Data from: A snapping shrimp has the fastest vision of any aquatic animal
Cite this dataset
Kingston, Alexandra; Chappell, Daniel; Speiser, Daniel (2020). Data from: A snapping shrimp has the fastest vision of any aquatic animal [Dataset]. Dryad. https://doi.org/10.5061/dryad.wdbrv15kp
Animals use their sensory systems to sample information from their environments. The physiological properties of sensory systems differ, leading animals to perceive their environments in different ways. For example, eyes have different temporal sampling rates, with faster-sampling eyes able to resolve faster-moving scenes. Eyes can also have different dynamic ranges. For every eye, there is a light level below which vision is unreliable because of an insufficient signal-to-noise ratio and a light level above which the photoreceptors are saturated. Here, we report the eyes of the snapping shrimp Alpheus heterochaelis have a temporal sampling rate of at least 160 Hz, making them the fastest-sampling eyes ever described in an aquatic animal. Fast-sampling eyes help flying animals detect objects moving across their retinas at high angular velocities. A. heterochaelis are fast-moving animals that live in turbid, structurally-complex oyster reefs and their fast-sampling eyes, like those of flying animals, may help them detect objects moving rapidly across their retinas. We also report the eyes of A. heterochaelis have a broad dynamic range that spans conditions from late twilight (~1 lux) to direct sunlight (~100,000 lux), a finding consistent with the circatidal activity patterns of this shallow-dwelling species.
Equipment for electroretinography
For ERG, we used equipment and methods described previously . We amplified DC signals using an AM Systems model 3000 AC/DC differential amplifier with headstage (Sequim, WA) set to a low-pass cut-off frequency of 20 kHz, digitized signals using a ADInstruments PowerLab model 8/35 data acquisition board (Colorado Springs, CO), and compared signals using LabChart 8 Pro (ADInstruments). We dampened electromagnetic and vibrational noise by taking recordings inside a custom-built Faraday cage that was set atop a passively isolated air table with an attached breadboard (ThorLabs SDH7512 and B3048F; Newton, NJ). As electrodes, we used electrolytically sharpened 0.2 mm tungsten rods (A-M Systems, Sequim, WA). We placed these electrodes using Narishige MM-3 manual micromanipulators (Amityville, NY).
We used a 150 W tungsten-halogen lamp (Spectral Products ASBN-W150-PV; Putnam, CT) to generate light for test stimuli and then adjusted the intensity and temporal dynamics of this light using, respectively, a continuously variable, circular neutral density filter (Edmund Optics 54-082; Barrington, NJ) and a Uniblitz LS3 high speed shutter (Rochester, NY). For adapting stimuli, we produced and controlled light with a 20 W tungsten-halogen lamp with an integrated shutter (Ocean Optics HL-2000-HP-FHSA; Dunedin, FL), along with a continuously variable, circular neutral density filter (Edmund Optics 54-082).
We quantified the absolute irradiance (integrated from 375 to 725 nm) of the test stimuli and adapting stimuli at a distance and orientation similar to those of the preparations. To do so, we used a spectrometer system with components from Ocean Optics that included a Flame-S-VIS-NIR-ES spectrometer, a QP400-1-UV-VIS optical fiber, and a CC-3 cosine-corrector. To calibrate the absolute response of the spectrometer, we used a HL-3P-CAL Vis-NIR calibrated light source. We operated the system using Ocean View software.
Procedures for electroretinography
To prepare animals for ERG, we chilled them in ice cold NSW. Next, to prevent animals from desiccating, we wrapped them in a Kimwipe that had been soaked in chilled NSW. We then attached animals to a nylon post by wrapping them in Parafilm. To perform monopolar recordings, we placed the recording electrode into an animal's right eye and placed the reference electrode, electrically coupled to ground, into the animal's dorsal thorax.
To find an appropriate stimulus intensity for assessing the CFFmax of the eyes of A. heterochaelis, we calculated their response–stimulus intensity (VlogI) function. To do so, we used ERG to record the response magnitudes of eyes (n = 8) to white light stimuli of varying intensities . In these trials, we dark-adapted animals for 15 minutes, then presented a series of stimuli in which each stimulus lasted for 1 s and was followed by a 15 s dark period. The intensities of these stimuli ranged from 1.97 x 1010 (~ 0.01 lux, equivalent to a quarter moon) to 1.57 x 1017 photons/cm2/s (~100,000 lux, equivalent to direct sunlight). To analyze our results, we normalized the response magnitudes of eyes, averaged these normalized responses, and then fit a curve to the averaged results using the Zettler modification of the Naka-Rushton function .
Next, we used ERG to assess the CFFmax of the eyes of A. heterochaelis. Prior to recordings, we light-adapted animals for 15 minutes under white light with an intensity of 3.65 x 1016 photons/cm2/s. We recorded the responses of eyes to a flickering white light stimulus with an intensity of 1.57 x 1017 photons/cm2/s . In all trials, we kept the adapting light on continuously, presented stimuli in increasing steps of 10 Hz, and determined the durations of light stimuli and rest periods based on the requirements of the ERG system. We ran three sets of trials, each with separate groups of animals. In the first set of trials, we presented A. heterochaelis (n = 6) with a series of light stimuli flickering at rates of 30-100 Hz in which each stimulus lasted for 0.75 s and was followed by a 60 s rest period. In our second set of trials, we presented animals (n = 6) with a series of light stimuli flickering at rates of 60-130 Hz in which each stimulus lasted for 0.5 s and was followed by a 60 s rest period. In our third set of trials, we presented animals (n = 8) with a series of light stimuli flickering at rates of 100-200 Hz in which each stimulus lasted for 0.5 s and was followed by a 90 s rest period.
To assess the range of frequencies over which the eyes of A. heterochaelis were able to follow flickering light stimuli, we used R to implement an approach similar to Bok et al. . We prepared electrophysiological recordings for analysis by smoothing them with a moving average algorithm and then linearly detrending them. Next, we applied a fast Fourier transform (FFT) to get the relative power of the FFT of the responses of each eye at each frequency of stimulation. We generated power curves for each eye and then normalized and averaged the power curves to produce one averaged power curve for each of the three sets of trials. To evaluate whether an eye was following a light stimulus flickering at a particular frequency, we used a 5% relative power threshold. We defined maximum critical flicker fusion frequency (CFFmax) as the highest frequency stimulus for which the averaged relative powers of the FFTs of the responses of eyes (hereafter “averaged response powers”) remained above the 5% power threshold.
National Science Foundation, Award: 1457148
University of South Carolina, Award: ASPIRE II-B