Our protocols combining virtual 3D environments with inhibitory responses and neuromodulation showed promise for exploring the role of SMA in spatial impulsivity, offering both (i) novel insights on how to impact on impulsivity in naturalistic spatial settings and (ii) a possible relationship of SMA in spatial impulsive contexts. First, our study replicates a previous finding 32 showing that close stimuli generate impulsive behaviours. Second, there was a significant main effect of SMA stimulation, where actions were slower with real stimulation than with sham. While exploratory, we consider it interesting to discuss the potential relationship between real versus sham SMA neuromodulation and spatial impulsivity. A decrease in commission errors to close stimuli appears in real stimulation, as shown by significant decrements of commission errors on real condition (mean = 6.25%) compared to sham condition (mean = 9.04%). While these results should be interpreted with caution due to its exploratory nature, we believe they constitute promising findings to SMA functioning on selecting the right moment to withhold actions when distance is relevant in the computation.
Previous literature shows an enhanced ability in humans to detect and respond to close stimuli compared to distant ones 32. Yet, this biological constrain does not imply that we are able to inhibit an approach-avoidance balance to an immediate object in a biologically adaptive manner. Indeed, objects presented close generate shorter latencies, demonstrating the influence and priority of nearby spatial locations 7,32,43. Facing more challenging tasks or accumulating ambiguous evidence might lead to prolonged decision times, potentially favouring adaptive but also slower decisions. Hence, as humans we have been sufficiently trained to interact with far-distant spaces, whereby behavioural inhibition plays a major role 2. We reveal increments in response thresholds after inhibitory SMA neuromodulation that could explain its computational mechanisms mediating spatial impulsivity.
Close proximity to stimuli of interest may trigger automatic and reflexive responses, while stimuli further away require more deliberate and effortful processing 44. In line with this view, previous accounts suggest a prominent role of attentional sources that bias the space location guidance with impulsive behaviour 45,46. When objects are placed close in personal proximity, they may capture our attention more easily, which may lead faster and more impulsive responses. This can be due to the fact that objects that are closer to us occupy a larger portion of our visual field 47 and therefore require less cognitive effort. However, this reduced effort in attention may come at the cost of accuracy, as we report in experiment 1. Hence, the biological and natural response of delaying in order to succeed comes at a cost for close stimuli, possibly meaning that such close by condition makes our decision more vulnerable to fail. On the other hand, stimuli that are placed further away require greater effort to allocate our attention 48, which may provide time for deliberation and result in more accurate responses. Therefore, we might hypothesise that adaptive control constrained by a given spatial context could be influenced by distance (both for 2D and 3D stimuli).
In our study, using a linear integration model of speed-accuracy, SMA stimulation made participants more conservative showing slower responses. This was achieved by regulating decision trade-offs mediated by response thresholds. In a similar vein, the study by Pineda-Pardo (2019) found a decrease in errors but also an increase in RTs during a 4-choice RT task. Indeed, a parallel finding to our diffusion parameters was the increased decision thresholds modulated during real SMA stimulation. Consequently, the distance dimension included in our design may be exerting an influence on both the linear increase of LISAS (which includes both RTs and accuracy plus deviation parameters) and decision thresholds, making the results not directly comparable to those of earlier studies. However, a general effect on slower RTs may require a joint view of the specific process tested in our experiments. The increment seen after real stimulation on LISAS holds jointly for error, variability (SD) and speed. Thus, the general slower effects on the sample for closer stimuli may be confounded, at least, by either (i) parallel cognitive changes in improving accuracy following real stimulation (such as raising decision thresholds) or (ii) due to the neuromodulation protocol itself (30 minutes of withholding the real/sham tSMS helmet may contribute to a prolonged RTs in the sample, maybe linked to fatigue or attentional lapses). Yet, is difficult to disentangle them as the significant improvement on error rates during real tSMS can influence the increment in LISAS as well. A possible neurobiological explanation links our protocol to previous studies where tSMS influenced selection of actions in a choice reaction time (CRT) task when applied to the motor association cortex 49. In their study, tSMS over bilateral motor cortex increased reaction times. Similarly, tSMS applied to the SMA appears to modulate impulsive behaviours by improving anticipation of movements, by reducing errors and prolonging RTs 27. It is possible to suggest that we have modulated classical SMA functions. Being part of the cognitive control system 10, the SMA is needed when inhibition prepotent actions 11,12,15,17,50, movement anticipation 13,14 and explorative decisions 51. Hence, the underlying SMA cognitive operations shall be considered in our findings, where a neuromodulation perturbation modified some of its related functions when introduced distance as factor, possibly by modulating the choice quality, rather than its movement vigour and speed. In conclusion, the application of tSMS seems to influence impulsive performance, where distance implicates a qualitatively different choice relevant to SMA and its subcortical functional connectivity that may have been influenced by our stimulation.
Our results raise a first approach to the idea that the SMA could serve as a potential hub to integrate perceptual spatial information with inhibitory cortical commands. Neuromodulation of the SMA with tSMS could provide a neural marker to modify spatial impulsivity and probably part of a cortical system that constructs the best possible action. However, our tSMS protocol lacks a control stimulation site to compare possible related effects in related areas (i.e. inferior frontal gyrus, motor cortex), thus may not be sufficiently reflecting the essential influence of the SMA on spatial impulsivity. Yet, the possible SMA functions contributing to our results are multiple. Of note, the multi-functional SMA roles including planning and initiating movements 52, response inhibition (Albares et al., 2014; Obeso et al., 2013), switching 53, learning 54 or spatial cognition 10 could have been modulated within task performance. Moreover, previous neuroimaging evidence identifies the SMA role in detection of both object size and location in the context of grasping actions 23. In this investigation, researchers aimed to examine brain activation patterns using fMRI while participants were tasked with grasping objects that exhibited variations in both size and location. The findings imply that the SMA, along with regions like the primary motor cortex and the dorsal premotor cortex, play a role in sophisticated adaptive processes when dealing with information related to both object size and location within the framework of grasping movements. Here, SMA stimulation puts the individual in a more adaptive decision moment, by significantly increasing the decision thresholds and modulate action selection when faced with spatial moves. Our hypothesis is that the application of stimulation would influence performance by jointly increasing slower reaction times, without necessarily improving the selection of the correct moment to respond. This neuromodulator effect appears to manifest primarily in slower reaction times, while it does not seem to have a significant impact on errors committed.
Based on the mixed functions assessed with our virtual reality environment (i.e., inhibition and spatial functions), the behavioural changes after tSMS can be interpreted from two possible neurobiological viewpoints. First, based on prior works on brain connectivity changes after tSMS over the SMA 26,27, other interconnected brain areas may take control of the spatial decisions made during our task. Indeed, inferior-frontal gyrus was enhanced after 30 minutes tSMS procedure 27, which could provide a warning signal close or distant objects to withhold actions. This is plausible given its object detection and inhibitory roles 55 that could have been boosted following SMA neuromodulation. An alternative (non-exclusive) explanation of our findings is directly linked to local physiological SMA changes after neuromodulation. With similar inhibitory protocols using TMS, the physiological effects in humans can vary individually 56 and have been described as modifying the levels of neural “noise” after stimulation 57. tSMS over the SMA could possibly create a similar adjustment of neural noise and distant neural connectivity, resulting in ‘paradoxically’ improvement of spatial processing and/or impulsive outcomes. Together with the neural noise change, the mechanics of tSMS possibly relate to reductions in the accumulation of noisy evidence until a certain threshold is reached and decisions made 58,59.
The present study counts with some methodological limitations. In experiment 1, spatial perception was evaluated using a two-dimensional environment. While assessments of spatial perception have traditionally been conducted in two dimensions 7,60,61, the advancement toward constructing three-dimensional virtual environments offers a significant improvement. These 3D environments not only enhance ecological validity 62 but also provide greater control over experimental conditions 63. They closely mimic real-world settings, fostering a heightened sense of immersion and sustaining participants' attention more effectively. Regarding experiment 2, the absence of another stimulation target could reframe the inference of our findings. The application of tSMS to other cortical areas related to spatial learning and/or control over impulsive tendencies could show related effects as the ones here reported, which would relate as well other possible cortical hubs. We could anticipate the possible scenario where other areas show related findings as those here obtained, given that the system level functioning of both learning 64 and inhibition 65 might involve implies other regions also relevant in the process. On the other hand, the reliability of the stimulation results could be a problem due to the large number of measures analysed in the study. We used from the most basic (RTs, errors) to speed-accuracy models (LISAS, DDM) to account for different understanding levels of SMA functions, which added considerable statistical tests to our design. Hence, a potential reliability problem arises due to the increased likelihood of false positives when several measures are examined simultaneously.
Overall, our study might suggest that SMA computes the integration of spatial information and inhibitory functions, where SMA shall play a role in accommodating decision thresholds. Current results show promising effects of neuromodulation on spatial impulsivity but should be taken with caution as we did not find significant distance x stimulation interaction. However, our findings place the SMA as a possible cortical driver in charge of favouring a response threshold. Alternatively, regions interconnected with the SMA could have driven a more conservative and adaptive response by signalling spatial cues to favour optimal behaviour. These findings could provide valuable information to better understand the organization of adaptive responses in various contexts where spatial cues drive lost control over behaviour, including those associated with conditions such as OCD, ADHD, or addictions.