Brain-computer interfaces (BCIs) provide a unique technological solution to circumvent the damaged motor system. For neurorehabilitation, the BCI can be used to translate neural signals associated with movement intentions into tangible feedback for the patient, when they are unable to generate functional movement themselves. Clinical interest in BCI is growing rapidly, as it would facilitate rehabilitation to commence earlier following brain damage and provides options for patients who are unable to partake in traditional physical therapy. However, substantial challenges with existing BCI implementations have prevented its widespread adoption. Recent advances in knowledge and technology provide opportunities to facilitate a change, provided that researchers and clinicians using BCI agree on standardisation of guidelines for protocols and shared efforts to uncover mechanisms. We propose that addressing the speed and effectiveness of learning BCI control are priorities for the field, which may be improved by multimodal or multi-stage approaches harnessing more sensitive neuroimaging technologies in the early learning stages, before transitioning to more practical, mobile implementations. Clarification of the neural mechanisms that give rise to improvement in motor function is an essential next step towards justifying clinical use of BCI. In particular, quantifying the unknown contribution of non-motor mechanisms to motor recovery calls for more stringent control conditions in experimental work. Here we provide a contemporary viewpoint on the factors impeding the scalability of BCI. Further, we provide a future outlook for optimal design of the technology to best exploit its unique potential, and best practices for research and reporting of findings.

The loss of body ownership, the feeling that your body and its limbs no longer belong to you, presents a severe clinical condition that has proven difficult to study directly. We here propose a novel paradigm using mixed reality to interfere with natural embodiment using temporally conflicting sensory signals from the own hand. In Experiment 1 we investigated how such a mismatch affects phenomenological and physiological aspects of embodiment, and identified its most important dimensions using a principle component analysis. The results suggest that such a mismatch induces a strong reduction in embodiment accompanied by an increase in feelings of disownership and deafference, which was, however, not reflected in physiological changes. In Experiment 2 we refined the paradigm to measure perceptual thresholds for temporal mismatches and compared how different multimodal, mismatching information alters the sense of embodiment. The results showed that while visual delay decreased embodiment both while actively moving and during passive touch, the effect was stronger for the former. Our results extend previous findings as they demonstrate that a sense of disembodiment can be induced through controlled multimodal mismatches about one's own body and more so during active movement as compared to passive touch. Based on the ecologically more valid protocol we propose here, we argue that such a sense of disembodiment may fundamentally differ from disownership sensations as discussed in the rubber hand illusion literature, and emphasize its clinical relevance. This might importantly advance the current debate on the relative contribution of different modalities to our sense of body and its plasticity.

Altered states of embodiment are fundamental to the scientific understanding of bodily self consciousness. The feeling of disembodiment during everyday activities is common to clinical conditions; however, the direct study of disembodiment in experimental setups is rare compared to the extensive investigation of illusory embodiment of an external object. Using mixed reality to modulate embodiment through temporally mismatching sensory signals from the own body, we assessed how such mismatches affect phenomenal and physiological aspects of embodiment and measured perceptual thresholds for these across multimodal signals. The results of a principal component analysis suggest that multimodal mismatches generally induce disembodiment by increasing the sense of disownership and deafference and decreasing embodiment; however, this was not generally reflected in physiological changes. Although visual delay decreased embodiment both during active movement and passive touch, the effect was stronger for the former. We discuss the relevance of these findings for understanding bodily self plasticity.

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Brain Computer Interfaces (BCI) provide a unique technological solution to circumvent the damaged motor system. For neurorehabilitation, the BCI can be used to translate neural signals associated with movement intentions into tangible feedback for the patient, when they are unable to generate functional movement themselves. Clinical interest in BCI is growing rapidly, as it would facilitate rehabilitation to commence earlier following brain damage, and provides options for patients who are unable to partake in traditional physical therapy. However, substantial challenges with existing BCI implementations have prevented its widespread adoption. Recent advances in knowledge and technology provide opportunities to facilitate a change, provided that researchers and clinicians using BCI agree on standardisation of guidelines for protocols and shared efforts to uncover mechanisms. We propose that addressing the speed and effectiveness of learning BCI control are priorities for the field, which may be improved by multimodal or multi-stage approaches harnessing more sensitive neuroimaging technologies in the early learning stages, before transitioning to more practical, mobile implementations. Clarification of the neural mechanisms that give rise to improvement in motor function is an essential next step towards justifying clinical use of BCI. In particular, quantifying the unknown contribution of non-motor mechanisms to motor recovery calls for more stringent control conditions in experimental work.Here we provide a contemporary viewpoint on the factors impeding the scalability of BCI. Further, we provide a future outlook for optimal design of the technology to best exploit its unique potential, and best practices for research and reporting of findings.

Patients suffering from body integrity dysphoria (BID) desire to become disabled, arising from a mismatch between the desired body and the physical body. We focus here on the most common variant, characterized by the desire for amputation of a healthy limb. In most reported cases, amputation of the rejected limb entirely alleviates the distress of the condition and engenders substantial improvement in quality of life. Since BID can lead to life-long suffering, it is essential to identify an effective form of treatment that causes the least amount of alteration to the person’s anatomical structure and functionality. Treatment methods involving medications, psychotherapy, and vestibular stimulation have proven largely ineffective. In this hypothesis article, we briefly discuss the characteristics, etiology, and current treatment options available for BID before highlighting the need for new, theory driven approaches. Drawing on recent findings relating to functional and structural brain correlates of BID, we introduce the idea of brain–computer interface (BCI)/neurofeedback approaches to target altered patterns of brain activity, promote re-ownership of the limb, and/or attenuate stress and negativity associated with the altered body representation.

The occurrence of neuronal spikes recorded directly from sensory cortex is highly irregular within and between presentations of an invariant stimulus. The traditional solution has been to average responses across many trials. However, with this approach, response variability is downplayed as noise, so it is assumed that statistically controlling it will reveal the brain’s true response to a stimulus. A mounting body of evidence suggests that this approach is inadequate. For example, experiments show that response variability itself varies as a function of stimulus dimensions like contrast and state dimensions like attention. In other words, response variability has structure, is therefore potentially informative and should be incorporated into models which try to explain neural encoding. In this article we provide commentary on a recently published study by Coen-Cagli and Solomon that incorporates spike variability in a quantitative model, by explaining it as a function of divisive normalization. We consider the potential role of neural oscillations in this process as a potential bridge between the current microscale findings and response variability at the mesoscale/macroscale level.

Patients suffering from Body Integrity Dysphoria (BID) desire to become disabled, arising from a mismatch between the desired body and the physical body. We focus here on the most common variant, characterised by the desire for amputation of a healthy limb. In most reported cases amputation of the rejected limb entirely alleviates the distress of the condition and engenders substantial improvement in quality of life. Since BID can lead to life-long suffering, it is essential to identify an effective form of treatment that causes the least amount of alteration to the person’s anatomical structure and functionality. Treatment methods involving medications, psychotherapy and vestibular stimulation have proven largely ineffective. In this hypothesis article, we briefly discuss the characteristics, aetiology, and current treatment options available for BID before highlighting the need for new, theory driven approaches. Drawing on recent findings relating to functional and structural brain correlates of BID, we introduce the idea of Brain Computer Interface (BCI)/neurofeedback approaches to target altered patterns of brain activity, promote re-ownership of the limb and/or attenuate stress and negativity associated with the altered body representation.