Executive control of walking in people with Parkinson’s disease with freezing of gait

Background: Walking abnormalities in people with Parkinson’s disease (PD) are characterized by a shift in locomotor control from healthy automaticity to compensatory prefrontal executive control. Indirect measures of automaticity of walking (e.g., step-to-step variability and dual-task cost) suggest that freezing of gait (FoG) may be associated with reduced automaticity of walking. However, the influence of FoG status on actual prefrontal cortex (PFC) activity during walking remains unclear. Objective: To investigate the influence of FoG status on automaticity of walking in people with PD. Methods: Forty-seven people with PD were distributed into two groups based on FoG status, which was assessed by the New Freezing of Gait Questionnaire: PD-FoG (n=23; UPDRS-III=35) and PD+FoG (n=24; UPDRS-III=43.1). Participants walked over a 9m straight path (with a 180° turn at each end) for 80s. Two conditions were tested Off medication: single- and dual-task walking (i.e., with a concomitant cognitive task). A portable functional near-infrared spectroscopy system recorded PFC activity while walking (including turns). Wearable inertial sensors were used to calculate spatiotemporal gait parameters. Results: PD+FoG had greater PFC activation during both single and dual-task walking than PD-FoG (p=0.031). There were no differences in gait between PD-FoG and PD+FoG. Both groups decreased gait speed (p=0.029) and stride length (p<0.001) during dual-task walking compared to single-task walking. Conclusions: These findings suggest that PD+FoG have reduced automaticity of walking, even in absence of FoG episodes. PFC activity while walking seems to be more sensitive than gait measures in identifying reduction in automaticity of walking in PD+FoG

Performance Improvement for Detecting Brain Function Using fNIRS: A Multi-Distance Probe Configuration With PPL Method

To improve the spatial resolution of imaging and get more effective brain function information, a multi-distance probe configuration with three distances (28.2, 40, and 44.7 mm) and 52 channels is designed. At the same time, a data conversion method of modified Beer–Lambert law (MBLL) with partial pathlength (PPL) is proposed. In the experiment, three kinds of tasks, grip of left hand, grip of right hand, and rest, are performed with eight healthy subjects. First, with a typical single-distance probe configuration (30 mm, 24 channels), the feasibility of the proposed MBLL with PPL is preliminarily validated. Further, the characteristic of the proposed method is evaluated with the multi-distance probe configuration. Compared with MBLL with differential pathlength factor (DPF), the proposed MBLL with PPL is able to acquire more obvious concentration change and can achieve higher classification accuracy of the three tasks. Then, with the proposed method, the performance of the multi-distance probe configuration is discussed. Results show that, compared with a single distance, the combination of the three distances has better spatial resolution and could explore more accurate brain activation information. Besides, the classification accuracy of the three tasks obtained with the combination of three distances is higher than that of any combination of two distances. Also, with the combination of the three distances, the two-class classification between different tasks is carried out. Both theory and experimental results demonstrate that, using multi-distance probe configuration and the MBLL with PPL method, the performance of brain function detected by NIRS can be improved

帯状疱疹後神経痛患者における右背外側前頭前野の血行動態の障害は、プラシーボ効果の障害および臨床症状に関与する

富山大学・富医薬博甲第323号・日比 大亮・2020/03/24公表論文IBRO Reports, Volume 8, June 2020, Pages 56-64, https://doi.org/10.1016/j.ibror.2020.01.003富山大

Transient increase in systemic interferences in the superficial layer and its influence on event-related motor tasks: a functional near-infrared spectroscopy study

Abstract. Functional near-infrared spectroscopy (fNIRS) is a widely utilized neuroimaging tool in fundamental neuroscience research and clinical investigation. Previous research has revealed that task-evoked systemic artifacts mainly originating from the superficial-tissue may preclude the identification of cerebral activation during a given task. We examined the influence of such artifacts on event-related brain activity during a brisk squeezing movement. We estimated task-evoked superficial-tissue hemodynamics from short source–detector distance channels (15 mm) by applying principal component analysis. The estimated superficial-tissue hemodynamics exhibited temporal profiles similar to the canonical cerebral hemodynamic model. Importantly, this task-evoked profile was also observed in data from a block design motor experiment, suggesting a transient increase in superficial-tissue hemodynamics occurs following motor behavior, irrespective of task design. We also confirmed that estimation of event-related cerebral hemodynamics was improved by a simple superficial-tissue hemodynamic artifact removal process using 15-mm short distance channels, compared to the results when no artifact removal was applied. Thus, our results elucidate task design-independent characteristics of superficial-tissue hemodynamics and highlight the need for the application of superficial-tissue hemodynamic artifact removal methods when analyzing fNIRS data obtained during event-related motor tasks

Current state and future prospects of EEG and fNIRS in robot-assisted gait rehabilitation : a brief review

Gait and balance impairments are frequently considered as the most significant concerns among individuals suffering from neurological diseases. Robot-assisted gait training (RAGT) has shown to be a promising neurorehabilitation intervention to improve gait recovery in patients following stroke or brain injury by potentially initiating neuroplastic changes. However, the neurophysiological processes underlying gait recovery through RAGT remain poorly understood. As non-invasive, portable neuroimaging techniques, electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) provide new insights regarding the neurophysiological processes occurring during RAGT by measuring different perspectives of brain activity. Due to spatial information about changes in cortical activation patterns and the rapid temporal resolution of bioelectrical changes, more features correlated with brain activation and connectivity can be identified when using fused EEG-fNIRS, thus leading to a detailed understanding of neurophysiological mechanisms underlying motor behavior and impairments due to neurological diseases. Therefore, multi-modal integrations of EEG-fNIRS appear promising for the characterization of neurovascular coupling in brain network dynamics induced by RAGT. In this brief review, we surveyed neuroimaging studies focusing specifically on robotic gait rehabilitation. While previous studies have examined either EEG or fNIRS with respect to RAGT, a multi-modal integration of both approaches is lacking. Based on comparable studies using fused EEG-fNIRS integrations either for guiding non-invasive brain stimulation (NIBS) or as part of brain-machine interface (BMI) paradigms, the potential of this methodologically combined approach in RAGT is discussed. Future research directions and perspectives for targeted, individualized gait recovery that optimize the outcome and efficiency of RAGT in neurorehabilitation were further derived

Adaptive yoga versus low-impact exercise for adults with chronic acquired brain injury: a pilot randomized control trial protocol

BackgroundEach year, millions of Americans sustain acquired brain injuries (ABI) which result in functional impairments, such as poor balance and autonomic nervous system (ANS) dysfunction. Although significant time and energy are dedicated to reducing functional impairment in acute phase of ABI, many individuals with chronic ABI have residual impairments that increase fall risk, decrease quality of life, and increase mortality. In previous work, we have found that yoga can improve balance in adults with chronic (i.e., ≥6 months post-injury) ABI. Moreover, yoga has been shown to improve ANS and brain function in healthy adults. Thus, adults with chronic ABI may show similar outcomes. This protocol details the methods used to examine the effects of a group yoga program, as compared to a group low-impact exercise, on primary and secondary outcomes in adults with chronic ABI.MethodsThis study is a single-blind randomized controlled trial comparing group yoga to group low-impact exercise. Participants must be ≥18 years old with chronic ABI and moderate balance impairments. Group yoga and group exercise sessions occur twice a week for 1 h for 8 weeks. Sessions are led by trained adaptive exercise specialists. Primary outcomes are balance and ANS function. Secondary outcomes are brain function and structure, cognition, quality of life, and qualitative experiences. Data analysis for primary and most secondary outcomes will be completed with mixed effect statistical methods to evaluate the within-subject factor of time (i.e., pre vs. post intervention), the between-subject factor of group (yoga vs. low-impact exercise), and interaction effects. Deductive and inductive techniques will be used to analyze qualitative data.DiscussionDue to its accessibility and holistic nature, yoga has significant potential for improving balance and ANS function, along with other capacities, in adults with chronic ABI. Because there are also known benefits of exercise and group interaction, this study compares yoga to a similar, group exercise intervention to explore if yoga has a unique benefit for adults with chronic ABI.Clinical trial registration:ClinicalTrials.gov, NCT05793827. Registered on March 31, 2023

A consensus guide to using functional near-infrared spectroscopy in posture and gait research

BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is increasingly used in the field of posture and gait to investigate patterns of cortical brain activation while people move freely. fNIRS methods, analysis and reporting of data vary greatly across studies which in turn can limit the replication of research, interpretation of findings and comparison across works. RESEARCH QUESTION AND METHODS: Considering these issues, we propose a set of practical recommendations for the conduct and reporting of fNIRS studies in posture and gait, acknowledging specific challenges related to clinical groups with posture and gait disorders. RESULTS: Our paper is organized around three main sections: 1) hardware set up and study protocols, 2) artefact removal and data processing and, 3) outcome measures, validity and reliability; it is supplemented with a detailed checklist. SIGNIFICANCE: This paper was written by a core group of members of the International Society for Posture and Gait Research and posture and gait researchers, all experienced in fNIRS research, with the intent of assisting the research community to lead innovative and impactful fNIRS studies in the field of posture and gait, whilst ensuring standardization of research

Biomedical Signal Analysis of the Brain and Systemic Physiology

Near-infrared spectroscopy (NIRS) is a non-invasive and easy-to-use diagnostic technique that enables real-time tissue oxygenation measurements applied in various contexts and for different purposes. Continuous monitoring with NIRS of brain oxygenation, for example, in neonatal intensive care units (NICUs), is essential to prevent lifelong disabilities in newborns. Moreover, NIRS can be applied to observe brain activity associated with hemodynamic changes in blood flow due to neurovascular coupling. In the latter case, NIRS contributes to studying cognitive processes allowing to conduct experiments in natural and socially interactive contexts of everyday life. However, it is essential to measure systemic physiology and NIRS signals concurrently. The combination of brain and body signals enables to build sophisticated systems that, for example, reduce the false alarms that occur in NICUs. Furthermore, since fNIRS signals are influenced by systemic physiology, it is essential to understand how the latter impacts brain signals in functional studies. There is an interesting brain body coupling that has rarely been investigated yet. To take full advantage of these brain and body data, the aim of this thesis was to develop novel approaches to analyze these biosignals to extract the information and identify new patterns, to solve different research or clinical questions. For this the development of new methodological approaches and sophisticated data analysis is necessary, because often the identification of these patterns is challenging or not possible with traditional methods. In such cases, automatic machine learning (ML) techniques are beneficial. The first contribution of this work was to assess the known systemic physiology augmented (f)NIRS approach for clinical use and in everyday life. Based on physiological and NIRS signals of preterm infants, an ML-based classification system has been realized, able to reduce the false alarms in NICUs by providing a high sensitivity rate. In addition, the SPA-fNIRS approach was further applied in adults during a breathing task. The second contribution of this work was the advancement of the classical fNIRS hyperscanning method by adding systemic physiology measures. For this, new biosignal analyses in the time-frequency domain have been developed and tested in a simple nonverbal synchrony task between pairs of subjects. Furthermore, based on SPA-fNIRS hyperscanning data, another ML-based system was created, which is able distinguish familiar and unfamiliar pairs with high accuracy. This approach enables to determine the strength of social bonds in a wide range of social interaction contexts. In conclusion, we were the first group to perform a SPA-fNIRS hyperscanning study capturing changes in cerebral oxygenation and hemodynamics as well as systemic physiology in two subjects simultaneously. We applied new biosignals analysis methods enabling new insights into the study of social interactions. This work opens the door to many future inter-subjects fNIRS studies with the benefit of assessing the brain-to-brain, the brain-to-body, and body-to-body coupling between pairs of subjects

NNeMo (Neonatal NeuroMonitor) - a hybrid optical system to characterize perfusion and metabolism in the newborn brain

Premature birth, defined as a gestational period less than 37 weeks, occurs in 8% of infants born in Canada. These births are associated with a higher risk of developing neurological complications. Infants born with very low birth weights (VLBW, \u3c 1500 g) experience cognitive or behavioural deficits at a rate of 40-50%, while a further 5-10% develop major disorders such as cerebral palsy. The likelihood of injury increases with a shorter gestational period and/or a lower birthweight. Intraventricular hemorrhaging (IVH) occurs in 20-25% of VLBW infants, characterized by bleeding in the germinal matrix and surrounding white matter. This highly vascularized region is particularly susceptible to bleeds due to underdeveloped cerebrovascular structures. Severe IVH causes an inflammatory response and subsequent obstruction of cerebrospinal fluid (CSF) drainage, resulting in enlargement of the brain’s ventricles, referred to as post-hemorrhagic ventricular dilatation (PHVD). PHVD increases intracranial pressure and can result in compression/damage of brain tissue. Diagnosis of IVH and PHVD is regularly performed using cranial ultrasound. Clinicians can visually assess and grade hemorrhaging/ventricle dilatation. Ultrasound, however, is limited in its ability to continuously monitor and only detects irreversible damage. NNeMo (Neonatal NeuroMonitor) is a hybrid optical device combining diffuse correlation (DCS) and near-infrared spectroscopy (NIRS) to simultaneous monitor cerebral blood flow (CBF) and metabolism at the bedside. DCS analyzes light scatter from red blood cells to infer their motion and calculate CBF while NIRS exploits light absorption properties to quantify changes in oxidized cytochrome c oxidase (oxCCO), a direct marker of energy metabolism. System validation was presented in a piglet model of neonatal hypoxia-ischemia. Clinical translation of NNeMo was demonstrated in PHVD infants during ventricular taps (i.e., CSF drainage). Changes in perfusion and metabolism are presented in premature infants at high risk of IVH within the first 72 hours of life. Lastly, NNeMo was translated to the cardiac operating room, in patients undergoing surgery with cardiopulmonary bypass, to observe metabolic response to large intraoperative changes in CBF. Optical measures of perfusion and metabolism show potential to act as prognostic markers of injury and could aid clinicians in patient management before significant damage persists