USN is one of the most frequent disorders following a stroke. In fact, USN occurs in 25–30% of all stroke patients (Pedersen et al., 1997; Buxbaum et al., 2004; Esposito et al., 2021), approximately 50% of survivors of right hemisphere strokes (Buxbaum et al., 2004), and is typically associated with a poorer response to stroke rehabilitation and greater disability (Buxbaum et al., 2004; Chen et al., 2015; Spaccavento et al., 2017). USN is a complex syndrome clinically defined as “a failure to report, respond or orient to stimuli that are presented contralateral to a brain lesion, provided that this failure is not due to elementary sensory or motor disorders” (Heilman and Valenstein, 1979). This contrasts with other common disorders, such as hemianopsia, that consist in damaged visual function. Indeed, USN impacts not only visual perception but also attentional processes, thus affecting visuospatial awareness.

USN can manifest in various ways, leading to the classification of different subtypes of hemineglect, each associated with specific brain lesion sites (Rode et al., 2017), predominantly in the frontal and parietal areas (Corbetta et al., 2005) (Figure 1A). Symptoms can be categorized based on the reference frame (egocentric or allocentric, i.e., object-centered neglect irrespective of its position relative to the person), modality (motor, perceptual, intentional, or representational neglect) and the sector of space involved, including imaginary space (personal, peri-personal and extrapersonal) (Buxbaum et al., 2004; Rode et al., 2017; Gammeri et al., 2020). Near and far space neglect can also be distinguished. The resulting deficit in attention and awareness of one hemispace significantly impacts patients’ behavior and impedes overall stroke rehabilitation, particularly after right brain damage (RBD) (Stone et al., 1991; Esposito et al., 2021).

Spontaneous recovery from hemineglect can occur within the first 3 months post-stroke. However, more than one-third of USN patients show chronic symptoms after one year, especially following RBD (Nijboer et al., 2013). Given the widespread impact of USN on daily life, this syndrome necessitates careful attention and management.

Right and left USN appear equally common after left and right brain damage during the acute phase. However, left USN after RBD tends to be more noticeable, enduring and severe (Rode et al., 2017). Although the occurrence of hemineglect varies among studies based on experimental protocols, left USN predominates in the later stages (Beis et al., 2004; Buxbaum et al., 2004; Esposito et al., 2021).

Underlying mechanisms related to the right hemisphere’s specialization for spatial attention and awareness (Heilman and Valenstein, 1979) could explain the lateralized and heterogeneous nature of symptoms.

USN has been explained as both a deficit in orienting attention to the contralesional hemispace (Heilman and Valenstein, 1979) and a pathological hyper-attention to the ipsilesional hemispace (see Bartolomeo and Chokron, 2002 for review).

Two distributed cerebral networks control different components of attention (Corbetta and Shulman, 2002). The dorsal attentional network (DAN) serves as a top-down system involved in stimuli selection, saccadic scanning eyes movements, exogenous and spatial attention. The DAN exhibits bilateral frontoparietal networks interactivity, particularly between the frontal eye fields and intraparietal sulcus that compose it (Corbetta et al., 2005; Corbetta and Shulman, 2011) (Figure 1A). On the other hand, the ventral attentional network (VAN) operates as a stimulus-driven (bottom-up) system regulating endogenous attention, reorientation of attention, vigilance, and response to alertness. The VAN mainly relies on the right temporoparietal junction and the ventral frontal cortex (Husain and Rorden, 2003; He et al., 2007; Corbetta and Shulman, 2011; Bartolomeo et al., 2012) (Figure 1A). While functionally distinct, previous research suggests that both networks interact and work together in certain attentional processes (Husain and Rorden, 2003; He et al., 2007; Corbetta and Shulman, 2011; Bartolomeo et al., 2012).

These distributed cortical networks are disrupted in USN (Corbetta and Shulman, 2002; Bartolomeo et al., 2012). Their dysfunction could better explain USN complex symptoms than specific structural changes at the lesions sites (e.g., intrahemispheric disconnections) (Buxbaum et al., 2004; Corbetta et al., 2005). Impaired functionality of the VAN could indirectly cause dysfunction of the bilateral DAN (He et al., 2007), explaining the higher severity of USN caused by RBD. This vision is supported by the recovery mechanisms and reorganization of attentional networks observed during rehabilitation (Corbetta et al., 2005; Umarova et al., 2016).

The current gold standard for clinical USN assessment is the behavioral inattention test (BIT) which employs a brief battery of pen-and-paper screening tests to determine the presence, extent and nature of neglect in daily life situations (Wilson et al., 1987). Such tests include cancelation tasks, visual search, copying and representational drawing (see Figure 1B), as well as visual extinction assessment. However, no consensus exist on their efficiency to diagnose USN given the challenges in detecting and identifying underlying types of motor and visual neglect (Williams et al., 2021). Numerous developments have explored the use of computerized assessment tasks (notably involving virtual reality) (Ogourtsova et al., 2018) to address the limitations of existing methods (Giannakou et al., 2022), such as their lack of ecological validity and inability to detect compensatory strategies (Azouvi, 2017; Williams et al., 2021). In particular, standard pen-and-paper tests batteries have been translated to VR with comparable or improved performance, and new USN management platforms have emerged (Fordell et al., 2016; Knobel et al., 2020).

Therapeutic approaches for USN rehabilitation can be categorized into bottom-up and top-down strategies, primarily contrasting visual scanning training (VST) with methods involving aids such as prism adaptation (PA; Gammeri et al., 2023). While the top-down approach consists in teaching the patient compensatory strategies for neglect (with short-term impact), the bottom-up approach aims to remediate attention biases and spatial representations. Typically, VST promotes neuroplasticity and the reorganization of disrupted attentional networks by encouraging active exploration of the environment. On the other hand, PA induces an artificial visual shift to the neglected space, temporarily modifying sensorimotor mapping. Mental practice has also been used to improve the perception of the contralesional limbs in neglect patients. Such task consists in imaging performing a movement, for instance with the contralesional upper limb to improve patients’ self and spatial perception (Welfringer et al., 2011). Other approaches involving brain stimulations or robot-assisted motor rehabilitation exist (see Durfee and Hillis, 2023; Singh and Leff, 2023 for reviews) with no clear consensus on their efficacy. Amidst the growing interest in computer-based therapy, the implementation of VR protocols emerges as a promising intervention option for USN therapy (Gamito et al., 2017; Durfee and Hillis, 2023). Notably, VR provides enriched rehabilitation possibilities, including multimodal stimulations, immersiveness, ecological training conditions, and the ability to implement various rehabilitation strategies (Kim et al., 2011; Van Kessel et al., 2013). Several innovative rehabilitative methods for USN now rely on VR (Yasuda et al., 2017; Ogourtsova et al., 2018; Huygelier et al., 2020; Knobel et al., 2021). Compared to conventional rehabilitation programs, immersive VR-based training usually improves patients adherence and compliance with treatment (Martino Cinnera et al., 2022).

Surprisingly, despite substantial advancements in neurotechnologies, the application of rehabilitative BCIs within the context of USN remains largely unexplored. In the following section, we will delve into the realm of non-invasive BCI technology and its untapped potential.

BCIs are primarily designed to replace, restore, enhance, supplement, or improve cognitive and motor functions (Daly and Huggins, 2015). This technology holds significant potential for stroke rehabilitation, as BCIs can promote neuroplasticity through various mechanisms and have proven efficiency in providing communication channels, restoring or compensating motor functions loss in patients (Zander et al., 2014; Mane et al., 2020).

Among clinical applications, two types of BCIs have been developed. Assistive BCIs aim to bypass damaged brain pathways and compensate the deficits by providing alternative means for impaired individuals to interact with their environment. Rehabilitative BCIs, on the other hand, aim to stimulate the recovery of the damaged neural networks within the brain, thereby facilitating the restoration or relearning of lost functions (Mane et al., 2020). The latter approach has demonstrated its efficiency to tackle post-stroke syndromes, particularly contralesional motor deficits (Chaudhary et al., 2016).

These two approaches are based on distinct BCI paradigms (see Table 1) that reflect both the mental activities performed by the participants and the brain signals used to construct the interface. They are thus categorized as passive, active and reactive BCIs (Zander et al., 2014). Clinical BCIs primarily involve active and reactive paradigms. Therefore, we will focus on these two categories in the remainder of this section.

Active BCIs involve intentional modulation of brain activity, often through motor imagery (MI-BCI), which relies on the mental execution of movements without muscular activation. MI-BCIs are currently the dominant type on BCI-based post-stroke motor-related rehabilitation (Mane et al., 2020) and promote motor recovery by increasing functional activity in damaged motor brain regions involved in intended movements execution (Chaudhary et al., 2016; Mane et al., 2022).

Active BCIs also include NF-BCIs in which users learn to self-regulate brain activity or improve cognitive functions by getting real-time feedbacks. For example, they may train to increase attention-related brainwave activity, receiving immediate feedback of their performance like visual or auditory cues (Zoefel et al., 2011).

Reactive BCIs rely on specific cerebral responses to external stimuli, such as visually-evoked potential (VEP) or P300 event-related potential, to facilitate communication or device control (Amiri et al., 2013). P300 is typically triggered by the apparition of a rare or desired stimulus among non-targets. It is commonly used in spelling device, where users focus on symbols arranged in a grid, with the system detecting the P300 when the desired symbol is flashed. VEP-based BCIs (VEP-BCIs) require the user to focus their attention on stimuli that exhibit either periodic (steady-state VEPs, SSVEPs) or pseudo-periodic (code-modulated VEPs, c-VEPs) repetitive behavior, such as high-contrast flickering (Herrmann, 2001; Martínez-Cagigal et al., 2021). The flicker frequency or pattern is then mirrored through brain activity, enabling to select or discriminate a specific target among stimuli. VEP-BCIs typical assistive applications are spellers, exoskeleton control etc. (Bin et al., 2011; Kwak et al., 2015; Mannan et al., 2020). Henceforth, the term VEP will refer to both SSVEP and c-VEP.

Stroke can result in a wide range of impairments, including motor, cognitive and attentional deficits. However, the field of BCIs for poststroke cognitive rehabilitation remains quite nascent and has received significantly less attention from researchers compared to motor neurorehabilitation, despite being a key factor in overall stroke recovery and outcomes (Barker-Collo et al., 2010; Mane et al., 2020, 2022).

Indeed, after brain damage, motor function restoration is usually the primary focus. Many MI-BCIs have been successfully developed to this end. For example, MI-BCIs enable patients to control prosthetics and perform voluntary movements, by imaging their execution, stimulating neural plasticity and strengthening associated neural networks (Case et al., 2015). Barria et al. (2021) introduced a promising MI-BCI for post-stroke patients with lower limb hemiparesis to regain ankle mobility. Patients were instructed to imagine moving or relaxing their foot, receiving feedback from an ankle skeleton that facilitated dorsiflexion or relaxation accordingly.

Until recently, only NF-BCI paradigm had been applied to poststroke cognitive rehabilitation (Carelli et al., 2017; Mane et al., 2022). For instance, this paradigm enabled to enhance cognitive functions (Zoefel et al., 2011; for review see Enriquez-Geppert et al., 2017) and improve various conditions, including neurodevelopmental and neurodegenerative disorders—such as attention-deficit/hyperactivity disorders (Gevensleben et al., 2009) or aphasia in stroke patients (Ferro et al., 2004).

Although BCIs have demonstrated effective recovery and may promote neuroplasticity, no efficient BCI device has yet been proposed to manage cerebral visual impairments resulting from brain lesions.

To date, no effective BCI device has been proposed for the treatment of cerebral visual impairments, which are prevalent following stroke and hamper overall rehabilitation effectiveness. Despite the acknowledged impact of BCIs on neuroplasticity for motor recovery following brain injury, there remains a scarcity of applications targeting cognitive and attentional deficits. Nevertheless, through the current review, we identified two technologies particularly promising for USN management: VEP-BCIs and VR.

VEP-BCIs demonstrate particular accuracy in measuring attentional and awareness levels (Kashiwase et al., 2012), and have already shown interesting results in addressing neurodevelopmental attentional disorders (Arpaia et al., 2020). Implementing VEP-based paradigm within selection tasks, such as visual scanning training (VST), could enhance USN management. Indeed, this hybrid approach would effectively combine both bottom-up and top-down rehabilitation strategies, by encouraging patients to search for targets, redirecting attention to the contralesional hemispace, and requiring sustained attention, thus stimulating the disrupted attentional networks (see Figure 1A).

As mentioned in section 2.3, VR-based USN therapy incorporating attention training and VST has received considerable attention for its ability to augment standard rehabilitation. VEP-BCI interest could be further enhanced if associated with ecological environment featuring standardized and well-integrated stimuli, which aligns with current research emphasis. In this context, the combination with VR technology could address the limitations of current rehabilitative methods, by providing 3D, naturalistic, and fully controlled environments. VEP-BCI could complement these developments by enabling precise monitoring of attentional processes and removing motor control requirements.

Integrating BCI into VR-based cognitive rehabilitation appears promising for addressing specific nuances of USN, by providing precise and adaptative interventions that would dynamically address patients’ individual needs. A VST application combining VR and VEP-BCI (VR-VEP-BCI) would harness the benefits of both technologies, simultaneously training a broad spectrum of attentional processes disrupted in USN, mirroring real-life conditions. VR facilitates multimodal stimulations, allowing for exogenous attention training through the use of multisensory cues to redirect attention to the contralesional hemispace. This challenges the spatial awareness of USN patients, while enhancing VST efficacy (Fordell et al., 2016). Additionally, sustained attention would be necessary for target detection validation and in device interaction, engaging endogenous attention as well.

Typically, in the proposed approach, USN patients would be immersed in a virtual environment with flickering targets to catch by focusing their attention on them to earn points and progress in the game for explicit rehabilitation (Figure 1C). With an asymmetric reward system, where the most rewarding targets are predominantly located near the neglected hemifield for increased difficulty, patients would be implicitly encouraged to explore the ipsilesional space through operant conditioning mechanisms (Figure 1D). Finally, the VEP paradigm establishes a direct link between gaze and conscious perception, which is not achievable with other technologies, such as eye-tracking. This direct link creates a strong sense of agency (Nierula et al., 2021) and enhances the overall effectiveness of the rehabilitation approach.

Despite the potential of VR-VEP-BCI for USN cognitive rehabilitation, challenges remain in overcoming hardware limitations and ensuring efficient BCI, while maintaining immersion and a comfortable VR experience.

Combining advanced interventions with traditional therapeutic protocols may be the future of USN rehabilitation, enriching the possibilities and mixing strategies, toward a holistic approach. VR-BCI combination not only offers interesting perspectives for USN management but also for enriching cognitive models of attention orientation in space with this particularly adapted pathological model. Integrating cognitive therapy into existing BCI-based motor therapies could synergically enhance the overall effectiveness of post-stroke USN rehabilitation programs, addressing the heterogeneous nature of USN. Further research and investigations are now required to draw firm conclusions about the clinical efficacy of the latest approaches.