The time-varying networks of the wrist extension in post-stroke hemiplegic patients

Prefrontal cortex activity of active motion, cyclic electrical muscle stimulation, assisted motion, and imagery of wrist extension in stroke using fNIRS

OBJECTIVES

This study aimed to determine whether the prefrontal cortex (PFC) was activated during four training approaches for wrist extension in patients with stroke, including active motion, cyclic electrical muscle stimulation (EMS), assisted motion, and motor imagery (MI).

MATERIALS AND METHODS

We conducted a cross-sectional study involving 16 patients with stroke, and adopted functional near-infrared spectroscopy (fNIRS) to observe PFC activity during four treatment paradigms. The beta value of 53 channels in fNIRS under each paradigm, compared to the baseline, was evaluated using single sample t-test. The one-way analysis of variance with post hoc analysis was employed to compare the difference of significantly activated channels among four treatment paradigms.

RESULTS

This study revealed that the active motion (t values ranging from 2.399 to 4.368, p values <0.05), as well as MI of wrist extension (t values ranging from 2.161 to 4.378, p values <0.05), significantly increased HBO concentration across the entire PFC. The cyclic EMS enhanced the activation of Broca's area and frontal pole (FP) (t values ranging from -2.540 to 2.303, p values <0.05). The assisted motion induced significant activation in Broca's area, dorsolateral prefrontal cortex, and FP (t values ranging from -2.226 to 3.056, p values <0.05). The difference in ΔHBO among the four tasks was seen in Broca's area, FP, and frontal eye field.

CONCLUSIONS

Active wrist extension and MI activate most PFC areas, whereas assisted motion and single-use of cyclic EMS have limited effectiveness for PFC activation in stroke patients.

Beta Changes Induced by Acute Hand Loss Model during NMES. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-4. [PMID: 38082588 DOI: 10.1109/embc40787.2023.10341119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Neuromuscular electrical stimulation (NMES) has been demonstrated to effectively modulate cortical activities by evoking muscle contraction in upper limb and generating joint movements, which showed an excellent performance in motor rehabilitation. However, due to hand loss and cortical function reorganization induced by hand amputation, how neural activities in sensorimotor cortex response to NMES-evoked muscle contraction in the end of an amputation stump is not clear. In this paper, Ischemic nerve block (INB) technique was used to build an acute hand loss model, and 64-channel EEG signals were recorded from 11 healthy subjects to perform a 2×2 factorial design protocol, with the INB state and the current intensity as factors. The changes of NMES-evoked sensorimotor cortical activities were quantified by computing Beta-band event-related desynchronization (Beta ERD) patterns and the time-varying functional connectivity using adaptive directed transfer function (ADTF) before and during INB. The acute hand "loss" resulted in ipsilateral dominance of Beta ERD induced by NMES with two current intensities in the topographic maps, that is, ipsilateral Beta ERD was significantly higher than that the contralateral one (p<0.05). However, before INB, Beta ERD in the contralateral sensorimotor cortex induced by NMES above motor threshold was significantly higher than that in the ipsilateral area (p< 0.01). Meanwhile, whatever before or during INB, clustering coefficients of the ADTF network in sensorimotor cortex showed temporal dynamics during two NMES tasks. During INB, NMES above motor threshold-evoked lower clustering coefficients of the time-varying network in sensorimotor cortex than that before INB (p<0.05). The present results suggest that the loss of the hand proprioception will degrade cortical activities in the contralateral area, and increase cortical activities in the ipsilateral area compensatively responding to NMES. This finding may be particularly important to improve the reconstruction of the proprioception function of hand prosthesis.

820-nm Transcranial Near-infrared Stimulation on the Left DLPFC Relieved Anxiety: A Randomized, Double-blind, Sham-controlled Study

OBJECTIVE

Generalized anxiety disorder (GAD) is a chronic mood disease associated with abnormal brain network connections, including decreased activity in the left dorsolateral prefrontal cortex (DLPFC). Cortical excitability can be increased with 820-nm transcranial near-infrared stimulation (tNIRS), while transcranial magnetic stimulation with electroencephalography (TMS-EEG) can help evaluate time-varying brain network connectivity. A randomized, double-blind, sham-controlled trial was conducted to assess the efficacy of tNIRS on the left DLPFC and the impact on time-varying brain network connections in GAD patients.

METHODS

A total of 36 GAD patients were randomized to receive active or sham tNIRS for 2 weeks. Clinical psychological scales were assessed before, after, and at the 2-, 4-, and 8-week follow-ups. TMS-EEG was performed for 20minutes before and immediately after tNIRS treatment. The healthy controls did not receive tNIRS and only had TMS-EEG data collected once in the resting state.

RESULTS

The Hamilton Anxiety Scale (HAMA) scores of the active stimulation group decreased post-treatment compared with the sham group (P=0.021). The HAMA scores of the active stimulation group at the 2-, 4-, and 8-week follow-up assessments were lower than those before treatment (P<0.05). The time-varying EEG network pattern showed an information outflow from the left DLPFC and the left posterior temporal region after active treatment.

CONCLUSION

Herein, 820-nm tNIRS targeting the left DLPFC had significant positive effects on therapy for GAD that lasted at least 2 months. tNIRS may reverse the abnormality of time-varying brain network connections in GAD.

A comprehensive review on motion trajectory reconstruction for EEG-based brain-computer interface

The advance in neuroscience and computer technology over the past decades have made brain-computer interface (BCI) a most promising area of neurorehabilitation and neurophysiology research. Limb motion decoding has gradually become a hot topic in the field of BCI. Decoding neural activity related to limb movement trajectory is considered to be of great help to the development of assistive and rehabilitation strategies for motor-impaired users. Although a variety of decoding methods have been proposed for limb trajectory reconstruction, there does not yet exist a review that covers the performance evaluation of these decoding methods. To alleviate this vacancy, in this paper, we evaluate EEG-based limb trajectory decoding methods regarding their advantages and disadvantages from a variety of perspectives. Specifically, we first introduce the differences in motor execution and motor imagery in limb trajectory reconstruction with different spaces (2D and 3D). Then, we discuss the limb motion trajectory reconstruction methods including experiment paradigm, EEG pre-processing, feature extraction and selection, decoding methods, and result evaluation. Finally, we expound on the open problem and future outlooks.

Exploring construction workers' brain connectivity during hazard recognition: a cognitive psychology perspective

Monitoring brain activity is a novel development for hazard recognition in the construction industry. However, very few empirical studies have investigated the causal connections within the brain. This study aimed to explore the brain connectivity of construction workers during hazard recognition. Electroencephalogram data were collected from construction workers to perform image-based hazard recognition tasks. The Granger causality-based adaptive directed transfer function was used to simulate directed and time-variant information flow across the observed brain activity from the perspective of cognitive psychology. The results suggested a top-down modulation of behavioral goals originating from the dorsal attention network during hazard relocation. The sensory cortex predominantly serves as the information outlet center and interacts extensively with the frontal and visual cortices, reflecting a top-down attention reorientation mechanism for processing threatening stimuli. Our findings of brain effective connectivity supplement new evidence underpinning parallel distributed processing theory for workplace hazard recognition.

Time-Varying Effective Connectivity for Describing the Dynamic Brain Networks of Post-stroke Rehabilitation

Hemiplegia is a common motor dysfunction caused by a stroke. However, the dynamic network mechanism of brain processing information in post-stroke hemiplegic patients has not been revealed when performing motor imagery (MI) tasks. We acquire electroencephalography (EEG) data from healthy subjects and post-stroke hemiplegic patients and use the Fugl-Meyer assessment (FMA) to assess the degree of motor function damage in stroke patients. Time-varying MI networks are constructed using the adaptive directed transfer function (ADTF) method to explore the dynamic network mechanism of MI in post-stroke hemiplegic patients. Finally, correlation analysis has been conducted to study potential relationships between global efficiency and FMA scores. The performance of our proposed method has shown that the brain network pattern of stroke patients does not significantly change from laterality to bilateral symmetry when performing MI recognition. The main change is that the contralateral motor areas of the brain damage and the effective connection between the frontal lobe and the non-motor areas are enhanced, to compensate for motor dysfunction in stroke patients. We also find that there is a correlation between FMA scores and global efficiency. These findings help us better understand the dynamic brain network of patients with post-stroke when processing MI information. The network properties may provide a reliable biomarker for the objective evaluation of the functional rehabilitation diagnosis of stroke patients.