The experiments were supported by a grant from the Natural Sciences and Engineering Research Council of Canada to CMSP. We thank Koppert Canada for their bumblebee colony donations. Portions of this manuscript, including some figures and tables have been published in Naturwissenschaften11, and reproduced here with permission from Springer.

The Animal Care Committee of the University of Ottawa has approved our experimental protocol, which delineates safety procedures for personnel working with bees.
1. Testing Environment Preparation
<ol>
	<li>Prepare an empty space (isolated room, or metal-screen covered flight cage) of 2 m x 2 m x 2 m. 
	NOTE: If the room is chosen as the testing space, ensure that bees cannot escape through windows, spaces under doors, and air exchange ducts.</li>
	<li>Add small entry points (e.g., approx. 2 cm diameter holes) to the flight cage where bees can enter and exit the testing space without obstruction. Design a mechanism to block access points to keep bees out of the testing space during periods reserved for maintenance and equipment configuration. 
	NOTE: We used Bombus impatiens Cresson workers.</li>
	<li>Connect one or two colony boxes to the testing-space using a connector. Ensure that a dead bee cannot block the connector. 
	NOTE: Here, use two types of connecting structures: a wooden &#8220;bridge&#8221; structure with a glass top cover, and a wire mesh tube. They are easy to clean and they provide traction for the bees.</li>
	<li>Place two artificial flower holders inside the testing-space.
	<ol>
		<li>Place flower holders in the center of the testing-space, or attach them to the wall.</li>
		<li>Connect a &#8220;2k6 head&#8221; RFID reader to the top of the cylinder portion of the artificial flower using masking tape (see Figure 1 for positioning). Use a 1.2 m tall wooden stand to which to attach artificial flowers. 
		NOTE: The top of the stand should feature an attachment mechanism where artificial flowers can be connected. See Figure 2 for a schematic drawing</li>
	</ol>
	</li>
	<li>Add high-frequency (min. 200 Hz) fluorescent light fixtures to adequately light the testing-space. Use a high frequency electronic ballast to ensure that light flicker is above bumblebees&#8217; visual flicker fusion threshold6. 
	NOTE: Here, use 12 daylight fluorescent bulbs that produce about 1,200 Lux light intensity for a space of 2 x 2 x 2 m.</li>
</ol>
<img alt="Figure 1" src="/files/ftp_upload/52033/52033fig1highres.jpg" /> 
Figure 1. RFID Artificial Flower Design. Schematic diagram of the RFID-enabled artificial flower used in Experiment 1. The RFID reader rested on top of the open cylinder through the center of the flower. Stimuli patterns and positions: a. peripheral-concentric, b. central-concentric, c. peripheral-radial and d. central-radial. This figure has been modified from Orb&#225;n et al.11.
<img alt="Figure 2" src="/files/ftp_upload/52033/52033fig2highres.jpg" /> 
Figure 2. Stimulus Display Stand. A schematic drawing showing the design of the artificial flower stimulus stand, and attachment clip. The attachment clip is glued to the artificial flower and is used to quickly attach and detach the stimuli to and from the stimuli stands. This configuration was used in the motion-sensitive video experiment. <a href="https://www.jove.com/files/ftp_upload/52033/52033fig2highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
2. Bumblebee Colony Preparation
<ol>
	<li>Upon arrival of commercially ordered colonies, connect the colony box to the flight cage.</li>
	<li>Provide pollen (collected by honeybees from a variety of plants) and sugar-water (1:1 by volume) ad libitum until the start of the testing sessions.
	<ol>
		<li>Boil 1 L of water, and mix in the same volume of sugar to create the sugar-water solution.</li>
		<li>Purchase pollen from an apiarist or the commercial supplier of bumblebee colonies. Grind the pollen with a mortar and pestle, and mix with honey and water (as needed) to make it into a moist paste.</li>
	</ol>
	</li>
	<li>Once the experiment begins, provide 15&#8211;40 ml of sugar water (quantity proportional to the colony size) daily. Continue to provide pollen ad libitum. Adjust sugar-water quantity according to storage levels in the honey pots. 
	NOTE: Keeping food storage levels low provides an incentive for workers to leave the nest to seek more food.</li>
	<li>Allow bees to enter the testing environment via the connector structure, as described in step 1.3. 
	NOTE: Bees move freely between the nest and the testing environment throughout the experiment.</li>
</ol>
3. Preparation for Observation by Radio-frequency Identification
<ol>
	<li>Start gluing RFID tags to the thorax of the workers as soon as the colony arrives, and continue throughout the experiment, as new workers emerge.</li>
	<li>Gluing Technique
	<ol>
		<li>Place all workers in individual containers during initial tagging. Cool workers down for approximately 1 hr in the fridge (approximately 7 &#176;C) to slow them down. 
		NOTE: Cooling down workers in advance of tagging helps make aggressive colonies more manageable. This minimizes the chance of stings.</li>
		<li>Using the tagging apparatus and non-toxic glue (provided by the tag provider), attach the RFID tag to the thorax of the worker. Glue RFID tags to workers as they emerge, while they are still in callow stage (before they are capable of flying).</li>
		<li>Wait a minimum of 10 min before placing the worker back in the colony to ensure the RFID tag cannot be removed by the worker.&#160;</li>
	</ol>
	</li>
	<li>Dispose of workers that were not tagged during their callow stage, or workers that have lost their RFID tags (as seen by glue residue or bald patch on the thorax). 
	NOTE: These bees may have had experience outside the colony.</li>
	<li>RFID Reader software
	<ol>
		<li>Use a personal computer (PC) to configure the RFID reader software. Change the operating system&#8217;s date format to yyyy-mm-dd hh:mm:ss to ensure the downloaded RFID data are correctly encoded. Adjust the program supplied with the RFID readers using C++ programming language to allow exporting the data on the RFID reader as Comma Separated Values (CSV).</li>
		<li>Connect the RFID reader to the computer using an RS-232 to USB connector. Download the data to the RFID reader periodically, before the reader reaches storage capacity (up to 32,000 records). Use RFID readers to record date, time and a thirteen character unique string associated with each tag. Import the downloaded CSV file into a relational database management system (RDBMS).</li>
	</ol>
	</li>
</ol>
4. Artificial Flower Preparation for RFID Readers
<ol>
	<li>Purchase blue and yellow bake clay from a local crafts store.</li>
	<li>Create a blue cylinder with a diameter of 1.5 cm, and cut a 1.5 cm x 3 cm hole on the side. 
	NOTE: The hole on the side of the cylinder will serve as the receptacle for the RFID reader.</li>
	<li>Create a blue cone with a diameter of 8 cm on one end, and 1.5 cm on the other end.</li>
	<li>Merge the cylinder and the cone.</li>
	<li>Create a 20 cm long and 0.5 cm wide strand of yellow clay.</li>
	<li>Cut the yellow strand to size, and work into the blue cone and the cylinder. 
	NOTE: Radial shapes will require 5 cm long straight lines, and concentric shapes will require 4&#8211;8 cm long circular lines.</li>
	<li>Bake clay at 130 &#176;F until fully hardened.</li>
</ol>
5. Preparation for Observation by Motion-sensitive Video Recording
<ol>
	<li>Start gluing colored plastic number tags to the thorax of the worker bees as soon as the colony arrives, and continue throughout the experiment as new workers emerge.</li>
	<li>Remove all workers during the initial tagging session to ensure that every individual receives a number tag. Place workers back in the colony immediately after tagging. 
	NOTE: Unlike RFID tags, number tags are more difficult for workers to remove.</li>
	<li>As new workers emerge, tag them while they are still callow. Tagging frequency varies with the state of colony cycle, but averages to about 7&#8211;10 workers every 2&#8211;3 days. Dispose of workers that were not tagged during their callow stage because they may no longer be flower-na&#239;ve.</li>
	<li>System for tagging more workers than available tag numbers 
	NOTE: If the experiment continues for a period of months and multiple colonies are involved, there is a good chance that available tag numbers run out. There are about 7 distinguishable tag colors, each numbered from 1 to 99 allowing up to 693 concurrently tagged workers. An experiment running for 3 months using 3&#8211;4 colonies will have well over 693 workers in total, but never concurrently alive.
	<ol>
		<li>Ensure that numbers tags are positioned systematically (e.g., top side of the tag number is always aligned with the bee&#8217;s head), especially for the following numbers: 6, 9, 66, 69, 99.</li>
		<li>Remove dead workers, and record their tag number as &#8220;freed up&#8221;. Maintain a database of tag numbers and colors that are &#8220;available&#8221; or &#8220;in use&#8221; to ensure that a unique tag is not used on multiple bees at the same time. 
		NOTE: Additional tag combinations may be produced by adding colors to already existing colors. For example, adding a yellow dot to a blue tag with a sharpie pen can create new combinations.</li>
	</ol>
	</li>
	<li>Video Data Processing
	<ol>
		<li>Place two internet protocol (IP) camcorders (minimum 1 mp picture resolution) in front of each floral display, outside the testing environment (see Figure 3). 
		<img alt="Figure 3" src="/files/ftp_upload/52033/52033fig3highres.jpg" /> 
		Figure 3. Testing Environment. A photograph of the testing environment showing the two frontal camcorders in the foreground, the ceiling camcorder in between the light fixtures, and the stimuli stands with sample stimuli in the middle of the room. 
		NOTE: A glass divider between the IP camcorders and the artificial flowers ensures that the artificial flowers are clearly visible. The IP camcorders may be up to 5 m away from the stimuli. <a href="https://www.jove.com/files/ftp_upload/52033/52033fig3highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a></li>
		<li>Replace the stock lenses with 1.8 mm vari-focal lenses. These lenses allow sufficient zoom and focus on the artificial flowers.</li>
		<li>Place an additional IP camcorder directly above the artificial flower, focusing on an area 1&#8211;2 m in front of the artificial flowers. This camcorder captures hovering and antennation behaviors.</li>
		<li>Connect the IP camcorders to a PC via a secondary network interface controller (NIC), and an Ethernet hub.</li>
		<li>Configure the PC&#8217;s dynamic host configuration protocol (DHCP) to dynamically distribute IP addresses to the IP camcorders.</li>
		<li>Configure a file transfer protocol (FTP) server on the PC.</li>
		<li>Configure an FTP client process to automatically deposit video clips on the PC.</li>
		<li>Configure the IP camcorder to record a 10 sec video clip each time motion is detected.&#160;</li>
	</ol>
	</li>
	<li>Video Clip Analysis
	<ol>
		<li>Open a video clip, and view the contents frame-by-frame using a video viewer of choice.</li>
		<li>Record a bee&#8217;s plastic tag number, date and time of recording in a spreadsheet or an RDBMS. Here, define a landing as a bee&#8217;s legs coming into contact with the artificial flower. 
		NOTE: Discard choices that are socially influenced (landing while another bee is present on the stimulus).</li>
	</ol>
	</li>
</ol>
6. Artificial Flower Preparation for Video Observation
<ol>
	<li>Design visual properties using a graphics editing software. 
	NOTE: Ensure that the printed pattern can be cut and folded into a cone. Use geometrical calculations to produce the cutout shape that results in a cone with an 8 cm diameter.</li>
	<li>Print, cut, and fold the visual property into a cone.</li>
	<li>Glue attachment clips to stimulus (see Figure 2).</li>
</ol>
7. Statistical Analysis
<ol>
	<li>In both experiments, compute a choice proportion for each bee (e.g., a particular bee made x choices of one flower out of a total of y).</li>
	<li>Analyze these proportions with a replicated Goodness of Fit Test7. 
	NOTE: A replicated G-Test computes a heterogeneity value (Gh) that indicates the amount of variability of replicates (i.e., each bee), and a pooled value (Gp) that indicates the overall significance of all choice proportions. The G values are compared to &#967;2 values in tests of significance.</li>
</ol>
8. Stimuli Presentation Sequence
<ol>
	<li>Attach artificial flowers to the flower stands inside the testing space. Change the combination and location of displayed stimuli at regular time intervals (e.g., daily) to avoid location effects.</li>
</ol>
9. Study Termination
<ol>
	<li>Place the colonies in the deep freezer at -10 &#176;C for 3 days to kill the bees.</li>
</ol>

<ol>
	<li>Plowright, C. M. S., Evans, S. A., Leung, J. C., Collin, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+preference+for+symmetry+in+flower-na&#239;ve+and+not-so-na&#239;ve+bumblebees.">The preference for symmetry in flower-na&#239;ve and not-so-na&#239;ve bumblebees.</a> Learn. Motiv. 42 (1), 76-83 (2011).</li><li>Streit, S., Bock, F., Pirk, C. W. W., Tautz, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+life-long+monitoring+of+individual+insect+behaviour+now+possible.">Automatic life-long monitoring of individual insect behaviour now possible.</a> Zool. 106, 169-171 (2003).</li><li>Chittka, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+human+are+insects,+and+does+it+matter.">How human are insects, and does it matter.</a> Formosan Entomol. 31, 85-99 (2011).</li><li>Lihoreau, 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=Radar+tracking+and+motion-sensitive+cameras+on+flowers+reveal+the+development+of+pollinator+multi-destination+routes+over+large+spatial+scales.">Radar tracking and motion-sensitive cameras on flowers reveal the development of pollinator multi-destination routes over large spatial scales.</a> PLoS Biol. 10 (9), e1001392 (2012).</li><li>Brodbeck, D. R., Shettleworth, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Matching+location+and+color+of+a+compound+stimulus:+Comparison+of+a+food-storing+and+a+nonstoring+bird+species.">Matching location and color of a compound stimulus: Comparison of a food-storing and a nonstoring bird species.</a> J. Exp. Psychol. Anim. Behav. 21 (1), 64-77 (1995).</li><li>Srinivasan, M., Lehrer, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temporal+resolution+of+colour+vision+in+the+honeybee.">Temporal resolution of colour vision in the honeybee.</a> J. Comp. Physiol. A. 157 (5), 579-586 (1985).</li><li>Sokal, R. R., Rohlf, F. J., Freeman, W. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> , (2011).</li><li>Lunau, K., Fieselmann, G., Heuschen, B., van de Loo, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visual+targeting+of+components+of+floral+colour+patterns+in+flower-na&#239;ve+bumblebees+(Bombus+terrestris;+Apidae).+.">Visual targeting of components of floral colour patterns in flower-na&#239;ve bumblebees (Bombus terrestris; Apidae). .</a> Naturwissenschaften. 93 (7), 325-328 (2006).</li><li>Lehrer, M., Horridge, G. A., Zhang, S. W., Gadagkar, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Shape+vision+in+bees:+Innate+preference+for+flower-like+patterns.">Shape vision in bees: Innate preference for flower-like patterns.</a> Phil. Trans. R. Soc. B. 347 (1320), 123-137 (1995).</li><li>Thompson, E. L., Plowright, C. M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+images+may+or+may+not+represent+flowers:+picture-object+correspondence+in+bumblebees+(Bombus+impatiens).">How images may or may not represent flowers: picture-object correspondence in bumblebees (Bombus impatiens).</a> Anim. Cognit. , (2014).</li><li>Orb&#225;n, L. L., Plowright, C. M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effect+of+flower-like+and+non-flower-like+visual+properties+on+choice+of+unrewarding+patterns+by+bumblebees.">The effect of flower-like and non-flower-like visual properties on choice of unrewarding patterns by bumblebees.</a> Naturwissenschaften. 100 (7), 621-631 (2013).</li><li>Leonard, A. S., Papaj, D. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=X&#8221;+marks+the+spot:+The+possible+benefits+of+nectar+guides+to+bees+and+plants.">X&#8221; marks the spot: The possible benefits of nectar guides to bees and plants.</a> Funct. Ecol. 25 (6), 1293-1301 (2011).</li></ol>

The authors have no competing financial interests.

RFID technology enables studying hundreds of individual workers with ease and high precision, but the characteristics of the recorded behavior is different from observations by humans and video recordings. The choice behavior recorded by RFID can be described as floral exploration. This is a very strict criterion of preference compared to criteria used in other studies, such as approach8, entry into a maze-arm9,10, antennal reaction8, or landing on a pattern11,12. In order to compare the validity of choice behavior definitions, and to validate the new RFID method for unrewarded behavior, video recordings of landing were observed in Experiment 2. All choice measures are not equal: the RFID criterion as measured by floral entry, indicated that the visual property of pattern positioning is more important to bee choice, while the video data indicated that the visual property of pattern type is more important to bee choice.
One of the general challenges in studying unlearned choice behavior is that it is very difficult to attract flower na&#239;ve, untrained bees to artificial flowers that do not offer any pollen or nectar. Indeed, many of the previous experiments resorted to training bees in the testing environment on stimuli that are thought to be irrelevant to choice behavior at testing stimuli. RFID and motion-sensitive video recordings overcome this obstacle by allowing continuous recording, 24 hr a day, without the constant supervision of the researcher, and by increasing the sample size from 15&#8211;20 bees to several hundred bees. While unrewarded choices by untrained bees remain a rare occurrence, these new experimental design parameters make the observation possible.
Other improvements offered by these two techniques include the elimination of sample bias, the improvement of external validity, and tracking of individual differences. Sample bias may be introduced when only studying a dozen or so bees in a colony. There are significant differences in behavioral idiosyncrasies across individual workers even within the same colony that are likely missed because only those workers are observed that happen to &#8220;cooperate&#8221; with the researcher at a given time. Studying 15&#8211;20 bees in a colony of 300 or more bees, represents as little as 5% of the total colony, in which case sampling bias may be significant. Tagging and observing the behavior of all workers eliminates this issue altogether. The number of simultaneous stimuli choices can also be manipulated. We offered binary choices in our experiment for technical reasons, but single choice or several choice designs are also feasible.
In terms of external validity, studying bees in a laboratory environment has traditionally been highly artificial, which has impeded the generalizability of results. For example, researchers had to be present for data collection, bees had to forage in a testing environment one by one, and testing was restricted to a small time window. The new techniques described in this paper remove these artificial limitations by making the observation unsupervised and unrestricted. Finally, individual differences of behavior can be documented because we can ascertain whether these were repeated choices by a single bee or by several bees.
Motion-sensitive, high-spatial resolution camcorders have the edge over RFID techniques in terms of the flexibility of stimuli designs: the appearance of a visual stimulus can be almost any shape or form as long as the subject&#8217;s identification can be captured on at least a few frames. Processing videos is a little more time-consuming than processing RFID data because the identification needs to be read by the researcher, which requires manual inspection of each video clip. If the visual stimulus design can meet the constraints of RFID reader (i.e., the RFID tags on the bee must come to at least 3&#8211;4 mm of the RFID reader), then RFID technology has the edge over automated large-scale data collection. Qualitative research would likely continue to be favored by video analysis. As shown in this experiment, RFID readers can amass very large data sets that requires no manual coding. The slightly different advantages associated with each technique suggest that in the future they could be used in a complementary way.
The future of both technologies may lie in the precise quantification of rarely occurring behaviors. For example, one distinct possibility for future applications is to employ these techniques in greenhouses and other more naturalistic environments. The combination of naturalism and experimental control would allow addressing questions that were not possible to answer before. Broadly speaking, these techniques offer two new ways of observing behavior in a rigorous and efficient manner. RFID and motion-sensitive video are a significant step forward not just for researchers studying pollinators or insects, but these techniques may also appeal to other behavioral scientists.

A key problem in studying unlearned choice behavior by bumblebees and honeybees is that flower-na&#239;ve, untrained workers do not readily enter the testing space where preferences can be measured. As a result, many researchers rely on a less than ideal technique: pre-training workers to feed inside the testing space from ostensibly neutral stimuli that researchers deem to be different from the experimental stimuli. However, recent experiments have shown that stimuli that were thought to be neutral (i.e., stimuli that do not influence subsequent choice behavior in a testing session) have influenced preferences in unexpected ways1. Automated systems that include Radio Frequency Identification (RFID)2 and motion-sensitive video recordings may offer an opportunity solve this problem. The aim of the study was twofold: (1) primarily to contribute to the literature on unlearned floral preferences by bumblebees, (2) and secondarily to evaluate two choice measurement systems, as recorded by two different automated recording devices.
Two automated systems3 were implemented in the present study to observe unlearned choice behavior: RFID and motion-sensitive video recordings. Two crucial elements of both systems are that choices are not rewarded, and the display of different visual cues can be manipulated. Motion-sensitive video (high definition, recording at 1 mp resolution) not only allows continuous observation of freely exploring workers in a flight room, but is critical for the efficient observation of relatively rare events4.
The research question in Experiment 1 relates to how different visual properties interact when displayed together. This study seeks to explore the relative importance of pattern positioning in relation to pattern type. Using a 2 x 2 design, radial (i.e., sunburst) and concentric (i.e., bull&#8217;s eye) pattern types are placed either centrally or peripherally on an artificial flower (see Figure 1 for examples of stimuli). RFID readers are built into these specially designed artificial flower stimuli, and bumblebees receive RFID enabled tags that allow us to record each tagged worker that enters the artificial flower stimulus. RFID observation works by the reader mechanism (built into the artificial flowers) sending signals at radio frequencies (13.56 MHz in this case), which are modulated by the presence of passive tags. The reader can detect and record these signal modulations, which vary slightly across tags enabling tag unique identification.
The questions of Experiment 2 are threefold. First, are flower-entry, as measured by RFID, and landing, as measured by video recordings equivalent choice criteria? Choice is measured at different points (landing for video, and flower entry for RFID), which may translate into different measures of preference. Second, what is the effect of central vs peripheral positioning? It is not known whether or not workers would choose a central pattern if a combination consisting of two radial patterns in different positions were presented (see Figure 4b). Third, what is the relative importance of pattern position vs pattern type? In other words, will bumblebees land on patterns of the preferred pattern type, or the preferred pattern position? Bees could prefer central-radial to a peripheral-concentric pattern, but the preference could be due to the pattern type or its central positioning. In this experiment, two variables were pitted against each other5 (see Figure 4c, d).
In Experiment 2, we used motion-sensitive video recordings on flower-like stimuli. Artificial flowers were placed inside a flight cage, and motion-sensitive high-definition camcorders were pointed at these flowers from the front and the top. More specifically, two camcorders were positioned so as to capture the frontal view of each of the two stimuli in the testing space. An additional camcorder was positioned between the stimuli to record hovering behavior from above, and captured behavior from both artificial flowers. Bumblebees were identified using number tags that could be read on high-definition video clips. Hovering, antennation and landing behaviors were observed.

<table border="0" cellpadding="0" cellspacing="0" width="708">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Name of Material/ Equipment</td>
			<td style="width:143px;">Company</td>
			<td style="width:119px;">Catalog Number</td>
			<td style="width:231px;">Comments/Description</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Miniaturized mic3 tags</td>
			<td style="width:143px;">Microsensys</td>
			<td style="width:119px;">mic3 TAG 64 bit RO</td>
			<td>RFID tags to glue to bee</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">RFID reader 2k6 head</td>
			<td style="width:143px;">Microsensys</td>
			<td style="width:119px;">2k6</td>
			<td>RFID readers built into artificial flowers</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">IP camcorders</td>
			<td style="width:143px;">Vivotek</td>
			<td style="width:119px;">IP8161</td>
			<td>Motion-sensitive video recorders</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Opalith Plattchen number tags and non-toxic glue</td>
			<td style="width:143px;">Beeworks.com</td>
			<td style="width:119px;">n/a</td>
			<td>Number tags to glue to bees</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Bumblebee Colony for Research</td>
			<td style="width:143px;">Koppert Canada</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Artificial flowers</td>
			<td style="width:143px;">N/A</td>
			<td style="width:119px;"></td>
			<td>Developed by campus biology shop</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Artificial flower stand</td>
			<td style="width:143px;">N/A</td>
			<td style="width:119px;"></td>
			<td>Developed by campus biology shop</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Flight room</td>
			<td style="width:143px;">N/A</td>
			<td style="width:119px;"></td>
			<td>Developed by campus biology shop</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Laptop with Windows</td>
			<td style="width:143px;">Generic hardware / Microsoft software</td>
			<td style="width:119px;"></td>
			<td>Used to download RFID data</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">RS 232 to USB converter</td>
			<td style="width:143px;">Generic</td>
			<td style="width:119px;"></td>
			<td>Connect RFID reader to computer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Desktop</td>
			<td style="width:143px;">IBM</td>
			<td style="width:119px;"></td>
			<td>Used to transmit video data</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Second NIC</td>
			<td style="width:143px;">Generic</td>
			<td style="width:119px;">10/100M NIC PCI</td>
			<td>Used to transmit video data</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Network hub</td>
			<td style="width:143px;">Generic</td>
			<td style="width:119px;">4-port</td>
			<td>Used to transmit video data</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">High precision tweezer</td>
			<td style="width:143px;">SPI</td>
			<td style="width:119px;"></td>
			<td>Used to glue number and RFID tags to bees</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Sugar</td>
			<td style="width:143px;">Generic</td>
			<td style="width:119px;"></td>
			<td>Used to mix with water to create sugar-water</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Pollen</td>
			<td style="width:143px;">Any local apiarist</td>
			<td style="width:119px;"></td>
			<td>Fed to bumblebees</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Marking cage with plunger</td>
			<td style="width:143px;">Beeworks.com</td>
			<td style="width:119px;"></td>
			<td>Aids tagging process</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Honey</td>
			<td style="width:143px;">Generic</td>
			<td style="width:119px;"></td>
			<td>Used to mix with water ot create pollen paste</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Bake clay</td>
			<td style="width:143px;">Sculpey</td>
			<td style="width:119px;"></td>
			<td>Stimulus for RFID</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Clay shaping tools</td>
			<td style="width:143px;">Generic</td>
			<td style="width:119px;"></td>
			<td>Stimulus for RFID</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">White paper</td>
			<td style="width:143px;">Generic</td>
			<td style="width:119px;"></td>
			<td>Stimulus for Video</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Laser printer</td>
			<td style="width:143px;">Generic</td>
			<td style="width:119px;"></td>
			<td>Stimulus for Video</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Wood</td>
			<td style="width:143px;">Generic</td>
			<td style="width:119px;"></td>
			<td>Stimulus for Video -- attachment clip</td>
		</tr>
	</tbody>
</table>

radio frequency identification and motion-sensitive video efficiently automate recording of unrewarded choice behavior by bumblebees

We present two methods for observing bumblebee choice behavior in an enclosed testing space. The first method consists of Radio Frequency Identification (RFID) readers built into artificial flowers that display various visual cues, and RFID tags (i.e., passive transponders) glued to the thorax of bumblebee workers. The novelty in our implementation is that RFID readers are built directly into artificial flowers that are capable of displaying several distinct visual properties such as color, pattern type, spatial frequency (i.e., &#8220;busyness&#8221; of the pattern), and symmetry (spatial frequency and symmetry were not manipulated in this experiment). Additionally, these visual displays in conjunction with the automated systems are capable of recording unrewarded and untrained choice behavior. The second method consists of recording choice behavior at artificial flowers using motion-sensitive high-definition camcorders. Bumblebees have number tags glued to their thoraces for unique identification. The advantage in this implementation over RFID is that in addition to observing landing behavior, alternate measures of preference such as hovering and antennation may also be observed. Both automation methods increase experimental control, and internal validity by allowing larger scale studies that take into account individual differences. External validity is also improved because bees can freely enter and exit the testing environment without constraints such as the availability of a research assistant on-site. Compared to human observation in real time, the automated methods are more cost-effective and possibly less error-prone.

Experiment 1: RFID Data
All 375 workers in the colony were RFID tagged, and 318 of these workers (85%) entered the flight-cage at some point during the study. A total of 197 (62% of bees that left the colony) visited at least one of four artificial flower stimuli.
Definition of a choice
A choice was defined as a worker entering into the artificial flower (see Figure 1). We labeled this behavior as &#8220;floral exploration.&#8221; This definition of a choice is stricter than the ones used in the literature, which, depending on the study, use some combination of hovering, antennation or landing. Floral exploration is a stricter definition of choice because it requires that bees not only attend to a stimulus by hovering, antennating, and landing on it, but also by exploring it.
Data management
RFID techniques have the capacity to collect an enormous amount of data relative to other methods. This experiment produced 310,221 records. A database program such as MySQL is an indispensable tool to store this amount of data and equally important are the SQL queries used to tease out answers to the research questions. For example, one issue is the definition of a choice. The RFID readers were configured to record the presence of a tag every 1 msec, which, in the case of bees that stayed inside the artificial flowers for minutes or even hours, can translate into several thousand recordings. Our definition of a choice was a visit that lasted at least 1 msec, but a new visit would not be counted until the current string of recordings was broken by at least a 1 min break.
Summary of experiment
Four-replicated goodness of fit tests were performed on all choices from a bees&#8217; &#8220;na&#239;ve session&#8221; to compare choice proportions to a theoretical value of chance7. A bee&#39;s na&#239;ve session refers to the first testing condition in which the bee &#8220;participated&#8221;. The G-tests reveal a preference for central positioning (see Table 1) and radial pattern type. Figure 4b shows that pattern preference is reversed when the concentric pattern is positioned centrally and the radial pattern is positioned peripherally. However, if positioning is held constant as in Figure 4a and d, pattern preference is towards the radial pattern. Figure 4 shows that the relative proportions of first choices for each pattern for each combination were comparable to the proportions shown for all choices.
<img alt="Figure 4" src="/files/ftp_upload/52033/52033fig4highres.jpg"/> 
Figure 4. RFID Experimental Results. Choice frequencies at the four different flower combinations in Experiment 1. The dark brown bar graphs show all choices from the bee&#39;s na&#239;ve session (left-side y-axis), and the light brown bars indicate the first choice of each worker (right-side y-axis). &#8220;All choices&#8221; show comparable patterns to &#8220;first choice&#8221;, but with greater statistical power. The bar charts show that the positioning of patterns is more important than the type of a pattern. A centrally positioned pattern was preferred even if the pattern type displayed an otherwise less preferable concentric pattern. Asterisks indicate a choice proportion that is significantly different from chance. Note. * p &#60; .05, ** p &#60; .01, *** p &#60; .001. This figure has been modified from Orb&#225;n et al.11.
<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td rowspan="2">Conditions</td>
			<td colspan="3">Pooled</td>
			<td colspan="3">Heterogeneity</td>
			<td></td>
		</tr>
		<tr>
			<td>Gp</td>
			<td>df</td>
			<td>p</td>
			<td>Gh</td>
			<td>df</td>
			<td>p</td>
			<td></td>
		</tr>
		<tr>
			<td>Central-Radial vs Central-Concentric</td>
			<td>3.96</td>
			<td>1</td>
			<td>0.047</td>
			<td>197.55</td>
			<td>41</td>
			<td>0.000</td>
			<td></td>
		</tr>
		<tr>
			<td>Peripheral-Radial vs Central-Concentric</td>
			<td>33.77</td>
			<td>1</td>
			<td>0.000</td>
			<td>210.81</td>
			<td>42</td>
			<td>0.000</td>
			<td></td>
		</tr>
		<tr>
			<td>Central-Radial vs Peripheral-Concentric</td>
			<td>508.31</td>
			<td>1</td>
			<td>0.000</td>
			<td>345.78</td>
			<td>30</td>
			<td>0.000</td>
			<td></td>
		</tr>
		<tr>
			<td>Peripheral-Radial vs Peripheral-Concentric</td>
			<td>7.42</td>
			<td>1</td>
			<td>0.000</td>
			<td>84.06</td>
			<td>24</td>
			<td>0.000</td>
			<td></td>
		</tr>
	</tbody>
</table>
Table 1. Inferential Statistics of RFID Data. Experiment 1. This table has been modified from Orb&#225;n et al. (2013)11. Gp refers to significant deviation of a group proportion from chance, and Gh refers to the tests for individual differences (i.e., heterogeneity). Please refer to the manuscript for full details on the statistical tests.
Experiment 2: Video Data
A total of 264 choices were recorded across the four conditions over three testing sessions. Table 2 shows the number of workers and choices contributed from each colony.
Definition of a choice
Video data allows the recording of three types of choice behavior: hovering, antennation and landing. While all three types of behaviors can be observed, hovering and antennation are difficult to associate with a tag number due to quick motions that camcorders with poor resolution, or low speed cannot record. It is crucial to use a high-definition camcorder (though this was not available to us, ideally a high-frame rate camcorder should be used to minimize blurring) to ensure tag numbers that may appear only on a small number of frames can be read. This method was also used to compare choice patterns with the RFID technique, which detects floral exploration.
Motion sensitivity considerations
One of the key issues in producing a successful experiment is the configuration of the motion-sensitive camcorders. A camcorder that is too sensitive will record too much data that is impractical and can become very expensive to process. For example, initially our camcorder was triggered by regular vibrations in the building (e.g., people passing by on the hallway, air conditioner, etc.), which resulted in 1&#8211;2 valid data points for every 150&#8211;200 recorded video clips. On the other hand, an even more serious error is a low sensitivity configuration, which can miss key data. It is crucial to configure all camcorders in the same way, otherwise, sampling errors can skew the results.
Summary of experiment
Four replicated goodness of fit tests found three group proportions that deviated significantly from chance, and one non-significant overall proportion (see Table 3 and Figure 5). (1) Pattern is important: a significant preference for the central-radial over the central-concentric pattern was found (see Table 3). (2) Position of the radial pattern is less important: the presentation of the central-radial and peripheral radial combination showed no significant difference from chance. (3) The central-radial and peripheral-concentric combination resulted in a strong preference towards the central-radial pattern. The central-concentric and peripheral-radial combination elicited significant preference towards the peripheral-radial pattern. Pattern trumped location. Individual differences were non-significant in all four combinations (see Table 3).
<img alt="Figure 5" src="/files/ftp_upload/52033/52033fig5highres.jpg"/> 
Figure 5. Motion-Sensitive Video Results. Choice frequencies at the four different flower combinations in Experiment 2. The results show the importance of pattern type over pattern positioning: Radial patterns were preferred even if the patterns were positioned peripherally. Values indicate the number of choices of the displayed pattern. Asterisks indicate a choice proportion that is significantly different from chance. Note. ** p &#60; 0.01, *** p &#60; 0.001. This figure has been modified from Orb&#225;n11.
<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td rowspan="2">Conditions</td>
			<td>Session 1</td>
			<td colspan="2">Session 2</td>
			<td colspan="2">Session 3</td>
		</tr>
		<tr>
			<td>Colony 1</td>
			<td>Colony 2</td>
			<td>Colony 3</td>
			<td>Colony 4</td>
			<td>Colony 5</td>
		</tr>
		<tr>
			<td>No. of Workers</td>
			<td>45</td>
			<td>7</td>
			<td>2</td>
			<td>8</td>
			<td>23</td>
		</tr>
		<tr>
			<td>No. of Choices</td>
			<td>151</td>
			<td>25</td>
			<td>2</td>
			<td>20</td>
			<td>65</td>
		</tr>
	</tbody>
</table>
Table 2. Descriptive Statistics of Motion-Sensitive Video Data. Total number of choices recorded at the artificial flowers in Experiment 2 for each colony, and the number of workers making these choices. This table has been modified from Orb&#225;n et al.11. Please refer to the manuscript for full details.
<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td rowspan="2">Conditions</td>
			<td colspan="3">Pooled</td>
			<td colspan="3">Heterogeneity</td>
		</tr>
		<tr>
			<td>Gp</td>
			<td>df</td>
			<td>p</td>
			<td>Gh</td>
			<td>df</td>
			<td>p</td>
		</tr>
		<tr>
			<td>Central-Radial vs Central-Concentric</td>
			<td>17.98</td>
			<td>1</td>
			<td>0.000</td>
			<td>40.72</td>
			<td>29</td>
			<td>0.073</td>
		</tr>
		<tr>
			<td>Central-Radial vs Peripheral Radial</td>
			<td>1.85</td>
			<td>1</td>
			<td>0.173</td>
			<td>53.63</td>
			<td>39</td>
			<td>0.060</td>
		</tr>
		<tr>
			<td>Peripheral Radial vs Central Concentric</td>
			<td>6.57</td>
			<td>1</td>
			<td>0.010</td>
			<td>26.31</td>
			<td>27</td>
			<td>0.500</td>
		</tr>
		<tr>
			<td>Central Radial vs Peripheral Concentric</td>
			<td>18.18</td>
			<td>1</td>
			<td>0.000</td>
			<td>41.92</td>
			<td>37</td>
			<td>0.256</td>
		</tr>
	</tbody>
</table>
Table 3. Inferential Statistics Motion-Sensitive Video Data. Experiment 2. This table has been modified from Orb&#225;n et al.11. Gp refers to significant deviation of a group proportion from chance, and Gh refers to the tests for individual differences (i.e., heterogeneity). Please refer to the manuscript for full details on the statistical tests.

Watch this Scientific Journal Video about Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees at JoVE.com

Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees

This video describes Radio-Frequency Identification (RFID) and motion-sensitive video recording methods to monitor choice behavior by bumblebees.

We present two methods for observing bumblebee choice behavior in an enclosed testing space. The first method consists of Radio Frequency Identification ...

radio-frequency-identification-motion-sensitive-video-efficiently

Nanyang Technological University

Research

JoVE Journal

Neuroscience

10.9K Views.  University of Ottawa. This video describes Radio-Frequency Identification (RFID) and motion-sensitive video recording methods to monitor choice behavior by bumblebees. 

Video: Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees

Single Sensillum Recordings in the Insects Drosophila melanogaster and Anopheles gambiae

The sense of smell is essential for insects to find foods, mates, predators, and oviposition sites3. Insect olfactory sensory neurons (OSNs) are enclosed in sensory hairs called sensilla, which cover the surface of olfactory organs. The surface of each sensillum is covered with tiny pores, through which odorants pass and dissolve in a fluid called sensillum lymph, which bathes the sensory dendrites of the OSNs housed in a given sensillum. The OSN dendrites express odorant receptor (OR) proteins, which in insects function as odor-gated ion channels4, 5. The interaction of odorants with ORs either increases or decreases the basal firing rate of the OSN. This neuronal activity in the form of action potentials embodies the first representation of the quality, intensity, and temporal characteristics of the odorant6, 7.
Given the easy access to these sensory hairs, it is possible to perform extracellular recordings from single OSNs by introducing a recording electrode into the sensillum lymph, while the reference electrode is placed in the lymph of the eye or body of the insect. In Drosophila, sensilla house between one and four OSNs, but each OSN typically displays a characteristic spike amplitude. Spike sorting techniques make it possible to assign spiking responses to individual OSNs. This single sensillum recording (SSR) technique monitors the difference in potential between the sensillum lymph and the reference electrode as electrical spikes that are generated by the receptor activity on OSNs1, 2, 8. Changes in the number of spikes in response to the odorant represent the cellular basis of odor coding in insects. Here, we describe the preparation method currently used in our lab to perform SSR on Drosophila melanogaster and Anopheles gambiae, and show representative traces induced by the odorants in a sensillum-specific manner.

Single Sensillum Recordings in the Insects Drosophila melanogaster and Anopheles gambiae

Electrophysiological responses of olfactory sensory neurons to odorants can be measured in insects using single sensillum recordings. In this video article we will demonstrate how to perform single sensillum recordings in the antennae of the vinegar fly (Drosophila melanogaster) and the maxillary palps of the malaria mosquito (Anopheles gambiae).

The sense of smell is essential for insects to find foods, mates, predators, and oviposition sites3. Insect olfactory sensory neurons (OSNs) are enclosed ...

Cryopreservation of Cortical Tissue Blocks for the Generation of Highly Enriched Neuronal Cultures

In this study, we outline a standardized protocol for the successful cryopreservation and thawing of cortical brain tissue blocks to generate highly enriched neuronal cultures. For this protocol the freezing medium used is 10% dimethyl sulfoxide (DMSO) diluted in Hank's Buffered Salt Solution (HBSS). Blocks of cortical tissue are transferred to cryovials containing the freezing medium and slowly frozen at -1&deg;C/min in a rate-controlled freezing container. Post-thaw processing and dissociation of frozen tissue blocks consistently produced neuronal-enriched cultures which exhibited rapid neuritic growth during the first 5 days in culture and significant expansion of the neuronal network within 10 days. Immunocytochemical staining with the astrocytic marker glial fibrillary acidic protein (GFAP) and the neuronal marker beta-tubulin class III, revealed high numbers of neurons and astrocytes in the cultures. Generation of neural precursor cell cultures after tissue block dissociation resulted in rapidly expanding neurospheres, which produced large numbers of neurons and astrocytes under differentiating conditions. This simple cryopreservation protocol allows for the rapid, efficient, and inexpensive preservation of cortical brain tissue blocks, which grants increased flexibility for later generation of neuronal, astrocyte, and neuronal precursor cell cultures.

Here, we describe a method for efficient cryopreservation and thawing of cortical brain tissue blocks to generate highly enriched neuronal cultures. This simple protocol provides flexibility for later generation of neuronal, astrocyte, and neuronal precursor cell cultures.

In this study, we outline a standardized protocol for the successful cryopreservation and thawing of cortical brain tissue blocks to generate highly ...

Large-scale Recording of Neurons by Movable Silicon Probes in Behaving Rodents

A major challenge in neuroscience is linking behavior to the collective activity of neural assemblies. Understanding of input-output relationships of neurons and circuits requires methods with the spatial selectivity and temporal resolution appropriate for mechanistic analysis of neural ensembles in the behaving animal, i.e. recording of representatively large samples of isolated single neurons. Ensemble monitoring of neuronal activity has progressed remarkably in the past decade in both small and large-brained animals, including human subjects1-11. Multiple-site recording with silicon-based devices are particularly effective because of their scalability, small volume and geometric design.
Here, we describe methods for recording multiple single neurons and local field potential in behaving rodents, using commercially available micro-machined silicon probes with custom-made accessory components. There are two basic options for interfacing silicon probes to preamplifiers: printed circuit boards and flexible cables. Probe supplying companies (<a href="http://www.neuronexustech.com/" >http://www.neuronexustech.com/</a>; <a href="http://www.sbmicrosystems.com/">http://www.sbmicrosystems.com/</a>; <a href="http://www.acreo.se/">http://www.acreo.se/</a>) usually provide the bonding service and deliver probes bonded to printed circuit boards or flexible cables. Here, we describe the implantation of a 4-shank, 32-site probe attached to flexible polyimide cable, and mounted on a movable microdrive. Each step of the probe preparation, microdrive construction and surgery is illustrated so that the end user can easily replicate the process.

We describe methods for large-scale recording of multiple single units and local field potential in behaving rodents with silicon probes. Drive fabrication, probe attachment to the drive and probe implantation processes are illustrated in sufficient details for easy replication.

A major challenge in neuroscience is linking behavior to the collective activity of neural assemblies. Understanding of input-output relationships of ...

Simultaneous Recording of Calcium Signals from Identified Neurons and Feeding Behavior of Drosophila melanogaster

To study neuronal networks in terms of their function in behavior, we must analyze how neurons operate when each behavioral pattern is generated. Thus, simultaneous recordings of neuronal activity and behavior are essential to correlate brain activity to behavior. For such behavioral analyses, the fruit fly, Drosophila melanogaster, allows us to incorporate genetically encoded calcium indicators such as GCaMP1, to monitor neuronal activity, and to use sophisticated genetic manipulations for optogenetic or thermogenetic techniques to specifically activate identified neurons2-5. Use of a thermogenetic technique has led us to find critical neurons for feeding behavior (Flood et al., under revision). As a main part of feeding behavior, a Drosophila adult extends its proboscis for feeding6 (proboscis extension response; PER), responding to a sweet stimulus from sensory cells on its proboscis or tarsi. Combining the protocol for PER7 with a calcium imaging technique8 using GCaMP3.01, 9, I have established an experimental system, where we can monitor activity of neurons in the feeding center &#x2013; the suboesophageal ganglion (SOG), simultaneously with behavioral observation of the proboscis. I have designed an apparatus ("Fly brain Live Imaging and Electrophysiology Stage": "FLIES") to accommodate a Drosophila adult, allowing its proboscis to freely move while its brain is exposed to the bath for Ca2+ imaging through a water immersion lens. The FLIES is also appropriate for many types of live experiments on fly brains such as electrophysiological recording or time lapse imaging of synaptic morphology. Because the results from live imaging can be directly correlated with the simultaneous PER behavior, this methodology can provide an excellent experimental system to study information processing of neuronal networks, and how this cellular activity is coupled to plastic processes and memory.

Simultaneous Recording of Calcium Signals from Identified Neurons and Feeding Behavior of Drosophila melanogaster

The fruit fly, Drosophila melanogaster, extends its proboscis for feeding, responding to a sugar stimulus from its proboscis or tarsus. I have combined observations of the proboscis extension response (PER) with a calcium imaging technique, allowing us to monitor the activity of neurons in the brain, simultaneously with behavioral observation.

To study neuronal networks in terms of their function in behavior, we must analyze how neurons operate when each behavioral pattern is generated.  Thus, ...

Video-oculography in Mice

Eye movements are very important in order to track an object or to stabilize an image on the retina during movement. Animals without a fovea, such as the mouse, have a limited capacity to lock their eyes onto a target. In contrast to these target directed eye movements, compensatory ocular eye movements are easily elicited in afoveate animals1,2,3,4. Compensatory ocular movements are generated by processing vestibular and optokinetic information into a command signal that will drive the eye muscles. The processing of the vestibular and optokinetic information can be investigated separately and together, allowing the specification of a deficit in the oculomotor system. The oculomotor system can be tested by evoking an optokinetic reflex (OKR), vestibulo-ocular reflex (VOR) or a visually-enhanced vestibulo-ocular reflex (VVOR). The OKR is a reflex movement that compensates for "full-field" image movements on the retina, whereas the VOR is a reflex eye movement that compensates head movements. The VVOR is a reflex eye movement that uses both vestibular as well as optokinetic information to make the appropriate compensation. The cerebellum monitors and is able to adjust these compensatory eye movements. Therefore, oculography is a very powerful tool to investigate brain-behavior relationship under normal as well as under pathological conditions (f.e. of vestibular, ocular and/or cerebellar origin).
Testing the oculomotor system, as a behavioral paradigm, is interesting for several reasons. First, the oculomotor system is a well understood neural system5. Second, the oculomotor system is relative simple6; the amount of possible eye movement is limited by its ball-in-socket architecture ("single joint") and the three pairs of extra-ocular muscles7. Third, the behavioral output and sensory input can easily be measured, which makes this a highly accessible system for quantitative analysis8. Many behavioral tests lack this high level of quantitative power. And finally, both performance as well as plasticity of the oculomotor system can be tested, allowing research on learning and memory processes9.
Genetically modified mice are nowadays widely available and they form an important source for the exploration of brain functions at various levels10. In addition, they can be used as models to mimic human diseases. Applying oculography on normal, pharmacologically-treated or genetically modified mice is a powerful research tool to explore the underlying physiology of motor behaviors under normal and pathological conditions. Here, we describe how to measure video-oculography in mice8.

Video-oculography is a very quantitative method to investigate ocular motor performance as well as motor learning. Here, we describe how to measure video-oculography in mice. Applying this technique on normal, pharmacologically-treated or genetically modified mice is a powerful research tool to explore the underlying physiology of motor behaviors.

Eye movements are very important in order to track an object or to stabilize an image on the retina during movement. Animals without a fovea, such as the ...

Vertical T-maze Choice Assay for Arthropod Response to Odorants

Given the economic importance of insects and arachnids as pests of agricultural crops, urban environments or as vectors of plant and human diseases, various technologies are being developed as control tools. A subset of these tools focuses on modifying the behavior of arthropods by attraction or repulsion. Therefore, arthropods are often the focus of behavioral investigations. Various tools have been developed to measure arthropod behavior, including wind tunnels, flight mills, servospheres, and various types of olfactometers. The purpose of these tools is to measure insect or arachnid response to visual or more often olfactory cues. The vertical T-maze oflactometer described here measures choices performed by insects in response to attractants or repellents. It is a high throughput assay device that takes advantage of the positive phototaxis (attraction to light) and negative geotaxis (tendency to walk or fly upward) exhibited by many arthropods. The olfactometer consists of a 30 cm glass tube that is divided in half with a Teflon strip forming a T-maze. Each half serves as an arm of the olfactometer enabling the test subjects to make a choice between two potential odor fields in assays involving attractants. In assays involving repellents, lack of normal response to known attractants can also be measured as a third variable.

A vertical, T-maze olfactometer is described for assaying the behavioral response of arthropods. The olfactometer allows the experimenter to measure choices performed by test subjects when subjected to two potential odor fields. Both attraction to and repulsion from odorants can be measured with this device.

Given the economic importance of insects and arachnids as pests of agricultural crops, urban environments or as vectors of plant and human diseases, ...

Selective Tracing of Auditory Fibers in the Avian Embryonic Vestibulocochlear Nerve

The embryonic chick is a widely used model for the study of peripheral and central ganglion cell projections. In the auditory system, selective labeling of auditory axons within the VIIIth cranial nerve would enhance the study of central auditory circuit development. This approach is challenging because multiple sensory organs of the inner ear contribute to the VIIIth nerve 1. Moreover, markers that reliably distinguish auditory versus vestibular groups of axons within the avian VIIIth nerve have yet to be identified. Auditory and vestibular pathways cannot be distinguished functionally in early embryos, as sensory-evoked responses are not present before the circuits are formed. Centrally projecting VIIIth nerve axons have been traced in some studies, but auditory axon labeling was accompanied by labeling from other VIIIth nerve components 2,3. Here, we describe a method for anterograde tracing from the acoustic ganglion to selectively label auditory axons within the developing VIIIth nerve. First, after partial dissection of the anterior cephalic region of an 8-day chick embryo immersed in oxygenated artificial cerebrospinal fluid, the cochlear duct is identified by anatomical landmarks. Next, a fine pulled glass micropipette is positioned to inject a small amount of rhodamine dextran amine into the duct and adjacent deep region where the acoustic ganglion cells are located. Within thirty minutes following the injection, auditory axons are traced centrally into the hindbrain and can later be visualized following histologic preparation. This method provides a useful tool for developmental studies of peripheral to central auditory circuit formation.

Here we describe a microdissection technique followed by fluorescent dye injection into the acoustic ganglion of early chick embryos for selective tracing of auditory axon fibers in the nerve and hindbrain.

The embryonic chick is a widely used model for the study of peripheral and central ganglion cell projections. In the auditory system, selective labeling ...

Measuring Spinal Presynaptic Inhibition in Mice By Dorsal Root Potential Recording In Vivo

Presynaptic inhibition is one of the most powerful inhibitory mechanisms in the spinal cord. The underlying physiological mechanism is a depolarization of primary afferent fibers mediated by GABAergic axo-axonal synapses (primary afferent depolarization). The strength of primary afferent depolarization can be measured by recording of volume-conducted potentials at the dorsal root (dorsal root potentials, DRP). Pathological changes of presynaptic inhibition are crucial in the abnormal central processing of certain pain conditions and in some disorders of motor hyperexcitability. Here, we describe a method of recording DRP in vivo in mice. The preparation of spinal cord dorsal roots in the anesthetized animal and the recording procedure using suction electrodes are explained. This method allows measuring GABAergic DRP and thereby estimating spinal presynaptic inhibition in the living mouse. In combination with transgenic mouse models, DRP recording may serve as a powerful tool to investigate disease-associated spinal pathophysiology. In vivo recording has several advantages compared to ex vivo isolated spinal cord preparations, e.g. the possibility of simultaneous recording or manipulation of supraspinal networks and induction of DRP by stimulation of peripheral nerves.

Measuring Spinal Presynaptic Inhibition in Mice By Dorsal Root Potential Recording In Vivo

GABAergic presynaptic inhibition is a powerful inhibitory mechanism in the spinal cord important for motor and sensory signal integration in spinal cord networks. Underlying primary afferent depolarization can be measured by recording of dorsal root potentials (DRP). Here we demonstrate a method of in vivo recording of DRP in mice.

Presynaptic inhibition is one of the most powerful inhibitory mechanisms in the spinal cord. The underlying physiological mechanism is a depolarization of ...

A Procedure for Implanting a Spinal Chamber for Longitudinal In Vivo Imaging of the Mouse Spinal Cord

Studies in the mammalian neocortex have enabled unprecedented resolution of cortical structure, activity, and response to neurodegenerative insults by repeated, time-lapse in vivo imaging in live rodents. These studies were made possible by straightforward surgical procedures, which enabled optical access for a prolonged period of time without repeat surgical procedures. In contrast, analogous studies of the spinal cord have been previously limited to only a few imaging sessions, each of which required an invasive surgery. As previously described, we have developed a spinal chamber that enables continuous optical access for upwards of 8 weeks, preserves mechanical stability of the spinal column, is easily stabilized externally during imaging, and requires only a single surgery. Here, the design of the spinal chamber with its associated surgical implements is reviewed and the surgical procedure is demonstrated in detail. Briefly, this video will demonstrate the preparation of the surgical area and mouse for surgery, exposure of the spinal vertebra and appropriate tissue debridement, the delivery of the implant and vertebral clamping, the completion of the chamber, the removal of the delivery system, sealing of the skin, and finally, post-operative care. The procedure for chronic in vivo imaging using nonlinear microscopy will also be demonstrated. Finally, outcomes, limitations, typical variability, and a guide for troubleshooting are discussed.

A Procedure for Implanting a Spinal Chamber for Longitudinal In Vivo Imaging of the Mouse Spinal Cord

In this video, we describe a procedure for implanting a chronic optical imaging chamber over the dorsal spinal cord of a live mouse. The chamber, surgical procedure, and chronic imaging are reviewed and demonstrated.

Studies in the mammalian neocortex have enabled unprecedented resolution of cortical structure, activity, and response to neurodegenerative insults by ...

Quantifying Fish Swimming Behavior in Response to Acute Exposure of Aqueous Copper Using Computer Assisted Video and Digital Image Analysis

Behavioral responses of aquatic organisms to environmental contaminants can be precursors of other effects such as survival, growth, or reproduction. However, these responses may be subtle, and measurement can be challenging. Using juvenile white sturgeon (Acipenser transmontanus) with copper exposures, this paper illustrates techniques used for quantifying behavioral responses using computer assisted video and digital image analysis. In previous studies severe impairments in swimming behavior were observed among early life stage white sturgeon during acute and chronic exposures to copper. Sturgeon behavior was rapidly impaired and to the extent that survival in the field would be jeopardized, as fish would be swept downstream, or readily captured by predators. The objectives of this investigation were to illustrate protocols to quantify swimming activity during a series of acute copper exposures to determine time to effect during early lifestage development, and to understand the significance of these responses relative to survival of these vulnerable early lifestage fish. With mortality being on a time continuum, determining when copper first affects swimming ability helps us to understand the implications for population level effects. The techniques used are readily adaptable to experimental designs with other organisms and stressors.

Measuring the impacts of environmental contaminants on fish behavior is often subjective and challenging particularly when dealing with sublethal endpoints. We describe methods including video technology to quantify swimming behavior of early life stage white sturgeon (Acipenser transmontanus) during and after 96 hr acute exposures to various concentrations of copper.

Behavioral responses of aquatic organisms to environmental contaminants can be precursors of other effects such as survival, growth, or reproduction.  ...