We thank Mr. T. Nishida (Technician, Dept of Sales, Division of Device Performance Materials, Nitta Co., Ltd, Osaka, Japan.) for technical support.

The series of studies in the present paper were approved by Gunma University Ethical Review Board for Medical Research Involving Human Subjects.
NOTE: Inclusion criteria for participants were the ability to understand the use of minimal force and the ability to perform the task with the thumb and index finger. Exclusion criteria were selected based on the purpose of the experiments.
1. Equipment preparation
<ol>
	<li>Connect two sensor connector cables to the USB ports of a computer. Pull up the lever attached to the sensor connector and insert the sensor&#8217;s tab into the insertion slot. Return the attached lever to its original position.</li>
	<li>Open the sensor software on a computer. Make sure that real-time pressure distribution maps appear automatically on the monitor when the sensor sheets are correctly connected.</li>
	<li>Pressure adjustment
	<ol>
		<li>Insert the sensing area of the sensor sheet one by one into a compressor rig.</li>
		<li>Turn on the air valve of the compressor&#8217;s controller and start to apply pressure. Operate the regulator and adjust to the appropriate load value (i.e., 172 kPa) to check the indicator on the controller. Make sure that the whole area of the sensor sheet is equally pressurized on the monitor.</li>
	</ol>
	</li>
	<li>While applying pressure to the sensor sheets, perform equilibration and calibration. 
	NOTE: Equilibration is an operation to adjust the reactivity of the sensor cells equally. Calibration is an operation to convert the pressure on the sensor sheet (raw sum) into a unit of weight (grams or Newtons) and display it. Both must be done for the sensor sheet before starting data collection for each participant.
	<ol>
		<li>Select Tools | Equilibration on the software main window. Click Equilibrate-1 | Start in the equilibration dialog box. Check the equilibration result in the dialog box and confirm the window of equilibration changes color to gray.</li>
		<li>Save the equilibration settings by clicking Save Eq. File in the equilibration dialog box. Enter the equilibration file name and click Save in the Save As dialog box.</li>
		<li>Next, perform calibration by selecting Tools | Calibration. Click the Add and enter the load value (134.33 N) in the Applied Force box.</li>
		<li>Click the Start button in the dialog box. Check the calibration result in the calibration dialog box and confirm that the calibration was done correctly; the value of Newton is shown as 134.33 and the value of loaded Cells matches with that of the sensor sheets being used if the calibration was done correctly.</li>
		<li>After that, save the calibration setting by clicking Save Cal. File. Enter the calibration file name and click Save in the Save As dialog box. After the equilibration and calibration, turn off the air valve on the controller and extract the sensor sheet from the compressor.</li>
	</ol>
	</li>
</ol>
2. Measurement
<ol>
	<li>Preparation
	<ol>
		<li>Connect each device and start up the software according to steps 1.1. and 1.2. Make sure that two real-time pressure distribution maps for each sensor sheet are displayed when the sensor sheets are connected via the cable at the same time. 
		NOTE: In this experiment, two sensor sheets are needed to measure the thumb and index finger, respectively. It is necessary to perform equilibration and calibration for each of them according to the procedures described in section 1.4.</li>
		<li>Recall the equilibration and calibration files created in steps 1.4.2. and 1.4.5. With the real-time pressure distribution map active, select Tools | Load Equilibration File. Select the equilibration file and click Open. Then, select Tools | Load Calibration File. Select the calibration file and click Open. Make sure that the real-time pressure distribution map is displayed in Newtons after loading calibration file. Perform the above for each of the two maps.</li>
		<li>Attach the pressure-sensitive parts of the two sensor sheets to both sides of the iron cube using double-sided tape. To prevent the sensor sheets from being damaged, cut 3&#8722;5 mm lengths of tape and place them on the four corners on the outside of the iron cube. Make sure that the surface of the sensor sheet is on the outside.</li>
		<li>Place the iron cube on top of a setting stand on a table before the measurement.</li>
		<li>After arranging the measurement environment, fix the recording settings for the movie frames, period, and frequency. Select the Options | Acquisition Parameter command. In the data acquisition parameter dialog box, enter 36000 in the movie frames, 0.01 in the Period, and 100 in the frequency. Click OK and close the dialog box.</li>
	</ol>
	</li>
	<li>Starting the measurement 
	NOTE: Figure 1 demonstrates a grip and lift task.
	<ol>
		<li>Have the participant sit in front of a table and adjust the table height (participant&#8217;s shoulder joint flexion 0&#176; and elbow joint flexion 90&#176; position). Set the iron cube and setting stand 30 cm from the participant in the midsagittal plane on the table. Wipe the participant&#8217;s finger pulps with an alcohol swab or towelette.</li>
		<li>Give the participant verbal instructions as follows: &#8220;Use minimal force with your thumb and index finger to grasp both sides of the iron cube to which the sensor sheets are attached. After that, lift it approximately 5 cm above the setting stand, hold it for 5&#8722;7 s, and then place it back on the setting stand.&#8221;</li>
		<li>If the participant is ready, give them a cue to start the task and start a recording by clicking Record on the toolbar. Click Center Of Force Trajectory to monitor the COP while recording. When the task is over, click Stop on the toolbar. After the recording, save the movie data by selecting File | Save Movie as. Enter the movie file name and click Save in the dialog box. 
		NOTE: The weight of the iron cube, number of lifts, and the interval between tasks should be considered according to the purpose of the experiment and task difficulty.</li>
	</ol>
	</li>
	<li>Change the measurement conditions according to the purpose of the experiment. For example, to investigate the effect of dual task interference in a grip and lift task, adjust the measurement conditions as follows depending on the type of interference.
	<ol>
		<li>For postural interference, have the participant stand in front of a table and adjust the table height. Give the participant verbal instructions as follows: &#8220;Stand on one leg, and use minimal force with your thumb and index finger to lift the iron cube approximately 5 cm above the setting stand. Hold it for 5&#8722;7 s and then place it back on the setting stand.&#8221;</li>
		<li>For visual interference, have the participant sit in front of a table and adjust the table height. Give the participant verbal instructions as follows: &#8220;Close your eyes. Use minimal force with your thumb and index finger with to lift the iron cube approximately 5 cm above the setting stand. Hold it for 5&#8722;7 s and place it back on the setting stand.&#8221; Allow participants to touch the sensors without exceeding 0.5 N before closing their eyes.</li>
		<li>For cognitive interference, have the participant sit in front of a table and adjust the table height. Give the participant verbal instructions as follows: &#8220;As a calculation task, continuously subtract 7 from 100 as accurately as possible. While performing the calculation, use minimal force with your thumb and index finger to lift the iron cube approximately 5 cm above the setting stand. Hold it for 5&#8722;7 s and place it back on the setting stand.&#8221;</li>
		<li>For contralateral hand movement interference (Figure 2), have the participant sit in front of a table and adjust the table height. Place the peg board 30 cm from the participant in the midsagittal plane next to the iron cube and consider the size and number of pegs to adjust the task difficulty. Give the participant verbal instructions as follows: &#8220;Manipulate the iron cube with minimal force using your thumb and index finger. Lift and hold the iron cube approximately 5 cm above the setting stand with one hand, and invert the peg using the other hand. Repeat using the opposite hand.&#8221;</li>
	</ol>
	</li>
</ol>
3. Data analysis
<ol>
	<li>Analysis of grip force
	<ol>
		<li>Start the software on the computer. Click File | Open Movie, select the movie file for analysis and Open.</li>
		<li>As the recorded pressure distribution map appears, click Multiple Window View on the map and refer the graph 1 window. Find the point in time which the load (grip force) starts to be applied in each lift, and note the time with reference to this graph.</li>
		<li>After that, save the grip force data in ASCII format. Select File | Save ASCII after making the graph 1 window activated. In the object-graph 1 dialog box, select Panes with the file name and click Save ASCII. In the dialog box, select Save Force, Pressure, and Area values. Specify Force in the Y-axis box, Time in the X-axis box, and Absolute in the Y-mode. Click OK in the property dialog box. Enter the ASCII file name and click Save in the dialog box.</li>
		<li>If information on the contact areas between finger pulps and sensor sheets is needed, specify Contact Area in the Y-axis box and click OK. Enter the ASCII file name and click Save in the dialog box.</li>
		<li>Next, open the movie file. Confirm that the file is opened in spreadsheet format and Frames, Time, Absolute time, Raw Sum and Force are noted. With reference to the time noted in step 3.1.2., find a cell which the load starts to be applied; the load values starts to increase and exceed 0.5N in the force row.</li>
		<li>Calculate the total grip force used in a range, which is the sum of the values from the cell was applied in the force line.</li>
	</ol>
	</li>
	<li>Analysis of center of pressure
	<ol>
		<li>Start the software. Click File | Open Movie, select the movie file for analysis and click Open.</li>
		<li>With the pressure distribution map active, click Play Forward to play the movie. Make sure that the COP trajectory appears on the pressure distribution map. Find the frame which the COP starts to appear in each lift with Next Frame or Previous Frame, which are the commands to move forward or backward the frames. Then, note that frame number.</li>
		<li>After that, save the COP data in ASCII format. Select File | Save ASCII with the distribution map active. Specify Center of Force in the data type dialog box and Whole movie in the movie range dialog box. Click OK in the property dialog box. Enter the ASCII file name and click Save in the dialog box.</li>
		<li>Next, open the movie file. Confirm that the file opens in spreadsheet format and COMMENTS Frame, Time, Absolute time, Row, Col and Raw Sum are noted. With reference to the frame noted in steps 3.2.2., find a cell (1) which the COP starts to appear.</li>
		<li>Calculate the COP trajectory length between frames. Select a cell (2) after the row including the frame which the COP starts to appear. Insert the following calculation formula: (=SQRT((Row cell (2) -Row cell (1))^2+(Col cell (2) -Col cell (1))^2). The sum of the COP trajectory length between frames in a range is the total COP trajectory within that range. 
		NOTE:&#160;In the graph 1 window, the vertical line shows the load value (N), and the horizontal line shows the time (s). This load value corresponds to the grip force. Data saved in ASCII format can be used in applications such as spreadsheets and text editors. In this experiment, the participants were instructed to hold the cube for 5&#8722;7 s in the task, so the grip force and COP trajectory were calculated and recorded for 4 s from their first appearance. In the spread sheet of the COP data, the position of the COP on X- and Y-axis coordinates is shown as a value.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Johansson, R. S., Flanagan, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coding+and+use+of+tactile+signals+from+the+fingertips+in+object+manipulation+tasks.">Coding and use of tactile signals from the fingertips in object manipulation tasks.</a> Nature Reviews Neuroscience. 10 (5), 345-359 (2009).</li><li>Cole, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Grasp+force+control+in+older+adults.">Grasp force control in older adults.</a> Journal of Motor Behavior. 23 (4), 251-258 (1991).</li><li>Lang, C. E., Schieber, M. H., Nowak, D. A., Hermsd&#246;rfer, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stroke.">Stroke.</a> Sensorimotor control of grasping. , 296-310 (2009).</li><li>Johansson, R. S., Westling, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Roles+of+glabrous+skin+receptors+and+sensorimotor+memory+in+automatic+control+of+precision+grip+when+lifting+rougher+or+more+slippery+objects.">Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objects.</a> Experimental Brain Research. 56 (3), 550-564 (1984).</li><li>Parikh, P. J., Cole, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Handling+objects+in+old+age:+forces+and+moments+acting+on+the+object.">Handling objects in old age: forces and moments acting on the object.</a> Journal of Applied Physiology. 112 (7), 1095-1104 (2012).</li><li>Augurelle, A. S., Smith, A. M., Lejeune, T., Thonnard, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Importance+of+cutaneous+feedback+in+maintaining+a+secure+grip+during+manipulation+of+hand-held+objects.">Importance of cutaneous feedback in maintaining a secure grip during manipulation of hand-held objects.</a> Journal of Neurophysiology. 89 (2), 665-671 (2003).</li><li>Monz&#233;e, J., Lamarre, Y., Smith, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effects+of+digital+anesthesia+on+force+control+using+a+precision+grip.">The effects of digital anesthesia on force control using a precision grip.</a> Journal of Neurophysiology. 89 (2), 672-683 (2003).</li><li>Fortier-Poisson, P., Langlais, J. S., Smith, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Correlation+of+fingertip+shear+force+direction+with+somatosensory+cortical+activity+in+monkey.">Correlation of fingertip shear force direction with somatosensory cortical activity in monkey.</a> Journal of Neurophysiology. 115 (1), 100-111 (2016).</li><li>Kurihara, J., Lee, B., Hara, D., Noguchi, N., Yamazaki, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Increased+center+of+pressure+trajectory+of+the+finger+during+precision+grip+task+in+stroke+patients.">Increased center of pressure trajectory of the finger during precision grip task in stroke patients.</a> Experimental Brain Research. 237 (2), 327-333 (2018).</li><li>Noguchi, N., 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=Grip+force+control+during+object+manipulation+in+cervical+myelopathy.">Grip force control during object manipulation in cervical myelopathy.</a> Spinal Cord. , (2020).</li><li>Lee, B., Miyanjo, R., Tozato, F., Shiihara, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dual-task+interference+in+a+grip+and+lift+task.">Dual-task interference in a grip and lift task.</a> The Kitakanto Medical Journal. 64 (4), 309-312 (2014).</li></ol>

The authors declare that they have no competing financial interests.

This experimental procedure provides evidence that a flexible pressure sensor sheet could be useful for evaluating spatial stability during precision grip. Altered grip force direction represents grasping spatial instability such as a finger slip. However, existing load cell-type force direction instruments have a limitation in terms of ensuring a natural reach-to-grip movement. To resolve this technical problem, the COP trajectory of the area between the finger pulps and contact surface based on a biomechanical relation...

Force control is the fundamental basis of precision grip. Compared with power grip, precision grip evaluates the minimal force output reflecting the ability to manipulate an object. Multiple sensorimotor systems contribute to precision grip. For example, during a grip and lift task, visual information enables the perception of the object&#8217;s size and shape. After the fingertips touch the object, tactile signals are delivered to the somatosensory cortex to adjust the precision grip force. Grip force (GF) is generated when the fingertips make contact with the object, and it increases during the lifting phase1. When an object approaches the goal height in the air, healthy young adults produce the minimal GF to optimize cutaneous input from the finger pulps and conserve energy. On the other hand, older adults use a large grip force to avoid letting the object slip from their grip2. In stroke patients, onset of grip force is delayed and the ability to adjust the safety margin is impaired due to sensory and motor deficits. Exaggerated grip force is considered to be a strategic response to compensate for sensory and motor deficits3.
The standard protocol to measure GF control in precision grip was suggested by Johansson and Westling in the 1980s4. They developed a device to monitor both load and grip forces simultaneously. Since then, GF amplitude and its temporal regulation have been used as typical kinetic parameters in numerous studies on precision grip. Another kinetic parameter is the force direction5. The force direction results from a combination of grip and lift forces. In order to maintain stable precision grip, properly directed grip and lift forces must be generated between the thumb and index finger, and the deviated force direction can cause spatial instability. Although various load cell-type force direction instruments are used in grasping studies, these instruments have a limitation in terms of monitoring the grip force control in manipulating objects of different sizes and shapes used in daily living. Thus, a flexible and attachable sensor is essential to investigate the relationships between grip force control and daily functions.
The purpose of this protocol is to indirectly evaluate the finger force direction during manipulation of an object based on the biomechanical relationship in which deviated force direction causes Center of Pressure (COP) replacement. The COP is the center of all the forces, and represents how the forces are balanced on the sensor sheet. The use of COP to evaluate grip force control was first suggested by Augurelle et al.6. They monitored COP displacement to investigate the role of cutaneous feedback and found that deviated COP occurred after digital anesthesia. However, COP displacement was monitored only vertically in their study; therefore, the COP displacement in a three-dimensional space has not been adequately evaluated. To solve this limitation a thin, flexible, and high spatial resolution pressure sensor sheet was used to measure COP. Relatively high spatial resolution sensors (~60&#8211;100 points per cm2) to measure grip force control have been used7,8, but recent advances in spatial resolution (248 points per cm2) allow measurement of the COP trajectory as a parameter to quantify spatial stability. This paper describes the experimental procedure and discusses how finger COP contributes to the understanding of the physiology and pathophysiology of grasping.

<table>
	<tbody>
		<tr>
			<td>Alcohol swab</td>
			<td></td>
			<td></td>
			<td>Wipe participant&#8217;s finger pulps</td>
		</tr>
		<tr>
			<td>Compressor</td>
			<td>Nitta Corporation</td>
			<td></td>
			<td>Apply pressure to the sensor seats</td>
		</tr>
		<tr>
			<td>Computer</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Controller of compressor</td>
			<td>Nitta Corporation</td>
			<td></td>
			<td>Use to manupirate the compressor</td>
		</tr>
		<tr>
			<td>Double-sides tapes</td>
			<td></td>
			<td></td>
			<td>Use to attach the sensorseats to the iron cube</td>
		</tr>
		<tr>
			<td>Iron cube</td>
			<td></td>
			<td></td>
			<td>150-250g, 30&#215;30&#215;30 mm</td>
		</tr>
		<tr>
			<td>Sensor connector</td>
			<td></td>
			<td></td>
			<td>Connect the sensorseats to computer.</td>
		</tr>
		<tr>
			<td>Sensor sheet</td>
			<td></td>
			<td></td>
			<td>Pressure Mapping Sensor 5027, Tekscan, South Boston, MA, 50 USA</td>
		</tr>
		<tr>
			<td>Setting stand</td>
			<td></td>
			<td></td>
			<td>Set the iron cube on it during the measurement</td>
		</tr>
		<tr>
			<td>Software; I-SCAN 5027, Ver. 7.51</td>
			<td>Nitta Corporation</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Table</td>
			<td></td>
			<td></td>
			<td>Use for the measurement</td>
		</tr>
	</tbody>
</table>

measurement of spatial stability in precision grip

The purpose of the protocol is to indirectly evaluate the direction of the finger force during manipulation of a handheld object based on the biomechanical relationships in which deviated force direction causes center of pressure (COP) replacement. To evaluate this, a thin, flexible, and high spatial resolution pressure sensor sheet is used. The system allows measurement of the COP trajectory in addition to the force amplitude and its temporal regulation. A series of experiments found that increased trajectory length reflected a sensorimotor deficit in stroke patients, and that decreased COP trajectory reflects a compensatory strategy to avoid an object slipping from the hand grip in the elderly. Moreover, the COP trajectory could also be decreased by dual task interference. This article describes the experimental procedure and discusses how finger COP contributes to an understanding of the physiology and pathophysiology of grasping.

Several studies have introduced experimental protocols and two kinetic parameters (the COP trajectory and the GF) to measure finger force during manipulation of an object. In previous studies, it was found that the COP trajectory increased in stroke patients9. In cervical myelopathy patients, the GF correlated with the cutaneous pressure threshold and upper extremity function10. In healthy young subjects, the GF increased with cognitive interference11</sup...

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Measurement of Spatial Stability in Precision Grip

The goal of this protocol is to measure the center of pressure (COP) replacement using a high spatial resolution sensor sheet to reflect the spatial stability in a precision grip. The use of this protocol could contribute to greater understanding of the physiology and pathophysiology of grasping.

The purpose of the protocol is to indirectly evaluate the direction of the finger force during manipulation of a handheld object based on the ...

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3.1K Views.  Geriatrics Research Institute and Hospital. The goal of this protocol is to measure the center of pressure (COP) replacement using a high spatial resolution sensor sheet to reflect the spatial stability in a precision grip. The use of this protocol could contribute to greater understanding of the physiology and pathophysiology of grasping.

Video: Measurement of Spatial Stability in Precision Grip

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with schizophrenia who are at familial high risk (FHR) may show similar cognitive and emotional changes. However, the neurological changes underlying the emergence of these symptoms remain unclear. This study sought to identify differences in frontal, striatal, and limbic regions in children and adolescents with FHR using functional magnetic resonance imaging. Groups of 21 children and adolescents at FHR and 21 healthy controls completed an emotional oddball task that relied on selective attention and the suppression of task-irrelevant emotional information. The standard oddball task was modified to include aversive and neutral distractors in order to examine potential group differences in both emotional and executive processing. This task was designed specifically to allow for children and adolescents to complete by keeping the difficulty and emotional image content age-appropriate. Furthermore, we demonstrate a technique for suitable fMRI registration for children and adolescent participants. This paradigm may also be applied in future studies to measure changes in neural activity in other populations with hypothesized developmental changes in executive and emotional processing.

This paper describes how to use the emotional oddball task and fMRI to measure brain activation in children and adolescents at familial high risk for schizophrenia (FHR).&#160;FMRI was used to measure differences in fronto-striato-limbic regions during an emotional oddball task. Children with FHR exhibited abnormal functional activation during adolescence.

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with ...

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Attention control is the ability to selectively attend to some sensory signals while ignoring others. This ability is thought to involve two processes: enhancement of sensory signals that are to be attended and the attenuation of sensory signals that are to be ignored. The overall strength of attentional modulation is often measured by comparing the amplitude of a sensory neural response to an external input when attended versus when ignored. This method is robust for detecting attentional modulation, but precludes the ability to assess the separate dynamics of attending and ignoring processes. Here, we describe methodology to measure independently the neurophysiological signals of attending and ignoring using the intermodal attention task (IMAT). This task, when combined with electroencephalography, isolates neurophysiological sensory responses in auditory and visual modalities, when either attending or ignoring, with respect to a passive control. As a result, independent dynamics of attending and of a ignoring can be assessed in either modality. Our results using this task indicate that the timing and cortical sources of attending and ignoring effects differ, as do their contributions to the attention modulation effect, pointing to unique neural trajectories and demonstrating sample utility of measuring them separately.

Attention control comprises enhancement of target signals and attenuation of distractor signals. We describe an approach to measure separately but concurrently, the neurophysiology of attending and ignoring in sustained intermodal attention, utilizing a passive control condition during which neither process is continuously engaged.

Attention control is the ability to selectively attend to some sensory signals while ignoring others. This ability is thought to involve two processes: ...

Measurement of Vibration Detection Threshold and Tactile Spatial Acuity in Human Subjects

Tests that allow the precise determination of psychophysical thresholds for vibration and grating orientation provide valuable information about mechanosensory function that are relevant for clinical diagnosis as well as for basic research. Here, we describe two psychophysical tests designed to determine the vibration detection threshold (automated system) and tactile spatial acuity (handheld device). Both procedures implement a two-interval forced-choice and a transformed-rule up and down experimental paradigm. These tests have been used to obtain mechanosensory profiles for individuals from distinct human cohorts such as twins or people with sensorineural deafness.

Here, we present protocols to determine vibration detection thresholds and tactile acuity using psychophysical methods in man.

Tests that allow the precise determination of psychophysical thresholds for vibration and grating orientation provide valuable information about ...

Acquisition of a High-precision Skilled Forelimb Reaching Task in Rats

Movements are the main measurable output of central nervous system function. Developing behavioral paradigms that allow detailed analysis of motor learning and execution is of critical importance in order to understand the principles and processes that underlie motor function. Here we present a paradigm to study movement acquisition within a daily session of training (within-session) representing the fast learning component and primary acquisition as well as skilled motor learning over several training sessions (between-session) representing the slow learning component and consolidation of the learned task. This behavioral paradigm increases the degree of difficulty and complexity of the motor skill task due to two features: First, the animal realigns its body prior to each pellet retrieval forcing renewed orientation and preventing movement execution from the same angle. Second, pellets are grasped from a vertical post that matches the diameter of the pellet and is placed in front of the cage. This requires a precise grasp for successful pellet retrieval and thus prevents simple pulling of the pellet towards the animal. In combination with novel genetics, imaging and electrophysiological technologies, this behavioral method will aid to understand the morphological, anatomical and molecular underpinnings of motor learning and memory.

A paradigm is presented to analyze the acquisition of a high-precision skilled forelimb reaching task in rats.

Movements are the main measurable output of central nervous system function. Developing behavioral paradigms that allow detailed analysis of motor ...

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Spatial intelligence is often linked to success in engineering education and engineering professions. The use of electroencephalography enables comparative calculation of individuals&#39; neural efficiency as they perform successive tasks requiring spatial ability to derive solutions. Neural efficiency here is defined as having less beta activation, and therefore expending fewer neural resources, to perform a task in comparison to other groups or other tasks. For inter-task comparisons of tasks with similar durations, these measurements may enable a comparison of task type difficulty. For intra-participant and inter-participant comparisons, these measurements provide potential insight into the participant&#39;s level of spatial ability and different engineering problem solving tasks. Performance on the selected tasks can be analyzed and correlated with beta activities. This work presents a detailed research protocol studying the neural efficiency of students engaged in the solving of typical spatial ability and Statics problems. Students completed problems specific to the Mental Cutting Test (MCT), Purdue Spatial Visualization test of Rotations (PSVT:R), and Statics. While engaged in solving these problems, participants&#39; brain waves were measured with EEG allowing data to be collected regarding alpha and beta brain wave activation and use. The work looks to correlate functional performance on pure spatial tasks with spatially intensive engineering tasks to identify the pathways to successful performance in engineering and the resulting improvements in engineering education that may follow.

This manuscript describes an approach to measure neural activity of humans while solving spatially focused engineering problems. The electroencephalogram methodology helps interpret beta brain wave measurements in terms of neural efficiency, with the aim of ultimately enabling comparisons of task performance both between problem types and between participants.

Spatial intelligence is often linked to success in engineering education and engineering professions. The use of electroencephalography enables ...

Assessing Spatial Memory Impairment in a Mouse Model of Traumatic Brain Injury Using a Radial Water Tread Maze

Despite the recent increase in use of mouse models in scientific research, researchers continue to use cognitive tasks that were originally designed and validated for rat use. The Radial Water Tread (RWT) maze test of spatial memory (designed specifically for mice and requiring no swimming) has been shown previously to successfully distinguish between controlled cortical impact-induced TBI mice and sham controls. Here, a detailed protocol for this task is presented. The RWT maze capitalizes on the natural tendency of mice to avoid open areas in favor of hugging the sides of an apparatus (thigmotaxis). The walls of the maze are lined with nine escape holes placed above the floor of the apparatus, and mice are trained to use visual cues to locate the escape hole that leads out of the maze. The maze is filled with an inch of cold water, sufficient to motivate escape but not deep enough to require that the mouse swim. The acquisition period takes only four training days, with a test of memory retention on day five and a long-term memory test on day 12. The results reported here suggest that the RWT maze is a feasible alternative to rat-validated, swimming-based cognitive tests in the assessment of spatial memory deficits in mouse models of TBI.

Here we present a protocol for a mouse-specific test of cognition that does not require swimming. This test can be used to successfully distinguish controlled cortical impact-induced traumatic brain injury mice from sham controls.

Despite the recent increase in use of mouse models in scientific research, researchers continue to use cognitive tasks that were originally designed and ...

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

The memory game paradigm is a behavioral procedure to explore the relationship between language, spatial memory, and object knowledge. Using two different versions of the paradigm, spatial language use and memory for object location are tested under different, experimentally manipulated conditions. This allows us to tease apart proposed models explaining the influence of object knowledge on spatial language (e.g., spatial demonstratives), and spatial memory, as well as understanding the parameters that affect demonstrative choice and spatial memory more broadly. Key to the development of the method was the need to collect data on language use (e.g., spatial demonstratives: &#34;this/that&#34;) and spatial memory data under strictly controlled conditions, while retaining a degree of ecological validity. The language version (section 3.1) of the memory game tests how conditions affect language use. Participants refer verbally to objects placed at different locations (e.g., using spatial demonstratives: &#34;this/that red circle&#34;). Different parameters can be experimentally manipulated: the distance from the participant, the position of a conspecific, and for example whether the participant owns, knows, or sees the object while referring to it. The same parameters can be manipulated in the memory version of the memory game (section 3.2). This version tests the effects of the different conditions on object-location memory. Following object placement, participants get 10 seconds to memorize the object&#39;s location. After the object and location cues are removed, participants verbally direct the experimenter to move a stick to indicate where the object was. The difference between the memorized and the actual location shows the direction and strength of the memory error, allowing comparisons between the influences of the respective parameters.

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

We present a protocol to explore the relationship between spatial language production, spatial memory, and object knowledge. The procedure allows experimental manipulation of, and control over, conditions of object knowledge, language at instruction, and physical location, thus teasing apart cognitive and linguistic models describing interactions between these variables.

The memory game paradigm is a behavioral procedure to explore the relationship between language, spatial memory, and object knowledge. Using two different ...

A Behavioral Assay for Investigating the Role of Spatial Memory During Instinctive Defense in Mice

Evolution has selected a repertoire of defensive behaviors that are essential for survival across all animal species. These behaviors are often stereotyped actions elicited in response to innately aversive sensory stimuli, but their success requires enough flexibility for adapting to different spatial environments, which can change rapidly. Here, we describe a behavioral assay to evaluate the influence of learned spatial knowledge on defensive behaviors in mice. We have adapted the widely used Barnes maze spatial memory assay to investigate how mice navigate to a shelter during escape responses to innately aversive sensory stimuli in a novel environment, and how they adapt to acute changes in the environment. This new assay is an ethological paradigm that does not require training and exploits the natural exploration patterns and navigation strategies in mice. We propose that the set of protocols described here are a powerful means of studying goal-directed behaviors and stimulus-triggered navigation, which should be of interest to both the fields of instinctive behaviors and spatial memory.

This protocol describes a behavioral assay, based on the Barnes maze test, to study how instinctive defensive actions are modified by the knowledge of spatial environment.

Evolution has selected a repertoire of defensive behaviors that are essential for survival across all animal species. These behaviors are often ...

Analyzing Spatial Learning and Prosocial Behavior in Mice Using the Barnes Maze and Damsel-in-Distress Paradigms

The Barnes maze is a reliable measure of spatial learning and memory that does not require food restriction or exposure to extremely stressful stimuli. The Barnes maze can also assess other mouse behaviors, such as general motivation to escape from the maze platform and exploratory behavior. The Barnes maze can measure whether a genetic mutation or environmental variable can impact the acquisition and retention of spatial memories, as well as provide information about the search strategy employed by the mice. Here we use the Barnes maze to detect a memory deficit in adult mice following a single developmental ethanol exposure event. The newly described Damsel-in-Distress paradigm exposes a male mouse to a female mouse trapped in a chamber in the open center field of the arena. It provides an opportunity for the mouse to socially respond to the trapped female and exhibit prosocial behavior. The Damsel-in-Distress paradigm can also be used to examine mouse behavior in a novel arena and measure locomotor activity. Both the Barnes Maze and the Damsel-in-Distress protocols require minimal financial investment and most aspects of the tests can be constructed from common lab supplies. These flexible and accessible tools can also be used to detect behavioral changes over the course of development.

This protocol measures spatial learning and memory using the Barnes maze. A novel Damsel-in-Distress paradigm is used to assess locomotor activity and prosocial behavior in mice.

The Barnes maze is a reliable measure of spatial learning and memory that does not require food restriction or exposure to extremely stressful stimuli. ...

Impact of High-intensity Interval Exercise and Moderate-Intensity Continuous Exercise on the Cardiac Troponin T Level at an Early Stage of Training

An elevation in cardiac troponin T (cTnT), as a highly specific biomarker of cardiomyocyte damage, after moderate-intensity continuous exercise (MCE) has been described. The exercise-induced cTnT response distorts the diagnostic role of the cTnT assay. Although high-intensity interval exercise (HIE) is growing in popularity and concerns remain about its safety, available data related to cTnT release after HIE is limited, which hampers the use of HIE as a health intervention. Here, we present three representative HIE protocols [traditional HIE (repeated 4 min cycling at 90% V&#775;O2max interspersed with 3 min rest, 200 kJ/session); sprint interval exercise (SIE, repeated 1 min cycling at 120% V&#775;O2max interspersed with 1.5 min rest, 200 kJ/session); and repeated sprint exercise (RSE, 40 x 6 s all-out sprints interspersed with 9 s rest)] and one representative MCE protocol (continuous cycling exercise at an intensity of 60% V&#775;O2max, 200 kJ/session). Forty-seven sedentary, overweight young women were randomly assigned to one of four groups (HIE, SIE, RSE, and MCE). Six bouts of respective exercise were performed by every single group, with each being 48 h apart. Meanwhile, for four groups, the duration of the entire testing period was identical, being 10 days. Before and after the first and final exercise bouts, an assessment was conducted of cTnT. The current study provides a frame of reference giving a clear picture of how a specific exercise session affects the circulating cTnT concentration at the early stage of training. The information may assist with clinical interpretations of post-exercise cTnT elevation and guide the prescription of exercise, especially for HIE.

Here, we present protocols of high-intensity interval and moderate-intensity continuous exercise to observe the response of circulating cardiac troponin T (cTnT) concentration to acute exercise over 10 days. The information may assist with clinical interpretations of post-exercise cTnT elevation and guide the prescription of exercise.

An elevation in cardiac troponin T (cTnT), as a highly specific biomarker of cardiomyocyte damage, after moderate-intensity continuous exercise (MCE) has ...