Autonomic Nervous System Activity During Actual and Mentally Simulated Preparation for Movement

Toward brain-heart computer interfaces: a study on the classification of upper limb movements using multisystem directional estimates

OBJECTIVE

Brain-computer interfaces (BCI) exploit computational features from brain signals to perform a given task. Despite recent neurophysiology and clinical findings indicating the crucial role of functional interplay between brain and cardiovascular dynamics in locomotion, heartbeat information remains to be included in common BCI systems. In this study, we exploit the multidimensional features of directional and functional interplay between electroencephalographic and heartbeat spectra to classify upper limb movements into three classes.

APPROACH

We gathered data from 26 healthy volunteers that performed 90 movements; the data were processed using a recently proposed framework for brain-heart interplay (BHI) assessment based on synthetic physiological data generation. Extracted BHI features were employed to classify, through sequential forward selection scheme and k-nearest neighbors algorithm, among resting state and three classes of movements according to the kind of interaction with objects.

MAIN RESULTS

The results demonstrated that the proposed brain-heart computer interface (BHCI) system could distinguish between rest and movement classes automatically with an average 90% of accuracy.

SIGNIFICANCE

Further, this study provides neurophysiology insights indicating the crucial role of functional interplay originating at the cortical level onto the heart in the upper limb neural control. The inclusion of functional BHI insights might substantially improve the neuroscientific knowledge about motor control, and this may lead to advanced BHCI systems performances.

A pilot study exploring the relationship between wellness and physical fitness: an examination into autonomic health

Objective: To explore the relationship between physical fitness and wellness in order to determine if perceptions of wellness can be predicted by physical fitness level.Participants: Sixty-seven college students (41 females; M = 20.86 years, SD = 4.23 years) were recruited from a large southeastern university during March-May 2018.Methods: Baseline measures for skin conductance and heart rate variability were obtained. Participants completed a wellness questionnaire and a series of tests (body composition, cardiorespiratory fitness, flexibility, and muscular fitness) designed to determine physical fitness levels. Correlation and regression analyses were run to explore relationships between physical fitness and wellness measures.Results: Muscular fitness and composite physical fitness significantly predicted perceived wellness. Heart rate variability was significantly related to physical fitness components.Conclusion: College students endorse muscular fitness as representative of health status; suggesting that by remaining physically active, in particular through muscular fitness, college student quality of life and cardiovascular health can be improved.

Integrating mental imagery and fascial tissue: A conceptualization for research into movement and cognition

Mental imagery (MI) research has mainly focused to date on mechanisms of effect and performance gains associated with muscle and neural tissues. MI's potential to affect fascia has rarely been considered. This paper conceptualizes ways in which MI might mutually interact with fascial tissue to support performance and cognitive functions. Such ways acknowledge, among others, MI's positive effect on proprioception, body schema, and pain. Drawing on cellular, physiological, and functional similarities and associations between muscle and fascial tissues, we propose that MI has the potential to affect and be affected by fascial tissue. We suggest that fascia-targeted MI (fascial mental imagery; FMI) can therefore be a useful approach for scientific as well as clinical purposes. We use the example of fascial dynamic neuro-cognitive imagery (FDNI) as a codified FMI method available for scientific and therapeutic explorations into rehabilitation and prevention of fascia-related disabling conditions.

Motor imagery muscle contraction strength influences spinal motor neuron excitability and cardiac sympathetic nerve activity

[Purpose] The aim of this study was to investigate the changes in spinal motor neuron excitability and autonomic nervous system activity during motor imagery of isometric thenar muscle activity at 10% and 50% maximal voluntary contraction (MVC). [Methods] The F-waves and low frequency/high frequency (LF/HF) ratio were recorded at rest, during motor imagery, and post-trial. For motor imagery trials, subjects were instructed to imagine thenar muscle activity at 10% and 50% MVC while holding the sensor of a pinch meter for 5 min. [Results] The F-waves and LF/HF ratio during motor imagery at 50% MVC were significantly increased compared with those at rest, whereas those during motor imagery at 10% MVC were not significantly different from those at rest. The relative values of the F/M amplitude ratio during motor imagery at 50% MVC were significantly higher than those at 10% MVC. The relative values of persistence and the LF/HF ratio during motor imagery were similar during motor imagery at the two muscle contraction strengths. [Conclusion] Motor imagery can increase the spinal motor neuron excitability and cardiac sympathetic nerve activity. Motor imagery at 50% MVC may be more effective than motor imagery at 10% MVC.

Assessing motor imagery ability in younger and older adults by combining measures of vividness, controllability and timing of motor imagery

With the population aging, a large number of patients undergoing rehabilitation are older than 60 years. Also, since the use of motor imagery (MI) training in rehabilitation is becoming more popular, it is important to gain a better knowledge about the age-related changes in MI ability. The main goal of this study was to compare MI ability in younger and older adults as well as to propose a new procedure for testing this ability. Thirty healthy young subjects (mean age: 22.9±2.7 years) and 28 healthy elderly subjects (mean age: 72.4±5.5 years) participated in the experiment. They were administered three tests aimed at assessing three dimensions of MI: (1) the kinesthetic and visual imagery questionnaire (KVIQ) to assess MI vividness; (2) a finger-thumb opposition task to assess MI controllability; and (3) a chronometric task to assess the timing of MI. On average, the younger and older groups showed similar results on the KVIQ and the chronometric task, but the younger group was more accurate at the finger-thumb opposition task. Interestingly, there was a large variability in the performance within both groups, emphasizing the importance of considering each person individually regarding MI ability, whatever his age. Finally, we propose two indexes of MI ability to identify the potential of persons to engage in MI training programs. Future studies are needed to confirm the predictive value of these MI indexes and define inclusion/exclusion thresholds for their use as a screening tool in both younger and older adults.

Autonomic nervous system correlates in movement observation and motor imagery

The purpose of the current article is to provide a comprehensive overview of the literature offering a better understanding of the autonomic nervous system (ANS) correlates in motor imagery (MI) and movement observation. These are two high brain functions involving sensori-motor coupling, mediated by memory systems. How observing or mentally rehearsing a movement affect ANS activity has not been extensively investigated. The links between cognitive functions and ANS responses are not so obvious. We will first describe the organization of the ANS whose main purposes are controlling vital functions by maintaining the homeostasis of the organism and providing adaptive responses when changes occur either in the external or internal milieu. We will then review how scientific knowledge evolved, thus integrating recent findings related to ANS functioning, and show how these are linked to mental functions. In turn, we will describe how movement observation or MI may elicit physiological responses at the peripheral level of the autonomic effectors, thus eliciting autonomic correlates to cognitive activity. Key features of this paper are to draw a step-by step progression from the understanding of ANS physiology to its relationships with high mental processes such as movement observation or MI. We will further provide evidence that mental processes are co-programmed both at the somatic and autonomic levels of the central nervous system (CNS). We will thus detail how peripheral physiological responses may be analyzed to provide objective evidence that MI is actually performed. The main perspective is thus to consider that, during movement observation and MI, ANS activity is an objective witness of mental processes.

Taking NIRS-BCIs outside the lab: towards achieving robustness against environment noise

This paper reported initial findings on the effects of environmental noise and auditory distractions on the performance of mental state classification based on near-infrared spectroscopy (NIRS) signals recorded from the prefrontal cortex. Characterization of the performance losses due to environmental factors could provide useful information for the future development of NIRS-based brain-computer interfaces that can be taken beyond controlled laboratory settings and into everyday environments. Experiments with a hidden Markov model-based classifier showed that while significant performance could be attained in silent conditions, only chance levels of sensitivity and specificity were obtained in noisy environments. In order to achieve robustness against environment noise, two strategies were proposed and evaluated. First, physiological responses harnessed from the autonomic nervous system were used as complementary information to NIRS signals. More specifically, four physiological signals (electrodermal activity, skin temperature, blood volume pulse, and respiration effort) were collected in synchrony with the NIRS signals as the user sat at rest and/or performed music imagery tasks. Second, an acoustic monitoring technique was proposed and used to detect startle noise events, as both the prefrontal cortex and ANS are known to involuntarily respond to auditory startle stimuli. Experiments with eight participants showed that with a startle noise compensation strategy in place, performance comparable to that observed in silent conditions could be recovered with the hybrid ANS-NIRS system.

Contribution from neurophysiological and psychological methods to the study of motor imagery

This paper reviews studies on neurophysiological and behavioral methods used to evaluate motor imagery accuracy. These methods can be used when performed in the field and are based on recordings of peripheral indices such as autonomic nervous system or electromyographic activities, mental chronometry and psychological tests. Providing physiological signs that correlate to these types of mental processes may be considered an objective approach for motor imagery analysis. However, although autonomic nervous system activity recording has been shown to match motor imagery in real time, to evaluate its accuracy qualitatively and the individual ability to form mental images, the relationship between physiological responses and mental processes remains an inference. Moreover, electromyographic recordings may be associated with postural control data, but due to inconsistent results, they remain insufficient to solely evaluate motor imagery accuracy. Other techniques traditionally used in psychology and cognitive psychology are questionnaires, "debriefing" with subjects and mental chronometry. Although such methods lead to interesting results, there remains an important part of subjectivity as subjects perform an auto-evaluation of motor imagery accuracy. Similarly, mental chronometry gives information on the ability to preserve temporal organization of movement but does not allow the evaluation of the vividness of mental images. Thus, several methods should be combined to analyze motor imagery accuracy in greater detail. Neurophysiological recordings cannot therefore be considered an alternative but rather a complementary technique to behavioral and psychological methods. The advantages and inconvenient of each technique and the hypotheses that could be tested are discussed.