HZ is supported by the Wellcome Trust and GlaxoSmithKline funded Translational Medicines and Therapeutics (TMAT) program, and by the Bernard Wolfe Health Neuroscience Fund. NM is funded by the Wellcome Trust PhD program. ISF and PCF are supported by the Wellcome Trust Senior Fellowship program&#160;and the Bernard Wolfe Health Neuroscience Fund. NS is supported by the Bernard Wolfe Health Neuroscience Fund.

All the procedures described in this protocol were developed and tested following ethical approval from the Cambridge Local Research Ethics Committees.
1. Grip Force as a Measure of Food Related Motivation
<ol>
	<li>Apparatus and set up:
	<ol>
		<li>Install MATLAB with Cogent toolboxes on the stimulus delivery laptop.</li>
		<li>Connect the force transducer and associated data acquisition system to the stimulus delivery laptop via the ethernet port. See Table 1 for details of the required hardware and software. 
		Note: To run the task in the magnetic resonance imaging (MRI) scanner a simple clench force rubber bulb is used, linked to pressure transducer outside the scanner. Changes in air pressure inside the bulb when it is squeezed, can be measured by the transducer and be directly related to the exerted effort.</li>
		<li>Set up the program to continuously poll the data acquisition system and read in 10 samples on each polling. Take the mean of the samples as the force exerted. Note: Galvanic skin response (GSR) can also be measured alongside. For this the stimulus delivery laptop requires a parallel port to connect to the GSR data acquisition system to synchronize the GSR with the other measures. Use a separate computer to record the measured GSR signal to minimize the load on the stimulus delivery laptop. GSR measurement is not discussed further.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 1" fo:content-width="5in" fo:src="/files/ftp_upload/51281/51281fig1highres.jpg" src="/files/ftp_upload/51281/51281fig1.jpg" /> 
Figure 1. Hardware set up for the grip force task.
<ol start="2">
	<li>Procedure:
	<ol>
		<li>Set up the equipment on a table or other stable surface as shown in Figure 1. Wait for the data acquisition system to connect to the laptop.</li>
		<li>Collect a baseline measure for the grip force transducer and the participant&#39;s maximal effort, hereafter referred to as the maximal voluntary contraction (MVC) prior to starting the task.
		<ol>
			<li>Place the grip force transducer on the table and collect the baseline measure.</li>
			<li>To measure the MVC, ask the participant to hold the grip force transducer and choose a comfortable arm position to maintain for the duration of the task. Instruct the participant to squeeze the transducer five times as hard as possible and take the mean of the five exertions as the maximal calibration for the task. Note: The force exerted by the participant during the response period is measured as a percentage of the difference between the baseline and the MVC as follows: <img alt="" fo:content-width="2in" height="44" src="/files/ftp_upload/51281/51281eq1.jpg" width="210" />If the effort is negative it is set to the minimum force of zero and if it is greater than the MVC measured during calibration it is set to the maximum effort of 100 units. This is done to account for any remaining noise after the 10 sample point smoothing is applied as described above. The resulting series of effort samples are accumulated during the response period and stored as the effort response for the trial.</li>
		</ol>
		</li>
		<li>Start the task. 
		Note: If the task session is long, then fatigue effects can be taken in to account by measuring the MVC at the end of the task as well, and relating the fatigue effect to the difference between the MVCs at the beginning and the end of the task session.</li>
	</ol>
	</li>
	<li>Key dependent variables: 
	This method captures the force-time curve on each trial. From the force-time curve extract the following variables: area under the curve (AUC), maximum or peak force exerted and the rate or the slope of the force time curve.</li>
	<li>Applications: 
	Three applications of the grip force measure are described below.
	<ol>
		<li>Examining relative reward value: the Effortful Picture Selection task. 
		Note: This task measures the relative effort participants are willing to exert to view different kinds of rewarding images such as foods and consumer goods. The effort ratings are related to their subjective liking ratings for the same images. The experimental design is as follows:
		<ol>
			<li>Present two images side by side on each trial of the task; one is a large (300 x 300 pixels) and clearly visible default image, and the other a small (5 x 5 pixels) indistinct nondefault image. Exerting force on the transducer enlarges the nondefault image and shrinks the default image.</li>
			<li>Select 6 images from three reward categories: high calorie food, low calorie food and (gender specific) rewarding nonfoods. Have the images independently rated for subjective liking by a healthy volunteer group. Create image pairs such that every image is paired with all the images from the other two categories. Counterbalance the pairs such that each image appears as default and nondefault image in an equal number of trials.</li>
			<li>Running the task: Perform all steps described in section 1.2.</li>
			<li>Explain the trial structure to the participant and tell her that she can increase the size of the size of the nondefault image and correspondingly decrease that of the default image by squeezing the transducer. 
			Note: The counterbalancing ensures that all images will have equal numbers of trials in which effort will enlarge or shrink them.</li>
			<li>Set the force required to make the nondefault image as large as possible at 10% of each individual&#39;s MVC (This percentage may have to be set individually for each Biopac module). 
			Note: The relationship between exerted force and picture size is determined as follows. Assuming both the background and foreground images are square, let lB and lF be the length of background and foreground images respectively. Let g, GMVC and, GBASE be the grip force response measured during the response period of a trial, maximum force measured during calibration and baseline measured during calibration respectively. Further, assuming a linear relationship between grip force and image size, lB and lF can be written as <img alt="" fo:content-width="1.5in" src="/files/ftp_upload/51281/51281eq2.jpg" width="140" /> under the constraints <img alt="" fo:content-width="1.5in" src="/files/ftp_upload/51281/51281eq3.jpg" width="120" /> 
			where <img alt="" fo:content-width="3in" src="/files/ftp_upload/51281/51281eq4.jpg" width="280" /> 
			The constraints ensure that an image does not expand more than Lmax even if a force exceeding GMVC is exerted.</li>
			<li>Present a short demonstration of the task.</li>
			<li>Tell the participant that she can view images as she choses depending on how much effort she exerts. Leave the participant on her own to complete the task.</li>
			<li>After the task is complete, collect liking ratings for each image on visual analogue scales subsequently.</li>
			<li>To analyze the data, for each image take the average of the areas under the force-time curves across all the trials in which it was the nondefault image and effort was required to enlarge it. This mean AUC is taken as the measure of the motivation for that particular image.</li>
		</ol>
		</li>
		<li>Examining subliminal motivation for food. 
		Note: Using both subliminal and conscious stimulus presentations, this task examines both subliminal and conscious motivation for food. The description below is based on a previous study using sensory specific satiation (see Ziauddeen&#160;et al.16). The experimental design is as follows:
		<ol>
			<li>Select three stimuli: a savory food, a sweet food and a neutral nonfood item. Collect two images of each item, one for the conscious trial and the other for the subliminal trials so as to minimize direct motor specification effects12. Using Adobe Photoshop, format all images to have the same luminance and the same patterned background (a checkered array of 1 mm squares of yellow, red, green, and brown). Blur the picture edges using a single pass.</li>
			<li>Create a mask image by randomly scrambling all pictures, and then blend them to create a composite image.</li>
			<li>The subliminal presentation is achieved by sandwich masking. To do this present the mask image for 200 msec, then the stimulus image for 33 msec, followed by the mask again for 267 msec. For the conscious trials present the mask for 200 msec, then the stimulus image for 200 msec and the backward mask for 100 msec. The total presentation is 500 msec in both trial types.</li>
			<li>After the masked stimulus presentation, start the response window during which the participant can exert force on the grip force transducer. Provide real time feedback by way of a fluid level on the screen. 
			Note: In all tasks using the fluid level for feedback to the participants, the height of the column and the maximal height that can be achieved are both varied randomly across trials. e.g. the height of the column is set to vary between 100, 110, and 120 units and the maximal height that can be achieved between 80, 90, and 100 units as a percentage of each participant&#39;s maximal force as measured at the start of the task. While the feedback serves an important role in engaging subjects with the task, this set up ensures that there is no consistent relationship between the exerted force and the height of the fluid level from trial to trial. The purpose is to prevent participants from modulating their effort to achieve a particular feedback, such as the getting the fluid level to the very top. Participants are explicitly informed that the feedback is unreliable and are instructed to judge their effort themselves and not to rely on the fluid level.</li>
			<li>For each trial, present a fixation cross for 500 msec, followed by the masked stimulus for 500 msec and then the response window with fluid level feedback for 3,000 msec.</li>
			<li>Running the task: Perform all steps as described in section 1.2.</li>
			<li>On each trial ask the participant to focus her attention on the central fixation cross. Explain to her that when the fluid level appears she can squeeze the force transducer to win points towards the item just presented. Explain that on some trials the image may be difficult to see and suggest she follow her instincts. Emphasize that the feedback in unreliable.</li>
			<li>Run the task in as many blocks as required.</li>
			<li>Following the completion of the task, check how well the masking procedure worked. This can be done in two ways: by collecting the participant&#39;s subjective report and by performing a forced choice discrimination. In the latter, present the masked stimulus as in the main task, followed by two options and ask the participant to indicate which one was just presented. Present each image as many times as it was presented in each block of the main task.</li>
			<li>Calculate the discriminability index (d&#39;) as per signal detection theory, if the masking has worked well, the d&#39; should be close to zero.</li>
		</ol>
		</li>
		<li>Examining food related motivation in the scanner.
		<ol>
			<li>Using the grip force bulb and the accompanying pressure transducer, these grip force based tasks can be run in the MRI scanner. If feedback is used, then do so as in section 1.4.2.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
2. Willingness to Pay as a Measure of Reward Value
Note: This task can be programmed in any appropriate stimulus delivery software and requires only a standard desktop or laptop computer. The version described here has been programmed in Presentation (version 14.5, Neurobehavioral Systems).
<ol>
	<li>Procedures: 
	Note: This procedure is a modification of the computerized auction procedure from Plassmann 13. The auction procedure is as follows:
	<ol>
		<li>The auction involves a series of rounds, each featuring one food item. Photograph all food items on identical plates and backgrounds. Prior to the start of the task show participants the actual plates used in the images to provide an accurate sense of scale.</li>
		<li>Give the participants a fixed monetary budget, e.g. &#163;3.</li>
		<li>Tell the participant that she will be taken through several rounds of the auction and she can place a bid on each round. She can place her bid on a sliding scale that goes from &#163;0-&#163;3 in increments of 10p.</li>
		<li>Inform the participant that one round will be selected at the end of the auction as the round that counts. Therefore she does not have to spread her &#163;3 budget across different rounds, and can treat every round as if were the only one.</li>
		<li>Tell the participant the computer will be bidding against them in each round. If they outbid the computer on the selected round, they win the food item and only have to pay the amount the computer bid and will be able to keep any remaining change. If however, the computer outbids or matches their bid, they do not get the food item, but still get to keep their monetary budget.</li>
		<li>Explain to the participant that that given these set of rules, the best strategy for bidding in this auction is to bid the amount closest to how much they would be really willing to pay for the food item on offer. 
		Note: The bid collected in this way corresponds to their WTP.</li>
	</ol>
	</li>
	<li>Applications:
	<ol>
		<li>Examining sensitivity of the measure to changes in internal state. 
		Note: As a proof of concept, the sensitivity of the measure to changes in value with changes in hunger and satiety was examined. Healthy normal-weight volunteers took part in the auction procedure before and after eating a fixed-calorie meal (550 kCal). A sensory specific satiety manipulation was used.
		<ol>
			<li>Collect hunger and fullness ratings on a visual analogue scale.</li>
			<li>Perform the first block of the task as described in section 2.1. Design the task such that the planned food item is selected as the round that counts provided a nonzero bid is placed.</li>
			<li>Present the participant with the food they have won and give them 15 min to consume the meal. Subtract the payment from the &#163;3 budget.</li>
			<li>Collect hunger and fullness rating again.</li>
			<li>Perform the second block of the task with a new &#163;3 budget. No food is won in the second block.</li>
			<li>Contrast the WTP for different items across the two blocks.</li>
		</ol>
		</li>
		<li>Future applications: Examining neural systems involved in value computation. 
		Note: This task can be set up and run in the fMRI scanner to examine the neural correlates of value computation. It has recently been used in a pharmacological fMRI study looking at the effect of dopaminergic influences on value computation for food reward. Participants performed a single block of the task after receiving a single dose of either a dopamine agonist (bromocriptine), a dopamine antagonist (sulpiride) or placebo. The procedure was almost identical to section 2.1 apart from the fact that the scale was set to increase in 20p increments. Compared to similar tasks13, this measure permits the capture of the WTP as a more continuous variable as opposed to a discrete variable that takes a maximum of 4 values (corresponding to each button of the standard MRI button box).</li>
	</ol>
	</li>
</ol>

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The authors declare that they have no competing financial interests. HZ, NS, VCC, ISF, and PCF have been involved in academic collaborations with GlaxoSmithKline that have used some of the techniques described in this manuscript.

This article describes a set of measures for the measurement of motivation for food rewards and reward value. The application of grip force measures to the study of food related motivation in humans is particularly novel. Representative results have been presented for most of the applications described demonstrating the value of these methods and their sensitivity to metabolic and pharmacological manipulations and therefore their potential further use in future studies of food related motivation and in trials of anti-obesity drugs. These more objective measures are easily transferable and comparable across different settings. It would also be useful to consider the influence of individual variability on these measures by examining the effects of traits such as impulsivity on them.
Some important points must be emphasized. In the use of the grip force tasks, the initial calibration and the capture of the MVC are critical. It is ideal to capture the grip response from the start of each trial and not limit it solely to the designated response window as this permits the examination of premature responding. There is some variability in the Biopac MP150 modules so each module should be tested to determine the settings that are most suitable for that piece of equipment. Where nonstandardized images are used, it is critical to have them independently rated to determine how rewarding they are perceived to be. An important limitation of all these measures is that they do not capture liking for the food rewards used so it is important to collect measures of subjective liking using visual analogue scales or other appropriate tools, after the task. These can then be compared to the motivational measures or used to model the effects of other variables on the primary dependent variables. However it is important to note that in studies where actual food rewards are consumed, liking ratings collected after the task are likely to be affected by food consumption. This emphasizes the importance of having not only representative images but also representative foods e.g. a chocolate brownie that looks and tastes like most chocolate brownies would; and to have these independently rated.
Finally it is critical to acknowledge that all these measures use food pictures as representations of food rewards instead of actual food rewards. While this does present some limitations, anticipatory behavior towards food and decisions regarding food are often guided by representations of the food rather than by immediate consummatory reward. Nevertheless, it is essential for the methods described here that when they are linked to outcomes such as successfully bidding for a food, real outcomes should be delivered.

The study of food reward processing in humans has received a significant impetus from the rising concerns about the obesity epidemic. As the route to obesity in most obese individuals is through increased energy intake over and above metabolic need1, it is important to understand the drivers and mechanisms of overconsumption. Prevailing models consider this overconsumption to be a form of nonhomeostatic or &#8216;hedonic&#39; eating, i.e. consumption that is driven not by homeostatic needs but by the rewarding aspects of the food(s) consumed2. However this is a complex phenomenon and the homeostatic and hedonic/reward systems are overlapping and interactive. Further there are several factors that affect nonhomeostatic eating that do not directly relate to hedonic aspects of the food such as portion size or the variety of foods available3. Nevertheless it is important to be able characterize and measure the different aspects of food reward.
Berridge and colleagues have described three components of reward: liking, wanting, and learning. These three components are linked but are dissociable in terms of their underlying neural systems. Liking refers to the hedonic impact of a reward and wanting is the motivation for the reward. Learning comprises the associations with and predictions about the reward. These components are further distinguished into two subcomponents, core or implicit, and conscious or explicit. Liking is comprised of &#8216;liking&#39; which refers to core objective hedonic reactions, and the conscious subjective experience of pleasure. Similarly wanting consists of &#8216;wanting&#39;, the incentive salience of rewards and reward related cues, and the conscious subjective experience of desire for incentives as is normally understood by the term. The conscious, subjective experiences of liking and wanting are elaborated out of the core reactions by higher cognitive mechanisms. Lastly learning too consists of implicit elements such as Pavlovian and instrumental associations and associative conditioning; as well as explicit representations and cognitive predictions4.
These three elements of reward are linked but are dissociable both experimentally and in terms of their neural substrates. While this framework helps us understand how the organism responds to one reward at a time, how does the individual organism respond when confronted with more than one potential reward? According to a widely accepted model in neuroeconomics, the central stage in behavioral selection involves computing subjective values of all options on offer. This computation is thought to entail evaluating and weighting different attributes of each option, leading to a single comparable value, often denoted as goal value5, with the option with the highest goal value can then be selected.
Much of this work on the neural basis of reward has been derived from elegant studies in animal neuroscience. A challenge in investigating hedonics, goal values and motivation in humans has been the difficulty in measuring these different components reliably and objectively. It is critical to go beyond subjective measures of reward value such as self-ratings of liking or goal value, as might, for example, be recorded on a visual analogue rating. Given the difficulty of correctly introspecting about value and the doubts over whether it is reported truthfully, it is essential to develop of robust quantitative tools that can be validated.
While the objective hedonic reactions observed in rodents are also seen in human infants6, these are difficult to assess in adult humans. The liking or hedonic element thus remains a difficult one to measure objectively in adult humans. However it is possible to examine wanting or motivation more objectively and precisely and this paper describes a set of methods based on the use of grip force as a motivational measure. The amount of effort that individuals will expend to receive a reward is modulated by the magnitude of the reward they expect. The motivation towards the reward can be operationalized as the exerted effort. Pessiglione and colleagues elegantly demonstrated the use of grip force as a measure of motivation for monetary rewards, with participants exerting greater force for monetary rewards that had larger values7. In the case of food rewards the value of the food reward to the individual depends on several factors of which internal state (hunger or satiety) is a critical one8. With satiation, there is a decrease in neural activity in the orbitofrontal cortex (OFC), a brain region that encodes the current value of stimulus, to receipt of the same food9,10. The OFC projects to the ventral striatum which modulates motivational responding7. Thus a good motivational measure should show sensitivity to changes in reward value with satiation.
To determine goal value, direct subjective evaluations are nonideal. A more indirect way that also has the benefit of incentivizing participants to reveal their true goal value is to use a modified version of the Becker-DeGroot-Marschak auction11. Through a simple set of rules, this auction procedure motivates people to reveal the maximum amount of monetary resources they are willing to pay for items on offer. Their willingness to pay (WTP) is taken as measure of goal value.

<table border="0" cellpadding="0" cellspacing="0" width="948">
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	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:335px;">HARDWARE</td>
			<td style="width:203px;"></td>
			<td style="width:119px;"></td>
			<td style="width:293px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Biopac MP150 data acquisition system</td>
			<td style="width:203px;">Biopac Systems Inc</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TSD121C hand held isometric dynamometer</td>
			<td style="width:203px;">Biopac Systems Inc</td>
			<td style="width:119px;">TSD121C</td>
			<td>Grip force transducer</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DA100C General Purpose Transducer Amplifier</td>
			<td style="width:203px;">Biopac Systems Inc</td>
			<td style="width:119px;">DA100C</td>
			<td>Interface between MP150 and TSD121C</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">SS56L Grip clench bulb</td>
			<td style="width:203px;">Biopac Systems Inc</td>
			<td style="width:119px;">SS56L</td>
			<td>MRI safe rubber clench bulb</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">TSD160C differential pressure transducer</td>
			<td style="width:203px;">Biopac Systems Inc</td>
			<td style="width:119px;">TSD160C</td>
			<td>Interface between MP150 and TSD160C</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">PowerLab 8/30 or 8/35</td>
			<td style="width:203px;">ADinstruments Ltd</td>
			<td style="width:119px;">PL358</td>
			<td>For Galvanic Skin Response (GSR) measurement only</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:335px;">FE116 GSR amplifier</td>
			<td style="width:203px;">ADinstruments Ltd</td>
			<td style="width:119px;">FE116</td>
			<td>For GSR measurement only</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MLT116F&#160;GSR electrodes</td>
			<td style="width:203px;">ADinstruments Ltd</td>
			<td style="width:119px;">MLT116F</td>
			<td>Supplied with GSR amplifier</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:335px;">Compute ethernet port and compatible with MP150</td>
			<td style="width:203px;"></td>
			<td style="width:119px;"></td>
			<td>For stimulus delivery and running of task. Ethernet port to connect to Biopac MP150</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:335px;">Computer with parallel port</td>
			<td style="width:203px;"></td>
			<td style="width:119px;"></td>
			<td>For GSR recording. Parallel port required to interface with Powerlab 8/30</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:335px;"></td>
			<td style="width:203px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:335px;">SOFTWARE</td>
			<td style="width:203px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">API module for Biopac hardware</td>
			<td style="width:203px;">Biopac Systems Inc</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Cogent and Cogent graphics toolboxes, version 1.29&#160;</td>
			<td style="width:203px;">Publically available</td>
			<td style="width:119px;"></td>
			<td>Download from Laboratory of Neurobiology, UCL</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:335px;">Labchart 6 or above</td>
			<td style="width:203px;">Adinstruments Ltd</td>
			<td style="width:119px;"></td>
			<td>For stimulus Display</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;">inpout.dll module for parallel port communication</td>
			<td style="width:203px;">Publically available</td>
			<td style="width:119px;"></td>
			<td>For Galvanic Skin Response measurement only</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:335px;">MATLAB R2009a</td>
			<td style="width:203px;">Mathworks Inc</td>
			<td style="width:119px;"></td>
			<td>Programming of main task</td>
		</tr>
	</tbody>
</table>

studying food reward and motivation in humans

A key challenge in studying reward processing in humans is to go beyond subjective self-report measures and quantify different aspects of reward such as hedonics, motivation, and goal value in more objective ways. This is particularly relevant for the understanding of overeating and obesity as well as their potential treatments. In this paper are described a set of measures of food-related motivation using handgrip force as a motivational measure. These methods can be used to examine changes in food related motivation with metabolic (satiety) and pharmacological manipulations and can be used to evaluate interventions targeted at overeating and obesity. However to understand food-related decision making in the complex food environment it is essential to be able to ascertain the reward goal values that guide the decisions and behavioral choices that people make. These values are hidden but it is possible to ascertain them more objectively using metrics such as the willingness to pay and a method for this is described. Both these sets of methods provide quantitative measures of motivation and goal value that can be compared within and between individuals.

Representative results from the different applications of each of the methods described above are shown here:
Grip force as a measure of motivation
Examining relative reward value: the Effortful Picture Selection task
This particular task was used in a proof-of-concept study of a novel mu-opioid antagonist drug GSK1521498 developed for the treatment of binge-eating and obesity14. In this study15, obese binge eating subjects were randomized to receive 4 weeks of either placebo or GSK1521498 at 2 mg/day or 5 mg/day. The aim was to determine whether the effects of the drug would be specific to food rewards without affecting other types of reward. Figures 2 and 3 show the data from the placebo and the 5 mg/day groups for the food and nonfood rewards respectively. The key question in this study was whether the drug would have a specific effect on food rewards and this measure allowed us to examine this. Figure 2 shows a specific effect of the drug on the motivation for high calorie food and it can be seen from Figure 3, there was no effect on the rewarding nonfood images.
<img alt="Figure 2" fo:content-width="5in" fo:src="/files/ftp_upload/51281/51281fig2highres.jpg" src="/files/ftp_upload/51281/51281fig2.jpg" /> 
Figure 2. Effortful Picture Selection task: effort expended and liking ratings for food images. The top panel shows the grip force exerted and the corresponding liking ratings at baseline in both groups and separately for placebo and the GSK1521498 group at the end of treatment. It can be seen that the difference between the force exerted for high-fat (HF) versus low-fat (LF) food images is no longer significant after drug treatment, even though the subjective liking for these images is higher. The bottom panel displays the correlations between the exerted force and liking ratings for the high-fat food images, again at baseline for both groups and separately at Day 28.The correlation between these two measures is seen at baseline and in the placebo group at the end of treatment but is lost in the drug group (*p &#60; 0.05; **p &#60;&#160; 0.01; ***p &#60; 0.001). This figure is reproduced from Cambridge et al.14). <a href="https://www.jove.com/files/ftp_upload/51281/51281fig2highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" fo:content-width="5in" fo:src="/files/ftp_upload/51281/51281fig3highres.jpg" src="/files/ftp_upload/51281/51281fig3.jpg" /> 
Figure 3. Effortful Picture Selection task: effort expended and liking ratings for nonfood images. The left panel shows the force exerted to view rewarding nonfood images in the placebo (PBO) and GSK1521498 (498 5 mg) groups. The right panel shows the liking ratings for the same images. It can be seen that there are no significant drug effects on the motivation towards or subjective liking for rewarding nonfood images. This figure is reproduced from Cambridge et al.14).
Examining subliminal motivation
This particular application is from a previous study in which participants performed two blocks of a food incentive force task16. In between blocks they were specifically sated (sensory specific) on one of two test foods, all participants were given 30% of their daily calorie intake in this one eating episode. On each trial they had the opportunity to win points towards the prize at stake depending on the amount of force they exerted on a grip force transducer. There were conscious trials, in which the prize at stake was presented for 200 msec and subliminal trials, where it is only presented for 33 msec. There were two food prizes, pizza and cake, and one nonfood prize which served as a control item. The subliminal presentation was achieved using a sandwich masking procedure employing a forward and backward mask. For the analysis of the data, the dependent variable of interest was grip force, which was extracted as the area under the force curve (AUC) for all trials. To allow comparisons across all participants, for each subject, the AUC for each trial type was normalized by the maximum mean AUC of the 6 types (sated, nonsated, nonfood; both fed and fasted). This provided a normalized score between 0-1 for each participant. To control for fatigue, post-prandial sluggishness and nonspecific effects across the fed and fasted sessions, the AUC for the nonfood item in each session was used as a baseline and subtracted from the sated and nonsated measures. (For further details see Ziauddeen&#160;et al.16). It can be seen that the motivation of the sated food decreases in both conscious and subliminal conditions (see Figure 4).
<img alt="Figure 4" fo:content-width="5in" fo:src="/files/ftp_upload/51281/51281fig4highres.jpg" src="/files/ftp_upload/51281/51281fig4.jpg" /> 
Figure 4. Specific satiety modulates motivational effort. (A) Change in hunger and fullness ratings with food consumption. (B, C) Participants exerted less for the food just consumed but still squeezed for the other food, regardless of awareness. Y-axis is the area under the curve normalized within subject and corrected for baseline changes. This figure is reproduced from Ziauddeen et al.15). <a href="https://www.jove.com/files/ftp_upload/51281/51281fig4highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Examining food related motivation in the scanner
Participants performed a session of the incentive force task in the scanner in which they squeezed the clench bulb to win points towards high calorie and low calorie food items for their lunch after the session. Figure 5 presents illustrative data from 10 subjects in a recent pharmacological fMRI study that shows that the task captures differential motivation for highly rewarding versus less rewarding foods.
<img alt="Figure 5" fo:content-width="5in" fo:src="/files/ftp_upload/51281/51281fig5highres.jpg" src="/files/ftp_upload/51281/51281fig5.jpg" /> 
Figure 5. Force exerted for different reward categories. Subjects squeezed the grip force bulb in the scanner to win points towards items from 3 different categories (HF: high calorie foods, LF: low calorie foods, NF: neutral nonfoods).
Willingness to pay as measure of reward value
Figure 6 presents the findings from the proof of concept study of the effect of satiety on willingness to pay for food rewards. To facilitate the within subjects comparison, each subject&#39;s bids were normalized by dividing by their maximum bid. It can be seen that participants were willing to pay more for the food items in the first round. This was reduced by satiation with 600 calories of the test food as reflected in lower bids in the second round. There appeared to be a stronger effect of satiation with savory foods compared to sweet foods but this was not significant.
<img alt="Figure 6" fo:content-width="5in" fo:src="/files/ftp_upload/51281/51281fig6highres.jpg" src="/files/ftp_upload/51281/51281fig6.jpg" /> 
Figure 6. Effect of satiety on willingness to pay (WTP). 10 healthy volunteers took part in this study. It can be seen that the normalized mean bid decreased following satiation with the study meal. As a sensory specific satiety manipulation was used the results for the second auction are presented separately for foods from the sated and nonsated categories. While there appears to be a greater effect on foods from the sated category, this was not statistically significant.

Watch this Scientific Journal Video about Studying Food Reward and Motivation in Humans at JoVE.com

Studying Food Reward and Motivation in Humans

This article describes a set of methods for the measurement of food related motivation and food related goal values in humans.

A key challenge in studying reward processing in humans is to go beyond subjective self-report measures and quantify different aspects of reward such as ...

studying-food-reward-and-motivation-in-humans

Research

JoVE Journal

Behavior

22.8K 次观看.  University of Cambridge. 本文介绍了一套用于食品相关的动机和人类食品相关目标值的测量方法。 

视频: Studying Food Reward and Motivation in Humans

A Procedure to Study the Effect of Prolonged Food Restriction on Heroin Seeking in Abstinent Rats

In human drug addicts, exposure to drug-associated cues or environments that were previously associated with drug taking can trigger relapse during abstinence. Moreover, various environmental challenges can exacerbate this effect, as well as increase ongoing drug intake.
The procedure we describe here highlights the impact of a common environmental challenge, food restriction, on drug craving that is expressed as an augmentation of drug seeking in abstinent rats.
Rats are implanted with chronic intravenous i.v. catheters, and then trained to press a lever for i.v. heroin over a period of 10-12 days. Following the heroin self-administration phase the rats are removed from the operant conditioning chambers and housed in the animal care facility for a period of at least 14 days. While one group is maintained under unrestricted access to food (sated group), a second group (FDR group) is exposed to a mild food restriction regimen that results in their body weights maintained at 90% of their nonrestricted body weight. On day 14 of food restriction the rats are transferred back to the drug-training environment, and a drug-seeking test is run under extinction conditions (i.e.&#160;lever presses do not result in heroin delivery).
The procedure presented here results in a highly robust augmentation of heroin seeking on test day in the food restricted rats. In addition, compared to the acute food deprivation manipulations we have used before, the current procedure is a more clinically relevant model for the impact of caloric restriction on drug seeking. Moreover, it might be closer to the human condition as the rats are not required to go through an extinction-training phase before the drug-seeking test, which is an integral component of the popular reinstatement procedure.

A procedure that allows a demonstration of robust augmentation of drug seeking in food-restricted rats is described. Following heroin self-administration training, rats go through an abstinence period, in a drug-free environment, during which they are mildly food restricted. Drug seeking is then tested in the drug-associated environment.

In human drug addicts, exposure to drug-associated cues or environments that were previously associated with drug taking can trigger relapse during ...

Disrupting Reconsolidation of Fear Memory in Humans by a Noradrenergic &#946;-Blocker

The basic design used in our human fear-conditioning studies on disrupting reconsolidation includes testing over different phases across three consecutive days. On day 1 - the fear acquisition phase, healthy participants are exposed to a series of picture presentations. One picture stimulus (CS1+) is repeatedly paired with an aversive electric stimulus (US), resulting in the acquisition of a fear association, whereas another picture stimulus (CS2-) is never followed by an US. On day 2 - the memory reactivation phase, the participants are re-exposed to the conditioned stimulus without the US (CS1-), which typically triggers a conditioned fear response. After the memory reactivation we administer an oral dose of 40 mg of propranolol HCl, a &#946;-adrenergic receptor antagonist that indirectly targets the protein synthesis required for reconsolidation by inhibiting the noradrenaline-stimulated CREB phosphorylation. On day 3 - the test phase, the participants are again exposed to the unreinforced conditioned stimuli (CS1- and CS2-) in order to measure the fear-reducing effect of the manipulation. This retention test is followed by an extinction procedure and the presentation of situational triggers to test for the return of fear. Potentiation of the eye blink startle reflex is measured as an index for conditioned fear responding. Declarative knowledge of the fear association is measured through online US expectancy ratings during each CS presentation. In contrast to extinction learning, disrupting reconsolidation targets the original fear memory thereby preventing the return of fear. Although the clinical applications are still in their infancy, disrupting reconsolidation of fear memory seems to be a promising new technique with the prospect to persistently dampen the expression of fear memory in patients suffering from anxiety disorders and other psychiatric disorders.

Disrupting Reconsolidation of Fear Memory in Humans by a Noradrenergic &amp;#946;-Blocker

Disrupting reconsolidation is a promising approach to dampen the behavioral expression of fear memory in patients with anxiety disorders or posttraumatic stress disorder. In a series of human fear conditioning studies we showed that disrupting reconsolidation by the noradrenergic &#946;-blocker propranolol is very effective in erasing conditioned fear responding.

The basic design used in our human fear-conditioning studies on disrupting reconsolidation includes testing over different phases across three consecutive ...

A Treatment Package without Escape Extinction to Address Food Selectivity

Feeding difficulties and feeding disorders are a commonly occurring problem for young children, particularly children with developmental delays including autism. Behavior analytic interventions for the treatment of feeding difficulties oftentimes include escape extinction as a primary component of treatment. The use of escape extinction, while effective, may be problematic as it is also associated with the emergence of challenging behavior (e.g., extinction burst). Such challenging behavior may be an acceptable side effect in treatment cases where feeding problems are severe and chronic (e.g., failure to thrive). However, in more acute cases (e.g., selective eating), the negative side effect may be unwarranted and undesired. More recent research on the behavioral treatment of food selectivity has begun to evaluate treatments for feeding difficulties that do not include escape extinction (e.g., demand fading, behavioral momentum), with some success. However, research to date reveals individual differences in responsiveness to such treatments and no clear preferable treatment has emerged. This manuscript describes a multi-component treatment package that includes shaping, sequential presentation and simultaneous presentation, for the treatment of food selectivity in four young children with developmental delays. This treatment package extends the literature on the behavioral treatment for food selectivity and offers a multi-component treatment protocol that may be clinically applicable across a range of treatment scenarios and settings.

Feeding difficulties are a common problem for children with developmental disorders, including autism, and behavioral interventions often include escape extinction. Recent research has begun to evaluate treatments that do not include escape extinction. This manuscript describes a multicomponent treatment package that does not use escape extinction to treat feeding difficulties.

Feeding difficulties and feeding disorders are a commonly occurring problem for young children, particularly children with developmental delays including ...

Quantifying Social Motivation in Mice Using Operant Conditioning

In this protocol, social motivation is measured in mice through a pair of operant conditioning paradigms. To conduct the experiments, two-chambered shuttle boxes were equipped with two operant levers (left and right) and a food receptacle in one chamber, which was then divided from the second chamber by an automated guillotine door covered by a wire grid. Different stimulus mice, rotated across testing days, served as a social stimulus behind the wire grid, and were only visible following the opening of the guillotine door. Test mice were trained to lever press in order to open the door and gain access to the stimulus partner for 15 sec. The number of lever presses required to obtain the social reward progressively increased on a fixed schedule of 3. Testing sessions ended after test mice stopped lever pressing for 5 consecutive minutes. The last reinforced ratio or breakpoint can be used as a quantitative measure of social motivation. For the second paradigm, test mice were trained to discriminate between left and right lever presses in order to obtain either a food reward or the social reward. Mice were rewarded for every 3 presses of each respective lever. The number of food and social rewards can be compared as a measurement of the value placed upon each reward. The ratio of each reward type can also be compared between mouse strains and the change in this ratio can be monitored within testing sessions to measure satiation with a given reward type. Both of these operant conditioning paradigms are highly useful for the quantification of social motivation in mouse models of autism and other disorders of social behavior.

This article describes a new protocol for the quantitative measurement of social motivation in mice using operant conditioning for a social reward. The protocol is useful for the measurement of social motivation in mouse models of autism and other disorders of social behavior.

In this protocol, social motivation is measured in mice through a pair of operant conditioning paradigms. To conduct the experiments, two-chambered ...

Force and Position Control in Humans - The Role of Augmented Feedback

During motor behaviour, humans interact with the environment by for example manipulating objects and this is only possible because sensory feedback is constantly integrated into the central nervous system and these sensory inputs need to be weighted in order meet the task specific goals. Additional feedback presented as augmented feedback was shown to have an impact on motor control and motor learning. A number of studies investigated whether force or position feedback has an influence on motor control and neural activation. However, as in the previous studies the presentation of the force and position feedback was always identical, a recent study assessed whether not only the content but also the interpretation of the feedback has an influence on the time to fatigue of a sustained submaximal contraction and the (inhibitory) activity of the primary motor cortex using subthreshold transcranial magnetic stimulation. This paper describes one possible way to investigate the influence of the interpretation of feedback on motor behaviour by investigating the time to fatigue of submaximal sustained contractions together with the neuromuscular adaptations that can be investigated using surface EMG. Furthermore, the current protocol also describes how motor cortical (inhibitory) activity can be investigated using subthreshold TMS, a method known to act solely on the cortical level. The results show that when participants interpret the feedback as position feedback, they display a significantly shorter time to fatigue of a submaximal sustained contraction. Furthermore, subjects also displayed an increased inhibitory activity of the primary cortex when they believed to receive position feedback compared when they believed to receive force feedback. Accordingly, the results show that interpretation of feedback results in differences on a behavioural level (time to fatigue) that is also reflected in interpretation-specific differences in the amount of inhibitory M1 activity.

Controlling an identical movement with position or force feedback results in different neural activation and motor behavior. This protocol describes how to investigate behavioral changes by looking at neuromuscular fatigue and how to evaluate motor cortical (inhibitory) activity using subthreshold TMS with respect to the interpretation of augmented feedback.

During motor behaviour, humans interact with the environment by for example manipulating objects and this is only possible because sensory feedback is ...

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Delay discounting refers to a decline in the value of a reward when it is delayed relative to when it is immediately available. Delay discounting tasks are used to identify indifference points, which reflect equal preference for two dichotomous reward alternatives differing in both delay and magnitude. Indifference points are key to assessing the shape of a delay-discounting gradient because they allow us to isolate the effect of delay on value. For example, if at a 1 week delay and a maximum of $1,000, the indifference point is at $700 we know that, for that participant, a 1-week delay corresponds to a 30% reduction in value. This video outlines an adjusting amount delay-discounting task that identifies indifference points relatively quickly and is inexpensive and easy to administer. Once data have been collected, non-linear regression techniques are typically used to generate discounting curves. The steepness of the discounting curve reflects the degree of impulsive choice of a group or individual. These techniques have been used with a wide range of commodities and have identified populations that are relatively impulsive. For example, people with substance abuse problems discount delayed rewards more steeply than control participants. Although degree of discounting varies as a function of the commodity examined, discounting of one commodity correlates with discounting of other commodities, which suggests that discounting may be a persistent pattern of behavior1.

Delay discounting refers to a decline in the value of a reward when it is delayed relative to when it is immediately available. We outline a computer-based delay discounting task that is easy to implement and allows for the quantification of the degree of delay discounting in human participants.

Delay discounting refers to a decline in the value of a reward when it is delayed relative to when it is immediately available. Delay discounting tasks ...

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

Numerous qualitative and quantitative techniques can be used to test sensory nerves and pain in both research and clinical settings. The current study demonstrates a quantitative sensory testing protocol using techniques to measure tactile sensation and pain threshold for pressure and heat using portable and easily accessed equipment. These techniques and equipment are ideal for new laboratories and clinics where cost is a concern or a limiting factor. We demonstrate measurement techniques for the following: cutaneous mechanical sensitivity on the arms and legs (von-Frey filaments), radiant and contact heat sensitivity (with both threshold and qualitative assessments using the Visual Analog Scale (VAS)), and mechanical pressure sensitivity (algometer, with both threshold and the VAS). The techniques and equipment described and demonstrated here can be easily purchased, stored, and transported by most clinics and research laboratories around the world. A limitation of this approach is a lack of automation or computer control. Thus, these processes can be more labor intensive in terms of personnel training and data recording than the more sophisticated equipment. We provide a set of reliability data for the demonstrated techniques. From our description, a new laboratory should be able to set up and run these tests and to develop their own internal reliability data.

The goal of this procedure is to demonstrate a battery of quantitative techniques for sensory and pain measurement in humans. The equipment and techniques described are commonly found in pain clinics or are easy to obtain.

Numerous qualitative and quantitative techniques can be used to test sensory nerves and pain in both research and clinical settings. The current study ...

Combining Quantitative Food-intake Assays and Forcibly Activating Neurons to Study Appetite in Drosophila

Food consumption is under the tight control of the brain, which integrates the physiological status, palatability, and nutritional contents of the food, and issues commands to start or stop feeding. Deciphering the processes underlying the decision-making of timely and moderate feeding carries major implications in our understanding of physiological and psychological disorders related to feeding control. Simple, quantitative, and robust methods are required to measure the food ingestion of animals after experimental manipulation, such as forcibly increasing the activities of certain target neurons. Here, we introduced dye-labeling-based feeding assays to facilitate the neurogenetic study of feeding control in adult fruit flies. We review available feeding assays, and then describe our methods step-by-step from setup to analysis, which combine thermogenetic and optogenetic manipulation of neurons controlling feeding motivation with dye-labeled food intake assay. We also discuss the advantages and limitations of our methods, compared with other feeding assays, to help readers choose an appropriate assay.

Combining Quantitative Food-intake Assays and Forcibly Activating Neurons to Study Appetite in Drosophila

Quantitative food-intake assays with dyed food provide a robust and high-throughput means to evaluate feeding motivation. Combining the food consumption assay with thermogenetic and optogenetic screens is a powerful approach to investigate the neural circuits underlying appetite in adult Drosophila melanogaster.

Food consumption is under the tight control of the brain, which integrates the physiological status, palatability, and nutritional contents of the food, ...

An Electrophysiology Protocol to Measure Reward Anticipation and Processing in Children

We present a protocol designed to measure the neural correlates of reward in children. The protocol allows researchers to measure both reward anticipation and processing. Its purpose is to create a reward task that is appropriate for young children with and without autism while controlling reward properties between two conditions: social and nonsocial. The current protocol allows for comparisons of brain activity between social and nonsocial reward conditions while keeping the reward itself identical between conditions. Using this protocol, we found evidence that neurotypical children demonstrate enhanced anticipatory brain activity during the social condition. Furthermore, we found that neurotypical children anticipate social reward more robustly than children with autism diagnoses. As the task uses snacks as a reward, it is most appropriate for young children. However, the protocol may be adapted for use with adolescent or adult populations if snacks are replaced by monetary incentives. The protocol is designed to measure electrophysiological events (event-related potentials), but it may be customized for use with eye-tracking or fMRI.

This protocol is designed to measure reward anticipation and processing in young children with and without autism. Specifically, the protocol is designed to study the neural correlates of reward during social and nonsocial conditions while controlling for reward between conditions.

We present a protocol designed to measure the neural correlates of reward in children. The protocol allows researchers to measure both reward anticipation ...

A Conflict Model of Reward-seeking Behavior in Male Rats

The present protocol describes a novel conflict task as a model of inhibitory control in rats. In this model, a natural rewarding stimulus (sexual stimulus) that represents a high-value reward, and the aversive stimuli (pins), are concurrently presented. The male rats have to climb or jump over the obstacle full of pins to approach and investigate the sexual partner. If the animal persists in their approaching behavior regardless of the aversive stimuli, it is considered as a maladaptive or risky reward-seeking behavior. The conflict task permits the evaluation of deficit in inhibitory control resulting from exposure to abused drug, such as morphine, or a stressful event. 
The main advantage of this model is that it provides a simple and quick way to discover the deficit in inhibitory control after exposure to opiate drugs or other stressful events. In addition to opiates, this behavioral model would also be useful for quickly discovering the inhibitory control deficits induced by other addictive drugs. However, the limitation is that the male rats' performance may be subject to exercising effects with repeated testing under this conflict task. In the future, one can hope that the individuals with the compulsive phenotype of reward-seeking behavior after exposure to opiates will be identified based on modifying this conflict model.

This conflict model is used to measure the impairment of inhibitory control after exposure to addictive drugs, or other factors that may influence inhibitory control. A sexual stimulus and an aversive obstacle are concurrently presented, thus male rats have to conquer the obstacle to approach the sexual reward.