Cortical activation and functional connectivity during locomotion tasks in Parkinson’s disease with freezing of gait

Feng, Hongsheng; Jiang, YanNa; Lin, JinPeng; Qin, Wenting; Jin, LingJing; Shen, Xia

doi:10.3389/fnagi.2023.1068943

Cited by 4 publications

(4 citation statements)

References 73 publications

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“…The increased premotor area activity in the PD group during turning and doorway passage is in line with previous fMRI studies 44,45,78 and one previous fNIRS study. 79 Even while there were differences between the fMRI studies' findings of increased or decreased activity, they all identified the SMA as a significant locus of action. The fNIRS study reported increased SMA and PMC activity during turning in people with PD compared to controls, but not in freezers.…”

Section: The Premotor Areas Are Consistently Related To Freezing Path...mentioning

confidence: 93%

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Freezing of gait in Parkinson’s disease is related to imbalanced stopping-related cortical activity

Cockx,

Oostenveld,

et al. 2023

Preprint

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BACKGROUND: 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 (SMA) and other cortical regions. We used functional near-infrared spectroscopy (fNIRS), to investigate cortical hemodynamics related to freezing in freely moving people. METHODS: We measured fNIRS 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 fNIRS signals for confounds of walking. We first compared cortical activity between freezers and controls during voluntary stops and during freezing-provoking tasks without freezing. Secondly, within the freezers, we compared cortical activity between freezing, stopping, and freezing-provoking tasks without freezing. RESULTS: Here, we provide new evidence suggesting that freezing results from an oversensitivity to stopping signals and a disbalance between the SMA and the prefrontal cortex (PFC), areas known for their role in inhibiting actions. First, we show that freezing-provoking tasks (without freezing) resemble cortical activity during stopping in both groups, with the freezers displaying higher activity in the SMA and premotor cortex than controls during freezing-provoking tasks. Secondly, we show that, during actual freezing events, activity in the PFC was lower than during voluntary stopping.CONCLUSION: We extend upon the current role of the SMA in freezing pathophysiology by postulating that freezing results from a paroxysmal imbalance between the SMA and the PFC within the stopping network.

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Section: The Premotor Areas Are Consistently Related To Freezing Path...mentioning

confidence: 93%

“…The fNIRS study reported increased SMA and PMC activity during turning in people with PD compared to controls, but not in freezers. 79 However, this study did not specify whether freezing episodes were excluded from analysis.…”

Section: The Premotor Areas Are Consistently Related To Freezing Path...mentioning

confidence: 97%

Freezing of gait in Parkinson’s disease is related to imbalanced stopping-related cortical activity

Cockx,

Oostenveld,

et al. 2023

Preprint

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“…Its robust resistance to motion artifacts, coupled with superior temporal resolution compared to functional magnetic resonance imaging (fMRI) and better spatial resolution relative to electroencephalogram (EEG), positions fNIRS as a promising tool, particularly in identifying early cognitive impairments in PD patients (Oku and Sato, 2021;Pereira et al, 2023;Su et al, 2023). Current studies utilizing fNIRS have identified differences in frontal cortex activation in PD patients during motor tasks compared to healthy subjects (Feng et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Exploring the application and challenges of fNIRS technology in early detection of Parkinson’s disease

Hui,

Jiang,

Wang

et al. 2024

Front. Aging Neurosci.

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BackgroundParkinson’s disease (PD) is a prevalent neurodegenerative disorder that significantly benefits from early diagnosis for effective disease management and intervention. Despite advancements in medical technology, there remains a critical gap in the early and non-invasive detection of PD. Current diagnostic methods are often invasive, expensive, or late in identifying the disease, leading to missed opportunities for early intervention.ObjectiveThe goal of this study is to explore the efficiency and accuracy of combining fNIRS technology with machine learning algorithms in diagnosing early-stage PD patients and to evaluate the feasibility of this approach in clinical practice.MethodsUsing an ETG-4000 type near-infrared brain function imaging instrument, data was collected from 120 PD patients and 60 healthy controls. This cross-sectional study employed a multi-channel mode to monitor cerebral blood oxygen changes. The collected data were processed using a general linear model and β values were extracted. Subsequently, four types of machine learning models were developed for analysis: Support vector machine (SVM), K-nearest neighbors (K-NN), random forest (RF), and logistic regression (LR). Additionally, SHapley Additive exPlanations (SHAP) technology was applied to enhance model interpretability.ResultsThe SVM model demonstrated higher accuracy in differentiating between PD patients and control group (accuracy of 85%, f1 score of 0.85, and an area under the ROC curve of 0.95). SHAP analysis identified the four most contributory channels (CH) as CH01, CH04, CH05, and CH08.ConclusionThe model based on the SVM algorithm exhibited good diagnostic performance in the early detection of PD patients. Future early diagnosis of PD should focus on the Frontopolar Cortex (FPC) region.

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“…Compared with other brain functional imaging techniques, fNIRS has the following advantages: high temporal resolution (~10 Hz), good spatial resolution (2-3 cm), being non-invasive or non-traumatic, real-time monitoring, easy continuous and repeated measurement, low cost, miniaturization, portability, anti-motion artifacts, suitable for a wider range of individuals, and easy to combine with other techniques for multimodal functional imaging, including functional magnetic resonance imaging (fMRI), positron emission tomography (PET), magnetoencephalography (MEG), electroencephalography (EEG), event-related potential (ERP), or electromyography (EMG) (33,(35)(36)(37). fNIRS experiments can be carried out in the natural environment without constraints and large amplitude movement monitoring (38). Thus, given its technical properties, especially the anti-motor artifact property, fNIRS has merged as an ideal brain functional imaging techniques for detecting MNS activation.…”

Section: Introductionmentioning

confidence: 99%

Cortical activation of neuromuscular electrical stimulation synchronized mirror neuron rehabilitation strategies: an fNIRS study

et al. 2023

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BackgroundThe mirror neuron system (MNS) plays a key role in the neural mechanism underlying motor learning and neural plasticity. Action observation (AO), action execution (AE), and a combination of both, known as action imitation (AI), are the most commonly used rehabilitation strategies based on MNS. It is possible to enhance the cortical activation area and amplitude by combining traditional neuromuscular electrical stimulation (NMES) with other top-down and active rehabilitation strategies based on the MNS theory.ObjectiveThis study aimed to explore the cortical activation patterns induced by NMES synchronized with rehabilitation strategies based on MNS, namely NMES+AO, NMES+AE, and NMES+AI. In addition, the study aimed to assess the feasibility of these three novel rehabilitative treatments in order to provide insights and evidence for the design, implementation, and application of brain-computer interfaces.MethodsA total of 70 healthy adults were recruited from July 2022 to February 2023, and 66 of them were finally included in the analysis. The cortical activation patterns during NMES+AO, NMES+AE, and NMES+AI were detected using the functional Near-Infrared Spectroscopy (fNIRS) technique. The action to be observed, executed, or imitated was right wrist and hand extension, and two square-shaped NMES electrodes were placed on the right extensor digitorum communis. A block design was adopted to evaluate the activation intensity of the left MNS brain regions.ResultsGeneral linear model results showed that compared with the control condition, the number of channels significantly activated (PFDR < 0.05) in the NMES+AO, NMES+AE, and NMES+AI conditions were 3, 9, and 9, respectively. Region of interest (ROI) analysis showed that 2 ROIs were significantly activated (PFDR < 0.05) in the NMES+AO condition, including BA6 and BA44; 5 ROIs were significantly activated in the NMES+AE condition, including BA6, BA40, BA44, BA45, and BA46; and 6 ROIs were significantly activated in the NMES+AI condition, including BA6, BA7, BA40, BA44, BA45, and BA46.ConclusionThe MNS was activated during neuromuscular electrical stimulation combined with an AO, AE, and AI intervention. The synchronous application of NMES and mirror neuron rehabilitation strategies is feasible in clinical rehabilitation. The fNIRS signal patterns observed in this study could be used to develop brain-computer interface and neurofeedback therapy rehabilitation devices.

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Cortical activation and functional connectivity during locomotion tasks in Parkinson’s disease with freezing of gait

Cited by 4 publications

References 73 publications

Freezing of gait in Parkinson’s disease is related to imbalanced stopping-related cortical activity

Freezing of gait in Parkinson’s disease is related to imbalanced stopping-related cortical activity

Exploring the application and challenges of fNIRS technology in early detection of Parkinson’s disease

Cortical activation of neuromuscular electrical stimulation synchronized mirror neuron rehabilitation strategies: an fNIRS study

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