A Dynamical Systems Approach to Characterizing Brain–Body Interactions during Movement: Challenges, Interpretations, and Recommendations

Brain–body interactions (BBIs) have been the focus of intense scrutiny since the inception of the scientific method, playing a foundational role in the earliest debates over the philosophy of science. Contemporary investigations of BBIs to elucidate the neural principles of motor control have benefited from advances in neuroimaging, device engineering, and signal processing. However, these studies generally suffer from two major limitations. First, they rely on interpretations of ‘brain’ activity that are behavioral in nature, rather than neuroanatomical or biophysical. Second, they employ methodological approaches that are inconsistent with a dynamical systems approach to neuromotor control. These limitations represent a fundamental challenge to the use of BBIs for answering basic and applied research questions in neuroimaging and neurorehabilitation. Thus, this review is written as a tutorial to address both limitations for those interested in studying BBIs through a dynamical systems lens. First, we outline current best practices for acquiring, interpreting, and cleaning scalp-measured electroencephalography (EEG) acquired during whole-body movement. Second, we discuss historical and current theories for modeling EEG and kinematic data as dynamical systems. Third, we provide worked examples from both canonical model systems and from empirical EEG and kinematic data collected from two subjects during an overground walking task

Cortical activity during walking and balance tasks in older adults and in people with Parkinson’s disease: a structured review

An emerging body of literature has examined cortical activity during walking and balance tasks in older adults and in people with Parkinson’s disease, specifically using functional near infrared spectroscopy (fNIRS) or electroencephalography (EEG). This review provides an overview of this developing area, and examines the disease-specific mechanisms underlying walking or balance deficits. Medline, PubMed, PsychInfo and Scopus databases were searched. Articles that described cortical activity during walking and balance tasks in older adults and in those with PD were screened by the reviewers. Thirty-seven full-text articles were included for review, following an initial yield of 566 studies. This review summarizes study findings, where increased cortical activity appears to be required for older adults and further for participants with PD to perform walking and balance tasks, but specific activation patterns vary with the demands of the particular task. Studies attributed cortical activation to compensatory mechanisms for underlying age- or PD-related deficits in automatic movement control. However, a lack of standardization within the reviewed studies was evident from the wide range of study protocols, instruments, regions of interest, outcomes and interpretation of outcomes that were reported. Unstandardized data collection, processing and reporting limited the clinical relevance and interpretation of study findings. Future work to standardize approaches to the measurement of cortical activity during walking and balance tasks in older adults and people with PD with fNIRS and EEG systems is needed, which will allow direct comparison of results and ensure robust data collection/reporting. Based on the reviewed articles we provide clinical and future research recommendations

Comparing postural stability entropy analyses to differentiate fallers and non-fallers

The health and financial cost of falls has spurred research to differentiate the characteristics of fallers and non-fallers. Postural stability has received much of the attention with recent studies exploring various measures of entropy. This study compared the discriminatory ability of several entropy methods at differentiating two paradigms in the center-of-pressure of elderly individuals: (1) eyes open (EO) vs. eyes closed (EC) and (2) fallers (F) vs. non-fallers (NF). Methods were compared using the area under the curve (AUC) of the receiver-operating characteristic curves developed from logistic regression models. Overall, multiscale entropy (MSE) and composite multiscale entropy (CompMSE) performed the best with AUCs of 0.71 for EO/EC and 0.77 for F/NF. When methods were combined together to maximize the AUC, the entropy classifier had an AUC of for 0.91 the F/NF comparison. These results suggest researchers and clinicians attempting to create clinical tests to identify fallers should consider a combination of every entropy method when creating a classifying test. Additionally, MSE and CompMSE classifiers using polar coordinate data outperformed rectangular coordinate data, encouraging more research into the most appropriate time series for postural stability entropy analysis

Gait Performance in People with Symptomatic, Chronic Mild Traumatic Brain Injury

There is a dearth of knowledge about how symptom severity affects gait in the chronic (>3 months) mild traumatic brain injury (mTBI) population despite up to 53% of people reporting persisting symptoms following mTBI. The purpose of this investigation was to determine if gait is affected in a symptomatic, chronic mTBI group and to assess the relationship between gait performance and symptom severity on the Neurobehavioral Symptom Inventory (NSI). Gait was assessed under single- and dual-task conditions using five inertial sensors in 57 control subjects and 65 people with chronic mTBI (1.1 year from mTBI). The single- and dual-task gait domains of Pace, Rhythm, Variability, and Turning were calculated from individual gait characteristics. Dual-task cost (DTC) was calculated for each domain. The mTBI group walked (domain z-score mean difference: single-task = 0.70; dual-task = 0.71) and turned (z-score mean difference: single-task = 0.69; dual-task = 0.70) slower (p<0.001) under both gait conditions, with less rhythm under dual-task gait (z-score difference = 0.21, p=0.001). DTC was not different between groups. Higher NSI somatic sub-score was related to higher single- and dual-task gait variability as well as slower dual-task pace and turning (p<0.01). People with chronic mTBI and persistent symptoms exhibited altered gait, particularly under dual-task, and worse gait performance related to greater symptom severity. Future gait research in chronic mTBI should assess the possible underlying physiological mechanisms for persistent symptoms and gait deficits

Gait measurement in chronic mild traumatic brain injury: A model approach

INTRODUCTION: Mild traumatic brain injury (mTBI) can impact gait, with deficits linked to underlying neural disturbances in cognitive, motor and sensory systems. Gait is complex as it is comprised of multiple characteristics that are sensitive to underlying neural deficits. However, there is currently no clear framework to guide selection of gait characteristics in mTBI. This study developed a model of gait in chronic mTBI and replicated this in a separate group of controls, to provide a comprehensive and structured methodology on which to base gait assessment and analysis. METHODS: Fifty-two people with chronic mTBI and 59 controls completed a controlled laboratory gait assessment; walking for two minutes back and forth over a 13 m distance while wearing five wirelessly synchronized inertial sensors. Thirteen gait characteristics derived from the inertial sensors were selected for entry into the principle component analysis based on previous literature, robustness and novelty. Principle component analysis was then used to derive domains (components) of gait. RESULTS: Four gait domains were derived for our chronic mTBI group (variability, rhythm, pace and turning) and this was replicated in a separate control cohort. Domains totaled 80.8% and 77.4% of variance in gait for chronic mTBI and controls, respectively. Gait characteristic loading was unambiguous for all features, with the exception of gait speed in controls that loaded on pace and rhythm domains. CONCLUSION: This study contributes a four component model of gait in chronic mTBI and controls that can be used to comprehensively assess and analyze gait and underlying mechanisms involved in impairment, or examine the influence of interventions

Implementation of a Central Sensorimotor Integration Test for Characterization of Human Balance Control During Stance

Balance during stance is regulated by active control mechanisms that continuously estimate body motion, via a “sensory integration” mechanism, and generate corrective actions, via a “sensory-to-motor transformation” mechanism. The balance control system can be modeled as a closed-loop feedback control system for which appropriate system identification methods are available to separately quantify the sensory integration and sensory-to-motor components of the system. A detailed, functionally meaningful characterization of balance control mechanisms has potential to improve clinical assessment and to provide useful tools for answering clinical research questions. However, many researchers and clinicians do not have the background to develop systems and methods appropriate for performing identification of balance control mechanisms. The purpose of this report is to provide detailed information on how to perform what we refer to as “central sensorimotor integration” (CSMI) tests on a commercially available balance test device (SMART EquiTest CRS, Natus Medical Inc, Seattle WA) and then to appropriately analyze and interpret results obtained from these tests. We describe methods to (1) generate pseudorandom stimuli that apply cyclically-repeated rotations of the stance surface and/or visual surround (2) measure and calibrate center-of-mass (CoM) body sway, (3) calculate frequency response functions (FRFs) that quantify the dynamic characteristics of stimulus-evoked CoM sway, (4) estimate balance control parameters that quantify sensory integration by measuring the relative contribution of different sensory systems to balance control (i.e., sensory weights), and (5) estimate balance control parameters that quantify sensory-to-motor transformation properties (i.e., feedback time delay and neural controller stiffness and damping parameters). Additionally, we present CSMI test results from 40 subjects (age range 21–59 years) with normal sensory function, 2 subjects with results illustrating deviations from normal balance function, and we summarize results from previous studies in subjects with vestibular deficits. A bootstrap analysis was used to characterize confidence limits on parameters from CSMI tests and to determine how test duration affected the confidence with which parameters can be measured. Finally, example results are presented that illustrate how various sensory and central balance deficits are revealed by CSMI testing

The Sensor Technology and Rehabilitative Timing (START) Protocol: A Randomized Controlled Trial for the Rehabilitation of Mild Traumatic Brain Injury

BACKGROUND: Clinical practice for rehabilitation after mild traumatic brain injury (mTBI) is variable, and guidance on when to initiate physical therapy is lacking. Wearable sensor technology may aid clinical assessment, performance monitoring, and exercise adherence, potentially improving rehabilitation outcomes during unsupervised home exercise programs. OBJECTIVE: The objectives of this study were to: (1) determine whether initiating rehabilitation earlier than typical will improve outcomes after mTBI, and (2) examine whether using wearable sensors during a home-exercise program will improve outcomes in participants with mTBI. DESIGN: This was a randomized controlled trial. SETTING: This study will take place within an academic hospital setting at Oregon Health & Science University and Veterans Affairs Portland Health Care System, and in the home environment. PARTICIPANTS: This study will include 160 individuals with mTBI. INTERVENTION: The early intervention group (n = 80) will receive one-on-one physical therapy 8 times over 6 weeks and complete daily home exercises. The standard care group (n = 80) will complete the same intervention after a 6- to 8-week wait period. One-half of each group will receive wearable sensors for therapist monitoring of patient adherence and quality of movements during their home exercise program. MEASUREMENTS: The primary outcome measure will be the Dizziness Handicap Inventory score. Secondary outcome measures will include symptomatology, static and dynamic postural control, central sensorimotor integration posturography, and vestibular-ocular-motor function. LIMITATIONS: Potential limitations include variable onset of care, a wide range of ages, possible low adherence and/or withdrawal from the study in the standard of care group, and low Dizziness Handicap Inventory scores effecting ceiling for change after rehabilitation. CONCLUSIONS: If initiating rehabilitation earlier improves primary and secondary outcomes post-mTBI, this could help shape current clinical care guidelines for rehabilitation. Additionally, using wearable sensors to monitor performance and adherence may improve home exercise outcomes

Sensory functions and their relation to balance metrics: a secondary analysis of the LIMBIC-CENC multicenter cohort

IntroductionAmong patients with traumatic brain injury (TBI), balance problems often persist alongside hearing and vision impairments that lead to poorer outcomes of functional independence. As such, the ability to regain premorbid independent gait may be dictated by the level of sensory acuity or processing decrements that are shown following TBI assessment. This study explores the relationships between standardized sensory acuity and processing outcomes to postural balance and gait speed.MethodsSecondary analysis was performed on the Long-Term Impact of Military- Relevant Brain Injury Consortium Chronic Effects of Neurotrauma Consortium LIMBIC (CENC) data set. Separate regression analyses were carried out for each of the balance assessments (via Computerized Dynamic Posturography, CDP) and walking speed.DiscussionTBI frequency was significantly related to the majority of single CDP outcomes (i.e., Conditions 2–6), while various sensory processing outcomes had task-specific influences. Hearing impairments and auditory processing decrements presented with lower CDP scores (CDP Conditions 3,5,6, and 1–3 respectively), whereas greater visual processing scores were associated with better CDP scores for Conditions 2,5, and 6. In sum, patients with TBI had similar scores on static balance tests compared to non-TBI, but when the balance task got more difficult patients with TBI scored worse on the balance tests. Additionally, stronger associations with sensory processing than sensory acuity measures may indicate that patients with TBI have increased fall risk

A new framework for cortico-striatal plasticity: behavioural theory meets In vitro data at the reinforcement-action interface

Operant learning requires that reinforcement signals interact with action representations at a suitable neural interface. Much evidence suggests that this occurs when phasic dopamine, acting as a reinforcement prediction error, gates plasticity at cortico-striatal synapses, and thereby changes the future likelihood of selecting the action(s) coded by striatal neurons. But this hypothesis faces serious challenges. First, cortico-striatal plasticity is inexplicably complex, depending on spike timing, dopamine level, and dopamine receptor type. Second, there is a credit assignment problem—action selection signals occur long before the consequent dopamine reinforcement signal. Third, the two types of striatal output neuron have apparently opposite effects on action selection. Whether these factors rule out the interface hypothesis and how they interact to produce reinforcement learning is unknown. We present a computational framework that addresses these challenges. We first predict the expected activity changes over an operant task for both types of action-coding striatal neuron, and show they co-operate to promote action selection in learning and compete to promote action suppression in extinction. Separately, we derive a complete model of dopamine and spike-timing dependent cortico-striatal plasticity from in vitro data. We then show this model produces the predicted activity changes necessary for learning and extinction in an operant task, a remarkable convergence of a bottom-up data-driven plasticity model with the top-down behavioural requirements of learning theory. Moreover, we show the complex dependencies of cortico-striatal plasticity are not only sufficient but necessary for learning and extinction. Validating the model, we show it can account for behavioural data describing extinction, renewal, and reacquisition, and replicate in vitro experimental data on cortico-striatal plasticity. By bridging the levels between the single synapse and behaviour, our model shows how striatum acts as the action-reinforcement interface

Gait Stability Has Phase-Dependent Dual-Task Costs in Parkinson’s Disease

Dual-task (DT) paradigms have been used in gait research to assess the automaticity of locomotion, particularly in people with Parkinson’s disease (PD). In people with PD, reliance on cortical control during walking leads to greater interference between cognitive and locomotor tasks. Yet, recent studies have suggested that even healthy gait requires cognitive control, and that these cognitive contributions occur at specific phases of the gait cycle. Here, we examined whether changes in gait stability, elicited by simultaneous cognitive DTs, were specific to certain phases of the gait cycle in people with PD. Phase-dependent local dynamic stability (LDS) was calculated for 95 subjects with PD and 50 healthy control subjects during both single task and DT gait at phases corresponding to (1) heel contact—weight transfer, (2) toe-off—early swing, and (3) single-support—mid swing. PD-related DT interference was evident only for the duration of late swing and LDS during the heel contact—weight transfer phase of gait. No PD-related DT costs were found in other traditional spatiotemporal gait parameters. These results suggest that PD-related DT interference occurs only during times where cortical activity is needed for planning and postural adjustments. These results challenge our understanding of DT costs while walking, particularly in people with PD, and encourage researchers to re-evaluate traditional concepts of DT interference