This work was funded by NIH/NINDS R01 NS114046 to BAP.

This protocol was approved for human subjects&#39; research by the Institutional Review Board of Washington University School of Medicine. All participants gave informed consent.
1. Equipment construction
NOTE: This process will produce the equipment shown in Figure 1&#160;using the supplies listed in the Table of Materials.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66919/66919fig1v2.jpg" /> 
Figure 1: BBT equipment. The top-down view of the table is of the participant at the bottom and the experimenter at the top. To set up the study, tape down the green baseplate and then (A) place the posterboard on the table, (B) place bricks in posterboard cutouts (tape measure included for scale), and (C) remove the posterboard. <a href="https://www.jove.com/files/ftp_upload/66919/66919fig1v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol>
	<li>Build the 4 models shown in Figure 2, each using 1 of the 10 standard bricks listed in Table 1. In the end, 40 more bricks (plus spares) should remain in addition to those included in the models. Glue each model together so that the bricks will stay connected. Label each model with a number on the backside.</li>
</ol>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/66919/66919fig5.jpg" /> 
Figure 2: Suggested models. Sample models; the BBT is robust to changes in model design. (A) Front (participant-facing). (B) Back (experimenter-facing). <a href="https://www.jove.com/files/ftp_upload/66919/66919fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Color</td>
			<td>Color (official)</td>
			<td>Shape</td>
		</tr>
		<tr>
			<td>White</td>
			<td>White</td>
			<td>2x2 square</td>
		</tr>
		<tr>
			<td>Black</td>
			<td>Black</td>
			<td>2x2 square</td>
		</tr>
		<tr>
			<td>Red</td>
			<td>Red</td>
			<td>2x4 rectangle</td>
		</tr>
		<tr>
			<td>Yellow</td>
			<td>Bright Yellow</td>
			<td>2x4 rectangle</td>
		</tr>
		<tr>
			<td>Orange</td>
			<td>Orange</td>
			<td>1x2 rectangle</td>
		</tr>
		<tr>
			<td>Blue</td>
			<td>Dark Azure</td>
			<td>1x2 rectangle</td>
		</tr>
		<tr>
			<td>Maroon</td>
			<td>Dark Red</td>
			<td>1x2 with 45&#176; slope</td>
		</tr>
		<tr>
			<td>Ash</td>
			<td>Medium Stone Gray</td>
			<td>1x2 with 45&#176; slope</td>
		</tr>
		<tr>
			<td>Green</td>
			<td>Dark Green</td>
			<td>2x3 with arch</td>
		</tr>
		<tr>
			<td>Navy</td>
			<td>Dark Blue</td>
			<td>2x2 with 45&#176; slope</td>
		</tr>
	</tbody>
</table>
Table 1: Suggested bricks. Official colors are useful for purchasing but not recommended for experiment labeling because they are long and alphabetically ambiguous. See Table of Materials for product identifiers.
<ol start="2">
	<li>Cut out a baseplate sized 5 inch/12.7 cm with a square notch at the center of a long side of the posterboard.</li>
	<li>Place the bricks on the posterboard at the suggested locations shown in Figure 1&#160;and quantified in Figure 3&#160;and Table 2.</li>
</ol>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/66919/66919fig3v2.jpg" /> 
Figure 3: Schematic of posterboard with suggested brick locations. The BBT is robust to changes in brick locations and orientations. Dashed lines represent quadrants; each quadrant contains 1 brick. Precision = 0.5 cm; Letters = key for Table 2. For suggested orientations, see Figure 1. <a href="https://www.jove.com/files/ftp_upload/66919/66919fig3v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Key</td>
			<td>Quadrant</td>
			<td>Color</td>
			<td>X position (cm)</td>
			<td>Y position (cm)</td>
		</tr>
		<tr>
			<td>A</td>
			<td>Far left</td>
			<td>Orange</td>
			<td>-27.5</td>
			<td>49.5</td>
		</tr>
		<tr>
			<td>B</td>
			<td>Far left</td>
			<td>White</td>
			<td>-21.5</td>
			<td>52</td>
		</tr>
		<tr>
			<td>C</td>
			<td>Far left</td>
			<td>Black</td>
			<td>-12.5</td>
			<td>54.5</td>
		</tr>
		<tr>
			<td>D</td>
			<td>Far left</td>
			<td>Green</td>
			<td>-3.5</td>
			<td>54</td>
		</tr>
		<tr>
			<td>E</td>
			<td>Far right</td>
			<td>Maroon</td>
			<td>9</td>
			<td>54.5</td>
		</tr>
		<tr>
			<td>F</td>
			<td>Far right</td>
			<td>Red</td>
			<td>19</td>
			<td>55</td>
		</tr>
		<tr>
			<td>G</td>
			<td>Far right</td>
			<td>Ash</td>
			<td>26.5</td>
			<td>50.5</td>
		</tr>
		<tr>
			<td>H</td>
			<td>Far left</td>
			<td>Yellow</td>
			<td>-19</td>
			<td>45.5</td>
		</tr>
		<tr>
			<td>I</td>
			<td>Far left</td>
			<td>Blue</td>
			<td>-8.5</td>
			<td>47.5</td>
		</tr>
		<tr>
			<td>J</td>
			<td>Far right</td>
			<td>Orange</td>
			<td>4</td>
			<td>50</td>
		</tr>
		<tr>
			<td>K</td>
			<td>Far right</td>
			<td>Navy</td>
			<td>12.5</td>
			<td>48</td>
		</tr>
		<tr>
			<td>L</td>
			<td>Far right</td>
			<td>Blue</td>
			<td>19.5</td>
			<td>47</td>
		</tr>
		<tr>
			<td>M</td>
			<td>Far left</td>
			<td>Maroon</td>
			<td>-34</td>
			<td>29</td>
		</tr>
		<tr>
			<td>N</td>
			<td>Far left</td>
			<td>Red</td>
			<td>-24</td>
			<td>39</td>
		</tr>
		<tr>
			<td>O</td>
			<td>Far left</td>
			<td>Navy</td>
			<td>-14</td>
			<td>39.5</td>
		</tr>
		<tr>
			<td>P</td>
			<td>Far left</td>
			<td>Ash</td>
			<td>-4.5</td>
			<td>39</td>
		</tr>
		<tr>
			<td>Q</td>
			<td>Far right</td>
			<td>Yellow</td>
			<td>7</td>
			<td>40</td>
		</tr>
		<tr>
			<td>R</td>
			<td>Far right</td>
			<td>Green</td>
			<td>19.5</td>
			<td>40</td>
		</tr>
		<tr>
			<td>S</td>
			<td>Far right</td>
			<td>Black</td>
			<td>26.5</td>
			<td>42.5</td>
		</tr>
		<tr>
			<td>T</td>
			<td>Far right</td>
			<td>White</td>
			<td>34.5</td>
			<td>40.5</td>
		</tr>
		<tr>
			<td>U</td>
			<td>Near left</td>
			<td>Navy</td>
			<td>-34</td>
			<td>27.5</td>
		</tr>
		<tr>
			<td>V</td>
			<td>Near left</td>
			<td>Blue</td>
			<td>-24.5</td>
			<td>32.5</td>
		</tr>
		<tr>
			<td>W</td>
			<td>Near left</td>
			<td>Maroon</td>
			<td>-15</td>
			<td>31.5</td>
		</tr>
		<tr>
			<td>X</td>
			<td>Near left</td>
			<td>Green</td>
			<td>-5</td>
			<td>29</td>
		</tr>
		<tr>
			<td>Y</td>
			<td>Near right</td>
			<td>White</td>
			<td>6</td>
			<td>30</td>
		</tr>
		<tr>
			<td>Z</td>
			<td>Near right</td>
			<td>Ash</td>
			<td>14</td>
			<td>35</td>
		</tr>
		<tr>
			<td>AA</td>
			<td>Near right</td>
			<td>Yellow</td>
			<td>24.5</td>
			<td>30.5</td>
		</tr>
		<tr>
			<td>AB</td>
			<td>Near left</td>
			<td>Yellow</td>
			<td>-31.5</td>
			<td>21.5</td>
		</tr>
		<tr>
			<td>AC</td>
			<td>Near left</td>
			<td>White</td>
			<td>-22</td>
			<td>24</td>
		</tr>
		<tr>
			<td>AD</td>
			<td>Near left</td>
			<td>Black</td>
			<td>-9</td>
			<td>21</td>
		</tr>
		<tr>
			<td>AE</td>
			<td>Near right</td>
			<td>Red</td>
			<td>5</td>
			<td>22.5</td>
		</tr>
		<tr>
			<td>AF</td>
			<td>Near right</td>
			<td>Blue</td>
			<td>19</td>
			<td>24</td>
		</tr>
		<tr>
			<td>AG</td>
			<td>Near right</td>
			<td>Orange</td>
			<td>32</td>
			<td>22</td>
		</tr>
		<tr>
			<td>AH</td>
			<td>Near left</td>
			<td>Red</td>
			<td>-25</td>
			<td>14</td>
		</tr>
		<tr>
			<td>AI</td>
			<td>Near left</td>
			<td>Ash</td>
			<td>-14</td>
			<td>15.5</td>
		</tr>
		<tr>
			<td>AJ</td>
			<td>Near left</td>
			<td>Orange</td>
			<td>-6.5</td>
			<td>17</td>
		</tr>
		<tr>
			<td>AK</td>
			<td>Near right</td>
			<td>Navy</td>
			<td>10</td>
			<td>16</td>
		</tr>
		<tr>
			<td>AL</td>
			<td>Near right</td>
			<td>Black</td>
			<td>23</td>
			<td>16</td>
		</tr>
		<tr>
			<td>AM</td>
			<td>Near right</td>
			<td>Maroon</td>
			<td>19.5</td>
			<td>10.5</td>
		</tr>
		<tr>
			<td>AN</td>
			<td>Near right</td>
			<td>Green</td>
			<td>30.5</td>
			<td>13</td>
		</tr>
	</tbody>
</table>
Table 2: Suggested brick locations. This table contains the same information as Figure 3. It is listed row by row, then left to right. Quadrants are defined from the participant&#39;s point of view, with far/near divided at Y = 36 cm.
<ol start="4">
	<li>On the poster board, use a pen or pencil to outline the location of each brick, leaving a border (~2 mm) around the brick. This outline will be cut out in step 1.6. 
	NOTE: The purpose of the border is so that, when the posterboard is removed, bricks will not get caught on the cutout edges.</li>
	<li>Outside each outline, place a label that identifies the associated brick (e.g., Orange). Orient the label text so it can be read by an experimenter on the side opposite the baseplate.
	<ol>
		<li>For asymmetrical bricks, add an arrow to the label to indicate a consistent orientation for the brick. This should not affect results but will make setting up easier.</li>
	</ol>
	</li>
	<li>Cut out the rectangular outlines from the poster board. This will produce a posterboard containing 40 labeled outlines, one for each brick, as shown in Figure 1A.</li>
</ol>
2. Setting up the study before participant arrival
<ol>
	<li>Tape the baseplate down on one edge of the table.</li>
	<li>Place a chair without wheels in front of the base plate. Set posterboard on the table, with its notch over the baseplate.</li>
	<li>Place the appropriate brick into each cutout on the poster board. Then, remove the posterboard so only the bricks and baseplate remain (Figure 1C). Do not allow the participant to see the posterboard at any time before study completion.</li>
	<li>Choose the order of the 4 models (for research purposes, counterbalance or randomization). Place a stand (to hold the models) on the experimenter&#39;s side of the table.
	<ol>
		<li>Position the stand where the camera can see the model without the model blocking the camera&#39;s view of hand activities.</li>
	</ol>
	</li>
	<li>Position the camera with a clear view of the workspace, blocks, and hands, including ~20 cm above the baseplate for the building, with the participant&#39;s face out of view.
	<ol>
		<li>Ensure the capacity to perform offline tallying from the video is available, or alternatively, have three experimenters ready to tally left and right reaches during the main task execution.</li>
	</ol>
	</li>
</ol>
3. Main task
<ol>
	<li>Seat participant in the chair. Ensure bricks are visible on the table following step 2. Provide no other training or acclimatization.</li>
	<li>Ensure that the video does not include personally identifiable information by removing or covering any visible identifiers on the participant&#39;s body, e.g., providing a face mask and covering tattoos.</li>
	<li>Instruct participant: &#8220;We&#39;re going to ask you to build some shapes out of these bricks. Start by placing your hands next to the baseplate. I&#39;ll place a model at the front of the table. When I say Go, use the pieces on the table to build the model, including copying the colors. You&#39;ll build it on that green baseplate. We want you to do this as quickly and accurately as you can. The only things we ask are that you pick the pieces up, don&#39;t drag them across the table, and don&#39;t pick up pieces to save for later &#8211; just pick them up when you&#39;re ready to build with them.&#8221; (Demonstrate both if needed.) &#8220;When you finish building, put your hands on either side of the baseplate. Do you have any questions?&#8221;</li>
	<li>If the participant has questions, do not provide any information that is not in the script, but it is acceptable to clarify/repeat or rephrase the script information.
	<ol>
		<li>Do not mention left/right or anything that might make the participant think they are required to use one hand over another.</li>
	</ol>
	</li>
	<li>Tell the participant that the recording will start and do so.</li>
	<li>Place a model on the stand. Say &#34;Go&#34;. Orient the model so the number label faces the experimenter. Wait for the participant to complete their model.</li>
	<li>Remove both models (the experimenter&#39;s glued model and the participant&#39;s just-built model) from the table.</li>
	<li>Return to Step 3.6 with a new model. Repeat until all 4 models are complete and the participant has used all 40 bricks from the table.</li>
</ol>
4. Contingencies during the main task
<ol>
	<li>If the participant omits a brick, wait until they finish the model and then say: &#34;Does your model look like mine?&#34;.&#160;Wait for them to fix it.</li>
	<li>If the participant uses the same brick twice in a model, wait until they finish the model and then say: &#34;Let me add another brick to make sure you&#39;ll have enough for later.&#34;&#160;Put a replacement dead center in the workspace.</li>
	<li>If the participant builds the model with the correct bricks but in the wrong places, say nothing and continue as normal.</li>
	<li>If a brick falls off the table, wait until they finish the model (unless the participant is currently working on the last model), then replace the fallen piece dead center in the workspace.</li>
	<li>If a participant moves a brick when they should not be moving (e.g., before saying Go), say: &#34;Please wait until I say go.&#34;&#160;Stop the participant and put the bricks back in their approximate original locations.</li>
	<li>If a participant scoops bricks or repositions them without building, stop the participant, clarify the instructions, and put the bricks back in their approximate original locations.</li>
</ol>
5. Data collection and coding
<ol>
	<li>Data collection is best performed offline based on video recording, using event logging software (e.g., 26). If recording is impossible, ask coders to follow the below procedure live during the Main Task. For reliability, compare results from two or more coders and achieve a consensus, aiming for 100% agreement. In cases of disagreement, coders will discuss their assessments and reach a consensus through collaborative review.</li>
	<li>Ask the coders to review the video and count the number of times the participant makes a valid reach-to-grasp action (grasp for brevity) with each hand.</li>
	<li>Consider the following actions and invalid grasp:
	<ol>
		<li>Picking up a brick without using a pincer grip, e.g., scooping or sliding a brick across the table.</li>
		<li>Picking up a brick that they had previously picked up. For example, if the participant picks up a brick and then puts it back down, do not count the next time they pick up that brick.</li>
	</ol>
	</li>
	<li>Use the counts of valid grasps with each hand to calculate the fraction of dominant (or affected) hand grasps measured for each participant as 
	Number of valid grasps with hand of interest / total number of valid grasps</li>
	<li>Perform additional analyses (e.g., time spent manipulating bricks with each hand) based on their scientific needs.</li>
</ol>

Quantitative Assessment of Hand Use in Unilateral Nerve Injury

The authors have no conflicts of interest.

The Block Building Task (BBT) allows rapid, inexpensive, quantitative assessment of left/right-hand choices in an unconstrained goal-directed context. Therefore, the BBT provides a unique means to assess the left/right-hand usage patterns that are associated with patient outcomes after unilateral peripheral nerve injury (PNI)3. The novel results in the current manuscript (Figure 4, Figure 5, Figure 6) demonstrate that hand usage after unilateral PNI can be typical DH usage or an overwhelming shift to the DH or NDH &#8211; either of which is possible regardless of whether the injured side is DH or NDH. Hand usage could not be predicted by preexisting clinical variables, so direct measurement is necessary to identify atypical hand usage patterns that could identify what kind of training or rehabilitation might best benefit a patient.
Patients fall into three clusters
The BBT reveals that individual patients fall into three clusters with distinct responses to unilateral PNI: some continue approximately typical hand usage; some switch entirely to their DH or NDH &#8211; including a few individuals who switch to always using their injured hand. It remains unknown whether the approximately-typical patients have changed their hand usage from their pre-injury baseline, but 57% of patients fall into one of the clusters with atypical hand usage. Therefore, further research is needed to identify the effects of subtle shifts in hand usage (within the approximately-typical cluster), but patients who use only one hand are likely to have dramatic effects on their lives and activities.
Critically, clinical characteristics of injury did not predict hand usage. Neither injury side, location, severity, location, duration, or pain provided significant predictors of hand usage. Self-reported hand preference was correlated with actual hand usage, but while this correlation achieved statistical significance, it was partial: hand preference explained &#8776; 23% of the variation in hand usage. This matches previous findings that hand usage is an independent construct7 that cannot be accurately predicted from self-report surveys11 or assessments of manual dexterity22. As a result, quantitative measurement of hand usage is necessary to identify how a patient has responded to DH impairment and thus determine whether intervention is required to encourage a usage-related outcome, such as increased performance of the hand that is used or a shift in the pattern of hand usage.
When hand usage shifts occur (i.e., into always using the affected or unaffected hand), they may represent a strategic choice wherein patients either avoid the injured side&#8217;s discomfort or limited function or self-rehabilitate through directed use of the injured side. However, these explanations are circular because it remains unknown why individual participants choose one strategy or the other. Future studies should identify the psychological or other factors that drive some patients to use or avoid their affected hand.
Individual shifts in hand usage often do not occur, and it remains unknown why such shifts are difficult to achieve. Certainly, patients often fail to shift their hand usage even when their NDH becomes more dexterous after injury, and handedness-shift interventions have mixed results27,28,29. The neural substrates of hand dominance are partly, but not wholly, based on practice29; and hand dominance also has a genetic component30,31. Nevertheless, some lines of research suggest that dominance retraining may be possible. In stroke patients with a paretic DH, preliminary data suggests that NDH performance training can lead to increased functional independence32. Among upper limb amputees, decades of DH loss (and thus forced use of the NDH) can be followed by NDH performance that approximates a healthy DH33. However, most of these studies have focused on hand performance rather than hand usage. Future studies may be able to clarify whether and how hand usage may shift across rehabilitation, including the possibility that neuromodulation might permit changes that do not typically occur through time and rehabilitation alone. Regardless, quantification of hand usage is useful even if it remains difficult to shift hand usage/preference because measurement of hand usage also allows the identification of individuals who might benefit from performance-based rehabilitation due to their existing atypical hand usage.
The block-building task
The primary outcome of the BBT (fraction of movements performed with the hand of interest) is easy to measure it represents a simple tally of left/right reaches. Nevertheless, video recording of the BBT is recommended to ensure accurate results, as is having at least 2 coders review the video and compare their tallies to achieve a consensus.
The BBT is robust to small changes in model choices, brick choices, and brick locations. This manuscript suggests bricks, models, and locations (Figure 2, Figure 3), but these should be taken as suggestions for ease of development, not a mandate. Alternative bricks and models should not affect the results as long as the bricks remain approximately the same sizes as the suggestions22, and the models are positioned where participants can clearly see the bricks and their relative positions. Brick location within the workspace also should not affect the results, so long as the bricks are evenly distributed across the workspace: in unpublished data, participants have completed multiple consecutive runs of the BBT using the same locations each time (i.e., different brick colors and shapes, but in the same locations), and they have never noticed that the locations repeat.
The BBT offers numerous advantages over existing tools to assess actual hand choices quantitatively. A few specialized research tools exist, but those alternatives restrict participant motions to a two-dimensional plane34,35, require expensive virtual reality equipment and specialized data analysis36, or limit actions to 3-5 target locations37,38,39. The Quantification of Hand Preference Test17 involves real-world reaching to pick up cards in 7 locations but is limited because all of its movements have the same distance, and object usage is non-functional (place cards in a box instead of using cards for a game). In contrast, the BBT requires participants to use their bricks to build a model, which places the reach-to-grasp actions within a goal-directed behavioral context. Goals, context, and upcoming actions influence reaching movements40 and their neural mechanisms41,42,43,44 &#8211; and between goal-directed and non-goal-directed actions, the former better reflects natural human reaching behavior because people generally reach to accomplish an external goal. For example, when a person reaches for their coffee mug, their goal is not to pick up the mug; their goal is to drink coffee.
The BBT has numerous limitations, even though few alternatives exist to rapidly quantitively measure hand usage. First, hand choices are task-specific, so BBT results may not generalize to other actions or environments. However, one previous study compared BBT results with a brick stacking task (similar design but with 750 g half-bricks, built into simple stacks instead of complex models); results in the two tasks were correlated (r2 = 0.64)3, suggesting that BBT results should apply beyond the specific context of reach actions with subsequent fine object manipulation. Second, BBT setup logistics require the bricks in fixed locations rather than participant-specific locations, so reach distance/effort depends on the participant&#39;s arm&#39;s length. However, the co-authors have never encountered a participant unable to reach all the bricks. Third, little is known about how left-handed typical adults perform at the BBT; left-handed participants were included in early studies19,45, but the only left-handers who have used the current design are patients. Fourth and finally, the BBT depends on unconstrained choices, so if the experimenter accidentally discloses that the BBT&#8217;s goal is to measure which hand(s) they use, that knowledge may lead to participant self-monitoring that could influence their results. Participant deception is inappropriate, but experimenters can use non-leading language such as: &#34;This task will let us measure how you use your hands to build a simple figure.&#34;
Overall, the Block Building Task (BBT) fills an open niche in clinical and research assessment of patients with unilateral upper extremity impairment (e.g., PNI) by providing the first rapid, inexpensive, quantitative assessment of unconstrained goal-directed left/right-hand choices.

Peripheral nerve injuries to the upper extremity (PNI) are usually unilateral (82%-97%)1,2, but few effective methods exist for quantitative assessment of how unilateral injuries affect unconstrained goal-directed action choices&#8212;specifically, whether people choose to use their left or right hand during daily life.
Left/right-hand choices affect patient outcomes after PNI
Good patient outcomes are associated with continued use of the affected hand, whereas poor patient outcomes occur when the affected hand has preserved function but low usage3. More broadly, changes in hand usage (hand choices in unconstrained environments) can be adaptive or maladaptive: one patient might want to improve the function of their affected hand by increasing its use (i.e., practice), while another patient with chronic impairment might benefit from increased compensatory use of the unaffected hand. Such strategies need intentional clinician guidance; for example, in the case of patients who would benefit from compensating with the unaffected hand, such compensation will not happen naturally if the injured hand is the dominant hand (DH)4. Therefore, many patients with PNI would benefit from accurate assessment or tracking of their hand-choice behavior.
Current assessments are inadequate to quantitatively capture functional hand usage after PNI
Hand usage cannot be captured through standard measures of hand preference, hand function, or disability. Hand preference surveys such as the Edinburgh Handedness Inventory5 or Motor Activity Log6 address a fundamentally different concept (self-reported hand usage)7; moreover, preference surveys suffer from the limited accuracy inherent to self-report surveys8,9, have poorly established psychometric properties10, and their results may not generalize beyond the specific tasks listed in the survey11. Few clinical assessments of hand function can quantify hand usage because common assessments, such as the Fugl-Meyer12 and Box and Blocks13 measure dexterity rather than hand usage7 and focus on hand actions with only modest left-right asymmetry14. Standard patient-reported outcome assessments cannot identify the consequences of unilateral injury, for example, the Disabilities of the Arm, Shoulder, and Hand (DASH)1,15 and QuickDASH16 are designed to omit or minimize actions that depend strongly on hand dominance. Finally, while two established measures of hand usage exist, they both have shortcomings. The Quantification of Hand Preference Test (QHPT)17 allows quantitative measurement of reaching actions that may resemble everyday tasks, but it narrowly samples movement distances (all targets equidistant from participant) and avoids functional use of objects (participants pick up playing cards but do not use them for a game), which could limit the QHPT&#8217;s applicability to real-world scenarios. The Actual Amount of Use test involves real-world contextualized actions but does not provide numerical quantitative results because it involves only one sample per activity18. Therefore, measurement of left/right-hand use requires new and specific assessments.
The Block Building Task (BBT)4,19,20 provides a rapid, inexpensive, quantitative method to address this gap in measurement by assessing left/right-hand choices in an unconstrained goal-directed context, including in individuals with unilateral PNI. The BBT is suitable to characterize left/right-hand usage in any participants who have the ability to make reach-to-grasp actions and is ideally suited to characterize atypical hand usage after unilateral impairment &#8211; i.e., elevated use of one hand (and accompanying disuse of the other hand) compared to typical adults. The BBT is not in widespread use, especially in the clinical environment. The current manuscript addresses this gap by presenting a protocol for using the BBT to assess how often a participant uses each hand for unconstrained reach-to-grasp actions and also by presenting new results about the distribution and clustering of hand usage outcomes after unilateral PNI.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Baseplate</td>
			<td>The Lego Group</td>
			<td>11023</td>
			<td></td>
		</tr>
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			<td>Brick: 1x2 rectangle, dark azure</td>
			<td>The Lego Group</td>
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			<td>Brick: 1x2 with 45&#176; slope, dark red</td>
			<td>The Lego Group</td>
			<td>4541526</td>
			<td>8 copies + spares; best acquired from brickowl.com</td>
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			<td>Brick: 1x2 with 45&#176; slope, medium stone gray</td>
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			<td>Brick: 2x2 square, black</td>
			<td>The Lego Group</td>
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			<td>Brick: 2x2 square, white</td>
			<td>The Lego Group</td>
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			<td>8 copies + spares; best acquired from brickowl.com</td>
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			<td>Brick: 2x2 with 45&#176; slope, dark blue</td>
			<td>The Lego Group</td>
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			<td>8 copies + spares; best acquired from brickowl.com</td>
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			<td>Brick: 2x3 with arch, dark green</td>
			<td>The Lego Group</td>
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			<td>8 copies + spares; best acquired from brickowl.com</td>
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			<td>Brick: 2x4 rectangle, red</td>
			<td>The Lego Group</td>
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			<td>8 copies + spares; best acquired from brickowl.com</td>
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			<td>Brick: 2x4 rectangle, yellow</td>
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			<td>For gluing models together</td>
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			<td>Posterboard: Two Cool Tri-Fold Poster Board, 36 x 48&#34;, White/White</td>
			<td>Geographics</td>
			<td>GEO26790</td>
			<td>BBT will use an 80 x 60 cm workspace. Folding posterboards are recommended.</td>
		</tr>
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			<td>Stand</td>
			<td>Adorox</td>
			<td>KPL7_ADX_FBK</td>
			<td>To support models during experiment</td>
		</tr>
	</tbody>
</table>

block building task identifies distinct groups of left/right-hand choice patterns after unilateral peripheral nerve injury

Numerous methods exist to assess hand and arm function after upper extremity peripheral nerve injury, but peripheral injuries are often unilateral, and few existing methods are designed to capture the unique consequences of unilateral injury. Unilateral impairment of an upper extremity can lead to increased or decreased use of the dominant hand, and either change may be adaptive or maladaptive depending on the individual patient&#8217;s needs. To identify atypical hand usage (left/right choices), researchers and clinicians need to measure it. However, hand usage is traditionally assessed with self-report surveys, which do not necessarily reflect actual left/right-hand choices. Here, this gap in knowledge is addressed with the Block Building Task (BBT), which provides a rapid, quantitative, inexpensive assessment of left/right-hand choices in an unconstrained environment. In the BBT, participants build abstract shapes with interlocking plastic bricks, with no instructions about hand usage. The primary outcome is the fraction of reaches (i.e., for the initial pickup of each brick) made with each hand. After unilateral peripheral nerve injury, patients fell into three clusters: approximately typical hand use (44%), always use the dominant hand (44%), or never use the dominant hand (13%). Even among patients with an injured dominant hand, atypically elevated use of the dominant hand occurred regularly (36%). Notably, hand usage was not predicted by clinical characteristics, so the BBT provides an objective measurement of left/right-hand choices that are not otherwise predictable from the clinical characteristics of patients with peripheral nerve injury. The BBT protocol will be of interest to researchers or clinicians interested in the assessment of conditions with asymmetric effects on the upper limb.

Participant selection
Inclusion/exclusion criteria were: age of 18 years or older, English-speaking, unilateral upper extremity PNI (defined as non-pathologic origin, determined from medical records), and Quick Disabilities of the Arm, Shoulder, and Hand (Q-DASH)16&#160;score &#8805; 18, measured at the start of the study session. This threshold was chosen to select individuals whose life is affected by their impairment, at 1 minimum clinically important difference24&#160;above 0. This threshold was designed to capture a wide range of patients with PNI because it also lies 1 SD below the mean of patients with upper extremity disorder25.
Exclusion criteria were: cognitive disorders, uncorrected visual impairment, chronic pain diagnoses, major mental health diagnosis (not including depression, anxiety, bipolar, or posttraumatic stress disorder), surgery within the preceding 2 months, or motor function diagnosis affecting the arm contralateral to their PNI in preceding 2 years. To examine the effects of injury severity, injuries of all types and severity levels were recruited within the above criteria.
In the current data, participants were 48 adults with unilateral PNI, recruited from the Washington University School of Medicine (St. Louis, MO) Center for Nerve Injury and Paralysis Injury Clinic and Milliken Hand Center outpatient hand therapy clinic. For the recruitment flowchart, see4. To compare patients with typical adults, data was used from a previous study using the same design with 20 additional participants (typical right-handed adults, age range 18-33 years, collected in 2013-2014 at the University of Lethbridge, Alberta, Canada)21. Data were stored and managed via the Research Electronic Data Capture system22.
The patients included 22 participants with PNI to their DH and 26 with PNI to their non-dominant hand (NDH). Full demographic details are listed in Table 3; no differences were found between groups (affected DH versus affected NDH), except that the affected DH group had a marginally higher time since injury (p = 0.050). Both groups underwent the same protocol.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="2" rowspan="4">Variable&#160;</td>
			<td>Total</td>
			<td>DH affected</td>
			<td>NDH affected</td>
			<td colspan="2" rowspan="2">Between Groups&#160;</td>
		</tr>
		<tr>
			<td>(n = 48)</td>
			<td>(n = 22)</td>
			<td>(n = 26)</td>
		</tr>
		<tr>
			<td>Mean/Count</td>
			<td>Mean/Count</td>
			<td>Mean/Count</td>
			<td rowspan="2">t/&#967;2</td>
			<td rowspan="2">p&#160;</td>
		</tr>
		<tr>
			<td>(%, SD, or Range)</td>
			<td>(%, SD, or Range)</td>
			<td>(%, SD, or Range)</td>
		</tr>
		<tr>
			<td colspan="2">Age (years)</td>
			<td>44.42 &#177; 15.55</td>
			<td>41 &#177; 15.5</td>
			<td>43 &#177; 15.6</td>
			<td>-0.896</td>
			<td>0.375</td>
		</tr>
		<tr>
			<td colspan="2">Sex = female (n)</td>
			<td>28 (58%)</td>
			<td>15(68%)</td>
			<td>13(50%)</td>
			<td>0.959</td>
			<td>0.327</td>
		</tr>
		<tr>
			<td rowspan="5">Race</td>
			<td>White&#160;</td>
			<td>37 (77%)</td>
			<td>18 (81.8%)</td>
			<td>19 (73%)</td>
			<td>0.139</td>
			<td>0.709</td>
		</tr>
		<tr>
			<td>Black/African American&#160;</td>
			<td>9 (19%)</td>
			<td>4 (18.2%)</td>
			<td>5 (19.3%)</td>
			<td>0.000</td>
			<td>1.000</td>
		</tr>
		<tr>
			<td>Native American&#160;</td>
			<td>3 (6%)</td>
			<td>1 (4.5%)</td>
			<td>2 (7.7%)</td>
			<td>0.000</td>
			<td>1.000</td>
		</tr>
		<tr>
			<td>Asian American/Pacific&#160;&#160;</td>
			<td>0 (0%)</td>
			<td>0 (0%)</td>
			<td>0 (0%)</td>
			<td>0.333</td>
			<td>0.564</td>
		</tr>
		<tr>
			<td>Other&#160;</td>
			<td>2 (4%)</td>
			<td>0 (0%)</td>
			<td>2 (7.7%)</td>
			<td>0.365</td>
			<td>0.546</td>
		</tr>
		<tr>
			<td rowspan="5">Education</td>
			<td>Some high school&#160;</td>
			<td>&#160;2 (4%)</td>
			<td>0 (0%)</td>
			<td>2(7.7%)</td>
			<td>0.053</td>
			<td>0.819</td>
		</tr>
		<tr>
			<td>High school or equivalent&#160;</td>
			<td>10 (21%)</td>
			<td>4(18%)</td>
			<td>6(23%)</td>
			<td>0.400</td>
			<td>0.527</td>
		</tr>
		<tr>
			<td>Some college&#160;</td>
			<td>16 (33%)</td>
			<td>9 (41%)</td>
			<td>7(27%)</td>
			<td>0.250</td>
			<td>0.617</td>
		</tr>
		<tr>
			<td>College +</td>
			<td>19 (39%)</td>
			<td>9(41%)</td>
			<td>10 (38.5%)</td>
			<td>0.053</td>
			<td>0.819</td>
		</tr>
		<tr>
			<td>Other&#160;</td>
			<td>1(2%)&#160;</td>
			<td>0(0%)</td>
			<td>1(4%)</td>
			<td>0.015</td>
			<td>0.904</td>
		</tr>
		<tr>
			<td colspan="2">Affected hand = dominant (n)</td>
			<td></td>
			<td>22 (45.8%)</td>
			<td>26 (54%)</td>
			<td>&#8211;</td>
			<td>&#8211;</td>
		</tr>
		<tr>
			<td colspan="2">Months since injury (median)</td>
			<td>11 (1-160)</td>
			<td>13 (4-47)</td>
			<td>9 (1-160)&#160;</td>
			<td>-0.306</td>
			<td>0.761</td>
		</tr>
		<tr>
			<td colspan="2">Recent injury related pain (0-10)</td>
			<td>3 (0-10)</td>
			<td>&#160;3 (0-8)&#160;</td>
			<td>3 (0 -10)&#160;</td>
			<td>0.226</td>
			<td>0.822</td>
		</tr>
		<tr>
			<td rowspan="3">Severity</td>
			<td>Neurapraxia</td>
			<td>8 (17%)</td>
			<td>&#160;4 (8.33%)</td>
			<td>4 (8.33%)</td>
			<td>0.017</td>
			<td>0.897</td>
		</tr>
		<tr>
			<td>Axonotmesis</td>
			<td>18 (38%)</td>
			<td>&#160;7 (14.6 %)</td>
			<td>11 (23%)</td>
			<td>0.889</td>
			<td>0.346</td>
		</tr>
		<tr>
			<td>Neurotmesis</td>
			<td>22 (46%)</td>
			<td>11 (23%)</td>
			<td>11 (23%)</td>
			<td>0</td>
			<td>1</td>
		</tr>
		<tr>
			<td rowspan="7">Affected nerve</td>
			<td>Ulnar</td>
			<td>27 (56%)</td>
			<td>12 (54.5%)</td>
			<td>15 (57.6%)</td>
			<td>0</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Median</td>
			<td>33 (68.75%)</td>
			<td>15 (68%)</td>
			<td>18 (69%)</td>
			<td>0</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Radial</td>
			<td>18 (37.5%)</td>
			<td>5 (23%)</td>
			<td>13 (50%)</td>
			<td>2.708</td>
			<td>0.100</td>
		</tr>
		<tr>
			<td>Posterior interosseous</td>
			<td>4 (8%)</td>
			<td>2 (9%)</td>
			<td>2(7.6%)</td>
			<td>0</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Anterior interosseous</td>
			<td>3 (6%)</td>
			<td>1 (4.5%)</td>
			<td>2 (7.6%)</td>
			<td>0</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Cutaneous</td>
			<td>7 (14.5%)</td>
			<td>4 (18.6%)</td>
			<td>3 (11.5%)</td>
			<td>0.057</td>
			<td>0.811</td>
		</tr>
		<tr>
			<td>Other</td>
			<td>11 (22%)</td>
			<td>7 (32%)</td>
			<td>4 (15%)</td>
			<td>1.010</td>
			<td>0.315</td>
		</tr>
		<tr>
			<td rowspan="7">Injury location</td>
			<td>Brachial Plexus</td>
			<td>15 (31.3%)</td>
			<td>8 (36%)</td>
			<td>7 (27%)</td>
			<td>0.153</td>
			<td>0.696</td>
		</tr>
		<tr>
			<td>Upper Arm</td>
			<td>7 (14.5%)</td>
			<td>4 (18%)</td>
			<td>3 (11.5%)</td>
			<td>0.057</td>
			<td>0.811</td>
		</tr>
		<tr>
			<td>Elbow</td>
			<td>11 (23%)</td>
			<td>6(27%)</td>
			<td>5(19%)</td>
			<td>0.100</td>
			<td>0.752</td>
		</tr>
		<tr>
			<td>Forearm</td>
			<td>15 (31%)</td>
			<td>9 (27%)</td>
			<td>6 (19%)</td>
			<td>1.031</td>
			<td>0.310</td>
		</tr>
		<tr>
			<td>Wrist</td>
			<td>22 (46%)</td>
			<td>8 (41%)</td>
			<td>14(23%)</td>
			<td>0.847</td>
			<td>0.357</td>
		</tr>
		<tr>
			<td>Hand</td>
			<td>6 (12.5%)</td>
			<td>3 (13%.6)</td>
			<td>3 (11.5%)</td>
			<td>0</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Digit&#160;</td>
			<td>4(8%)</td>
			<td>2 (9%)</td>
			<td>2(7.6%)</td>
			<td>0</td>
			<td>1</td>
		</tr>
		<tr>
			<td rowspan="4">Injury cause</td>
			<td>Trauma</td>
			<td>&#160;29 (60%)</td>
			<td>12 (54.5%)</td>
			<td>&#160;17 (65.4%)&#160;</td>
			<td>0.862</td>
			<td>0.353</td>
		</tr>
		<tr>
			<td>Surgical complication</td>
			<td>&#160;9 (19%)</td>
			<td>&#160;5 (22.7%)</td>
			<td>&#160;4 (15.4%)</td>
			<td>0.111</td>
			<td>0.739</td>
		</tr>
		<tr>
			<td>Chronic compression</td>
			<td>&#160;7 (15%)</td>
			<td>4 (18.2 %)</td>
			<td>&#160;3 (11.5%)</td>
			<td>0.143</td>
			<td>0.706</td>
		</tr>
		<tr>
			<td>Other</td>
			<td>3 (6%)</td>
			<td>&#160;1 (4.55%)</td>
			<td>&#160; 2 (7.7)%</td>
			<td>0.333</td>
			<td>0.564</td>
		</tr>
	</tbody>
</table>
Table 3: Patient demographics. Between-group differences assessed by t-tests for numerical data and x2&#160;tests for categorical data. Surgery = for this injury. No participants identified as Hispanic and/or Latino.
Data analysis specific to the current report included identifying subgroups of participants through a cluster analysis of hand usage ratios. Data analysis was performed in MATLAB 23.2.0; cluster analysis was performed using the linkage function using the shortest Euclidian distance, and the results were visualized using the dendrogram function. In addition, to determine whether a demographic factor was associated with hand usage, categorical factors were tested with ANOVAs and quantitative factors through Spearman correlations. No multiple comparison correction was applied.
The primary outcome of the BBT is the fraction of dominant (or affected) hand grasps, measured for each participant as described in step 5.4:
number of grasps with the hand of interest / total number of grasps
The BBT reveals a distinct pattern of atypical hand usage after PNI, as shown in Figure 4. In the current data, healthy adults (data available for right-handers only) used their DH at a rate of 0.63 &#177; 0.14, which closely matches previous studies using the same design (0.64 &#177; 0.0721, 0.64 &#177; 0.0223). Among patients with unilateral PNI to the dominant hand, average hand usage remained indistinguishable from healthy adults: right-handers 0.59 &#177; 0.32 (n = 20, Mann Whitney U-test p = 0.70), all handedness 0.62 &#177; 0.3 (n = 22, p = 0.90); left-handers not analyzed statistically (n=2). Nevertheless, most individual patients showed atypical usage. To quantify this pattern, a cluster analysis was performed on all participants regardless of injury or hand dominance (n=68), producing the dendrogram shown in Figure 5.
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/66919/66919fig1.jpg" /> 
Figure 4: Hand usage with and without PNI. Each point represents 1 participant. At the group level, patients do not differ significantly from typical adults, but 57% of individual patients lie outside the typical range (0.4-0.875). Horizontal jitter was introduced to increase the visibility of individual points. Injured hand: DH = dominant hand, NDH = non-dominant hand, None = typical adult. (A) Right-handed patients (n=41) and typical adults (n=20). (B) Left-handed patients (n=7). (C) Patients of any handedness (n=61). <a href="https://www.jove.com/files/ftp_upload/66919/66919fig1large.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/66919/66919fig2.jpg" /> 
Figure 5: Clustering of hand usage among participants. The dendrogram shows three clusters of participants: typical DH usage (cyan), always DH usage (green), and never DH usage (magenta). Individual participants are labeled with a group (DH injured, NDH injured, or Healthy), handedness (R-dom, L-dom), and a fraction of DH use. <a href="https://www.jove.com/files/ftp_upload/66919/66919fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
This clustering identified three groups, with cutoffs of &#62;0.100 and &#62;0.875: patients who almost never use the DH&#160;(median 0.03); patients who almost always use the DH&#160;(median 1.00); and&#160;individuals who use the DH at a typical rate&#160;(median 0.60). Cluster cutoffs were identical if left-handers were excluded. Overall, most patients had atypical hand usage (27/47, 57%), but the hand usage cluster was not determined by whether the DH was injured, as shown in Figure 6. Specifically, some patients showed elevated use of the affected hand, including 8/22 patients with DH injury (36%). Therefore, individual patients&#39; hand usage can be dramatically atypical, but the direction of atypicality cannot be predicted without individual measurement.
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/66919/66919fig3.jpg" /> 
Figure 6: Relationship between individual characteristics and hand usage clusters. Some participants always use their DH despite DH injury or never use their DH despite NDH injury. Numbers = # of participants in each cluster. <a href="https://www.jove.com/files/ftp_upload/66919/66919fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Hand usage among right-handed participants was not predicted by key clinical characteristics, including affected nerve, injury location, severity, months since surgery, or pain (p &#62; 0.2 in all cases); for details, see Supplementary Table.&#160;The ANOVA included only right-handers due to the small sample of left-handers and differences between groups. Despite the lack of significant factors in the ANOVA, one factor did correlate significantly but partially with hand usage: preference shift, as measured by change in Edinburgh self-report (&#961; = -0.594, p &#60; .001). This pattern remained true when restricting the analysis to patients with DH injury for all the above characteristics (p&#160; &#8805; 0.09, 0.170, 0.816, 0.978, 0.615, and .038, respectively). Overall, while self-reported hand usage was partially correlated with hand usage, atypical hand usage could not be well predicted from prior factors.
The BBT is rapid and reliable. Most participants complete the BBT in less than 3 min: time from first to last movement in healthy adults is 157 &#177; 33 s (range 99-291 s, median 152 s; data from 22); in patients with unilateral PNI, the time is 245 &#177; 141 s (range 120-919 s, median 217 s).
To measure external validity, a previous study compared BBT hand choices with Motor Activity Log (MAL) self-reported hand preferences6 in patients with unilateral PNI; these two measures were moderately correlated (r2 = 0.33)4, as appropriate for instruments that measure a similar construct with major differences in method; for example, the MAL measures self-reported use/disuse of the affected hand independent from the use of the unaffected hand. The BBT has good test-retest reliability (r = 0.838), even when the multiple tests have substantial differences in model design (comparing 10-brick models versus 5-brick models, all with normal-size bricks)23.
These results demonstrate the BBT&#39;s precision, speed, and validity and, accordingly, its ability to detect atypical patterns of hand usage that may not be otherwise evident in clinical characteristics.
Supplementary Table. <a href="https://www.jove.com/files/ftp_upload/66919/LegoJOVE_suppTable_.docx" target="_blank">Please click here to download this file.</a>

Block Building Task Identifies Distinct Groups of Left/Right-hand Choice Patterns After Unilateral Peripheral Nerve Injury

The block-building task provides a rapid, objective, quantitative measurement of how often individuals choose to use their left versus right hand for reach-to-grasp action. After unilateral peripheral nerve injury, patients often shift to near-total usage of one hand, the direction of which is not predictable from other clinical factors.

Numerous methods exist to assess hand and arm function after upper extremity peripheral nerve injury, but peripheral injuries are often unilateral, and ...

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118 Views.  Washington University School of Medicine. The block-building task provides a rapid, objective, quantitative measurement of how often individuals choose to use their left versus right hand for reach-to-grasp action. After unilateral peripheral nerve injury, patients often shift to near-total usage of one hand, the direction of which is not predictable from other clinical factors.

Video: Block Building Task Identifies Distinct Groups of Left/Right-hand Choice Patterns After Unilateral Peripheral Nerve Injury

Transplantation of Olfactory Ensheathing Cells to Evaluate Functional Recovery after Peripheral Nerve Injury

Olfactory ensheathing cells (OECs) are neural crest cells which allow growth and regrowth of the primary olfactory neurons. Indeed, the primary olfactory system is characterized by its ability to give rise to new neurons even in adult animals. This particular ability is partly due to the presence of OECs which create a favorable microenvironment for neurogenesis. This property of OECs has been used for cellular transplantation such as in spinal cord injury models. Although the peripheral nervous system has a greater capacity to regenerate after nerve injury than the central nervous system, complete sections induce misrouting during axonal regrowth in particular after facial of laryngeal nerve transection. Specifically, full sectioning of the recurrent laryngeal nerve (RLN) induces aberrant axonal regrowth resulting in synkinesis of the vocal cords. In this specific model, we showed that OECs transplantation efficiently increases axonal regrowth.
OECs are constituted of several subpopulations present in both the olfactory mucosa (OM-OECs) and the olfactory bulbs (OB-OECs). We present here a model of cellular transplantation based on the use of these different subpopulations of OECs in a RLN injury model. Using this paradigm, primary cultures of OB-OECs and OM-OECs were transplanted in Matrigel after section and anastomosis of the RLN. Two months after surgery, we evaluated transplanted animals by complementary analyses based on videolaryngoscopy, electromyography (EMG), and histological studies. First, videolaryngoscopy allowed us to evaluate laryngeal functions, in particular muscular cocontractions phenomena. Then, EMG analyses demonstrated richness and synchronization of muscular activities. Finally, histological studies based on toluidine blue staining allowed the quantification of the number and profile of myelinated fibers.
All together, we describe here how to isolate, culture, identify and transplant OECs from OM and OB after RLN section-anastomosis and how to evaluate and analyze the efficiency of these transplanted cells on axonal regrowth and laryngeal functions.

Olfactory ensheathing cells (OECs) are neural crest cells which allow growth of the primary olfactory neurons. This specific property can be used for cellular transplantation. We present here a model of cellular transplantation based on the use of OECs in a laryngeal nerve injury model.

Olfactory ensheathing cells (OECs) are neural crest cells which allow growth and regrowth of the primary olfactory neurons. Indeed, the primary olfactory ...

Bioluminescence Imaging of Neuroinflammation in Transgenic Mice After Peripheral Inoculation of Alpha-Synuclein Fibrils

To study the prion-like behavior of misfolded alpha-synuclein, mouse models are needed that allow fast and simple transmission of alpha-synuclein prionoids, which cause neuropathology within the central nervous system (CNS). Here we describe that intraglossal or intraperitoneal injection of alpha-synuclein fibrils into bigenic Tg(M83+/-:Gfap-luc+/-) mice, which overexpress human alpha-synuclein with the A53T mutation from the prion protein promoter and firefly luciferase from the promoter for glial fibrillary acidic protein (Gfap), is sufficient to induce neuropathologic disease. In comparison to homozygous Tg(M83+/+) mice that develop severe neurologic symptoms beginning at an age of 8 months, heterozygous Tg(M83+/-:Gfap-luc+/-) animals remain free of spontaneous disease until they reach an age of 22 months. Interestingly, injection of alpha-synuclein fibrils via the intraperitoneal route induced neurologic disease with paralysis in four of five Tg(M83+/-:Gfap-luc+/-) mice with a median incubation time of 229 &#177;17 days. Diseased animals showed severe deposits of phosphorylated alpha-synuclein in their brains and spinal cords. Accumulations of alpha-synuclein were sarkosyl-insoluble and colocalized with ubiquitin and p62, and were accompanied by an inflammatory response resulting in astrocytic gliosis and microgliosis. Surprisingly, inoculation of alpha-synuclein fibrils into the tongue was less effective in causing disease with only one of five injected animals showing alpha-synuclein pathology after 285 days. Our findings show that inoculation via the intraglossal route and more so via the intraperitoneal route is suitable to induce neurologic illness with relevant hallmarks of synucleinopathies in Tg(M83+/-:Gfap-luc+/-) mice. This provides a new model for studying prion-like pathogenesis induced by alpha-synuclein prionoids in greater detail.

Peripheral injection of alpha-synuclein fibrils into the peritoneum or tongue of Tg(M83+/-:Gfap-luc+/-) mice, which express human alpha-synuclein with the familial A53T mutation and firefly luciferase, can induce neuropathology, including neuroinflammation, in their central nervous system.

To study the prion-like behavior of misfolded alpha-synuclein, mouse models are needed that allow fast and simple transmission of alpha-synuclein ...

Toluidine Blue Staining of Resin-Embedded Sections for Evaluation of Peripheral Nerve Morphology

Peripheral nerves extend throughout the body, innervating target tissues with motor or sensory axons. Due to widespread distribution, peripheral nerves are frequently damaged because of trauma or disease. As methods and strategies have been developed to assess peripheral nerve injury in animal models, function and regeneration, analyzing the morphometry of the peripheral nerve has become an essential terminal outcome measurement. Toluidine blue staining of nerve cross sections obtained from resin embedded nerve sections is a reproducible method for qualitative and quantitative assessments of peripheral nerves, enabling visualization of morphology number of axons and degree of myelination. This technique, as with many other histological methods, can be difficult to learn and master using standard written protocols. The intent of this publication is therefore to accentuate written protocols for toluidine blue staining of peripheral nerves with videography of the method, using sciatic nerves harvested from rats. In this protocol, we describe in vivo peripheral nerve fixation and collection of the tissue, and post-fixation with 2% osmium tetroxide, embedding of nerves in epoxy resin, and ultramicrotome sectioning of nerves to 1-2&#956;m thickness. Nerve sections then transferred to a glass slide and stained with toluidine blue, after which they are quantitatively and qualitatively assessed. Examples of the most common problems are shown, as well as steps for mitigating these issues.

Here we present a protocol to visualize fine structures of peripheral nerves by obtaining and staining 1-2 &#181;m sections with toluidine blue

Peripheral nerves extend throughout the body, innervating target tissues with motor or sensory axons. Due to widespread distribution, peripheral nerves ...

Ethanol-Induced Cervical Sympathetic Ganglion Block Applications for Promoting Canine Inferior Alveolar Nerve Regeneration Using an Artificial Nerve

Polyglycolic acid collagen (PGA-C) tubes are bio-absorbable nerve tubes filled with collagen of multi-chamber structure, which consist of thin collagen films. Favorable clinical outcomes have been achieved when using these tubes for the treatment of damaged inferior alveolar nerve (IAN). A critical factor for the successful nerve regeneration using PGA-C tubes is blood supply to the surrounding tissue. Cervical sympathetic ganglion block (CSGB) creates a sympathetic blockade in the head and neck region thus increasing blood flow in the area. To ensure an adequate effect, the blockade must be administered with local anesthetics one to two times a day for several consecutive weeks; this poses a challenge when creating animal models for investigating this technique. To address this limitation, we developed an ethanol-induced CSGB in a canine model of long-term increase in blood flow in the orofacial region. We examined whether IAN regeneration via PGA-C tube implantation can be enhanced by this model. Fourteen Beagles were each implanted with a PGA-C tube across a 10-mm gap in the left IAN. The IAN is located within the mandibular canal surrounded by bone, therefore we chose piezoelectric surgery, consisting of ultrasonic waves, for bone processing, in order to minimize the risk of nerve and vessel injury. A good surgical outcome was obtained with this approach. A week after surgery, seven of these dogs were subjected to left CSGB by injection of ethanol. Ethanol-induced CSGB resulted in improved nerve regeneration, suggesting that the increased blood flow effectively promotes nerve regeneration in IAN defects. This canine model can contribute to further research on the long-term effects of CSGB.

We evaluated the effect of cervical sympathetic ganglion block on nerve repair using artificial nerve conduits. Male beagle dogs were each implanted with an artificial nerve across a 10-mm gap in the left inferior alveolar nerve; left cervical sympathetic ganglion was blocked by injecting 99.5% ethanol via lateral thoracotomy.

Polyglycolic acid collagen (PGA-C) tubes are bio-absorbable nerve tubes filled with collagen of multi-chamber structure, which consist of thin collagen ...

Purification of Fibroblasts and Schwann Cells from Sensory and Motor Nerves in Vitro

The principal cells in the peripheral nervous system are the Schwann cells (SCs) and the fibroblasts. Both these cells distinctly express the sensory and motor phenotypes involved in different patterns of neurotrophic factor gene expression and other biological processes, affecting nerve regeneration. The present study has established a protocol to obtain highly purified rat sensory and motor SCs and fibroblasts more rapidly. The ventral root (motor nerve) and the dorsal root (sensory nerve) of neonatal rats (7-days-old) were dissociated and the cells were cultured for 4-5 days, followed by isolation of sensory and motor fibroblasts and SCs by combining differential digestion and differential adherence methods sequentially. The results of immunocytochemistry and flow cytometry analyses showed that the purity of the sensory and motor SCs and fibroblasts were &#62;90%. This protocol can be used to obtain a large number of sensory and motor fibroblasts/SCs more rapidly, contributing to the exploration of sensory and motor nerve regeneration.

Here, we present a method to purify fibroblasts and Schwann cells from sensory and motor nerves in vitro.

The principal cells in the peripheral nervous system are the Schwann cells (SCs) and the fibroblasts. Both these cells distinctly express the sensory and ...

Preparation of Peripheral Nerve Stimulation Electrodes for Chronic Implantation in Rats

Peripheral nerve cuff electrodes have long been used in the neurosciences and related fields for stimulation of, for example, vagus or sciatic nerves. Several recent studies have demonstrated the effectiveness of chronic VNS in enhancing central nervous system plasticity to improve motor rehabilitation, extinction learning, and sensory discrimination. Construction of chronically implantable devices for use in such studies is challenging due to rats&#8217; small size, and typical protocols require extensive training of personnel and time-consuming microfabrication methods. Alternatively, commercially available implantable cuff electrodes can be purchased at a significantly higher cost. In this protocol, we present a simple, low-cost method for construction of small, chronically implantable peripheral nerve cuff electrodes for use in rats. We validate the short and long-term reliability of our cuff electrodes by demonstrating that VNS in ketamine/xylazine anesthetized rats produces decreases in breathing rate consistent with activation of the Hering-Breuer reflex, both at the time of implantation and up to 10 weeks after device implantation. We further demonstrate the suitability of the cuff electrodes for use in chronic stimulation studies by pairing VNS with skilled lever press performance to induce motor cortical map plasticity.

Existing approaches for constructing chronically implantable peripheral nerve cuff electrodes for use in small rodents often require specialized equipment and/or highly trained personnel. In this protocol we demonstrate a simple, low-cost approach for fabricating chronically implantable cuff electrodes, and demonstrate their effectiveness for vagus nerve stimulation (VNS) in rats.

Peripheral nerve cuff electrodes have long been used in the neurosciences and related fields for stimulation of, for example, vagus or sciatic nerves. ...

Automated Gait Analysis to Assess Functional Recovery in Rodents with Peripheral Nerve or Spinal Cord Contusion Injury

Peripheral and central nerve injuries are mostly studied in rodents, especially rats, given the fact that these animal models are both cost-effective and a lot of comparative data has been published in the literature. This includes a multitude of assessment methods to study functional recovery following nerve injury and repair. Besides evaluation of nerve regeneration by means of histology, electrophysiology, and other in vivo and in vitro assessment techniques, functional recovery is the most important criterion to determine the degree of neural regeneration. Automated gait analysis allows recording of a vast quantity of gait-related parameters such as Paw Print Area and Paw Swing Speed as well as measures of inter-limb coordination. Additionally, the method provides digital data of the rats&#8217; paws after neuronal damage and during nerve regeneration, adding to our understanding of how peripheral and central nervous injuries affect their locomotor behavior. Besides the predominantly used sciatic nerve injury model, other models of peripheral nerve injury such as the femoral nerve can be studied by means of this method. In addition to injuries of the peripheral nervous systems, lesions of the central nervous system, e.g., spinal cord contusion can be evaluated. Valid and reproducible data assessment is strongly dependent on meticulous adjustment of the hard- and software settings prior to data acquisition. Additionally, proper training of the experimental animals is of crucial importance. This work aims to illustrate the use of computerized automated gait analysis to assess functional recovery in different animal models of peripheral nerve injury as well as spinal cord contusion injury. It also emphasizes the method&#8217;s limitations, e.g., evaluation of nerve regeneration in rats with sciatic nerve neurotmesis due to limited functional recovery. Therefore, this protocol is thought to help researchers interested in peripheral and central nervous injuries to assess functional recovery in rodent models.

Automated gait analysis is a feasible tool to evaluate functional recovery in rodent models of peripheral nerve injury and spinal cord contusion injury. While it requires only one setup to assess locomotor function in various experimental models, meticulous hard- and soft-ware adjustment and training of the animals is highly important.

Peripheral and central nerve injuries are mostly studied in rodents, especially rats, given the fact that these animal models are both cost-effective and ...

Multifactorial Assessment of Motor Behavior in Rats after Unilateral Sciatic Nerve Crush Injury

The induction of a peripheral nerve injury is a widely used method in neuroscience for the assessment of repair and pain mechanisms among others. In addition, in the research field of movement disorders, sciatic crush injury has been employed to trigger a dystonia-like phenotype in genetically predisposed DYT-TOR1A rodent models of dystonia. To achieve consistent, reproducible and comparable results after a sciatic nerve crush injury, a standardized method for inducing the nerve crush is essential, in addition to a standardized phenotypical characterization. Attention must be paid not only to the specific assortment of behavioral tests, but also to the technical requirements, the correct execution and consecutive data analysis. This protocol describes in detail how to perform a sciatic nerve crush injury and provides a behavioral test battery for the assessment of motor deficits in rats that includes the open field test, the CatWalk XT gait analysis, the beam walking task, and the ladder rung walking task.

We provide a protocol for the assessment of motor behavior via a behavioral test battery in rats after sciatic nerve crush injury.

The induction of a peripheral nerve injury is a widely used method in neuroscience for the assessment of repair and pain mechanisms among others. In ...

Implantation and Control of Wireless, Battery-free Systems for Peripheral Nerve Interfacing

Peripheral nerve interfaces are frequently used in experimental neuroscience and regenerative medicine for a wide variety of applications. Such interfaces can be sensors, actuators, or both. Traditional methods of peripheral nerve interfacing must either tether to an external system or rely on battery power that limits the time frame for operation. With recent developments of wireless, battery-free, and fully implantable peripheral nerve interfaces, a new class of devices can offer capabilities that match or exceed those of their wired or battery-powered precursors. This paper describes methods to (i) surgically implant and (ii) wirelessly power and control this system in adult rats. The sciatic and phrenic nerve models were selected as examples to highlight the versatility of this approach. The paper shows how the peripheral nerve interface can evoke compound muscle action potentials (CMAPs), deliver a therapeutic electrical stimulation protocol, and incorporate a conduit for the repair of peripheral nerve injury. Such devices offer expanded treatment options for single-dose or repeated dose therapeutic stimulation and can be adapted to a variety of nerve locations.

This is a protocol for the surgical implantation and operation of a wirelessly powered interface for peripheral nerves. We demonstrate the utility of this approach with examples from nerve stimulators placed on either the rat sciatic or phrenic nerve.

Peripheral nerve interfaces are frequently used in experimental neuroscience and regenerative medicine for a wide variety of applications. Such interfaces ...

Combined Peripheral Nerve Stimulation and Controllable Pulse Parameter TMS

Combined Peripheral Nerve Stimulation and Controllable Pulse Parameter Transcranial Magnetic Stimulation to Probe Sensorimotor Control and Learning

Skilled motor ability depends on efficiently integrating sensory afference into the appropriate motor commands. Afferent inhibition provides a valuable tool to probe the procedural and declarative influence over sensorimotor integration during skilled motor actions. This manuscript describes the methodology and contributions of short-latency afferent inhibition (SAI) for understanding sensorimotor integration. SAI quantifies the effect of a convergent afferent volley on the corticospinal motor output evoked by transcranial magnetic stimulation (TMS). The afferent volley is triggered by the electrical stimulation of a peripheral nerve. The TMS stimulus is delivered to a location over the primary motor cortex that elicits a reliable motor-evoked response in a muscle served by that afferent nerve. The extent of inhibition in the motor-evoked response reflects the magnitude of the afferent volley converging on the motor cortex and involves central GABAergic and cholinergic contributions. The cholinergic involvement in SAI makes SAI a possible marker of declarative-procedural interactions in sensorimotor performance and learning. More recently, studies have begun manipulating the TMS current direction in SAI to tease apart the functional significance of distinct sensorimotor circuits in the primary motor cortex for skilled motor actions. The ability to control additional pulse parameters (e.g., the pulse width) with state-of-the-art controllable pulse parameter TMS (cTMS) has enhanced the selectivity of the sensorimotor circuits probed by the TMS stimulus and provided an opportunity to create more refined models of sensorimotor control and learning. Therefore, the current manuscript focuses on SAI assessment using cTMS. However, the principles outlined here also apply to SAI assessed using conventional fixed pulse width TMS stimulators and other forms of afferent inhibition, such as long-latency afferent inhibition (LAI).

Author Spotlight: Combined Peripheral Nerve Stimulation and Controllable Pulse Parameter Transcranial Magnetic Stimulation to Probe Sensorimotor Control and Learning  

Short-latency afferent inhibition (SAI) is a transcranial magnetic stimulation protocol to probe sensorimotor integration. This article describes how SAI can be used to study the convergent sensorimotor loops in the motor cortex during sensorimotor behavior.

Skilled motor ability depends on efficiently integrating sensory afference into the appropriate motor commands. Afferent inhibition provides a valuable ...