We are grateful to Stanislav Lazopulo for help with the video content.

1. Measuring Fly Locomotion Using Drosophila Activity Monitor (DAM)
NOTE: For more details see reference5.
<ol>
	<li>Prepare individual fly tubes with food on one end and cotton on the other. The end with food should be sealed to prevent the food from drying out.
	<ol>
		<li>Put 5-6 g of fly food in a 50 mL beaker. Cut the food into small pieces so that it is easier to melt it.</li>
		<li>Connect 32 individual glass tubes with a rubber band.</li>
		<li>Melt the food in the beaker by heating it in a microwave oven for 10-15 s. Stop the microwave every 5 s and carefully shake the beaker to ensure equal melting of food.</li>
		<li>While the food is still liquid, put the prepared individual tubes in the beaker with food. Move the tubes up and down so they are equally filled.</li>
		<li>Allow the food to cool down and solidify for approximately 1 h.</li>
		<li>After the food is solid, remove the tubes with the food from the beaker.</li>
		<li>Seal the end containing the food using wax. First, carefully clean a tube using a paper towel, then press the tube against the wax. Visually check the quality of the seal, and if necessary, repeat the sealing again.</li>
		<li>Close the other end of the tube with cotton; cotton will permit air to go through while keeping a fly locked in the tube.</li>
	</ol>
	</li>
	<li>Place a single fly in each individual tube and place the tubes in the DAM.</li>
	<li>Place monitors in an incubator that maintains constant temperature and humidity. Based on the experiment, set the proper light/dark conditions as follows.
	<ol>
		<li>For light/dark experiments keep the flies in light/dark cycle for the whole experiment. Do not use the first day of measurements in the analysis.</li>
		<li>For constant darkness experiments, first keep the flies for two days in light/dark conditions for entrainment and synchronization of the clocks and then switch to constant darkness. Do not use the measurements from the first day of constant darkness in the analysis.</li>
	</ol>
	</li>
	<li>Collect at least four days of data that can be used in the analysis. 
	NOTE: The DAM system will output a single file with a locomotion recording of all flies in the monitor.</li>
</ol>
2. Data Analysis
<ol>
	<li>Split the monitor output file into multiple single fly activity files; each file should be a single column &#39;.txt&#39; file with an individual fly locomotion measurement.</li>
	<li>Run &#39;ModelFitPS3.m&#39; function in a Matlab command window with the following input parameters:
	<ol>
		<li>For samplingrate, set the data sampling time interval in seconds. For example, if activity was measured every minute, enter 60 as the samplingrate.</li>
		<li>For bin_interval, set the time interval in minutes to which data will be binned for better visualization; the recommended bin interval is 20-30 min.</li>
		<li>For trend, enter &#34;1&#34; if the data show baseline trend and &#34;0&#34; otherwise; data with trend will be detrended first by fitting a second order polynomial and then subtracting it from the data.</li>
	</ol>
	</li>
	<li>In the popup window select a single fly activity file. 
	Note: The first plot is data power spectrum, and not the familiar activity plot. From the plotted power spectrum, determine the primary period T0: Either click with the left mouse button on the circadian peak, or with right mouse button on the second harmonic peak (around T0/2).</li>
	<li>On the opened data plot, check if the morning and evening peaks are well visualized. If not, change the bin_interval value by right clicking anywhere on the graph and inputting the new bin_interval value in the dialog box. The program will redraw the data with the new value of the interval. To accept the bin_interval value, left click anywhere on the graph.</li>
	<li>The program will redraw the data again and show the first five days of activity. On this plot, click on the first M peak that will be used in the analysis (sometimes it is necessary to skip one or two days). 
	NOTE: The program will redraw the graph starting from the picked morning peak. The blue and red lines will show the approximate position of the E peak and next day M peak, respectively, based on the period determined in step 2.4.</li>
	<li>On the same graph, choose data for a preliminary fit of the data with the model: Click on the following points (in this order; note that the click location will be indicated with a red star on the bottom): (i) Top of M peak; (ii) End of the M peak; (iii) Start of the E peak; (iv) Top of the E peak; (v) End of the E peak; (vi) Top of the M peak of the next day.</li>
	<li>Note that the program now presents the power spectrum. 
	NOTE: The x axis is now given in frequency.
	<ol>
		<li>In the opened window with the power spectrum, pick points that will be used for fitting the analytical expression for the model power spectrum. The period detected in step 2.4 is marked with a red line. To pick fitting points, first roughly determine the primary period, similar to step 2.4. Then using the slider, fine tune the primary period value so that the fitting points (shown with red circles, will appear after moving the slider) are closed to peak values.</li>
	</ol>
	</li>
	<li>After the visual peak selection, click &#34;Accept&#34; and the program will fit selected points with the analytical expression to calculate the model parameters.</li>
	<li>Note that the parameters and spectral fit error are saved to the file &#34;model_fit_parameters.txt&#34;; the program will additionally save 2 figures with fits of the locomotor data and its power spectrum.</li>
</ol>

<ol>
	<li>Pittendrigh, C. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Circadian+systems:+general+perspective.">Circadian systems: general perspective.</a> Biological Rhythms. II, 57-80 (1981).</li><li>Zhang, E. E., Kay, S. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clocks+not+winding+down:+unravelling+circadian+networks.">Clocks not winding down: unravelling circadian networks.</a> Nat Rev Mol Cell Biol. 11 (11), 764-776 (2010).</li><li>Tataroglu, O., Emery, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+molecular+ticks+of+the+Drosophila+circadian+clock.">The molecular ticks of the Drosophila circadian clock.</a> Curr Opin Insect Sci. 7, 51-57 (2015).</li><li>Plautz, J. D., 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=Quantitative+analysis+of+Drosophila+period+gene+transcription+in+living+animals.">Quantitative analysis of Drosophila period gene transcription in living animals.</a> J Biol Rhythms. 12 (3), 204-217 (1997).</li><li>Chiu, J. C., Low, K. H., Pike, D. H., Yildirim, E., Edery, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assaying+locomotor+activity+to+study+circadian+rhythms+and+sleep+parameters+in+Drosophila.">Assaying locomotor activity to study circadian rhythms and sleep parameters in Drosophila.</a> J Vis Exp. (43), e2157 (2010).</li><li>Helfrich-F&#246;rster, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+control+of+morning+and+evening+components+in+the+activity+rhythm+of+Drosophila+melanogaster--sex-specific+differences+suggest+a+different+quality+of+activity.">Differential control of morning and evening components in the activity rhythm of Drosophila melanogaster--sex-specific differences suggest a different quality of activity.</a> J Biol Rhythms. 15 (2), 135-154 (2000).</li><li>Dautzenberg, F. M., Neysari, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Irreversible+binding+kinetics+of+neuropeptide+Y+ligands+to+Y2+but+not+to+Y1+and+Y5+receptors.">Irreversible binding kinetics of neuropeptide Y ligands to Y2 but not to Y1 and Y5 receptors.</a> Pharmacology. 75 (1), 21-29 (2005).</li><li>Lazopulo, A., Syed, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+mathematical+model+provides+mechanistic+links+to+temporal+patterns+in+Drosophila+daily+activity.">A mathematical model provides mechanistic links to temporal patterns in Drosophila daily activity.</a> BMC Neuroscience. 17 (1), 14 (2016).</li><li>Donelson, N., Kim, E. Z., Slawson, J. B., Vecsey, C. G., Huber, R., Griffith, L. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-resolution+positional+tracking+for+long-term+analysis+of+Drosophila+sleep+and+locomotion+using+the+&amp;#34;tracker&amp;#34;+program.">High-resolution positional tracking for long-term analysis of Drosophila sleep and locomotion using the &amp;#34;tracker&amp;#34; program.</a> PloS ONE. 7 (5), e37250 (2012).</li><li>Schlichting, 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=A+Neural+Network+Underlying+Circadian+Entrainment+and+Photoperiodic+Adjustment+of+Sleep+and+Activity+in+Drosophila.">A Neural Network Underlying Circadian Entrainment and Photoperiodic Adjustment of Sleep and Activity in Drosophila.</a> J Neurosci. 36 (35), 9084-9096 (2016).</li><li>Guo, F., 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=Circadian+neuron+feedback+controls+the+Drosophila+sleep-activity+profile.">Circadian neuron feedback controls the Drosophila sleep-activity profile.</a> Nature. 536 (7616), 292-297 (2016).</li></ol>

The authors have nothing to disclose.

This work presents instructions for using a computational tool that provides a quantitative description of fly locomotion pattern. The tool fits locomotion data with a mathematical model consisting of four exponential terms that together describe the shape and size of the M and E peaks. The final values for the model parameters are obtained from fitting the power spectra of the data, where the use of the raw data can avoid artefactual effects that data binning or filtering can impose on parameter values. The model parame...

The circadian clock is an endogenous biochemical oscillator with a period of approximately 24 hours and is almost ubiquitous in animals and plants1,2. The clock helps synchronize an organism&#39;s internal processes and behavior to the external light dark cycle. The genetic structure of the circadian clock has been widely studied since the 1960s using the fruit fly, D. melanogaster. In this insect, the core of the circadian clock consists of four proteins: PERIOD, TIMELESS, CLOCK, and CYCLE. These core components together with other molecules form a feedback loop that produces nearly sinusoidal oscillations of clock genes3,4. The circadian clock in flies is widely studied using multiday locomotor recordings where fly activity is detected with a single infrared beam crossing the middle of an individual tube5. A typical fly recording has a complex bimodal pattern with two well distinguishable peaks: Morning peak (M) that starts at the end of the night and has a maximum when lights turn on; and Evening peak (E) that starts at the end of the day and has a maximum when lights turn off6. Interestingly, the shape of such behavioral recording is very different from the simple sinusoidal oscillations observed at the molecular level, suggesting the action of additional mechanisms contributing to the observed temporal patterns. To better understand these hidden mechanisms, we have developed a computational tool that provides a quantitative description of the temporal patterns.
In our work, locomotor rhythms are defined in terms of a waveform that mimics fly activity pattern. Since simple sine waves cannot be used to model the observed rhythmic changes in activity, we tested various signal shapes to select the simplest one that captures all the salient features seen in the recordings. Fruit fly circadian behavior is controlled by the activity of clock neurons that often have exponential patterns of activation and deactivation7. The exponential dynamics and visual analysis of the data motivated us to build a model with exponential terms consisting of four exponents with nine independent parameters and closely resembling the fly activity pattern8. In addition to the locomotor data, we also analyze its power spectrum. Typical fly activity spectrum shows multiple peaks at harmonics T0/2, T0/3, etc., in addition to the expected fundamental peak at the circadian period T0. According to the Fourier theorem, only a pure sine wave produces a single peak in power spectra, while more complex waveforms show multiple spectral peaks at harmonics of the primary period (Figure 1). Therefore, given the non-sinusoidal temporal pattern in fly activity8, a multi-peak power spectrum of the data is mathematically expected and does not necessarily imply the presence of multiple periods of oscillation. Importantly, the power spectrum of the proposed model waveform also shows peaks at all harmonics of the primary period, similar to the fly locomotor recordings, thus underscoring the high fidelity with which our model describes fly data both in time and in frequency.
At time resolutions of a few minutes or less, fly activity data appears noisy, making it difficult to extract parameters directly from the raw data. Binning data into longer time intervals can decrease noise level, but, can alter the data in ways that can affect the estimation of model parameters. We therefore obtain the parameters from power spectra of the recordings, using an analytical expression for the expected power spectra calculated from the Fourier transform of the model function8 (see Additional File 1 of reference8). This approach of obtaining parameters from the power spectra yields accurate parameter values without any additional manipulations, such as binning or filtering, of the raw activity data. Mathematical details of the model and applications to wild-type and mutant data are described in reference8. The protocol presented here focuses on the step-by-step instructions to use the computational tool.

<table border="0" cellpadding="0" cellspacing="0" width="1389">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:296px;">Drosophila Activity Monitor</td>
			<td style="width:81px;">TriKinetics</td>
			<td style="width:201px;">DAM2, DAM5</td>
			<td style="width:811px;">Measures fly locootion using single infrared beam</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:296px;">MatLab</td>
			<td style="width:81px;">Mathworks</td>
			<td style="width:201px;"></td>
			<td>Computing environment and programming language, MatLab should include Optimization and Symbolic Math toolboxes</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;width:296px;">Drosophila melanogaster&#160;</td>
			<td style="width:81px;"></td>
			<td style="width:201px;">per[S], per[L], iso31(wild type)</td>
			<td>Our analysis can be performed with fly mutants of any circadian period</td>
		</tr>
	</tbody>
</table>

a computational method to quantify fly circadian activity

In most animals and plants, circadian clocks orchestrate behavioral and molecular processes and synchronize them to the daily light-dark cycle. Fundamental mechanisms that underlie this temporal control are widely studied using the fruit fly Drosophila melanogaster as a model organism. In flies, the clock is typically studied by analyzing multiday locomotor recording. Such a recording shows a complex bimodal pattern with two peaks of activity: a morning peak that happens around dawn, and an evening peak that happens around dusk. These two peaks together form a waveform that is very different from sinusoidal oscillations observed in clock genes, suggesting that mechanisms in addition to the clock have profound effects in producing the observed patterns in behavioral data. Here we provide instructions on using a recently developed computational method that mathematically describes temporal patterns in fly activity. The method fits activity data with a model waveform that consists of four exponential terms and nine independent parameters that fully describe the shape and size of the morning and evening peaks of activity. The extracted parameters can help elucidate the kinetic mechanisms of substrates that underlie the commonly observed bimodal activity patterns in fly locomotor rhythms.

The method presented here allows quantification of the main features in fly locomotion pattern. The quantification is achieved by fitting the activity data with a model that consists of four exponential terms:
<img alt="Equation 1" src="/files/ftp_upload/55977/55977eq1.jpg" />
The model has nine independent parameters that describe activity pattern. The parameters b<su...

Watch this Scientific Journal Video about A Computational Method to Quantify Fly Circadian Activity at JoVE.com

A Computational Method to Quantify Fly Circadian Activity

A method to quantify the main temporal features seen in fly circadian locomotor rhythms is presented. The quantification is achieved by fitting fly activity with a multi-parametric model waveform. The model parameters describe the shape and size of the morning and evening peaks of daily activity.

In most animals and plants, circadian clocks orchestrate behavioral and molecular processes and synchronize them to the daily light-dark cycle. ...

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5.9K Views.  University of Miami. A method to quantify the main temporal features seen in fly circadian locomotor rhythms is presented. The quantification is achieved by fitting fly activity with a multi-parametric model waveform. The model parameters describe the shape and size of the morning and evening peaks of daily activity.

Video: A Computational Method to Quantify Fly Circadian Activity

Topographical Estimation of Visual Population Receptive Fields by fMRI

Visual cortex is retinotopically organized so that neighboring populations of cells map to neighboring parts of the visual field. Functional magnetic resonance imaging allows us to estimate voxel-based population receptive fields (pRF), i.e., the part of the visual field that activates the cells within each voxel. Prior, direct, pRF estimation methods1 suffer from certain limitations: 1) the pRF model is chosen a-priori and may not fully capture the actual pRF shape, and 2) pRF centers are prone to mislocalization near the border of the stimulus space. Here a new topographical pRF estimation method2 is proposed that largely circumvents these limitations. A linear model is used to predict the Blood Oxygen Level-Dependent (BOLD) signal by convolving the linear response of the pRF to the visual stimulus with the canonical hemodynamic response function. PRF topography is represented as a weight vector whose components represent the strength of the aggregate response of voxel neurons to stimuli presented at different visual field locations. The resulting linear equations can be solved for the pRF weight vector using ridge regression3, yielding the pRF topography. A pRF model that is matched to the estimated topography can then be chosen post-hoc, thereby improving the estimates of pRF parameters such as pRF-center location, pRF orientation, size, etc. Having the pRF topography available also allows the visual verification of pRF parameter estimates allowing the extraction of various pRF properties without having to make a-priori assumptions about the pRF structure. This approach promises to be particularly useful for investigating the pRF organization of patients with disorders of the visual system.

It is important to obtain unbiased estimates of visual population receptive fields (pRFs) by functional magnetic resonance imaging. We use mild regularization constraints to estimate pRF topography without a-priori assumptions about pRF shape, allowing us to choose specific pRF models post-hoc. This is particularly advantageous in subjects with visual-pathway lesions.

Visual cortex is retinotopically organized so that neighboring populations of cells map to neighboring parts of the visual field. Functional magnetic ...

A Method for Remotely Silencing Neural Activity in Rodents During Discrete Phases of Learning

This protocol describes how to temporarily and remotely silence neuronal activity in discrete brain regions while animals are engaged in learning and memory tasks. The approach combines pharmacogenetics (Designer-Receptors-Exclusively-Activated-by-Designer-Drugs) with a behavioral paradigm (sensory preconditioning) that is designed to distinguish between different forms of learning. Specifically, viral-mediated delivery is used to express a genetically modified inhibitory G-protein coupled receptor (the Designer Receptor) into a discrete brain region in the rodent. Three weeks later, when designer receptor expression levels are high, a pharmacological agent (the Designer Drug) is administered systemically 30 min prior to a specific behavioral session. The drug has affinity for the designer receptor and thus results in inhibition of neurons that express the designer receptor, but is otherwise biologically inert. The brain region remains silenced for 2-5 hr (depending on the dose and route of administration). Upon completion of the behavioral paradigm, brain tissue is assessed for correct placement and receptor expression. This approach is particularly useful for determining the contribution of individual brain regions to specific components of behavior and can be used across any number of behavioral paradigms.

This protocol describes how to temporarily and remotely silence neuronal activity in discrete brain regions while rats are engaged in learning and memory tasks. The approach combines pharmacogenetics (Designer-Receptors-Exclusively-Activated-by-Designer-Drugs) with a behavioral paradigm (sensory preconditioning) that is designed to distinguish between different components of learning.

This protocol describes how to temporarily and remotely silence neuronal activity in discrete brain regions while animals are engaged in learning and ...

A Method to Quantify Visual Information Processing in Children Using Eye Tracking

Visual problems that occur early in life can have major impact on a child's development. Without verbal communication and only based on observational methods, it is difficult to make a quantitative assessment of a child's visual problems. This limits accurate diagnostics in children under the age of 4 years and in children with intellectual disabilities. Here we describe a quantitative method that overcomes these problems. The method uses a remote eye tracker and a four choice preferential looking paradigm to measure eye movement responses to different visual stimuli. The child sits without head support in front of a monitor with integrated infrared cameras. In one of four monitor quadrants a visual stimulus is presented. Each stimulus has a specific visual modality with respect to the background, e.g., form, motion, contrast or color. From the reflexive eye movement responses to these specific visual modalities, output parameters such as reaction times, fixation accuracy and fixation duration are calculated to quantify a child's viewing behavior. With this approach, the quality of visual information processing can be assessed without the use of communication. By comparing results with reference values obtained in typically developing children from 0-12 years, the method provides a characterization of visual information processing in visually impaired children. The quantitative information provided by this method can be advantageous for the field of clinical visual assessment and rehabilitation in multiple ways. The parameter values provide a good basis to: (i) characterize early visual capacities and consequently to enable early interventions; (ii) compare risk groups and follow visual development over time; and (iii), construct an individual visual profile for each child.

A method is described to quantify the quality of visual information processing based on reflexive eye movements in response to specific visual modalities. Reaction times and fixation output parameters are used to characterize visual performance in children with and without visual impairments from 6 months of age.

Visual problems that occur early in life can have major impact on a child's development. Without verbal communication and only based on observational ...

Psychophysical Tracking Method to Measure Taste Preferences in Children and Adults

The Monell two-series, forced-choice, paired-comparison tracking method provides a reliable measure of sweet taste preferences from childhood to adulthood. The method, which is identical for children, adolescents, and adults, is of short duration (&#60; 15 min), does not rely on sustained attention or place demands on memory (which would yield spurious age differences), and minimizes the impact of language development, making this method amenable to the cognitive limitations of pediatric populations. In this whole-mouth tasting method, subjects are asked to taste (without swallowing) pairs of solutions of different sucrose concentrations and to point to the solution they prefer. Each subsequent pair contains the participant&#39;s preceding preferred concentration and an adjacent stimulus concentration. The procedure continues until the subject chooses either a given concentration of sucrose when paired with both a higher and a lower concentration, or the highest or lowest concentration two consecutive times. Subjects are prevented from reaching response criteria on the basis of first or second position bias by the two-series design of the method, which counterbalances the order of solution presentation within each pair between the series (the weaker concentration is presented first in Series 1, second in Series 2). The geometric mean of the two sucrose concentrations chosen in Series 1 and 2 is an estimate of the participant&#39;s most preferred level of sucrose. Sucrose preference as determined with this laboratory-based measure has been shown to be associated with preference for sugars in foods and beverages and with taste receptor genotype, family history of alcoholism, and race/ethnicity, as well as depressive symptomatology among pediatric populations. The method has real-world relevance and has been applied to determine most preferred level of other tastes (e.g., salt), making it a valuable psychophysical tool.

Sweet taste has powerful hedonic appeal among people of all ages, particularly children. Described herein is a reliable and valid method that can be used to determine the level of sweetness most preferred, making it a valuable psychophysical tool for scientists.

The Monell two-series, forced-choice, paired-comparison tracking method provides a reliable measure of sweet taste preferences from childhood to ...

A Method to Test the Effect of Environmental Cues on Mating Behavior in Drosophila melanogaster

An individual's sexual drive is influenced by genotype, experience and environmental conditions. How these factors interact to modulate sexual behaviors remains poorly understood. In Drosophila melanogaster, environmental cues, such as food availability, affect mating activity offering a tractable system to investigate the mechanisms modulating sexual behavior. In D. melanogaster, environmental cues are often sensed via the chemosensory gustatory and olfactory systems. Here, we present a method to test the effect of environmental chemical cues on mating behavior. The assay consists of a small mating arena containing food medium and a mating couple. The mating frequency for each couple is continuously monitored for 24 h. Here we present the applicability of this assay to test environmental compounds from an external source through a pressurized air system as well as manipulation of the environmental components directly in the mating arena. The use of a pressurized air system is especially useful to test the effect of very volatile compounds, while manipulating components directly in the mating arena can be of value to ascertain a compound's presence. This assay can be adapted to answer questions about the influence of genetic and environmental cues on mating behavior and fecundity as well as other male and female reproductive behaviors.

A Method to Test the Effect of Environmental Cues on Mating Behavior in Drosophila melanogaster

We demonstrate an assay to analyze the environmental and genetic cues that influence mating behavior in the fruit fly Drosophila melanogaster.

An individual's sexual drive is influenced by genotype, experience and environmental conditions. How these factors interact to modulate sexual behaviors ...

A Method to Study Adaptation to Left-Right Reversed Audition

An unusual sensory space is one of the effective tools to uncover the mechanism of adaptability of humans to a novel environment. Although most of the previous studies have used special spectacles with prisms to achieve unusual spaces in the visual domain, a methodology for studying the adaptation to unusual auditory spaces has yet to be fully established. This study proposes a new protocol to set-up, validate, and use a left-right reversed stereophonic system using only wearable devices, and to study the adaptation to left-right reversed audition with the help of neuroimaging. Although individual acoustic characteristics are not yet implemented, and slight spillover of unreversed sounds is relatively uncontrollable, the constructed apparatus shows high performance in a 360&#176; sound source localization coupled with hearing characteristics with little delay. Moreover, it looks like a mobile music player and enables a participant to focus on daily life without arousing curiosity or drawing attention of other individuals. Since the effects of adaptation were successfully detected at the perceptual, behavioral, and neural levels, it is concluded that this protocol provides a promising methodology for studying adaptation to left-right reversed audition, and is an effective tool for uncovering the adaptability of humans to a novel environments in the auditory domain.

The present study proposes a protocol to investigate the adaptation to left-right reversed audition achieved only by wearable devices, using neuroimaging, which can be an effective tool for uncovering the adaptability of humans to a novel environment in the auditory domain.

An unusual sensory space is one of the effective tools to uncover the mechanism of adaptability of humans to a novel environment. Although most of the ...

Visual Classical Conditioning in Wood Ants

Several species of insects have become model systems for studying learning and memory formation. Although many studies focus on freely moving animals, studies implementing classical conditioning paradigms with harnessed insects have been important for investigating the exact cues that individuals learn and the neural mechanisms underlying learning and memory formation. Here we present a protocol for evoking visual associative learning in wood ants through classical conditioning. In this paradigm, ants are harnessed and presented with a visual cue (a blue cardboard), the conditional stimulus (CS), paired with an appetitive sugar reward, the unconditional stimulus (US). Ants perform a Maxilla-Labium Extension Reflex (MaLER), the unconditional response (UR), which can be used as a readout for learning. Training consists of 10 trials, separated by a 5-minute intertrial interval (ITI). Ants are also tested for memory retention 10 minutes or 1 hour after training. This protocol has the potential to allow researchers to analyze, in a precise and controlled manner, the details of visual memory formation and the neural basis of learning and memory formation in wood ants.

We present a protocol for the classical conditioning of harnessed ants that permits researchers to study visual learning and memory formation at a level of analysis not possible with freely moving individuals.

Several species of insects have become model systems for studying learning and memory formation. Although many studies focus on freely moving animals, ...

Modified Blood Collection from Tail Veins of Non-anesthetized Mice with a Vacuum Blood Collection System and Eyeglass Magnifier

Blood sample collection is the basis of experimental animal research. It is of importance to obtain adequate blood samples for various research purposes. The tail veins of mice are small, and it is sometimes difficult to obtain the required blood volume by conventional puncture methods. This study investigates the superiority of repeated blood sample collection from tail veins of mice through use of a vacuum blood collection system and eyeglass magnifier (experimental group) compared to conventional blood sampling methods (conventional group), performed by beginners and experts, respectively. With the help of an eyeglass magnifier, a butterfly needle tip is inserted into the tail vein of each mouse in the experimental group. When the vein is penetrated successfully, a blood sample is collected in the vacuum collection tube by insertion of the rubber end of a butterfly needle into the vacuum blood collection tube. The plunger is then used to collect blood without the help of the eyeglass magnifier in the conventional group. Success rates of blood sample collection by the beginners and experts were shown to be 70% vs. 100% (p &#60; 0.01) in the experimental group and 35% vs. 85% (p &#60; 0.01) in the conventional group. For both beginners and experts, puncture times required for obtaining required blood sample were significantly lower in the experimental group compared to the conventional group (2.40 &#177; 0.75 vs. 2.90 &#177; 0.31, p &#60; 0.05; 1.15 &#177; 0.37 vs. 1.55 &#177; 0.76, p &#60; 0.05). In conclusion, the presented blood sampling technique is feasible and easy to practice and enables frequent sampling of adequate blood volumes from non-anesthetized mice.&#160;

This study reports blood sampling from tail vein in mice using a vacuum extraction tube system with eyeglass magnifier. Our method is easy to practice and could be used for repeat blood sampling in mice.

Blood sample collection is the basis of experimental animal research. It is of importance to obtain adequate blood samples for various research purposes. ...

A Laboratory Method to Measure Contagious Yawning in Rats

Communication is an essential aspect of animal social life. Animals may influence one another and come together in schools, flocks, and herds. Communication is also the way sexes interact during courtship and how rivals settle disputes without fighting. However, there are some behavioral patterns for which it is difficult to test the existence of a communicatory function, because several types of sensory modalities are likely involved. For example, contagious yawning is a communicatory act in mammals that potentially occurs through sight, hearing, smell, or a combination of these senses depending on whether the animals are familiar to one another. Therefore, to test hypotheses about the possible communicatory role of such behaviors, a suitable method is necessary to identify the participating sensory modalities.
The method proposed here aims to obtain yawn contagion curves for familiar and unfamiliar rats and evaluate the relative participation of visual and olfactory sensory modalities. The method uses inexpensive materials, and with some minor changes, it can also be used with other rodent species such as mice. Overall, the method involves the substitution of clear dividers (with or without holes) with opaque dividers (with or without holes) that either allow or prevent communication between rats placed in adjacent cages with holes in adjoining sides. Accordingly, four conditions can be tested: olfactory communication, visual communication, both visual and olfactory communication, and neither visual nor olfactory communication. As social interaction occurs between the rats, these test conditions simulate what may occur in a natural environment. In this respect, the method proposed here is more effective than traditional methods that rely on video presentations whose biological validity can raise concerns. Nonetheless, it does not discriminate between the potential role of hearing and roles of smell and vision in yawn contagion.

The method described here aims to obtain yawn contagion curves in pairs of familiar or unfamiliar male rats. Cages with holes separated by either clear or opaque partitions with (or without) holes are used to detect whether visual, olfactory, or both types of sensory cues can stimulate yawn contagion.

Communication is an essential aspect of animal social life. Animals may influence one another and come together in schools, flocks, and herds. ...

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Multisensory integration research investigates how the brain processes simultaneous sensory information. Research on animals (mainly cats and primates) and humans reveal that intact multisensory integration is crucial for functioning in the real world, including both cognitive and physical activities. Much of the research conducted over the past several decades documents multisensory integration effects using diverse psychophysical, electrophysiological, and neuroimaging techniques. While its presence has been reported, the methods used to determine the magnitude of multisensory integration effects varies and typically faces much criticism. In what follows, limitations of previous behavioral studies are outlined and a step-by-step tutorial for calculating the magnitude of multisensory integration effects using robust probability models is provided.

The current study aims to provide a step-by-step tutorial for calculating the magnitude of multisensory integration effects in an effort to facilitate the production of translational research studies across diverse clinical populations.

Multisensory integration research investigates how the brain processes simultaneous sensory information. Research on animals (mainly cats and primates) ...

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A Laboratory Method to Measure Contagious Yawning in Rats

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects