Neural Variability in the Prefrontal Cortex as a Reflection of Neural Flexibility and Stability in Patients With Parkinson Disease

Exploring Brain-Body Interactions in Parkinson's Disease: A Study on Dual-Task Performance

Parkinson's disease (PD) leads to impairments in cortical structures, resulting in motor and cognitive symptoms. Given the connection between brain structure deficits and physical symptoms in PD, assessing objective brain activity and body motion could provide valuable insights for PD assessment and understanding its underlying mechanisms. This study aimed to explore the connection between brain activity and body movement metrics in a group of individuals with PD and an age-matched healthy control (HC) group. The goal was to evaluate the feasibility of using brain and body motion measures for assessing PD. Participants from both groups underwent the Timed Up and Go (TUG) test under three conditions: simple TUG, cognitive dual-task TUG (CDTUG), and motor dual-task TUG (MDTUG). Key findings include: Both groups exhibited similar activation patterns in the prefrontal cortex (PFC) during the simple TUG, with motor performance differences observed in cadence. During CDTUG, both groups showed the highest PFC activation with more pronounced motor impairments, such as higher stride and step time. During MDTUG, the HC group exhibited significantly higher PFC activity compared to the PD group. While both groups had similar patterns of activation in PFC area while TUG and CDTUG, they showed distinct behaviour during MDTUG. These results suggest that motor and cognitive impairments in PD are more pronounced during complex activities. While MDTUG effectively differentiated between PD and HC groups, the findings indicate that both cognitive and motor dual-tasks are essential for comprehensive PD assessment.

Impact of hearing loss on brain signal variability in older adults under different auditory load conditions

Introduction

The moment-by-moment variability in brain signals, a newly recognized indicator, demonstrates both the adaptability of an individual's brain as a unique trait and the distribution of neural resources within that individual in response to constantly shifting task requirements. This study aimed to explore brain signal variability in older adults using oxyhemoglobin (HbO) variability derived from fNIRS during tasks with increasing signal-to-noise ratio (SNR) loads and to assess the effects of varying degrees of hearing loss on speech recognition performance and related brain signal variability patterns.

Methods

Eighty-one participants were categorized into three groups: healthy controls (n = 30, aged 65.5 ± 3.4), mild hearing loss (n = 25, aged 66.0 ± 3.7), and moderate to severe hearing loss (n = 26, aged 67.5 ± 3.7). Speech perception was tested under quiet, 5 dB SNR, and 0 dB SNR conditions.

Results

Results revealed that the brain signal variability increased with higher SNR loads in healthy older adults, indicating enhanced neural resource allocation with the SNR load. In contrast, we found that hearing loss reduced brain signal variability during speech recognition tasks, especially in noisy conditions, in the mild hearing loss and moderate to severe hearing loss groups, possibly indicating decreased neural processing efficiency. Additionally, a positive correlation between brain signal variability and speech recognition performance was observed in healthy control participants across all SNR conditions, suggesting that brain signal variability could dynamically respond to the precise level of auditory environment demands. However, this relationship was only significant at the 5 dB SNR condition in hearing loss groups.

Discussion

Taken together, this study underscores the significant impact of hearing loss on brain signal variability modulation in auditory cognitive tasks and highlights the need for further research to understand the underlying neural mechanisms.

A Knowledge-Driven Framework Discovers Brain ACtivation-Transition-Spectrum (ACTS) Features for Parkinson's Disease

Dopaminergic treatment has proved effective to Parkinson's disease (PD), but the conventional treatment assessment is human-administered and prone to intra- and inter-assessor variability. In this paper, we propose a knowledge-driven framework and discover that brain ACtivation-Transition-Spectrum (ACTS) features achieve effective quantified assessments of dopaminergic therapy in PD. Firstly, brain activities of fifty-one PD patients during clinical walking tests under the OFF and ON states (without and with dopaminergic medication) were measured with functional near-infrared spectroscopy (fNIRS). Then, brain ACTS features were formulated based on the medication-induced variations in temporal features of brain regional activation, transition features of brain hemodynamic states, and graph spectrum of brain functional connectivity. Afterwards, a prior selection algorithm was constructed based on recursive feature elimination and graph spectrum analysis for the selection of principal discriminative features. Further, linear discriminant analysis was conducted to predict the treatment-induced improvements. The results demonstrated that the proposed method decreased the misclassification probability from 42% to 16% in the evaluations of dopaminergic treatment and outperformed existing fNIRS-based methods. Therefore, the proposed method promises a quantified and objective approach for dopaminergic treatment assessment, and our brain ACTS features may serve as promising functional biomarkers for treatment evaluation.

Early screening of post-stroke fall risk: A simultaneous multimodal fNIRs-EMG study

BACKGROUND

Stroke is the third-leading cause of death and disability, and poststroke falls (PSF) are common at all stages after stroke and could even lead to injuries or death. Brain information from functional near-infrared spectroscopy (fNIRs) may precede conventional imaging and clinical symptoms but has not been systematically considered in PSF risk prediction. This study investigated the difference in brain activation between stroke patients and healthy subjects, and this study was aimed to explore fNIRs biomarkers for early screening of PSF risk by comparing the brain activation in patients at and not at PSF risk.

METHODS

In this study, we explored the differences in brain activation and connectivity between stroke and healthy subjects by synchronizing the detection of fNIRs and EMG tests during simple (usual sit-to-stand) and difficult tasks (sit-to-stand based on EMG feedback). Thereby further screened for neuroimaging biomarkers for early prediction of PSF risk by comparing brain activation variability in poststroke patients at and not at fall risk during simple and difficult tasks. The area under the ROC curve (AUROC), sensitivity, and specificity were used to compare the diagnostic effect.

RESULTS

A total of 40 patients (22 not at and 18 at PSF risk) and 38 healthy subjects were enrolled. As the difficulty of standing task increased, stroke patients compared with healthy subjects further increased the activation of the unaffected side of supplementary motor area (H-SMA) and dorsolateral prefrontal cortex-Brodmann area 46 (H-DLFC-BA46) but were unable to increase functional connectivity (Group*Task: p < 0.05). More importantly, the novel finding showed that hyperactivation of the H-SMA during a simple standing task was a valid fNIRs predictor of PSF risk [AUROC 0.74, p = 0.010, sensitivity 77.8%, specificity 63.6%].

CONCLUSIONS

This study provided novel evidence that fNIR-derived biomarkers could early predict PSF risk that can facilitate the widespread use of real-time assessment tools in early screening and rehabilitation. Meanwhile, this study demonstrated that the higher brain activation and inability to increase the brain functional connectivity in stroke patients during difficult task indicated the inefficient use of brain resources.

Dual-Task Performance and Brain Morphologic Characteristics in Parkinson's Disease

INTRODUCTION

Parkinson's disease (PD) reduces an individual's capacity for automaticity which limits their ability to perform two tasks simultaneously, negatively impacting daily function. Understanding the neural correlates of dual tasks (DTs) may pave the way for targeted therapies. To better understand automaticity in PD, we aimed to explore whether individuals with differing DT performances possessed differences in brain morphologic characteristics.

METHODS

Data were obtained from 34 individuals with PD and 47 healthy older adults including (1) demographics (age, sex), (2) disease severity (Movement Disorder Society - Unified Parkinson's Disease Rating Scale [MDS-UPDRS], Hoehn and Yahr, levodopa equivalent daily dose [LEDD]), (3) cognition (Montreal Cognitive Assessment), (4) LEDD, (5) single-task and DT performance during a DT-timed-up-and-go test utilizing a serial subtraction task, and (6) cortical thicknesses and subcortical volumes obtained from volumetric MRI. Participants were categorized as low or high DT performers if their combined DT effect was greater than the previously determined mean value for healthy older adults (μ = -74.2). Nonparametric testing using Quade's ANCOVA was conducted to compare cortical thicknesses and brain volumes between the highDT and lowDT groups while controlling for covariates: age, sex, MDS-UPDRS part III, LEDD, and intracranial volume. Secondarily, similar comparisons were made between the healthy older adult group and the highDT and lowDT groups. Lastly, a hierarchical linear regression model was conducted regressing combined DT effect on covariates (block one) and cortical thicknesses (block 2) in stepwise fashion.

RESULTS

The highDT group had thicker cortices than the lowDT group in the right primary somatosensory cortex (p = 0.001), bilateral primary motor cortices (p ≤ 0.001, left; p = 0.002, right), bilateral supplementary motor areas (p = 0.001, left; p < 0.001, right), and mean of the bilateral hemispheres (p = 0.001, left; p < 0.001, right). Of note, left primary cortex thickness (p = 0.002), left prefrontal cortex thickness (p < 0.001), and right supplementary motor area thickness (p = 0.003) differed when adding a healthy comparison group. Additionally, the regression analysis found that the left paracentral lobule thickness explained 20.8% of the variability in combined DT effect (p = 0.011) beyond the influence of covariates.

CONCLUSIONS

These results suggest regions underlying DT performance, specifically, a convergence of neural control relying on sensorimotor integration, motor planning, and motor activation to achieve higher levels of DT performance for individuals with PD.

INTRODUCTION

Parkinson's disease (PD) reduces an individual's capacity for automaticity which limits their ability to perform two tasks simultaneously, negatively impacting daily function. Understanding the neural correlates of dual tasks (DTs) may pave the way for targeted therapies. To better understand automaticity in PD, we aimed to explore whether individuals with differing DT performances possessed differences in brain morphologic characteristics.

METHODS

Data were obtained from 34 individuals with PD and 47 healthy older adults including (1) demographics (age, sex), (2) disease severity (Movement Disorder Society - Unified Parkinson's Disease Rating Scale [MDS-UPDRS], Hoehn and Yahr, levodopa equivalent daily dose [LEDD]), (3) cognition (Montreal Cognitive Assessment), (4) LEDD, (5) single-task and DT performance during a DT-timed-up-and-go test utilizing a serial subtraction task, and (6) cortical thicknesses and subcortical volumes obtained from volumetric MRI. Participants were categorized as low or high DT performers if their combined DT effect was greater than the previously determined mean value for healthy older adults (μ = -74.2). Nonparametric testing using Quade's ANCOVA was conducted to compare cortical thicknesses and brain volumes between the highDT and lowDT groups while controlling for covariates: age, sex, MDS-UPDRS part III, LEDD, and intracranial volume. Secondarily, similar comparisons were made between the healthy older adult group and the highDT and lowDT groups. Lastly, a hierarchical linear regression model was conducted regressing combined DT effect on covariates (block one) and cortical thicknesses (block 2) in stepwise fashion.

RESULTS

The highDT group had thicker cortices than the lowDT group in the right primary somatosensory cortex (p = 0.001), bilateral primary motor cortices (p ≤ 0.001, left; p = 0.002, right), bilateral supplementary motor areas (p = 0.001, left; p < 0.001, right), and mean of the bilateral hemispheres (p = 0.001, left; p < 0.001, right). Of note, left primary cortex thickness (p = 0.002), left prefrontal cortex thickness (p < 0.001), and right supplementary motor area thickness (p = 0.003) differed when adding a healthy comparison group. Additionally, the regression analysis found that the left paracentral lobule thickness explained 20.8% of the variability in combined DT effect (p = 0.011) beyond the influence of covariates.

CONCLUSIONS

These results suggest regions underlying DT performance, specifically, a convergence of neural control relying on sensorimotor integration, motor planning, and motor activation to achieve higher levels of DT performance for individuals with PD.

The neurophysiological brain-fingerprint of Parkinson's disease

BACKGROUND

Research in healthy young adults shows that characteristic patterns of brain activity define individual "brain-fingerprints" that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson's disease (PD).

METHODS

We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s.

FINDINGS

The arrhythmic spectral components of cortical activity in patients with Parkinson's disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson's brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson's symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology.

INTERPRETATION

The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson's disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets.

FUNDING

Data collection and sharing for this project was provided by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer's Disease (PREVENT-AD; release 6.0) program, the Cambridge Centre for Aging Neuroscience (Cam-CAN), and the Open MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311).

The Effect of Gua Sha Therapy on Pain in Parkinson's Disease: a Randomized Controlled Trial

Purpose

Pain is a common yet undertreated symptom of Parkinson's disease (PD). This study investigated the effect of Gua Sha therapy on pain in patients with PD.

Patients and Methods

A total of 56 PD patients with pain were randomized into either the experimental group (n=28), receiving 12 sessions of Gua Sha therapy, or the control group (n=28) without additional treatment. Participants underwent assessment at baseline, after the twelfth invention, and at the 2-month follow-up timepoints. The primary outcome was KPPS and VAS. Secondary outcomes included UPDRS I-III, PDSS-2, HADS, PDQ-39, and blood biomarkers (5-HT, IL-8, IL-10).

Results

The experimental group reported a significant improvement in pain severity, motor functions, affective disorder, and sleep quality (P < 0.05). Furthermore, increasing trends in both 5-HT and IL-10, as well as decreasing trends in IL-8 were observed. No serious adverse events occurred.

Conclusion

The preliminary findings suggest that Gua Sha therapy may be effective and safe for alleviating pain and improving other disease-related symptoms in PD patients.

Effects of Age on the Auditory Cortex During Speech Perception in Noise: Evidence From Functional Near-Infrared Spectroscopy

OBJECTIVES

Age-related speech perception difficulties may be related to a decline in central auditory processing abilities, particularly in noisy or challenging environments. However, how the activation patterns related to speech stimulation in different noise situations change with normal aging has yet to be elucidated. In this study, we aimed to investigate the effects of noisy environments and aging on patterns of auditory cortical activation.

DESIGN

We analyzed the functional near-infrared spectroscopy signals of 20 young adults, 21 middle-aged adults, and 21 elderly adults, and evaluated their cortical response patterns to speech stimuli under five different signal to noise ratios (SNRs). In addition, we analyzed the behavior score, activation intensity, oxyhemoglobin variability, and dominant hemisphere, to investigate the effects of aging and noisy environments on auditory cortical activation.

RESULTS

Activation intensity and oxyhemoglobin variability both showed a decreasing trend with aging at an SNR of 0 dB; we also identified a strong correlation between activation intensity and age under this condition. However, we observed an inconsistent activation pattern when the SNR was 5 dB. Furthermore, our analysis revealed that the left hemisphere may be more susceptible to aging than the right hemisphere. Activation in the right hemisphere was more evident in older adults than in the left hemisphere; in contrast, younger adults showed leftward lateralization.

CONCLUSIONS

Our analysis showed that with aging, auditory cortical regions gradually become inflexible in noisy environments. Furthermore, changes in cortical activation patterns with aging may be related to SNR conditions, and that understandable speech with a low SNR ratio but still understandable may induce the highest level of activation. We also found that the left hemisphere was more affected by aging than the right hemisphere in speech perception tasks; the left-sided dominance observed in younger individuals gradually shifted to the right hemisphere with aging.

Role of exercise in modulating prefrontal cortical activation for improved gait and cognition in Parkinson's disease patients

PURPOSE

This narrative review evaluated the impact of exercise on gait and cognitive functions in patients with Parkinson's disease (PD), focusing on prefrontal cortical (PFC) activation assessed using near-infrared spectroscopy (NIRS).

METHODS

A literature search was conducted in the PubMed and Web of Science databases using keywords such as "Parkinson's disease," "gait," "cognitive functions," "exercise," and "NIRS," focusing on publications from the last decade. Studies measuring PFC activity using NIRS during gait tasks in patients with PD were selected.

RESULTS

The review indicated that patients with PD demonstrate increased PFC activity during gait tasks compared to healthy controls, suggesting a greater cognitive demand for movement control. Exercise has been shown to enhance neural efficiency, thus improving gait and cognitive functions.

CONCLUSION

Exercise is crucial for improving gait and cognitive functions in patients with PD through increased PFC activation. This emphasizes the importance of incorporating exercise into PD management plans and highlights the need for further studies on its long-term effects and the neurobiological mechanisms underlying its benefits, with the aim of optimizing therapeutic strategies and improving patients' quality of life.

Cortical thickness moderates intraindividual variability in prefrontal cortex activation patterns of older adults during walking

OBJECTIVE

Increased intraindividual variability (IIV) in behavioral and cognitive performance is a risk factor for adverse outcomes but research concerning hemodynamic signal IIV is limited. Cortical thinning occurs during aging and is associated with cognitive decline. Dual-task walking (DTW) performance in older adults has been related to cognition and neural integrity. We examined the hypothesis that reduced cortical thickness would be associated with greater increases in IIV in prefrontal cortex oxygenated hemoglobin (HbO2) from single tasks to DTW in healthy older adults while adjusting for behavioral performance.

METHOD

Participants were 55 healthy community-dwelling older adults (mean age = 74.84, standard deviation (SD) = 4.97). Structural MRI was used to quantify cortical thickness. Functional near-infrared spectroscopy (fNIRS) was used to assess changes in prefrontal cortex HbO2 during walking. HbO2 IIV was operationalized as the SD of HbO2 observations assessed during the first 30 seconds of each task. Linear mixed models were used to examine the moderation effect of cortical thickness throughout the cortex on HbO2 IIV across task conditions.

RESULTS

Analyses revealed that thinner cortex in several regions was associated with greater increases in HbO2 IIV from the single tasks to DTW (ps < .02).

CONCLUSIONS

Consistent with neural inefficiency, reduced cortical thickness in the PFC and throughout the cerebral cortex was associated with increases in HbO2 IIV from the single tasks to DTW without behavioral benefit. Reduced cortical thickness and greater IIV of prefrontal cortex HbO2 during DTW may be further investigated as risk factors for developing mobility impairments in aging.

The neurophysiological brain-fingerprint of Parkinson's disease

In this study, we investigate the clinical potential of brain-fingerprints derived from electrophysiological brain activity for diagnostics and progression monitoring of Parkinson's disease (PD). We obtained brain-fingerprints from PD patients and age-matched healthy controls using short, task-free magnetoencephalographic recordings. The rhythmic components of the individual brain-fingerprint distinguished between patients and healthy participants with approximately 90% accuracy. The most prominent cortical features of the Parkinson's brain-fingerprint mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also show that Parkinson's disease stages can be decoded directly from cortical neurophysiological activity. Additionally, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology. We further demonstrate that the arrhythmic components of cortical activity are more variable over short periods of time in patients with Parkinson's disease than in healthy controls, making individual differentiation between patients based on these features more challenging and explaining previous negative published results. Overall, we outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and clinical staging of Parkinson's disease. For this reason, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification and to the improved identification and testing of therapeutic neurostimulation targets.

Lower back muscle activity during weight-shifting is affected by ageing and dual-tasking

PURPOSE

Postural control deteriorates with age, especially under dual-task conditions. It is currently unknown how a challenging virtual reality weight-shifting task affects lower back muscle activity. Hence, this study investigated erector spinae neuromuscular control during mediolateral weight-shifting as part of an exergame during single- (ST) and dual-task (DT) conditions in young and older adults.

METHODS

Seventeen young and 17 older adults performed mediolateral weight-shifts while hitting virtual wasps in a virtual environment with and without a serial subtraction task (DT). Center of mass position was recorded in real-time using 3D motion capturing. Electromyography recorded bilateral activation of the lumbar longissimus and iliocostalis muscles.

RESULTS

Weight-shifting (p < 0.03) and targeting the wasps (p < 0.005) deteriorated with age and DT. Relative muscle activation during both quiet stance and weight-shifting increased with age, while the DT-effect did not differ consistently between age-groups. However, bilateral muscle co-contraction decreased with DT in young adults only. When switching direction and targeting the wasps, variability of muscle activation increased with age and DT and proved related to worse targeting performance. These effects were mainly visible at the non-dominant body side.

CONCLUSION

Older adults showed a higher erector spinae muscle contribution to perform weight-shifts with increased variability at the end of a shift, whereby muscle activity was modulated less well in older than in young adults in response to DT. Hence, the current findings point to the potential for developing postural training in which older adults learn to fine-tune trunk muscle activity to improve weight-shifting and reduce fall risk.

Toward a Multi-Modal Brain-Body Assessment in Parkinson's Disease: A Systematic Review in fNIRS

Parkinson's disease (PD) causes impairments in cortical structures leading to motor and cognitive symptoms. While common disease management and treatment strategies mainly depend on the subjective assessment of clinical scales and patients' diaries, research in recent years has focused on advances in automatic and objective tools to help with diagnosing PD and determining its severity. Due to the link between brain structure deficits and physical symptoms in PD, objective brain activity and body motion assessment of patients have been studied in the literature. This study aimed to explore the relationship between brain activity and body motion measures of people with PD to look at the feasibility of diagnosis or assessment of PD using these measures. In this study, we summarised the findings of 24 selected papers from the complete literature review using the Scopus database. Selected studies used both brain activity recording using functional near-infrared spectroscopy (fNIRS) and motion assessment using sensors for people with PD in their experiments. Results include 1) the most common study protocol is a combination of single tasks. 2) Prefrontal cortex is mostly studied region of interest in the literature. 3) Oxygenated haemoglobin (HbO 2) concentration is the predominant metric utilised in fNIRS, compared to deoxygenated haemoglobin (HHb). 4) Motion assessment in people with PD is mostly done with inertial measurement units (IMUs) and electronic walkway. 5) The relationship between brain activity and body motion measures is an important factor that has been neglected in the literature.

An fNIRS-Based Dynamic Functional Connectivity Analysis Method to Signify Functional Neurodegeneration of Parkinson's Disease

Parkinson's disease (PD) is a prevalent brain disorder, and PD diagnosis is crucial for treatment. Existing methods for PD diagnosis are mainly focused on behavior analysis, while the functional neurodegeneration of PD has not been well investigated. This paper proposes a method to signify functional neurodegeneration of PD with dynamic functional connectivity analysis. A functional near-infrared spectroscopy (fNIRS)-based experimental paradigm was designed to capture brain activation from 50 PD patients and 41 age-matched healthy controls in clinical walking tests. Dynamic functional connectivity was constructed with sliding-window correlation analysis, and k-means clustering was applied to generate the key brain connectivity states. Dynamic state features including state occurrence probability, state transition percentage and state statistical features were extracted to quantify the variations of brain functional networks. A support vector machine was trained to classify PD patients and healthy controls. Statistical analysis was conducted to investigate the difference between PD patients and healthy controls as well as the relationship between dynamic state features and the MDS-UPDRS sub-score of gait. The results showed that PD patients had a higher probability of transiting to brain connectivity states with high levels of information transmission compared with healthy controls. The MDS-UPDRS sub-score of gait and the dynamics state features showed a significant correlation. Moreover, the proposed method had better classification performances than the available fNIRS-based methods in terms of accuracy and F1 score. Thus, the proposed method well signified functional neurodegeneration of PD, and the dynamic state features may serve as promising functional biomarkers for PD diagnosis.

Changes in cortical activation during upright stance in individuals with chronic low back pain: An fNIRS study

Introduction

Postural control deficits are a potential cause of persistent and recurrent pain in patients with chronic low back pain (CLBP). Although some studies have confirmed that the dorsolateral prefrontal cortex (DLPFC) contributes to pain regulation in CLBP, its role in the postural control of patients with CLBP remains unclear. Therefore, this study aimed to investigate the DLPFC activation of patients with CLBP and healthy controls under different upright stance task conditions.

Methods

Twenty patients with CLBP (26.50 ± 2.48 years) and 20 healthy controls (25.75 ± 3.57 years) performed upright stance tasks under three conditions: Task-1 was static balance with eyes open; Task-2 was static balance with eyes closed; Task-3 involved dynamic balance on an unstable surface with eyes open. A wireless functional near-infrared spectroscopy (fNIRS) system measured cortical activity, including the bilateral DLPFC, pre-motor cortex (PMC) and supplementary motor area (SMA), the primary motor cortex (M1), the primary somatosensory cortex (S1), and a force platform measured balance parameters during upright stance.

Results

The two-way repeated measures ANOVA results showed significant interaction in bilateral PMC/SMA activation. Moreover, patients with CLBP had significantly increased right DLPFC activation and higher sway 32 area and velocity than healthy controls during upright stance.

Discussion

Our results imply that PMC/SMA and DLPFC maintain standing balance. The patients with CLBP have higher cortical activity and upright stance control deficits, which may indicate that the patients with CLBP have low neural efficiency and need more motor resources to maintain balance.

Neural activation in the prefrontal cortex during the digital clock drawing test measured with functional near-infrared spectroscopy in early stage Parkinson's disease

INTRODUCTION

The clock drawing test (CDT) is a neuropsychological test for the screening of global cognitive functioning. The test requires use of multiple cognitive domains including executive functions, visuospatial abilities and semantic memory and can be a suitable tool for screening cognitive decline in participants in the early stages of Parkinson's Disease (PD). Behavioral performance on the CDT has been studied in depth, however, neural activation during real-time performance has not been extensively investigated. In this study we explored changes in prefrontal cortex (PFC) activation during the performance of CDT in participants with PD compared to healthy controls (HC) and assessed the correlations between PFC activation and CDT performance.

METHODS

The study included 60 participants, 29 PD and 31 HC participants whom performed a digital CDT (DCTclock) in conjunction with a Functional Near-Infrared Spectroscopy (fNIRS) system measuring neural activation in the PFC.

RESULTS

HbO2 signals derived from the fNIRS during the CDT revealed that PD participants showed more moderate slopes than the HC in the right hemisphere in the command (p = 0.042) and copy task (p = 0.009). Better score on the measurement of information processing correlated with steeper right hemisphere HbO2 slope in the copy task in the PD group (p = 0.003).

CONCLUSION

Our results reflect slower PFC activation in participants with PD which correlates with behavioral measures. In addition, the findings of the study indicate the importance of performing the CDT copy task condition that detect early cognitive decline in participants with PD.

fNIRS-based brain state transition features to signify functional degeneration after Parkinson's disease

OBJECTIVE

Parkinson's disease (PD) is a common neurodegenerative brain disorder, and early diagnosis is of vital importance for treatment. Existing methods are mainly focused on behavior examination, while the functional neurodegeneration after PD has not been well explored. This paper aims to investigate the brain functional variation of PD patients in comparison with healthy controls.

APPROACH

In this work, we propose brain hemodynamic states and state transition features to signify functional degeneration after PD. Firstly, a functional near-infrared spectroscopy (fNIRS)-based experimental paradigm was designed to capture brain activation during dual-task walking from PD patients and healthy controls. Then, three brain states, named expansion, contraction, and intermediate states, were defined with respect to the oxyhemoglobin and deoxyhemoglobin responses. After that, two features were designed from a constructed transition factor and concurrent variations of oxy- and deoxy-hemoglobin over time, to quantify the transitions of brain states. Further, a support vector machine classifier was trained with the proposed features to distinguish PD patients and healthy controls.

RESULTS

Experimental results showed that our method with the proposed brain state transition features achieved classification accuracy of 0:8200 and F score of 0:9091, and outperformed existing fNIRS-based methods. Compared with healthy controls, PD patients had significantly smaller transition acceleration and transition angle.

SIGNIFICANCE

The proposed brain state transition features well signify functional degeneration of PD patients and may serve as promising functional biomarkers for PD diagnosis.

Network-Based Transcranial Direct Current Stimulation May Modulate Gait Variability in Young Healthy Adults

Purpose

Previous studies have linked gait variability to resting-state functional connectivity between the dorsal attention network (DAN) and the default network (DN) in the brain. The purpose of this study was to examine the effects of a novel transcranial direct current stimulation (tDCS) paradigm designed to simultaneously facilitate the excitability of the DAN and suppress the excitability of the DN (i.e., DAN+/DN-tDCS) on gait variability and other gait characteristics in young healthy adults.

Methods

In this double-blinded randomized and sham-controlled study, 48 healthy adults aged 22 ± 2 years received one 20-min session of DAN+/DN-tDCS (n = 24) or no stimulation (the Sham group, n = 24). Immediately before and after stimulation, participants completed a gait assessment under three conditions: walking at self-selected speed (i.e., normal walking), walking as fast as possible (i.e., fast walking), and walking while counting backward (i.e., dual-task walking). Primary outcomes included gait stride time variability and gait stride length variability in normal walking conditions. Secondary outcomes include gait stride time and length variability in fast and dual-task conditions, and other gait metrics derived from the three walking conditions.

Results

Compared to the Sham group, DAN+/DN-tDCS reduced stride length variability in normal and fast walking conditions, double-limb support time variability in fast and dual-task walking conditions, and step width variability in fast walking conditions. In contrast, DAN+/DN-tDCS did not alter average gait speed or the average value of any other gait metrics as compared to the sham group.

Conclusion

In healthy young adults, a single exposure to tDCS designed to simultaneously modulate DAN and DN excitability reduced gait variability, yet did not alter gait speed or other average gait metrics, when tested just after stimulation. These results suggest that gait variability may be uniquely regulated by these spatially-distinct yet functionally-connected cortical networks. These results warrant additional research on the short- and longer-term effects of this type of network-based tDCS on the cortical control of walking in younger and older populations.