Chronometric Electrical Stimulation of Right Inferior Frontal Cortex Increases Motor Braking

Introduction

The right inferior frontal cortex (rIFC) is critical for rapidly stopping manual responses when a signal occurs (Aron et al., 2003; Chambers et al., 2006; Verbruggen et al., 2010; Zandbelt et al., 2013b), along with its associated functional and structurally connected network (Aron et al., 2007; Neubert et al., 2010; Forstmann et al., 2012). Although externally triggered stopping is occasionally required in everyday life, a more common requirement is to inhibit a motor tendency according to one's goal. This can be modeled by examining how people slow down when they might have to stop. Indeed, the rIFC is active when subjects anticipate that they might have to stop (Chikazoe et al., 2009; Jahfari et al., 2010; Jahfari et al., 2012; Swann et al., 2013; Zandbelt et al., 2013a), with the level of activation corresponding to the degree of motor caution (Jahfari et al., 2010) and the timing of activation corresponding tightly to the motor response (Swann et al., 2013). Although these findings are consistent with rIFC having a braking function (along with its network), causal evidence is required. To establish a potential causal role for the rIFC (and/or its connected network) in braking, we used direct-electrical stimulation (DES; Lüders et al., 1995; Borchers et al., 2012; Filevich et al., 2012; Desmurget et al., 2013). We implemented a novel computer-controlled, double-blind stimulation paradigm in which a single pair of DES pulses was time locked to impending movement and functionally localized to rIFC.

We studied four subjects with subdural electrodes implanted for electrocorticography (ECoG). First, in each subject, we localized an rIFC electrode with an “inhibitory-control” ECoG signature during a stop-signal task (SST; Fig. 1A). We screened all electrodes for typical stopping-related activity-patterns (i.e., an increase in beta-band activity; Swann et al., 2009) and/or an increase in gamma-band activity (Swann et al., 2012; 2013). All subjects showed one or both of these signatures in an rIFC electrode (Figs. 2, 3). This, along with an adjacent electrode (bipolar configuration), was designated as the stimulation site for the braking task, which consisted of alternating blocks of “Maybe Stop” (MS) or “No Stop” (NS) trials (Fig. 1B). Based on a recent study showing that rIFC is active around the motor response on MS trials (Swann et al., 2013), we delivered stimulation using a dynamic reaction time (RT) forecast in each condition. Stimulation trials (STIM) and no stimulation trials (SHAM) were delivered alternately.

We predicted that rIFC stimulation would slow down responses compared with sham. In addition, we investigated the difference in stimulation-induced slowing between the MS and NS conditions. If stimulation only induces slowing in the MS condition, this would imply that rIFC-induced braking is context sensitive (Swann et al., 2013; Chiu and Aron, 2013), whereas if stimulation induces slowing in both conditions, then rIFC exerts its braking influence regardless of context. In addition, to establish specificity to rIFC, we also performed stimulation of a control site in the temporal lobe in a subset of patients.

Materials and Methods

Results

Discussion

For each of four subjects, we localized an rIFC site having an electrophysiological signature of inhibitory control for outright stopping and then, in a subsequent session, we electrically stimulated that site during a braking task. In all subjects, rIFC stimulation slowed down responding, and more so in the braking (MS) than nonbraking (NS) context. Critically, in S3, in whom the control site was not connected to the “stopping network,” stopping-network, rIFC stimulation increased braking more than control-site stimulation (S2 showed the same numerical pattern). Stimulation-induced slowing for rIFC was highly reliable across and within subjects (Figs. 4, 6). This is the first demonstration of behavioral change induced by a single pair of prefrontal DES pulses time locked to ongoing behavior in humans. Moreover, this was done in double-blind fashion (neither the experimenter nor the patient was aware of whether stimulation was delivered on a given trial or not, or which site was being stimulated) using a functionally localized experimental site, a control site, and computer-controlled stimulation with millisecond precision.

Stimulation elongated RT in the braking context (MS) more than in the nonbraking context (NS). Given that the timing of stimulation was more than half a second after the Go stimulus and temporally much closer to the movement, this is not consistent with a disruption of the decision process (of which button to press); also, we note that stimulation did not affect accuracy (Table 2). It is also unlikely that rIFC stimulation merely affected motor initiation because, again, slowing was greater for MS than NS (when there was initiation in both conditions) and this remained true in four of six sessions even when taking into account the baseline (nonstimulation) slowing. There was also a striking correlation: stimulation induced greater slowing for those subjects who did not slow down much without stimulation. This is evidence against stimulation merely interfering with the movement itself and is more consistent with an augmentation of an endogenously activated brake provided that it is not already maximally engaged (i.e., we suppose that the rIFC-based braking system was maximally active at non-stimulation baseline in some patients, and DES could not affect it—a form of saturation). One might wonder whether rIFC stimulation disrupted the release of a brake rather than augmenting a brake. However, that account does not explain the fact that rIFC is more active for successful than failed outright stopping in this and another study before SSRT (Swann et al., 2009) and that the rIFC is critical for outright stopping (Aron et al., 2003; Chambers et al., 2006). Instead, we argue that rIFC stimulation enhanced a rIFC-mediated brake.

Our results are relevant to debates about rIFC's role in inhibitory control. By showing that artificially activating a node of the brain's stopping network slows down responding without an explicit stop signal, the results argue against the view that the rIFC is merely an attentional/salience detector (Hampshire et al., 2010; Sharp et al., 2010) because here it was causally important for a form of inhibitory control even in the absence of any signal. Our results are also inconsistent with the view that rIFC is merely an attentional/contextual monitor (Stuss and Alexander, 2007; Munakata et al., 2011; Chatham et al., 2012). Although stimulation of an attentional monitor would lead to a better or worse detection of a stop signal on Stop trials, here we are only examining RT on Go trials. We cannot see how altering an attentional monitor would affect Go trial RTs unless that monitor is tightly coupled with an inhibitory control system. Therefore, although this does not rule out the possibility that rIFC is involved in both attentional monitoring and motor inhibition, it refutes the “pure” attentional monitoring account. What also refutes this account is the observation that rIFC ECoG activity tracked the time of the response much better than the estimated time of the stop signal, which is consistent with a brake (Swann et al., 2013). Together, these results argue for the view that rIFC is tightly integrated within a network for inhibitory control of action tendencies, which can lead to braking, motor pauses, or indeed outright stopping (Aron et al., 2004; Chambers et al., 2009; Neubert et al., 2010; Levy and Wagner, 2011; Wiecki and Frank, 2013). Although rIFC is integrated with presupplementary motor area and the subthalamic nucleus (STN) for outright stopping, it is not yet clear how rIFC implements the putative braking function via a wider network; this could be via striatum, STN, or premotor cortex/M1.

Our results also show how DES can provide key information about the causal role of brain networks in human cognitive function. One other potential method to test a causal role is transcranial magnetic stimulation (TMS). There have been several studies using TMS with stopping paradigms (Chambers et al., 2006; Chambers et al., 2007; Verbruggen et al., 2010); however, these were offline stimulation, not event related, and they did not so much investigate braking as outright stopping. This is a crucial distinction because a causal implication of rIFC in braking implies that it can be recruited by endogenously triggered control (intentions) rather than merely by external stop signals. DES provides some notable methodological advances compared with TMS. To provide appropriate temporal resolution, TMS would have to be done concurrent with task performance (i.e., event-related). However, event-related TMS of rIFC at a level sufficient to affect behavior is very uncomfortable given the proximity of facial muscles. It is also difficult for such TMS studies to reach our current standard of fully double-blind experimental control. This is because facial sensation is generated by such TMS, making sham stimulation difficult. Further, the experimenter has to physically hold a coil at the stimulation location, which also makes control-site blinding difficult. Another difference between our form of DES and TMS is that the latter has a mass action effect that usually results in disruption rather than facilitation of behavior, whereas here the event-related DES appears to be facilitatory. We used a novel form of DES that overcomes the limitations of standard DES, which typically entails high-frequency (60 Hz) stimulation for durations >1 s and often lacks double-blinding and other experimental controls (Borchers et al., 2012; Filevich et al., 2012). In short, we have exploited the merits of DES over TMS in the current paradigm to provide a fully double-blinded, sham- and location-controlled demonstration of the rIFC's role in braking. However, we note that DES is invasive and used exclusively on populations with neurological conditions. We regard the current results as a starting point for further experiments, including using various forms of TMS in healthy subject populations.

We delivered stimulation at rIFC in each subject and, in some subjects, we compared it with control-site stimulation in the temporal lobe. We did not, however, compare rIFC stimulation with many other possible prefrontal and premotor stimulation sites because it is impractical for patients to participate in more stimulation conditions. However, several considerations do suggest the likely specificity to the rIFC. First, we functionally localized a rIFC region based on a stop-signal electrophysiological signature of inhibitory control (gamma or beta power increase). Such outright stopping signatures are mostly seen in the posterior rIFC/premotor region (Swann et al., 2009, 2012) and not widely throughout lateral prefrontal cortex (also see fMRI meta-analysis by Levy and Wagner, 2011). Second, our observation of a striking effect of stimulation at loci that elicit an inhibitory control signature is also consistent with a study in monkeys (Sasaki et al., 1989). In that study, Sasaki et al. performed a much wider stimulation mapping of lateral prefrontal cortex, showing that stimulation of loci with an electrophysiological signature of inhibitory control (and not other regions without such a signature) was most effective in delaying or canceling behavior. Regarding specificity, one might wonder if our stimulation had its effects via general current spread rather than a specific effect at rIFC. Although stimulation does produce evoked responses in adjacent regions of cortex (Borchers et al., 2012), it is unlikely that those evoked responses themselves are systematic and strong enough, across subjects, to produce the same amount of elongation of RT that we found here, especially in the MS condition. A recent review (Desmurget et al., 2013) made a compelling case that DES effects on behavior do not merely reflect an anarchic spread of current. A final consideration in favor of a specific effect at rIFC is that rIFC stimulation produced a significantly larger RT slowing for MS trials compared with NS trials in all subjects and sessions. Such MS trials are known to activate rIFC compared with NS trials and they do so in a rather locally specific manner (including rIFC and middle frontal gyrus) in both ECoG and fMRI (Swann et al., 2012, 2013), with activity peaking around the time we stimulated in the current experiment (Swann et al., 2013). Therefore, the behavioral effects of stimulation seen here are likely specific to rIFC itself and would probably not occur with stimulation of other prefrontal regions, but this is a topic for future investigation.

In summary, using a novel application of DES with double-blind control and precise task-based stimulation, we provide causal evidence for a rIFC-mediated braking function. This argues strongly for classic views that lateral prefrontal cortex is important for implementing inhibitory action control (Iversen and Mishkin, 1970; Sasaki et al., 1989; Dias et al., 1996; Fuster, 1997; Knight et al., 1999) and against the view that rIFC is merely an attentional detector/monitor (Stuss and Alexander, 2007; Munakata et al., 2011; Chatham et al., 2012). The findings also extend this inhibitory control function beyond externally driven action cancellation to forms of self-control that are internally generated according to an individual's goals (Brass and Haggard, 2007; Aron, 2011). This may help to explain why this brain system has been implicated in various disorders of impulse control that are not simply characterized by deficits of phasic stimulus-driven inhibitory control, but which might instead involve internally generated control, done partially or completely, and perhaps repeatedly over a tonic interval in relation to urges (Robbins, 2007; Chambers et al., 2009; Marsh et al., 2009; Berman et al., 2012; Whelan et al., 2012). The results also provide key insights into the parameters for electrical stimulation in human prefrontal cortex that influence cognitive control (Pesaran et al., 2006).