Cortical reorganization to improve dynamic balance control with error amplification feedback

Background Error amplification (EA), virtually magnify task errors in visual feedback, is a potential neurocognitive approach to facilitate motor performance. With regional activities and inter-regional connectivity of electroencephalography (EEG), this study investigated underlying cortical mechanisms associated with improvement of postural balance using EA. Methods Eighteen healthy young participants maintained postural stability on a stabilometer, guided by two visual feedbacks (error amplification (EA) vs. real error (RE)), while stabilometer plate movement and scalp EEG were recorded. Plate dynamics, including root mean square (RMS), sample entropy (SampEn), and mean frequency (MF) were used to characterize behavioral strategies. Regional cortical activity and inter-regional connectivity of EEG sub-bands were characterized to infer neural control with relative power and phase-lag index (PLI), respectively. Results In contrast to RE, EA magnified the errors in the visual feedback to twice its size during stabilometer stance. The results showed that EA led to smaller RMS of postural fluctuations with greater SampEn and MF than RE did. Compared with RE, EA altered cortical organizations with greater regional powers in the mid-frontal cluster (theta, 4–7 Hz), occipital cluster (alpha, 8–12 Hz), and left temporal cluster (beta, 13–35 Hz). In terms of the phase-lag index of EEG between electrode pairs, EA significantly reduced long-range prefrontal-parietal and prefrontal-occipital connectivity of the alpha/beta bands, and the right tempo-parietal connectivity of the theta/alpha bands. Alternatively, EA augmented the fronto-centro-parietal connectivity of the theta/alpha bands, along with the right temporo-frontal and temporo-parietal connectivity of the beta band. Conclusion EA alters postural strategies to improve stance stability on a stabilometer with visual feedback, attributable to enhanced error processing and attentional release for target localization. This study provides supporting neural correlates for the use of virtual reality with EA during balance training.

Quality analysis for reliable complex multiclass neuroscience signal classification via electroencephalography

PurposeThe aim of this paper is to explore the brain–computer interface (BCI) as a methodology for generating awareness and increasing reliable use cases of the same so that an individual's quality of life can be enhanced via neuroscience and neural networks, and risk evaluation of certain experiments of BCI can be conducted in a proactive manner.Design/methodology/approachThis paper puts forward an efficient approach for an existing BCI device, which can enhance the performance of an electroencephalography (EEG) signal classifier in a composite multiclass problem and investigates the effects of sampling rate on feature extraction and multiple channels on the accuracy of a complex multiclass EEG signal. A one-dimensional convolutional neural network architecture is used to further classify and improve the quality of the EEG signals, and other algorithms are applied to test their variability. The paper further also dwells upon the combination of internet of things multimedia technology to be integrated with a customized design BCI network based on a conventionally used system known as the message query telemetry transport.FindingsAt the end of our implementation stage, 98% accuracy was achieved in a binary classification problem of classifying digit and non-digit stimuli, and 36% accuracy was observed in the classification of signals resulting from stimuli of digits 0 to 9.Originality/valueBCI, also known as the neural-control interface, is a device that helps a user reliably interact with a computer using only his/her brain activity, which is measured usually via EEG. An EEG machine is a quality device used for observing the neural activity and electric signals generated in certain parts of the human brain, which in turn can help us in studying the different core components of the human brain and how it functions to improve the quality of human life in general.

Ocular Autonomic Nervous System: An Update from Anatomy to Physiological Functions

The autonomic nervous system (ANS) confers neural control of the entire body, mainly through the sympathetic and parasympathetic nerves. Several studies have observed that the physiological functions of the eye (pupil size, lens accommodation, ocular circulation, and intraocular pressure regulation) are precisely regulated by the ANS. Almost all parts of the eye have autonomic innervation for the regulation of local homeostasis through synergy and antagonism. With the advent of new research methods, novel anatomical characteristics and numerous physiological processes have been elucidated. Herein, we summarize the anatomical and physiological functions of the ANS in the eye within the context of its intrinsic connections. This review provides novel insights into ocular studies.

Vagus Nerve Stimulation Reduces Indomethacin-Induced Small Bowel Inflammation

Crohn’s disease is a chronic, idiopathic condition characterized by intestinal inflammation and debilitating gastrointestinal symptomatology. Previous studies of inflammatory bowel disease (IBD), primarily in colitis, have shown reduced inflammation after electrical or pharmacological activation of the vagus nerve, but the scope and kinetics of this effect are incompletely understood. To investigate this, we studied the effect of electrical vagus nerve stimulation (VNS) in a rat model of indomethacin-induced small intestinal inflammation. 1 min of VNS significantly reduced small bowel total inflammatory lesion area [(mean ± SEM) sham: 124 ± 14 mm2, VNS: 62 ± 14 mm2, p = 0.002], intestinal peroxidation and chlorination rates, and intestinal and systemic pro-inflammatory cytokine levels as compared with sham-treated animals after 24 h following indomethacin administration. It was not known whether this observed reduction of inflammation after VNS in intestinal inflammation was mediated by direct innervation of the gut or if the signals are relayed through the spleen. To investigate this, we studied the VNS effect on the small bowel lesions of splenectomized rats and splenic nerve stimulation (SNS) in intact rats. We observed that VNS reduced small bowel inflammation also in splenectomized rats but SNS alone failed to significantly reduce small bowel lesion area. Interestingly, VNS significantly reduced small bowel lesion area for 48 h when indomethacin administration was delayed. Thus, 1 min of electrical activation of the vagus nerve reduced indomethacin-induced intestinal lesion area by a spleen-independent mechanism. The surprisingly long-lasting and spleen-independent effect of VNS on the intestinal response to indomethacin challenge has important implications on our understanding of neural control of intestinal inflammation and its potential translation to improved therapies for IBD.

Aerodynamics and motor control of ultrasonic vocalizations for social communication in mice and rats

Background Rodent ultrasonic vocalizations (USVs) are crucial to their social communication and a widely used translational tool for linking gene mutations to behavior. To maximize the causal interpretation of experimental treatments, we need to understand how neural control affects USV production. However, both the aerodynamics of USV production and its neural control remain poorly understood. Results Here, we test three intralaryngeal whistle mechanisms—the wall and alar edge impingement, and shallow cavity tone—by combining in vitro larynx physiology and individual-based 3D airway reconstructions with fluid dynamics simulations. Our results show that in the mouse and rat larynx, USVs are produced by a glottal jet impinging on the thyroid inner wall. Furthermore, we implemented an empirically based motor control model that predicts motor gesture trajectories of USV call types. Conclusions Our results identify wall impingement as the aerodynamic mechanism of USV production in rats and mice. Furthermore, our empirically based motor control model shows that both neural and anatomical components contribute to USV production, which suggests that changes in strain specific USVs or USV changes in disease models can result from both altered motor programs and laryngeal geometry. Our work provides a quantitative neuromechanical framework to evaluate the contributions of brain and body in shaping USVs and a first step in linking descending motor control to USV production.

Task-dependent neural control of regions within human genioglossus

Anatomical and imaging evidence suggests neural control of oblique and horizontal compartments of the genioglossus differs. However, neurophysiological evidence for differential control remains elusive. This study aimed to determine whether there are differences in neural drive to the oblique and horizontal regions of the genioglossus during swallowing and tongue protrusion. Adult participants (N=63; 48M) were recruited from a sleep clinic; 41 had Obstructive Sleep Apnoea (OSA: 34M, 8F). Electromyographic (EMG) was recorded at rest (awake, supine) using 4 intramuscular fine-wire electrodes inserted percutaneously into the anterior oblique, posterior oblique, anterior horizontal and posterior horizontal genioglossus. Epiglottic pressure and nasal airflow were also measured. During swallowing, two distinct EMG patterns were observed- a monophasic response (single EMG peak) and a biphasic response (two bursts of EMG). Peak EMG and timing of the peak relative to epiglottic pressure were significantly different between patterns (linear mixed models, p<0.001). Monophasic activation was more likely in the horizontal than oblique region during swallowing (OR=6.83, CI=3.46-13.53, p<0.001). In contrast, during tongue protrusion, activation patterns and EMG magnitude were not different between regions. There were no systematic differences in EMG patterns during swallowing or tongue protrusion between OSA and non-OSA groups. These findings provide evidence for functional differences in the motoneuronal output to the oblique and horizontal compartments, enabling differential task-specific drive. Given this, it is important to identify the compartment from which EMG is acquired. We propose that the EMG patterns during swallowing may be used to identify the compartment where a recording electrode is located.