Attentional spatial cueing of the stop-signal affects the ability to suppress behavioural responses

This research aimed to explore the influence of spatial attention cueing on inhibitory control. Our findings indicate that spatial attention cueing increased the probability of response inhibition in the valid condition compared to the invalid condition for Stop Signal Delays ranging from 100 to 250 milliseconds. Notably, the performance remained consistent across all conditions for the maximum Stop Signal Delay (450ms). The effect of spatial cueing was further corroborated when assessing the SSRT, where the duration required to inhibit the response was observed to be shorter in the valid condition. A plausible interpretation is that the stop signal is detected more swiftly and accurately when attentional resources are already focused on its expected location (Macaluso and Doricchi 2013). In contrast, the occurrence of the stop signal in the uncued location requires an automatic reorienting of attention, elongating the inhibitory process and possibly delaying its detection. The timing of the effect’s deployment, present as early as 100ms from the Go signal and disappearing after 250ms, suggests that this effect is mostly exogenous (Mulckhuyse and Theeuwes 2010). For example, in classical studies, the use of a peripheral cue (Posner and Cohen 1984) resulted in an advantage for the cued condition that ended before 200ms, followed by the inhibition of return (Klein 2000). However, similar advantages have been observed when employing central cueing (Posner et al. 1980), and these advantages can be modulated by the predictiveness of the cues (Tipples 2002; Langdon and Smith 2005; Giessing et al. 2006; Vossel et al. 2006; Bartolomeo et al. 2007). Other factors that could have affected this effect are the circular placeholders employed. Indeed, a study reported that the presence of placeholders can facilitate cueing response if target stimuli appear shortly after the cue (100 and 200ms), while for longer target onset times, an opposite effect was reported, possibly due to the inhibition of return (Taylor et al. 2015; Klein 2000). Furthermore, the dimension of the cued area by the circles and the related attentional focus can affect processing efficiency: reducing the area is associated with a reduction in RTs (Turatto et al. 2000; Ronconi et al. 2014; Castiello and Umiltà 1992). Although we did not observe an inhibition phenomenon in our case, the presence of circles as placeholders, spatial cueing in motion, and the higher predictability of valid versus invalid stop signals could all have contributed to the effect we observed.

Previous literature has discussed how the detection phase of the stop signal can be influenced. For instance, the perceptual attributes of the stop signal can impact inhibitory control: the salience of the stop signal can modulate the SSRT in stop-signal tasks with both auditory and visual signals (van der Schoot et al. 2005; Morein-Zamir and Kingstone 2006; Camalier et al. 2007; van Gaal et al. 2009; Montanari et al. 2017). Moreover, earlier studies have demonstrated that attentional factors can affect the capacity to suppress behavioural responses: the presence of distractors negatively impacts inhibitory control (Verbruggen et al. 2014b), as does the disappearance of fixation spots, although the effect can vary depending on the motor system involved (Mirabella et al. 2009; Stevenson et al. 2009). In a recent study, participants were asked to execute a combination of an endogenous Posner task with a Stop Signal Task. In this study the stop signal was presented in the same location as the go signal (Hilt and Cardellicchio 2020). Both reaction times and SSRT were shorter in valid than invalid condition, thus demonstrating an effect of attentional allocation on the inhibitory process. A key distinction from that study and ours is that those authors assessed how reorienting for the go signal affected inhibition, thereby aligning their work with tasks that investigate the functional interaction between GO and STOP processes. Indeed in their study the cueing was primarily related to go signal, that also required a different finger response depending on the position. Thus, to be performed adequately, it required to re-orient towards the go signal and then respond to the Stop signal. It is thus possible that in that case the re-orienting required for the go signal elongates the SSRT. A series of studies have shown that the specific demands of a task can modulate a concurrent STOP process. For example, the simultaneous performance of a Stop task and Flanker or a Stroop task can negatively affect the ability to suppress a motor response (Verbruggen et al. 2004). However, this is not always the case: indeed, the modulation of the Stimulus Response Compatibility (van den Wildenberg and van der Molen 2004) or of the level of difficulty of decision making in the go task (Middlebrooks et al. 2020) and in task-switching (Verbruggen et al. 2005) do not affect stopping performance. An important difference between the Hilt and Cardellicchio (2020) and our experiment is that, in our study, the nature of valid or invalid was exclusively related to the stop signal, and that we employed fixed Stop Signal Delays, thus demonstrating that the cueing advantage tends to decrease as the Stop Signal Delay increases. Despite these differences in experimental design, Hilt and Cardellicchio (2020) found that when comparing invalid with valid trials, both RTs and SSRT were delayed in invalid trials by about 50ms, a value similar to what we observed. One could speculate that the re-orienting required for the Go signals was also affecting the inhibitory process. The reduction of the STOP process’s efficacy we observed is further supported by the longer wrong reaction times observed in the invalid conditions. This data can be readily explained by a longer STOP process that can only interrupt longer response time compared to the valid condition. Our data, however, warrants further exploration. Our research aligns with a series of studies aimed at exploring the various factors that can influence inhibitory control. Currently, it is known that inhibitory control, as measured by the Stop Signal Task, can be considered as comprising different components or stages and, in turn, being influenced by other processes (Boucher et al. 2007; Verbruggen et al. 2014a; Logan et al. 2015). Despite this, many studies using the Stop Signal Task tend to treat SSRT as the estimation of a single process. However, recently, some studies have shown, even with if with modeling methods, that deficient inhibitory capacity may be associated not so much with a generic alteration of the inhibitory process but, for example, with difficulty in detecting the stop signal and thus in triggering the necessary STOP process for inhibition (Matzke et al. 2017; Choo et al. 2022). This type of approach is particularly important for studies investigating specific neurocognitive deficits in clinical populations, where changes in the ability to inhibit can be related either to attentional or executive processes (Lampe et al. 2007; Alderson et al. 2008; Senderecka et al. 2012; Salum et al. 2014). Indeed, an inappropriate response could be due to increased distractibility or a failure to implement an adequate inhibition process (Weigard et al. 2019; Anning et al. 2023). In this context, the employment of tasks that can more precisely affect stages of cognitive processing can be helpful to disentangle diverse hypotheses or to better characterize cognitive profiles associated with specific disorders. This type of investigation would be particularly important, as often simple processing features such as processing speed or phenomena like attentional facilitation are involved in neurocognitive tasks but neglected in the definition of the functional architectures supporting performance (Salum et al. 2014). Furthermore, the possibility to influence the STOP process by means of attention can help to investigate at a high temporal definition level the neuronal dynamics supporting movement inhibition, thus helping to describe the sequence of processing that brings from the stop signal to the implementation of behavioural control, further contributing to the mechanistic understanding of neurological or neuropsychiatric pathologies (Mueller et al. 2017; Pani et al. 2022).

In this study we investigated the interplay between motor inhibition and attentional orienting. The relationship between attention and inhibition is relevant because both functions might be supported by partially overlapping brain networks, both at cortical as well sub-cortical level (Wessel and Anderson 2024; Alves et al. 2022). More specifically, motor inhibition is typically associated to a fronto-basal ganglia network, spanning different brain regions (right Inferior Frontal Gyrus or rIFG, supplementary premotor area, dorsal premotor and motor cortices, orbitofrontal cortex and Sub-thalamic nucleus (Aron and Poldrack 2006; Bryden and Roesch 2015; Diesburg and Wessel 2021; Pani et al. 2022), where the rIFG seems to play a pivotal role. The same area is implicated in attentional tasks that require reorienting to unexpected or uncued, but behaviourally relevant, stimuli, operating as part of a ventral fronto-parietal network (Bressler et al. 2008; Corbetta and Shulman 2002). In the context of the motor inhibition literature its role would be to rapidly “pause“ the ongoing planned action (Aron et al. 2014) upon the presentation of a stop signal or an unexpected event (Diesburg and Wessel 2021); in the context of the “attentional ” literature its role would be to interrupt the ongoing orienting of attention and supporting the reorienting towards the new targets, working as a “circuit breaker” (Doricchi et al. 2010; Corbetta et al. 2009). More recently, some theories have been proposed for which, inspired by the common involvement of the right inferior frontal cortex, as detected by fMRI or EEG activity, or by TMS investigations (Corbetta and Shulman 2002; Corbetta et al. 2009;Verbruggen et al. 2010; Swann et al. 2009; Hampshire et al. 2010; Lenartowicz et al. 2011) the interruption of attentional focus followed by attentional reorienting associated to any type of salient (i.e. infrequent, unexpected) event, would rely on the same “inhibitory” process at play to exert motor control (Soh and Wessel 2021; Tatz et al. 2021). As such inhibition would be at the basis of attentional re-orientating. An alternative view, the “stimulus detection account” (Leiva et al. 2015; Verbruggen et al. 2014a) has been proposed that the response to behavioural relevant unfrequent or unexpected events would require first a re-orientation of attention to detect the infrequent stimulus, and then an inhibitory response if required. Thus, while the ‘inhibitory’ theory explains the attentional shift away from the current locus towards the salient event by means of an inhibition of the current attentional representation that would also have an effect at the behavioral level, the ‘stimulus detection account’ considers the shift of attention as the ‘premise’ for properly detecting the stop signal. Our data, support the “stimulus detection account” view. Indeed, according to the ‘inhibitory’ account, the invalid stop signal, being infrequent and behaviorally relevant, should have been at least as efficient as the valid stop signal in inhibiting, as the inhibitory process would be activated first. Contrary to this prediction, we observed an elongation of SSRT in the invalid condition, which we can explain with the reorienting process necessary before implementing response inhibition. Thus, our study suggests that depending on the context, motor inhibition and attentional re-orienting can be involved at different levels in relation to the task at hand. Another aspect to consider is the role of the rIFG: the fact that this region (and possibly other brain regions) is active in different processes or tasks does not necessarily means that the function at play is always the same. This general concept has been already demonstrated by behavioral neurophysiology studies in monkeys. Indeed, in frontal eye fields some cells show neuronal modulation during saccades execution while others, colocalized with the first ones, are active in covert shifts of attention (Petersen and Posner 2012; Schafer and Moore 2007; Thompson et al. 2005). This observation demonstrates that finer-grained dissociations between functions can be detected within the same brain region, making it challenging to establish a clear connection between a specific brain region and possibly a single associated function. This consideration is further strengthened by the mixed-selectivity shown by neurons in prefrontal cortex (Rigotti et al. 2013). We recognize that in this study there are limitations. To increase the potential efficacy of the attentional cueing, we combined exogenous cueing (the movement of the bar) with predictiveness, i.e., valid trials occurred with a higher frequency (around 70%). Thus, the frequency of validity probably contributed, along with the more specific spatial cueing, to driving the effect. Further studies are needed to establish whether the effect we observed can be obtained with an equal proportion of valid/invalid or higher proportions of invalid vs. valid stop trials. A second limitation is also posed by the motion onset effect; we do not know whether a static cue could yield a similar advantage for the cued position. Therefore, it would be necessary to systematically investigate whether the effect can be evoked even with just a static exogenous cue, as done in previous papers with signal detection (Posner 1980, Posner et al. 1984). Currently, we can only say that in our case, the two characteristics are combined, leading to an advantage up to 250ms from the presentation of the go signal. Furthermore, although the difference in inhibition we observe has sizable effect, it must be confirmed in more studies.