Name: probing the limits of egg recognition using egg rejection experiments along phenotypic gradients
Uploaded: 2018-08-22T13:00:00
Description: Watch this Scientific Journal Video about Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients at JoVE.com

MEH was funded by the HJ Van Cleave Professorship at the University of Illinois, Urbana-Champaign. In addition, for funding we thank the Human Frontier Science Program (to M.E.H. and T.G.) and the European Social Fund and the state budget of the Czech Republic, project no. CZ.1.07/2.3.00/30.0041 (to T.G.). We thank Ocean Optics for covering publication costs.

All methods described here have been approved by the Institutional Animal Care and Use Committee (IACUC) of Long Island University-Post.
1. Mixing Acrylic Paints
<ol>
	<li>Mix the eggshell ground coloration, which is the color that will uniformly cover the entire eggshell surface. The following recipe will make 50 g of paint, which will fill a little more than two 22 mL aluminum paint tubes.
	<ol>
		<li>Generate a blue-green color, representing a blue-green eggshell (e.g., an Americ...

Although egg rejection experiments are the most common method to study brood parasite-host coevolution70, concerted efforts to standardize materials, techniques, or protocols are lacking. This is especially problematic for meta-analyses. No meta-analysis, to our knowledge, of host egg rejection so far has controlled for methodological discrepancies among studies71,72, including what is considered mimetic or non-mimetic. This represents a m...

Brood parasites lay their eggs in the nests of other species that may then raise their young and pay the costs associated with parental care1,2,3. This act of deception to outwit the host on the part of the parasite and sleuthing to detect the parasite on the part of the host provides strong selective pressures on both actors. In some cases of avian brood parasitism, the host&#39;s recognition of disparate parasitic eggs selects for parasites that mimic host eggs, which produces an evolutionary arms race between host and parasite4. Studying brood parasitism is important because it is a model system for investigating coevolutionary dynamics and decision-making in the wild5. Egg rejection experiments are one of the most common methods used for studying avian brood parasitism in the field and an important tool that ecologists use to investigate interspecific interactions6.
During the course of egg rejection experiments, researchers typically introduce natural or model eggs and assess the host&#39;s response to these experimental eggs over a standardized period. Such experiments can involve swapping real eggs (that vary in appearance) between nests7, or dyeing or painting the surfaces of real eggs (optionally adding patterns) and returning them to their original nests8, or generating model eggs that have manipulated traits such as color9, spotting10, size11, and/or shape12. The host response to eggs of varying appearance can provide valuable insight into the information content they use to reach an egg rejection decision13 and just how different that egg needs to be to elicit a response14. Optimal acceptance threshold theory15 states that hosts should balance the risks of mistakenly accepting a parasitic egg (acceptance error) or mistakenly removing their own egg (rejection error) by examining the difference between their own eggs (or an internal template of those eggs) and the parasitic eggs. As such, an acceptance threshold exists beyond which hosts decide a stimulus is too different to tolerate. When parasitism risk is low, the risk of acceptance errors is lower than when the risk of parasitism is high; thus, decisions are context specific and will shift appropriately as perceived risks change14,16,17.
Optimal acceptance threshold theory assumes that hosts base decisions upon continuous variation in host and parasite phenotypes. Therefore, measuring host responses to varying parasite phenotypes is necessary to establish how tolerant a host population (with its own phenotypic variation) is to a range of parasitic phenotypes. However, virtually all prior studies have relied on categorical egg color and maculation treatments (e.g., mimetic/non-mimetic). Only if host eggshell phenotypes do not vary, which is not a biologically practical expectation, would all responses be directly comparable (regardless of the degree of mimicry). Otherwise, a &#34;mimetic&#34; egg model will vary in how similar it is to host eggs within and between populations, which could potentially lead to confusion when comparing findings18. Theory suggests that host decisions are based upon the difference between the parasitic egg and their own14, not necessarily a particular parasitic egg color. Therefore, using a single egg model type is not an ideal approach to test hypotheses on host decision thresholds or discrimination abilities, unless the just noticeable difference (hereafter JND) between the egg model type and individual host egg color is the variable of interest. This also applies to experimental studies that swap or add natural eggs to test host responses to a natural range of colors19. However, while these studies do allow for variation in host and parasite phenotypes, they are limited by natural variation found in traits6, particularly when using conspecific eggs7.
By contrast, researchers that make artificial eggs of varied colors are free from the constraints of natural variation (e.g., they can investigate responses to superstimuli20), allowing them to probe the limits of host perception6. Recent research has used novel techniques to measure host responses across a phenotypic range, by painting experimental eggs designed to match and surpass the natural range of variation in eggshell9 and spot colors21. Studying host responses to eggs with colors along gradients can uncover underlying cognitive processes because theoretical predictions, such as acceptance thresholds15 or coevolved mimicry4, are based on continuous differences between traits. For example, by using this approach, Dainson et al.21 established that when chromatic contrast between eggshell ground coloration and spot coloration is higher, the American Robin Turdus migratorius tends to reject eggs more strongly. This finding provides valuable insights on how this host processes information, in this case through spotting, to decide whether to remove a parasitic egg. By customizing paint mixtures, researchers can precisely manipulate the similarity between an experimental egg&#39;s color and host&#39;s egg color, while standardizing other confounding factors such as spotting patterns10, egg size22 and egg shape23.
To encourage further replication and metareplication24 of classic and recent egg rejection work, it is important that scientists use methodologies that are standardized across phylogeny (different host species)7,22, space (different host populations)7,22,25,26 and time (different breeding seasons)7,22,25,26,27, which was done only rarely. Methodologies that were not standardized28 were later shown to lead to artefactual results29,30. This paper serves as a set of guidelines for researchers seeking to replicate this type of egg rejection experiment that examines responses to continuous variation and highlights a number of important methodological concepts: the importance of control nests, a priori hypotheses, metareplication, pseudoreplication, and color and spectral analysis. Despite egg rejection experiments dominating the field of avian host-parasite coevolution, no comprehensive protocol exists yet. Therefore, these guidelines will be a valuable resource to increase inter- and intra-lab repeatability as the true test of any hypothesis lies in metareplication, i.e., repeating whole studies across phylogeny, space and time24, which can only be meaningfully done when using consistent methods29,30,31.

<table>
	<tbody>
		<tr>
			<td>Replicator Mini +</td>
			<td>Makerbot</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Professional Acrylic Paint Cobalt Turquoise Light</td>
			<td>Winsor &#38; Newton</td>
			<td>28382</td>
			<td></td>
		</tr>
		<tr>
			<td>Professional Acrylic Paint Titanium White</td>
			<td>Winsor &#38; Newton</td>
			<td>28489</td>
			<td></td>
		</tr>
		<tr>
			<td>Professional Acrylic Paint Cobalt Green</td>
			<td>Winsor &#38; Newton</td>
			<td>28381</td>
			<td></td>
		</tr>
		<tr>
			<td>Professional Acrylic Paint Cobalt Turquoise</td>
			<td>Winsor &#38; Newton</td>
			<td>28449</td>
			<td></td>
		</tr>
		<tr>
			<td>Professional Acrylic Paint Burnt Umber</td>
			<td>Winsor &#38; Newton</td>
			<td>28433</td>
			<td></td>
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		<tr>
			<td>Professional Acrylic Paint Red Iron Oxide</td>
			<td>Winsor &#38; Newton</td>
			<td>28486</td>
			<td></td>
		</tr>
		<tr>
			<td>Professional Acrylic Paint Cadmium Orange</td>
			<td>Winsor &#38; Newton</td>
			<td>28437</td>
			<td></td>
		</tr>
		<tr>
			<td>Professional Acrylic Paint Raw Umber Light</td>
			<td>Winsor &#38; Newton</td>
			<td>28391</td>
			<td></td>
		</tr>
		<tr>
			<td>Professional Acrylic Paint Yellow Ochre</td>
			<td>Winsor &#38; Newton</td>
			<td>28491</td>
			<td></td>
		</tr>
		<tr>
			<td>Professional Acrylic Paint Mars Black</td>
			<td>Winsor &#38; Newton</td>
			<td>28460</td>
			<td></td>
		</tr>
		<tr>
			<td>Paint Brush</td>
			<td>Utrecht</td>
			<td>206-FB</td>
			<td>Filbert brush</td>
		</tr>
		<tr>
			<td>Paint Brush</td>
			<td>Utrecht</td>
			<td>206-F</td>
			<td>Flat brush</td>
		</tr>
		<tr>
			<td>Hair Dryer</td>
			<td>Oster</td>
			<td>202</td>
			<td></td>
		</tr>
		<tr>
			<td>Fiber optic cables</td>
			<td>Ocean Optics Inc.</td>
			<td>OCF-103813</td>
			<td>1 m custom bifurcating fiber optic assembly with blue zip tube (PVDF), 3.8mm nominal OD jeacketing and 2 legs</td>
		</tr>
		<tr>
			<td>Spectrometer</td>
			<td>Ocean Optics Inc.</td>
			<td>Jaz</td>
			<td>Spectrometer unit with a 50 um slit width, installed with a 200-850 nm detector (DET2B-200-850), and grating option # 2.</td>
		</tr>
		<tr>
			<td>Battery and SD card module for spectrometer</td>
			<td>Ocean Optics Inc.</td>
			<td>Jaz-B</td>
			<td></td>
		</tr>
		<tr>
			<td>Light source</td>
			<td>Ocean Optics Inc.</td>
			<td>Jaz-PX</td>
			<td>A pulsed xenon light source</td>
		</tr>
		<tr>
			<td>White standard</td>
			<td>Ocean Optics Inc.</td>
			<td>WS-1-SL</td>
			<td>made from Spectralon</td>
		</tr>
		<tr>
			<td>OHAUS Adventurer Pro Scale</td>
			<td>OHAUS</td>
			<td>AV114C</td>
			<td>A precision microbalance</td>
		</tr>
		<tr>
			<td>Gemini-20 portable scale</td>
			<td>AWS</td>
			<td>Gemini-20</td>
			<td>A standard scale</td>
		</tr>
		<tr>
			<td>Empty Aluminum Paint Tubes (22 ml)</td>
			<td>Creative Mark</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Telescopic mirror</td>
			<td>SE</td>
			<td>8014TM</td>
			<td></td>
		</tr>
		<tr>
			<td>GPS</td>
			<td>Garmin</td>
			<td>Oregon 600</td>
			<td></td>
		</tr>
		<tr>
			<td>220-grit sandpaper</td>
			<td>3M</td>
			<td>21220-SBP-15</td>
			<td>very fine sandpaper</td>
		</tr>
		<tr>
			<td>400-grit sandpaper</td>
			<td>3M</td>
			<td>20400-SBP-5</td>
			<td>very fine sandpaper</td>
		</tr>
		<tr>
			<td>color analysis software: &#8216;pavo&#8217;, an R package</td>
			<td>for use in, R: A language and environment for statistical computing</td>
			<td>v 1.3.1</td>
			<td>https://cran.r-project.org/web/packages/pavo/index.html</td>
		</tr>
		<tr>
			<td>UV clear transparent</td>
			<td>Flock off!</td>
			<td>UV-001</td>
			<td>A transparent ultraviolet paint</td>
		</tr>
		<tr>
			<td>Plastic sandwich bags</td>
			<td>Ziploc</td>
			<td></td>
			<td>Regular plastic sandwich bags from Ziploc that can be purchased at the supermarket.</td>
		</tr>
		<tr>
			<td>Kimwipes</td>
			<td>Kimberly-Clark Professional</td>
			<td>34120</td>
			<td>11 x 21 cm kimwipes</td>
		</tr>
		<tr>
			<td>Toothbrush</td>
			<td>Colgate</td>
			<td></td>
			<td>Toothbrush</td>
		</tr>
	</tbody>
</table>

probing the limits of egg recognition using egg rejection experiments along phenotypic gradients

Brood parasites lay their eggs in other females' nests, leaving the host parents to hatch and rear their young. Studying how brood parasites manipulate hosts into raising their young and how hosts detect parasitism provide important insights in the field of coevolutionary biology. Brood parasites, such as cuckoos and cowbirds, gain an evolutionary advantage because they do not have to pay the costs of rearing their own young. However, these costs select for host defenses against all developmental stages of parasites, including eggs, their young, and adults. Egg rejection experiments are the most common method used to study host defenses. During these experiments, a researcher places an experimental egg in a host nest and monitors how hosts respond. Color is often manipulated, and the expectation is that the likelihood of egg discrimination and the degree of dissimilarity between the host and experimental egg are positively related. This paper serves as a guide for conducting egg rejection experiments from describing methods for creating consistent egg colors to analyzing the findings of such experiments. Special attention is given to a new method involving uniquely colored eggs along color gradients that has the potential to explore color biases in host recognition. Without standardization, it is not possible to compare findings between studies in a meaningful way; a standard protocol within this field will allow for increasingly accurate and comparable results for further experiments.

Generating colorful egg models
Reflectance spectra of custom paint mixtures and natural eggs are shown in Figure&#160;1A-1D. Paint mixtures used in brood parasitism studies should closely correspond with natural reflectance measurements in terms of spectral shape (color) and magnitude (brightness). If that is achieved, the color of the experimental egg should be per...

Watch this Scientific Journal Video about Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients at JoVE.com

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

This protocol provides guidelines for running egg rejection experiments: outlining techniques for painting experimental egg models to emulate the colors of natural bird eggs, conducting fieldwork, and analyzing the collected data. This protocol provides a uniform method for conducting comparable egg rejection experiments.

Brood parasites lay their eggs in other females' nests, leaving the host parents to hatch and rear their young. Studying how brood parasites manipulate ...

This method can help answer key questions in the field of evolutionary ecology, such as how hosts can discriminate between their own eggs and those of their parasites. The main advantage of this technique is that it provides a reproducible technique for conducting egg rejection experiments. To begin, paint an even coat of titanium white over a 3D printed, or otherwise sculpted, model egg.Use a hairdryer on the cool setting to expedite drying. Once dry, apply high quality acrylic paints to the egg to give it a unique look. Spots can first be added using a brush by hand and then by splattering paint with a toothbrush.To quantify the color, use a spectrometer. First, insert an SD card into the spectrometer. To link the SD card into the system, from the controls, select File System, and then Find SD cards.Complete this by pressing the Home button. Next, attach the fiber optic cables to the spectrometer and light source. Follow the cables to secure the correct ends to the correct connector.Then, insert a customized probe tip into the end of the fiber optic probe. Before proceeding, wash the probe tip with 95%ethanol. Next, turn on the light source by pressing the down button three times.First, select PX Lamp, then select Setup, and lastly, select Free Running from timing controls. Then, wait at least 15 minutes before taking any measurements to let the instrument warm up. While the machine warms up, take note to measure color using a standardized distance between the egg and the probe that has the best signal to noise ratio.Begin at about five millimeters and adjust from there. Once the machine is warmed up, calibrate it. Begin with pressing the Home button to select Tools.Then, from the menu, select Manual control and then select Acquire Parameters. Now, set the box car smoothing. Move the cursor right twice and then increase the box car setting to five using the Up button.Save the change using the green accept button. Next, navigate by pressing down, right, right, to set the averages to 10. Scroll through the 10s digits using the up button, then right one position and set the position of the ones digit.Press the green accept button once complete. Next, press the Home button and select the Reflectants option. Then, place the probe firmly on the white standard and store the saved value by pressing the Up button.Now, place the probe in a dark area away from light. Then, store a dark standard by pressing the scroll right button and view the reflectants by pressing the Menu Down button. Now, measure each eggshell's reflectants six times.Twice near the blunt pole, twice at the equator, and twice at the sharp pole. Be sure to report if the spots are avoided or not. Perform these measures on both the experimental eggs and the natural hosts eggs, which the experimental eggs are intended to replicate.Approach the monitored nest with the usual caution. Then, gently add an experimental egg to a host's nest by sliding it into the side of the nests cup. Do not drop the experimental models, as it can damage the hosts eggs.It's very important that birds don't watch the egg introduction, or if unavoidable, the presence at the time of the experiment controlled for statistically. We found evidence in a number of species that this can help explain their rejection behavior. Always remain at each nest for the same amount of time before retreating.Within a few hours, and periodically thereafter, revisit all the nests to determine the response of the host bird to the experimental egg. When checking on the nests, use a telescopic mirror to avoid the direct contact with either the nest or the clutch. Paint mixtures used in brood parasitism studies should closely correspond with natural reflectants measurements in terms of their spectral shape and magnitude.If that is achieved across both the ultraviolet and visible range, the color of an experimental egg should be perceived by the host as a natural color egg. Avian color perception is accomplished using four photo receptors. The quantum catch from these four photo receptors can be transformed into coordinates within a tetrahedral color space, where each vertex represents the relative stimulation of a specific photo receptor.Into this color space, the coordinates of painted eggs can be plotted. The color of the dot is the color of the egg as humans see it. Most studies have assumed that the hosts respond to trait dissimilarity, such as the difference between a parasitic egg and their own in an absolute or symmetrical fashion.However, most traits vary along multiple dimensions and there is no a priori reason to assume their responses should be similar across the phenotypic space. Research that manipulates traits across their full phenotypic range contests this assumption. When American robins are presented with eggs that were increasingly dissimilar from the bright blue color of their own eggs, they rejected them more frequently than eggs bluer than their own.American robins were also found to be more likely to reject spotted experimental eggs when they perceived those spots as browner then the blue-green color of the eggshell. Robins lay unspotted eggs, but their parasite, the brown-headed cow bird lays eggs with brown spots, such that their eggs appear browner than the American robin's eggs, thus, the response seems adaptive. After watching this video, you should have a good understanding of how to run an egg rejection experiment.Once mastered, this technique can produce comparable results. While attempting this procedure, it's important to collect data from control nests. This will help you determine whether or not hosts abandon their nests in response to the experimental treatment.Don't forget to exercise caution while working with wild animals. It's important to observe precautions, such as visiting nests infrequently, not marking nests, and approaching and leavings nests from different locations, whenever possible. Thank you for watching and good luck with your experiments.

probing-limits-egg-recognition-using-egg-rejection-experiments-along

Research

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Behavior

A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments

Rodents have been traditionally used as a standard animal model in laboratory experiments involving a myriad of sensory, cognitive, and motor tasks. Higher cognitive functions that require precise control over sensorimotor responses such as decision-making and attentional modulation, however, are typically assessed in nonhuman primates. Despite the richness of primate behavior that allows multiple variants of these functions to be studied, the rodent model remains an attractive, cost-effective alternative to primate models. Furthermore, the ability to fully automate operant conditioning in rodents adds unique advantages over the labor intensive training of nonhuman primates while studying a broad range of these complex functions.
Here, we introduce a protocol for operantly conditioning rats on performing working memory tasks. During critical epochs of the task, the protocol ensures that the animal's overt movement is minimized by requiring the animal to 'fixate' until a Go cue is delivered, akin to nonhuman primate experimental design. A simple two alternative forced choice task is implemented to demonstrate the performance. We discuss the application of this paradigm to other tasks.

A fully automated protocol for rodent operant conditioning is proposed. The protocol relies on precise temporal control of behavioral events to investigate the extent to which this control influences neural activity underlying sensorimotor integration and cognitive control experiments.

Rodents have been traditionally used as a standard animal model in laboratory experiments involving a myriad of sensory, cognitive, and motor tasks. ...

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

An evaluation method that includes continuous activities in a daily-living environment was developed for Wearable Mobility Monitoring Systems (WMMS) that attempt to recognize user activities. Participants performed a pre-determined set of daily living actions within a continuous test circuit that included mobility activities (walking, standing, sitting, lying, ascending/descending stairs), daily living tasks (combing hair, brushing teeth, preparing food, eating, washing dishes), and subtle environment changes (opening doors, using an elevator, walking on inclines, traversing staircase landings, walking outdoors). 
To evaluate WMMS performance on this circuit, fifteen able-bodied participants completed the tasks while wearing a smartphone at their right front pelvis. The WMMS application used smartphone accelerometer and gyroscope signals to classify activity states. A gold standard comparison data set was created by video-recording each trial and manually logging activity onset times. Gold standard and WMMS data were analyzed offline. Three classification sets were calculated for each circuit: (i) mobility or immobility, ii) sit, stand, lie, or walking, and (iii) sit, stand, lie, walking, climbing stairs, or small standing movement. Sensitivities, specificities, and F-Scores for activity categorization and changes-of-state were calculated.
The mobile versus immobile classification set had a sensitivity of 86.30% &#177; 7.2% and specificity of 98.96% &#177; 0.6%, while the second prediction set had a sensitivity of 88.35% &#177; 7.80% and specificity of 98.51% &#177; 0.62%. For the third classification set, sensitivity was 84.92% &#177; 6.38% and specificity was 98.17 &#177; 0.62. F1 scores for the first, second and third classification sets were 86.17 &#177; 6.3, 80.19 &#177; 6.36, and 78.42 &#177; 5.96, respectively. This demonstrates that WMMS performance depends on the evaluation protocol in addition to the algorithms. The demonstrated protocol can be used and tailored for evaluating human activity recognition systems in rehabilitation medicine where mobility monitoring may be beneficial in clinical decision-making.

A standardized evaluation method was developed for Wearable Mobility Monitoring Systems (WMMS) that includes continuous activities in a realistic daily living environment. Testing with a series of daily living activities can decrease activity recognition sensitivity; therefore, realistic testing circuits are encouraged for valid evaluation of WMMS performance.

An evaluation method that includes continuous activities in a daily-living environment was developed for Wearable Mobility Monitoring Systems (WMMS) that ...

Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury

The current study presented 60 people with traumatic brain injury (TBI) and 60 controls with isolated facial emotion expressions, isolated vocal emotion expressions, and multimodal (i.e., film clips) stimuli that included contextual cues. All stimuli were presented via computer. Participants were required to indicate how the person in each stimulus was feeling using a forced-choice format. Additionally, for the film clips, participants had to indicate how they felt in response to the stimulus, and the level of intensity with which they experienced that emotion.

This paper describes how to implement a battery of behavioral tasks to examine emotion recognition of isolated facial and vocal emotion expressions, and a novel task using commercial television and film clips to assess multimodal emotion recognition that includes contextual cues.

The current study presented 60 people with traumatic brain injury (TBI) and 60 controls with isolated facial emotion expressions, isolated vocal emotion ...

Novel Object Recognition Test for the Investigation of Learning and Memory in Mice

The object recognition test (ORT) is a commonly used behavioral assay for the investigation of various aspects of learning and memory in mice. The ORT is fairly simple and can be completed over 3 days: habituation day, training day, and testing day. During training, the mouse is allowed to explore 2 identical objects. On test day, one of the training objects is replaced with a novel object. Because mice have an innate preference for novelty, if the mouse recognizes the familiar object, it will spend most of its time at the novel object. Due to this innate preference, there is no need for positive or negative reinforcement or long training schedules. Additionally, the ORT can also be modified for numerous applications. The retention interval can be shortened to examine short-term memory, or lengthened to probe long-term memory. Pharmacological intervention can be used at various times prior to training, after training, or prior to recall to investigate different phases of learning (i.e., acquisition, early or late consolidation, or recall). Overall, the ORT is a relatively low-stress, efficient test for memory in mice, and is appropriate for the detection of neuropsychological changes following pharmacological, biological, or genetic manipulations.

The object recognition test (ORT) is a simple and efficient assay for evaluating learning and memory in mice. The methodology is described below.

The object recognition test (ORT) is a commonly used behavioral assay for the investigation of various aspects of learning and memory in mice. The ORT is ...

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Investigating the interactions among multiple participants is a challenge for researchers from various disciplines, including the decision sciences and spatial cognition. With a local area network and dedicated software platform, experimenters can efficiently monitor the behavior of the participants that are simultaneously immersed in a desktop virtual environment and digitalize the collected data. These capabilities allow for experimental designs in spatial cognition and navigation research that would be difficult (if not impossible) to conduct in the real world. Possible experimental variations include stress during an evacuation, cooperative and competitive search tasks, and other contextual factors that may influence emergent crowd behavior. However, such a laboratory requires maintenance and strict protocols for data collection in a controlled setting. While the external validity of laboratory studies with human participants is sometimes questioned, a number of recent papers suggest that the correspondence between real and virtual environments may be sufficient for studying social behavior in terms of trajectories, hesitations, and spatial decisions. In this article, we describe a method for conducting experiments on decision-making and navigation with up to 36 participants in a networked desktop virtual reality setup (i.e., the Decision Science Laboratory or DeSciL). This experiment protocol can be adapted and applied by other researchers in order to set up a networked desktop virtual reality laboratory.

This paper describes a method for conducting multi-user experiments on decision-making and navigation using a networked computer laboratory.

Investigating the interactions among multiple participants is a challenge for researchers from various disciplines, including the decision sciences and ...

Virtual Reality Experiments with Physiological Measures

Virtual reality (VR) experiments are increasingly employed because of their internal and external validity compared to real-world observation and laboratory experiments, respectively. VR is especially useful for geographic visualizations and investigations of spatial behavior. In spatial behavior research, VR provides a platform for studying the relationship between navigation and physiological measures (e.g., skin conductance, heart rate, blood pressure). Specifically, physiological measures allow researchers to address novel questions and constrain previous theories of spatial abilities, strategies, and performance. For example, individual differences in navigation performance may be explained by the extent to which changes in arousal mediate the effects of task difficulty. However, the complexities in the design and implementation of VR experiments can distract experimenters from their primary research goals and introduce irregularities in data collection and analysis. To address these challenges, the Experiments in Virtual Environments (EVE) framework includes standardized modules such as participant training with the control interface, data collection using questionnaires, the synchronization of physiological measurements, and data storage. EVE also provides the necessary infrastructure for data management, visualization, and evaluation. The present paper describes a protocol that employs the EVE framework to conduct navigation experiments in VR with physiological sensors. The protocol lists the steps necessary for recruiting participants, attaching the physiological sensors, administering the experiment using EVE, and assessing the collected data with EVE evaluation tools. Overall, this protocol will facilitate future research by streamlining the design and implementation of VR experiments with physiological sensors.

Virtual reality (VR) experiments can be difficult to implement and require meticulous planning. This protocol describes a method for the design and implementation of VR experiments that collect physiological data from human participants. The Experiments in Virtual Environments (EVE) framework is employed to accelerate this process.

Virtual reality (VR) experiments are increasingly employed because of their internal and external validity compared to real-world observation and ...

Novel Object Recognition and Object Location Behavioral Testing in Mice on a Budget

Ethologically relevant behavioral testing is a critical component of any study that uses mouse models to study the cognitive effects of various physiological or pathological changes. The object location task (OLT) and the novel object recognition task (NORT) are two effective behavioral tasks commonly used to reveal the function and relative health of specific brain regions involved in memory. While both of these tests exploit the inherent preference of mice for the novelty to reveal memory for previously encountered objects, the OLT primarily evaluates spatial learning, which relies heavily on hippocampal activity. The NORT, in contrast, evaluates non-spatial learning of object identity, which relies on multiple brain regions. Both tasks require an open-field-testing arena, objects with equivalent intrinsic value to mice, appropriate environmental cues, and video recording equipment and the software. Commercially available systems, while convenient, can be costly. This manuscript details a simple, cost-effective method for building the arenas and setting up the equipment necessary to perform the OLT and NORT. Furthermore, the manuscript describes an efficient testing protocol that incorporates both OLT and NORT and provides typical methods for data acquisition and analysis, as well as representative results. Successful completion of these tests can provide valuable insight into the memory function of various mouse model systems and appraise the underlying neural regions that support these functions.

Here we provide a protocol which includes comprehensive instructions for the economical establishment of murine object location and novel object recognition behavioral testing, including the design, cost, and construction of required equipment as well as execution of behavioral testing, data collection, and analysis.

Ethologically relevant behavioral testing is a critical component of any study that uses mouse models to study the cognitive effects of various ...

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

This protocol introduces a method for generating strictly controlled and objectively defined stimuli for figure recognition experiments. A (6, n) figure consists of n line segments that are spanned between n pairs of points located at the vertices of an invisible regular hexagon. The structural properties (graph invariants) and superficial features (non-graph invariants) of each (6, n) figure with n values ranging from 1 to 6 are calculated and stored in a database. Using this database, experimenters can systematically extract appropriate figures depending on the purpose of the experiment. Furthermore, if the database does not contain necessary information, new feature values can sometimes be calculated ad hoc from the formation of a specific (6, n) figure. Let us call a mirror-reflected pair of figures an axisymmetric (Ax) pair. An Ax pair of figures is known to be more difficult to discriminate than a non-identical pair in the decision of whether the shapes of a given pair are rotated-to-be-identical (Idr). The purpose of the present experiment is to examine whether the sameness of line lengths between two figures in a pair causes the discrimination of the pair to be as difficult as that of an Ax pair. Mutually isomorphic figures share common structural properties despite differences in shape. Ax pairs and Idr pairs are special cases of isomorphic pairs. Furthermore, an Ax pair and Idr pair share most of the superficial feature values, except the relative direction from one location to another location across an axis of symmetry is opposite for an Ax pair. Three types of mutually isomorphic (6, 4) figure pairs were generated: Idr; Ax; and non-identical, non-axisymmetric, isomorphic (Nd) pairs. Nd pairs were further classified into three subcategories according to the superficial feature values of the degree of line length differences.

This protocol describes a method for an experiment that examines whether specific graph and non-graph properties (features) are relevant to the recognition of figures. The method uses a database that stores various feature values of respective figures called (6 point, n line) figures.

This protocol introduces a method for generating strictly controlled and objectively defined stimuli for figure recognition experiments. A (6, n) figure ...

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Older adults are slower at recognizing visual objects than younger adults. The same is true for recognizing that a letter string is a real word. People with Alzheimer&#39;s disease (AD) or Mild Cognitive Impairment (MCI) demonstrate even longer responses in written word recognition than elderly controls. Despite the general tendency towards slower recognition in aging and neurocognitive disorders, certain characteristics of words influence word recognition speed regardless of age or neuropathology (e.g., a word&#8217;s frequency of use). We present here a protocol for examining the influence of lexical characteristics on word recognition response times in a simple lexical decision experiment administered to younger and older adults and people with MCI or AD. In this experiment, participants are asked to decide as quickly and accurately as possible whether a given letter string is an actual word or not. We also describe mixed-effects models and principal components analysis that can be used to detect the influence of different types of lexical variables or individual characteristics of participants on word recognition speed.

This article describes how to implement a simple lexical decision experiment to assess written word recognition in neurologically healthy participants and in individuals with dementia and cognitive decline. We also provide a detailed description of reaction time analysis using principal components analysis (PCA) and mixed-effects modeling.

Older adults are slower at recognizing visual objects than younger adults. The same is true for recognizing that a letter string is a real word. People ...

Assessing the Coherence of Parents' Short Narratives Regarding their Child Using the Five-Minute Speech Sample Procedure

Valid and efficient measures for assessing the quality of parent-child relationships are needed to facilitate research and evidence-based practice with parents. This paper focuses on such a method, namely Five-Minute Speech Sample-Coherence (FMSS-Coherence). In this method, a parent is asked to speak for five uninterrupted minutes about her/his child and their relationship. The resulted narrative is coded for coherence, namely the extent to which the parent provides&#160;in the narrative&#160;a clear, consistent, multidimensional and well-supported portrayal of the child. FMSS-Coherence is based on attachment research that shows that the coherence of parents&#8217; narratives is indicative of the quality of the parent-child relationship and child adjustment. It overcomes the limitations of attachment narrative measures which are typically labor intensive. FMSS-Coherence is less nuanced than extant attachment narrative measures. Yet, studies of families from different cultural backgrounds, across different child ages and in the context of typically developing children as well as children with special needs suggest that coherence can be reliably evaluated using the FMSS procedure. Furthermore, parents&#8217; FMSS-Coherence is associated with parenting quality and children&#8217;s socio-emotional adjustment. Thus, it holds promise for researchers and practitioners who seek a relatively time- and cost-effective method for assessing the coherence of parents&#8217; narratives regarding their child.

This paper introduces a method for assessing the coherence of parents' short narratives regarding their child and their relationship using the five-minute speech sample procedure.

Valid and efficient measures for assessing the quality of parent-child relationships are needed to facilitate research and evidence-based practice with ...