Annapurna Base Camp: Studying the Brain at High Altitude

by Matt Gaidica
PhD Candidate, Neuroscience Graduate Program, University of Michigan, Ann Arbor (USA)
Contact: mgaidica@med.umich.edu, http://gaidi.ca

Introduction

Human achievement at high altitude requires the performance of skilled behaviors with cognitive clarity. To better understand how the brain changes at high altitude during a motor task we used the actiCAP Xpress Bundle to characterize motor circuit changes up to 4,130 meters in the Himalayan mountains of Nepal.

Background

The high altitude brain has been of great interest since Angelo Mosso performed detailed studies of respiration and cerebral blood flow in the late nineteenth century [1]. Since then it has been known that the reduction in atmospheric pressure at increasing altitudes requires the body to work harder to maintain oxygen levels necessary for life [2]. If the body becomes deficient in oxygen it is considered in a state of hypoxia. How humans adapt, compensate, or ultimately succumb to hypoxic exposure is critical information in regards to high altitude exploration [3,4]. Our current understanding of the hypoxic cascade largely fails to describe the neuronal underpinnings of altered cognition and task performance. We stand here at an exciting intersection in history where we both appreciate skilled behaviors as an expression of the brain and have the technology to answer critical questions in neuroscience related to high altitude.

Problem

Successfully executing motor skills may mean the difference between life and death in high altitude environments (i.e. greater than 2,500 meters). The ability to tie ropes, operate clips, or manipulate small tools are just some of the skills we take for granted at the oxygen-rich sea level. There is a long history of anecdotes supporting the notion that either the will or capacity to perform such skills is compromised even at moderate altitudes, and further exacerbated at greater heights [5]. While it is clear that the brain’s motor circuitry undergoes changes at high altitude [6], little is known about the implications of those changes on motor task performance and skilled behaviors. Foundational studies on motor circuit adaptations in response to brain insults have led to enormous advances in brain machine interfaces (BMIs) [7] and treatments for movement disorders [8]. Surely developing countermeasures for high altitude motor dysfunction would benefit from that vast literature, if we had a clearer picture of the brain in this unique environment.

Pilot Study

We aimed to characterize such task-related neuronal activity by using the Brain Products actiCAP Xpress Bundle to measure cortical encephalography (EEG) during a seven-day trek to Annapurna Base Camp situated at 4,130 meters in the Nepalese Himalayas. To achieve this we developed a self-paced, reach-to-grasp task based on a homologous rodent task that we are using to study motor behavior in the laboratory [9]. Our reaching platform integrates sensors directly with the Brain Products V-Amp EEG amplifier, along with a wrist-based accelerometer. In total, we captured 16-channels of cortical EEG over motor brain regions in two subjects with time-locked markers for each stage of the movement: initiation, object lift-off, and object retrieval.

Annapurna Base Camp: Studying the Brain at High Altitude

In general, the information garnered from EEG reflects macro-level brain dynamics emergent of the neuronal activity from underlying cortical substructures. This activity may be intrinsic to the area of recording, or represent distant inputs and/or coupling from connected brain regions [10]. We focused our attention on the central motor axis involved in reaching, grasping, and fine motor movements [11], consisting of electrodes C3, Cz, and C4 based on standard 10-20 EEG locations. Our technical analysis began with filtering the wideband EEG data into five frequency bands classically associated with mammalian physiology [12]: Delta 0.5-3.5 Hz; Theta 4-8 Hz; Alpha 7.5-12.5 Hz; Beta 13-30 Hz; Gamma 30-100 Hz. Our primary hypothesis was that that beta band oscillations would be enhanced during skilled reaching at high altitude. To test this hypothesis, we calculated a trial-by-trial z-score of the power envelope and estimated a phase locking value [13] to determine if any frequency bands showed a distinct pattern of activity when time-locked to our sensor markers. Data were then plotted as a function of altitude.

Discussion

Contrary to our primary hypothesis that beta band oscillations would be enhanced during skilled reaching at high altitude, we found the greatest and most significant effect present in the delta band. Our data demonstrated increasing phase and amplitude synchrony mid-reach that significantly correlated with our altitude profile. Although we experienced mild levels of hypoxia (i.e. less than 90% blood oxygen saturation), no deficits in task performance were encountered, suggesting that our findings may represent early brain compensations not yet exposed by behavior. We presented this in graphical form as a poster at the 2017 International Hypoxia Symposia.

Annapurna Base Camp: Studying the Brain at High AltitudeBrainVision Analyzer 2 gave us the tools necessary to visualize and interpret our data leading to a larger discussion about the potential roles for delta oscillations at high altitude. Existing literature on delta oscillations can be viewed from two angles. On one hand, there exists a strong positive correlation between enhanced delta oscillations and homeostatic processes involved in states of fatigue, disease, sleep, hypoxia [14] and general anesthesia [15]. On the other hand, delta oscillations appear to establish an oscillatory framework for sensorimotor processing. This forms the basis of more complex phase-amplitude coupling of motor signals [16,17]. Furthermore, low frequency oscillations in the delta band optimally decode hand velocity [18], movement direction [19], and predict task accuracy [20]. While the direct source of delta oscillations is unclear [21,22], we hypothesize that the task-related enhancement we observed is a sensorimotor response necessary to maintain task coordination. That said, from a network perspective, one neural system is telling the body to slow down (homeostatic), while the other neural system is telling the body to perform (sensorimotor). In the context of our data, the “performance system” was more salient and thus influenced behavior over the “slow-down” system. For future research, one prediction is an asymptote for task-related delta oscillations. The brain and body may enter absolute survival mode, prioritizing vital functions over sensorimotor processing.

Conclusion

To understand neuronal adaptations of task performance at high altitude in the context of two competing regimes is an exciting future direction in need of further study. While many high-altitude countermeasures that are currently in place likely work to reduce homeostatic drive, it may be possible to positively augment the sensorimotor system using technologies such as transcranial electric or magnetic stimulation.

Trek Tips

Acknowledgements

The Harvard Travellers Club financially supported this study. Brain Vision LLC, sponsored all equipment. This study received “non-regulated” status by the University of Michigan Medical School Institutional Review Board (ID: HUM00119637).

References

[1] Mosso, A. Life of man in the high Alps. (TF Unwin, 1898).

[2] Milledge, J. S., West, J. B. & Schoene, R. B.
High Altitude Medicine and Physiology Fourth Edition. (CRC Press, 2007).

[3] Miscio, G., Milano, E., Aguilar, J., et al.
Functional involvement of central nervous system at high altitude.
Exp. Brain Res. 194, 157–162 (2009).

[4] Hornbein, T. F., Townes, B. D., Schoene, R. B., et al.
The Cost to the Central Nervous System of Climbing to Extremely High Altitude.
N. Engl. J. Med. 321, 1714–1719 (1989).

[5] Lankford, H. V. Dull Brains, Mountaineers, and Mosso: Hypoxic Words from on High. High Alt. Med. Biol. 16, 363–370 (2015).

[6] Kraaier, V., Van Huffelen, A. C. & Wieneke, G. H.
Quantitative EEG changes due to hypobaric hypoxia in normal subjects.
Electroencephalogr. Clin. Neurophysiol. 69, 303–312 (1988).

[7] Schroeder, K. E. & Chestek, C. A.
Intracortical brain-machine interfaces advance sensorimotor neuroscience.
Front. Neurosci. 10, 1–8 (2016).

[8] Ellens, D. J. & Leventhal, D. K.
Electrophysiology of Basal Ganglia and Cortex in Models of Parkinson Disease. 3, 241–254 (2014).

[9] Ellens, D. J., Gaidica, M., Toader, A., et al.
An automated rat single pellet reaching system with high-speed video capture.
J. Neurosci. Methods 271, 119–127 (2016).

[10] Buzsáki, G. & Draguhn, A.
Neuronal oscillations in cortical networks.
Science 304, 1926–9 (2004).

[11] Zaepffel, M., Trachel, R., Kilavik, B. E., et al.
Modulations of EEG Beta Power during Planning and Execution of Grasping Movements.
PLoS One 8, (2013).

[12] Buzsáki, G.
Rhythms of the Brain. Rhythms of the Brain (2009).
doi:10.1093/acprof:oso/9780195301069.001.0001

[13] Lachaux, J. P., Rodriguez, E., Martinerie, J., et al.
Measuring phase synchrony in brain signals.
Hum. Brain Mapp. 8, 194–208 (1999).

[14] Knyazev, G. G.
EEG delta oscillations as a correlate of basic homeostatic and motivational processes.
Neurosci. Biobehav. Rev. 36, 677–695 (2012).

[15] Schroeder, K. E., Irwin, Z. T., Gaidica, M., et al.
Disruption of corticocortical information transfer during ketamine anesthesia in the primate brain.
Neuroimage 134, 459–465 (2016).

[16] Arnal, L. H. & Giraud, A. L.
Cortical oscillations and sensory predictions.
Trends Cogn. Sci. 16, 390–398 (2012).

[17] Stefanics, G., Hangya, B., Hernadi, I., et al.
Phase Entrainment of Human Delta Oscillations Can Mediate the Effects of Expectation on Reaction Speed.
J. Neurosci. 30, 13578–13585 (2010).

[18] Bradberry, T. J., Gentili, R. J. & Contreras-Vidal, J. L.
Reconstructing Three-Dimensional Hand Movements from Noninvasive Electroencephalographic Signals.
J. Neurosci. 30, 3432–3437 (2010).

[19] Waldert, S., Preissl, H., Demandt, E., et al.
Hand movement direction decoded from MEG and EEG.
J. Neurosci. 28, 1000–8 (2008).

[20] Arnal, L. H., Doelling, K. B. & Poeppel, D.
Delta-beta coupled oscillations underlie temporal prediction accuracy.
Cereb. Cortex 25, 3077–3085 (2015).

[21] Hall, T. M., deCarvalho, F. & Jackson, A.
A Common Structure Underlies Low-Frequency Cortical Dynamics in Movement, Sleep, and Sedation.
Neuron 83, 1185–1199 (2014).

[22] Güntekin, B. & Başar, E.
Review of evoked and event-related delta responses in the human brain.
Int. J. Psychophysiol. 103, 43–52 (2016).