The authors are grateful to Dr. Margaret Wardle for her exceptional training and technical assistance. This work was funded in part by Swedish Research Council grant FYF-2013-687 (IM).

This protocol is based on Mayo et al.31 (Experiment 1) and Ree et al.32 (Experiment 2). Ethical approval was granted by the Regional Ethical Review Board, Link&#246;ping, Sweden (Experiment 1) and the local ethical committee at the Department of Psychology, University of Oslo, Norway (Experiment 2).
1. Participant Screening and Preparation
<ol>
	<li>Recruit participants who lack tactile or uncorrected visual disturbances and are free of any neurological or psychiatric disorder, unless a specific patient population is being recruited.</li>
	<li>Ensure that participants are fully able to understand task instructions (e.g., fluent in the language that tasks are administered).</li>
	<li>If including more than one task (e.g. Experienced, Observed), ensure that task order is counterbalanced across participants, stratifying for gender, age, or other distinguishing factors.</li>
</ol>
2. Stimuli and Task Construction
NOTE: See Table 1 for experimental design.
<ol>
	<li>Experienced touch task (Experiments 1 and 2)
	<ol>
		<li>Create trials such that they consist of a baseline period, touch administration, and self-report ratings, all separated by jittered ITIs.
		<ol>
			<li>Baseline periods consist of a blank screen, fixation cross, or other neutral scene prior to tactile stimulation.</li>
			<li>Tactile stimulation is followed by a short (e.g. 1-2 s) ITI, then self-report ratings are obtained.</li>
			<li>A jittered inter-trial interval (ITI; e.g. 6-7 s) follows self-report ratings to allow muscle activity to return to baseline levels before the next trial begins.</li>
		</ol>
		</li>
		<li>Use either audio (Experiment 131) or visual (Experiment 232) cues to ensure that touch is delivered at the appropriate velocity.
		<ol>
			<li>To use audio cues, have cues delivered to headphones worn by the experimenter to track the pace of the stimulation using a metronome. Distinguish velocities using tones of differing pitches (or other distinguishing audio cue, e.g., a cue saying &#34;10 cm/s&#34;) that precede the stimulation cues.</li>
			<li>To use visual cues, display cues on a tablet only in view of the experimenter. Use a moving bar to track velocity of touch administration.</li>
		</ol>
		</li>
		<li>Prior to the start of the study, practice to ensure that touch is delivered at the appropriate velocity and a consistent pressure. To do so, apply brushstrokes to the scale in a similar manner as to the participant. The scale readout is used to determine if the pressure changes throughout touch administration. For instance, a pressure of 0.4 N would read as 40 g on the scale.</li>
	</ol>
	</li>
	<li>Observed touch task (Experiment 1)
	<ol>
		<li>Ensure that videos of touch administration are of similar length, regardless of velocity.
		<ol>
			<li>Include both CT-optimal (1-10 cm/s) and non-optimal (less than 1 cm/s or more than 10 cm/s) velocities.</li>
		</ol>
		</li>
		<li>Start trials with a fixation cross or other neutral condition followed by video. 
		NOTE: Videos contain touch delivered to CT-rich hairy skin (arm), CT-lacking glabrous skin (palm), and a non-social condition in which touch is delivered to a fake wooden arm (Fig. 2; see supplemental videos).
		<ol>
			<li>After a 1-2 s ITI, obtain self-report ratings.</li>
			<li>Allow another 6-7 ITI following ratings to precede the next trial to allow EMG activity to return to baseline.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
3. Facial Electromyography
<ol>
	<li>Data acquisition and filtering guidelines (based on previous protocols27,34)
	<ol>
		<li>Use software to apply filtering steps either in real-time or offline. Typical filtering steps include a comb band stop filter to filter out potential noise from AC power (50/60 Hz), followed by smoothing and rectification. 
		NOTE: Initial basic filtering steps may be set on EMG amplifiers (e.g., a high pass filter of 10 Hz and a low pass filter of 500 Hz or 1,000 Hz).</li>
	</ol>
	</li>
	<li>Electrode application (based on previous protocols27,34)
	<ol>
		<li>Briefly describe the application process to the participant. Use neutral words (&#34;sensor&#34;) instead of potentially anxiety-evoking words (&#34;electrode&#34;)34.
		<ol>
			<li>Decide what information to tell the participants regarding the purpose of the sensors. 
			NOTE: In the current studies, participants were told sensors would measure muscle and sweat activity during the session.</li>
		</ol>
		</li>
		<li>Clean the participants&#39; skin prior to electrode application.
		<ol>
			<li>Use water to wipe clean the areas in which sensors will be applied.</li>
			<li>Use an exfoliant scrub to lightly abrade the same areas. Use caution to prevent major skin irritation, though minor irritation is likely to occur.</li>
		</ol>
		</li>
		<li>Use electrode pairs consisting of two 4 mm shielded bipolar recording electrodes plus one monopolar reference electrode.
		<ol>
			<li>Apply adhesive collars to the electrodes such that they adhere to the skin.</li>
			<li>Once collars adhere to the outer rim of the electrodes, fill sensors with a conductive electrode gel, taking care to prevent the formation of air bubbles.</li>
		</ol>
		</li>
		<li>Place electrode pairs parallel to the muscle(s) of interest and perpendicular to potential sources of noise, such as other muscles34.
		<ol>
			<li>Corrugator: Affix one electrode directly above the eyebrow along an imaginary vertical line that traverses the inner corner of the eye. Place the second electrode 1 cm lateral and slightly superior to the first, along the border of the eyebrow.</li>
			<li>Zygomatic: Place the first sensor midway along an imaginary line that connects the upper ear (where the ear meets the skull) and the corner of the mouth. Place the second electrode 1 cm medial (towards the mouth). Take care to avoid the masseter muscle.</li>
			<li>Use an 8 mm unshielded, monopolar recording electrode as a reference electrode. Place the electrode in the middle of the forehead, equidistant (above) the inner brows and (below) the hairline.</li>
			<li>Ensure that electrode wires are placed such that they do not impede vision. Use medical tape to ensure long-term adherence of the electrodes to skin and reduce noise/artifacts due to cord movement.</li>
		</ol>
		</li>
		<li>Determine the quality of electrode application with an impedance monitor. Acceptable impedance levels are below 20 k&#8486;. If electrodes need to be reapplied to reach appropriate impedance levels, use a clean pair of electrodes.</li>
	</ol>
	</li>
</ol>
4. Task Procedure
<ol>
	<li>General order
	<ol>
		<li>Following sensor application, complete task(s). If using more than one task, counterbalance order across participants.</li>
		<li>Ensure that participants are seated comfortably to minimize extraneous movement that may introduce movement artifacts34.</li>
	</ol>
	</li>
	<li>Experienced touch task
	<ol>
		<li>Seat participants in front of computer with the to-be-touched arm extended laterally, resting comfortably (e.g., on a cushion). 
		NOTE: It is recommended to apply touch to the arm that is not being used for self-reported ratings in order to minimize potential movement artifacts in the EMG signal.</li>
		<li>Occlude view of the arm from the participant either using a curtain separator31 or goggles that occlude lateral vision (Figure 132) 35.</li>
		<li>Instruct the participant to focus on how the touch makes them feel.</li>
		<li>Vary touch location to avoid CT fatigue36.</li>
		<li>Administer touch using a 75 mm goat hair brush applied to designated section(s) marked on the arm (and palm). Alternatively, apply touch using a force-controlled robot37.</li>
		<li>Use consistent touch administration direction, e.g., back-and-forth (distal-to-proximal, then proximal to distal) or single direction (proximal-to-distal only)</li>
	</ol>
	</li>
	<li>Observed touch task
	<ol>
		<li>Seat participant in front of the computer that will display the videos.</li>
		<li>Instruct the participant that they will have to rate how the video made them feel.</li>
		<li>Ensure that the participant is out of view of the experimenter34.</li>
	</ol>
	</li>
</ol>
5. Data Cleaning and Analysis
<ol>
	<li>To assess the mean EMG activation to a specific touch stimulus type, compare the response to the touch stimulus to the preceding baseline, i.e. [mean activation during 6 s touch stimulation] - [mean activation during 1 s prestimulus &#34;baseline&#34;], as suggested by Fridlund and Cacioppo34.
	<ol>
		<li>Average responses for each touch stimulus type (CT-optimal, non-optimal and, if appropriate, each location (arm/palm).</li>
		<li>Do this for each muscle (corrugator, zygomatic) and self-report rating (pleasantness, intensity) individually.</li>
	</ol>
	</li>
	<li>To obtain a more sensitive time course, compute mean EMG activation during smaller time intervals (e.g., 700 ms; see Figure 532). Subtract the same 1 s baseline from all intervals to remove baseline EMG activity. 
	NOTE: Prior to analysis, it is recommended to have data manually checked by raters blinded to touch conditions to eliminate trials with artifactual activations34.</li>
</ol>

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C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=C-tactile+afferent+stimulating+touch+carries+a+positive+affective+value.">C-tactile afferent stimulating touch carries a positive affective value.</a> PloS One. 12 (3), 0173457 (2017).</li><li>Scheele, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+oxytocin-induced+facilitation+of+neural+and+emotional+responses+to+social+touch+correlates+inversely+with+autism+traits.">An oxytocin-induced facilitation of neural and emotional responses to social touch correlates inversely with autism traits.</a> Neuropsychopharmacology. 39 (9), 2078-2085 (2014).</li><li>Ackerley, R., Saar, K., McGlone, F., Backlund Wasling, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantifying+the+sensory+and+emotional+perception+of+touch:+differences+between+glabrous+and+hairy+skin.">Quantifying the sensory and emotional perception of touch: differences between glabrous and hairy skin.</a> Frontiers in Behavioral Neuroscience. 8 (34), (2014).</li><li>Loken, L. S., Evert, M., Wessberg, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pleasantness+of+touch+in+human+glabrous+and+hairy+skin:+order+effects+on+affective+ratings.">Pleasantness of touch in human glabrous and hairy skin: order effects on affective ratings.</a> Brain Research. 1417, 9-15 (2011).</li></ol>

The authors have nothing to disclose

Here, we report on the use of facial electromyography (EMG) as a method to study affective responses to observed and experienced touch. Previously, many studies have focused on the use of self-report ratings to characterize the affective quality of touch. Touch that optimally activates CT afferents (e.g., 1-10 cm/s) is consistently rated as more pleasant than either faster or slower touch velocities10. In contrast, ratings of intensity seem to track with velocity, with faster touch velocities rated as more intense, likely mediated via A&#946; fibers37. Using two separate datasets, we show that both fast and slow non-optimal touch elicit robust corrugator reactivity that is attenuated during CT-optimal touch. Thus, we find that touch that is rated as less pleasant (e.g., non-optimal touch) also increases corrugator activity, suggestive of enhanced negative affect. In addition, we find that responses are similar across modalities. That is, both observed and experienced touch elicit similar facial muscle activity. In both modalities, these effects were only significant for touch to the arm, and not the palm or a wooden arm. Thus, while self-reported ratings of experienced and observed affective touch are similar regardless of location (arm, palm), facial EMG only significantly differentiates between touch velocities applied to the CT-rich arm, and not the CT-fiber-lacking palm.
The results further show that the temporal sensitivity of facial EMG yields insight into emotional processing that cannot be obtained solely by self-report. Namely, we found that corrugator reactivity to CT-optimal touch becomes evident at a timescale that coincides with known conduction velocities of CT afferents1,12. Thus, in the initial 700 ms of touch, which are believed to be dominated by A&#946; activation, there is no difference in EMG activation between the two touch velocities. However, the distinction between CT-optimal and non-optimal touch becomes evident following the first 700 ms, consistent with the previously reported temporal time lag of CT-afferents2,12. Hence, facial EMG is able to detect changes in affective responses to touch that occur with a temporal specificity that is likely inaccessible via verbal reporting.
Across both studies, we find that CT-optimal and non-optimal touch can be distinguished via corrugator activity. However, we did not find an effect of touch on zygomatic reactivity, which is in contrast to previous reports40. One potential reason for the discrepancies between the current data and previous findings include methodological differences such as inclusion of a post-touch period in the analysis. Thus, we stress the importance of methodological considerations such as the length of the touch stimulation and inter-trial intervals when designing these experiments.
There are several factors that should be considered when assessing affective reactions to touch. One potential area of concern is the gender of the experimenter (and thus, toucher) to that of the participant, as well as the relationship, if any, between the two41. Moreover, one should ensure that participants are precluded from viewing the experimenter and touch application, as visual processing of touch can influence the perception of touch35,39. There are also concerns to weigh during task design. For instance, it is important to consider the potential for order effects, both in regards to touch stimuli presentation (e.g. discussed in42) or touch location43. If several touch repetitions are used, one may want to vary touch location to avoid CT fatigue36. Here, we used a brush to apply touch to compare to previous studies17, though it is possible that EMG responses may be different using more ecologically valid methods (e.g., touch by hand).
While we believe the use of facial EMG will be of a great benefit to the field of affective touch, there are limitations to this methodology that warrant consideration. Training is required to learn how to apply the electrodes correctly, producing an increased burden on the experimenter on the outset of experimental planning. Excessive movement, talking, or other environmental factors present during the experiment may cause artifacts in the EMG signal, thus constraining some experimental design features. Moreover, the application of electrodes to the face may elicit an attempt to discern the purpose of the study. As such, one must consider what information to tell the participant regarding not only the purpose of the experiment, but also the use of the electrodes during the experiment. In the current experiments, the participants were told that the purpose of the study was the investigate decision-making and perceptions of various sensations32 or reactions to social interactions31. In both cases, participants were told that the electrodes would measure sweat and muscle activity and were fully debriefed following the conclusion of the experiment. These concerns and others are addressed thoroughly in Fridlund and Cacioppo 198634.
In sum, we demonstrate that facial EMG is a reliable, robust, and informative method to assess the affective valence of tactile stimulation. This method provides a means to implicitly assess responses to tactile stimulation independent of verbal reports, paving the way for studies in infants and young children, cross-cultural comparisons, investigations of clinical conditions, and other situations in which semantics and language may otherwise preclude scientific exploration.

C-tactile (CT) afferents are proposed to convey the affective component of touch, which can be distinguished from the discriminative aspects of touch processed via A&#946; fibers1,2. CT-mediated affective touch is believed to play an integral role in social affiliative behaviors3, leading to the &#34;skin as a social organ&#34; hypothesis4. Physical5,6, developmental7, and psychiatric8,9 factors can influence CT-mediated touch processing. Thus, establishing an objective measure to quantify affective reactions to CT-relevant touch is critical to allow for comparisons across populations.
In recent years, much insight has been gained regarding the characteristics of CT afferents. These unmyelinated afferents demonstrate an inverted U-shaped firing frequency, with velocities of 1-10 cm/s (&#34;CT-optimal&#34;) eliciting the greatest frequency and both greater (&#34;fast non-optimal&#34;) or lesser (&#34;slow non-optimal&#34;) velocities eliciting reduced firing10. CT firing frequency correlates with self-reported ratings of touch &#34;pleasantness&#34;, producing a similar inverted U-shaped curve in pleasantness ratings10. Moreover, CT-afferents also respond most robustly to stimuli close to skin temperature11. These fibers also show distinct conduction speeds. The unmyelinated CT afferents are slower2 and thus the volley of afferent input to the cortex shows a temporal lag when compared to the speed of the faster, myelinated A&#946; fibers1,12. Affective and discriminative touch can also be distinguished on a neural level. While both types of touch activate overlapping somatosensory areas, affective touch is more likely to activate the posterior insula, while discriminative touch activates sensorimotor areas13,14,15,16. This activation pattern is consistent whether the touch is directly experienced or merely observed17, suggesting that affective touch is not just a &#34;bottom-up&#34; process driven by physical activation of CT afferents, but also involves &#34;top-down&#34; integration of multimodal sensory processing.
Situations in which CT processing is deficient or otherwise atypical has also provided insight into the functional significance of these afferents. In a unique patient group with a heritable mutation affecting the nerve growth factor &#946; gene, there is a reduction in the density of thin and unmyelinated nerve fibers, including CT afferents. Compared to healthy controls, these patients report touch at CT-optimal velocities as less pleasant5. The converse scenario is also true; patients who lack myelinated A&#946; fibers are able to retain a faint sensation of pleasant touch carried by the still intact CT afferents6. Abnormal affective touch processing is not just confined to instances of physical changes in CT-afferents. Across patient and healthy populations, those higher on the spectrum of autistic traits reported reduced pleasantness ratings of touch8. Psychiatric patients also demonstrate reduced hedonic ratings of affective touch, with a history of childhood maltreatment as one of the most consistent predictors of dysregulated affective touch awareness8. Dysregulation in the CT-based affective touch system in anorexia nervosa has also been reported9. Thus, both physical and psychological factors can influence affective touch processing, and as such, it is imperative to establish methodologies that can be applied to all individuals in an equitable and comparable manner.
Insights into normo-typical and dysregulated affective processing have the opportunity to provide a more nuanced picture of many patient groups. However, one potential limitation of affective touch research is the necessity of self-reported ratings. At times, self-report can be unreliable18 and subject to recall bias19. Inquiries of self-report can psychologically remove a participant from the current setting, limiting the ecological validity of the responses and removing them temporally from the experience20. Moreover, self-report relies on a firm understanding of language and semantics, making cross-cultural and developmentally diverse (e.g. infant and toddler-aged individuals) comparisons challenging. For instance, individuals with an autism spectrum diagnosis frequently show distinct behavioral responses to touch21, but can also have difficulties in communicating verbally22. Thus, finding non-invasive methods to measure responses to touch that circumvent a reliance on self-report may translate, at least, to a better understanding of the mechanisms of affective touch, and at most, novel insights into dysregulation of social processing in patient populations.
Facial electromyography (EMG) is a suitable candidate to objectively assess affective responses to touch. It has been used to measure valence-specific reactions to visual23, audio-visual24, olfactory25, and gustatory26 stimuli. Facial EMG is a safe and non-invasive method consisting of surface electrodes that adhere to the face27. These surface electrodes record facial muscle activity continuously in real-time with time scale sensitivity in the tens of milliseconds. Of particular interest is the corrugator supercilii (&#34;corrugator&#34;), which is activated when furrowing the brow and relaxes during a smile. As a result, corrugator activity has a linear relationship with affective valence, with increased response to negative stimuli and decreased activity in response to positive stimuli28. In addition, the zygomaticus major (&#34;zygomatic&#34;) is the muscle activated as the corners of the mouth pull up into a smile. The zygomatic displays a &#34;J-shaped&#34; activation pattern with positive stimuli eliciting the greatest response, and the most negative stimuli eliciting a greater response than neutral stimuli28. Facial EMG recordings of these muscles can even be observed when stimuli are presented outside conscious awareness or when individuals are explicitly trying to suppress their reactions29,30. Importantly, facial EMG can be used alone or in combination with self-report ratings or other physiological recordings. Thus, it is an ideal methodology to assess affective reactions to tactile stimulation31,32.
In sum, facial EMG can be combined with self-report ratings to determine how CT-optimal tactile stimulation influences facial muscle activity as a potential indicator of affective response. One can take advantage of the velocity-dependent firing frequency of CTs to apply touch at CT-optimal and non-optimal velocities, and touch can be applied both to the CT-rich arm and the putatively CT-lacking palm. Comparisons can be made across modalities to determine whether affective responses to touch require direct stimulation or can be elicited via mere observation, suggestive of shared processing across sensory modalities. Finally, upon establishing facial EMG as a suitable methodology to study affective reactions to affective touch, researchers can then explore how affective touch processing may be influenced by various interventions (e.g., drug administration; stress exposure), how it changes throughout development7, how it is influenced by the relationship of the interactants33, and whether it is dysregulated in clinical populations8.

<table border="0" cellpadding="0" cellspacing="0" style="width:1149px;" width="1148">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">4mm Ag-AgCl sheilded reusable electrodes</td>
			<td style="width:189px;">Biopac</td>
			<td style="width:177px;">EL654</td>
			<td style="width:477px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">75mm goat hair brush</td>
			<td style="width:189px;">IN-EX Color AB</td>
			<td>77062</td>
			<td>Touch application; https://www.in-exfarg.se</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">8mm Ag-AgCl unsheilded reusable electrode</td>
			<td style="width:189px;">Biopac</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">Acqknowledge software</td>
			<td style="width:189px;">Biopac</td>
			<td>ACK100W</td>
			<td>Used for application of filtering steps, analysis</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">Adhesive collars</td>
			<td style="width:189px;">Biopac</td>
			<td style="width:177px;">ADD204</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">Cables</td>
			<td style="width:189px;">Biopac</td>
			<td style="width:177px;">BN-EL30-LEAD3; LEAD2</td>
			<td>LEAD3 includes ground, LEAD2 is only bipolar recording electrodes</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">Electro-gel</td>
			<td style="width:189px;">Biopac</td>
			<td style="width:177px;">GEL100</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">EMG aplifier x 2</td>
			<td style="width:189px;">Biopac</td>
			<td style="width:177px;">BN-EMG2</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">El-Prep</td>
			<td style="width:189px;">Biopac</td>
			<td style="width:177px;">ELPREP</td>
			<td style="width:477px;">Facial exfoliant</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">MP160 data acqusition system</td>
			<td style="width:189px;">Biopac</td>
			<td>MP160WSW</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:305px;">Presentation software</td>
			<td style="width:189px;">Neurobehavioral systems</td>
			<td style="width:177px;"></td>
			<td>Task presentation software</td>
		</tr>
	</tbody>
</table>

using facial electromyography to assess facial muscle reactions to experienced and observed affective touch in humans

"Affective" touch is believed to be processed in a manner distinct from discriminatory touch and to involve activation of C-tactile (CT) afferent fibers. Touch that optimally activates CT fibers is consistently rated as hedonically pleasant. Patient groups with impaired social-emotional functioning also show disordered affective touch ratings. However, relying on self-reported ratings of touch has many limitations, including recall bias and communication barriers. Here, we describe a methodological approach to study affective responses to touch via facial electromyography (EMG) that circumvents the reliance on self-report ratings. Facial EMG is an objective, quantitative, and non-invasive method to measure facial muscle activity indicative of affective responses. Responses can be assessed across healthy and patient populations without the need for verbal communication. Here, we provide two separate datasets demonstrating that CT-optimal and non-optimal touch elicit distinct facial muscle reactions. Moreover, facial EMG responses are consistent across stimulus modalities, e.g. tactile (experienced touch) and visual (observed touch). Finally, the temporal resolution of facial EMG can detect responses on timescales that supersede that of verbal reporting. Together, our data suggest that facial EMG is a suitable methodology for use in affective tactile research that can be used to supplement, or in some cases, supplant, existing measures.

CT-optimal touch elicits distinct EMG responses compared to fast non-optimal touch across modalities 
The first experiment addressed whether differential EMG reactivity could be detected in response to CT-optimal (3 cm/s) and fast non-optimal (30 cm/s) tactile stimulation that was directly experienced (Figure 3) or merely observed (Figure 2 and Figure 3)31.
Experienced CT-optimal touch was rated as more pleasant than non-optimal touch (F(1,28) = 32.2; p &#60; 0.001; Figure 3A) regardless of touch location (p = 0.063; velocity x location: p = 0.32). Similarly, observed CT-optimal touch was rated as more pleasant that non-optimal touch (touch velocity: F(1,28) = 47.5; p &#60; 0.001; touch type: F(2,56) = 6.09, p = 0.004; type x velocity interaction F(2,56) = 5.87, p = 0.005). CT-optimal touch to the arm was rated as more pleasant than touch to the palm (p = 0.024) and non-social touch (e.g., touch to the wooden arm; p = 0.001). Fast non-optimal touch was always rated as more intense (Figure 3B), regardless of whether the touch was experienced (touch velocity: F(1,28) = 34.3, p &#60; 0.001; touch location: p = 0.28; velocity x location interaction: p = 0.64) or observed (touch velocity: F(1,28) = 35.1, p &#60; 0.001; touch type: p = 0.40; velocity x type interaction: p = 0.39).
Experienced fast, non-optimal touch elicited robust corrugator reactivity that was mitigated by recruitment of CT-afferents during CT-optimal touch (effect of touch velocity: F(1,28) = 4.84, p = 0.036; effect of touch location: p = 0.93; touch velocity x location interaction: p = 0.42; Figure 3C). Corrugator response significantly differed between CT-optimal and non-optimal touch for touch to the arm (p = 0.050) but only trend level effects were seen for touch to the palm (p = 0.092). There was no main effect of touch velocity (p = 0.11) or type (p = 0.79) on corrugator reactivity to observed touch, but there was a touch velocity x type interaction (F(2,56) = 3.80, p = 0.028). Post hoc tests revealed that fast non-optimal touch elicited greater corrugator reactivity than CT-optimal touch particularly for videos of touch to the arm (p = 0.007), but not touch to the palm (p = 0.13) or non-social touch (p = 0.25). Zygomatic activity was not significantly affected by experienced touch (effect of touch velocity: p = 0.15; effect of touch type: p = 0.73; touch velocity x type interaction: p = 0.63; Figure 3D), nor observed touch (main effect of touch velocity: p = 0.37; main effect of touch type: p = 0.84; touch velocity x type interaction: p = 0.23).
CT-optimal touch elicits EMG responses distinct from slow non-optimal touch 
Experiment 2 assessed whether slow non-optimal (0.3 cm/s) would elicit similar responses as fast non-optimal (30 cm/s)32. We found that slow non-optimal touch was rated as less pleasant (Figure 4A) and less intense (Figure 4B) than CT-optimal touch. Similar to fast non-optimal touch, slow non-optimal touch elicited robust corrugator activitythat was attenuated by CT-optimal touch (effect of touch velocity: F(1,83) = 9.723, p = 0.002; Figure 4C). There was no effect of touch on zygomatic activity (p&#160;= 0.35; Figure 4D).
We next assessed the time course of EMG responses. During the first 700 ms, a window putatively free of CT input, there was no difference in corrugator reactivity (-0.031 &#177; 0.06 &#181;V and -0.017 &#177; 0.49 &#181;V, pBon = 0.98; Figure 5A). However, over the next 5.6 s, corrugator reactivity in response to CT optimal touch decreased gradually, whereas it gradually increased in response to slow non-optimal touch: during interval 2, the corrugator reactivity was marginally lower for CT optimal touch than non-optimal touch (pBon = 0.071). During intervals 3, 5, 6, 7 and 8, the corrugator reactivity was significantly lower during CT optimal touch than during non-optimal touch (pBon &#60; 0.034; Figure 5A). This pattern was absent in analysis of zygomatic reactivity (p = 0.83; Figure 5B).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59228/59228fig1.jpg" /> 
Figure 1: Example of experimental setup for the Experienced Touch task. Seat the participant in front of the computer with their arm extended laterally, comfortably resting on a cushion. If obtaining self-report ratings, it is recommended to apply touch to the arm that is not used to provide ratings to avoid potential movement artifacts from contaminating the EMG signal. The arm should be occluded from view of the participant35,39, either with customized glasses, as above, or using a curtain separator. This figure is adapted from Ree et al.32 <a href="https://www.jove.com/files/ftp_upload/59228/59228fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/59228/59228fig2.jpg" /> 
Figure 2: Example of touch stimuli used in the Observed Touch task. The observed touch task included 6 s videos of touch to the (A) CT-rich arm, (B) CT-lacking palm, and (C) non-social touch to a wooden arm. <a href="https://www.jove.com/files/ftp_upload/59228/59228fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/59228/59228fig3.jpg" /> 
Figure 3: CT-optimal touch elicits distinct responses compared to fast non-optimal touch across modalities. (A) CT-optimal touch (3 cm/s) is consistently rated as more pleasant than fast non-optimal touch (30 cm/s) across both tasks. Experienced touch is rated as most pleasant, followed by social (arm, palm) observed touch, then non-social touch (e.g. touch to a wooden arm). (B) CT-optimal touch is (3 cm/s) rated as less intense across modalities, regardless of modality or social content. (C) Fast non-optimal touch (30 cm/s) elicits more corrugator reactivity than CT-optimal touch (3 cm/s). This difference is most robust for touch to the CT-rich arm. (D) CT-optimal touch (3 cm/s) marginally increases zygomatic reactivity, though this does not reach significance for any modality or location. Bars and errors bars represent mean and standard error of the mean; *p &#60; 0.05 effect of velocity. This figure is adapted from Mayo et al.31 <a href="https://www.jove.com/files/ftp_upload/59228/59228fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/59228/59228fig4.jpg" /> 
Figure 4: CT-optimal touch (3 cm/s) elicits distinct responses as compared to slow non-optimal touch (0.3 cm/s). (A) CT-optimal touch (3 cm/s) is rated as more pleasant than slow non-optimal touch (0.3 cm/s). (B) CT-optimal touch (3 cm/s) is rated as more intense than slow non-optimal touch (0.3 cm/s). (C) Mean corrugator reactivity in response to CT-optimal (3 cm/s) is reduced compared to slow non-optimal (0.3 cm/s). (D) Touch does not significantly influence zygomatic reactivity. Bars and error bars represent means and standard error of the mean; *p &#60; 0.05. This figure is adapted from Ree et al.32 <a href="https://www.jove.com/files/ftp_upload/59228/59228fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/59228/59228fig5.jpg" /> 
Figure 5: Corrugator responses to CT-optimal touch are temporally specific. (A) When binned in intervals of 700 ms, CT-optimal touch elicits significantly less corrugator reactivity. The exception is in the first 700 ms, which is putatively free of CT input due to the slower conduction velocity of these unmyelinated afferents. (B) Zygomatic reactivity is not significantly different in response to optimal or slow non-optimal touch at any of the time points. Dots represent means and bars represent standard errors of the mean. This figure is adapted from Ree et al.32 <a href="https://www.jove.com/files/ftp_upload/59228/59228fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Table 1" src="/files/ftp_upload/59228/59228table1.jpg" /> 
Table 1: Summary of Experimental Designs. In the Experienced Touch task of Experiment 1, touch was delivered at CT-optimal (3 cm/s) or fast non-optimal (30 cm/s) velocities to hairy (arm) and glabrous (palm) skin. The Observed Touch instead included videos of touch delivered to the arm, palm, or to a wooden arm (e.g., non-social) at the same touch velocities. The &#34;non-social&#34; condition was included to control for potential responses elicited by low-level periodicity information encoded in the movement17, and determine the relevance of social content38 on ratings and EMG responses. Results were analyzed using repeated measures analysis of variance (ANOVA) with touch velocity and touch type as within-subjects factors. A post-hoc power analysis based on Experiment 1 suggests at least 22 individuals should be included to achieve similar effects. In Experiment 2, touch was delivered to the arm at CT-optimal (3 cm/s) or slow non-optimal (0.3 cm/s) velocities. Touch was delivered for a total of 2min, but here we only report on the first 6.3 s in order to compare results to Experiment 1. Each velocity was repeated twice. In all experiments, self-reported ratings of the affective quality (e.g., pleasantness) and discriminative aspects (e.g., intensity) were assessed10.

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Using Facial Electromyography to Assess Facial Muscle Reactions to Experienced and Observed Affective Touch in Humans

We describe a protocol to assess facial muscle activity in response to experienced and observed tactile stimulation using facial electromyography.

"Affective" touch is believed to be processed in a manner distinct from discriminatory touch and to involve activation of C-tactile (CT) afferent fibers. ...

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11.0K Views.  University of Oslo. We describe a protocol to assess facial muscle activity in response to experienced and observed tactile stimulation using facial electromyography.

Video: Using Facial Electromyography to Assess Facial Muscle Reactions to Experienced and Observed Affective Touch in Humans

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach

The main goal of this study was to assess the usability of a tablet-computer-based application (EmoCogMeter) in investigating the effects of age on cognitive functions across the lifespan in a sample of 378 healthy subjects (age range 18-89 years). Consistent with previous findings we found an age-related cognitive decline across a wide range of neuropsychological domains (memory, attention, executive functions), thereby proving the usability of our tablet-based application. Regardless of prior computer experience, subjects of all age groups were able to perform the tasks without instruction or feedback from an experimenter. Increased motivation and compliance proved to be beneficial for task performance, thereby potentially increasing the validity of the results. Our promising findings underline the great clinical and practical potential of a tablet-based application for detection and monitoring of cognitive dysfunction.

We tested the usability of a tablet-computer-based application (EmoCogMeter) in investigating the effects of age on cognition. Results show an age-related cognitive decline, thereby proving the usability of our application. Findings underline the great clinical and practical potential of a tablet-based application for detection and monitoring of cognitive dysfunction.

The main goal of this study was to assess the usability of a tablet-computer-based application (EmoCogMeter) in investigating the effects of age on ...

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.

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 ...

Uncovering Beat Deafness: Detecting Rhythm Disorders with Synchronized Finger Tapping and Perceptual Timing Tasks

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here with the goal of uncovering rhythm disorders, such as beat deafness. Beat deafness is characterized by poor performance in perceiving durations in auditory rhythmic patterns or poor synchronization of movement with auditory rhythms (e.g., with musical beats). These tasks include the synchronization of finger tapping to the beat of simple and complex auditory stimuli and the detection of rhythmic irregularities (anisochrony detection task) embedded in the same stimuli. These tests, which are easy to administer, include an assessment of both perceptual and sensorimotor timing abilities under different conditions (e.g., beat rates and types of auditory material) and are based on the same auditory stimuli, ranging from a simple metronome to a complex musical excerpt. The analysis of synchronized tapping data is performed with circular statistics, which provide reliable measures of synchronization accuracy (e.g., the difference between the timing of the taps and the timing of the pacing stimuli) and consistency. Circular statistics on tapping data are particularly well-suited for detecting individual differences in the general population. Synchronized tapping and anisochrony detection are sensitive measures for identifying profiles of rhythm disorders and have been used with success to uncover cases of poor synchronization with spared perceptual timing. This systematic assessment of perceptual and sensorimotor timing can be extended to populations of patients with brain damage, neurodegenerative diseases (e.g., Parkinson&#8217;s disease), and developmental disorders (e.g., Attention Deficit Hyperactivity Disorder).

Behavioral tasks that allow for the assessment of perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) are presented. Synchronization of finger tapping to the beat of an auditory stimuli and detecting rhythmic irregularities provides a means of uncovering rhythm disorders.

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here ...

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat

Fear of certain threat and anxiety about uncertain threat are distinct emotions with unique behavioral, cognitive-attentional, and neuroanatomical components. Both anxiety and fear can be studied in the laboratory by measuring the potentiation of the startle reflex. The startle reflex is a defensive reflex that is potentiated when an organism is threatened and the need for defense is high. The startle reflex is assessed via electromyography (EMG) in the orbicularis oculi muscle elicited by brief, intense, bursts of acoustic white noise (i.e., &#8220;startle probes&#8221;). Startle potentiation is calculated as the increase in startle response magnitude during presentation of sets of visual threat cues that signal delivery of mild electric shock relative to sets of matched cues that signal the absence of shock (no-threat cues). In the Threat Probability Task, fear is measured via startle potentiation to high probability (100% cue-contingent shock; certain) threat cues whereas anxiety is measured via startle potentiation to low probability (20% cue-contingent shock; uncertain) threat cues. Measurement of startle potentiation during the Threat Probability Task provides an objective and easily implemented alternative to assessment of negative affect via self-report or other methods (e.g., neuroimaging) that may be inappropriate or impractical for some researchers. Startle potentiation has been studied rigorously in both animals (e.g., rodents, non-human primates) and humans which facilitates animal-to-human translational research. Startle potentiation during certain and uncertain threat provides an objective measure of negative affective and distinct emotional states (fear, anxiety) to use in research on psychopathology, substance use/abuse and broadly in affective science. As such, it has been used extensively by clinical scientists interested in psychopathology etiology and by affective scientists interested in individual differences in emotion.

Potentiation of the startle reflex is measured via electromyography of the orbicularis oculi muscle during low (uncertain) and high (certain) probability electric shock threat in the Threat Probability Task. This provides an objective measure of distinct negative emotional states (fear/anxiety) for research on psychopathology, substance use/abuse, and broad affective science.

Fear of certain threat and anxiety about uncertain threat are distinct emotions with unique behavioral, cognitive-attentional, and neuroanatomical ...

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

The paradigm detailed in this manuscript describes an applied experimental method based on real police investigations during which an eyewitness or victim to a crime may create from memory a holistic facial composite of the culprit with the assistance of a police operator. The aim is that the composite is recognized by someone who believes that they know the culprit. For this paradigm, participants view a culprit actor on video and following a delay, participant-witnesses construct a holistic system facial composite. Controls do not construct a composite. From a series of arrays of computer-generated, but realistic faces, the holistic system construction method primarily requires participant-witnesses to select the facial images most closely meeting their memory of the culprit. Variation between faces in successive arrays is reduced until ideally the final image possesses a close likeness to the culprit. Participant-witness directed tools can also alter facial features, configurations between features and holistic properties (e.g., age, distinctiveness, skin tone), all within a whole face context. The procedure is designed to closely match the holistic manner by which humans&#8217; process faces. On completion, based on their memory of the culprit, ratings of composite-culprit similarity are collected from the participant-witnesses. Similar ratings are collected from culprit-acquaintance assessors, as a marker of composite recognition likelihood. Following a further delay, all participants &#8212; including the controls&#160;&#8212; attempt to identify the culprit in either a culprit-present or culprit-absent video line-up, to replicate circumstances in which the police have located the correct culprit, or an innocent suspect. Data of control and participant-witness line-up outcomes are presented, demonstrating the positive influence of holistic composite construction on identification accuracy. Correlational analyses are conducted to measure the relationship between assessor and participant-witness composite-culprit similarity ratings, delay, identification accuracy, and confidence to examine which factors influence video line-up outcomes.

This applied experimental paradigm replicates circumstances by which an eyewitness to a real crime may create a holistic facial composite of the culprit from memory, and then attempt to identify the culprit from a video line-up containing the culprit or one in which he or she is not present.

The paradigm detailed in this manuscript describes an applied experimental method based on real police investigations during which an eyewitness or victim ...

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 ...

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

We demonstrate a method for capturing emotional response to beverages and liquefied foods in a sensory evaluation laboratory using automated facial expression analysis (AFEA) software. Additionally, we demonstrate a method for extracting relevant emotional data output and plotting the emotional response of a population over a specified time frame. By time pairing each participant's treatment response to a control stimulus (baseline), the overall emotional response over time and across multiple participants can be quantified. AFEA is a prospective analytical tool for assessing unbiased response to food and beverages. At present, most research has mainly focused on beverages. Methodologies and analyses have not yet been standardized for the application of AFEA to beverages and foods; however, a consistent standard methodology is needed. Optimizing video capture procedures and resulting video quality aids in a successful collection of emotional response to foods. Furthermore, the methodology of data analysis is novel for extracting the pertinent data relevant to the emotional response. The combinations of video capture optimization and data analysis will aid in standardizing the protocol for automated facial expression analysis and interpretation of emotional response data.

A protocol for capturing and statistically analyzing emotional response of a population to beverages and liquefied foods in a sensory evaluation laboratory using automated facial expression analysis software is described.

We demonstrate a method for capturing emotional response to beverages and liquefied foods in a sensory evaluation laboratory using automated facial ...

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 ...

Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans

Prehension, the act of reaching to grasp an object, is central to the human experience. We use it to feed ourselves, groom ourselves, and manipulate objects and tools in our environment. Such behaviors are impaired by many sensorimotor disorders, yet our current understanding of their neural control is far from complete. Current technologies for investigating human reach-to-grasp movements often utilize motion tracking systems that can be expensive, require the attachment of markers or sensors to the hands, impede natural movement and sensory feedback, and provide kinematic output that can be difficult to interpret. While generally effective for studying the stereotypical reach-to-grasp movements of healthy sighted adults, many of these technologies face additional limitations when attempting to study the unpredictable and idiosyncratic reach-to-grasp movements of young infants, unsighted adults, and patients with neurological disorders. Thus, we present a novel, inexpensive, and highly reliable yet flexible protocol for quantifying the temporal and kinematic structure of idiosyncratic reach-to-grasp movements in humans. High speed video cameras capture multiple views of the reach-to-grasp movement. Frame-by-frame video analysis is then used to document the timing and magnitude of pre-defined behavioral events such as movement start, collection, maximum height, peak aperture, first contact, and final grasp. The temporal structure of the movement is reconstructed by documenting the relative frame number of each event while the kinematic structure of the hand is quantified using the ruler or measure function in photo editing software to calibrate 2 dimensional linear distances between two body parts or between a body part and the target. Frame-by-frame video analysis can provide a quantitative and comprehensive description of idiosyncratic reach-to-grasp movements and will enable researchers to expand their area of investigation to include a greater range of naturalistic prehensile behaviors, guided by a wider variety of sensory modalities, in both healthy and clinical populations.

This protocol describes how to use frame-by-frame video analysis to quantify idiosyncratic reach-to-grasp movements in humans. A comparative analysis of reaching in sighted versus unsighted healthy adults is used to demonstrate the technique, but the method can also be applied to the study of developmental and clinical populations.

Prehension, the act of reaching to grasp an object, is central to the human experience. We use it to feed ourselves, groom ourselves, and manipulate ...

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

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

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

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