The global rise in lower limb amputation cases necessitates advancements in prosthetic limb technology to enhance the quality of life for affected patients. This review paper explores recent advancements in the integration of EEG and fNIRS modalities for smart lower prosthetic limbs for rehabilitation applications. The paper synthesizes current research progress, focusing on the synergy between brain-computer interfaces and neuroimaging technologies to enhance the functionality and user experience of lower limb prosthetics. The review discusses the potential of EEG and fNIRS in decoding neural signals, enabling more intuitive and responsive control of prosthetic devices. Additionally, the paper highlights the challenges, innovations, and prospects associated with the incorporation of these neurotechnologies in the field of rehabilitation. The insights provided in this review contribute to a deeper understanding of the evolving landscape of smart lower prosthetic limbs and pave the way for more effective and user-friendly solutions in the realm of neurorehabilitation.

Freezing of gait, characterized by involuntary interruptions of walking, is a debilitating motor symptom of Parkinson\'s disease that restricts people\'s autonomy. Previous brain imaging studies investigating the mechanisms underlying freezing were restricted to scan people in supine positions and yielded conflicting theories regarding the role of the supplementary motor area and other cortical regions. We used functional near-infrared spectroscopy to investigate cortical haemodynamics related to freezing in freely moving people. We measured functional near-infrared spectroscopy activity over multiple motor-related cortical areas in 23 persons with Parkinson\'s disease who experienced daily freezing (\'freezers\') and 22 age-matched controls during freezing-provoking tasks including turning and doorway passing, voluntary stops and actual freezing. Crucially, we corrected the measured signals for confounds of walking. We first compared cortical activity between freezers and controls during freezing-provoking tasks without freezing (i.e. turning and doorway passing) and during stops. Secondly, within the freezers, we compared cortical activity between freezing, stopping and freezing-provoking tasks without freezing. First, we show that turning and doorway passing (without freezing) resemble cortical activity during stopping in both groups involving activation of the supplementary motor area and prefrontal cortex, areas known for their role in inhibiting actions. During these freezing-provoking tasks, the freezers displayed higher activity in the premotor areas than controls. Secondly, we show that, during actual freezing events, activity in the prefrontal cortex was lower than during voluntary stopping. The cortical relation between the freezing-provoking tasks (turning and doorway passing) and stopping may explain their susceptibility to trigger freezing by activating a stopping mechanism. Besides, the stopping-related activity of the supplementary motor area and prefrontal cortex seems to be out of balance in freezers. In this paper, we postulate that freezing results from a paroxysmal imbalance between the supplementary motor area and prefrontal cortex, thereby extending upon the current role of the supplementary motor area in freezing pathophysiology.

Electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) can objectively reflect a person\'s emotional state and have been widely studied in emotion recognition. However, the effective feature fusion and discriminative feature learning from EEG-fNIRS data is challenging. In order to improve the accuracy of emotion recognition, a graph convolution and capsule attention network model (GCN-CA-CapsNet) is proposed. Firstly, EEG-fNIRS signals are collected from 50 subjects induced by emotional video clips. And then, the features of the EEG and fNIRS are extracted; the EEG-fNIRS features are fused to generate higher-quality primary capsules by graph convolution with the Pearson correlation adjacency matrix. Finally, the capsule attention module is introduced to assign different weights to the primary capsules, and higher-quality primary capsules are selected to generate better classification capsules in the dynamic routing mechanism. We validate the efficacy of the proposed method on our emotional EEG-fNIRS dataset with an ablation study. Extensive experiments demonstrate that the proposed GCN-CA-CapsNet method achieves a more satisfactory performance against the state-of-the-art methods, and the average accuracy can increase by 3-11%.

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We used 34-channel functional near infrared spectroscopy to investigate and compare changes in oxyhemoglobin concentration of brain networks in bilateral prefrontal cortex, sensorimotor cortex, and occipital lobe of 22 right-handed healthy adults during executive right-handed grasp (motor execution task) and imagined right-handed grasp (motor imagery task). Then calculated lateral index and functional contribution degree, and measured functional connectivity strength between the regions of interest. In the motor executive block task, there was a significant increase in oxyhemoglobin concentration in regions of interest except for right occipital lobe (P<0.05), while in the motor imagery task, all left regions of interest\'s oxyhemoglobin concentration increased significantly (P<0.05). Except the prefrontal cortex in motor executive task, the left side of the brain was dominant. Left sensorimotor cortex played a major role in these two tasks, followed by right sensorimotor cortex. Among all functional contribution degree, left sensorimotor cortex, right sensorimotor cortex and left occipital lobe ranked top three during these tasks. In continuous acquisition tasks, functional connectivity on during motor imagery task was stronger than that during motor executive task. Brain functions during two tasks of right-hand grasping movement were partially consistent. However, the excitability of brain during motor imagery was lower, and it was more dependent on the participation of left prefrontal cortex, and its synchronous activity of the whole brain was stronger. The trend of functional contribution degree was basically consistent with oxyhemoglobin concentration and lateral index, and can be used as a novel index to evaluate brain function. [ChiCTR2200063792 (2022-09-16)].

Individuals with depressive tendencies are considered to be at high risk for the onset of depressive disorders. Currently, most research focuses on the impairment of working memory in patients with depression, while there is less attention paid to the WM of individuals with depressive tendencies, and their neural mechanisms underlying it are poorly understood. Therefore, this study focuses on the characteristics and neural mechanisms of WM in individuals with depressive tendencies. This study uses functional near-infrared spectroscopy (fNIRS) to monitor the concentration of Oxy-Hb in the prefrontal cortex and employs the n-back paradigm, designing three levels of load: 0, 1, and 2, to examine the characteristics of WM and its neural mechanisms in individuals with depressive tendencies. Behavioral results show that the accuracy rates of individuals with depressive tendencies is significantly lower than that of healthy individuals, and under the 0-back condition, the reaction time of individuals with depressive tendencies is significantly higher than that of healthy control individuals. Near-infrared results indicate that the activation level in the frontal pole and the dorsal lateral prefrontal cortex of individuals with depressive tendencies is significantly lower than that of healthy control individuals. The β values of channels 2, 7, and 9 are significantly negatively correlated with the Beck Depression Inventory scores of the participants. The results suggest that the reduced activation of the frontal pole and dorsal lateral prefrontal cortex in individuals with depressive tendencies leads to poorer WM performance compared to healthy control individuals. This is a rare brain evidence of the characteristics of WM in individuals with depressive tendencies, which can provide a deeper understanding of the WM characteristics of individuals with depressive tendencies.

Creativity is an indispensable competency in today\'s innovation-driven society. Yet, the influences of instructional strategy, a key determinant of educational outcomes, on the creativity-fostering process remains an unresolved mystery. We proposed that instructional strategy affects creativity cultivation and further investigated the intricate neural mechanisms underlying this relationship. In a naturalistic laboratory setting, 66 instructor-learner dyads were randomized into three groups (scaffolding, explanation, and control), with divergent thinking instructions separately. Functional near-infrared spectroscopy (fNIRS) hyperscanning simultaneously collected brain signals in the prefrontal cortex and temporal-parietal junction regions. Results indicated that learners instructed with a scaffolding strategy demonstrated superior creative performance both in acquisition (direct learning) and transfer (use in a novel context) of creativity skills, compared to pretest levels. In contrast, the control and explanation groups did not exhibit such effects. Notably, we also observed remarkable interbrain neural synchronization (INS) between instructors and learners in the left superior frontal cortex in the scaffolding group, but not in the explanation or control groups. Furthermore, INS positively predicted enhancements in creativity performance (acquisition and transfer), indicating that it is a crucial neural mechanism in the creativity-fostering process. These findings reveal that scaffolding facilitates the acquisition and transfer of creativity and deepen our understanding of the neural mechanisms underlying the process of creativity-fostering. The current study provides valuable insights for implementing teaching strategies to fostering creativity.

UNASSIGNED: Reaching movements are crucial for daily living and rehabilitation, for which Fitts\' Law describes a speed-accuracy trade-off that movement time increases with task difficulty. This study aims to investigate whether cortical activation in motor-related areas is directly linked to task difficulty as defined by Fitts\' Law. Understanding this relationship provides a physiological basis for parameter selection in therapeutic exercises.
UNASSIGNED: Sixteen healthy subjects performed 2D reaching movements using a rehabilitation robot, with their cortical responses detected using functional near-infrared spectroscopy (fNIRS). Task difficulty was manipulated by varying target size and distance, resulting in 3 levels of index-of-difficulty (ID). Kinematic signals were recorded alongside cortical activity to assess the relationship among movement time, task difficulty, and cortical activation.
UNASSIGNED: Our results showed that movement time increased with ID by 0.2974s/bit across all subjects (conditional r2 = 0.6434, p < 0.0001), and all subjects showed individual trends conforming Fitts\' Law (all p < 0.001). Neither activation in BA4 nor in BA6 showed a significant correlation with ID (p > 0.05), while both the target size and distance, as well as the interaction between them, showed a significant relationship with BA4 or BA6 activation (all p < 0.05).
UNASSIGNED: This study found that although kinematic measures supported Fitts\' Law, cortical activity in motor-related areas during reaching movements did not correlate directly with task difficulty as defined by Fitts\' Law. Additional factors such as muscle activation may call for different cortical control even when difficulty was identical.

Functional near-infrared spectroscopy (fNIRS), a non-invasive optical neuroimaging technique that is portable and acoustically silent, has become a promising tool for evaluating auditory brain functions in hearing-vulnerable individuals. This study, for the first time, used fNIRS to evaluate neuroplasticity of speech-in-noise processing in older adults. Ten older adults, most of whom had moderate-to-mild hearing loss, participated in a 4-week speech-in-noise training. Their speech-in-noise performances and fNIRS brain responses to speech (auditory sentences in noise), non-speech (spectrally-rotated speech in noise) and visual (flashing chequerboards) stimuli were evaluated pre- (T0) and post-training (immediately after training, T1; and after a 4-week retention, T2). Behaviourally, speech-in-noise performances were improved after retention (T2 vs. T0) but not immediately after training (T1 vs. T0). Neurally, we intriguingly found brain responses to speech vs. non-speech decreased significantly in the left auditory cortex after retention (T2 vs. T0 and T2 vs. T1) for which we interpret as suppressed processing of background noise during speech listening alongside the significant behavioural improvements. Meanwhile, functional connectivity within and between multiple regions of temporal, parietal and frontal lobes was significantly enhanced in the speech condition after retention (T2 vs. T0). We also found neural changes before the emergence of significant behavioural improvements. Compared to pre-training, responses to speech vs. non-speech in the left frontal/prefrontal cortex were decreased significantly both immediately after training (T1 vs. T0) and retention (T2 vs. T0), reflecting possible alleviation of listening efforts. Finally, connectivity was significantly decreased between auditory and higher-level non-auditory (parietal and frontal) cortices in response to visual stimuli immediately after training (T1 vs. T0), indicating decreased cross-modal takeover of speech-related regions during visual processing. The results thus showed that neuroplasticity can be observed not only at the same time with, but also before, behavioural changes in speech-in-noise perception. To our knowledge, this is the first fNIRS study to evaluate speech-based auditory neuroplasticity in older adults. It thus provides important implications for current research by illustrating the promises of detecting neuroplasticity using fNIRS in hearing-vulnerable individuals.

Recent research has extensively reported the phenomenon of inter-brain neural coupling between speakers and listeners during speech communication. Yet, the specific speech processes underlying this neural coupling remain elusive. To bridge this gap, this study estimated the correlation between the temporal dynamics of speaker-listener neural coupling with speech features, utilizing two inter-brain datasets accounting for different noise levels and listener\'s language experiences (native vs. non-native). We first derived time-varying speaker-listener neural coupling, extracted acoustic feature (envelope) and semantic features (entropy and surprisal) from speech, and then explored their correlational relationship. Our findings reveal that in clear conditions, speaker-listener neural coupling correlates with semantic features. However, as noise increases, this correlation is only significant for native listeners. For non-native listeners, neural coupling correlates predominantly with acoustic feature rather than semantic features. These results revealed how speaker-listener neural coupling is associated with the acoustic and semantic features under various scenarios, enriching our understanding of the inter-brain neural mechanisms during natural speech communication. We therefore advocate for more attention on the dynamic nature of speaker-listener neural coupling and its modeling with multilevel speech features.