University of Colorado Boulder Animal Cognition Discussion Questions

Hi, this is for the Psychology class called Animal Cognition, follow the instructions below and answer the questions based on the podcast and the link reading for instruction 1 and based on the podcast and the 2 pdf attached for instruction 2. See the instructions below. Please label the answers as instruction 1 and instruction 2 and the sub answers respectively with their numbers.

Instruction 1

For this assignment, you will be listening to two podcasts and reading one cartoon. Respond to the four questions below in the text box.

Read this Oatmeal cartoon (

https://theoatmeal.com/comics/mantis_shrimp

)

and listen to 8:10 -17:22 of this Radiolab podcast from 2012 (?), “Colors

(

https://www.radiolab.org/episodes/211119-colors

)

Question 1. They say on the show that the mantis shrimp sees the broadest rainbow of all the animals. On what basis do they make this statement?

Next, listen to Pulizter-Prize-winning author Ed Yong talk about his book An Immense World: How Animal Senses Reveal the Hidden Realms Around Us. Listen to the Armchair Expert (

https://armchairexpertpod.com/pods/ed-yong

) from 16:00 to 1:07 and answer the questions below:

Question 2.  Ed Yong says his latest book is about something we, as humans, “miss.” What is he referring to?

3. What is an “umwelt”?

4. How do we know birds have a magnetic sense?

5. How do rattlesnakes detect heat?

Instruction 2

There are two sections of the current assignment, outlined below. Be sure to do both of them.

First, listen to the Radiolab segment, “Rippin the Rainbow and Even Newer One” (14:07-end), which you can listen to online at (

https://radiolab.org/episodes/rippin-the-rainbow-an-even-newer-one

)

1. In a sentence or two, what was the “twist” revealed by this podcast (with respect to the original “Rippin the Rainbow a New One”)?

In class we are going to take a close look at the scientific data that this podcast was based upon, which was published in this Science paper in 2014 (I have attached the pdf below).

For now I just want you to understand the methods they used to determine what colors the mantis shrimp can see.

Read the abstract of the paper (pasted below), and the two paragraphs shown below (highlighted, copied from the original paper):

To better understand the methods, download the Supplementary Materials from that 2014 article (I have attached the pdf)

, and read the following sections:

“Behavioral determination of spectral discrimination”

“Training”

“Testing”

2. After reading these sections, write a few sentences in layperson English (no jargon, no cut-and- paste) about the experiment, being sure to include

The goal of the experiment

How they trained the animals

How they tested the animals

  www.sciencemag.org/content/343/6169/411/suppl/DC1
Supplementary Materials for
A Different Form of Color Vision in Mantis Shrimp
Hanne H. Thoen,* Martin J. How, Tsyr-Huei Chiou, Justin Marshall
*Corresponding author. E-mail: h.thoen@uq.edu.au
Published 24 January 2014, Science 343, 411 (2014)
DOI: 10.1126/science.1245824
This PDF file includes:
Materials and Methods
Figs. S1 and S2
Tables S1 to S3
References (26–29)
Material and Methods
Animal capture and handling
Stomatopods of the species Haptosquilla trispinosa were collected at Lizard Island
Research Station, Australia (GBRMPA Permit no. G12/35005.1, Fisheries Act no.
140763) and transported to our aquarium facility at The University of Queensland.
Animals were kept in saltwater aquaria in a 12h/12h-dark/light cycle with UV enhanced
full-spectrum lighting. Some experiments were also conducted under natural light
conditions at Lizard Island Research Station. Experiments were performed according to
the ethical considerations of the University of Queensland.
Intracellular electrophysiology
Intracellular electrophysiological recordings from the photoreceptors of H.
trispinosa were performed to determine the spectral sensitivities of this species.
Recordings were made using the spectral scan method (9, 26, 27) and were, in brief, as
follows: At least half an hour before each experiment the animal was placed in total
darkness to dark-adapt the photoreceptors. The following steps were then all performed
in dim red light. The animal was killed by chilling and decapitation and the eyestalk was
removed. A small hole was cut through the cornea in the dorsal or ventral hemisphere
using a sharp razorblade, taking care not to disturb the underlying photoreceptor cells.
The location of recorded cells was identified by injecting a fluorescent dye (Alexa Fluor
568, Molecular probes) through the microelectrode. The results from the
electrophysiological recordings are shown in figure 1 and Supplementary Table 1.
Model calculations
The spectral sensitivities (Fig 1) were used to model expected discrimination ability
based on analogue comparison. UV-sensitive photoreceptors were not included in this
modelling or in the following behavioural experiments due to the uncertain connections
between the UV- sensitive R8 cells and the R1-7 cells and to simplify both modelling and
behavioural methods. We used the Vorobyev-Osorio receptor noise-limited colour
opponent model (21) for a simplified serial di-chromatic system, using the spectral
sensitivities obtained from electrophysiological recordings for each row in the midband.
The comparison of within-row spectral sensitivities is based on previous hypotheses
detailed in Neumeyer (4) and later reviewed in Marshall et al. (3). From this model we
get the ΔSt, which is an estimated perceptual distance between the two stimuli. This
distance can then be used to predict the Δλ function by setting a threshold distance for
ΔS∆S. In this instance we set the threshold distance to be 1 according to Koshitaka et al.
(20). See Supplementary Text for details of the visual modelling.
Behavioural determination of spectral discrimination (Δλ).
Small burrows were constructed from small plastic screw-top vials covered with
black electrical tape to darken the interior (25) (Fig 1). The burrow was placed in a
container filled with sediment and one animal was added per container. The animal was
allowed to habituate for around 2 days before the experiment. Colour stimuli were
produced using a pair of high-pass and low-pass linear variable filters (LVF-H, LVF-L,
Ocean-optics) mounted together to create a nearly monochromatic light with a FWHM of
~ 20nm (Supplementary figure 1). The filters were placed in an adjustable filter holder
(Ocean optics, FHS-LVF) with a micromanipulator (Mitutoyo 151-223) placed on one
end to enable the fine-tuning of the correct wavelengths. A halogen light source
(AmScope Haloid 150w) was connected to a pair of adjustable filter holders via a
collimating lens using a split light guide. On the other side of the filters another
collimating lens guided the monochromatic light into an outgoing optical fibre (1000µm,
Ocean Optics). Prior to stimulus presentation, the animal’s burrow was temporarily
blocked with a small piece of white plastic sheet while the stimuli were placed in the
correct position to ensure standardised placement for each animal. When the plastic sheet
was removed the animal was therefore presented with two different light stimuli from the
end of each optical fibre. The natural foraging behaviour of this species involves
smashing or grabbing objects in front of the burrow, a behaviour which was exploited in
the current experiment, where a choice was determined by the animal swimming out and
grabbing the end of the optical fibre. The optical fibres were placed as close to each other
as possible (~1cm). This allowed animals to make and demonstrate a positive choice by
grabbing the stimulus while having both stimuli simultaneously in view.
Brightness control
Earlier calculations of the relative size and lengths of various parts of the ommatidia
in stomatopods (such as aperture widths, filter lengths and rhabdoms dimensions) (28)
have led to the conclusion that the photon absorption rates of the different photoreceptor
types are very similar, enabling the eye to operate at similar levels of stimulation. We
therefore kept the brightness of the presented stimuli as similar as possible using a variety
of neutral density (ND) filters, providing an absolute irradiance of around 2.16E15
photons/cm2/sec. In addition to this we performed several brightness control experiments
in which the intensity of light was varied randomly between choice stimuli over three log
units using ND filters, in order to make sure that the trained stomatopods did not use
brightness as a cue when making choices. We found no significant differences in
response rate between light and the dark stimuli (Supplementary figure 2) implying that
the trained animals made choices based only on colour information.
Training:
The animals were primed for about two weeks before testing using small pieces of
food attached to the end of a single optical fibre displaying the correct training colour.
We used 10 different training wavelengths, 400, 425, 450, 470, 500, 525, 570, 578, 628
and 650nm. After about 1 – 1½ week most of the animals were actively choosing, and the
priming continued with the trained colour. During priming the food reward was placed
directly on the target to allow the association between the training wavelength and food.
During testing, two cleaned or fresh fibres were used, one of which displayed a
wavelength 50 nm away from the trained wavelength either towards longer wavelengths
or towards shorter wavelengths. The position of the trained and the test stimuli (left –
right) was varied in a semi-randomised order.
Testing:
Testing was carried out approximately 4-6 times per day for 4-5 days each week.
During testing, re-enforcement was provided using a food-stick immediately after a
correct choice was made. An animal was therefore always rewarded if it made a correct
choice, thus avoiding any loss of motivation due to the loss of association between the
correct choice and the reward. Between 4 and 7 animals were successfully trained to each
of the ten training wavelengths. Wavelengths of the test stimuli were 5, 8, 12, 25, 50 and
100 nm longer or shorter than the trained wavelengths.
Statistical analysis
As the target choice was a binary response variable (correct or incorrect) we used a
binomial test to determine whether the choice frequencies were significantly different
from chance (P0 = 0.5, α = 0.05). All analyses were carried out using the open source
software R (29). The results from these tests are displayed in Supplementary Table 2 and
3.
Supplementary Text
Supplementary formulas 1
Visual modelling of a simplified serial di-chromatic system
For a dichromatic system the distance between stimuli will be:
2
(1)
( !q1 ” !q2 )
t 2
(!S ) =
e12 + e22
with
qi = ki ! Ri ( ! ) I ( ! ) d !
(2)
where ! = 1,2, … !; !! is the quantum catch of receptor !; ei is the noise level of a
particular group of receptors; ! is wavelength, Ri is the spectral sensitivity of receptor !,
!(!) is the spectrum of the stimuli, !! is an arbitrary scaling factor and the integration is
over the visible spectrum. !! is set so that the quantum catches for the background is
equal to 1:
(3)
ki = 1 / ! Ri ( ! )I b ( ! ) d !
!
!
where ! (!) is the background spectrum.
Noise is estimated using the following model:
ei = vi / !i
(4)
where !! is the noise level of a single photoreceptor and !! is the number of
receptors of a type !.
Here we assumed that noise in different photoreceptors were similar and set the
noise to 0.05 (Weber fraction), which is a value that has been used in previous studies of
animal colour vision (20, 21).
Using the threshold distance of 1 together with the data from equation 1) we can
predict the Δλ function using:
(5)
!! = 1 / ( !S t ) Ci
where  !! is the interval between the stimulus colours.
Housing
Animal
Optical fibres
Collimating lens
Collimating lens
ND – filter
ND – filter
Micromanipulator
Micromanipulator
Collimating lens
Linear
variable
filters
Collimating lens
Lightguides
Lightsource
Fig. S1.
Test setup: Experimental setup for presentation of monochromatic light in front of
stomatopod. The light from a 150w halogen lamp was directed through adjustable linear
variable filters using light guides and collimating lenses. The light was attenuated using
neutral density filters before it was led through two optical fibres (1000µm), which were
positioned in front of the animal.
0.6
0.2
Correct choice
500nm col
500nm int
525nm col
525nm int
Fig. S2
Brightness control: Animals trained to reward stimuli at 500 nm (left) and 525 nm
(right) were tested using the coloured stimuli presented at different light intensities, high
vs. low.. Results show that animal continued to choose the reward colour significantly
above chance (turquoise and green boxes; t-test with Bonferroni adjustment for 500 nm, p
= 0.009, n = 4 and for 525 nm, p = 0.008, n = 4;), while ignoring the effect of intensity
(grey boxes; t-test with Bonferroni adjustment for 500 nm, p = 0.62, n = 4 and for 525nm,
p = 0.67, n=4). Dots underneath each boxplot indicate the type of presented stimuli.
Table S1
Electrophysiological recordings: For each spectral sensitivity maximum (λmax)): number
of cells recorded, range of times each cell was recorded from, total number of recordings
from all cells, the identified midband row and the position (distal/proximal) in the
midband row.
Sensitivity max
No of
Range of
Total no of
Identified
Distal/
(nm)
cells
recordings per
recordings
row
proximal
cell
position
315
1
4
4

R8
325
3
3
9

R8
370
5
3
15

R8
420
6
3-4
20
1
D
445
7
2-4
21
4
D
470
4
3
12
1
P
490
5
3-4
16
4
P
555
5
3-4
18
2
D
585
2
3
6
2
P
610
2
3
6
3
D
665
5
4-5
21
3
P
Table S2
Choice numbers: Number of choices (n) made by (N) number of animals for each
trained wavelength and at each test interval.
No of choices made per test point (n)
Trained wl (nm)
N
100nm
50nm
25nm
12nm
8nm
5nm
400
5

113
98
104


425
4


154
76


450
6

106
103
118


470
7
133
77
76
140


500
5

174
236
182
170
161
525
4

116
187
137
132
123
570
4
82
51
48
99


578
5

138
166
155
127

628
6

209
215
181
236

650
5

84
92
88


Table S3
P-values: Exact p-values for each test and training wavelength using a binomial test (P0 =
0.5, α = 0.05).
Trained wl (nm)
100nm
50nm
25nm
12nm
8nm
5nm
400

5.73e-06
8.00 e-04
0.461


425


1.69e-05
0.211


450

4.55e -06
3.30e-05
0.463


470
1.46e-12
1.53e-06
7.72E-03
0.336


500

1.70e-04
5.68e-05
0.011
0.351
0.682
525

2.70e-05
1.67e-03
0.500
0.060
0.765
570
1.616e-05
3.11e-04
2.97e-02
0.843


578

2.69e-05
1.97e-03
0.012
0.239

628

5.11e-07
1.31e-03
0.117
0.892

650
–  
7.93e-07  
2.47e-06  
0.375  
–  
–  
 
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