The response of the vestibulosympathetic reflex to linear acceleration in the rat

Comparison of kinetic changes during helicopter medical evacuations: civilian versus military flights

BACKGROUND

Helicopter evacuation is crucial for providing medical care to casualties. Previous civilian studies have demonstrated that air transport can enhance survival rates compared with ground transport. However, there has been limited research on specific accelerations during helicopter flights, particularly in military flights. This study aims to analyse and compare the accelerations endured during civilian and military helicopter evacuations.

METHODS

Accelerations were recorded during evacuation flights from the site of injury to the first medical responders in civilian helicopter EC135 T1, and military Puma SA.330 and Caiman NH90 TTH helicopters. The research investigated global acceleration and compared acceleration distributions along the vertical, lateral and longitudinal axes. A specific comparative study of the take-off phases was also performed.

RESULTS

The analysis showed that vertical loads caused the most extreme accelerations for all types of helicopter but these extreme accelerations were rare and lasted for less than 1 s. Military flights show similar acceleration intensities to civilian flights, but accelerations are higher during short periods of the take-off phase.

CONCLUSIONS

The findings suggest that helicopter evacuations during military operations are as safe as civilian evacuations and highlight the importance of patient positioning in the aircraft. However, further research should investigate the haemodynamic response to accelerations experienced during actual evacuation flights.

Predicting Vasovagal Responses: A Model-Based and Machine Learning Approach

Vasovagal syncope (VVS) or neurogenically induced fainting has resulted in falls, fractures, and death. Methods to deal with VVS are to use implanted pacemakers or beta blockers. These are often ineffective because the underlying changes in the cardiovascular system that lead to the syncope are incompletely understood and diagnosis of frequent occurrences of VVS is still based on history and a tilt test, in which subjects are passively tilted from a supine position to 20° from the spatial vertical (to a 70° position) on the tilt table and maintained in that orientation for 10–15 min. Recently, is has been shown that vasovagal responses (VVRs), which are characterized by transient drops in blood pressure (BP), heart rate (HR), and increased amplitude of low frequency oscillations in BP can be induced by sinusoidal galvanic vestibular stimulation (sGVS) and were similar to the low frequency oscillations that presaged VVS in humans. This transient drop in BP and HR of 25 mmHg and 25 beats per minute (bpm), respectively, were considered to be a VVR. Similar thresholds have been used to identify VVR's in human studies as well. However, this arbitrary threshold of identifying a VVR does not give a clear understanding of the identifying features of a VVR nor what triggers a VVR. In this study, we utilized our model of VVR generation together with a machine learning approach to learn a separating hyperplane between normal and VVR patterns. This methodology is proposed as a technique for more broadly identifying the features that trigger a VVR. If a similar feature identification could be associated with VVRs in humans, it potentially could be utilized to identify onset of a VVS, i.e, fainting, in real time.

Modeling Interval Timing by Recurrent Neural Nets

The purpose of this study was to take a new approach in showing how the central nervous system might encode time at the supra-second level using recurrent neural nets (RNNs). This approach utilizes units with a delayed feedback, whose feedback weight determines the temporal properties of specific neurons in the network architecture. When these feedback neurons are coupled, they form a multilayered dynamical system that can be used to model temporal responses to steps of input in multidimensional systems. The timing network was implemented using separate recurrent “Go” and “No-Go” neural processing units to process an individual stimulus indicating the time of reward availability. Outputs from these distinct units on each time step are converted to a pulse reflecting a weighted sum of the separate Go and No-Go signals. This output pulse then drives an integrator unit, whose feedback weight and input weights shape the pulse distribution. This system was used to model empirical data from rodents performing in an instrumental “peak interval timing” task for two stimuli, Tone and Flash. For each of these stimuli, reward availability was signaled after different times from stimulus onset during training. Rodent performance was assessed on non-rewarded trials, following training, with each stimulus tested individually and simultaneously in a stimulus compound. The associated weights in the Go/No-Go network were trained using experimental data showing the mean distribution of bar press rates across an 80 s period in which a tone stimulus signaled reward after 5 s and a flash stimulus after 30 s from stimulus onset. Different Go/No-Go systems were used for each stimulus, but the weighted output of each fed into a final recurrent integrator unit, whose weights were unmodifiable. The recurrent neural net (RNN) model was implemented using Matlab and Matlab’s machine learning tools were utilized to train the network using the data from non-rewarded trials. The neural net output accurately fit the temporal distribution of tone and flash-initiated bar press data. Furthermore, a “Temporal Averaging” effect was also obtained when the flash and tone stimuli were combined. These results indicated that the system combining tone and flash responses were not superposed as in a linear system, but that there was a non-linearity, which interacted between tone and flash. In order to achieve an accurate fit to the empirical averaging data it was necessary to implement non-linear “saliency functions” that limited the output signal of each stimulus to the final integrator when the other was co-present. The model suggests that the central nervous system encodes timing generation as a dynamical system whose timing properties are embedded in the connection weights of the system. In this way, event timing is coded similar to the way other sensory-motor systems, such as the vestibulo-ocular and optokinetic systems, which combine sensory inputs from the vestibular and visual systems to generate the temporal aspects of compensatory eye movements.

The neural basis of motion sickness

Although motion of the head and body has been suspected or known as the provocative cause for the production of motion sickness for centuries, it is only within the last 20 yr that the source of the signal generating motion sickness and its neural basis has been firmly established. Here, we briefly review the source of the conflicts that cause the body to generate the autonomic signs and symptoms that constitute motion sickness and provide a summary of the experimental data that have led to an understanding of how motion sickness is generated and can be controlled. Activity and structures that produce motion sickness include vestibular input through the semicircular canals, the otolith organs, and the velocity storage integrator in the vestibular nuclei. Velocity storage is produced through activity of vestibular-only (VO) neurons under control of neural structures in the nodulus of the vestibulo-cerebellum. Separate groups of nodular neurons sense orientation to gravity, roll/tilt, and translation, which provide strong inhibitory control of the VO neurons. Additionally, there are acetylcholinergic projections from the nodulus to the stomach, which along with other serotonergic inputs from the vestibular nuclei, could induce nausea and vomiting. Major inhibition is produced by the GABA_B receptors, which modulate and suppress activity in the velocity storage integrator. Ingestion of the GABA_B agonist baclofen causes suppression of motion sickness. Hopefully, a better understanding of the source of sensory conflict will lead to better ways to avoid and treat the autonomic signs and symptoms that constitute the syndrome.

Interaction between graviception and carotid baroreflex function in humans during parabolic flight-induced microgravity

The aim of the present study was to assess carotid baroreflex (CBR) function during acute changes in otolithic activity in humans. To address this question, we designed a set of experiments to identify the modulatory effects of microgravity on CBR function at a tilt angle of -2°, which was identified to minimize changes in central blood volume during parabolic flight. During parabolic flight at 0 and 1 g, CBR function curves were modeled from the heart rate (HR) and mean arterial pressure (MAP) responses to rapid pulse trains of neck pressure and neck suction ranging from +40 to -80 Torr; CBR control of HR (carotid-HR) and MAP (carotid-MAP) function curves, respectively. The maximal gain of both carotid-HR and carotid-MAP baroreflex function curves were augmented during microgravity compared with 1 g (carotid-HR, -0.53 to -0.80 beats·min^-1·mmHg^-1, P < 0.05; carotid-MAP, -0.24 to -0.30 mmHg/mmHg, P < 0.05). These findings suggest that parabolic flight-induced acute change of otolithic activity may modify CBR function and identifies that the vestibular system contributes to blood pressure regulation under fluctuations in gravitational forces. NEW & NOTEWORTHY The effect of acute changes in vestibular activity on arterial baroreflex function remains unclear. In the present study, we assessed carotid baroreflex function without changes in central blood volume during parabolic flight, which causes acute changes in otolithic activity. The sensitivity of both carotid heart rate and carotid mean arterial pressure baroreflex function was augmented in microgravity compared with 1 g, suggesting that the vestibular system contributes to blood pressure regulation in humans on Earth.

Vestibular Activation Habituates the Vasovagal Response in the Rat

Vasovagal syncope is a significant medical problem without effective therapy, postulated to be related to a collapse of baroreflex function. While some studies have shown that repeated static tilts can block vasovagal syncope, this was not found in other studies. Using anesthetized, male Long–Evans rats that were highly susceptible to generation of vasovagal responses, we found that repeated activation of the vestibulosympathetic reflex (VSR) with ±2 and ±3 mA, 0.025 Hz sinusoidal galvanic vestibular stimulation (sGVS) caused incremental changes in blood pressure (BP) and heart rate (HR) that blocked further generation of vasovagal responses. Initially, BP and HR fell ≈20–50 mmHg and ≈20–50 beats/min (bpm) into a vasovagal response when stimulated with Sgv\S in susceptible rats. As the rats were continually stimulated, HR initially rose to counteract the fall in BP; then the increase in HR became more substantial and long lasting, effectively opposing the fall in BP. Finally, the vestibular stimuli simply caused an increase in BP, the normal sequence following activation of the VSR. Concurrently, habituation caused disappearance of the low-frequency (0.025 and 0.05 Hz) oscillations in BP and HR that must be present when vasovagal responses are induced. Habituation also produced significant increases in baroreflex sensitivity (p < 0.001). Thus, repeated low-frequency activation of the VSR resulted in a reduction and loss of susceptibility to development of vasovagal responses in rats that were previously highly susceptible. We posit that reactivation of the baroreflex, which is depressed by anesthesia and the disappearance of low-frequency oscillations in BP and HR are likely to be critically involved in producing resistance to the development of vasovagal responses. SGVS has been widely used to activate muscle sympathetic nerve activity in humans and is safe and well tolerated. Potentially, it could be used to produce similar habituation of vasovagal syncope in humans.