Sensory threshold neuromuscular electrical stimulation fosters motor imagery performance

Abstract

Motor imagery (MI) has been largely studied as a way to enhance motor learning and to restore motor functions. Although it is agreed that users should emphasize kinesthetic imagery during MI, recordings of MI brain patterns are not sufficiently reliable for many subjects. It has been suggested that the usage of somatosensory feedback would be more suitable than standardly used visual feedback to enhance MI brain patterns. However, somatosensory feedback should not interfere with the recorded MI brain pattern. In this study we propose a novel feedback modality to guide subjects during MI based on sensory threshold neuromuscular electrical stimulation (St-NMES). St-NMES depolarizes sensory and motor axons without eliciting any muscular contraction. We hypothesize that St-NMES does not induce detectable ERD brain patterns and fosters MI performance. Twelve novice subjects were included in a cross-over design study. We recorded their EEG, comparing St-NMES with visual feedback during MI or resting tasks. We found that St-NMES not only induced significantly larger desynchronization over sensorimotor areas (p<0.05) but also significantly enhanced MI brain connectivity patterns. Moreover, classification accuracy and stability were significantly higher with St-NMES. Importantly, St-NMES alone did not induce detectable artifacts, but rather the changes in the detected patterns were due to an increased MI performance. Our findings indicate that St-NMES is a promising feedback in order to foster MI performance and cold be used for BMI online applications.

Brain-Machine Interfaces: A Tale of Two Learners

“…First, it is a critical factor in training protocol design. For example, the explicit learning approach calls for more "explanatory" protocols that better take into account educational theories of learning, or instructional and motivational designs [32], whereas implicit learning could more likely be boosted by interventions like the establishment of more natural feedback provision strategies [75][76][77]. Second, the expected timescales of learning (and as a result, the required training times) should heavily depend on the degree of its explicit or implicit nature.…”

Kinaesthetic illusion shapes the cortical plasticity evoked by action observation

“…; Corbet et al . ). A further additive effect in terms of changes in the brain's activity would be obtained when combining altogether AO, MI and a peripheral electrical stimulation (Yasui et al .…”

“…This finding could be explained by the fact that AO exploits only the visual input channel, whilst the brain uses information from multiple sensory modalities to build the representation of the body, including its current position and motion (Dijkerman & de Haan, 2007;Tsakiris, 2010;Blanke, 2012;Limanowski & Blankenburg, 2016). In support of the role played by convergent sensory inputs in inducing cortical plasticity, recent studies showed that the combination of another cognitive stimulation technique, namely motor imagery (MI), led to motor cortical plasticity only when associated with peripheral electrical stimulation (Bonassi et al 2017;Corbet et al 2018). A further additive effect in terms of changes in the brain's activity would be obtained when combining altogether AO, MI and a peripheral electrical stimulation (Yasui et al 2019).…”

Investigation of Optimal Afferent Feedback Modality for Inducing Neural Plasticity with A Self-Paced Brain-Computer Interface

“…It has been suggested that improved BCI performance could increase the induction of plasticity [ 11 ]. Thus, different approaches have been investigated to optimize the BCI performance, such as using different signal processing techniques [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ], combining two different control signals [ 29 ], training the user [ 30 ], and facilitate motor imagination [ 31 ]. In addition to the technical optimization of the BCI, it is likely that the induction of plasticity can be improved by identifying the optimal type of afferent feedback.…”