The modern resurgence of tES was spawned by observations demonstrating that tDCS produces neurophysiological changes in cortical network excitability and brain plasticity (Nitsche and Paulus, 2000). Following this seminal observation, the field of noninvasive neuromodulation experienced explosive growth. A series of pioneering studies conducted by the US Air Force Research Laboratories provided the first evidence that cortical tES can be effective for enhancing remote operator cognition, training, performance (McKinley et al., 2011; McKinley et al., 2013; McIntire et al., 2014; Nelson et al., 2014). McKinley and colleagues (2013) initially demonstrated that 30-min tDCS (2 mA) can enhance remote operator training by producing a 25% improvement on visual search tasks compared to controls (McKinley et al., 2013). This work laid the foundation for follow-up investigations demonstrating tDCS applied to prefrontal cortex improves attention, reduces mental fatigue, and enhances multi-tasking during sustained, complex tasks that are ecologically valid and contextually relevant to remote drone and machine operations (McIntire et al., 2014; Nelson et al., 2014; Nelson et al., 2016).

Using EEG and fNIRS to record brain activity, it has been shown that tDCS delivered to the primary motor cortex (M1) increases neuronal excitability and enhances sensorimotor skill learning outcomes on a flight simulator (Choe et al., 2016). Targeting M1 using tDCS has been shown to enhance learning and performance on several other skilled motor tasks, such as sequential tapping and controlled force pinching tasks (Saucedo Marquez et al., 2013; Orban de Xivry and Shadmehr, 2014). Studies evaluating the influence of tES on motor vehicle operator performance have also shown improvements to executive function and cognitive performance. For example, a recent study demonstrated that 30-min tRNS delivered during VR truck driving simulation tasks significantly reduced mental fatigue compared to controls (Benelli et al., 2024). Another recent study showed tRNS can accelerate learning in VR environments (Neri et al., 2025). These data suggest that hybrid neurostimulation strategies incorporating VR or realistic simulations with tES may be particularly beneficial for remote operator training. Given that tDCS has been shown to protect against diminished executive vigilance decrement under high cognitive loads (Hemmerich et al., 2024), its application in long duration teleoperation training or missions may also significantly reduce operator fatigue and improve safety. Other research on driving simulators indicates that attentional control and reaction times can be significantly improved using tDCS, which further indicates tES methods holds promise for optimizing operator performance in dynamic, virtual, training or work environments (Facchin et al., 2023). Further research is required to identify the optimal parameters and brain targets for using tES methods before and during training or work procedures to improve remote operator attention and learning.

Evidence from investigations into the use of tDCS for treating various clinical conditions has evolved into insights that hold promise for enhancing general cognitive performance. Several studies have shown tDCS delivered to the prefrontal cortex can improve executive functions like working memory, impulse control, and cognitive flexibility, as well as time perception in children and adults with attention-deficit hyperactivity disorder (ADHD) (Nejati et al., 2020; Nejati et al., 2021; Nejati et al., 2024; Leffa et al., 2022). These observations combined with those described above showing tDCS improves driver skill training and performance, suggest tES may be useful for improving the safety of drivers with attention disorders like ADHD. In patient populations who exhibit problems with impulse control, such as those with gambling disorders, prefrontal tDCS has been shown to enhance cognitive control and decision making by reducing risk taking while improving cognitive flexibility (Soyata et al., 2019; Gilmore et al., 2018). In healthy adults tDCS can improve working memory, decision making, and impulse control (Ke et al., 2019; Ruf et al., 2017; Ouellet et al., 2015; Yang et al., 2017). Likewise, tACS delivered at theta and gamma frequencies can improve working memory and recall in healthy adults (Jaušovec et al., 2014; Hoy et al., 2015). Further, tACS delivered 4 days in a row can produce significant improvements in working and long-term memory that last up to 1 month in healthy aged adults (Grover et al., 2022). These cognitive enhancements would be beneficial to remote operators to improve skill learning and retention. The increasing prevalence of teleoperated machines and construction equipment justifies deeper explorations into how neuromodulation can improve attention and support adaptive decision-making by reducing risk taking, particularly in hazardous and high-risk environments (Lee et al., 2022). While the literature clearly supports these approaches, further investigations are required to understand how different stimulation intensities, frequencies, and locations differentially affect executive function during realistic remote operator training scenarios.

Using pulsed electrical currents to modulate vagus nerve fibers located in different locations along the side of the neck or external ear has gained attention for its safe ability to modulate autonomic nervous system activity, inflammation, neuroplasticity, attention, stress, learning, mood, and sleep (Tyler, 2017; Kim et al., 2022; Liu et al., 2020; Wang et al., 2021; Butt et al., 2020; Verma et al., 2021; Sant'Anna et al., 1992; Tan et al., 2023; Urbin et al., 2021; Bottari et al., 2024; Srinivasan et al., 2023; Ma et al., 2022; Phillips et al., 2021; Prescott and Liberles, 2022; Henry, 2002; Thayer and Sternberg, 2006). It is well established that noninvasive VNS works by modulating the activity of the locus coeruleus and ascending reticular activating system located in brainstem. This primary action alters the release of norepinephrine across large brain regions and organs in the body produces changes in activity, arousal, and plasticity (Urbin et al., 2021; Frangos et al., 2015; Sharon et al., 2021; Schuerman et al., 2021; Frangos and Komisaruk, 2017). Other neurotransmitters like acetylcholine (Martin et al., 2024; Pavlov and Tracey, 2005) and serotonin (Hulsey et al., 2019; Manta et al., 2009) have also been shown to regulate immune function and brain plasticity following transcutaneous VNS. Targeting cervical vagus nerve fibers using tcVNS is FDA cleared to treat headache, while targeting auricular vagus nerve fibers using taVNS is FDA cleared to treat opiate withdrawal. When proper precautions and methods are used, tcVNS and taVNS pose a low-risk or non-significant risk and have numerous other health and wellness applications. In fact, several tcVNS and taVNS devices are distributed over the counter as General Wellness devices when not used to treat or diagnose a disease or medical condition. Many studies in healthy volunteers demonstrate these noninvasive neuromodulation approaches can enhance human cognition and performance as further discussed below.

Several studies have shown that both tcVNS and taVNS can reduce the sympathetic nervous system activity, as well as the psychological and neurophysiological symptoms of stress (Trifilio et al., 2023; Bretherton et al., 2019; Clancy et al., 2014; Machetanz et al., 2021a; Machetanz et al., 2021b; Gurel et al., 2020; Moazzami et al., 2023). A recent randomized, sham-controlled study demonstrated that taVNS produced significant changes in bottom-up neurophysiological arousal leading to significantly improved impulse control during emotional tasks. It also been demonstrated that taVNS can improve cognitive control during multi-tasking to enhance performance (Sommer et al., 2023). The ability of taVNS to dampen stress responses is likely a contributing factor to the improved performance observed under high cognitive and emotional loads. In fact, taVNS has been shown to improve action control performance and response selection when task demands are high (Jongkees et al., 2018). The reduction of stress by taVNS also suggest it can be used following virtual or realistic training sessions to improve rest and recovery from mental strain or fatigue (Ferstl et al., 2022). Several studies have also shown that both taVNS and tcVNS can improve human learning and memory (Phillips et al., 2021; Kaan et al., 2021; Pandža et al., 2020; Jacobs et al., 2015; Olsen et al., 2023; Zhang et al., 2020; Cibulcova et al., 2024; Ridgewell et al., 2021; Miyatsu et al., 2024; Choudhary et al., 2023; Klaming et al., 2022).

In addition to direct effects on neuroplasticity, the influence of tVNS on learning and memory can be also attributed to its ability to modulate human cortical arousal and attention (Sharon et al., 2021; Trifilio et al., 2023; Miyatsu et al., 2024; Chen et al., 2023; Rufener et al., 2018; Giraudier et al., 2024; Tyler et al., 2019). Recent studies show that taVNS can significantly improve motor action planning, enhance motor sequence learning, and improve associated motor cortex efficiency (Chen et al., 2022; Chen et al., 2024). It has also been demonstrated that taVNS can improve human working memory (Sun et al., 2021) and cognitive flexibility (Borges et al., 2020). When subjects are sleep deprived, taVNS has been shown to reduce fatigue and improve working memory (Zhao et al., 2023), while tcVNS also reduces fatigue and improves multitasking performance (McIntire et al., 2021). Attention, working memory, and cognitive control networks are critical in decision making (Bechara et al., 1998; Curtis and Lee, 2010; McGuire and Botvinick, 2010; Cole and Schneider, 2007). Impaired working memory has been shown to underlie impulsivity in decision making (Hinson et al., 2003). These different approaches to enhancing cognition can prove beneficial to improving human-machine operator training and performance (Figure 4).

Impulsive decision-making by vehicle and remote operators represents a major risk since it can lead to dangerous situations or crashes injuring people and property. Interestingly, studies have demonstrated that taVNS can produce more efficient neural processing requiring fewer resources to achieve cognitive control (Pihlaja et al., 2020), as well as to improve cognitive control or adaptation in response to conflict (Fischer et al., 2018). As cited above, taVNS improves action control performance when task demands are high (Jongkees et al., 2018) and enhances cognitive control during multi-tasking (Sommer et al., 2023). These data indicate tVNS may improve cognitive control and flexibility, enabling vehicle and remote machine operators to switch between tasks and manage multiple streams of information more efficiently (Figure 4). Given that cognitive training has been shown to reduce motor vehicle collision involvement by up to 50% in older drivers (Ball et al., 2010), similar cognitive training approaches combined with tVNS to reinforce learning outcomes and executive control may help mitigate human error in remote industrial robotics and autonomous vehicle supervision. It has also been shown that taVNS boosts human drive to work for rewards suggesting it may be useful for improving the motivation of tele-operators, drivers, and remote pilots to engage in reward-based training (Neuser et al., 2020).

Studies have shown that tcVNS and taVNS provide roughly equal benefits. The choice to use one method or approach over another can be distilled down to human factors issues. One may consider whether they need hands-free capabilities for real-time modulation. One may also consider how one makes the operator feel from a sensory stimulation standpoint as this is becoming one of the key issues related to the use of tVNS for cognitive enhancement. For enhancing cognition and reducing stress it is critical that the user or patient has a comfortable experience where the stimulation is just noticeable or not noticeable from a sensory stimulation perspective. Otherwise the off target sensory effects that emerge as distracting and uncomfortable sensations from electrical stimulation can override intended tVNS outcomes (Miyatsu et al., 2024; Jigo et al., 2024). In other words, modulating vagus nerve activity using transcutaneous, pulsed electrical nerve stimulation methods can both activate and suppress sympathetic activity (stress) depending on many variables including the electrode interface, user sensation and comfort, stimulus frequency, pulse duration, ease of use, and others (Figures 3B,C). This has been observed in studies evaluating the influence of cognitive load and tVNS on pupillometry as a noradrenergic-related measure of neurophysiological arousal (Faller et al., 2019; Urbin et al., 2021; Phillips et al., 2021; Sharon et al., 2021; Pandža et al., 2020; Tyler et al., 2019; Ramakrishnan et al., 2021). Efforts aimed at improving human factors or neuroergonomics of tVNS can be combined with work to advance neurostimulation algorithms and parameters for continuing to enhance the electrical sensation experiences, ease of use, user comfort, and efficacy. This approach should prove valuable considering provocative demonstrations that high frequency (20,000 Hz), sub-perceptual taVNS produces significant changes in cerebellar activity (Chen et al., 2021), as well as changes in the functional connectivity of the prefrontal cortex, cingulate cortex, and insula.

Using vibrotactile and haptic stimulation of the external ear and vagus nerve has also shown potential for enhancing human-computer interactions. It has been argued the tactile sensitivity of the external ear has been overshadowed by its auditory functions and that haptic stimulation of the ear represents an opportunity for information transfer (Lee et al., 2019). This point reiterates the importance of ensuring sensations from stimulation are not distracting to the user (Tyler, 2025). Lee and colleagues (2019) demonstrated small ear worn haptic stimulation devices could encode environmentally relevant spatiotemporal information by stimulating six different locations on the external ear. In an adaptive embodiment, ear haptics were demonstrated as a human-computer interface to enhance the experience of virtual reality applications for deaf and hard-of-hearing (DHH) individuals (Mirzaei et al., 2020). Haptic stimulation of the ear can convey sound direction in relation to DHH users during a VR experience when a system was not universally designed and intended for hearing enabled persons using spatially encoded audio to simulate sound distance (Mirzaei et al., 2020). Combining different methods of vibrotactile and electrical stimulation may open new possibilities for modulation of human-machine cognition, such as to improve situational awareness and multimodal attention. Future human factors studies and engineering efforts should aim to identify and translate these methods to interoperate with traditional methods, such as cognitive training that have proven indispensable.

Neuromodulation by transcranial focused ultrasound (tFUS) provides unrivaled spatial resolution and precision compared to other noninvasive modalities (Tyler et al., 2018). This method enables noninvasive, deep-brain stimulation in humans across many brain regions. Advancing tFUS or transcranial ultrasound stimulation (TUS) for human-machine interfaces has been a major interest since our pioneering studies demonstrating that low-intensity pulsed ultrasound can stimulate intact brain circuits (Tyler et al., 2008; Tufail et al., 2010). Ultrasonic neuromodulation and tFUS work when the sound waves of low-intensity, pulsed ultrasound mechanically modulate the electrical activity of brain circuits and nerves by altering the activity of pressure-sensitive ion channels, transporters, and neuronal membranes (Tyler et al., 2018; Tyler et al., 2008; Naor et al., 2016; Darmani et al., 2022). Depending on the frequency of ultrasound implemented, the spatial resolution of focused ultrasound for neuromodulation can achieve single cell resolutions in vitro, to a few microns in nerves, to a couple millimeters when delivered transcranial to deep-brain regions (Tyler et al., 2018; Naor et al., 2016). As discussed below, several lines of evidence demonstrate that tFUS can be useful for modulating human-machine cognition and interactions (Tyler, 2017; Tyler et al., 2018; Lee et al., 2024; Kim T. et al., 2021).

Modulation of human cortex to influence sensory processing and motor performance during training or teleoperation of machines may enhance human operator performance. The first functional evidence that 0.5 MHz tFUS can noninvasively modulate human brain activity recorded by EEG demonstrated that tactile discrimination abilities are enhanced following brief delivery of tFUS to the hand region of primary somatosensory cortex (Legon et al., 2014). In similar functional studies, tFUS delivered to the hand region of primary motor cortex has been shown to modulate brain circuit activity and enhance reaction times (Legon et al., 2018a; Fomenko et al., 2020). These approaches are particularly interesting options to optimize human interactions with joysticks, buttons, or hand controls by enhancing sensorimotor performance. A recent breakthrough study demonstrated the accurate, reliable, and individualized, deep-brain targeting of tFUS to the globus pallidus internus of the basal ganglia in Parkinson’s patients (Darmani et al., 2025). These observations combined with others demonstrating deep-brain modulation of motor and sensory thalamic nuclei (Legon et al., 2018b; Dallapiazza et al., 2018; Bancel et al., 2024) open the possibility of using tFUS to influence different nodes in human sensorimotor circuits for enhancing teleoperator performance. Another potential avenue is to modulate visual spatial processing by TUS. In support of this approach a recent study in healthy human volunteers showed tFUS delivered to visual cortex area 5 (V5) enhanced feature-based attention to motion by modulating activity in the dorsal visual processing pathway (Kosnoff et al., 2024). Interestingly, Kosnoff and colleagues (2024) also found this performance improvement led to reduced errors when subjects performed a spelling task using an EEG-based brain-computer interface (BCI) (Kosnoff et al., 2024). These findings raise the possibility of using tFUS to modulate human visual cortex and attention during robotic and semi-autonomous operation, as well as to improve BCI performance.

Other targets and approaches for modulating the cognitive function of remote operators or pilots with tFUS should be considered. A recent study demonstrated that tFUS improved cognitive control when delivered to the right inferior frontal gyrus (rIFG), which helps to regulate cognitive aspects of behavioral response inhibition (Fine et al., 2023). Fine and colleagues (2023) showed that tFUS targeted to the rIFG significantly decreased P300 response latencies and enhanced response inhibition in healthy volunteers (Fine et al., 2023). Another recent study found faster reaction times to “go” signals in cognitive tasks following tFUS delivery to the right inferior frontal cortex (IFC) (Atkinson-Clement et al., 2024). Magnetic resonance imaging revealed the enhancement of reaction time was correlated with a decrease in functional connectivity between the IFC and post-central gyrus (Atkinson-Clement et al., 2024). There were also significant changes in the functional connectivity between IFC and the anterior cingulate cortex superior frontal cortex that evolved over 20–40 min following brief tFUS treatment (Atkinson-Clement et al., 2024). These observations collectively demonstrate that tFUS can be used to enhance various aspects of cognitive control networks in healthy humans. Until recently however, it has been difficult to explore how these approaches may be used in human-machine interfaces due to the power requirements and size of equipment needed to conduct tFUS and ultrasonic neuromodulation. Several engineering breakthroughs led to the development of miniaturized transducers and systems that could be used in various applications (Tyler et al., 2018). Remarkably, it has recently been demonstrated that wearable tFUS devices with integrated EEG sensors that are comfortable enough to wear during sleep (Meads et al., 2024) are useful for modulating deep-brain thalamic targets in humans (Figure 5) (Fan et al., 2024). Ongoing human factors, science, and engineering efforts should be aimed at advancing tFUS or TUS to enhance HMI’s and BCI’s in robotic and teleoperation.