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Matt Gaidica, Ph.D edited this page Dec 15, 2019 · 8 revisions

HARDWARE

Wireless Communication & Telemetry

Recording data from free-ranging animals makes it difficult to either transmit or “dump” data using wireless transmission. However, the longer an animal is left to roam, the more likely it is animal-borne data would become unrecoverable (e.g., the animal is eaten). Therefore, it would be ideal to develop a strategy to intermittently recover data from the bio-logger, perhaps by using Bluetooth low-energy technology. Simpler protocols (e.g., RFID, NFC) should also be considered to tag animals or devices and read/write device state.

Key Questions. What is the likelihood that we can recover data from animals? How far can data be transmitted and at what rate? What are the energetic costs of such transmission? Is this feasible with large cohorts of animals and what is the financial cost of implementing this?

  1. Open BCI Cyton board: https://docs.openbci.com/docs/02Cyton/CytonLanding

Energy Harvesting

Batteries have a definite life span depending on the bio-logging device they are powering. For long-duration studies, this limits an investigator either by limiting the amount of data that can be collected or the overall length of the study. Strategies to harvest energy from movement or external sources (e.g., solar) and recharge an on-board battery may be a useful strategy in some cases.

Key Questions. What are the most appropriate harvesting techniques for wild animals? What are the impeding factors (e.g., can solar energy transmit through fur?) How can we visualize the cost-benefit associated with each harvesting technique? What does a 10-year projection look like?

  1. Haeberlin, A., Zurbuchen, A., Walpen, S., Schaerer, J., Niederhauser, T., Huber, C., . . . Vogel, R. (2015). The first batteryless, solar-powered cardiac pacemaker. Heart Rhythm, 12(6), 1317-1323. doi:10.1016/j.hrthm.2015.02.032
  2. Zurbuchen, A., Pfenniger, A., Stahel, A., Stoeck, C. T., Vandenberghe, S., Koch, V. M., & Vogel, R. (2013). Energy Harvesting from the Beating Heart by a Mass Imbalance Oscillation Generator. Annals of Biomedical Engineering, 41(1), 131-141. doi:10.1007/s10439-012-0623-3
  3. Starner, T., & Paradiso, J. A. (2004). Human generated power for mobile electronics. Low-power electronics design, 45, 1-35.

VHF Triangulation

Analog VHF collars are used to track and locate animals via transmitting collars. Understanding the physical space animals occupy may lend itself to a better understanding of social interactions or how far the animal travels during a day. It may be possible to triangulate animals using a grid (3 or more) of antennas.

Key Questions. Is there high enough fidelity on the VHF signal to triangulate data? What would the necessary grid size be? What is the temporal resolution? Is this idea reasonable to implement at scale across an entire field site?

  1. Bartolommei, P., Francucci, S., & Pezzo, F. (2013). Accuracy of conventional radio telemetry estimates: a practical procedure of measurement. Hystrix, the Italian Journal of Mammalogy, 23(2), 12-18.

Glucocorticoid Catch Tray

The temporal resolution of glucocorticoid measurements suffer because of the sampling methods (e.g., blood, hair, feces). However, in caged animals, we have the opportunity to unobtrusively collect feces through a catch tray, yet it would take a monumental effort on behalf of a researcher to obtain and organize those samples every ~2 hours. Therefore, a collection mechanism is needed that is robust and could be approved on an institutional protocol.

Key Questions. Has anyone done this? What types of catch trays or motorized devices exist that can withstand the elements (i.e. IP6)? How do we ensure feces make it through the cage and we are not collecting old samples?

  1. Littermaid: https://www.youtube.com/watch?v=0o1LkLkFMrQ

SOFTWARE

Power Planning and Optimal Recording Techniques

Bio-loggers implemented on small animals cannot record high-resolution data (>200 Hz) for very long due to body mass limitations on battery size. Therefore, in order to perform long-duration studies, sub-sampling data is necessary, where the devices transition from a low-power, to high-power mode. The cost of losing important information about the animal’s behavior or physiology is therefore at risk, however, the relative trade-off is not well characterized.

Key Questions. Are there existing models or tools that have dealt with this problem? Are there any novel recording regimes that we could implement? What are the best “wake-up” mechanisms to trigger a recording? Is there a critical inflection point where sub-sampling begins to affect data interpretation?

  1. Spivey, R. J., & Bishop, C. M. (2014). An implantable instrument for studying the long-term flight biology of migratory birds. Rev Sci Instrum, 85(1), 014301. doi:10.1063/1.4854635

APPLICATIONS

Circadian Entrainment

There are cues all around us, namely, light/dark cycles that regulate our internal circadian rhythms. When these cues are obstructed, health is compromised. The Yukon is a good example where darkness is reduced during summer. The effects of such a drastic change on the ability to sleep deeply has many open questions. Any effort to correlate stress and sleep (as well as sleep states) must consider the circadian pressures that are present and whether access to deep sleep states is possible.

Key Questions. Why do we get a “poor sleep” when we watch tv at night? Do those effects apply to terrestrial environments and seasonal shifts in light availability? Does circadian entrainment correlate with performance or fitness? How do we measure the circadian phase? Can we augment the environment to enhance deep sleep?

  1. Eban-Rothschild, A., Giardino, W. J., & de Lecea, L. (2017). To sleep or not to sleep: neuronal and ecological insights. Current Opinion in Neurobiology, 44, 132-138. doi:10.1016/j.conb.2017.04.010
  2. Bellesi, M., Riedner, B. A., Garcia-Molina, G. N., Cirelli, C., & Tononi, G. (2014). Enhancement of sleep slow waves: underlying mechanisms and practical consequences. Front Syst Neurosci, 8, 208. doi:10.3389/fnsys.2014.00208
  3. Aulsebrook, A. E., Jones, T. M., Rattenborg, N. C., Roth, T. C., & Lesku, J. A. (2016). Sleep Ecophysiology: Integrating Neuroscience and Ecology. Trends Ecol Evol, 31(8), 590-599. doi:10.1016/j.tree.2016.05.004
  4. Goel, N., Basner, M., Rao, H., & Dinges, D. F. (2013). Circadian rhythms, sleep deprivation, and human performance. In Progress in molecular biology and translational science 119 (pp. 155-190). Elsevier.

Neural Entrainment

Brains rhythms are correlated with, and potentially causal to, cognitive and behavioral states. Electrical or optogenetic stimulation has proved useful in determining how inducing or augmenting rhythms affects an organism. However, how rhythms can be entrained via external stimulation is less clear. Many modalities have been considered: auditory, visual, tactile, etc. In addition to efficacy and spatial distribution of these rhythms on the brain (i.e. does auditory entrainment only affect auditory circuits?), it is appreciated that out of phase stimulation can reduce oscillatory patterns rather than induce them, a phenomenon under current investigation in the fields of brain stimulation and biofeedback.

Key Questions. What are the current, validated methods of entrainment? How would we achieve this in a bio-logger or animal? How would we validate it? How to accomplish real-time oscillation phase detection (and do we need to)?

  1. Kim, J., Gulati, T., & Ganguly, K. (2019). Competing Roles of Slow Oscillations and Delta Waves in Memory Consolidation versus Forgetting. Cell, 179(2), 514-526. e13. Retrieved from https://www.sciencedirect.com/science/article/pii/S0092867419309596
  2. Gaidica, M., Hurst, A., Cyr, C., & Leventhal, D. K. (2019). Interactions between motor thalamic field potentials and single unit spiking predict behavior in rats. doi:10.1101/642991
  3. Cagnan, H., Pedrosa, D., Little, S., Pogosyan, A., Cheeran, B., Aziz, T., . . . Brown, P. (2017). Stimulating at the right time: phase-specific deep brain stimulation. Brain, 140(1), 132-145. doi:10.1093/brain/aww286
  4. EEG Analysis on Brain.fm (Sleep): https://www.brain.fm/assets/pdfs/EEGSleepAnalysis.pdf

Physical and Cognitive Performance Tasks

Wild animals offer a significant challenge in assessing day-to-day performance measures. However, in order to translate fieldwork to problems of human performance, we need experiments that do just that. Furthermore, training a wild animal is not only sufficiently difficult but may augment their environment in a way that affects the variables being studied (e.g., if a behavior is rewarded, they are increasing their calorie intake and likely to forage less). Developing a set of experiments that addresses both physical and cognitive performance would bolster studies attempting to address human work where deficits in these domains have already been demonstrated.

Key Questions. What exists—who has measured these variables in wild animals? Are there any passive measures that are highly correlated (e.g., max acceleration of movement, cache size, mating success)? What are the barriers to implementing a physical/cognitive test in the field?

  1. Basner, M., Savitt, A., Moore, T. M., Port, A. M., McGuire, S., Ecker, A. J., . . . Gur, R. C. (2015). Development and Validation of the Cognition Test Battery for Spaceflight. Aerosp Med Hum Perform, 86(11), 942-952. doi:10.3357/AMHP.4343.2015
  2. Anderson, R. A., McBrayer, L. D., & Herrel, A. (2008). Bite force in vertebrates: opportunities and caveats for use of a nonpareil whole-animal performance measure. Biological Journal of the Linnean Society, 93(4), 709-720.
Printed from https://github.com/mattgaidica/biologging/wiki/Open-Questions

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