaluative functions of the anterior cingulate cortex.
Proceedings of the National Academy of Sciences, U.S.A.
,
97
,
1944
1948
.
Carter
,
C. S.
, &
van Veen
,
V.
(
2007
).
Anterior cingulate cortex and conflict detection: An update of theory and data.
Cognitive, Affective & Behavioral Neuroscience
,
7
,
367
379
.
Cole
,
M. W.
,
Yeung
,
N.
,
Freiwald
,
W. A.
, &
Botvinick
,
M.
(
2009
).
Cingulate cortex: Diverging data from humans and monkeys.
Trends in Neurosciences
,
32
,
566
574
.
Creutzfeldt
,
O. D.
(
1993
).
Cortex cerebri.
Goettingen
:
Springer
.
Curtis
,
C. E.
, &
D'Esposito
,
M.
(
2003
).
Success and failure suppressing reflexive behavior.
Journal of Cognitive Neuroscience
,
15
,
409
418
.
Desouza
,
J. F.
, &
Everling
,
S.
(
2004
).
Focused attention modulates visual responses in the primate prefrontal cortex.
Journal of Neurophysiology
,
91
,
855
.
Duncan
,
J.
, &
Owen
,
A. M.
(
2000
).
Common regions of the human frontal lobe recruited by diverse cognitive demands.
Trends in Neurosciences
,
23
,
475
.
Emeric
,
E. E.
,
Brown
,
J. W.
,
Leslie
,
M.
,
Pouget
,
P.
,
Stuphorn
,
V.
, &
Schall
,
J. D.
(
2008
).
Performance monitoring local field potentials in the medial frontal cortex of primates: Anterior cingulate cortex.
Journal of Neurophysiology
,
99
,
759
772
.
Everling
,
S.
, &
Desouza
,
J. F.
(
2005
).
Rule-dependent activity for prosaccades and antisaccades in the primate prefrontal cortex.
Journal of Cognitive Neuroscience
,
17
,
1483
1496
.
Everling
,
S.
,
Dorris
,
M. C.
,
Klein
,
R. M.
, &
Munoz
,
D. P.
(
1999
).
Role of primate superior colliculus in preparation and execution of antisaccades and pro-saccades.
Journal of Neuroscience
,
19
,
2740
2754
.
Everling
,
S.
, &
Fischer
,
B.
(
1998
).
The antisaccade: A review of basic research and clinical studies.
Neuropsychologia
,
36
,
885
899
.
Everling
,
S.
, &
Munoz
,
D. P.
(
2000
).
Neuronal correlates for preparatory set associated with pro-saccades and anti-saccades in the primate frontal eye field.
Journal of Neuroscience
,
20
,
387
400
.
Field
,
C. B.
,
Johnston
,
K.
,
Gati
,
J. S.
,
Menon
,
R. S.
, &
Everling
,
S.
(
2008
).
Connectivity of the primate superior colliculus mapped by concurrent microstimulation and event-related FMRI.
PLoS ONE
,
3
,
e3928
.
Ford
,
K. A.
, &
Everling
,
S.
(
2009
).
Neural activity in primate caudate nucleus associated with pro- and anti-saccades.
Journal of Neurophysiology
,
102
,
2334
.
Ford
,
K. A.
,
Goltz
,
H. C.
,
Brown
,
M. R.
, &
Everling
,
S.
(
2005
).
Neural processes associated with antisaccade task performance investigated with event-related fMRI.
Journal of Neurophysiology
,
94
,
429
440
.
Fuchs
,
A. F.
, &
Robinson
,
D. A.
(
1966
).
A method for measuring horizontal and vertical eye movement chronically in the monkey.
Journal of Applied Physiology
,
21
,
1068
.
Funahashi
,
S.
,
Chafee
,
M. V.
, &
Goldman-Rakic
,
P. S.
(
1993
).
Prefrontal neuronal activity in rhesus monkeys performing a delayed anti-saccade task.
Nature
,
365
,
753
.
Gaymard
,
B.
,
Rivaud
,
S.
,
Cassarini
,
J. F.
,
Dubard
,
T.
,
Rancurel
,
G.
,
Agid
,
Y.
,
et al
(
1998
).
Effects of anterior cingulate cortex lesions on ocular saccades in humans.
Experimental Brain Research
,
120
,
173
183
.
Gottlieb
,
J.
, &
Goldberg
,
M. E.
(
1999
).
Activity of neurons in the lateral intraparietal area of the monkey during an antisaccade task.
Nature Neuroscience
,
2
,
906
912
.
Hallett
,
P. E.
(
1978
).
Primary and secondary saccades to goals defined by instructions.
Vision Research
,
18
,
1279
1296
.
Hazy
,
T. E.
,
Frank
,
M. J.
, &
O'Reilly
,
R. C.
(
2007
).
Towards an executive without a homunculus: Computational models of the prefrontal cortex/basal ganglia system.
Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences
,
362
,
1601
1613
.
Hikosaka
,
O.
,
Takikawa
,
Y.
, &
Kawagoe
,
R.
(
2000
).
Role of the basal ganglia in the control of purposive saccadic eye movements.
Physiological Reviews
,
80
,
953
.
Holroyd
,
C. B.
, &
Coles
,
M. G.
(
2002
).
The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity.
Psychological Review
,
109
,
679
709
.
Huerta
,
M. F.
, &
Kaas
,
J. H.
(
1990
).
Supplementary eye field as defined by intracortical microstimulation: Connections in macaques.
Journal of Comparative Neurology
,
293
,
299
330
.
Inase
,
M.
,
Tokuno
,
H.
,
Nambu
,
A.
,
Akazawa
,
T.
, &
Takada
,
M.
(
1999
).
Corticostriatal and corticosubthalamic input zones from the presupplementary motor area in the macaque monkey: Comparison with the input zones from the supplementary motor area.
Brain Research
,
833
,
191
201
.
Isoda
,
M.
, &
Hikosaka
,
O.
(
2007
).
Switching from automatic to controlled action by monkey medial frontal cortex.
Nature Neuroscience
,
10
,
240
248
.
Isoda
,
M.
, &
Hikosaka
,
O.
(
2008
).
Role for subthalamic nucleus neurons in switching from automatic to controlled eye movement.
Journal of Neuroscience
,
28
,
7209
7218
.
Ito
,
S.
,
Stuphorn
,
V.
,
Brown
,
J. W.
, &
Schall
,
J. D.
(
2003
).
Performance monitoring by the anterior cingulate cortex during saccade countermanding.
Science
,
302
,
120
122
.
Jayaraman
,
A.
,
Batton
,
R. R.
, III, &
Carpenter
,
M. B.
(
1977
).
Nigrotectal projections in the monkey: An autoradiographic study.
Brain Research
,
135
,
147
152
.
Johnston
,
K.
, &
Everling
,
S.
(
2006
).
Monkey dorsolateral prefrontal cortex sends task-selective signals directly to the superior colliculus.
Journal of Neuroscience
,
26
,
12471
12478
.
Johnston
,
K.
, &
Everling
,
S.
(
2008
).
Neurophysiology and neuroanatomy of reflexive and voluntary saccades in nonhuman primates.
Brain and Cognition
,
68
,
271
283
.
Johnston
,
K.
,
Levin
,
H. M.
,
Koval
,
M. J.
, &
Everling
,
S.
(
2007
).
Top-down control-signal dynamics in anterior cingulate and prefrontal cortex neurons following task switching.
Neuron
,
53
,
453
462
.
Judge
,
S. J.
,
Richmond
,
B. J.
, &
Chu
,
F. C.
(
1980
).
Implantation of magnetic search coils for measurement of eye position: An improved method.
Vision Research
,
20
,
535
.
Kerns
,
J. G.
,
Cohen
,
J. D.
,
MacDonald
,
A. W.
, III,
Cho
,
R. Y.
,
Stenger
,
V. A.
, &
Carter
,
C. S.
(
2004
).
Anterior cingulate conflict monitoring and adjustments in control.
Science
,
303
,
1023
1026
.
Leichnetz
,
G. R.
,
Spencer
,
R. F.
,
Hardy
,
S. G.
, &
Astruc
,
J.
(
1981
).
The prefrontal corticotectal projection in the monkey; an anterograde and retrograde horseradish peroxidase study.
Neuroscience
,
6
,
1023
.
Mansouri
,
F. A.
,
Tanaka
,
K.
, &
Buckley
,
M. J.
(
2009
).
Conflict-induced behavioural adjustment: A clue to the executive functions of the prefrontal cortex.
Nature Reviews Neuroscience
,
10
,
141
152
.
Miller
,
E. K.
, &
Cohen
,
J. D.
(
2001
).
An integrative theory of prefrontal cortex function.
Annual Review of Neuroscience
,
24
,
167
.
Monakow
,
K. H.
,
Akert
,
K.
, &
Kunzle
,
H.
(
1978
).
Projections of the precentral motor cortex and other cortical areas of the frontal lobe to the subthalamic nucleus in the monkey.
Experimental Brain Research
,
33
,
395
403
.
Munoz
,
D. P.
, &
Everling
,
S.
(
2004
).
Look away: The anti-saccade task and the voluntary control of eye movement.
Nature Reviews Neuroscience
,
5
,
218
228
.
Nakamura
,
K.
,
Roesch
,
M. R.
, &
Olson
,
C. R.
(
2005
).
Neuronal activity in macaque SEF and ACC during performance of tasks involving conflict.
Journal of Neurophysiology
,
93
,
884
908
.
Nambu
,
A.
,
Tokuno
,
H.
, &
Takada
,
M.
(
2002
).
Functional significance of the cortico-subthalamo-pallidal “hyperdirect” pathway.
Neuroscience Research
,
43
,
111
117
.
Paus
,
T.
(
2001
).
Primate anterior cingulate cortex: Where motor control, drive and cognition interface.
Nature Reviews Neuroscience
,
2
,
417
424
.
Pouget
,
P.
,
Emeric
,
E. E.
,
Stuphorn
,
V.
,
Reis
,
K.
, &
Schall
,
J. D.
(
2005
).
Chronometry of visual responses in frontal eye field, supplementary eye field, and anterior cingulate cortex.
Journal of Neurophysiology
,
94
,
2086
2092
.
Schlag-Rey
,
M.
,
Amador
,
N.
,
Sanchez
,
H.
, &
Schlag
,
J.
(
1997
).
Antisaccade performance predicted by neuronal activity in the supplementary eye field.
Nature
,
390
,
398
401
.
Selemon
,
L. D.
, &
Goldman-Rakic
,
P. S.
(
1985
).
Longitudinal topography and interdigitation of corticostriatal projections in the rhesus monkey.
Journal of Neuroscience
,
5
,
776
.
Sestini
,
S.
,
Scotto di Luzio
,
A.
,
Ammannati
,
F.
,
De Cristofaro
,
M. T.
,
Passeri
,
A.
,
Martini
,
S.
,
et al
(
2002
).
Changes in regional cerebral blood flow caused by deep-brain stimulation of the subthalamic nucleus in Parkinson's disease.
Journal of Nuclear Medicine
,
43
,
725
732
.
Shook
,
B. L.
,
Schlag-Rey
,
M.
, &
Schlag
,
J.
(
1990
).
Primate supplementary eye field: I. Comparative aspects of mesencephalic and pontine connections.
Journal of Comparative Neurology
,
301
,
618
.
Sparks
,
D. L.
, &
Hartwich-Young
,
R.
(
1989
).
The deep layers of the superior colliculus.
Reviews of Oculomotor Research
,
3
,
213
255
.
Stuphorn
,
V.
, &
Schall
,
J. D.
(
2006
).
Executive control of countermanding saccades by the supplementary eye field.
Nature Neuroscience
,
9
,
925
931
.
Wang
,
Y.
,
Matsuzaka
,
Y.
,
Shima
,
K.
, &
Tanji
,
J.
(
2004
).
Cingulate cortical cells projecting to monkey frontal eye field and primary motor cortex.
NeuroReport
,
15
,
1559
1563
.
Watanabe
,
M.
, &
Munoz
,
D. P.
(
2009
).
Neural correlates of conflict resolution between automatic and volitional actions by basal ganglia [Electronic version].
European Journal of Neuroscience
,
30
,
2165
2176
.
Yasoshima
,
Y.
,
Kai
,
N.
,
Yoshida
,
S.
,
Shiosaka
,
S.
,
Koyama
,
Y.
,
Kayama
,
Y.
,
et al
(
2005
).
Subthalamic neurons coordinate basal ganglia function through differential neural pathways.
Journal of Neuroscience
,
25
,
7743
7753
.
Yoshida
,
A.
, &
Tanaka
,
M.
(
2009
).
Enhanced modulation of neuronal activity during antisaccades in the primate globus pallidus.
Cerebral Cortex
,
19
,
206
217
.
Zhang
,
M.
, &
Barash
,
S.
(
2000
).
Neuronal switching of sensorimotor transformations for antisaccades.
Nature
,
408
,
971
975
.

Author notes

*

Present address: Centre for Neuroscience Studies, Queen's University, Rm. 234 Botterell Hall, Kingston, Ontario, Canada K7L 3N6.