We thank Keith Holding for his assistance with chemical analyses at the Rosalind Franklin Science Center, Wolverhampton, and Ben Mantle for the production of the video. We are also grateful to Prof. Gloriano Moneti, Dr. Giuseppe Pieraccini and the members of the University of Florence&#39;s Mass Spectrometry Center, Florence, and to Prof. Luca Calamai and Dr. Marco Michelozzi of the CNR&#39;s ARCA Lab, Florence, for their help with setting up this methodology. The research projects which included the sampling and analysis methods described in the manuscript were supported by two Marie Sk&#322;odowska-Curie Intra European Fellowships (Grant Agreement IDs: 327083, 703611), a small grant (&#39;The sensory enriched primate&#39;) from the Primate Society of Great Britain, and a small research grant (&#39;Do hunter-gatherers have a special sense of smell?&#39;) from the British Academy/The Leverhulme Trust to S.V. The lab work needed to set up this methodology also received funding from the Faculty of Science and Engineering&#39;s Annual Funding Competition (Wolverhampton) to S.V.

1. Sample collection
<ol>
	<li>Sample odors that are one of the following:
	<ol>
		<li>Collect spontaneously released by habituated study subjects (e.g., zoo primates) via scent-marking on sterile filter paper (e.g., scent-gland odor secretions) or directly into vials (e.g., urine).</li>
		<li>Collect by rubbing sterile cotton swabs after training study subjects by using positive reinforcement training.</li>
		<li>Collect by rubbing sterile cotton swabs after sedation of study subjects.</li>
	</ol>
	</li>
	<li>Place samples into sterile 10 mL screw-capped clear glass vials, and seal with screw topped caps incorporating FTFE/silicone septa. Immediately store them at -20 &#176;C. 
	NOTE: It is vital to use clean personal protective equipment, such as nitrile gloves; change them frequently; avoid direct skin contact with samples and vials. It is preferred to use brand-new vials; however, in case of used vials, it is vital to pre-clean the vials, and then use the same protocol.</li>
	<li>Take environmental blanks every time scent-marks are collected. For example, collect the sampling media (e.g., filter paper or swab) and a headspace vial that are exposed to the environment while sampling is undertaken.</li>
</ol>
2. Sample preparation
<ol>
	<li>Prepare samples in the field by cutting with a blade an approximate 10 mm square from a scent-marked filter paper, or the head of the swab, and placing it in a 10 mL screw-topped head-space vial.</li>
	<li>After each sample has been prepared, dispose or clean the blade used to cut the sampling media using an appropriate antibacterial wipe and/or alcohol and dry thoroughly.</li>
	<li>Store all samples at -20 &#176;C. 
	NOTE: Preferred at -20 &#176;C or otherwise as low as practically possible in the field.</li>
</ol>
3. Preparation for analysis
<ol>
	<li>Remove samples from the freezer and allow to warm naturally to room temperature for at least 1 h.</li>
	<li>Set up the analytical method on the GC-MS as follows:
	<ol>
		<li>For SPME analysis conditions, follow the manufacturer&#39;s directions to condition SPME fibers before first use: fiber pre-condition (260 &#176;C for 5 min), sample incubation (40 &#176;C for 2 min), extraction time (15 min), desorption time (2 min), and fiber post-condition (260 &#176;C for 20 min).</li>
		<li>Use the following GC conditions: column (HP5-MS 30 m x 0.25 mm; 0.25 &#181;m), injector temperature (270 &#176;C), flow rate (1 mL/min), injection mode (splitless), GC oven profile (45 &#176;C for 2 min; 4 &#176;C/min to 170 &#176;C; 20 &#176;C/min to 300 &#176;C), MSD transfer line (280 &#176;C). 
		NOTE: To improve between sample retention time consistency the analytical method is retention time locked).</li>
		<li>Use the following MSD conditions: solvent delay (2.5 min) and scan range (29 to 400 amu). 
		NOTE: A range of 10 to 400 was used in previous protocols4.</li>
	</ol>
	</li>
	<li>Ensure that the purge gas supply to the fiber conditioning unit is turned on. 
	&#8203;NOTE: It is vital that the SPME assembly is correctly installed in the auto-sampler and that it is aligned to the auto-sampler trays, fiber conditioning unit and GC inlet port. Incorrect alignment could result in damage or destruction of the SPME fiber.</li>
</ol>
4. Analysis
<ol>
	<li>Place an empty headspace vial (to act as a system blank) in the first position of the GC-MS auto-sampler tray. Place the environmental blank in the second position of the auto-sampler tray. Place the samples for analysis in the subsequent positions of the auto-sample tray.</li>
	<li>Create an analytical sequence to analyze each sample within the sample tray.
	<ol>
		<li>In the MassHunter home screen, select Sequence | Load sequence.</li>
		<li>Complete the sequence table for all blanks and samples by inserting the appropriate information. Save the completed sequence table. 
		NOTE: The exact information for the sequence table will be dependent on the laboratories formatting for the table. Minimum information would normally include sample type, sample name, vial location and number, analytical method and data file location and name (allocation of a data file name that matches the sample name aids future data processing). Additional samples can be added to the sequence during the analysis.</li>
	</ol>
	</li>
	<li>Run the sequence by selecting Sequence | Run sequence.</li>
	<li>After analysis return samples to the freezer as soon as possible. 
	&#8203;NOTE: it may be possible to reanalyze samples, but it should be noted that some volatile components may have been totally extracted during the initial analysis and some compounds may have undergone thermal and bacterial decomposition at 40 &#176;C, thus the resulting chromatogram may not be thoroughly representative of the original scent-marking.</li>
</ol>
5. Data analysis
NOTE: Initial data analysis includes the integration of chromatograms to obtain retention time and peak area data together with tentative identification of peaks using ChemStation software and NIST (National Institute of Standards and Technology) mass spectral databases, version MSD F.01.01.2317. Data analysis can be carried out either manually or through a semi-automated method. If the semi-automated method is used then it is sometimes beneficial to undertake a degree of manual data analysis to verify tentative identifications.
<ol>
	<li>Open the data file by clicking on the appropriate file in the left-hand navigation bar. The total ion chromatogram (TIC) will be displayed in the top window of the data analysis screen.</li>
	<li>To integrate the TIC using the RTE integrator, select Chromatogram | Integrate.</li>
	<li>Adjust integration parameters so that peaks that are greater than 3 x baseline noise are integrated. Select Chromatogram | MS Signal Integration Parameters. In the output box adjust the minimum peak area as appropriate (1.0 produces acceptable results in our examples).</li>
	<li>To identify peaks and generate a summary report, select Export Reports | Library search results report to XLS. 
	NOTE: The spectral libraries to be searched together with the number of library matches to be displayed need to be preset within the software before a library search can be undertaken.</li>
	<li>The resulting spreadsheet report contains integration data for each peak and a tentative spectral library match to assign identity. Typically, the library quality/library match should be &#62;80 to accept the tentative identification. Save the spreadsheet.</li>
	<li>Identify a peak directly from the TIC.
	<ol>
		<li>Choose the peak of interest.</li>
		<li>If the peak is small, zoom in by drawing a box around the peak by holding the left hand mouse button down, stretch the box over the peak and release.</li>
		<li>Place the cursor line so that it is at the highest point of the peak (or just after).</li>
		<li>Double click the right hand mouse button and the mass spectrum for the peak will appear in the lower window of the data analysis screen.</li>
		<li>To search the spectral library, move the cursor anywhere in the spectral window and double click the right hand mouse button. The library search results will appear in a new window.</li>
		<li>To remove the background noise from a spectrum of interest, first double click the right hand mouse button on the peak in question. Then double click the right hand mouse button in an area with no peaks immediately in front of the peak of interest. Select Chromatogram | Subtract spectra. The subtracted spectrum will display in the lower window of the data analysis screen and will display &#39;(-)&#39; next to the SCAN data in the window header.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Wyatt, T. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Pheromones and Animal Behavior: Chemical Signals and Signatures. , (2014).</li><li>Heymann, E. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+neglected+sense-olfaction+in+primate+behavior,+ecology,+and+evolution.">The neglected sense-olfaction in primate behavior, ecology, and evolution.</a> American Journal of Primatology. 68 (6), 519-524 (2006).</li><li>Drea, C. M., Boulet, M., DelBarco-Trillo, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+"secret"+in+secretions:+Methodological+considerations+in+deciphering+primate+olfactory+communication.">The "secret" in secretions: Methodological considerations in deciphering primate olfactory communication.</a> American Journal of Primatology. 75 (7), 621-642 (2013).</li><li>Vaglio, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sternal+gland+scent-marking+signals+sex,+age,+rank+and+group+identity+in+captive+mandrills.">Sternal gland scent-marking signals sex, age, rank and group identity in captive mandrills.</a> Chemical Senses. 41 (2), 177-186 (2016).</li><li>Marneweck, C., J&#252;rgens, A., Shrader, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dung+odours+signal+sex,+age,+territorial+and+oestrous+state+in+white+rhinos.">Dung odours signal sex, age, territorial and oestrous state in white rhinos.</a> Proceedings of the Royal Society of London B: Biological Sciences. 284 (1846), (2016).</li><li>Shear, W. A., Jones, T. H., Miras, H. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+possible+phylogenetic+signal+in+milliped+chemical+defenses.">A possible phylogenetic signal in milliped chemical defenses.</a> Biochemical Systematics and Ecology. 35, 838-842 (2007).</li><li>Kimura, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Volatile+substances+in+feces,+urine+and+urine-marked+feces+of+feral+horses.">Volatile substances in feces, urine and urine-marked feces of feral horses.</a> Canadian Journal of Animal Science. 81 (3), 411-420 (2001).</li><li>Vaglio, S., Minicozzi, P., Bonometti, E., Mello, G., Chiarelli, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Volatile+signals+during+pregnancy:+a+possible+chemical+basis+for+mother-infant+recognition.">Volatile signals during pregnancy: a possible chemical basis for mother-infant recognition.</a> Journal of Chemical Ecology. 35 (1), 131-139 (2009).</li><li>Setchell, J. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chemical+composition+of+scent-gland+secretions+in+an+Old+World+monkey+(Mandrillus+sphinx):+influence+of+sex,+male+status,+and+individual+identity.">Chemical composition of scent-gland secretions in an Old World monkey (Mandrillus sphinx): influence of sex, male status, and individual identity.</a> Chemical Senses. 35 (3), 205-220 (2010).</li><li>Setchell, J. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Odour+signals+MHC+genotype+in+an+Old+World+monkey.">Odour signals MHC genotype in an Old World monkey.</a> Proceedings of the Royal Society of London B: Biological Sciences. 278 (1703), 274-280 (2011).</li><li>Pawliszyn, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Solid phase microextraction: theory and practice. , (1997).</li><li>Janda, E. D., Perry, K., Hankinson, E., Walker, D., Vaglio, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sex+differences+in+scent-marking+in+captive+red-ruffed+lemurs.">Sex differences in scent-marking in captive red-ruffed lemurs.</a> American Journal of Primatology. 81 (1), 22951 (2019).</li></ol>

The authors have nothing to disclose.

The use of control samples, both environmental controls created at the time of sample collection and system blanks, are crucial for the interpretation of the scent-mark samples. Any peaks attributed to the sampling environment or the instrumental system need to be excluded from scent-mark samples so that only the peaks of interest are included in any interpretation. These controls can also play a role in assessing and monitoring the 'health' of the instrumentation.
The protocol includes steps ...

Very little is known about the chemical changes underpinning the olfactory signals in animals1, also because of methodological challenges in recording and quantifying volatile chemical profiles of odors2. There are several potential pitfalls when working with highly complex, chemical matrices; these include when sampling and analyzing the odor samples3.
At the Rosalind Franklin Science Center, University of Wolverhampton, we are undertaking the analysis of odors and scent-marks to understand how they may be used by animals. We combine semiochemistry with behavioral ecology, endocrinology and cytology to improve our understanding of the role played by olfactory signals in animal communication.
We have developed a methodology and then analyzed odors and markings from a variety of species including several non-human primates (i.e., crowned lemurs, red-ruffed lemurs, Japanese macaques, olive baboons, chimpanzees) and other mammals (i.e., cats, cows). We have collected and analyzed a variety of samples, including urine, feces, hair and scent-gland odor secretions. These odors and scent-marks consist of complex mixtures of compounds and therefore any methodology used for their analysis need to include some form of separatory technique. As illustrated, they also occur in a range of matrices which necessitates the use of techniques to extract the components of interest.
Previous studies by Vaglio et al.4 and other authors5 used dynamic headspace extraction (DHS) with gas chromatography-mass spectrometry (GC-MS) while direct solvent extraction6 and complex solvent extractions7 have also been used. Particularly, dynamic headspace sampling involves purging the headspace with a known volume of inert gas that ultimately removes all volatile compounds with the exception of those showing a strong affinity for the sample matrix (for example, polar compounds in aqueous samples).
For the current methodology, we have adopted the technique of headspace solid-phase microextraction (HS-SPME) coupled with GC-MS. In particular, we have developed and enhanced the methodology already used by Vaglio et al. in its previous GC-MS laboratory8,9,10.
Solventless extraction techniques are very effective for analyzing small, highly volatile compounds (which otherwise can be lost easily from a sample) because these methods immobilize compounds on a stable, solid phase support. The HS-SPME uses a &#64257;ber coated with an adsorbent polymer to capture volatile compounds in the sample headspace or to extract dissolved compounds by immersion in an aqueous biological &#64258;uid11. The polymer coating does not bind the compounds strongly, therefore by heating in the injection port of the GC they can be removed. This method is more powerful than solvent extraction techniques and also more effective than DHS.
In the current approach samples are contained within glass vials. These vials are warmed to a temperature of 40 &#176;C to simulate animal body temperature in order to promote the volatile components of the scent-mark to occupy the head-space of the vial. A SPME fiber, coated with 65 &#181;m of polydimethylsiloxane/divinylbenzene (PDMS/DVB) sorbent material, is exposed to the headspace environment and volatile components from the sample are adsorbed onto the fiber. On heating the fiber in the inlet port of a GC-MS, the volatile components are desorbed from the fiber and then separated by the GC. Mass spectral fragmentation patterns are obtained for each component using the MS. By comparison of these mass spectra against mass spectral databases, it can be possible to tentatively identify the components of the scent-mark. Through the use of an auto-sampler, we are able to analyze multiple samples in batches in a consistent manner.
Given that each type of SPME fiber has a different affinity with polar chemicals, the fiber is usually chosen depending on the polarity and/or molecular weight of the target chemical compounds. In addition, the GC conditions are changed depending on the type of GC column and the characteristics of the target chemical compounds.
This technique allows the semi-quantitative analysis of the volatile components of scent-markings by enabling the separation and tentative identification of the components in the sample, followed by the analysis of peak area ratios to look for trends that could signify components of the scent-marking that may be involved in signaling.
The key strengths of this current approach are:
<ul style="list-style-type: square;">
	<li>The range of sample types that can be analyzed.</li>
	<li>No complex sample preparation or extractions are required.</li>
	<li>The ability to analyze volatile components.</li>
	<li>The ability to separate the components of a mixture.</li>
	<li>To be able to identify the components detected.</li>
	<li>The ability to provide semi-quantitative and potentially quantitative information on the components detected.</li>
</ul>

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>10 mL autosampler vials</td>
			<td>Agilent</td>
			<td>5188-5392</td>
			<td>10 ml screwtop vials with</td>
		</tr>
		<tr>
			<td>18 mm vial caps</td>
			<td>Agilent</td>
			<td>8010-0139</td>
			<td>Magnetic with PTFE/silicone septa</td>
		</tr>
		<tr>
			<td>Autosampler</td>
			<td>Agilent</td>
			<td>GC120 PAL autosampler</td>
			<td></td>
		</tr>
		<tr>
			<td>Capillary column</td>
			<td>Agilent</td>
			<td>HP5-MS</td>
			<td>30 m x 0.25 mm; 0.25 &#181;m</td>
		</tr>
		<tr>
			<td>Data analysis software</td>
			<td>Agilent</td>
			<td>-</td>
			<td>ChemStation</td>
		</tr>
		<tr>
			<td>Gas Chromatograph</td>
			<td>Agilent</td>
			<td>7890B</td>
			<td></td>
		</tr>
		<tr>
			<td>Inlet septa</td>
			<td>Agilent</td>
			<td>5182-3442</td>
			<td>Merlin microseal</td>
		</tr>
		<tr>
			<td>Mass Selective Detector</td>
			<td>Agilent</td>
			<td>5977A</td>
			<td></td>
		</tr>
		<tr>
			<td>Reporting software</td>
			<td>Microsoft</td>
			<td>-</td>
			<td>Excel</td>
		</tr>
		<tr>
			<td>Spectral library</td>
			<td>NIST</td>
			<td>-</td>
			<td>NIST/EPA/NIH Mass Spectral Library</td>
		</tr>
		<tr>
			<td>Spectral library search program</td>
			<td>NIST</td>
			<td>-</td>
			<td>MS Search v.2.2</td>
		</tr>
		<tr>
			<td>Splitless Inlet liner</td>
			<td>Agilent</td>
			<td>5190-4048</td>
			<td></td>
		</tr>
		<tr>
			<td>SPME fibres</td>
			<td>Agilent</td>
			<td>SU57345U</td>
			<td>65 &#181;m PDMS/DVB fibre</td>
		</tr>
	</tbody>
</table>

sampling and analysis of animal scent signals

We have developed an effective methodology for sampling and analysis of odor signals, by using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry, to understand how they may be used in animal communication. This technique allows the semi-quantitative analysis of the volatile components of odor secretions by enabling the separation and tentative identification of the components in the sample, followed by the analysis of peak area ratios to look for trends that could signify compounds that may be involved in signaling. The key strengths of this current approach are the range of sample types that can be analyzed; the lack of need for any complex sample preparation or extractions; the ability to separate and analyze the components of a mixture; the identification of the components detected; and the capability to provide semi-quantitative and potentially quantitative information on the components detected. The main limitation to the methodology relates to the samples themselves. Since the components of specific interest are volatile, and these could easily be lost, or their concentrations altered, it is important that the samples are stored and transported appropriately after their collection. This also means that sample storage and transport conditions are relatively costly. This method can be applied to a variety of samples (including urine, feces, hair and scent-gland odor secretions). These odors consist of complex mixtures, occurring in a range of matrices, and thus necessitate the use of techniques to separate the individual components and extract the compounds of biological interest.

Following this protocol, we tentatively identified a total of 32 volatile chemical compounds from the analysis of 14 ano-genital scent-marks spontaneously released on filter paper by red-ruffed lemurs (Varecia variegata rubra) and compared odor profiles with features of the signaler12. Naturally occurring volatile compounds, such as hydrocarbons, terpenes, terpene alcohols and ketones, were present within these profiles and included compounds that had previously been found to act as sex p...

Watch this Scientific Journal Video about Sampling and Analysis of Animal Scent Signals at JoVE.com

Sampling and Analysis of Animal Scent Signals

We have developed an effective methodology for sampling and analysis of odor signals in order to understand how they may be used in animal communication. Particularly, we use headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry to analyze the volatile components of animal odors and scent-markings.

We have developed an effective methodology for sampling and analysis of odor signals, by using headspace solid-phase microextraction coupled with gas ...

sampling-and-analysis-of-animal-scent-signals

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Behavior

4.6K Views.  University of Wolverhampton. We have developed an effective methodology for sampling and analysis of odor signals in order to understand how they may be used in animal communication. Particularly, we use headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry to analyze the volatile components of animal odors and scent-markings.

Video: Sampling and Analysis of Animal Scent Signals

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the &#34;cloud&#34; and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in&#160;cabinet; two such cabinets (16 environments) may be controlled by one computer.

Fully automated system for measuring physiologically meaningful properties of the mechanisms mediating spatial localization, temporal localization, duration, rate&#160;and probability estimation, risk assessment, impulsivity, and the accuracy and precision of memory, in order to assess the effects of genetic and pharmacological manipulations on foundational mechanisms of cognition in mice.

We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and ...

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Attention control is the ability to selectively attend to some sensory signals while ignoring others. This ability is thought to involve two processes: enhancement of sensory signals that are to be attended and the attenuation of sensory signals that are to be ignored. The overall strength of attentional modulation is often measured by comparing the amplitude of a sensory neural response to an external input when attended versus when ignored. This method is robust for detecting attentional modulation, but precludes the ability to assess the separate dynamics of attending and ignoring processes. Here, we describe methodology to measure independently the neurophysiological signals of attending and ignoring using the intermodal attention task (IMAT). This task, when combined with electroencephalography, isolates neurophysiological sensory responses in auditory and visual modalities, when either attending or ignoring, with respect to a passive control. As a result, independent dynamics of attending and of a ignoring can be assessed in either modality. Our results using this task indicate that the timing and cortical sources of attending and ignoring effects differ, as do their contributions to the attention modulation effect, pointing to unique neural trajectories and demonstrating sample utility of measuring them separately.

Attention control comprises enhancement of target signals and attenuation of distractor signals. We describe an approach to measure separately but concurrently, the neurophysiology of attending and ignoring in sustained intermodal attention, utilizing a passive control condition during which neither process is continuously engaged.

Attention control is the ability to selectively attend to some sensory signals while ignoring others. This ability is thought to involve two processes: ...

Wheel Running and Environmental Complexity as a Therapeutic Intervention in an Animal Model of FASD

Aerobic exercise (e.g., wheel running (WR) extensively used in animal research) positively impacts many measures of neuroplastic potential in the brain, such as rates of adult neurogenesis, angiogenesis, and expression of neurotrophic factors in rodents. This intervention has also been shown to mitigate behavioral and neuroanatomical aspects of the negative impacts of teratogens (i.e., developmental exposure to alcohol) and age-related neurodegeneration in rodents. Environmental complexity (EC) has been shown to produce numerous neuroplastic benefits in cortical and subcortical structures and can be coupled with wheel running to increase the proliferation and survival of new cells in the adult hippocampus. The combination of these two interventions provides a robust &#34;superintervention&#34; (WR-EC) that can be implemented in a range of rodent models of neurological disorders. We will discuss the implementation of WR/EC and its constituent interventions for use as a more powerful therapeutic intervention in rats using the animal model of prenatal exposure to alcohol in humans. We will also discuss which elements of the procedures are absolutely necessary for the interventions and which ones may be altered depending on the experimenter&#39;s question or facilities.

Cardiovascular exercise and stimulating experiences in a complex environment have positive benefits on multiple measures of neuroplasticity within the rodent brain. This article will discuss the implementation of these interventions as a &#34;superintervention&#34; which combines wheel running and environmental complexity and will address the limitations of these interventions.

Aerobic exercise (e.g., wheel running (WR) extensively used in animal research) positively impacts many measures of neuroplastic potential in the brain, ...

Introducing Clicker Training as a Cognitive Enrichment for Laboratory Mice

Establishing new refinement strategies in laboratory animal science is a central goal in fulfilling the requirements of Directive 2010/63/EU. Previous research determined a profound impact of gentle handling protocols on the well-being of laboratory mice. By introducing clicker training to the keeping of mice, not only do we promote the amicable treatment of mice, but we also enable them to experience cognitive enrichment. Clicker training is a form of positive reinforcement training using a conditioned secondary reinforcer, the "click" sound of a clicker, which serves as a time bridge between the strengthened behavior and an upcoming reward. The effective implementation of the clicker training protocol with a cohort of 12 BALB/c inbred mice of each sex proved to be uncomplicated. The mice learned rather quickly when challenged with tasks of the clicker training protocol, and almost all trained mice overcame the challenges they were given (100% of female mice and 83% of male mice). This study has identified that clicker training for mice strongly correlates with reduced fear in the mice during human-mice interactions, as shown by reduced anxiety-related behaviors (e.g., defecation, vocalization, and urination) and fewer depression-like behaviors (e.g., floating). By developing a reliable protocol that can be easily integrated into the daily routine of the keeping of laboratory mice, the lifetime experience of welfare in the mice can be improved substantially.

The development of new refinement strategies for laboratory mice is a challenging task that contributes towards fulfilling the 3R principle. This protocol introduces clicker training as a cognitive enrichment program for laboratory mice.

Establishing new refinement strategies in laboratory animal science is a central goal in fulfilling the requirements of Directive 2010/63/EU. Previous ...

Systematic Assessment of Well-Being in Mice for Procedures Using General Anesthesia

In keeping with the 3R Principle (Replacement, Reduction, Refinement) developed by Russel and Burch, scientific research should use alternatives to animal experimentation whenever possible. When there is no alternative to animal experimentation, the total number of laboratory animals used should be the minimum needed to obtain valuable data. Moreover, appropriate refinement measures should be applied to minimize pain, suffering, and distress accompanying the experimental procedure. The categories used to classify the degree of pain, suffering, and distress are non-recovery, mild, moderate, or severe (EU Directive 2010/63). To determine which categories apply in individual cases, it is crucial to use scientifically sound tools.
The well-being-assessment protocol presented here is designed for procedures during which general anesthesia is used. The protocol focuses on home cage activity, the Mouse Grimace Scale, and luxury behaviors such as burrowing and nest building behavior as indicators of well-being. It also uses the free exploratory paradigm for trait anxiety-related behavior. Fecal corticosterone metabolites as indicators of acute stress are measured over the 24-h post-anesthetic period.
The protocol provides scientifically solid information on the well-being of mice following general anesthesia. Due to its simplicity, the protocol can easily be adapted and integrated in a planned study. Although it does not provide a scale to classify distress in categories according to the EU Directive 2010/63, it can help researchers estimate the degree of severity of a procedure using scientifically sound data. It provides a way to improve the assessment of well-being in a scientific, animal-centered manner.

We developed a protocol to assess well-being in mice during procedures using general anesthesia. A series of behavioral parameters indicating levels of well-being as well as glucocorticoid metabolites were analyzed. The protocol can serve as a general aid to estimate the degree of severity in a scientific, animal-centered manner.

In keeping with the 3R Principle (Replacement, Reduction, Refinement) developed by Russel and Burch, scientific research should use alternatives to animal ...

Tickling, a Technique for Inducing Positive Affect When Handling Rats

Handling small animals such as rats can lead to several adverse effects. These include the fear of humans, resistance to handling, increased injury risk for both the animals and the hands of their handlers, decreased animal welfare, and less valid research data. To minimize negative effects on experimental results and human-animal relationships, research animals are often habituated to being handled. However, the methods of habituation are highly variable and often of limited effectiveness. More potently, it is possible for humans to mimic aspects of the animals&#39; playful rough-and-tumble behavior during handling. When applied to laboratory rats in a systematic manner, this playful handling, referred to as tickling, consistently gives rise to positive behavioral responses. This article provides a detailed description of a standardized rat tickling technique. This method can contribute to future investigations into positive affective states in animals, make it easier to handle rats for common husbandry activities such as cage changing or medical/research procedures such as injection, and be implemented as a source of social enrichment. It is concluded that this method can be used to efficiently and practicably reduce rats&#39; fearfulness of humans and improve their welfare, as well as reliably model positive affective states.

This article demonstrates the standardized application of playful handling, a tickling technique designed to mimic rat rough-and-tumble play. This technique is effective at reducing fearful reactions to humans and generating positive affect when rats are handled for common husbandry activities and medical and research procedures such as injection.

Handling small animals such as rats can lead to several adverse effects. These include the fear of humans, resistance to handling, increased injury risk ...

Methods of Pairing and Pair Maintenance of New Zealand White Rabbits (Oryctolagus Cuniculus) Via Behavioral Ethogram, Monitoring, and Interventions

New Zealand White (NZW) laboratory rabbits (Oryctolagus cuniculus), as well as their ancestors the European Rabbit, are a social species that exhibit numerous benefits to being housed accordingly. Although these rabbits are innately gregarious, certain behaviors can still arise when kept in captivity, which if left unchecked, can confound research results or lead to wounding, which in extreme cases can be severe. To prevent these issues, there must be a well-structured plan for the monitoring and maintenance of paired laboratory rabbits. The purpose of this protocol is to present effective procedures for establishing newly paired NZW rabbits as well as methods for successful maintenance. Multiple methods have been tested for the creation of newly paired female rabbits from the vendor, but the most efficacious technique emphasizes capitalizing on the stress bonding from transport, urine marking, pairing in a neutral cage with no forced sharing of resources and a system of monitoring and intervention. To determine the best method of housing paired rabbits in a standard caging environment, data were collected to generate a behavioral ethogram. Behaviors were then quantified as positive, neutral or negative and were tracked across the lifespan of the pair to determine which behaviors indicated pair success or failure. With the newfound knowledge of socially housed laboratory NZW rabbit behavior, enrichment intervention was applied to alleviate aggression and prevent wounding, thus resulting in a higher percentage of successful pairs. Through several years of trialing different pairing methods, the development of the ethogram and the resulting enrichment interventions, understanding of the highly complex social constructs that dominate pair housed rabbit behavior has dramatically increased and allowed for the provision of more species-specific care and increased standards of welfare.

Methods of Pairing and Pair Maintenance of New Zealand White Rabbits Oryctolagus Cuniculus Via Behavioral Ethogram, Monitoring, and Interventions

Though European rabbits are a social species, socially housing them can be challenging. Therefore, there must be a thorough understanding of behaviors and social structures of pair-housed laboratory rabbits. Here we present a protocol to identify pairing methods, species-typical hierarchy establishment behaviors and behaviors that warrant appropriate intervention.

New Zealand White (NZW) laboratory rabbits (Oryctolagus cuniculus), as well as their ancestors the European Rabbit, are a social species that exhibit ...

Key Elements of Photo Attraction Bioassay for Insect Studies or Monitoring Programs

Optimized visual attractants will increase insect trapping efficiency by using the target insect&#39;s innate behaviors (positive photo-taxis) as a means to lure the insect into a population control or monitoring trap. Light emitting diodes (LEDs) have created customizable lighting options with specific wavelengths (colors), intensities, and bandwidths, all of which can be customized to the target insects. Photo-attraction behavioral bioassays can use LEDs to optimize the attractive color(s) for an insect species down to specific life history stages or behaviors (mating, feeding, or seeking shelter). Researchers must then confirm the bioassay results in the field and understand the limited attractive distance of the visual attractants.
The cloverleaf bioassay arena is a flexible method to assess photo attraction while also assessing a range of natural insect behaviors such as escape and feeding responses. The arena can be used for terrestrial or aerial insect experiments, as well as diurnal, and nocturnal insects. Data collection techniques with the arena are videotaping, counting contact with the lights, or physically collecting the insects as they are attracted towards the lights. The assay accounts for insects that make no-choice and the arenas can be single (noncompetitive) color or multiple (competitive) colors. The cloverleaf design causes insects with strong thigmotaxis to return to the center of the arena where they can view all the options in a competitive LED tests. The cloverleaf arena presented here has been used with mosquitoes, bed bugs, Hessian fly, house flies, biting midges, red flour beetles, and psocids. Bioassays are used to develop accurate and effective insect traps to guide the development and optimization of insect traps used to monitor pest population fluctuations for disease vector risk assessments, the introduction of invasive species, and/or be used for population suppression.

Photo-attraction bioassay arenas are used to determine the optimal light color(s) to maximize insect attraction; however bioassays and methods are specific to target insect behaviors and habitats. Customizable equipment and modifications are explained for nocturnal or diurnal and terrestrial or aerial insects.

Optimized visual attractants will increase insect trapping efficiency by using the target insect&#39;s innate behaviors (positive photo-taxis) as a means ...

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 ...

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

The assessment of pain relies mostly on methods that require a person to communicate. However, for people with cognitive and verbal impairments, existing methods are not sufficient as they lack reliability and validity. To approach this problem, recent research focuses on an objective pain assessment facilitated by parameters of responses derived from physiology, and video and audio signals. To develop reliable automated pain recognition systems, efforts have been made in creating multimodal databases in order to analyze pain and detect valid pain patterns. While the results are promising, they only focus on discriminating pain or pain intensities versus no pain. In order to advance this, research should also consider the quality and duration of pain as they provide additional valuable information for more advanced pain management. To complement existing databases and the analysis of pain regarding quality and length, this paper proposes a psychophysiological experiment to elicit, measure, and collect valid pain reactions. Participants are subjected to painful stimuli that differ in intensity (low, medium, and high), duration (5 s / 1 min), and modality (heat / electric pain) while audio, video (e.g., facial expressions, body gestures, facial skin temperature), and physiological signals (e.g., electrocardiogram [ECG], skin conductance level [SCL], facial electromyography [EMG], and EMG of M. trapezius) are being recorded. The study consists of a calibration phase to determine a subject&#8217;s individual pain range (from low to intolerable pain) and a stimulation phase in which pain stimuli, depending on the calibrated range, are applied. The obtained data may allow refining, improving, and evaluating automated recognition systems in terms of an objective pain assessment. For further development of such systems and to investigate pain reactions in more detail, additional pain modalities such as pressure, chemical, or cold pain should be included in future studies. Recorded data of this study will be released as the &#8220;X-ITE Pain Database&#8221;.

This article focuses on the experimental elicitation of pain through heat (thermal) and electrical stimulation while recording physiological, visual, and paralinguistic responses. It aims at collecting valid multimodal data for analyzing pain based on its intensity, quality, and duration.&#160;

The assessment of pain relies mostly on methods that require a person to communicate. However, for people with cognitive and verbal impairments, existing ...